Australia’s 
National 
Science 
Agency 


Sequestration 
Cost 
Reduction 
Workshops 
Report 


June 
2023 




Citation 


Fitch 
P, 
Battaglia 
M, 
Roxburgh 
S, 
Steven 
A, 
Feron 
P, 
Gillespie 
M, 
Birchall 
R, 
Lenton 
A, 
Seyyedi 
M, 
Fawell 
P, 
Jenkins 
C, 
Evans 
D 
(2023) 
Sequestration 
cost 
reduction 
workshops 
report, 
CSIRO, 
Canberra. 


Copyright 


© 
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Scientific 
and 
Industrial 
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2023. 
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Title 
Sequestration 
Cost 
Reduction 
Workshops 
Report 
Description 
A 
report 
on 
a 
series 
of 
workshops 
convened 
to 
assess 
the 
cost 
reduction 
potential 
of 
different 
technology 
innovations 
on 
six 
sequestration 
approaches. 
Created 
By 
Peter 
Fitch 
Date 
Created 
17 
March 
2023 
Version 
Number 
Released 
By 
Description 
Date 
Released 
Status 
1.0 
Peter 
Fitch 
Preliminary 
report 
March 
17 
2023 
Draft 
2.0 
Peter 
Fitch 
Interim 
Final 
draft 
May 
5 
2023 
Draft 
3.0 
Peter 
Fitch 
Final 
draft 
May 
29 
2023 
Draft 
4.0 
Peter 
Fitch 
Final 
Report 
June 
15 
2023 
Released 
4.1 
Peter 
Fitch 
Small 
edits 
to 
Mineral 
Carbonation 
chapter, 
and 
small 
corrections. 
June 
19 
2023 
Released 



Contents 


Acknowledgments 
......................................................................................................................................viii 
1 
Key 
messages 
.................................................................................................................................. 
9 


1.1 
Summary 
of 
cost 
reduction 
potential 
results 
................................................................. 
10 
1.2 
Planted 
vegetation.......................................................................................................... 
13 
1.3 
Blue 
carbon..................................................................................................................... 
15 
1.4 
Direct 
air 
capture............................................................................................................ 
16 
1.5 
Savanna 
fire 
management.............................................................................................. 
17 
1.6 
Carbon 
capture 
and 
storage 
........................................................................................... 
18 
1.7 
Biomass/biochar 
............................................................................................................. 
18 
1.8 
Mineral 
carbonation 
....................................................................................................... 
20 
1.9 
Using 
these 
estimates 
for 
integrated 
assessment 
modelling......................................... 
21 
1.10 
References 
...................................................................................................................... 
22 
2 
Introduction 
.................................................................................................................................. 
23 
3 
Workshop 
method 
........................................................................................................................ 
23 
3.1 
Method 
........................................................................................................................... 
23 
3.2 
Miro 
board...................................................................................................................... 
24 
3.3 
Determining 
the 
technical 
innovation 
areas 
.................................................................. 
24 
3.4 
Process............................................................................................................................ 
24 


3.5 
Outputs 
........................................................................................................................... 
25 
3.6 
Definitions....................................................................................................................... 
25 


3.7 
Out 
of 
scope.................................................................................................................... 
25 
3.8 
Participants 
..................................................................................................................... 
25 
3.9 
Schedule.......................................................................................................................... 
25 


3.10 
Participant 
Review 
.......................................................................................................... 
26 
3.11 
References 
...................................................................................................................... 
26 
4 
Scaling 
and 
maturity 
analysis 
........................................................................................................ 
27 
4.1 
Possible 
uptake 
trajectories 
........................................................................................... 
28 
4.2 
Relative 
sequestration 
benefit 
metric 
............................................................................ 
30 
4.3 
References 
...................................................................................................................... 
31 
Workshopoutputs32
Planted 
vegetation 
sequestration................................................................................................. 
32 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
i 



5.1 
Workshop 
results............................................................................................................ 
32 


5.2 
Analysis 
of 
implementation 
steps................................................................................... 
42 


5.3 
Ranking 
........................................................................................................................... 
44 


5.4 
Discussion 
....................................................................................................................... 
44 


5.5 
References 
...................................................................................................................... 
45 
6 
Blue 
carbon 
................................................................................................................................... 
46 


6.1 
Workshop 
results............................................................................................................ 
46 


6.2 
Analysis 
of 
implementation 
steps................................................................................... 
57 


6.3 
Ranking 
........................................................................................................................... 
58 


6.4 
Discussion 
....................................................................................................................... 
58 


6.5 
Blue 
carbon 
case 
study: 
the 
benefits 
of 
a 
national 
hydrological 
modelling 
capability 
for 
blue 
carbon 
tidal 
inundation 
modelling........................................................................................ 
59 


6.6 
References 
...................................................................................................................... 
62 
7 
Direct 
air 
capture 
.......................................................................................................................... 
63 


7.1 
Workshop 
results............................................................................................................ 
63 


7.2 
Analysis 
of 
implementation 
steps................................................................................... 
68 


7.3 
Discussion 
....................................................................................................................... 
69 


7.4 
References 
...................................................................................................................... 
69 
8 
Savanna 
fire 
management 
............................................................................................................ 
70 


8.1 
Background 
and 
methodology........................................................................................ 
70 


8.2 
Remotely 
sensed 
fire 
severity 
to 
remove 
the 
need 
for 
an 
early 
dry 
season/late 
dry 
season 
cut-off 
date 
....................................................................................................................... 
70 


8.3 
Improved 
provision 
of 
fire 
risk 
information 
to 
inform 
prescribed 
burn 
planning.......... 
71 


8.4 
Conclusion....................................................................................................................... 
72 


8.5 
References 
...................................................................................................................... 
72 
9 
Combined 
biomass/biochar 
.......................................................................................................... 
75 


9.1 
Workshop 
results............................................................................................................ 
75 


9.2 
Analysis 
of 
implementation 
steps................................................................................... 
83 


9.3 
Ranking 
........................................................................................................................... 
84 


9.4 
Discussion 
....................................................................................................................... 
84 


9.5 
References 
...................................................................................................................... 
85 
10 
Carbon 
capture 
and 
storage 
......................................................................................................... 
86 


10.1 
Workshop 
differences..................................................................................................... 
86 


10.2 
Workshop 
findings.......................................................................................................... 
87 


10.3 
References 
...................................................................................................................... 
88 
11 
Mineral 
carbonation...................................................................................................................... 
89 


ii 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



11.1 
Workshop 
results............................................................................................................ 
89 
11.2 
Discussion 
....................................................................................................................... 
98 
11.3 
References 
.................................................................................................................... 
100 
Appendix101
Workshop 
outputs 
........................................................................................................ 
101 
Miro 
Screens................................................................................................................. 
132 
Workshop 
participants 
................................................................................................. 
149 
Review 
Comments 
........................................................................................................ 
151 
Cash 
flow 
model 
for 
a 
biochar 
production 
plant.......................................................... 
152 


Shortened 
forms157 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
iii 



Figures 


Figure 
1-1: 
Visualisation 
of 
cost 
reduction, 
scaling 
factor 
and 
maturity. 
* 
Indicates 
the 
scaling 
factor.... 
12 


Figure 
1-2:Hypothetical 
cumulative 
sequestration 
for 
the 
uptake 
of 
technical 
innovation 
for 
scaling 
factors 
of 
2 
and 
3, 
for 
maturity 
timeframes 
of 
2030. 
................................................................................ 
12 
Figure 
1-3: 
Hypothetical 
cumulative 
sequestration 
for 
the 
uptake 
of 
technical 
innovation 
for 
maturity 


timeframes 
of 
2025, 
2030 
and 
2035, 
for 
a 
scaling 
factor 
of 
3. 
.................................................................. 
13 


Figure 
1-4: 
Comparison 
of 
cost 
reduction, 
year 
of 
maturity 
and 
scaling 
factor 
for 
planted 
vegetation 
technical 
innovation 
areas. 
* 
Indicates 
the 
scaling 
factor. 
........................................................................ 
14 
Figure 
1-5: 
Comparison 
of 
cost 
reduction, 
year 
of 
maturity 
and 
scaling 
factor 
for 
blue 
carbon 
technical 


innovation 
areas. 
* 
Indicates 
the 
scaling 
factor......................................................................................... 
16 


Figure 
1-6: 
Comparison 
of 
cost 
reduction, 
year 
of 
maturity 
and 
scaling 
factor 
for 
direct 
air 
capture 
technical 
innovation 
areas. 
* 
Indicates 
the 
scaling 
factor. 
........................................................................ 
17 
Figure 
1-7: 
Comparison 
of 
cost 
reduction, 
year 
of 
maturity 
and 
scaling 
factor 
for 
biomass/biochar 


technical 
innovation 
areas. 
* 
Indicates 
the 
scaling 
factor. 
........................................................................ 
19 


Figure 
1-8: 
Comparison 
of 
cost 
reduction, 
year 
of 
maturity 
and 
scaling 
factor 
for 
ex-situ 
mineral 
carbonation 
technical 
innovation 
areas. 
* 
Indicates 
the 
scaling 
factor..................................................... 
21 
Figure 
1-9: 
Comparison 
of 
cost 
reduction, 
year 
of 
maturity 
and 
scaling 
factor 
for 
in-situ 
mineral 


carbonation 
technical 
innovation 
areas. 
* 
Indicates 
the 
scaling 
factor..................................................... 
21 


Figure 
3-1: 
Delphi 
continuum 
for 
expert 
opinion 
elicitation. 
The 
circles 
labelled 
1–3 
represent 
the 
opinions 
of 
three 
participants. 
................................................................................................................... 
24 
Figure 
4-1: 
Example 
of 
an 
S-curve, 
representing 
adoption 
of 
a 
new 
technology/innovation. 
.................. 
27 
Figure 
4-2: 
Hypothetical 
increase 
of 
sequestration 
modelled 
by 
S-curve, 
based 
on 
uptake 
of 
technology 


innovation 
with 
a 
scaling 
factor 
of 
2, 
with 
maturity 
timeframes 
of 
2025, 
2030, 
and 
2035....................... 
29 


Figure 
4-3: 
Hypothetical 
increase 
of 
sequestration 
modelled 
by 
S-curve, 
based 
on 
uptake 
of 
technology 
innovation 
with 
a 
scaling 
factor 
of 
3, 
with 
maturity 
timeframes 
of 
2025, 
2030, 
and 
2035....................... 
29 
Figure 
4-4:Hypothetical 
cumulative 
sequestration 
for 
the 
uptake 
of 
technical 
innovation 
for 
scaling 


factors 
of 
2 
and 
3, 
for 
maturity 
timeframes 
of 
2030. 
................................................................................ 
29 


Figure 
4-5: 
Hypothetical 
cumulative 
sequestration 
for 
the 
uptake 
of 
technical 
innovation 
for 
maturity 
timeframes 
of 
2025, 
2030 
and 
2035, 
for 
a 
scaling 
factor 
of 
3. 
.................................................................. 
30 
Figure 
5-1: 
Plot 
of 
cost 
reduction 
percentages 
versus 
scaling 
factor 
for 
planted 
vegetation 
technical 


innovation 
areas......................................................................................................................................... 
35 
Figure 
5-2: 
Bar 
graph 
of 
cost 
reductions 
for 
planted 
vegetation 
technical 
innovation 
areas. 
.................. 
38 
Figure 
5-3: 
Comparison 
of 
technology 
cost 
reduction, 
year 
of 
maturity 
and 
scaling 
factor 
for 
planted 


vegetation 
technical 
innovation 
areas. 
* 
Indicates 
the 
scaling 
factor. 
...................................................... 
39 


Figure 
5-4: 
Sensitivity 
analysis 
of 
the 
cash 
flow 
model 
for 
planted 
vegetation 
carbon 
sequestration 
projects....................................................................................................................................................... 
40 
Figure 
5-5: 
Sensitivity 
analysis 
of 
sequestration 
costs 
for 
planted 
vegetation 
carbon 
sequestration 


projects....................................................................................................................................................... 
40 


iv 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Figure 
6-1: 
Plot 
of 
average 
cost 
reduction 
percentages 
versus 
scaling 
factor 
for 
blue 
carbon 
technical 
innovation 
areas......................................................................................................................................... 
49 


Figure 
6-2: 
Bar 
graph 
of 
cost 
reductions 
for 
blue 
carbon 
technical 
innovation 
areas............................... 
52 
Figure 
6-3: 
Comparison 
of 
technology 
cost 
reduction, 
year 
of 
maturity 
and 
scaling 
factor 
for 
blue 
carbon 
technical 
innovation 
areas. 
* 
Indicates 
the 
scaling 
factor. 
........................................................................ 
53 
Figure 
6-4: 
Sensitivity 
analysis 
of 
the 
cash 
flow 
model 
for 
blue 
carbon 
sequestration 
projects............... 
54 
Figure 
6-5: 
Sensitivity 
analysis 
of 
sequestration 
costs 
for 
blue 
carbon 
sequestration 
projects. 
............... 
54 
Figure 
6-6: 
Reintroduction 
of 
tidal 
flow 
site, 
Maroochy 
flood 
plain, 
Queensland. 
Photo 
credit 
Blue 
Heart. 


.................................................................................................................................................................... 
61 


Figure 
7-1: 
Plot 
of 
average 
cost 
reduction 
percentages 
versus 
scaling 
factor 
for 
direct 
air 
capture 
technical 
innovation 
areas. 
........................................................................................................................ 
65 
Figure 
7-2: 
Bar 
graph 
of 
cost 
reductions 
for 
direct 
air 
capture 
technical 
innovation 
areas. 
..................... 
66 
Figure 
7-3: 
Comparison 
of 
technology 
cost 
reduction, 
year 
of 
maturity 
and 
scaling 
factor 
for 
direct 
air 


capture 
technical 
innovation 
areas. 
........................................................................................................... 
67 
Figure 
7-4: 
Sensitivity 
of 
sequestration 
costs 
to 
relative 
changes 
in 
different 
cost 
drivers, 
adapted 
from 
global 
assessment 
of 
direct 
air 
capture 
costs 
based 
on 
sensitivity 
of 
1 
Mt 
CO2 
per 
year 
capacity 
Nth-of-a


kind 
hybrid 
solid 
sorbent 
system 
costs 
($ 
per 
t 
CO2 
net). 
Capex 
= 
capital 
expenditure. 
Adapted 
from 
IEAGHG 
(2021)............................................................................................................................................ 
67 
Figure 
9-1: 
Plot 
of 
average 
cost 
reduction 
percentages 
versus 
scaling 
factor 
for 
biomass/biochar 


technical 
innovation 
areas. 
........................................................................................................................ 
77 
Figure 
9-2: 
Bar 
graph 
of 
cost 
reductions 
for 
biomass/biochar 
technical 
innovation 
areas. 
...................... 
80 
Figure 
9-3: 
Comparison 
of 
technology 
cost 
reduction, 
year 
of 
maturity 
and 
scaling 
factor 
for 


biomass/biochar 
technical 
innovation 
areas.............................................................................................. 
81 
Figure 
9-4: 
Sensitivity 
analysis 
of 
the 
cash 
flow 
model 
for 
biomass/biochar 
sequestration 
projects. 
...... 
81 
Figure 
9-5: 
Sensitivity 
analysis 
of 
sequestration 
costs 
for 
biomass/biochar 
sequestration 
projects. 
....... 
82 
Figure 
11-1: 
Plot 
of 
average 
cost 
reduction 
percentages 
versus 
scaling 
factor 
for 
(A) 
ex-situ 
and 
(B) 
in-

situ 
mineral 
carbonation 
technical 
innovation 
areas. 
Both 
datasets 
have 
a 
positive 
association 
(R2 
> 
0). 


Ex-situ 
data 
are 
moderately 
correlated 
(R2 
= 
0.72); 
in-situ 
data 
are 
weakly 
correlated 
(R2 
= 
0.16)........... 
94 
Figure 
11-2: 
Bar 
graph 
of 
cost 
reductions 
for 
ex-situ 
mineral 
carbonation 
technology 
innovation 
areas. 
The 
cost 
reductions 
are 
from 
a 
baseline 
of 
$222 
per 
tonne. 
..................................................................... 
95 


Figure 
11-3: 
Bar 
graph 
of 
cost 
reductions 
for 
in-situ 
mineral 
carbonation 
technology 
innovation 
areas. 


The 
cost 
reductions 
are 
from 
a 
baseline 
of 
$37 
per 
tonne. 
....................................................................... 
95 
Figure 
11-4: 
Comparison 
of 
technology 
cost 
reduction, 
year 
of 
maturity 
and 
scaling 
factor 
for 
ex-situ 
mineral 
carbonation. 
.................................................................................................................................. 
97 


Figure 
11-5: 
Comparison 
of 
technology 
cost 
reduction, 
year 
of 
maturity 
and 
scaling 
factor 
for 
in-situ 
mineral 
carbonation. 
.................................................................................................................................. 
97 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
v 



Tables 


Table 
1.1: 
Summary 
of 
the 
cost 
reduction 
potential 
of 
technology 
innovation 
areas 
for 
each 
sequestration 
approach 
reviewed.............................................................................................................. 
10 
Table 
1.2: 
Cost 
reductions 
for 
planted 
vegetation 
technical 
innovation 
areas. 
........................................ 
13 
Table 
1.3: 
Ranking 
of 
technical 
innovation 
areas 
for 
planted 
vegetation 
carbon 
sequestration. 
............. 
14 
Table 
1.4: 
Cost 
reductions 
for 
blue 
carbon 
technical 
innovation 
areas..................................................... 
15 
Table 
1.5: 
Ranking 
of 
technical 
innovation 
areas 
for 
blue 
carbon 
sequestration...................................... 
16 
Table 
1.6: 
Cost 
reductions 
for 
direct 
air 
capture 
technical 
innovation 
areas. 
........................................... 
17 
Table 
1.7: 
Cost 
reductions 
for 
biomass/biochar 
technical 
innovation 
areas............................................. 
19 
Table 
1.8: 
Ranking 
of 
technical 
innovation 
areas 
for 
biomass/biochar 
carbon 
sequestration.................. 
19 
Table 
1.9: 
Cost 
reductions 
for 
mineral 
carbonation 
technical 
innovation 
areas. 
...................................... 
20 
Table 
3.1: 
Workshop 
schedule. 
.................................................................................................................. 
25 
Table 
5.1: 
Technical 
innovation 
opportunities 
for 
carbon 
sequestration 
through 
planted 
vegetation. 
... 
32 
Table 
5.2: 
Summary 
of 
outputs 
from 
the 
planted 
vegetation 
workshop................................................... 
34 
Table 
5.3: 
Cost 
reduction 
factors 
for 
planted 
vegetation 
technical 
innovation 
areas. 
All 
factors 
are 
percentage 
reductions 
(costs) 
or 
increases 
(revenues) 
relative 
to 
current 
costs. 
Blank 
cells 
indicate 
no 
change 
to 
cost 
drivers. 
............................................................................................................................... 
36 
Table 
5.4: 
Cost 
factors 
for 
planted 
vegetation 
projects............................................................................. 
36 
Table 
5.5: 
Cost 
reductions 
for 
planted 
vegetation 
technical 
innovation 
areas. 
........................................ 
37 
Table 
5.6: 
Relative 
sequestration 
benefit 
of 
each 
planted 
vegetation 
technical 
innovation 
area. 
........... 
41 
Table 
5.7: 
Ranking 
of 
technical 
innovation 
areas 
for 
planted 
vegetation 
carbon 
sequestration. 
............. 
44 
Table 
6.1: 
Technical 
innovation 
opportunities 
for 
carbon 
sequestration 
through 
blue 
carbon................ 
46 
Table 
6.2: 
Summary 
of 
outputs 
from 
the 
blue 
carbon 
workshop.............................................................. 
48 
Table 
6.3: 
Cost 
reduction 
factors 
for 
blue 
carbon 
technical 
innovation 
areas. 
All 
factors 
are 
percentage 
reductions 
(costs) 
or 
increases 
(revenues) 
relative 
to 
current 
costs. 
........................................................ 
50 
Table 
6.4: 
Cost 
factors 
for 
blue 
carbon 
projects. 
....................................................................................... 
50 
Table 
6.5: 
BlueCAM 
scenario 
modelling 
results......................................................................................... 
51 
Table 
6.6: 
Cost 
reductions 
for 
blue 
carbon 
technical 
innovation 
areas..................................................... 
52 
Table 
6.7: 
Relative 
sequestration 
benefit 
of 
each 
blue 
carbon 
technical 
innovation 
area........................ 
55 
Table 
6.8: 
Summary 
of 
BlueCAM 
modelled 
scenarios 
............................................................................... 
57 
Table 
6.9: 
Ranking 
of 
technical 
innovation 
areas 
for 
blue 
carbon 
sequestration...................................... 
58 
Table 
7.1: 
Technical 
innovation 
opportunities 
for 
carbon 
sequestration 
through 
direct 
air 
capture. 
...... 
63 
Table 
7.2: 
Summary 
of 
outputs 
from 
the 
direct 
air 
capture 
workshop. 
.................................................... 
64 
Table 
7.3: 
Cost 
reductions 
for 
direct 
air 
capture 
technical 
innovation 
areas. 
........................................... 
65 


vi 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Table 
9.1: 
Technical 
innovation 
opportunities 
for 
carbon 
sequestration 
through 
biomass/biochar........ 
75 
Table 
9.2: 
Summary 
of 
outputs 
from 
the 
biomass/biochar 
workshop. 
..................................................... 
76 
Table 
9.3: 
Cost 
reduction 
factors 
for 
biomass/biochar 
technical 
innovation 
areas. 
All 
factors 
are 


percentage 
reductions 
(costs) 
or 
increases 
(revenues) 
relative 
to 
current 
costs...................................... 
78 
Table 
9.4: 
Cost 
reductions 
for 
biomass/biochar 
technical 
innovation 
areas............................................. 
79 
Table 
9.5: 
Relative 
sequestration 
benefit 
for 
each 
biomass/biochar 
technical 
innovation 
area. 
............. 
82 
Table 
9.6: 
Ranking 
of 
technical 
innovation 
areas 
for 
biomass/biochar 
carbon 
sequestration.................. 
84 
Table 
11.1: 
Technical 
innovation 
opportunities 
for 
carbon 
sequestration 
through 
ex-situ 
mineral 


carbonation. 
............................................................................................................................................... 
90 


Table 
11.2: 
Technical 
innovation 
opportunities 
for 
carbon 
sequestration 
through 
in-situ 
mineral 
carbonation. 
............................................................................................................................................... 
90 
Table 
11.3: 
Voting 
results 
for 
the 
mineral 
carbonation 
technical 
innovation 
areas. 
The 
technical 


innovation 
areas 
with 
the 
highest 
votes 
for 
each 
theme 
are 
shown 
in 
bold 
font. 
These 
areas 
were 


assessed 
as 
a 
priority 
in 
the 
workshop....................................................................................................... 
91 
Table 
11.4: 
Summary 
of 
outputs 
from 
the 
mineral 
carbonation 
workshop. 
The 
prioritised 
in-situ 
and 
ex-
situ 
technical 
innovation 
areas 
are 
shown 
in 
bold. 
Note: 
fractures 
characterisation 
was 
not 
included 
in 
the 
workshop.............................................................................................................................................. 
92 


Table 
11.5: 
Cost 
reductions 
for 
mineral 
carbonation 
technical 
innovation 
areas. 
.................................... 
94 


Table 
11.6: 
Relative 
sequestration 
benefit 
of 
each 
ex-situ 
mineral 
carbonation 
technical 
innovation 
area. 


.................................................................................................................................................................... 
97 
Table 
11.7: 
Relative 
sequestration 
benefit 
of 
each 
in-situ 
mineral 
carbonation 
technical 
innovation 
area. 
.................................................................................................................................................................... 
98 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
vii 



Acknowledgments 


This 
project 
was 
co-funded 
by 
the 
Climate 
Change 
Authority 
and 
the 
Clean 
Energy 
Regulator. 


The 
authors 
would 
like 
to 
thank 
and 
acknowledge 
the 
helpful 
advice 
provided 
by 
Ben 
Holt, 
Will 
Howard 
and 
Erik 
Olbrei. 


The 
authors 
would 
also 
like 
to 
thank 
Maren 
Strachan 
for 
her 
great 
facilitation 
of 
the 
workshops, 
Nawshad 
Haque 
for 
his 
helpful 
assistance 
with 
the 
setup 
and 
lead 
of 
the 
combined 
biomass 
biochar 
workshop 
and 
Jody 
Bruce 
for 
her 
assistance 
with 
workshop 
planning. 


The 
project 
team 
would 
like 
to 
acknowledge 
and 
thank 
all 
workshop 
participants 
who 
provided 
their 
valuable 
insights 
to 
this 
report. 
It 
is 
their 
contributions 
that 
made 
the 
insights 
possible. 


The 
list 
of 
participants 
is 
below, 
note 
that 
some 
participants 
have 
preferred 
to 
remain 
anonymous 
and 
are 
not 
included. 


Planted 
vegetation 
workshop 
participants: 


Natasa 
Sikman 
,Anthony 
Fitzgerald, 
Zoe 
Ryan,Tai, 
White-Toney, 
Shaun 
Levick, 
Stephen 
Roxburgh, 
Paul 
Ryan, 
Peter 
Ritson, 
Jenny 
Sinclair, 
Beren 
Spencer, 
Arjan 
Wilkie, 
Philipp 
Kilham, 
Annette 
Cowie, 
Simon 
Dawkins, 
Martin 
Moroni, 
Tim 
Moore, 
Rod 
Keenan, 
Liam 
Costello. 


Blue 
carbon 
workshop 
participants: 


Andy 
Steven, 
Ray 
Marcos 
Martinez, 
Cath 
Lovelock, 
Lauren 
Drake, 
Mat 
Vanderklift, 
Valerie 
Hagger, 
Nikki 
Fitzgerald, 
Veda 
Fitzsimmons. 


Direct 
Air 
Capture 
workshop 
participants: 


Paul 
Feron, 
Roger 
Aines, 
Timothy 
Fout, 
Paul 
Webley, 
Deanna 
Dalessandro, 
Julian 
Tureck, 
Ali 
Kiani, 
M 
Lucquiaud, 
Christopher 
Jones. 


Biomass/biochar 
workshop 
participants: 


Peter 
Burgess, 
Annette 
Cowie, 
Craig 
Bagnall, 
Fabiano 
Ximenes, 
Rajinder 
Singh, 
Ian 
O'Hara, 
Stephen 
Joseph, 
Gustavo 
Fimbres 
Weihs, 
Jenny 
Hayward, 
Nawshad 
Haque. 


Carbon 
Capture 
and 
Storage 
workshop 
participants: 


Peter 
Cook, 
Charles 
Jenkins, 
Darren 
Greer, 
Andrew 
Garnett, 
Phil 
Grainger, 
Geoff 
Obrien, 
Noel 
Simento, 
Matthew 
Sherwell. 


Mineral 
carbonation 
workshop 
participants: 


Renee 
Birchall, 
Andrew 
Lenton, 
John 
Beever, 
Sophia 
Hamblin-Wang, 
Philip 
Fawell, 
Mei 
Yuan, 
Stuart 
Watson, 
Ralf 
Haese 


viii 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



1 
Key 
messages 


This 
report 
details 
the 
methods, 
outputs 
and 
analysis 
from 
a 
series 
of 
workshops 
held 
to 
elicit 
expert 
advice 
on 
how 
technical 
innovation 
can 
lower 
the 
cost 
of 
carbon 
sequestration 
and 
correspondingly 
decrease 
an 
economic 
barrier 
to 
the 
uptake 
of 
different 
sequestration 
approaches. 
The 
expert 
advice 
is 
translated 
into 
estimates 
of 
sequestration 
cost 
reduction 
either 
by 
using 
simple 
cost 
flow 
models 
or 
by 
interpretation 
of 
workshop 
participant 
estimates. 
A 
ranked 
list 
of 
technical 
innovation 
options 
for 
each 
sequestration 
technology 
is 
developed 
using 
cost 
reduction 
estimates 
and 
other 
metrics. 


The 
report 
findings 
do 
not 
constitute 
a 
formal 
review, 
an 
economic 
analysis, 
or 
the 
final 
word 
on 
any 
of 
the 
sequestration 
technologies 
reviewed, 
which 
in 
some 
cases, 
are 
changing 
rapidly. 


The 
report 
does 
not 
provide 
estimates 
of 
additional 
economic 
potential 
sequestration 
that 
could 
be 
unlocked 
due 
to 
the 
cost 
reduction 
potential, 
and 
this 
is 
left 
for 
future 
studies 
to 
undertake. 


All 
cost 
reduction 
figures 
should 
be 
taken 
as 
indicative, 
or 
“ballpark”, 
and 
used 
more 
as 
a 
means 
of 
ranking 
or 
prioritising 
action 
to 
drive 
down 
the 
technology 
cost 
rather 
than 
for 
formal 
evaluation 
of 
costs 
of 
implementation. 


Workshops 
were 
conducted 
for 
sequestration 
opportunities 
using 
planted 
vegetation, 
blue 
carbon, 
direct 
air 
capture, 
biomass/biochar, 
carbon 
capture 
and 
storage, 
and 
mineral 
carbonation 
sequestration 
approaches. 
In 
addition, 
a 
brief 
review 
of 
two 
technology 
options 
for 
savanna 
fire 
management 
was 
undertaken. 


Key 
messages 
from 
the 
analysis 
of 
the 
workshops’ 
outputs 
are: 


 
For 
each 
sequestration 
approach, 
the 
identified 
technical 
innovation 
opportunities 
have 
varying 
potentials 
to 
reduce 
the 
sequestration 
cost. 
In 
some 
cases, 
such 
as 
direct 
air 
capture, 
biomass/biochar 
and 
mineral 
carbonation 
sequestration 
approaches, 
these 
technical 
innovations 
have 
significant 
potential 
to 
lower 
costs 
and 
accelerate 
uptake. 
 
Each 
sequestration 
approach 
is 
at 
a 
different 
maturity 
stage 
(commercial 
readiness 
level 
or 
technical 
readiness 
level). 
The 
less 
mature 
approaches 
(generally 
the 
engineered 
sequestration 
approaches) 
have 
a 
better 
potential 
for 
lower 
costs 
because 
the 
current 
costs 
per 
tonne 
of 
sequestered 
carbon 
are 
typically 
higher. 
This 
is 
particularly 
the 
case 
with 
direct 
air 
capture, 
where 
current 
costs 
are 
high 
($878 
per 
tonne1), 
with 
reductions 
of 
about 
25% 
on 
current 
costs 
suggested 
as 
possible 
for 
each 
of 
the 
technologies. 
 
The 
cost 
reductions 
determined 
for 
this 
report 
are 
not 
additive. 
There 
are 
dependencies 
and 
feedbacks 
between 
the 
different 
cost 
drivers 
for 
each 
of 
the 
technology 
options. 
As 
a 
result, 
summing 
the 
individual 
cost 
reductions 
to 
determine 
an 
overall 
possible 
end 
cost 
for 
a 
sequestration 
approach 
is 
strongly 
discouraged. 
 
Blue 
carbon 
technical 
innovations 
could 
reduce 
costs 
by 
up 
to 
42% 
on 
current 
costs 
($92 
per 
tonne). 
 
Innovations 
in 
sequestration 
using 
planted 
vegetation 
could 
result 
in 
a 
more 
modest 
9– 
30% 
cost 
reduction 
on 
a 
baseline 
of 
$19.50 
per 
tonne. 
1 
All 
costs 
in 
this 
report 
are 
in 
Australian 
dollars 
except 
where 
otherwise 
specified. 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
9 



 
Although 
mineral 
carbonation 
is 
at 
a 
low 
maturity 
level, 
there 
are 
good 
opportunities 
to 
lower 
costs 
for 
ex-situ 
approaches, 
with 
workshops 
indicating 
a 
reduction 
range 
from 
38% 
to 
72% 
based 
on 
current 
costs 
of 
$222 
per 
tonne. 
In-situ 
approaches 
have 
a 
lower 
baseline 
cost 
($37 
per 
tonne) 
and 
good 
potential 
to 
lower 
costs 
by 
13–54% 
of 
the 
current 
cost. 
 
No 
cost 
reduction 
estimates 
for 
carbon 
capture 
and 
storage 
are 
reported 
due 
to 
differences 
with 
the 
workshop 
format 
and 
the 
general 
feeling 
that 
the 
technology 
is 
relatively 
mature 
with 
a 
reasonable 
commercial 
readiness 
level 
and 
that 
the 
challenges 
are 
elsewhere 
(financing, 
social 
license 
etc.) 
 
The 
provision 
of 
fire 
risk 
and 
remotely 
sensed 
fire 
severity 
information 
can 
potentially 
improve 
the 
setting 
of 
the 
early 
dry 
or 
late 
dry 
season 
cut-off 
dates 
for 
the 
savanna 
fire 
management 
sequestration 
approach. 
 
Developing 
a 
common 
language 
(terms 
and 
concepts) 
to 
discuss 
sequestration 
issues 
would 
be 
valuable, 
helping 
to 
avoid 
confusion 
and 
improving 
the 
efficiency 
of 
these 
discussions. 
Most 
workshops 
took 
time 
to 
reach 
a 
common 
understanding 
of 
the 
terms 
and 
concepts 
under 
discussion. 
This 
is 
not 
unexpected 
as 
different 
sectors 
(e.g. 
industry, 
government, 
academia) 
often 
have 
their 
preferred 
dialect. 
 
It 
should 
be 
noted 
that 
at 
time 
of 
writing 
the 
spot 
price 
for 
one 
tonne 
of 
carbon 
is 
$35.50. 
1.1 
Summary 
of 
cost 
reduction 
potential 
results 
The 
economic 
viability 
of 
sequestration 
approaches 
can 
be 
improved 
by 
reducing 
costs 
or 
generating 
additional 
values 
from 
the 
sequestration 
activity 
that 
provide 
an 
economic 
return 
– 
for 
example, 
developing 
new 
long-lived 
products 
from 
biomass 
residue. 
. 
In 
such 
cases, 
creating 
a 
new 
product 
does 
not 
impact 
the 
sequestration 
cost 
but 
will 
improve 
the 
overall 
economic 
viability 
of 
the 
approach. 
In 
instances 
where 
such 
additional 
value 
creation 
is 
used 
in 
the 
analysis, 
the 
cost 
reduction 
is 
reported 
as 
zero. 


Table 
1.1 
A 
summary 
of 
the 
individual 
technologies 
reviewed, 
and 
their 
cost 
reduction 
potential 
is 
provided 
in 
Table 
1.1. 
For 
more 
detail 
and 
description 
of 
the 
technology 
innovation 
areas, 
see 
the 
relevant 
chapters 
of 
this 
report. 


Table 
1.1: 
Summary 
of 
the 
cost 
reduction 
potential 
of 
technology 
innovation 
areas 
for 
each 
sequestration 
approach 
reviewed. 


SequestrationtechnologyTechnicalinnovationareaCostreductionfrombaseline($
pertonne)
Netcost($pertonne)
Vegetation 
Baseline 
cost 


0 
19.5 


Low-costimagery–2.816.7Zeroorlowemissionfuels–3.416.1
Small-scale 
equipment 
for 
agroforestry 
–4.7 
14.8 


Control 
of 
pests, 
diseases 
and 
browsing 
animals 
–6.1 
13.4 
Decision 
support 
for 
informing 
optimal 
species 
selection 
–3.9 
15.6 
Lower-cost 
fencing 
–2.9 
16.6 



10 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Genetic 
improvements 
–1.8 


Newproductsforbiomassresidue019.5Driverlessorautomatedvehicles–3.016.5
Blue 
carbon 
Baseline 
cost 


0 
92 


Methods 
and 
indices 
for 
measuring 
other 
benefits 
0 
92 
National 
model 
for 
tidal 
introduction 
and 
feasibility 
assessment 
–39 
53 
Earth 
observation 
technologies 
for 
restoration 
site 
identification 
and 
assessment 
–17 
75 
Direct 
air 
capture 
Baseline 
cost 
0 
878 


Materials 
–218 
660 
Energy 
supply 
–232 
646 
Process 
and 
equipment 
–197 
681 
Combined 
Baseline 
cost 
0 
60 
biomass/biochar 


Technology 
at 
scale 
–10.2 
49 
Large-scale 
modular 
plants 
–14.7 
45 
Utilisation 
cases 
0 
60 


Biocharconversion–1148Guidelines060
Mineral 
carbonation 
ex-Baseline 
cost 
0 
222 
situ 


Characterisation 
of 
feedstock 
–86 
136 
Feedstock/mineral 
pre-treatment 
–128 
94 
Catalyst/additive 
development 
for 
enhancing 
mineral 
–89 
133 


carbonation 
kinetics 


Creating 
high-value 
end 
products 
–159 
63 
Mineral 
carbonation 
in-Baseline 
cost 
0 
37 
situ 
In-situ 
mineral 
carbonation 
mapping 
–20 
17 
Innovations 
that 
enable 
use 
of 
seawater 
–14 
23 


Understandingthekineticstoimprovetheefficiency–532Optimisationofinjectionstrategyandpatterns–1720
Readers 
should 
use 
the 
following 
definitions 
to 
provide 
a 
consistent 
interpretation 
of 
the 
opportunity 
created 
by 
the 
technical 
innovations 
investigated: 


 
Cost 
factor 
is 
defined 
as 
a 
sequestration 
cost 
reduction 
factor 
relative 
to 
current 
sequestration 
costs 
achieved 
through 
routine 
use 
of 
the 
technical 
innovation 
opportunity. 
 
Maturity 
is 
defined 
as 
the 
year 
at 
which 
the 
technical 
innovation 
would 
be 
suitable 
for 
routine 
use 
(subject 
to 
appropriate 
investment). 
 
Scaling 
factor 
is 
defined 
as 
the 
multiplier 
increases 
in 
sequestration 
uptake 
if 
the 
technical 
innovation 
was 
routinely 
used. 
Maturity, 
cost 
reduction 
and 
scaling 
factors 
are 
presented 
on 
bubble 
diagrams. 
A 
cost 
reduction/maturity 
space 
is 
created 
on 
the 
x–y 
plane, 
with 
the 
x-axis 
being 
the 
year 
of 
maturity 
and 
the 
y-axis 
being 
the 
cost 
reduction 
in 
dollars. 
The 
lower 
left-hand 
quadrant 
describes 
a 
space 
of 
high-cost 
reduction 
and 
early 
maturity, 
with 
the 
lower 
right-hand 
quadrant 
maturing 
later. 
The 
scaling 
factor 
is 
represented 
as 
the 
size 
of 
the 
bubble. 
The 
technology 
options 
with 
the 
greatest 
scale, 
highest 
cost-reduction 
potential 
and 
earliest 
maturity 
dates 
will 
generate 
the 
largest 
additional 
sequestration 
– 
that 
is, 
the 
largest 
bubbles 
in 
the 
lower 
left-hand 
quadrant. 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
11 



Figure 
1-1: 
Visualisation 
of 
cost 
reduction, 
scaling 
factor 
and 
maturity. 
* 
Indicates 
the 
scaling 
factor. 


To 
answer 
the 
question, 
is 
it 
better 
to 
have 
a 
greater 
scaling 
factor 
or 
earlier 
maturity 
time 
for 
a 
technical 
innovation, 
an 
S-curve 
model 
typically 
found 
in 
the 
uptake 
of 
innovations 
is 
used 
to 
compare 
scaling 
factors 
and 
maturity 
time 
frames. 
Six 
scenarios 
were 
modelled 
with 
three 
different 
scaling 
factors(baseline 
-one, 
two 
and 
three) 
and 
three 
different 
maturity 
dates 
(2025, 
2030 
and 
2035). 
The 
output 
of 
the 
scenario 
modelling 
is 
Mt 
per 
year 
of 
sequestration, 
and 
more 
details 
of 
this 
approach 
are 
in 
Chapter 
4. 


140 
120 


Cumulative 
sequestratioin 
(Mt) 


100 
80 
60 
40 
20 
0 



baseline 
2% 
growth 
Scale 
factor 
2, 
maturity 
2030 
Scale 
factor 
3, 
maturity 
2030 


2020 
2025 
2030 
2035 
2040 
2045 
2050 
Year 


Figure 
1-2:Hypothetical 
cumulative 
sequestration 
for 
the 
uptake 
of 
technical 
innovation 
for 
scaling 
factors 
of 
2 
and 
3, 
for 
maturity 
timeframes 
of 
2030. 


12 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Cumulative 
sequestratioin 
(Mt) 


160 
140 
120 
100 
80 
60 
40 
20 


0 
2020 
2025 
2030 
2035 
2040 
2045 
2050 
Year 



baseline 
2% 
growth 
Scale 
factor 
3, 
maturity 
2025 
Scale 
factor 
3, 
maturity 
2030 
Scale 
factor 
3, 
maturity 
2035 


Figure 
1-3: 
Hypothetical 
cumulative 
sequestration 
for 
the 
uptake 
of 
technical 
innovation 
for 
maturity 
timeframes 
of 
2025, 
2030 
and 
2035, 
for 
a 
scaling 
factor 
of 
3. 


The 
modelling 
shows 
that 
the 
scaling 
factor 
has 
a 
larger 
impact 
on 
cumulative 
sequestration 
than 
maturity 
time 
for 
this 
analysis 
(Figure 
1-2 
and 
Figure 
1-3). 
A 
technical 
innovation 
with 
a 
maturity 
year 
of 
2030 
and 
a 
scaling 
factor 
of 
three 
would 
deliver 
an 
additional 
40Mt 
of 
sequestration 
by 
2050, 
compared 
to 
a 
scaling 
factor 
of 
2 
(Figure 
1-2). 
The 
earlier 
the 
maturity 
date, 
the 
more 
sequestration 
will 
be 
potentially 
delivered 
(Figure 
1-3). 
Overall, 
technical 
innovations 
with 
an 
earlier 
maturity 
date 
and 
a 
larger 
scaling 
factor 
have 
the 
greatest 
sequestration 
benefit. 
By 
2050, 
all 
scenarios 
with 
larger 
scaling 
factors 
generate 
more 
sequestration 
than 
the 
lower 
scaling 
factor 
cases. 


1.2 
Planted 
vegetation 
 
The 
best 
technology 
innovations 
to 
lower 
cost 
are 
those 
that 
mature 
early 
as 
they 
provide 
greater 
cumulative 
sequestration, 
have 
large 
cost 
reduction 
potential 
and 
have 
a 
large 
scaling 
factor. 
The 
control 
of 
pests, 
diseases 
and 
browsing 
animals 
and 
species 
decision 
support 
are 
the 
two 
technical 
innovation 
areas 
that 
have 
good 
cost 
reduction 
potential 
and 
early 
maturity 
and 
scaling 
factors. 
Small-scale 
agroforestry 
equipment 
has 
good 
cost 
reduction 
potential 
though 
a 
later 
maturity 
time 
and 
smaller 
scaling 
factor. 
 
All 
technical 
innovations 
reviewed 
have 
potential 
to 
lower 
costs, 
with 
cost 
reductions 
of 
up 
to 
30% 
(range 
9–30% 
on 
a 
baseline 
of 
$19.50 
per 
tonne, 
see 
Table 
1.2). 
 
The 
baseline 
cost 
($19.50 
per 
tonne) 
determined 
in 
this 
analysis 
compares 
well 
to 
the 
figures 
reported 
in 
chapters 
of 
Fitch 
et 
al. 
(2022) 
of 
$20–$30 
per 
tonne 
for 
permanent 
plantings 
and 
$10–$30 
per 
tonne 
for 
plantation 
and 
farm 
forestry. 
 
The 
rankings 
of 
the 
technology 
options 
(see 
Table 
1.3), 
and 
the 
broader 
analysis 
results, 
are 
sensitive 
to 
the 
modelling 
assumptions, 
particularly 
biomass 
revenue 
and 
biomass 
yield. 
Further 
detailed 
analysis 
of 
the 
high-priority 
options 
identified 
in 
the 
workshop 
would 
provide 
greater 
insight 
and 
greater 
confidence 
for 
potential 
future 
investment. 
Table 
1.2: 
Cost 
reductions 
for 
planted 
vegetation 
technical 
innovation 
areas. 


TechnicalinnovationareaCostreductionfrombaseline($pertonne)
Netcost($pertonne)
Baselinecost019.5
Control 
of 
pests, 
diseases 
and 
browsing 
–6.1 
13.4 
animals 
Small-scale 
equipment 
for 
agroforestry 
–4.7 
14.8 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
13 



Decision 
support 
for 
informing 
optimal 
–3.9 
15.6 
species 
selection 
Zero 
or 
low 
emission 
fuels 
–3.4 
16.1 


Lower-cost 
fencing 
–2.9 
16.6 
Low-cost 
imagery 
–2.8 
16.7 


Genetic 
improvements 
–1.8 
17.7 
New 
products 
for 
biomass 
residue 
0 
19.5 



Figure 
1-4: 
Comparison 
of 
cost 
reduction, 
year 
of 
maturity 
and 
scaling 
factor 
for 
planted 
vegetation 
technical 
innovation 
areas. 
* 
Indicates 
the 
scaling 
factor. 


TechnicalinnovationareaCostreduction($pertonne)
ScalingandmaturityrelativebenefitImplementationcomplexityPrioritygroup
Low-cost 
imagery 
–2.8 
0.9 
Low–medium 
1 


Decision 
support 
for 
informing 
optimal 
species 
–3.9 
0.7 
Medium 
1 
selection 
Small-scale 
equipment 
for 
agroforestry 
–4.7 
0.4 
Medium 
1 


Lower-cost 
fencing 
–2.9 
0.3 
Low 
1 
Control 
of 
pests, 
diseases 
and 
browsing 
animals 
–6.1 
1.0 
Low–high 


2 


Genetic 
improvements 
–1.8 
0.8 
High 
2 
New 
products 
for 
biomass 
residue 
0 
0.7 
Medium 


2 


Zero 
or 
low 
emission 
fuels 
–3.4 
0.5 
High 
3 
Driverless 
or 
automated 
vehicles 
–3 
0.7 
High 


3 


Table 
1.3: 
Ranking 
of 
technical 
innovation 
areas 
for 
planted 
vegetation 
carbon 
sequestration. 


14 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



1.3 
Blue 
carbon 
 
This 
report 
reviewed 
technical 
innovation 
opportunities 
of 
blue 
carbon 
(mangrove 
and 
saltbush) 
restoration 
projects 
for 
their 
potential 
to 
lower 
costs 
and 
improve 
project 
economic 
viability. 
The 
analysis 
indicated 
cost 
reductions 
ranging 
from 
20–42% 
were 
possible 
on 
a 
baseline 
of 
$92 
per 
tonne. 
 
The 
baseline 
cost 
($92 
per 
tonne) 
determined 
in 
this 
analysis 
is 
significantly 
higher 
than 
the 
$18–$30 
per 
tonne 
reported 
in 
the 
chapters 
of 
Fitch 
et 
al. 
(2022). 
This 
high 
baseline 
uses 
updated 
estimates 
of 
costs 
(Hagger 
et 
al., 
2022) 
and 
reflects 
the 
low 
maturity 
and 
scale 
of 
blue 
carbon 
projects. 
 
The 
economic 
viability 
of 
blue 
carbon 
projects 
is 
challenging, 
and 
technical 
innovations 
that 
lower 
the 
establishment 
or 
start-up 
costs 
have 
significant 
potential 
to 
reduce 
costs, 
improve 
the 
economic 
viability 
and 
unlock 
additional 
sequestration. 
A 
national 
tidal 
hydrodynamic 
model 
that 
could 
produce 
the 
necessary 
outputs 
to 
quickly 
confirm 
the 
suitability 
and 
eligibility 
of 
blue 
carbon 
projects 
has 
good 
cost 
reduction 
potential. 
 
Any 
technologies 
that 
can 
increase 
the 
revenue 
stream 
for 
blue 
carbon 
projects 
will 
improve 
economic 
viability. 
Methods 
and 
indices 
that 
quantify 
environmental 
service 
provision 
of 
projects 
and 
enable 
a 
premium 
carbon 
price 
for 
a 
differentiated 
product 
or 
support 
other 
environmental 
crediting 
schemes 
(e.g. 
reef 
credits) 
would 
be 
beneficial. 
 
This 
analysis 
and 
ranking 
(see 
Table 
1.5) 
is 
sensitive 
to 
the 
underlying 
assumptions 
in 
the 
modelling. 
Table 
1.4: 
Cost 
reductions 
for 
blue 
carbon 
technical 
innovation 
areas. 


TechnicalinnovationareaCostreductionfrombaseline($pertonne)
Netcost($pertonne)
Baselinecost092
Methods 
and 
indices 
for 
measuring 
other 
benefits 
0 
92 
National 
model 
for 
tidal 
introduction 
and 
feasibility 
–39 
53 
assessment 


Earth 
observation 
technologies 
for 
restoration 
site 
–18 
74 
identification 
and 
assessment 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
15 



Figure 
1-5: 
Comparison 
of 
cost 
reduction, 
year 
of 
maturity 
and 
scaling 
factor 
for 
blue 
carbon 
technical 
innovation 
areas. 
* 
Indicates 
the 
scaling 
factor. 


Table 
1.5: 
Ranking 
of 
technical 
innovation 
areas 
for 
blue 
carbon 
sequestration. 


TechnicalinnovationareaCostreduction($pertonne)
ScalingandmaturityrelativebenefitImplementationcomplexityPriority
Methods 
and 
indices 
for 
measuring 
other 
0 
0.7 
Medium–high 
1 
benefits 


National 
model 
for 
tidal 
introduction 
and 
feasibility 
assessment 
–39 
1 
Medium 
2 
Earth 
observation 
technologies 
for 
restoration 
site 
identification 
and 
assessment 
–17 
0.6 
Medium 
3 


1.4 
Direct 
air 
capture 
 
Direct 
air 
capture 
technologies 
are 
improving 
rapidly. 
 
Analysis 
of 
workshop-participants’ 
inputs 
indicated 
that 
an 
average 
overall 
cost 
reductions 
of 
69% 
could 
be 
anticipated 
through 
technology 
innovation 
and 
scale-up. 
There 
was, 
however, 
considerable 
variation 
in 
the 
individual 
responses. 
 
Two 
of 
the 
innovation 
areas 
identified 
(materials, 
and 
process 
and 
equipment) 
were 
considered 
most 
effective 
in 
reducing 
the 
direct 
air 
capture 
cost 
and 
should 
be 
pursued 
for 
the 
achievement 
of 
optimum 
performance. 
16 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



 
The 
baseline 
cost 
($900 
per 
tonne) 
used 
in 
this 
analysis 
is 
higher 
than 
the 
$300–$600 
per 
tonne 
reported 
in 
chapters 
of 
Fitch 
et 
al. 
(2022) 
and 
is 
sourced 
from 
the 
latest 
literature 
(IEAGHG, 
2021). 
 
Achievement 
of 
these 
cost 
reductions 
is 
anticipated 
in 
the 
early 
2030s. 
Table 
1.6: 
Cost 
reductions 
for 
direct 
air 
capture 
technical 
innovation 
areas. 


TechnicalinnovationareaCostreductionfrombaseline($pertonne)
Cost($pertonne)
Baselinecost0900
Materials 
–243 
657 
Energy 
supply 
–72 
828 
Process 
and 
equipment 
–306 
694 



Figure 
1-6: 
Comparison 
of 
cost 
reduction, 
year 
of 
maturity 
and 
scaling 
factor 
for 
direct 
air 
capture 
technical 
innovation 
areas. 
* 
Indicates 
the 
scaling 
factor. 


1.5 
Savanna 
fire 
management 
 
There 
is 
high 
agreement 
among 
those 
consulted, 
and 
evidence 
from 
the 
literature, 
that 
the 
1 
August 
cut-off 
date 
for 
early/late 
dry 
season 
fires 
could 
be 
improved, 
or 
replaced, 
with 
a 
more 
appropriate 
measure. 
 
A 
transition 
to 
a 
system 
based 
on 
vegetation 
curing 
could 
be 
established 
and 
supplemented 
with 
weather 
conditions 
to 
forecast 
fire 
severity. 
 
Emerging 
technology 
may 
provide 
a 
means 
for 
better 
mapping 
fire 
severity 
and 
extent 
and 
could 
form 
the 
basis 
of 
evidence-or 
outcome-based 
assessment 
of 
burning, 
rather 
than 
relying 
on 
hard 
dates. 
Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
17 



 
Fire 
severity 
prediction 
has 
recently 
been 
shifted 
to 
the 
Australian 
Fire 
Danger 
Rating 
System. 
It 
is 
likely 
that 
the 
system 
will 
undergo 
extensive 
refinement 
and 
updating 
to 
improve 
its 
applicability 
across 
the 
continent. 
1.6 
Carbon 
capture 
and 
storage 
 
Carbon 
capture 
and 
storage 
is 
an 
industry 
made-up 
of 
mature 
components. 
Cost 
reductions 
in 
carbon 
capture 
and 
storage 
will 
likely 
come 
about 
through 
numerous 
small 
improvements 
throughout 
the 
processing 
chain. 
It 
is 
the 
execution 
of 
large 
projects 
that 
will 
require 
‘learning 
by 
doing’ 
that 
will 
lead 
to 
subsequent 
cost 
reduction. 
 
Carbon 
capture 
and 
storage 
hubs 
are 
clear 
examples 
of 
system-level 
improvement 
involving 
developments 
and 
enhancements 
across 
the 
entire 
carbon 
capture 
and 
storage 
chain. 
 
There 
are 
opportunities 
for 
focused 
research 
and 
development 
into 
capture 
technology 
in 
hard-to-abate 
areas 
such 
as 
steel 
and 
cement 
manufacturing. 
 
A 
horizon-scanning 
exercise 
undertaken 
as 
an 
IEAGHG 
study 
(Orchard 
et 
al. 
2021) 
projected 
operational 
cost 
reductions 
by 
2040 
in 
the 
20–30% 
range. 
These 
are 
likely 
to 
result 
from 
a 
combination 
of 
factors, 
including 
smarter 
materials, 
additive 
manufacturing, 
and 
more 
effective 
operations 
and 
maintenance 
due 
to 
the 
use 
of 
the 
Internet 
of 
Things, 
virtual 
reality 
and 
artificial 
intelligence. 
1.7 
Biomass/biochar 
 
All 
technical 
innovation 
options 
looked 
to 
have 
the 
potential 
to 
lower 
costs 
either 
through 
reducing 
costs 
or 
improving 
the 
overall 
economic 
viability 
of 
char 
production 
(Table 
1.7, 
Table 
1.8). 
The 
cost 
reductions 
ranged 
from 
$11 
to 
$14.70 
per 
tonne, 
with 
large-scale 
modular 
plants 
having 
the 
largest 
cost 
reduction 
potential. 
 
The 
baseline 
cost 
($60 
per 
tonne) 
used 
in 
this 
analysis 
is 
lower 
than 
the 
$80–$120 
per 
tonne 
reported 
in 
the 
chapters 
of 
Fitch 
et 
al. 
(2022). 
The 
lower 
cost 
reflects 
the 
larger 
scale 
plant 
used 
for 
this 
analysis 
(13,000 
tonnes 
per 
year). 
 
There 
was 
a 
sentiment 
during 
the 
workshop 
that 
most 
of 
the 
technical 
challenges 
of 
this 
sequestration 
method 
have 
been 
solved 
(i.e. 
the 
industry 
knows 
how 
to 
produce 
char) 
and 
that 
the 
obstacles 
to 
scaling 
the 
output 
relate 
to 
increasing 
the 
commercial 
readiness 
level 
and 
confidence 
in 
economic 
viability. 
 
There 
are 
opportunities 
to 
grow 
the 
demand 
for 
biochar 
by 
better 
identifying 
utilisation 
cases 
and 
articulating 
the 
co-benefits 
of 
use. 
 
There 
are 
specific 
technical 
areas 
identified 
during 
the 
workshop 
that 
could 
aid 
in 
lower 
sequestration 
costs. 
These 
are: 
o 
cost-effective 
methods 
to 
convert 
syngas 
to 
a 
more 
readily 
transportable 
form 
o 
decision 
support 
for 
process 
optimisation 
o 
decision 
support 
for 
plant 
location, 
including 
as 
part 
of 
a 
regional 
hub. 
18 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Table 
1.7: 
Cost 
reductions 
for 
biomass/biochar 
technical 
innovation 
areas. 


TechnicalinnovationareaCostreductionfrombaseline($pertonne)
Netcost($pertonne)
Baselinecost060
Technology 
at 
scale 
–10.2 
49 
Large-scale 
modular 
plants 
–14.7 
45 
Utilisation 
cases 
0 
60 
Biochar 
conversion 
–11 
48 
Guidelines 
0 
60 



Figure 
1-7: 
Comparison 
of 
cost 
reduction, 
year 
of 
maturity 
and 
scaling 
factor 
for 
biomass/biochar 
technical 
innovation 
areas. 
* 
Indicates 
the 
scaling 
factor. 


Table 
1.8: 
Ranking 
of 
technical 
innovation 
areas 
for 
biomass/biochar 
carbon 
sequestration. 


TechnicalinnovationareaCostreduction($pertonne)
Scalingandmaturityrelativebenefit(2050)
ImplementationcomplexityRanking
Large-scale 
modular 
plants 
–14.7 
0.7 
Moderate 


1 


Technology 
at 
scale 
–10.2 
1.0 
Moderate 


2 


Biochar 
conversion 
–11 
0.1 
Not 
discussed 


3 


Guidelines 
0 
0.2 
Not 
discussed 
4 
Utilisation 
cases 
0 
0.1 
Low 


5 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
19 



1.8 
Mineral 
carbonation 
 
There 
is 
no 
globally 
agreed 
list 
of 
definitions 
for 
each 
area 
of 
mineral 
carbonation. 
An 
opportunity 
and 
need 
exist 
to 
develop 
formal 
guidelines 
here 
that 
will 
aid 
knowledge 
exchange. 
 
When 
ex-situ 
carbonation 
involves 
dissolution 
or 
partial 
dissolution 
to 
solubilise 
magnesium, 
there 
is 
generally 
little 
detail 
on 
what 
is 
left 
behind 
in 
any 
residue 
or 
what 
becomes 
of 
the 
process 
liquor 
after 
reaction 
of 
magnesium 
to 
form 
a 
product. 
Consideration 
needs 
to 
be 
given 
to 
whether 
the 
carbonation 
process 
is 
creating 
a 
new 
problem 
for 
which 
a 
response 
then 
introduces 
additional 
costs. 
This 
will 
be 
dependent 
on 
the 
minerals/tailings 
being 
considered. 
 
There 
is 
often 
an 
assumption 
that 
critical 
metals 
within 
tailings 
or 
mine 
waste 
can 
be 
recovered. 
The 
reality 
is 
that 
they 
need 
to 
be 
present 
at 
levels 
that 
make 
the 
additional 
processing 
a 
viable 
option, 
with 
recovery 
processes 
being 
complex 
and 
expensive. 
 
The 
methodology 
associated 
with 
measurement, 
reporting 
and 
verification 
of 
carbon 
dioxide 
removal 
and 
storage 
methods 
are 
critical. 
They 
may 
have 
a 
huge 
impact 
on 
the 
cost 
reduction 
potential 
and 
uptake 
scaling 
potential 
for 
technology 
innovation 
areas. 
The 
measurement, 
reporting 
and 
verification 
process 
needs 
to 
be 
as 
cost-effective 
as 
possible 
in 
meeting 
the 
requirements 
of 
a 
given 
carbon 
crediting 
scheme. 
 
The 
cost 
reduction 
potential 
may 
increase 
significantly 
by 
expanding 
existing 
feedstock 
options 
to 
include 
novel 
feedstocks 
from 
industrial 
waste 
streams 
in 
Australia. 
These 
industrial 
waste 
streams 
might 
include 
steel 
slags 
or 
incinerator 
bottom 
ash. 
 
Product 
market 
scaling 
potential 
is 
much 
larger 
than 
existing 
markets. 
The 
exact 
intent 
of 
these 
product 
markets 
needs 
additional 
work. 
Table 
1.9: 
Cost 
reductions 
for 
mineral 
carbonation 
technical 
innovation 
areas. 


MineralcarbonationtypeTechnicalinnovationareaCostreductionfrombaseline($pertonne)
Netcost($pertonne)
Ex-situ 
Characterisation 
of 
feedstock 
–86 
136 
Feedstock/mineral 
pre-treatment 
–128 
94 


Baselinecost(ex-situ)0222
Catalyst/additive 
development 
for 
–89 
133 
enhancing 
mineral 
carbonation 
kinetics 
Creating 
high-value 
end 
products 
–159 
63 
In-situ 
In-situ 
mineral 
carbonation 
mapping 
–20 
17 


Baselinecost(in-situ)037
Innovations 
that 
enable 
use 
of 
seawater 
–14 
23 
Understanding 
the 
kinetics 
to 
improve 
–5 
32 
efficiency 


Optimisation 
of 
injection 
strategy 
and 
–17 


20 


patterns 


20 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Figure 
1-8: 
Comparison 
of 
cost 
reduction, 
year 
of 
maturity 
and 
scaling 
factor 
for 
ex-situ 
mineral 
carbonation 
technical 
innovation 
areas. 
* 
Indicates 
the 
scaling 
factor. 



Figure 
1-9: 
Comparison 
of 
cost 
reduction, 
year 
of 
maturity 
and 
scaling 
factor 
for 
in-situ 
mineral 
carbonation 
technical 
innovation 
areas. 
* 
Indicates 
the 
scaling 
factor. 


1.9 
Using 
these 
estimates 
for 
integrated 
assessment 
modelling 
As 
described 
in 
this 
report, 
the 
cost 
reduction 
estimates 
and 
the 
time 
it 
is 
likely 
to 
take 
for 
these 
reductions 
to 
be 
realised 
will 
be 
an 
important 
input 
into 
modelling 
technology 
uptake 
and 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
21 



assessing 
the 
contributions 
these 
technologies 
can 
make 
to 
Australia’s 
emission 
reduction 
pathway. 
They 
provide 
guidance 
on 
where 
investment 
can 
unlock 
the 
most 
change 
in 
costs. 
Integrated 
assessment 
modelling 
will 
help 
us 
understand 
plausible 
pathways 
of 
emissions 
reduction 
when 
combined 
with 
the 
other 
key 
considerations 
of 
resource 
supply, 
trade-offs 
and 
social 
barriers 
to 
scaling. 


Uncertainty 
about 
the 
reduction 
in 
costs 
over 
time 
and 
the 
best 
investment 
pathway 
to 
achieve 
these 
reductions 
is 
high. 
Notably, 
one 
of 
the 
critical 
outcomes 
of 
comparing 
the 
results 
across 
different 
workshops 
is 
the 
varying 
agreement 
on 
the 
critical 
issues 
for 
cost 
reduction 
of 
each 
technology. 
Not 
unexpectedly, 
there 
is 
a 
broader 
and 
better-developed 
understanding 
of 
the 
cost 
reduction 
trajectories 
of 
more 
mature 
technologies 
(higher 
technical 
readiness 
level) 
and 
a 
poorer 
understanding 
of 
those 
of 
the 
less 
mature 
technologies. 
This 
makes 
a 
quantitative 
and 
robust 
comparison 
between 
two 
or 
more 
technologies 
challenging. 
Carrying 
this 
forward 
into 
marginal 
abatement 
cost 
curves 
that 
project 
technology 
changes 
over 
time 
for 
integrated 
assessment 
modelling 
will 
be 
tricky 
and 
may 
introduce 
high 
levels 
of 
uncertainty 
into 
pathways. 


Nonetheless, 
the 
workshops 
for 
each 
technology 
have 
provided 
powerful 
insights 
from 
a 
cross-
section 
of 
key 
stakeholders 
around 
cost 
barriers 
to 
scale, 
deployment 
and 
innovation, 
as 
well 
as 
critical 
insights 
around 
perceived 
innovation 
timelines, 
resource 
requirements, 
challenges 
such 
as 
permanence 
and 
the 
importance 
of 
other 
market 
drivers 
of 
environmental 
co-benefits. 


Given 
that 
technologies 
underpinning 
the 
net-zero 
transition 
through 
sequestration 
are 
rapidly 
being 
refined, 
developed 
and 
scaled, 
particularly 
with 
recent 
significant 
investments 
around 
the 
world, 
estimates 
of 
time 
to 
delivery 
and 
even 
breakthrough 
pathways 
may 
need 
to 
be 
revisited 
regularly. 


1.10References 


Fitch 
P, 
Battaglia 
M, 
Lenton 
A, 
Feron 
P, 
Gao 
L, 
Mei 
Y, 
Hortle 
A, 
Macdonald 
L, 
Pearce 
M, 
Occhipinti 
S, 
Roxburgh 
S, 
Steven 


A 
(2022) 
Australia’s 
carbon 
sequestration 
potential: 
a 
stocktake 
and 
analysis 
of 
sequestration 
technologies, 


CSIRO, 
Canberra. 


Hagger 
V, 
Stewart-Sinclair 
P, 
Rossini 
R, 
Waltham 
NJ, 
Ronan 
M, 
Adame 
MF, 
Lavery 
P, 
Glamore 
W, 
Lovelock 
CE 
(2022) 


Coastal 
wetland 
restoration 
for 
blue 
carbon 
in 
Australia. 
Values-based 
approach 
for 
selecting 
restoration 
sites. 


Report 
to 
the 
National 
Environmental 
Science 
Program, 
The 
University 
of 
Queensland. 


IEAGHG 
(2021) 
Global 
assessment 
of 
direct 
air 
capture 
costs: 
technical 
report 
2021-05, 
December 
2021, 
IEA 
Greenhouse 
Gas 
R&D 
Programme, 
Cheltenham, 
UK. 


Orchard 
K, 
Simon 
R, 
Durusut 
E, 
Neades 
S, 
Kemper 
J 
(2021) 
‘Value 
of 
emerging 
and 
enabling 
technologies 
in 
reducing 


costs, 
risks 
and 
timescales 
for 
CCS,’ 
15th 
International 
Conference 
on 
Greenhouse 
Gas 
Control 
Technologies, 


GHGT-15 
proceedings. 


22 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



2 
Introduction 


This 
report 
details 
the 
methods, 
outputs 
and 
analysis 
from 
a 
series 
of 
workshops 
that 
aimed 
to 
explore 
how 
technical 
innovation 
might 
lower 
the 
cost 
of 
carbon 
sequestration 
and 
increase 
the 
uptake 
of 
different 
sequestration 
approaches. 
The 
workshops 
were 
run 
as 
part 
of 
phase 
2 
of 
the 
Climate 
Change 
Authority 
Carbon 
Sequestration 
Project. 
They 
built 
on 
work 
from 
phase 
1, 
which 
resulted 
in 
a 
report 
titled 
Australia’s 
carbon 
sequestration 
potential 
(Fitch 
et 
al. 
2022). 
The 
report 
provided 
defensible 
estimates 
of 
economic 
sequestration 
quantity 
and 
cost. 


The 
phase 
2 
workshops 
were 
designed 
to 
identify 
technical 
innovations 
that 
could 
be 
applied 
to 
sequestration 
approaches 
reviewed 
in 
phase 
1 
and 
to 
estimate 
their 
potential 
to 
reduce 
costs 
and 
increase 
uptake. 
The 
sequestration 
approaches 
workshopped 
were: 


 
planted 
vegetation 
 
blue 
carbon 
 
direct 
air 
capture 
 
combined 
biomass/biochar 
 
carbon 
capture 
and 
storage 
 
mineral 
carbonation. 
The 
workshops 
aimed 
to 
elicit 
qualitative 
information 
that 
the 
project 
team 
could 
use 
to 
develop 
cost 
reduction 
estimates 
and 
rank 
the 
technical 
innovation 
opportunities 
based 
on 
their 
cost 
reduction 
and 
scaling 
potential. 


The 
workshop 
methodology 
is 
detailed 
in 
Chapter 
3, 
and 
the 
results 
are 
presented 
in 
Chapter 
4, 
with 
workshop 
outputs 
presented 
in 
Appendix 
A 
. 


3 
Workshop 
method 


3.1 
Method 
The 
technology 
workshops 
utilised 
a 
modified 
Delphi 
method 
to 
elicit 
participant 
(expert 
opinion) 
responses 
(Helmer 
1967). 
In 
the 
Delphi 
method, 
participants 
are 
asked 
questions 
and 
must 
state 
their 
level 
of 
agreement 
with 
a 
proposition. 
The 
Delphi 
process 
is 
widely 
used 
to 
develop 
expert 
consensus. 
Expert 
opinions 
were 
captured 
using 
three 
continuums 
(cost 
reduction, 
maturity 
and 
scaling 
factor). 
A 
fourth 
continuum 
(investment) 
was 
added 
for 
the 
later 
workshops 
(blue 
carbon; 
carbon 
capture 
and 
storage; 
biomass/biochar; 
and 
mineral 
carbonation). 


The 
consensus 
building 
method 
is 
illustrated 
in 
Figure 
3-1. 
The 
participants 
place 
a 
marker 
on 
a 
continuum, 
representing 
their 
opinion 
in 
response 
to 
a 
question. 
The 
group 
then 
reviews 
the 
continuum 
and, 
based 
on 
the 
evidence 
provided, 
the 
responses 
on 
the 
continuum 
are 
updated 
until 
no 
further 
change 
occurs 
(i.e. 
when 
the 
emergence 
of 
distribution 
becomes 
apparent). 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
23 



Costreductioncontinuum(%)
11%100%
23Costreductioncontinuum(%)
11%100%
23
Figure 
3-1: 
Delphi 
continuum 
for 
expert 
opinion 
elicitation. 
The 
circles 
labelled 
1–3 
represent 
the 
opinions 
of 
three 
participants. 


3.2 
Miro 
board 
The 
workshops 
made 
use 
of 
an 
online 
collaboration 
tool 
called 
Miro©2. 
Miro 
enables 
online 
visual 
collaboration 
and 
can 
be 
used 
by 
multiple 
geographically 
distributed 
participants 
concurrently. 
It 
allows 
users 
to 
place 
content 
in 
the 
form 
of 
notes 
on 
virtual 
whiteboards. 
The 
workshop 
utilised 
Miro 
to 
provide 
a 
virtual 
whiteboard 
for 
framing 
and 
capturing 
responses. 
Ahead 
of 
the 
workshop, 
the 
facilitator 
established 
the 
required 
Miro 
boards, 
one 
for 
each 
continuum 
and 
one 
for 
each 
implementation 
step 
capture. 
A 
brief 
Miro 
training 
session 
for 
participants 
was 
held 
prior 
to 
the 
workshop 
to 
facilitate 
ease 
of 
use. 
Despite 
the 
sessions 
to 
familiarise 
participants 
with 
Miro, 
several 
users 
experienced 
problems 
that 
impacted 
the 
schedule 
of 
the 
workshop. 
At 
all 
workshops, 
additional 
facilitators 
engaged 
with 
participants 
who 
were 
experiencing 
challenges 
with 
the 
technology, 
and 
in 
most 
cases, 
they 
were 
able 
to 
include 
their 
responses 
manually. 


3.3 
Determining 
the 
technical 
innovation 
areas 
Each 
workshop 
was 
primed 
with 
a 
set 
of 
questions 
designed 
to 
identify 
technical 
innovation 
areas 
that 
could 
drive 
down 
the 
cost 
and 
increase 
the 
uptake 
of 
carbon 
sequestration 
technologies. 
A 
goal 
of 
priming 
the 
workshop 
was 
to 
help 
participants 
get 
to 
a 
common 
point 
where 
the 
workshop 
could 
proceed 
efficiently. 
This 
proved 
to 
be 
more 
difficult 
than 
expected, 
and 
each 
workshop 
took 
time 
to 
create/reach 
common 
ground. 


3.4 
Process 
The 
workshop 
process 
consisted 
of 
five 
steps. 


1. 
A 
pre-workshop 
online 
questionnaire 
and 
relevant 
chapters 
from 
the 
Climate 
Change 
Authority 
phase 
1 
report, 
Australia’s 
carbon 
sequestration 
potential 
(Fitch 
et 
al. 
2022), 
were 
emailed 
to 
all 
participants. 
2. 
The 
pre-workshop 
questionnaire 
responses 
were 
collated 
by 
the 
workshop 
technical 
lead 
to 
prepare 
the 
key 
focus 
areas 
for 
the 
workshop. 
3. 
Participants 
attended 
a 
facilitated 
online 
workshop, 
with 
input 
capture 
via 
a 
Miro 
board 
(as 
described 
in 
section 
3.2). 
There 
was 
a 
5-day 
period 
after 
the 
workshop 
to 
capture 
additional 
input 
from 
attendees 
or 
those 
unable 
to 
attend. 
4. 
Workshop 
outputs 
were 
analysed, 
forming 
this 
report. 
2 
https://miro.com 


24 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



3.5 
Outputs 
The 
primary 
output 
of 
the 
workshops 
is 
estimates 
of 
cost 
reduction 
enabled 
by 
specific 
technology 
innovations. 
A 
second 
output 
is 
a 
prioritised 
list 
of 
technology 
innovation 
areas 
for 
each 
sequestration 
approach. 


3.6 
Definitions 
The 
following 
continuum 
definitions 
were 
used 
during 
the 
workshop 
and 
in 
this 
report: 


 
Cost 
factor 
is 
defined 
as 
a 
sequestration 
cost 
reduction 
factor 
relative 
to 
current 
sequestration 
costs 
achieved 
through 
routine 
use 
of 
the 
technical 
innovation 
opportunity. 
 
Maturity 
is 
defined 
as 
the 
year 
when 
the 
technical 
innovation 
would 
be 
suitable 
for 
routine 
use 
(subject 
to 
appropriate 
investment). 
 
Scaling 
factor 
is 
defined 
as 
the 
multiplier 
increases 
in 
sequestration 
uptake 
if 
the 
technical 
innovation 
was 
routinely 
used. 
 
Investment 
is 
defined 
as 
the 
quantity 
of 
funds 
required 
to 
take 
the 
technical 
innovation 
to 
routine 
use. 
3.7 
Out 
of 
scope 
At 
the 
client’s 
request, 
these 
workshops 
were 
limited 
in 
scope 
to 
technology 
innovation 
areas 
where 
investment 
could 
lower 
costs 
and 
increase 
uptake. 
Consequently, 
policy 
and 
institutional 
barriers 
were 
out 
of 
scope. 


3.8 
Participants 
The 
participants 
for 
the 
workshops 
were 
from 
academia, 
government 
and 
Industry. 


3.9 
Schedule 
The 
workshop 
schedule 
is 
listed 
in 
Table 
3.1. 


Table 
3.1: 
Workshop 
schedule. 


TechnologyTechnologyleadWorkshopdateNotes
Planted 
vegetation 
Stephen 
28/10/2022 
This 
was 
the 
first 
workshop 
completed, 
and 
it 
was 
used 
to 
test 
the 
Roxburgh 


Delphi 
methodology. 


Blue 
carbon 
Andy 
Steven 
8/12/2022 
Cost 
reduction 
did 
not 
resonate 
with 
the 
participants; 
improvements 
to 
financial 
viability 
used 
instead 
of 
cost 
reduction 
factor. 
Direct 
air 
capture 
Paul 
Feron 
14/12/2022 
Savanna 
fire 
Michael 
N/A 
A 
review 
was 
agreed 
to 
instead 
of 
a 
workshop; 
the 
early/late 
season 
management 
Battaglia 
cut-off 
date 
and 
approaches 
to 
predicting 
fire 
severity 
were 
reviewed. 
Biomass/biochar 
Nawshad 
2/3/2023 
The 
broad 
scope 
made 
the 
workshop 
difficult, 
despite 
the 
Haque 
commonality 
with 
the 
biomass 
feedstock. 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
25 



Carbon 
capture 
and 
storage 
Charles 
Jenkins 
9/3/2023 
A 
broad 
workshop 
with 
diverse 
views 
and 
difficulty 
in 
reaching 
consensus. 
The 
workshop 
was 
hampered 
in 
some 
regards 
due 
to 
the 
limited 
breadth 
of 
experts 
able 
to 
be 
convened. 
Mineral 
carbonation 
Renee 
Birchall 
4/4/2023 
Final 
workshop. 
The 
workshop 
discussed 
the 
two 
types 
of 
carbonation 
(ex-situ 
and 
in-situ) 
separately. 


3.10 
Participant 
Review 
To 
ensure 
an 
opportunity 
for 
workshop 
participants 
to 
provide 
feedback 
on 
the 
workshop 
report, 
a 
web-based 
review 
form 
was 
developed. 
The 
review 
consisted 
of 
5 
questions 
and 
was 
emailed 
to 
each 
participant 
along 
with 
a 
copy 
of 
the 
draft 
chapter 
and 
report 
summary 
to 
solicit 
feedback. 
: 


1. 
Does 
the 
report 
broadly 
capture 
the 
discussion 
of 
the 
workshop? 
2. 
Do 
you 
feel 
a 
qualifying 
statement 
is 
required 
to 
ensure 
your 
perspective 
is 
represented? 
If 
so, 
what 
is 
it? 
3. 
Are 
you 
broadly 
comfortable 
with 
the 
methodology 
used 
to 
translate 
workshop 
outputs 
to 
estimates 
of 
cost 
reduction? 
4. 
Are 
you 
broadly 
comfortable 
with 
the 
summary 
of 
findings? 
5. 
Is 
there 
anything 
else 
that 
you 
think 
is 
important 
for 
readers 
to 
be 
aware 
of 
in 
reading 
this 
workshop 
report? 
Qualifying 
statements 
gathered 
as 
part 
of 
this 
review 
by 
workshop 
participants 
are 
detailed 
in 
Appendix 
D 


3.11References 


Fitch 
P, 
Battaglia 
M, 
Lenton 
A, 
Feron 
P, 
Gao 
L, 
Mei 
Y, 
Hortle 
A, 
Macdonald 
L, 
Pearce 
M, 
Occhipinti 
S, 
Roxburgh 
S, 
Steven 
A 
(2022) 
Australia’s 
carbon 
sequestration 
potential: 
a 
stocktake 
and 
analysis 
of 
sequestration 
technologies, 
CSIRO, 
Canberra. 


Helmer 
O 
(1967) 
Analysis 
of 
the 
future: 
the 
Delphi 
method, 
http://www.rand.org/content/dam/rand/pubs/papers/2008/P3558.pdf. 


26 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



4 
Scaling 
and 
maturity 
analysis 


This 
chapter 
details 
the 
trajectory 
modelling 
approach 
used 
for 
this 
project 
and 
will 
assist 
in 
interpreting 
the 
relative 
sequestration 
benefit 
tables 
presented 
in 
the 
subsequent 
chapters. 
The 
analysis 
allows 
for 
answers 
to 
two 
key 
questions: 


 
Is 
it 
better 
to 
have 
a 
larger 
scaling 
factor 
or 
an 
earlier 
technology 
maturity 
date? 
 
With 
technologies 
that 
have 
different 
maturity 
dates 
and 
scaling 
factors, 
which 
one 
will 
yield 
the 
greatest 
additional 
sequestration 
by 
2050? 
This 
question 
is 
answered 
using 
a 
relative 
sequestration 
benefit 
metric. 
Integrated 
assessment 
modelling, 
where 
a 
broad 
range 
of 
techno-economic 
considerations 
are 
included 
in 
the 
analysis, 
is 
the 
routine 
approach 
to 
providing 
defensible 
estimates. 
This 
form 
of 
modelling 
is 
out 
of 
scope 
for 
this 
project, 
and 
a 
simpler 
approach 
is 
used. 


Logistic 
models 
are 
widely 
used 
to 
produce 
an 
S-curve 
typically 
found 
in 
the 
uptake 
of 
innovations. 
They 
are 
a 
useful 
tool 
for 
modelling 
the 
diffusion 
of 
innovations, 
offering 
a 
simple, 
flexible 
and 
predictive 
approach 
for 
understanding 
the 
adoption 
of 
new 
products 
and 
technologies 
(Shimogawa 
et 
al. 
2012). 



Figure 
4-1: 
Example 
of 
an 
S-curve, 
representing 
adoption 
of 
a 
new 
technology/innovation. 


Figure 
4-1 
presents 
a 
typical 
S-curve, 
representing 
the 
slow 
early 
diffusion 
of 
an 
innovation, 
where 
an 
initial 
uptake 
is 
a 
small 
number 
of 
all 
the 
potential 
adopters. 
The 
adoption 
rate 
(dashed 
line 
in 
the 
figure) 
increases 
over 
time, 
leading 
to 
an 
inflection 
point 
where 
it 
starts 
to 
decrease 
as 
the 
number 
of 
adopters 
reaches 
saturation. 
This 
gradual 
uptake, 
followed 
by 
saturation, 
contributed 
to 
the 
wide 
use 
of 
the 
model. 


Here 
a 
basic 
logistic 
function 
(Equation 
2) 
that 
simulates 
an 
S-curve 
is 
used 
to 
compare 
scaling 
factors 
to 
maturity 
time 
frames. 
The 
logistic 
model 
nicely 
simulates 
the 
initial 
slow 
rate 
of 
change 
(adoption), 
and 
this 
accelerates 
as 
technological 
learning 
rates 
increase 
and 
widespread 
adoption 
occurs 
(Figure 
4-1). 
It 
is 
also 
important 
to 
recognise 
that 
for 
this 
modelling, 
the 
saturation 
point 
(maximum 
vertical 
asymptote) 
will 
be 
the 
scaling 
factor 
multiplied 
by 
the 
base 
rate. 


A 
baseline 
is 
created 
with 
a 
nominal 
annual 
growth 
to 
make 
comparative 
assessments, 
as 
shown 
in 
Equation 
1: 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
27 



𝑏𝑎𝑠𝑒𝑙𝑖𝑛𝑒(𝑡(𝑡) 
= 
1 
∗ 
(1 
+ 
𝑔𝑟𝑜𝑤𝑡ℎ 
𝑟𝑎𝑡𝑒)ç 
where 
𝑔𝑟𝑜𝑤𝑡ℎ 
𝑟𝑎𝑡𝑒 
= 
0.02 
(Eqn 
1) 


The 
growth 
rate 
is 
arbitrarily 
selected. 


The 
logistic 
model 
used 
is 
presented 
in 
Equation 
2, 
with 
c 
and 
b 
being 
fitted 
parameters. 


􀯕􀯔􀯦􀯘􀯟􀯜􀯡􀯘(􀬶􀬴􀬹􀬴)∗􀯦􀯖􀯔􀯟􀯘􀯙􀯔􀯖􀯧􀯢å 


sequestration(t) 
= 
(Eqn 
2)

􀵫􀬵􀬾􀯘(􀰷􀳎∗(􀳟􀰷􀳏)􀵯􀬾Õ 


4.1 
Possible 
uptake 
trajectories 
To 
understand 
how 
different 
maturity 
timeframes 
and 
different 
scaling 
factors 
can 
influence 
the 
uptake 
of 
a 
technology, 
two 
scaling 
factor 
scenarios 
and 
three 
maturity 
scenarios 
were 
defined. 
For 
these 
scenarios, 
the 
maturity 
timeframes 
used 
were 
2025, 
2030 
and 
2035, 
with 
the 
scaling 
factors 
being 
two 
times 
and 
three 
times 
the 
baseline 
values. 
The 
maturity 
timeframes 
were 
selected 
to 
cover 
most 
of 
the 
timeframes 
identified 
as 
part 
of 
the 
workshops. 
Similarly, 
the 
scaling 
factors 
considered 
are 
representative 
of 
the 
outputs 
from 
the 
initial 
planted 
vegetation 
workshop. 
In 
subsequent 
workshops, 
larger 
scaling 
factors 
were 
identified 
(6–10). 


For 
each 
scenario, 
the 
logistic 
model 
(S-curve) 
was 
fitted 
to 
three 
data 
points: 
the 
initial 
value, 
in 
this 
case 
1; 
a 
mid-point, 
being 
the 
maturity 
year 
with 
a 
sequestration 
estimate 
of 
the 
baseline 
sequestration 
multiplied 
by 
the 
scaling 
factor; 
and 
the 
end-point, 
being 
the 
baseline 
sequestration 
multiplied 
by 
the 
scaling 
factor. 
The 
mid-point 
was 
selected 
based 
on 
the 
rationale 
that 
on 
maturity 
the 
technology 
is 
routinely 
used 
and 
therefore 
delivers 
the 
scaling 
factor 
multiplied 
by 
the 
baseline 
increase 
of 
sequestration. 


01234562020202520302035204020452050Sequestratioin(Mtperyr)
Yearbaseline2%growthScalefactor2,maturity2025Scalefactor2,maturity2030Scalefactor2,maturity2035
28 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Figure 
4-2: 
Hypothetical 
increase 
of 
sequestration 
modelled 
by 
S-curve, 
based 
on 
uptake 
of 
technology 
innovation 
with 
a 
scaling 
factor 
of 
2, 
with 
maturity 
timeframes 
of 
2025, 
2030, 
and 
2035. 


6 


Sequestratioin 
(Mt 
per 
yr) 


5 
baseline 
2% 
growth 


4 


Scale 
factor 
3, 
maturity 
2025 


3 


Scale 
factor 
3, 
maturity 
2030 


2 


Scale 
factor 
3, 
maturity 
2035 


1 
0 


Year 


2020202520302035204020452050


Figure 
4-3: 
Hypothetical 
increase 
of 
sequestration 
modelled 
by 
S-curve, 
based 
on 
uptake 
of 
technology 
innovation 
with 
a 
scaling 
factor 
of 
3, 
with 
maturity 
timeframes 
of 
2025, 
2030, 
and 
2035. 


Figure 
4-2 
and 
Figure 
4-3 
present 
the 
results 
of 
the 
modelled 
sequestration 
generated 
by 
the 
uptake 
of 
technical 
innovation. 
Both 
sets 
of 
results 
commence 
with 
an 
initial 
sequestration 
of 
1 
Mt 
per 
year 
and 
yield 
a 
sequestration 
value 
in 
2050 
of 
baseline 
sequestration 
amount 
at 
2050 
multiplied 
by 
the 
scaling 
factor. 


The 
results 
illustrate 
that 
investment 
in 
technology 
that 
matures 
earlier, 
over 
a 
timeframe 
to 
2050, 
has 
a 
greater 
benefit 
(greater 
sequestration 
generated) 
than 
technology 
that 
matures 
later. 
This 
intuitive 
finding 
confirms 
that 
higher 
scaling 
with 
the 
earliest 
maturity 
has 
the 
highest 
benefit. 


Note 
that 
for 
maturities 
in 
2035, 
the 
modelled 
curve 
has 
not 
reached 
equilibrium 
by 
2050, 
so 
running 
the 
model 
to 
a 
later 
end 
date 
would 
possibly 
generate 
additional 
benefits. 


140 


Cumulative 
sequestratioin 
(Mt) 


120 
100 
80 
60 
40 
20 
0 



baseline 
2% 
growth 
Scale 
factor 
2, 
maturity 
2030 
Scale 
factor 
3, 
maturity 
2030 


2020 
2025 
2030 
2035 
2040 
2045 
2050 
Year 


Figure 
4-4:Hypothetical 
cumulative 
sequestration 
for 
the 
uptake 
of 
technical 
innovation 
for 
scaling 
factors 
of 
2 
and 
3, 
for 
maturity 
timeframes 
of 
2030. 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
29 



0204060801001201401602020202520302035204020452050Cumulativesequestratioin(Mt)
Yearbaseline2%growthScalefactor3,maturity2025Scalefactor3,maturity2030Scalefactor3,maturity20350204060801001201401602020202520302035204020452050Cumulativesequestratioin(Mt)
Yearbaseline2%growthScalefactor3,maturity2025Scalefactor3,maturity2030Scalefactor3,maturity2035
Figure 
4-5: 
Hypothetical 
cumulative 
sequestration 
for 
the 
uptake 
of 
technical 
innovation 
for 
maturity 
timeframes 
of 
2025, 
2030 
and 
2035, 
for 
a 
scaling 
factor 
of 
3. 


The 
cumulative 
sequestration 
modelling 
shows 
that 
the 
scaling 
factor 
has 
a 
larger 
impact 
on 
cumulative 
sequestration 
than 
maturity 
time 
for 
this 
analysis 
(Figure 
4-4 
and 
Figure 
4-5). 
A 
technical 
innovation 
with 
a 
maturity 
year 
of 
2030 
and 
a 
scaling 
factor 
of 
three 
would 
deliver 
an 
additional 
40Mt 
of 
sequestration 
by 
2050, 
compared 
to 
a 
scaling 
factor 
of 
2 
(Figure 
4-4Figure 
1-2). 
The 
earlier 
the 
maturity 
date, 
the 
more 
sequestration 
will 
be 
potentially 
delivered 
(Figure 
4-5). 


A 
clear 
benefit 
can 
be 
seen 
with 
a 
technical 
innovation 
that 
matures 
in 
2025, 
with 
the 
scaling 
factor 
of 
3 
yielding 
an 
additional 
100 
Mt 
of 
sequestration 
over 
28 
years 
relative 
to 
the 
baseline 
(Figure 
4-5). 


It 
is 
important 
to 
note 
that 
this 
analysis 
is 
purely 
illustrative, 
aiming 
to 
explore 
the 
interplay 
between 
investing 
in 
technology 
options 
with 
different 
scaling 
factors 
and 
maturity 
time 
frames. 
A 
technology 
that 
matures 
during 
2025–2030 
with 
a 
scaling 
factor 
of 
two 
has 
roughly 
the 
same 
benefit 
as 
a 
technology 
innovation 
that 
has 
a 
scaling 
factor 
of 
three 
but 
matures 
in 
2040. 
The 
actual 
uptake 
depends 
on 
a 
wide 
range 
of 
factors, 
including 
suitable 
economics, 
resolution 
of 
resource 
competition, 
suitable 
policy 
and 
institutional 
settings, 
and 
social 
license. 


4.2 
Relative 
sequestration 
benefit 
metric 
For 
the 
relative 
sequestration 
benefit 
analysis, 
the 
workshop 
outputs 
were 
used 
to 
calibrate 
a 
logistic 
model, 
producing 
sequestration 
estimates 
for 
2030, 
2035, 
2040 
and 
2050. 


The 
baseline 
was 
created 
by 
taking 
an 
arbitrary 
starting 
point 
(in 
this 
case, 
1 
Mt 
of 
sequestration 
per 
year) 
and 
applying 
a 
growth 
rate 
of 
2% 
per 
year. 


The 
values 
were 
normalised 
to 
the 
maximum 
sequestration 
obtained 
for 
year 
T. 
The 
equation 
for 
calculating 
the 
relative 
sequestration 
benefit 
is 
shown 
in 
Equation 
3, 
where 
T 
is 
the 
end 
year 
for 
cumulative 
sequestration 
(2025, 
2030, 
2035, 
2050), 
and 
S 
is 
sequestration 
calculated 
from 
the 
logistic 
model 
at 
time 
t, 
where 
t 
is 
the 
year 
between 
2022 
and 
T. 


􀯍

1 


𝑅𝑒𝑙𝑎𝑡𝑖𝑣𝑒 
𝑠𝑒𝑞𝑢𝑒𝑠𝑡𝑟𝑎𝑡𝑖𝑜𝑛 
𝑏𝑒𝑛𝑒𝑓𝑖𝑡 
= 
Í 
𝑆(𝑡) 
(Eqn 
3) 


max 
(𝑆(𝑇)) 
ç 


30 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



For 
each 
year 
of 
interest, 
the 
relative 
sequestration 
benefit 
for 
each 
technology 
will 
be 
between 
0 
and 
1. 
A 
technology 
with 
a 
value 
of 
1 
will 
potentially 
deliver 
the 
greatest 
additional 
sequestration 
by 
year 
T, 
and 
a 
technology 
with 
a 
value 
closest 
to 
0, 
the 
lowest 
additional 
sequestration. 


4.3 
References 
Shimogawa, 
S., 
Shinno, 
M., 
& 
Saito, 
H. 
(2012). 
Structure 
of 
S-shaped 
growth 
in 
innovation 
diffusion. 
Physical 
Review 
E, 
85(5), 
056121. 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
31 



Workshop 
outputs 


5 
Planted 
vegetation 
sequestration 


The 
planted 
vegetation 
workshop 
was 
held 
on 
28 
October 
2022 
with 
20 
participants. 
Appendix 
C, 
section 
C.1.1, 
includes 
a 
full 
list 
of 
workshop 
participants. 


5.1 
Workshop 
results 
5.1.1 
Technology 
list 
The 
first 
workshop 
output 
is 
a 
list 
of 
technology 
innovations 
that 
can 
lower 
the 
cost 
and 
increase 
the 
uptake 
rate 
of 
sequestering 
carbon 
with 
vegetation. 
The 
technology 
list 
was 
assembled 
from 
the 
responses 
given 
to 
the 
pre-workshop 
questionnaire 
and 
reviewed 
by 
the 
workshop 
technical 
lead. 


Table 
5.1 
presents 
and 
defines 
the 
technical 
innovation 
opportunities. 
Note 
that 
the 
specifics 
of 
the 
technical 
innovation 
area 
were 
not 
discussed 
or 
agreed 
to 
at 
the 
workshop 
and 
so 
the 
definitions 
are 
indicative. 


Table 
5.1: 
Technical 
innovation 
opportunities 
for 
carbon 
sequestration 
through 
planted 
vegetation. 


TechnicalinnovationareaDescriptionCostreductionarea
Low-cost 
imagery 
Remotely 
sensed 
imagery 
is 
used 
to 
locate 
suitable 
project 
Potential 
to 
reduce 


locations 
and 
ensure 
that 
the 
carbon 
project 
eligibility 
establishment 
and 
carbon 


requirements 
are 
met. 
In 
addition, 
imagery 
can 
be 
used 
as 
project 
costs. 


part 
of 
the 
verification 
and 
auditing 
of 
a 
vegetation 
project. 


Currently, 
costs 
for 
acquiring 
high-resolution 
imagery 
can 
be 


high 
and 
impact 
the 
transaction 
costs 
of 
the 
carbon 
project. 


Zero 
or 
low 
emission 
fuels 
Fuels 
contribute 
to 
project 
costs 
in 
two 
ways. 
Firstly, 
the 
Potential 
to 
reduce 
emissions 
from 
the 
fuels 
used 
to 
generate 
sequestration 
are 
establishment 
and 
deducted 
from 
the 
sequestration 
generated, 
making 
the 
operational 
costs. 
project 
less 
economically 
viable. 
Secondly, 
fuel 
adds 
costs 
to 
operations 
that 
require 
machinery, 
including 
harvest 
and 
transport 
to 
the 
mill. 
An 
ideal 
fuel 
is 
low 
or 
zero 
emission 
and 
low 
cost. 
Small-scale 
equipment 
for 
Reduced-cost 
small-scale 
equipment 
is 
becoming 
available 
Potential 
to 
reduce 
agroforestry 
applications 
more 
widely. 
The 
equipment 
includes 
small-scale 
all-terrain 
establishment 
and 
vehicles 
for 
operations, 
cranes 
and 
log 
forwarders. 
It 
has 
the 
operational 
costs. 
additional 
benefit 
of 
reducing 
environmental 
impacts 
during 
operations. 
Using 
lower-cost 
equipment 
has 
the 
potential 
to 
lower 
the 
operational 
costs 
for 
vegetation 
or 
forestry 
projects. 


Control 
of 
pests, 
diseases 
and 
Pests, 
diseases 
and 
browsing 
animals 
all 
have 
the 
potential 
to 
Potential 
to 
reduce 
browsing 
animals 
reduce 
vegetation 
growth 
and 
potentially 
increase 
mortality, 
establishment 
and 
especially 
when 
trees 
are 
young. 
Invasive 
weed 
and 
pest 
operational 
costs 
with 


32 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Decision 
support 
for 
informing 
optimal 
species 
selection 


management 
is 
also 
a 
requirement 
under 
state 
and 
federal 
legislation. 
Control 
typically 
involves 
mechanical 
and/or 
chemical 
application 
techniques. 
Improved 
and/or 
lower-cost 
methods 
for 
pest 
and 
disease 
control 
have 
the 
potential 
to 
both 
reduce 
establishment 
costs 
and 
improve 
overall 
biomass 
yield. 


Selecting 
the 
most 
appropriate 
species 
for 
a 
given 
location 
is 
a 
key 
decision, 
especially 
given 
the 
potential 
for 
the 
impacts 
of 
climate 
change 
to 
alter 
future 
growth 
conditions. 
The 
desired 
outcome 
of 
the 
planting 
is 
a 
key 
consideration 
influencing 
species 
selection. 
It 
might 
range 
from 
long-term 
restoration 
of 
a 
multi-species 
mixture 
of 
native 
or 
endemic 
species 
to 
the 
establishment 
of 
monocultures 
for 
timber 
and 
other 
plant 
products. 
Improved 
decision 
support 
for 
species 
selection 
has 
the 
potential 
to 
reduce 
operational 
costs 
and 
increase 
biomass 
yields. 


potential 
to 
also 
improve 
biomass 
yield. 


Potential 
to 
reduce 
operational 
costs 
and 
increase 
biomass 
yield. 


Lower-cost 
fencing 
Fencing 
can 
be 
a 
significant 
cost 
to 
planted 
vegetation 
Potential 
reduction 
of 
carbon 
sequestration 
projects 
that 
require 
the 
exclusion 
of 
establishment 
costs. 
non-domestic 
browsers 
and/or 
domestic 
livestock, 
or 
for 
defining 
and 
separating 
carbon 
farming 
activity 
from 
traditional 
production 
areas. 
Because 
fencing 
is 
an 
initial 
cost 
outlay, 
it 
can 
play 
a 
significant 
role 
in 
determining 
overall 
total 
costs 
when 
considered 
over 
the 
full 
lifetime 
of 
a 
project. 
Lower-cost 
fencing 
could 
include 
the 
development 
of 
new 
materials 
or 
methods 
for 
fence 
construction, 
which 
could 
also 
include 
virtual 
fencing. 
Reducing 
the 
costs 
of 
fencing 
contributes 
to 
reduced 
establishment 
costs. 
Genetic 
improvement 
Tree 
breeding 
for 
genetic 
improvement 
in 
commercial 
Potential 
to 
increase 
plantation 
species 
has 
a 
long 
and 
continuing 
history 
in 
establishment 
costs 
due 
to 
Australia, 
starting 
in 
the 
1950s 
with 
radiata 
pine 
and 
then 
added 
cost 
of 
genetically 
extending 
to 
include 
eucalypt 
tree 
improvement. 
Tree 
improved 
seedlings, 
with 
breeding 
is 
typically 
guided 
by 
economic 
considerations, 
potential 
improvements 
in 
focusing 
on 
traits 
such 
as 
improved 
disease 
resistance, 
wood 
biomass 
yield. 
density, 
seedling 
survivorship, 
and 
increased 
yields. 
Although 
the 
development 
of 
new 
genetic 
strains 
can 
incur 
additional 
costs 
through 
increased 
costs 
for 
seeds 
or 
seedlings, 
these 
additional 
costs 
are 
assumed 
to 
be 
overcome 
by 
improvements 
in 
performance 
and 
yield. 


New 
products 
for 
biomass 
residues 


Driverless 
or 
automated 
vehicles 


There 
is 
increasing 
interest 
in 
using 
forest 
biomass 
residues 
to 
develop 
new 
products, 
such 
as 
engineered 
wood 
products, 
biomaterials 
and 
biochemicals, 
which 
could 
displace 
plastics 
and 
other 
fossil 
fuel–based 
chemicals. 
The 
potential 
benefits 
include 
increased 
revenue 
through 
the 
development 
of 
these 
new 
products, 
product 
diversification 
and 
the 
displacement 
of 
non-renewable 
fossil 
fuel–based 
products 
with 
products 
based 
on 
renewable 
biomass. 


Robotic 
and 
autonomous 
machinery 
has 
the 
potential 
to 
play 
an 
important 
role 
in 
forest 
operations 
into 
the 
future, 
with 
potential 
technologies 
ranging 
from 
remote 
‘telecontrol’ 
of 
machinery 
for 
tree 
harvesting, 
transport 
and 
processing 
(for 
example, 
in 
remote 
or 
hazardous 
terrain) 
to 
autonomous 
vehicles 
for 
forestry 
operations 
and 
the 
use 
of 
drones/autonomous 
aircraft 
for 
broadscale 
seeding 
operations. 


Potential 
to 
improve 
prices 
paid 
for 
biomass. 


Potential 
to 
lower 
costs 
of 
establishment 
and 
operations. 


5.1.2 
Workshop 
outputs 
The 
most 
significant 
innovations 
were 
determined 
by 
voting 
to 
be: 


 
access 
to 
low-cost 
imagery 
for 
remote 
mapping 
and 
monitoring 
(9 
votes) 
 
zero 
or 
low 
emission 
fuels 
(6 
votes) 
Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
33 



 
control 
of 
pests, 
diseases 
and 
browsing 
animals 
(5 
votes) 
 
small-scale 
equipment 
for 
agroforestry 
(5 
votes). 
The 
other 
technologies 
either 
received 
3 
or 
4 
votes. 
The 
workshop 
continuum 
results 
are 
summarised 
in 
Table 
5.2. 
To 
help 
interpret 
the 
results, 
please 
see 
the 
definitions 
in 
section 
3.6. 


Table 
5.2: 
Summary 
of 
outputs 
from 
the 
planted 
vegetation 
workshop. 


TechnicalinnovationareaCostreduction(%)Maturity(Year)ScalingfactorAvgMinMaxAvgMinMaxAvgMinMaxLow-costimagery(n=11)2015282031202520344.12.75.8Zeroorlowemissionfuels(n=6)
2919422033203020353.124Small-scaleequipmentforagroforestry(n=6)
2112292035203220372.924.7Controlofpests,diseasesandbrowsinganimals(n=7)
2012332032202920364.62.76.5Decisionsupportforinformingoptimalspeciesselection(n=7)
2314292028202620313.02.33.9Lower-costfencing(n=3)104132034203420342.22.22.2Geneticimprovements(n=4)2710502031202720383.52.45.8Newproductsforbiomassresidue(n=3)
17639202920272032333Driverlessorautomatedvehicles(n=6)
2015282031202720353.31.94.2
All 
the 
average 
cost 
factors 
are 
in 
the 
order 
of 
10–30% 
with 
significant 
variation, 
despite 
the 
process 
of 
consensus 
building. 
For 
example, 
the 
cost 
reduction 
estimates 
for 
low-cost 
imagery 
vary 
from 
5 
to 
31% 
compared 
to 
current 
costs. 
Similarly, 
the 
estimates 
vary 
with 
maturity 
timeframes 
but 
are 
generally 
more 
consistent 
than 
the 
cost 
reduction 
factors. 
Most 
of 
the 
maturity 
estimates 
are 
in 
the 
order 
of 
10 
years, 
possibly 
reflecting 
an 
overly 
optimistic 
outlook 
by 
the 
participants. 


34 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Figure 
5-1: 
Plot 
of 
cost 
reduction 
percentages 
versus 
scaling 
factor 
for 
planted 
vegetation 
technical 
innovation 
areas. 


In 
Figure 
5-1, 
the 
cost 
reduction 
was 
plotted 
against 
the 
scaling 
factor. 
If 
the 
technology 
has 
a 
significant 
cost 
reduction 
factor, 
it 
would 
be 
reasonable 
to 
expect 
that 
the 
scaling 
factor 
would 
similarly 
be 
high. 
Conversely, 
if 
the 
cost 
reduction 
factor 
was 
relatively 
low, 
it 
would 
be 
reasonable 
to 
expect 
a 
low 
scaling 
factor. 
As 
shown 
in 
Figure 
5-1, 
the 
cost 
factors 
do 
follow 
this 
trend, 
with 
a 
few 
outliers 
(control 
of 
pests, 
diseases 
and 
browsing 
animals, 
low-cost 
imagery 
and 
lower-cost 
fencing). 


5.1.3 
Cost 
reduction 
analysis 
Planted 
vegetation 
sequestration 
cost 
areas 
or 
cost 
drivers 


The 
following 
cost 
and 
revenue 
categories 
were 
defined 
in 
preparation 
for 
the 
cost 
reduction 
modelling: 


 
Establishment: 
costs 
of 
establishing 
the 
technology 
at 
a 
location, 
excluding 
cost 
of 
land. 
 
Operations: 
ongoing 
maintenance 
costs, 
e.g. 
weeding, 
fertiliser 
application 
and 
operations 
including 
thinning, 
pruning 
and 
harvest. 
 
Carbon 
project 
costs: 
carbon 
offset 
project 
establishment, 
auditing 
and 
crediting 
costs. 
 
Yield: 
revenue 
obtained 
from 
biomass 
yield. 
 
Revenue: 
revenue 
obtained 
from 
biomass 
products. 
Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
35 



The 
workshop 
cost 
factors 
were 
assigned 
to 
the 
cost 
areas 
defined 
above 
and 
presented 
in 
Table 
5.3. 


Table 
5.3: 
Cost 
reduction 
factors 
for 
planted 
vegetation 
technical 
innovation 
areas. 
All 
factors 
are 
percentage 
reductions 
(costs) 
or 
increases 
(revenues) 
relative 
to 
current 
costs. 
Blank 
cells 
indicate 
no 
change 
to 
cost 
drivers. 


TechnicalinnovationareaCostsRevenuesEstablishment(%)
Operational(%)
Project(%)
Yield(%)Price(%)
Low-cost 
imagery 
22 
– 
22 
–– 
Zero 
or 
low 
emission 
fuels 
20 
20 
––– 


Small-scale 
equipment 
for 
29 
29 
––– 


agroforestry 
Control 
of 
pests, 
diseases 
and 
21 
21 
–10 
– 
browsing 
animals 


Decision 
support 
for 
informing 
– 
20 
–10 
– 
optimal 
species 
selection 
Lower-cost 
fencing 
23 
–––– 


Genetic 
improvements 
–10 
– 
–10 
– 


New 
products 
for 
biomass 
– 
– 
––27 
residue 


Driverless 
or 
automated 
17 
17 
––– 
vehicles 


Where 
the 
cost 
reduction 
factor 
can 
reduce 
several 
areas, 
it 
is 
applied 
to 
all 
applicable 
areas. 
For 
example, 
small-scale 
agroforestry 
equipment 
has 
the 
potential 
to 
lower 
both 
the 
establishment 
and 
operational 
costs 
of 
projects. 
Also 
note 
that 
for 
genetic 
improvements, 
the 
cost 
factor 
has 
been 
represented 
as 
a 
cost 
increase 
as 
well 
as 
a 
yield 
increase, 
anticipating 
that 
plantation 
stock 
costs 
could 
increase. 


Cost 
model 


The 
outputs 
from 
the 
vegetation 
workshop 
are 
translated 
into 
comparable 
results 
using 
a 
simplified 
cash 
flow 
model 
to 
determine 
changes 
to 
the 
net 
present 
value 
(NPV) 
and 
the 
cost 
per 
tonne 
of 
sequestration 
for 
an 
indicative 
commercial 
plantation 
or 
farm 
forestry 
(with 
product 
harvest) 
project. 
The 
model 
allows 
partitioning 
of 
costs, 
allowing 
cost 
reductions 
to 
be 
applied 
selectively 
to 
the 
relevant 
cost 
area 
and 
for 
the 
lifetime 
cost 
reductions 
(in 
this 
case, 
over 
100 
years) 
to 
be 
converted 
to 
NPVs. 
The 
cash 
flow 
model 
used 
for 
this 
analysis 
is 
based 
on 
Roxburgh 
et 
al. 
(2020), 
and 
more 
detail 
can 
be 
found 
there. 


The 
default 
parameters 
used 
for 
this 
analysis 
are 
shown 
in 
Table 
5.4, 
following 
Roxburgh 
et 
al. 
(2020). 
Note 
that 
water 
offset 
costs 
were 
not 
included 
in 
the 
analysis. 


Table 
5.4: 
Cost 
factors 
for 
planted 
vegetation 
projects. 


CostareaCostitemValue
Establishment 
Planting 
$1800 
per 
ha 
Fertiliser 
$400 
per 
ha 
Weeding 
$400 
per 
ha 
Windrow 
burn 
$400 
per 
ha 


36 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Chopper 
roller 
$400 
per 
ha 
Land 
Area 
specific 
$4000–$7000 
per 
ha 
Operation 
Distance 
to 
processing 
plant 
50 
km 


Haulage 
cost 
per 
km 
for 
1 
cubic 
metre 
$15.60 
wood 



Thinning 
$400 
per 
ha 


Pruning 
$400 
per 
ha 



Harvesting 
$400 
per 
ha 


The 
transaction 
costs 
associated 
with 
administering 
the 
carbon 
project 
were 
calculated 
as 
a 
fraction 
of 
the 
carbon 
project 
revenue. 
The 
annualised 
carbon 
project 
revenue 
was 
calculated 
from 
the 
FullCAM 
modelled 
abatement 
(tonnes 
CO2-e 
per 
ha) 
and 
multiplied 
by 
the 
project 
area. 
The 
carbon 
project 
costs 
are 
modelled 
to 
be 
a 
factor 
widely 
used 
of 
25% 
of 
the 
carbon 
sequestration 
revenue. 
Therefore, 
the 
cost 
reduction 
of 
carbon 
project 
costs 
is 
modelled 
as 
an 
increase 
in 
revenue 
rather 
than 
directly 
as 
a 
cost. 


Project 
costs 
are 
defined 
using 
Equation 
4: 


𝐶𝑜𝑠𝑡 
= 
𝑁𝑃𝑉(Σ􀯜.ç 
𝑐𝑜𝑠𝑡􀯜.􀯧) 
(Eqn 
4) 


where 
i 
is 
the 
cost 
area 
and 
t 
the 
project 
year. 
Future 
costs 
were 
calculated 
over 
a 
100-year 
timeframe. 
Cost 
per 
tonne 
of 
sequestration 
was 
calculated 
by 
calculating 
the 
total 
NPV 
cost 
of 
sequestration 
and 
dividing 
it 
by 
the 
total 
sequestration 
generated 
over 
the 
life 
of 
the 
project 
as 
per 
Equation 
5: 


𝐶𝑜𝑠𝑡 
𝑝𝑒𝑟 
𝑡𝑜𝑛𝑛𝑒 
= 
􀮼􀯢􀯦ç 
(Eqn 
5) 


Σß 
􀯌􀯘􀯤􀯨􀯘􀯦􀯧􀯥􀯔􀯧􀯜􀯢á 
ß 


Project 
NPV 
was 
calculated 
by 
determining 
the 
net 
cash 
flow 
(revenue 
– 
costs) 
and 
subtracting 
the 
carbon 
project 
costs, 
as 
shown 
in 
Equation 
6: 


𝑃𝑟𝑜𝑗𝑒𝑐𝑡 
𝑁𝑃𝑉 
= 
𝑁𝑃𝑉(𝑟𝑒𝑣𝑒𝑛𝑢𝑒) 
− 
𝑁𝑃𝑉(𝐶𝑜𝑠𝑡𝑠) 
− 
𝑁𝑃𝑉(𝐶𝑎𝑟𝑏𝑜𝑛 
𝑃𝑟𝑜𝑗𝑒𝑐𝑡 
𝐶𝑜𝑠𝑡𝑠) 
(Eqn 
6) 


For 
the 
analysis, 
a 
discount 
rate 
of 
7% 
was 
used, 
with 
a 
nominal 
carbon 
price 
of 
$20 
per 
tonne, 
a 
project 
size 
of 
100 
ha 
and 
a 
project 
duration 
of 
100 
years. 
Note 
that 
at 
the 
time 
of 
writing, 
the 
spot 
carbon 
price 
is 
$35.5 
per 
tonne. 
The 
sequestration 
yield 
data 
is 
from 
Roxburgh 
et 
al. 
(2020) 
and 
was 
generated 
using 
FullCAM 
for 
each 
National 
Plantation 
Inventory 
(NPI) 
plantation 
region, 
species 
type 
and 
management 
scenario. 
The 
model 
was 
initially 
run 
with 
no 
changes 
to 
costs 
to 
develop 
a 
baseline. 
This 
baseline 
was 
then 
used 
for 
the 
cost 
reduction 
analysis. 


Note, 
the 
cost 
reductions 
and 
changes 
to 
NPV 
are 
averages 
for 
all 
NPI 
regions, 
species 
and 
scenarios. 


Cost 
analysis 


The 
results 
of 
the 
modelling 
are 
listed 
in 
Table 
5.5. 
The 
cost 
reductions 
are 
the 
difference 
in 
cost 
in 
$ 
per 
tonne 
compared 
to 
the 
baseline. 


Table 
5.5: 
Cost 
reductions 
for 
planted 
vegetation 
technical 
innovation 
areas. 


TechnicalinnovationareaCostreductionfrombaseline($
pertonne)
Netcost($pertonne)
Baselinecost019.5
Low-cost 
imagery 
–2.8 
16.7 
Zero 
or 
low 
emission 
fuels 
–3.4 
16.1 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
37 



Small-scale 
equipment 
for 
–4.7 
14.8 
agroforestry 
Control 
of 
pests, 
diseases 
and 
–6.1 
13.4 
browsing 
animals 
Decision 
support 
for 
informing 
–3.9 
15.6 
optimal 
species 
selection 
Lower-cost 
fencing 
–2.9 
16.6 
Genetic 
improvements 
–1.8 
17.7 
New 
products 
for 
biomass 
residue 
0 
19.5 


The 
innovation 
area 
with 
the 
greatest 
potential 
to 
lower 
the 
cost 
of 
sequestration 
over 
the 
life 
of 
a 
project 
is 
better 
control 
of 
pests, 
diseases 
and 
browsing 
animals, 
which 
is 
discussed 
further 
in 
the 
following 
paragraph. 
Note 
that 
the 
cost 
reduction 
for 
new 
products 
for 
biomass 
is 
listed 
in 
Table 
5.5 
as 
0. 
This 
is 
due 
to 
the 
benefit 
being 
realised 
as 
increased 
revenue 
rather 
than 
a 
cost 
reduction, 
resulting 
in 
no 
change 
in 
costs. 



Figure 
5-2: 
Bar 
graph 
of 
cost 
reductions 
for 
planted 
vegetation 
technical 
innovation 
areas. 


The 
cost 
reductions 
are 
presented 
as 
a 
bar 
graph 
in 
Figure 
5-2. 
The 
largest 
cost 
reduction 
is 
control 
of 
pest 
and 
diseases 
at 
around 
$6 
per 
tonne 
less 
than 
the 
baseline 
of 
$19.50 
per 
tonne. 
This 
is 
due 
not 
only 
to 
a 
reduction 
of 
operational 
costs 
but 
also 
to 
the 
corresponding 
additional 
benefit 
in 
biomass 
yield. 
The 
model 
is 
sensitive 
to 
changes 
in 
biomass 
yield, 
as 
discussed 
in 
section 
5.1.5, 
and 
the 
result 
here 
is 
likely 
to 
reflect 
that. 
The 
next 
most 
beneficial 
technology 
is 
small-scale 
equipment 
for 
agroforestry, 
with 
a 
cost 
reduction 
of 
almost 
$5 
per 
tonne, 
followed 
by 
decision 
support 
for 
informing 
optimal 
species 
selection. 
In 
the 
case 
of 
decision 
support, 
this 
reduction 
is 
due 
to 
the 
assumed 
yield 
benefit 
corresponding 
to 
better 
species 
selection. 
Small-
scale 
equipment 
for 
agroforestry 
provides 
benefits 
to 
both 
operational 
and 
establishment 
cost 
areas. 
The 
least 
cost-effective 
technical 
innovation 
area 
is 
genetic 
improvements 
(apart 
from 
new 
products 
from 
biomass, 
which 
provides 
additional 
revenue 
rather 
than 
reducing 
costs). 
Genetic 
improvements 
were 
simply 
modelled, 
and 
the 
benefits 
of 
improved 
genetics 
can 
apply 
to 
several 
cost 
areas. 
A 
cost 
penalty 
was 
applied 
as 
part 
of 
the 
genetic 
improvement 
to 
represent 
the 
additional 
cost 
of 
improved 
tree 
stock. 


38 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



5.1.4 
Cost 
reduction, 
maturity 
and 
scale 
Figure 
5-3 
summarises 
the 
outputs 
of 
the 
workshop 
on 
one 
chart. 
The 
x-axis 
represents 
the 
year 
of 
maturity, 
the 
y-axis 
the 
cost 
reduction 
per 
tonne 
of 
CO2 
sequestration, 
and 
the 
size 
of 
the 
bubble 
represents 
the 
scaling 
factor. 



Figure 
5-3: 
Comparison 
of 
technology 
cost 
reduction, 
year 
of 
maturity 
and 
scaling 
factor 
for 
planted 
vegetation 
technical 
innovation 
areas. 
* 
Indicates 
the 
scaling 
factor. 


The 
best 
technologies 
are 
those 
that 
mature 
early, 
as 
they 
provide 
greater 
cumulative 
sequestration, 
have 
large 
cost 
reduction 
potential 
and 
have 
a 
large 
scaling 
factor. 
The 
control 
of 
pests, 
diseases 
and 
browsing 
animals 
and 
species 
decision 
support 
are 
the 
two 
technical 
innovation 
areas 
that 
have 
good 
cost 
reduction 
potential, 
early 
maturity 
and 
high 
scaling 
factors. 
Small-scale 
equipment 
for 
agroforestry 
has 
good 
cost 
reduction 
potential 
though 
a 
later 
maturity 
time 
and 
smaller 
scaling 
factor 
than 
control 
of 
pests, 
diseases 
and 
browsing 
animals 
and 
species 
decision 
support. 


5.1.5 
Sensitivity 
analysis 
of 
the 
cash 
flow 
model 
A 
sensitivity 
analysis 
can 
readily 
be 
done 
to 
explore 
which 
cost 
areas 
are 
more 
likely 
to 
change 
either 
the 
NPV 
or 
the 
cost 
of 
sequestration. 
NPV 
is 
important 
as 
it 
reflects 
changes 
to 
the 
economic 
viability 
of 
the 
sequestration 
approach, 
and 
in 
many 
cases, 
improvements 
in 
economic 
viability 
can 
unlock 
additional 
sequestration. 


In 
the 
analysis 
presented 
in 
Figure 
5-4, 
different 
cost 
parameters 
in 
the 
model 
were 
varied 
in 
four 
steps 
relative 
to 
the 
baseline: 
–10%, 
–5%, 
+5% 
and 
+10%. 
The 
changes 
to 
NPV 
as 
a 
percentage 
of 
the 
baseline 
are 
presented 
as 
a 
colour-coded 
heatmap. 
The 
purpose 
of 
this 
analysis 
is 
to 
identify 
those 
cost 
or 
revenue 
areas 
that, 
if 
changed, 
can 
significantly 
lower 
the 
cost 
of 
sequestration 
or 
change 
the 
economic 
viability 
of 
a 
project. 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
39 



Figure 
5-4: 
Sensitivity 
analysis 
of 
the 
cash 
flow 
model 
for 
planted 
vegetation 
carbon 
sequestration 
projects. 


Figure 
5-4 
presents 
the 
results 
of 
this 
analysis, 
in 
which 
changes 
to 
NPV 
are 
presented 
as 
a 
percentage 
change 
from 
the 
no-change 
baseline. 
The 
model 
is 
most 
sensitive 
to 
biomass 
revenue 
(price 
for 
products), 
followed 
by 
biomass 
yield. 
Land 
cost 
and 
project 
establishment 
are 
the 
next 
highest 
factors, 
followed 
by 
the 
carbon 
price. 
Any 
changes 
to 
these 
costs 
or 
revenues 
will 
significantly 
affect 
the 
economic 
viability 
of 
planted 
vegetation 
carbon 
sequestration 
projects. 
The 
carbon 
price 
has 
a 
smaller 
but 
still 
significant 
impact 
on 
economic 
viability. 
Reducing 
the 
project 
establishment 
cost 
is 
a 
significant 
opportunity, 
as 
the 
cost 
is 
accrued 
at 
the 
start 
of 
a 
project, 
which 
has 
greater 
impact 
on 
the 
overall 
economic 
viability, 
than 
costs 
incurred 
later 
in 
a 
project. 



Figure 
5-5: 
Sensitivity 
analysis 
of 
sequestration 
costs 
for 
planted 
vegetation 
carbon 
sequestration 
projects. 


Figure 
5-5 
presents 
a 
sensitivity 
analysis 
of 
cost 
areas. 
As 
with 
the 
NPV 
sensitivity 
analysis, 
biomass 
yield 
changes 
sequestration 
cost 
the 
most; 
therefore, 
any 
technologies 
that 
can 
increase 
biomass 
yield 
will 
have 
the 
greatest 
impact 
on 
cost 
reduction. 
This 
is 
followed 
by 
land 
cost, 
then 


40 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



by 
establishment 
costs. 
Reducing 
operational 
costs 
has 
the 
lowest 
impact 
on 
cost 
reduction. 
Zeros 
indicate 
that 
the 
factor 
has 
no 
impact 
on 
cost 
reduction. 


5.1.6 
Scaling 
and 
maturity 
analysis 
The 
results 
in 
Table 
5.6 
allow 
for 
the 
ranking 
of 
the 
technology 
innovation 
areas 
and 
present 
a 
relative 
measure 
of 
additional 
sequestration 
generated 
compared 
to 
the 
baseline. 
The 
results 
have 
been 
obtained 
per 
the 
relative 
sequestration 
benefit 
analysis 
described 
in 
section 
4.2. 


The 
baseline 
is 
created 
by 
taking 
an 
arbitrary 
starting 
point 
(in 
this 
case, 
1 
Mt 
per 
year 
of 
sequestration) 
and 
applying 
a 
growth 
rate 
of 
2% 
per 
year. 


Table 
5.6: 
Relative 
sequestration 
benefit 
of 
each 
planted 
vegetation 
technical 
innovation 
area. 


Technicalinnovationarea2030203520402050
Low-cost 
imagery 
0.8 
0.9 
0.9 
0.9 


Zero 
or 
low 
emission 
fuels 
0.4 
0.5 
0.5 
0.5 
Small-scale 
equipment 
for 
agroforestry 
0.3 
0.3 
0.4 
0.4 


Control 
of 
pests, 
diseases 
and 
browsing 
0.9 
animals 
Decision 
support 
for 
informing 
optimal 


1
0.9 
0.8 
0.7 


species 
selection 


Lower-cost 
fencing 
0.2 
0.3 
0.3 
0.3 
Genetic 
improvements 
0.8 
0.8 
0.8 
0.8 


New 
products 
for 
biomass 
residue 
0.9 
0.9 
0.8 
0.7 
Driverless 
or 
automated 
vehicles 
0.8 
0.8 
0.8 
0.7 


Control 
of 
pests, 
diseases 
and 
browsing 
animals 
has 
the 
highest 
relative 
sequestration 
benefit 
for 
2040 
and 
2050, 
with 
decision 
support 
for 
informing 
optimal 
species 
selection 
having 
the 
highest 
benefit 
in 
2030. 
The 
early 
maturing 
of 
control 
of 
pests, 
diseases 
and 
browsing 
animals 
(2029), 
with 
its 
high 
scaling 
factor 
(4.1), 
has 
the 
potential 
to 
provide 
additional 
sequestration 
by 
2050, 
as 
does 
decision 
support 
for 
species 
selection 
(maturing 
in 
2028). 
This 
is 
contrasted 
with 
lower-cost 
fencing, 
with 
a 
longer 
maturity 
timeframe 
(2034) 
and 
lower 
scaling 
factor 
(2), 
which 
delivers 
a 
lower 
relative 
benefit 
by 
2050. 


The 
results 
are 
to 
be 
expected 
as 
technical 
innovations 
that 
mature 
earlier 
and 
have 
larger 
scaling 
factors 
will 
deliver 
the 
largest 
additional 
sequestration 
relative 
to 
the 
baseline 
case. 


5.1.7 
Assumptions 
and 
limitations 
of 
the 
analysis 
The 
limitations 
and 
assumptions 
used 
in 
this 
analysis 
are 
described 
below. 


 
This 
analysis 
only 
used 
plantation 
forestry 
data 
for 
economic 
modelling. 
The 
costings 
will 
be 
different 
for 
different 
planted 
vegetation 
and 
farm 
forestry 
projects. 
 
The 
assessment 
used 
a 
single 
discount 
rate 
and 
project 
size. 
Discount 
rate 
variability 
and 
project 
size 
variability 
were 
not 
considered, 
but 
we 
note 
that 
the 
cost 
model 
is 
sensitive 
to 
both 
factors. 
 
The 
trajectory 
modelling 
is 
illustrative 
only 
and 
excludes 
a 
range 
of 
factors, 
including 
the 
actual 
current 
trajectory, 
resource 
competition 
and 
any 
social 
license 
constraints 
on 
the 
uptake. 
Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
41 



5.2 
Analysis 
of 
implementation 
steps 
The 
implementation 
steps 
in 
this 
section 
were 
obtained 
during 
the 
workshop 
by 
asking 
workshop 
participants 
to 
attempt 
to 
define 
the 
steps 
required 
to 
implement 
the 
technical 
innovation 
areas. 


A 
brief 
qualitative 
analysis 
of 
the 
workshop 
implementation 
steps 
is 
done 
below 
(the 
complete 
implementation 
step 
list 
is 
in 
Appendix 
A.1) 
to 
obtain 
an 
overall 
implementation 
complexity 
score 
used 
in 
the 
final 
ranking 
of 
technology 
areas 
in 
section 
5.3. 


5.2.1 
Low-cost 
imagery 
The 
use 
of 
remotely 
sensed 
imagery 
for 
vegetation 
sequestration 
projects 
falls 
into 
three 
areas: 
project 
site 
selection, 
site 
eligibility 
and 
monitoring/auditing 
of 
sequestration 
generation. 
For 
plantation 
forestry 
projects, 
site 
selection 
may 
not 
be 
a 
major 
issue 
with 
NPI 
regions 
and 
established 
plantation 
estates 
already 
defined. 
Extending 
the 
current 
plantation 
footprint 
and 
for 
farm 
forestry 
and 
permanent 
plantings, 
site 
eligibility 
could 
be 
more 
of 
an 
opportunity. 
Perhaps 
the 
greatest 
benefit 
of 
low-cost 
imagery 
would 
be 
in 
monitoring/auditing 
the 
generation 
of 
sequestration. 
What 
is 
unclear 
are 
the 
specific 
barriers 
to 
uptake, 
if 
the 
major 
barrier 
is 
cost, 
or 
if 
there 
are 
limitations 
with 
the 
resolution 
that 
higher 
resolution 
imagery 
(such 
as 
LIDAR) 
would 
overcome. 


The 
implementation 
steps 
captured 
in 
the 
workshop 
can 
be 
organised 
into 
five 
groups: 


 
improved 
calibration 
and 
validation 
 
better 
(higher 
resolution) 
imagery 
 
lower-cost 
imagery 
 
improved 
models 
(including 
AI) 
to 
convert 
imagery 
to 
indicators 
or 
parameters 
of 
interest 
 
tools 
to 
access 
and 
use 
imagery 
resources. 
The 
implementation 
complexity 
depends 
on 
what 
the 
solution 
is. 
Suppose 
the 
scope 
is 
reduced 
to 
utilising 
existing 
remote 
sensing 
data 
products 
(of 
which 
there 
are 
many 
with 
high 
resolution 
available). 
In 
that 
case, 
the 
implementation 
complexity 
is 
assessed 
as 
being 
low 
to 
medium. 


5.2.2 
Zero 
or 
low 
emission 
fuels 
Identifying 
zero 
or 
low 
emission 
fuels 
as 
an 
opportunity 
to 
lower 
costs 
and 
baseline 
emissions 
is 
no 
different 
from 
other 
sectors, 
such 
as 
mining. 
ARENA 
(2019) 
estimates 
the 
cost 
of 
developing 
the 
required 
infrastructure 
to 
produce 
biofuels 
in 
Australia 
to 
be 
$25 
to 
$30 
billion 
dollars. 
McKinsey 
and 
Company 
(2022) 
estimate 
the 
cost 
of 
building 
an 
electric 
vehicle 
network 
to 
support 
the 
expected 
growth 
in 
these 
vehicles 
to 
be 
$18 
billion 
for 
the 
infrastructure 
alone. 
Clearly, 
these 
costs 
are 
significant 
and 
are 
part 
of 
a 
broader 
economic 
transition 
to 
net 
zero. 
The 
benefit 
of 
low 
emission 
fuels 
is 
a 
reduction 
in 
emissions 
generated 
to 
produce 
sequestration, 
which 
in 
turn 
increases 
the 
sequestration 
generated. 


The 
implementation 
complexity 
is 
assessed 
as 
being 
high. 


5.2.3 
Small-scale 
equipment 
for 
agroforestry 
There 
is 
growing 
interest 
in 
small-scale 
forestry 
because 
of 
perceived 
environmental 
and 
economic 
benefits. 
Small-scale 
projects 
could 
be 
part 
of 
a 
broader 
portfolio 
of 
vegetation 


42 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



sequestration 
projects 
that 
contribute 
to 
the 
national 
pool 
of 
sequestration. 
Manufacturers 
such 
as 
SAMPO 
Rosenlew, 
Vimek 
and 
others 
are 
now 
manufacturing 
a 
range 
of 
small-scale 
equipment 
that 
can 
reduce 
the 
cost 
of 
planting, 
thinning 
and 
harvest 
processes 
for 
smaller-scale 
operations, 
improving 
economic 
viability. 
The 
barriers 
to 
this 
technology 
are 
tractable, 
as 
the 
equipment 
itself 
is 
readily 
available 
globally. 
The 
limitations 
to 
uptake 
relate 
to 
the 
cost-effectiveness 
of 
small-
scale 
projects. 


As 
the 
technology 
for 
small-scale 
agroforestry 
equipment 
exists, 
although 
the 
required 
capital 
investment 
is 
high, 
the 
implementation 
complexity 
is 
assessed 
as 
medium. 


5.2.4 
Control 
of 
pests, 
diseases 
and 
browsing 
animals 
Better 
control 
of 
pests, 
diseases 
and 
browsing 
animals 
is 
one 
of 
the 
technology 
areas 
with 
the 
best 
potential 
to 
lower 
sequestration 
costs. 
The 
implementation 
steps 
are 
relatively 
easy 
and 
low-
cost 
for 
fencing 
or 
stock 
exclusions, 
and 
technology 
for 
the 
implementation 
steps 
is 
readily 
available. 
Genetic 
improvements 
to 
plant 
stock 
(also 
covered 
in 
section 
5.2.7) 
are 
categorised 
as 
moderately 
difficult 
to 
implement. 


Overall, 
the 
implementation 
complexity 
is 
assessed 
as 
being 
low 
to 
high. 


5.2.5 
Decision 
support 
for 
informing 
optimal 
species 
selection 
Most 
of 
the 
implementation 
steps 
identified 
during 
the 
workshop 
for 
better 
decision 
support 
for 
informing 
optimal 
species 
selection 
are 
categorised 
as 
easy 
or 
very 
easy. 
This 
implies 
that 
the 
knowledge 
required 
for 
better 
decision 
support 
for 
species 
is 
readily 
available. 
Implementation 
complexity 
is 
assessed 
as 
medium. 


5.2.6 
Low-cost 
fencing 
For 
low 
cost 
fencing, 
only 
one 
implementation 
step 
was 
captured 
during 
the 
workshop. 
It 
appears 
that 
with 
this 
technology, 
the 
major 
challenge 
is 
developing 
pest-specific 
solutions 
that 
seem 
easy 
to 
implement. 
Thus, 
the 
implementation 
complexity 
is 
rated 
as 
low. 


5.2.7 
Genetic 
improvements 
Selective 
breeding 
and 
genetically 
improving 
tree 
stock 
is 
a 
well-established 
though 
time-
consuming 
process. 
Recent 
advances 
in 
genetic 
engineering 
and 
genomics 
have 
made 
it 
easier 
to 
manipulate 
genes 
that 
produce 
desirable 
traits 
such 
as 
increased 
growth 
rate, 
drought 
tolerance 
or 
disease 
resistance. 
However, 
due 
to 
the 
complex 
nature 
of 
tree 
genetics 
and 
the 
timeframes 
required 
to 
produce 
generations 
of 
trees, 
it 
can 
take 
decades 
to 
produce 
new 
varieties. 
The 
implementation 
complexity 
is 
therefore 
rated 
as 
high. 


5.2.8 
New 
products 
for 
biomass 
residue 
A 
recent 
study 
has 
identified 
many 
new 
innovative 
products 
that 
can 
be 
produced 
from 
biomass 
residue 
and 
more 
generally, 
(Hassegawa 
et 
al. 
2022). 
These 
include 
wood 
foam, 
glycols, 
bioplastics, 
lignin-based 
adhesives 
and 
composite 
wood 
products. 
The 
implementation 
steps 
vary 
in 
difficulty 
from 
very 
easy 
to 
somewhat 
hard. 
Several 
steps 
relate 
to 
the 
challenges 
of 
scaling, 
though 
it 
is 
unclear 
what 
technical 
innovation 
is 
required 
to 
lower 
costs. 
Overall, 
the 
implementation 
complexity 
of 
this 
technology 
area 
is 
rated 
as 
medium. 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
43 



5.2.9 
Driverless 
and 
automated 
machinery 
Driverless 
vehicles 
are 
already 
available 
in 
some 
industries, 
including 
agriculture, 
with 
driverless 
trucks 
being 
tested 
on 
the 
road. 
Despite 
the 
rapid 
progress 
towards 
autonomous 
operation, 
there 
are 
still 
challenges 
in 
achieving 
full 
autonomy. 
The 
availability 
and 
uptake 
of 
driverless 
machinery 
will 
ultimately 
depend 
on 
regulatory 
approval, 
resolution 
of 
technical 
challenges 
(e.g. 
working 
on 
forest 
terrain) 
and 
public 
acceptance. 
The 
implementation 
steps 
collected 
during 
the 
workshop 
relate 
to 
cost, 
public 
acceptance 
and 
technical 
capabilities. 
As 
there 
are 
still 
outstanding 
technical 
challenges 
and 
challenges 
to 
bring 
the 
cost 
of 
this 
technology 
down, 
the 
implementation 
complexity 
is 
rated 
as 
high. 


5.3 
Ranking 
The 
workshop 
results 
and 
modelled 
outputs 
are 
ranked 
in 
Table 
5.7. 
The 
ranking 
was 
achieved 
by 
normalising 
the 
outputs 
(cost 
reduction, 
scaling 
and 
maturity 
relative 
benefit, 
and 
implementation 
complexity) 
into 
a 
figure 
between 
zero 
and 
one, 
summing 
and 
then 
ranking 
the 
technologies 
based 
on 
the 
total 
sum. 
Implementation 
complexity 
was 
translated 
into 
a 
numerical 
value, 
with 
low 
being 
assigned 
1 
and 
high 
0.2. 
Where 
a 
range 
of 
complexities 
was 
given, 
the 
highest 
complexity 
was 
taken 
(e.g. 
low 
to 
medium 
was 
taken 
as 
medium 
with 
a 
numerical 
value 
of 
0.6). 
The 
rankings 
are 
grouped 
into 
three 
priority 
groups 
to 
indicate 
the 
most 
prospective 
group 
of 
technologies. 
Note 
that 
in 
the 
final 
rankings, 
control 
of 
pest 
and 
diseases 
was 
relegated 
from 
priority 
1 
to 
priority 
2, 
as 
although 
the 
benefit 
was 
high, 
specifics 
on 
how 
this 
was 
to 
be 
achieved 
were 
not 
well 
identified 
during 
the 
workshop. 


Table 
5.7: 
Ranking 
of 
technical 
innovation 
areas 
for 
planted 
vegetation 
carbon 
sequestration. 


TechnicalinnovationareaCostreduction($pertonne)
ScalingandmaturityrelativebenefitImplementationcomplexityPrioritygroup
Low-cost 
imagery 
–2.8 
0.9 
Low–medium 
1 


Decision 
support 
for 
informing 
optimal 
–3.9 
0.7 
Medium 
1 
species 
selection 
Small-scale 
equipment 
for 
agroforestry 
–4.7 
0.4 
Medium 
1 


Lower-cost 
fencing 
–2.9 
0.3 
Low 
1 


Control 
of 
pests, 
diseases 
and 
browsing 
–6.1 
1.0 
Low–high 
2 
animals 


Genetic 
improvements 
–1.8 
0.8 
High 
2 
New 
products 
for 
biomass 
residue 
0 
0.7 
Medium 


2 


Zero 
or 
low 
emission 
fuels 
–3.4 
0.5 
High 
3 
Driverless 
or 
automated 
vehicles 
–3 
0.7 
High 


3 


5.4 
Discussion 
For 
reference, 
the 
baseline 
cost 
($19.50 
per 
tonne) 
determined 
in 
this 
analysis 
compares 
well 
to 
the 
figures 
reported 
in 
Fitch 
et 
al. 
(2022) 
of 
$20–$30 
per 
tonne 
for 
permanent 
plantings 
and 
$10– 
$30 
per 
tonne 
for 
plantation 
and 
farm 
forestry. 


44 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



All 
technologies 
looked 
at 
have 
benefits 
in 
reducing 
the 
cost 
of 
sequestration 
and 
increasing 
uptake, 
with 
cost 
reductions 
ranging 
from 
$4.7 
to 
$2.8 
per 
tonne. 
As 
noted 
above, 
improved 
control 
of 
pest 
and 
disease 
(without 
identifying 
how 
this 
was 
to 
be 
done), 
investment 
in 
small-
scale 
equipment 
for 
agroforestry 
and 
decision 
support 
for 
optimal 
species 
selection 
potentially 
have 
the 
most 
significant 
cost 
reductions. 
When 
we 
include 
the 
scaling 
and 
maturity 
analysis, 
the 
picture 
is 
a 
little 
different; 
however, 
investment 
in 
better 
control 
of 
pests, 
diseases 
and 
browsing 
animals 
was 
still 
the 
most 
beneficial 
opportunity. 
From 
a 
scaling 
perspective, 
low-cost 
imagery 
(due 
to 
its 
early 
maturity 
date) 
and 
genetic 
improvement 
rate 
highly. 


This 
is 
at 
odds 
with 
the 
economic 
analysis, 
in 
which 
low-cost 
imagery 
and 
genetic 
improvement 
do 
not 
yield 
as 
much 
cost 
reduction, 
at 
$2.8 
and 
$1.8 
per 
tonne, 
respectively. 
This 
difference 
is 
likely 
due 
to 
the 
optimistic 
outlook 
by 
the 
participants 
on 
the 
relative 
benefits 
of 
the 
technologies 
and 
their 
potential 
scaling 
factors, 
which 
are 
not 
borne 
out 
in 
the 
economic 
analysis. 


Zero 
or 
low 
emission 
fuels 
and 
driverless 
or 
autonomous 
vehicles 
are 
options 
that 
have 
a 
moderate 
ability 
to 
lower 
costs, 
but 
the 
maturity 
times 
are 
likely 
optimistic. 
This 
is 
particularly 
true 
for 
driverless 
or 
autonomous 
vehicles, 
with 
significant 
technical 
and 
legislative 
challenges. 


The 
workshop 
participants 
assembled 
the 
implementation 
list, 
and 
although 
the 
list 
was 
reviewed, 
it 
did 
not 
have 
sufficient 
review 
or 
harmonisation 
for 
a 
consensus 
to 
be 
formed. 
The 
implementation 
steps 
captured 
provide 
a 
first 
cut 
on 
what 
could 
be 
involved 
in 
implementing 
the 
technology 
areas. 
A 
more 
comprehensive 
review 
of 
the 
technology 
area 
status, 
including 
barriers, 
options 
and 
costs, 
is 
required 
to 
turn 
these 
into 
an 
action 
plan. 


In 
some 
technologies, 
the 
implementation 
steps 
are 
straightforward 
and 
require 
no 
additional 
investment 
(e.g. 
control 
of 
pests 
and 
disease 
with 
the 
use 
of 
fencing), 
whereas 
others, 
such 
as 
those 
for 
genetic 
improvement 
and 
autonomous 
vehicles, 
are 
far 
more 
complex. 


Overall, 
the 
technologies 
that 
have 
the 
highest 
likelihood 
of 
reducing 
cost 
and 
increasing 
carbon 
sequestration 
through 
planted 
vegetation 
are: 


 
low-cost 
imagery 
 
decision 
support 
for 
informing 
optimal 
species 
selection 
 
small-scale 
equipment 
for 
agroforestry 
 
lower-cost 
fencing. 
5.5 
References 
ARENA 
(2019) 
Biofuels 
and 
transport: 
an 
Australian 
opportunity, 
https://arena.gov.au/assets/2019/11/biofuels-andtransport-
an-australian-opportunity.pdf. 


Fitch 
P, 
Battaglia 
M, 
Lenton 
A, 
Feron 
P, 
Gao 
L, 
Mei 
Y, 
Hortle 
A, 
Macdonald 
L, 
Pearce 
M, 
Occhipinti 
S, 
Roxburgh 
S, 
Steven 


A 
(2022) 
Australia’s 
carbon 
sequestration 
potential: 
a 
stocktake 
and 
analysis 
of 
sequestration 
technologies, 


CSIRO, 
Canberra. 


McKinsey 
and 
Company 
(2022) 
Sydney 
2022: 
Scaling 
EV 
infrastructure 
to 
meet 
net-zero 
targets, 


https://www.mckinsey.com/capabilities/operations/our-insights/global-infrastructure


initiative/roundtables/sydney-2022-scaling-ev-infrastructure-to-meet-net-zero-targets. 


Hassegawa 
M, 
Karlberg 
A, 
Hertzberg 
M, 
Verkerk 
PJ 
(2022) 
Innovative 
forest 
products 
in 
the 
circular 
bioeconomy 
[version 
2; 
peer 
review: 
2 
approved]. 
Open 
Research 
Europe, 
2:19. 
doi:10.12688/openreseurope.14413.2. 


Roxburgh 
SH, 
England 
JR, 
Evans 
D, 
Nolan 
M, 
Opie 
K, 
Paul 
KI, 
Reeson 
A, 
Cook 
G, 
Thomas 
D 
(2020) 
Potential 
future 
supply 
of 
carbon 
offsets 
in 
the 
land 
sector 
in 
Australia, 
CSIRO, 
Canberra. 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
45 



6 
Blue 
carbon 


This 
chapter 
details 
the 
results 
and 
analysis 
of 
the 
blue 
carbon 
workshop. 
The 
workshop 
aimed 
to 
explore 
how 
technical 
innovation 
can 
lower 
the 
cost 
of 
blue 
(coastal) 
carbon 
sequestration 
and 
correspondingly 
increase 
the 
uptake 
of 
this 
sequestration 
approach 
in 
Australia. 
Specifically, 
the 
workshop 
considers 
the 
sequestration 
that 
could 
be 
achieved 
in 
coastal 
areas 
(mangroves 
and 
saltmarsh) 
by 
reintroducing 
tidal 
flows 
to 
previously 
drained 
or 
ponded 
coastal 
areas. 
This 
is 
the 
only 
approved 
eligible 
activity 
under 
the 
methodology 
determination 
of 
the 
Australian 
carbon 
credit 
unit 
(ACCU) 
scheme. 


The 
workshop 
was 
held 
on 
8 
December 
2022 
with 
eight 
participants, 
using 
the 
workshop 
methodology 
detailed 
in 
Chapter 
3. 
Appendix 
C, 
section 
C.1.2, 
includes 
a 
list 
of 
workshop 
participants. 
The 
cost 
reduction 
results 
are 
presented 
with 
a 
brief 
commentary 
on 
the 
implementation 
steps 
developed, 
with 
details 
of 
those 
steps 
listed 
in 
Appendix 
A.1. 


6.1 
Workshop 
results 
6.1.1 
Technology 
list 
Table 
6.1 
presents 
the 
technical 
innovation 
opportunities 
collated 
for 
the 
workshop 
and 
a 
brief 
definition 
of 
the 
opportunity 
for 
cost 
reduction. 
Note 
that 
the 
specifics 
of 
the 
technical 
innovation 
areas 
were 
not 
discussed 
or 
agreed 
to 
at 
the 
workshop 
and 
so 
are 
indicative 
of 
the 
technology 
innovation 
discussed. 


Table 
6.1: 
Technical 
innovation 
opportunities 
for 
carbon 
sequestration 
through 
blue 
carbon. 


TechnicalinnovationareaDescriptionCostreductionarea
Earth 
observation 
technologies 
for 
national 
assessment 


National 
models 
for 
tidal 
introduction 
and 
feasibility 
assessment 


Remotely 
sensed 
imagery 
is 
used 
to 
locate 
suitable 
project 
locations 
and 
ensure 
that 
the 
carbon 
project 
eligibility 
requirements 
are 
met. 
In 
addition, 
imagery 
can 
be 
used 
as 
part 
of 
the 
verification 
and 
auditing 
of 
a 
blue 
carbon 
project. 
Currently, 
costs 
for 
acquiring 
high-resolution 
imagery 
can 
be 
high 
and 
impact 
the 
establishment 
and 
transaction 
costs 
of 
the 
carbon 
project. 


A 
nationally 
consistent 
model 
to 
estimate 
the 
likely 
extent 
and 
frequency 
of 
inundation 
of 
coastal 
areas 
under 
highest 
astronomical 
tide 
conditions 
and 
to 
account 
for 
projected 
sea-level 
rise. 
The 
model 
would 
identify 
coastal 
areas 


Potential 
to 
reduce 
establishment 
and 
carbon 
project 
costs. 


Potential 
to 
identify 
coastal 
areas 
suitable 
for 
inundation 
and 
thus 
reduce 
project 
establishment 
costs 
under 
the 
ACCU 
scheme 
tidal 
method. 


46 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Standardised 
hydrological 
modelling 
tool 
that 
project 
proponents 
can 
implement 
to 
identify 
risks 
and 
future 
abatement 


suitable 
for 
tidal 
reintroduction 
and 
available 
to 
project 
proponents. 
Current 
hydrological 
assessments 
are 
inconsistent 
and 
cost 
prohibitive. 


Similar 
in 
purpose 
to 
a 
national 
hydrological 
model 
but 
focused 
on 
making 
publicly 
available 
a 
toolkit 
for 
undertaking 
a 
standardised 
project-level 
hydrological 
assessment 
as 
a 
requirement 
of 
ACCU 
scheme 
accreditation. 


Potential 
to 
identify 
coastal 
areas 
that 
could 
be 
suitable 
for 
inundation 
and 
reduce 
project 
establishment 
costs 
under 
the 
ACCU 
scheme 
tidal 
method. 


Earth 
observation 
technologies 
for 
restoration 
site 
identification 
and 
assessment 


Methods 
and 
indices 
for 
measuring 
other 
benefits 


Remotely 
sensed 
imagery 
is 
used 
to 
locate 
suitable 
project 
locations 
and 
ensure 
the 
carbon 
project 
eligibility 
requirements 
are 
met. 
Currently, 
costs 
for 
acquiring 
high-resolution 
imagery 
can 
be 
high 
and 
impact 
the 
transaction 
costs 
of 
the 
carbon 
project. 


The 
development 
of 
appropriate 
methods 
for 
quantifying 
other 
ecosystem 
benefits 
derived 
from 
blue 
carbon 
habitat, 
including 
coastal 
protection, 
water 
quality 
improvement, 
fisheries 
enhancement 
and 
biodiversity 
benefits. 
There 
is 
great 
interest 
in 
developing 
high-value 
environmental 
credits 
that 
recognise 
the 
broader 
suite 
of 
services 
provided 
by 
blue 
carbon 
habitats 
(besides 
carbon) 
and 
account 
for 
these 
services 
in 
national 
ecosystem 
accounting 
processes. 


Potential 
to 
reduce 
establishment 
and 
carbon 
project 
costs. 


Potential 
to 
support 
participation 
in 
national 
and 
international 
crediting 
systems. 
These 
methods 
would 
assist 
in 
achieving 
a 
higher 
carbon 
price 
by 
valuing 
other 
non-market 
ecosystem 
services 
for 
inclusion 
in 
Environmental 
and 
Economic 
Accounts 
(EEA) 
processes 
and 
reporting 
obligations. 


AI 
and 
improved 
data 
management 
of 
monitoring, 
reporting 
and 
verification 


National 
model 
of 
sea 
level 
rise 
impacts 
on 
coasts 


Access 
to 
publicly 
accessible, 
relevant 
Potential 
to 
reduce 
establishment 
and 
timely 
inventory 
and 
project 
blue 
and 
carbon 
project 
costs. 
carbon 
data 
would 
streamline 
reporting, 
assessment 
approvals 
and 
verification 
processes. 
Access 
to 
publicly 
accessible, 
relevant 
Potential 
to 
reduce 
establishment 
and 
timely 
inventory 
and 
project 
blue 
and 
carbon 
project 
costs. 
carbon 
data 
would 
streamline 
reporting, 
assessment 
approvals 
and 
verification 
processes. 


Methane 
satellites 
for 
Methane 
measurement 
is 
a 
gap, 
but 
Not 
described. 
knowledge 
of 
potential 
avoided 
using 
satellites 
is 
out 
of 
scope. 
emissions 
from 
land-uses 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
47 



6.1.2 
Workshop 
outputs 
The 
most 
significant 
innovations 
were 
determined 
by 
voting 
to 
be: 


 
methods 
and 
indices 
for 
measuring 
other 
benefits 
(11 
votes) 
 
national 
model 
for 
tidal 
introduction 
and 
feasibility 
assessment 
(9 
votes, 
2 
more 
for 
a 
standardised 
hydrological 
model) 
 
earth 
observation 
technologies 
for 
restoration 
site 
identification 
and 
assessment 
(3 
votes 
+ 
1 
for 
earth 
observation 
for 
national 
assessments). 
The 
other 
technologies 
received 
3 
votes. 


As 
in 
the 
other 
workshops, 
each 
technical 
innovation 
area 
was 
investigated 
by 
workshop 
participants 
for 
its 
cost 
reduction 
and 
scaling 
potential. 
These 
results 
are 
summarised 
in 
Table 
6.2, 
with 
copies 
of 
the 
Miro 
board 
outputs 
in 
Appendix 
A, 
section 
A.1.2. 
To 
help 
interpret 
the 
results, 
please 
see 
the 
definitions 
in 
section 
3.4. 


Table 
6.2: 
Summary 
of 
outputs 
from 
the 
blue 
carbon 
workshop. 


TechnicalinnovationareaEconomicviabilityimprovement(%)
Maturity(Year)ScalingfactorAvgMinMaxAvgMinMaxAvgMinMaxMethodsandindicesformeasuringotherbenefits(n=6)
5825902029202720312.211.73Nationalmodelfortidalintroductionandfeasibilityassessment(n=7)
4619772029202720302.762.53.1Earthobservationtechnologiesforrestorationsiteidentificationandassessment(n=4)
1910302027202520291.91.72.2
There 
was 
a 
wide 
range 
of 
opinions 
regarding 
improvements 
to 
economic 
viability 
for 
both 
methods 
and 
indices 
for 
measuring 
other 
benefits 
and 
the 
development 
of 
a 
national 
model 
for 
tidal 
introduction 
and 
feasibility 
assessment. 
Overall, 
developing 
methods 
and 
indices 
for 
measuring 
other 
benefits 
was 
seen 
to 
have 
the 
greatest 
potential 
economic 
viability 
improvement, 
followed 
by 
the 
national 
model 
for 
tidal 
introduction 
and 
feasibility 
assessments. 
New 
methods 
and 
indices 
for 
measuring 
other 
benefits 
would 
include 
a 
broader 
set 
of 
values 
(economic 
and 
environmental) 
alongside 
the 
carbon 
sequestration 
benefit, 
thereby 
increasing 
demand 
for 
blue 
carbon, 
with 
additional 
revenue 
reflecting 
payment 
for 
those 
environmental 
services. 


The 
workshop 
participants 
agreed 
that 
focusing 
on 
cost 
reduction 
was 
inappropriate 
for 
blue 
carbon 
sequestration, 
and 
improved 
economic 
viability 
was 
the 
critical 
issue. 
In 
response, 
the 
workshop 
convenors 
reframed 
the 
cost 
reduction 
question 
around 
economic 
viability. 
Changes 
to 
economic 
viability 
gathered 
in 
the 
workshop 
were 
converted 
to 
a 
proportional 
cost 
reduction 
using 
the 
method 
described 
in 
the 
next 
section. 


Conversion 
of 
improved 
economic 
viability 
to 
cost 
reductions 


The 
approach 
to 
converting 
improvement 
in 
economic 
viability 
to 
percentage 
cost 
reduction 
is 
as 
follows: 


48 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



 
Economic 
viability 
is 
defined 
as 
NPV; 
therefore, 
an 
improvement 
in 
economic 
viability 
of 
x, 
translates 
to 
an 
improvement 
in 
NPV 
of 
NPV(1 
+ 
x). 
 
The 
corresponding 
cost 
reduction 
y 
was 
determined 
numerically 
by 
adjusting 
the 
NPV 
and 
determining 
the 
corresponding 
cost 
reduction 
that 
generated 
that 
change. 
Conversion 
of 
improved 
economic 
viability 
to 
revenue 
increase 


As 
with 
the 
conversion 
of 
improved 
economic 
viability 
to 
cost 
reductions, 
a 
conversion 
was 
required 
to 
convert 
changes 
in 
economic 
viability 
into 
an 
increase 
or 
decrease 
in 
revenues. 
The 
technical 
innovation 
area 
generating 
additional 
revenue 
in 
this 
way 
was 
methods 
and 
indices 
for 
measuring 
other 
benefits. 


A 
similar 
approach 
to 
converting 
economic 
viability 
to 
cost 
reduction 
was 
used 
to 
convert 
economic 
viability 
to 
increases 
in 
project 
revenue. 


The 
calculated 
cost 
reductions 
for 
improvements 
in 
economic 
viability 
are 
listed 
in 
Table 
6.3. 


Exploratory 
data 
analysis 


Economic 
viability 
versus 
scale 
factor 


Scale 
factor 
increase 
in 
uptake 
(avg) 


3 
2.5 
2 
1.5 
1 
0.5 
0 



tidal 
inNational 
model 
for 
troduction 
and 
assfeasibility 
essment 
Methods 
and 
indices 
for 
Earth 
obtechnolservation 
ogies 
for 
measuring 
other 
benefits 
restoraidentifiction 
site 
ation 
and 
assessment 


10 
20 
30 
40 
50 
60 
Improvement 
in 
economic 
viability 
(avg) 


Figure 
6-1: 
Plot 
of 
average 
cost 
reduction 
percentages 
versus 
scaling 
factor 
for 
blue 
carbon 
technical 
innovation 
areas. 


Cost 
reduction 
estimates 
were 
plotted 
against 
the 
scaling 
factors 
to 
explore 
the 
consistency 
of 
the 
workshop 
outputs. 
If 
the 
technology 
has 
a 
significant 
cost 
reduction 
factor, 
it 
would 
be 
reasonable 
to 
expect 
that 
the 
scaling 
factor 
would 
similarly 
be 
high. 
Conversely, 
expecting 
a 
low 
scaling 
factor 
would 
be 
reasonable 
if 
the 
cost 
reduction 
factor 
was 
relatively 
low. 


The 
lack 
of 
a 
relationship 
between 
the 
scaling 
factor 
and 
cost 
reduction 
is 
likely 
an 
artefact 
of 
the 
workshop 
and 
is 
a 
signal 
to 
interpret 
the 
results 
with 
care. 
This 
result 
could 
be 
due 
to 
insufficient 
time 
to 
reach 
a 
consensus 
or 
the 
lack 
of 
a 
consensus 
process 
to 
compare 
scaling 
factors 
to 
cost 
reduction. 
The 
weak 
trend 
line 
is 
plotted 
in 
Figure 
6-1, 
reflecting 
relatively 
poor 
consistency 
between 
improvements 
in 
economic 
viability 
and 
scaling 
potential. 


6.1.3 
Cost 
reduction 
analysis 
Blue 
carbon 
sequestration 
cost 
areas 
or 
cost 
drivers 


The 
following 
cost 
and 
revenue 
categories 
were 
defined 
in 
preparation 
for 
the 
cost 
modelling: 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
49 



 
Establishment: 
project 
start-up 
costs 
include 
planning 
feasibility, 
engineering 
assessment 
and 
hydrological 
modelling, 
site 
and 
regulatory 
approvals, 
application 
to 
the 
clean 
energy 
regulator, 
project 
management 
for 
the 
first 
2 
years, 
and 
environmental 
impact 
consultation; 
project 
maintenance 
costs 
include 
pest 
and 
animal 
control 
and 
other 
on-ground 
engineering 
maintenance 
as 
required. 
 
Operations: 
ongoing 
maintenance 
costs 
for 
years 
1 
to 
5 
inclusive. 
Yield: 
revenue 
obtained 
from 
sequestration 
generated. 


The 
workshop 
cost 
factors 
were 
then 
assigned 
to 
the 
cost 
areas 
defined 
above 
and 
presented 
in 
Table 
6.3. 


Table 
6.3: 
Cost 
reduction 
factors 
for 
blue 
carbon 
technical 
innovation 
areas. 
All 
factors 
are 
percentage 
reductions 
(costs) 
or 
increases 
(revenues) 
relative 
to 
current 
costs. 


TechnicalinnovationareaChangeinNPVCostreduction(%)
CostsRevenueEstablishment(%)
Operational(%)
Methods 
and 
indices 
for 
measuring 
other 
benefits 
0.58 
– 
– 
– 
5.6 
multiplier 
of 
revenue 
National 
model 
for 
tidal 
introduction 
and 
feasibility 
assessment 
0.46 
41 
29 
12 
– 


Earth 
observation 
technologies 
for 
0.18 
17 
12 
5 
– 
restoration 
site 
identification 
and 
assessment 


Cost 
model 


A 
simplified 
cash 
flow 
model 
translates 
the 
outputs 
from 
the 
blue 
carbon 
workshop 
into 
changes 
to 
NPV 
(economic 
viability) 
and 
reductions 
to 
the 
cost 
per 
tonne 
of 
sequestration 
for 
a 
project. 
The 
model 
allows 
partitioning 
of 
costs, 
allowing 
cost 
reductions 
to 
be 
applied 
selectively 
to 
the 
relevant 
cost 
areas 
and 
for 
lifetime 
cost 
reductions 
(in 
this 
case, 
over 
25 
years) 
to 
be 
converted 
to 
changes 
in 
NPVs. 


The 
following 
default 
parameters 
were 
used 
for 
this 
analysis, 
following 
Hagger 
et 
al. 
(2022) 
, 
for 
a 
25-year 
project 
lifetime. 


Table 
6.4: 
Cost 
factors 
for 
blue 
carbon 
projects. 


CostareaCostitemValue
Establishment 
This 
includes 
project 
start-up 
costs 
$8159 
per 
ha. 
including 
ACCU 
scheme 
recognition, 
state 
and 
local 
government 
site 
approvals 
(e.g. 
for 
removal 
and 
placement 
of 
hydrological 
structures) 
and 
feasibility 
assessment 
(e.g. 
hydrological 
modelling). 
Removal 
of 
hydrological 
structure 
could 
sit 
in 
either 
establishment 
cost 
area 
or 
operational 
costs 
or 
be 
rolled 
in 
together. 


50 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Maintenance 
The 
cost 
incurred 
for 
the 
first 
5 
years 
$750 
per 
ha 
per 
annum 
for 
the 
first 
5 
after 
establishment. 
years 
after 
establishment 
(Waltham 
et 
al. 
2021). 


In 
Table 
6.4, 
project 
establishment 
or 
start-up 
costs 
are 
defined 
and 
listed 
in 
cost 
areas, 
with 
the 
transaction 
costs 
associated 
with 
administering 
the 
carbon 
project 
are 
included 
in 
establishment 
costs. 


The 
annualised 
carbon 
project 
revenue 
was 
calculated 
from 
the 
BlueCAM 
modelled 
abatement 
(tonnes 
CO2e 
per 
ha) 
and 
multiplied 
by 
the 
project 
area. 


The 
cost 
per 
tonne 
of 
sequestration 
was 
determined 
by 
calculating 
the 
total 
NPV 
cost 
of 
sequestration 
and 
dividing 
it 
by 
the 
total 
sequestration 
generated 
over 
the 
life 
of 
the 
project 
as 
per 
Equation 
7. 


𝐶𝑜𝑠𝑡 
𝑝𝑒𝑟 
𝑡𝑜𝑛𝑛𝑒 
= 
􀮼􀯢􀯦ç 
(Eqn 
7) 


Σß 
􀯌􀯘􀯤􀯨􀯘􀯦􀯧􀯥􀯔􀯧􀯜􀯢á 
ß 


Project 
NPV 
was 
calculated 
by 
determining 
the 
net 
cash 
flow 
(revenue 
– 
costs) 
and 
subtracting 
the 
carbon 
project 
costs, 
as 
shown 
in 
Equation 
8: 


𝑃𝑟𝑜𝑗𝑒𝑐𝑡 
𝑁𝑃𝑉 
= 
𝑁𝑃𝑉(𝑟𝑒𝑣𝑒𝑛𝑢𝑒) 
− 
𝑁𝑃𝑉(𝐶𝑜𝑠𝑡𝑠) 
− 
𝑁𝑃𝑉(𝐶𝑎𝑟𝑏𝑜𝑛 
𝑃𝑟𝑜𝑗𝑒𝑐𝑡 
𝐶𝑜𝑠𝑡𝑠) 
(Eqn 
8) 


For 
the 
analysis, 
a 
discount 
rate 
of 
7% 
was 
used, 
with 
a 
nominal 
carbon 
price 
of 
$20 
per 
tonne 
of 
carbon 
and 
a 
project 
size 
of 
200 
ha 
with 
a 
project 
duration 
of 
25 
years. 
Note 
that 
at 
the 
time 
of 
writing, 
the 
spot 
carbon 
price 
is 
$35.5 
per 
tonne. 


Modelled 
sequestration 


The 
generation 
of 
cost 
per 
tonne 
estimates 
requires 
estimates 
of 
sequestration 
quantities 
for 
typical 
blue 
carbon 
projects. 


The 
Blue 
Carbon 
Accounting 
Model 
(Clean 
Energy 
Regulator, 
2022) 
has 
been 
developed 
to 
support 
the 
blue 
carbon 
method 
(Clean 
Energy 
Regulator, 
2022). 
BlueCAM 
is 
used 
to 
calculate 
the 
net 
carbon 
abatement 
from 
the 
soil 
and 
vegetation 
sequestration 
and 
emissions 
avoidance 
components 
of 
a 
project. 


For 
blue 
carbon 
projects, 
the 
project 
activity 
will 
be 
to 
introduce 
tidal 
flow, 
resulting 
in 
the 
rewetting 
of 
previously 
completely 
or 
partially 
drained 
coastal 
wetland 
ecosystems. 
This 
could 
involve 
removing 
or 
modifying 
part 
or 
all 
of 
a 
sea 
wall, 
bund, 
drain 
or 
other 
type 
of 
tidal 
flow 
restriction 
device, 
such 
as 
a 
tidal 
gate. 


For 
this 
analysis, 
four 
representative 
scenarios 
were 
used, 
one 
for 
each 
of 
the 
four 
expected 
blue 
carbon 
project 
climate 
zones. 
The 
scenarios 
are 
described 
in 
Table 
6.5. 
In 
the 
scenarios, 
earthworks 
were 
estimated 
as 
10% 
of 
the 
project 
area. 


Table 
6.5: 
BlueCAM 
scenario 
modelling 
results. 


ScenarioProjectsize(ha)
InitiallanduseFinallanduseNetsequestration(tonnes)
Annualsequestration(tonnesperhaperyear)
Tropical 
monsoon 
200 
Grazing 
Mangrove 
15366.6 
3.1 


Temperate 
200 
Cropping 
Mangrove 
27991.5 
5.6 
Tropical 
humid 
200 
Sugarcane 
Mangrove 
39034.3 
7.8 


Subtropical 
200 
Cropping 
Mangrove 
24041.0 
4.8 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
51 



The 
sequestration 
yield 
estimates 
from 
the 
scenarios 
were 
averaged, 
and 
an 
amount 
of 
5.3 
tonnes 
per 
ha 
per 
year 
was 
used 
to 
calculate 
cost 
reductions 
from 
the 
changes 
in 
economic 
viability. 
For 
more 
detail 
on 
the 
scenarios 
used, 
see 
assumptions 
and 
limitations 
in 
section 
6.1.7 
. 


The 
model 
was 
initially 
run 
with 
no 
changes 
to 
costs 
to 
develop 
a 
baseline. 
This 
baseline 
was 
then 
used 
for 
the 
cost 
reduction 
analysis. 


Cost 
analysis 


The 
results 
of 
the 
modelling 
are 
listed 
in 
Table 
6.6. 
The 
model 
determined 
the 
baseline 
cost 
as 
$92 
per 
tonne 
with 
a 
carbon 
price 
of 
$20 
per 
tonne 
and 
a 
discount 
rate 
of 
7%. 
The 
cost 
reductions 
are 
the 
difference 
in 
cost 
in 
$ 
per 
tonne 
compared 
to 
the 
baseline. 


Table 
6.6: 
Cost 
reductions 
for 
blue 
carbon 
technical 
innovation 
areas. 


TechnicalinnovationareaCostreductionfrombaseline($pertonne)
Netcost($pertonne)
Baselinecost092
Methods 
and 
indices 
for 
measuring 
other 
benefits 
0 
92 
National 
model 
for 
tidal 
introduction 
and 


–39 
53 


feasibility 
assessment 


Earth 
observation 
technologies 
for 
restoration 
site 


–18 
74 


identification 
and 
assessment 


In 
Table 
6.6 
and 
Figure 
6-2, 
developing 
a 
national 
model 
for 
tidal 
introduction 
and 
feasibility 
assessment 
is 
shown 
to 
have 
the 
most 
significant 
potential 
to 
lower 
the 
cost 
of 
sequestration 
(– 
$39 
per 
tonne) 
for 
the 
technical 
innovation 
areas 
assessed, 
followed 
by 
earth 
observation 
technologies 
(–$18 
per 
tonne). 
Methods 
and 
indices 
for 
measuring 
other 
benefits 
does 
not 
impact 
the 
cost 
of 
sequestration. 



Figure 
6-2: 
Bar 
graph 
of 
cost 
reductions 
for 
blue 
carbon 
technical 
innovation 
areas. 


6.1.4 
Cost 
reduction, 
maturity 
and 
scale 
Figure 
6-3 
summarises 
the 
outputs 
of 
the 
workshop 
on 
one 
chart. 
The 
x-axis 
represents 
the 
year 
of 
maturity, 
the 
y-axis 
the 
cost 
reduction 
per 
tonne 
of 
CO2 
sequestration, 
and 
the 
bubble 
size 


52 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



represents 
the 
scaling 
factor. 
The 
larger 
the 
circle, 
the 
lower 
on 
the 
chart 
and 
closest 
to 
the 
left-
hand 
axis, 
the 
greater 
the 
potential 
for 
cost 
reduction 
and 
scaling. 



Figure 
6-3: 
Comparison 
of 
technology 
cost 
reduction, 
year 
of 
maturity 
and 
scaling 
factor 
for 
blue 
carbon 
technical 
innovation 
areas. 
* 
Indicates 
the 
scaling 
factor. 


6.1.5 
Sensitivity 
analysis 
of 
cashflow 
model 
With 
a 
cashflow 
model, 
a 
sensitivity 
analysis 
can 
readily 
be 
performed 
to 
explore 
which 
cost 
areas 
more 
likely 
to 
change 
the 
NPV 
(economic 
viability) 
or 
the 
cost 
of 
sequestration. 
The 
economic 
viability 
of 
blue 
carbon 
projects 
is 
currently 
challenging, 
and 
technical 
innovations 
that 
lower 
the 
establishment 
or 
start-up 
costs 
have 
significant 
potential 
to 
reduce 
costs, 
improving 
the 
project’s 
economic 
viability, 
thus 
unlocking 
additional 
sequestration. 
The 
sensitivity 
analysis 
presented 
in 
Figure 
6-4 
identifies 
those 
cost 
areas 
with 
the 
greatest 
potential 
to 
improve 
the 
economic 
viability 
of 
blue 
carbon 
projects. 


In 
the 
analysis 
presented 
in 
Figure 
6-4, 
different 
model 
cost 
parameters 
were 
varied 
in 
four 
steps 
relative 
to 
the 
baseline: 
–10%, 
–5%, 
+5% 
and 
+10%. 
The 
changes 
to 
NPV 
as 
a 
percentage 
of 
the 
baseline 
are 
presented 
as 
a 
colour-coded 
heatmap. 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
53 



Figure 
6-4: 
Sensitivity 
analysis 
of 
the 
cash 
flow 
model 
for 
blue 
carbon 
sequestration 
projects. 


As 
shown 
in 
Figure 
6-4, 
establishment 
costs 
have 
the 
most 
significant 
impact 
on 
economic 
viability. 
The 
magnitude 
of 
the 
investment 
required 
is 
one 
reason 
for 
that 
impact, 
and 
the 
other 
reason 
is 
the 
timing 
of 
those 
costs 
being 
right 
at 
the 
beginning 
of 
a 
project. 



Figure 
6-5: 
Sensitivity 
analysis 
of 
sequestration 
costs 
for 
blue 
carbon 
sequestration 
projects. 


Additional 
revenue 
from 
environmental 
services 
or 
enhanced 
carbon 
pricing 
has 
no 
impact 
on 
the 
cost 
of 
sequestration. 
The 
insight 
here 
is 
that 
any 
technology 
innovation 
that 
can 
lower 
establishment 
costs 
will 
have 
the 
most 
significant 
potential 
to 
reduce 
the 
cost 
of 
blue 
carbon 
sequestration. 


54 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



6.1.6 
Scaling 
and 
maturity 
analysis 
The 
results 
in 
Table 
6.7 
allow 
for 
the 
ranking 
of 
the 
technology 
innovation 
areas 
and 
present 
a 
relative 
measure 
of 
additional 
sequestration 
generated 
compared 
to 
the 
baseline. 
The 
results 
were 
obtained 
using 
a 
calibrated 
logistic 
model 
(as 
described 
in 
Chapter 
4) 
using 
the 
scaling 
factors 
and 
maturity 
dates 
developed 
as 
part 
of 
the 
workshop 
(listed 
in 
6.1.2) 
and 
are 
colour 
coded 
to 
form 
a 
heatmap, 
with 
lower 
values 
lighter 
and 
higher 
values 
dark 
blue 
(higher 
is 
a 
larger 
benefit). 


The 
baseline 
was 
created 
by 
taking 
an 
arbitrary 
starting 
point 
(in 
this 
case, 
1 
Mt 
of 
sequestration 
per 
year) 
and 
applying 
a 
growth 
rate 
of 
2% 
per 
year. 


In 
2050, 
the 
greatest 
potential 
sequestration 
generated 
is 
for 
the 
national 
model 
for 
tidal 
introduction 
and 
feasibility 
assessment 
(value 
of 
1 
is 
the 
highest 
and 
the 
best), 
and 
the 
other 
technology 
options 
are 
scaled 
relative 
to 
that. 
Earth 
observation 
technologies 
for 
restoration 
site 
identification 
and 
assessment 
would 
generate 
0.6 
times 
as 
much 
additional 
sequestration 
by 
2050 
compared 
to 
the 
national 
hydrodynamic 
model. 


Table 
6.7: 
Relative 
sequestration 
benefit 
of 
each 
blue 
carbon 
technical 
innovation 
area. 


Technicalinnovationarea2030203520402050
Methods 
and 
indices 
for 
0.6 
0.6 
0.6 
0.7 
measuring 
other 
benefits 


National 
model 
for 
tidal 
introduction 
and 
feasibility 
assessment 
1 
1 
1 
1 
Earth 
observation 
technologies 
for 
restoration 
site 
identification 
and 
0.7 
0.7 
0.6 
0.6 
assessment 


6.1.7 
Assumptions 
and 
limitations 
of 
the 
analysis 
In 
undertaking 
these 
assessments, 
the 
following 
limitations 
and 
assumptions 
were 
made: 


 
Blue 
carbon 
habitats: 
only 
mangroves 
were 
considered; 
other 
blue 
and 
teal 
carbon 
habitats 
were 
not 
included. 
 
Sequestration 
methods: 
only 
the 
‘tidal 
reintroduction’ 
method 
was 
considered 
here; 
the 
tidal 
reintroduction 
method 
relies 
on 
the 
removal 
of 
barriers 
that 
have 
restricted 
natural 
tidal 
ingress 
to 
naturally 
re-establish 
blue 
carbon 
habitats, 
mainly 
mangrove 
and 
saltmarsh. 
 
BlueCAM 
model: 
as 
part 
of 
the 
tidal 
restoration 
method 
(Clean 
Energy 
Regulator, 
2022), 
an 
Excel-based 
model, 
BlueCAM, 
has 
been 
developed 
to 
assist 
proponents 
with 
calculating 
potential 
sequestration.3 
3 
BlueCAM 
can 
be 
found 
at: 
https://www.cleanenergyregulator.gov.au/DocumentAssets/Pages/The-blue-carbon-accounting-model-
BlueCAM.aspx. 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
55 



Project 
costs 


Establishment 
costs 
($ 
per 
ha). 
In 
this 
analysis, 
establishment 
costs 
of 
$8589 
were 
assumed, 
based 
on 
recent 
analyses 
by 
Hagger 
et 
al. 
(2022b). 
This 
analysis 
considered 
an 
earlier 
study 
(Bayraktarov 
et 
al. 
2016) 
of 
restoration 
costs, 
adapting 
the 
lower 
range 
of 
costs 
derived 
for 
saltmarsh 
on 
the 
assumption 
that 
hydrological 
restoration 
involves 
mainly 
earthworks 
for 
modification 
of 
drains/bunds 
and 
not 
costly 
active 
(i.e. 
replanting) 
restoration 
methods. 
Establishment 
costs 
available 
from 
two 
current 
tidal 
restoration 
projects 
(Blue 
Heart, 
Queensland 
and 
Dry 
River, 
South 
Australia) 
confirmed 
these 
costs. 


The 
costs 
considered 
under 
establishment 
costs 
include 
project 
approval 
and 
site 
remediation 
costs. 


An 
economy 
of 
scale 
factor 
to 
account 
for 
project 
size 
of 
20 
ha 
was 
assumed. 
It 
was 
based 
on 
a 
study 
of 
terrestrial 
restoration 
projects 
that 
demonstrated 
a 
non-linear 
cost 
reduction 
in 
restoration, 
particularly 
for 
projects 
over 
50 
ha 
in 
size 
(Strassburg 
et 
al. 
2019.) 


Maintenance 
costs 
($ 
per 
ha). 
Given 
that 
natural 
recovery 
requires 
minimal 
maintenance, 
maintenance 
costs 
of 
$750 
per 
ha 
per 
year 
were 
applied 
for 
the 
first 
five 
years 
of 
the 
project 
(Waltham 
et 
al. 
2021). 


Discount 
rate. 
Typically 
discount 
rates 
between 
5–10% 
are 
used; 
in 
this 
case 
a 
7% 
discount 
rate 
was 
applied. 


Technology 
costs 
reductions 


Cost 
of 
high-resolution 
imagery. 
The 
average 
cost 
of 
acquiring 
high-resolution 
(<5 
m) 
commercially 
available 
satellite 
data 
(e.g. 
Geo-eye, 
Planet, 
World 
View, 
Ikonos, 
Pleiades) 
was 
US$22 
(AU$33) 
per 
km2 
or 
$0.33 
per 
ha. 
Most 
of 
the 
satellite 
data 
have 
minimum 
order 
quantities 
(typically 
25 
to 
50 
km2) 
and 
the 
cost 
varies 
with 
the 
spatial 
resolution 
of 
the 
satellite 
image. 


Cost 
of 
hydrological 
modelling. 
It 
is 
a 
requirement 
under 
the 
ACCU 
scheme 
to 
undertake 
a 
hydrological/hydrodynamic 
assessment 
of 
project 
sites. 
Commercial 
companies 
undertake 
these 
assessments, 
which 
cost 
between 
$15,000 
and 
$35,000 
depending 
on 
the 
size 
of 
the 
project. 
This 
is 
a 
considerable 
up-front 
cost 
and 
a 
significant 
proportion 
of 
establishment 
costs. 
For 
this 
analysis, 
a 
cost 
of 
$15,000 
for 
a 
100-ha 
project 
site 
was 
assumed 
and 
scaled 
at 
$2,000 
per 
100 
ha. 
Thus, 
providing 
a 
public-use 
national 
modelling 
capability 
was 
assumed 
to 
significantly 
reduce 
these 
up-front 
costs. 
Implementing 
the 
model 
is 
likely 
to 
cost 
$3–5 
million 
over 
3 
years, 
with 
an 
ongoing 
operational 
sustainment 
requirement. 


Viability 
of 
co-benefits. 
Beyond 
carbon 
sequestration 
potential, 
there 
are 
a 
number 
of 
recognised 
co-benefits 
that 
blue 
carbon 
habitats 
provide, 
including 
biodiversity, 
fisheries, 
water 
quality 
improvement, 
coastal 
protection 
and 
myriad 
cultural 
and 
material 
benefits 
to 
customary 
landowners. 
The 
quantification 
and 
potential 
commodification 
of 
co-benefits, 
such 
as 
bundling 
them 
with 
carbon 
abatement, 
has 
been 
recently 
evaluated 
and 
could 
add 
a 
premium 
of 
30% 
compared 
to 
projects 
with 
lower 
co-benefits 
(Lou 
et 
al. 
2022). 
The 
caveat 
with 
the 
analysis 
is 
that 
the 
volume 
of 
credits 
produced 
must 
also 
be 
considered. 
While 
a 
project 
cost 
is 
associated 
with 
quantifying 
and 
verifying 
these 
co-benefits, 
the 
principal 
effect 
on 
project 
viability 
is 
the 
greater 
price 
yield. 


Scenarios 
summary. 
Baseline 
scenarios 
were 
estimated 
using 
the 
BlueCAM 
model 
for 
an 
assumed 
20-ha 
project 
size 
in 
each 
of 
the 
main 
bioregions, 
assuming 
the 
initial 
land 
uses, 
vegetation 
type 
and 
tidal 
conditions 
shown 
in 
Table 
6.8. 
While 
projects 
nearly 
always 
comprise 
multiple 
CEAs, 
for 
this 
analysis, 
only 
a 
single 
CEA 
was 
used 
with 
the 
dominant 
land 
use. 


56 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Table 
6.8: 
Summary 
of 
BlueCAM 
modelled 
scenarios 


ScenarioProjectsize(ha)
InitiallanduseFinallanduseTidalrange(HAT,mAHD)
Netabatement(tonnes)
Annualsequestration(tonnesperhaperyear)
Tropical 
monsoon 
200 
Grazing 
Mangrove 
8 
(4, 
0.05) 
15366.6 


3.1 


Tropical 
humid 
200 
Sugarcane 
Mangrove 
3 
(1.5, 
0.1) 
39034.3 


7.8 


Temperate 
200 
Cropping 
Mangrove 
2.4 
(1.4, 
0.1) 
27991.5 


5.6 


Subtropical 
200 
Cropping 
Mangrove 
0.7 
(0.4, 
0) 
24041.0 
4.8 


HAT, 
highest 
astronomical 
tide; 
mAHD, 
metres 
above 
Australian 
Height 
Datum, 


6.2 
Analysis 
of 
implementation 
steps 
6.2.1 
Methods 
and 
indices 
for 
measuring 
other 
benefits 
The 
implementation 
steps 
collated 
during 
the 
workshop 
for 
methods 
and 
indices 
for 
measuring 
other 
benefits, 
such 
as 
environmental 
services, 
are 
brief. 
Determining 
and 
valuing 
non-carbon 
benefits 
is 
viewed 
as 
a 
market-based 
approach 
to 
achieving 
additional 
revenue; 
however, 
methods 
and 
indices 
are 
only 
one 
part 
of 
establishing 
a 
market 
for 
these 
benefits. 
There 
are 
difficulties 
in 
valuing 
these 
benefits 
(such 
as 
biodiversity) 
and 
establishing 
a 
market. 
There 
are 
many 
options 
to 
value 
different 
parts 
of 
the 
environmental 
services 
that 
these 
blue 
carbon 
projects 
can 
provide, 
each 
requiring 
reasonable 
investment. 
Implementation 
complexity 
is 
rated 
as 
medium 
to 
high. 


6.2.2 
National 
model 
for 
tidal 
introduction 
and 
feasibility 
assessment 
A 
significant 
part 
of 
the 
blue 
carbon 
project 
costs 
relates 
to 
the 
need 
to 
undertake 
a 
hydrodynamic 
modelling 
analysis 
to 
confirm 
water 
movements 
within 
the 
carbon 
project 
area. 


A 
national 
model 
for 
tidal 
introduction 
and 
feasibility 
assessment 
for 
blue 
carbon 
projects 
has 
good 
potential 
to 
lower 
the 
sequestration 
cost. 
During 
the 
workshop, 
it 
was 
estimated 
that 
a 
high-resolution 
hydrodynamic 
model 
that 
works 
from 
a 
single 
platform 
would 
require 
an 
investment 
of 
$200 
million 
and 
more 
than 
10 
years 
to 
build. 
Unfortunately, 
due 
to 
the 
lack 
of 
time 
during 
the 
workshop, 
it 
was 
impossible 
to 
explore 
or 
reach 
a 
consensus 
on 
the 
timing 
of 
implementation 
steps 
and 
the 
scale 
of 
investment 
required. 
In 
subsequent 
discussions, 
the 
authors 
felt 
the 
estimate 
was 
overstated, 
and 
such 
a 
capability 
could 
be 
established 
with 
less 
investment 
and 
be 
ready 
at 
an 
earlier 
date. 
For 
this 
reason, 
the 
implementation 
complexity 
is 
rated 
as 
medium. 


6.2.3 
Earth 
observation 
technologies 
for 
restoration 
site 
identification 
and 
assessment 
Earth 
observation 
technologies 
for 
site 
identification 
and 
monitoring, 
reporting 
and 
verification 
have 
good 
potential 
to 
lower 
the 
costs 
of 
sequestration. 
The 
implementation 
steps 
identified 
during 
the 
workshop 
include 
improving 
the 
availability 
of 
key 
remote-sensed 
datasets, 
developing 
new 
indices 
or 
indicators 
that 
could 
aid 
in 
estimating 
the 
non-carbon 
benefits, 
as 
well 
as 


Sequestration 
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Workshops 
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developing 
improved 
data 
and 
methods 
to 
estimate 
the 
above 
and 
below-ground 
carbon 
sequestration. 
Most 
of 
the 
implementation 
steps 
required 
moderate 
investment, 
less 
than 
$5 
million, 
with 
a 
relatively 
early 
maturity 
timeframe 
of 
2025 
to 
2030. 
For 
these 
reasons, 
the 
implementation 
complexity 
of 
earth 
observation 
technologies 
is 
rated 
as 
medium. 


6.3 
Ranking 
The 
workshop 
results 
and 
modelled 
outputs 
are 
ranked 
in 
Table 
6.9. 
The 
ranking 
was 
achieved 
by 
normalising 
the 
outputs 
(cost 
reduction, 
scaling 
and 
maturity 
relative 
benefit, 
and 
implementation 
complexity) 
into 
a 
figure 
between 
zero 
and 
one, 
summing 
and 
then 
ranking 
the 
technologies 
based 
on 
the 
total 
sum. 
Implementation 
complexity 
was 
translated 
into 
a 
numerical 
value, 
with 
low 
being 
assigned 
1 
and 
high 
0.2. 


Table 
6.9: 
Ranking 
of 
technical 
innovation 
areas 
for 
blue 
carbon 
sequestration. 


TechnicalinnovationareaCostreduction($pertonne)
ScalingandmaturityrelativebenefitImplementationcomplexityPriority
Methods 
and 
indices 
for 
measuring 
0 
0.7 
Medium–high 
1 
other 
benefits 


National 
model 
for 
tidal 
introduction 
and 
feasibility 
assessment 
–39 
1 
Medium 
2 
Earth 
observation 
technologies 
for 
restoration 
site 
identification 
and 
–17 
0.6 
Medium 
3 
assessment 


6.4 
Discussion 
For 
reference, 
the 
baseline 
cost 
($92 
per 
tonne) 
determined 
in 
this 
analysis 
is 
significantly 
higher 
than 
the 
estimate 
reported 
in 
Fitch 
et 
al, 
(2022) 
of 
$18-$30 
per 
tonne. 
The 
difference 
is 
likely 
due 
to 
the 
low 
maturity 
of 
this 
technology 
and 
it 
is 
likely 
that 
the 
costs 
will 
reduce 
as 
uptake 
increases. 
The 
analysis 
indicated 
that 
a 
range 
of 
cost 
reductions 
from 
20 
to 
42% 
was 
possible 
on 
the 
baseline 
cost. 


The 
economic 
viability 
of 
blue 
carbon 
projects 
is 
challenging, 
and 
technical 
innovations 
that 
lower 
the 
establishment 
or 
start-up 
costs 
have 
significant 
potential 
to 
reduce 
costs, 
improve 
the 
economic 
viability 
and 
unlock 
additional 
sequestration. 
A 
national 
modal 
for 
tidal 
introduction 
and 
feasibility 
assessment 
that 
can 
rapidly 
produce 
the 
necessary 
outputs 
to 
confirm 
the 
suitability 
and 
eligibility 
of 
blue 
carbon 
projects 
has 
good 
cost 
reduction 
potential. 


Any 
technologies 
that 
can 
increase 
revenue 
streams 
for 
blue 
carbon 
projects 
will 
help 
improve 
the 
economic 
viability 
of 
projects. 
Methods 
and 
indices 
that 
quantify 
the 
environmental 
service 
provision 
of 
projects 
and 
enable 
a 
premium 
carbon 
price 
for 
a 
differentiated 
product 
or 
support 
other 
environmental 
crediting 
schemes 
(e.g. 
reef 
credits) 
would 
be 
beneficial. 
The 
analysis 
in 
this 
report 
is 
sensitive 
to 
the 
underlying 
assumptions 
in 
the 
modelling 
as 
described 
in 
section 
6.1.7. 


The 
performance 
of 
blue 
and 
teal 
carbon 
projects 
around 
Australia 
may 
vary 
depending 
on 
regional 
ecosystem 
type, 
condition 
and 
performance, 
and 
the 
prevailing 
policy 
setting. 
At 
a 
project 
level, 
proponents’ 
technical 
understanding 
of 
basic 
ecological 
and 
physiological 


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Science 
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requirements 
(e.g. 
low 
tide 
exposure) 
and 
their 
adoption 
of 
emerging 
technologies 
will 
affect 
the 
project’s 
success. 
Costs 
of 
entry, 
long 
(decadal) 
timeframes 
for 
a 
return 
on 
investment, 
and 
ongoing 
monitoring, 
reporting 
and 
verification 
(MRV) 
requirements 
are 
further 
factors 
that 
will 
influence 
the 
success 
of 
projects. 


Better 
data 
for 
predicting 
the 
feasibility 
of 
blue 
carbon 
projects 
include 
better 
resolution 
of 
tidal 
planes, 
mapping 
of 
hydrological 
modification 
and 
structures, 
more 
accurate 
income 
data 
from 
different 
land-uses 
and 
the 
costing 
of 
restoration 
activities. 
Increasing 
the 
range 
of 
case 
study 
regions 
would 
further 
help 
understanding 
of 
the 
extent 
of 
tidal 
restoration 
opportunities 
and 
limitations 
across 
Australia. 


The 
studies 
of 
Hagger 
et 
al. 
(2022a, 
b) 
conclude 
that 
carbon 
prices 
in 
Australia 
are 
too 
low 
for 
many 
projects 
to 
be 
feasible 
and 
that 
bundling 
or 
stacking 
co-benefits 
is 
the 
most 
viable 
medium-
term 
solution 
to 
increasing 
adoption 
(Hagger 
et 
al. 
2022a, 
b). 


Up-front 
project 
establishment 
costs 
can 
be 
high 
and 
include 
regulatory 
approvals 
that 
can 
require 
hydrological/hydrodynamic 
modelling 
to 
be 
undertaken, 
and 
capital 
outlays 
to 
remove 
or 
emplace 
structures 
and 
to 
undertake 
any 
earthworks 
and 
fencing. 
Ongoing 
maintenance 
costs 
and 
meeting 
MRV 
requirements 
must 
also 
be 
factored 
into 
assessments 
of 
the 
financial 
viability 
of 
any 
proposed 
projects. 
Studies 
from 
forest 
carbon 
projects 
have 
shown 
that 
the 
costs 
of 
monitoring 
and 
verification 
can 
exceed 
the 
revenue 
from 
carbon 
credits 
and 
that 
the 
cost 
is 
a 
critical 
component 
in 
developing 
forest 
carbon 
methods 
that 
provide 
incentives 
(Köhl 
et 
al. 
2020). 
A 
key 
motivation 
for 
developing 
modelling 
tools 
like 
BlueCAM 
is 
that 
they 
do 
not 
require 
costly 
field 
measurements 
of 
sequestration 
and 
so 
reduce 
the 
costs 
borne 
by 
project 
proponents. 


Blue 
carbon 
ecosystems 
provide 
multiple 
co-benefits, 
including 
biodiversity, 
fisheries 
enhancement, 
pollutant 
removal, 
coastal 
protection 
and 
reduced 
pest 
incursions. 
They 
are 
culturally 
significant 
to 
Indigenous 
people 
who 
rely 
on 
them 
for 
materials 
and 
resources. 


Co-benefit 
hotspots 
can 
be 
identified 
where 
multiple 
benefits 
are 
bundled 
to 
attain 
higher 
carbon 
prices 
for 
restoration 
projects 
or 
to 
undertake 
projects 
for 
emerging 
markets, 
such 
as 
biodiversity 
credits. 
As 
these 
ecosystem 
services 
vary 
regionally 
and 
locally, 
relevant 
systematic 
data 
collection 
and 
the 
development 
of 
modelling 
tools 
are 
required. 


National 
hydrological 
models 
that 
can 
assess 
the 
extent 
and 
frequency 
of 
inundation 
of 
coastal 
areas 
and 
habitats 
with 
improved 
delineation 
of 
the 
areal 
extent 
over 
which 
management 
interventions 
may 
feasibly 
operate 
are 
required. 
The 
CSIRO 
and 
BHP 
are 
undertaking 
a 
national 
blue 
carbon 
project 
to 
develop 
some 
of 
this 
national 
hydrological 
capability, 
and 
it 
should 
be 
available 
later 
in 
2023. 


A 
key 
motivation 
for 
the 
development 
of 
modelling 
tools 
like 
BlueCAM 
is 
that 
they 
do 
not 
require 
costly 
field 
measurements, 
ensuring 
consistency 
and 
reducing 
the 
costs 
borne 
by 
project 
proponents. 
However, 
for 
assessing 
the 
potential 
of 
tidal 
introduction 
methods, 
national 
hydrological 
models 
that 
can 
assess 
the 
extent 
and 
frequency 
of 
inundation 
of 
coastal 
areas 
and 
habitats 
are 
also 
required, 
along 
with 
improved 
delineation 
of 
the 
areal 
extent 
over 
which 
management 
interventions 
may 
feasibly 
operate. 


6.5 
Blue 
carbon 
case 
study: 
the 
benefits 
of 
a 
national 
hydrological 
modelling 
capability 
for 
blue 
carbon 
tidal 
inundation 
modelling 
A 
requirement 
of 
the 
Tidal 
Restoration 
of 
Blue 
Carbon 
Ecosystems 
(the 
blue 
carbon 
method, 
Clean 
Energy 
Regulator, 
2022) 
is 
a 
hydrological 
study 
to 
assist 
the 
planning 
of 
engineering 
works 
and 
to 
establish 
the 
extent 
of 
tidal 
inundation 
that 
would 
be 
likely 
to 
be 
achieved 
in 
the 
project 


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Cost 
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Workshops 
Report 
| 
59 



area 
with 
the 
removal 
of 
identified 
tidal 
barriers. 
This 
typically 
requires 
engaging 
a 
commercial 
engineering 
consultant 
to 
develop 
a 
hydrodynamic 
model 
for 
the 
project 
area. 
Depending 
on 
the 
project 
size, 
this 
might 
cost 
between 
$15,000 
and 
$45,000 
– 
a 
considerable 
outlay 
and 
up-front 
cost 
for 
any 
project 
proponent. 


In 
this 
study, 
we 
considered 
providing 
a 
public-use 
national 
modelling 
capability 
to 
reduce 
these 
up-front 
costs 
and 
stimulate 
project 
uptake. 
Such 
a 
national 
hydrological 
modelling 
capability 
would 
assist 
proponents 
in 
assessing 
the 
extent 
and 
frequency 
of 
inundation 
in 
their 
project 
areas, 
lower 
start-up 
costs, 
shorten 
delays 
in 
acquiring 
the 
data 
and 
engaging 
consultants, 
and 
contribute 
to 
more 
robust 
cost 
feasibility 
assessments. 


Fortunately, 
there 
are 
several 
initiatives 
already 
underway 
that 
could 
be 
harnessed 
to 
reduce 
costs 
and 
accelerate 
implementation. 
A 
national 
blue 
carbon 
project 
undertaken 
by 
the 
CSIRO 
and 
BHP 
provides 
a 
nationally 
consistent 
determination 
of 
the 
highest 
astronomical 
tides 
around 
Australia, 
which 
will 
be 
available 
for 
projects 
to 
use. 
Under 
the 
Australian 
Climate 
Services 
(https://www.acs.gov.au), 
national 
inundation 
modelling 
is 
being 
developed, 
primarily 
for 
more 
effective 
planning 
and 
response 
to 
extreme 
weather 
resulting 
in 
fluvial 
or 
storm 
surges. 
While 
the 
spatial 
resolution 
of 
this 
model 
is 
probably 
too 
coarse 
for 
the 
scale 
of 
many 
blue 
carbon 
projects, 
it 
provides 
an 
important 
framework 
and 
the 
necessary 
forcing 
data 
to 
nest 
more 
refined 
models. 
Such 
models 
will 
need 
better 
data, 
including 
fine-scale 
harmonised 
bathymetry 
and 
digital 
elevation 
information, 
particularly 
in 
the 
upper 
reaches 
of 
estuaries 
and 
floodplains. 
Sediment 
accretion 
models 
that 
underpin 
the 
BlueCAM 
models 
could 
also 
feasibly 
be 
used 
as 
part 
of 
this 
modelling 
approach 
and 
would 
further 
increase 
the 
rigour 
of 
project-scale 
and 
national 
assessments. 
In 
Queensland, 
a 
project 
along 
catchments 
adjacent 
to 
the 
Great 
Barrier 
Reef 
is 
being 
developed 
for 
assisting 
projects. 
The 
approach 
will 
be 
to 
trial 
the 
models 
in 
several 
pilot 
sites 
where 
data 
or 
models 
are 
already 
available. 
The 
trials 
will 
document 
sediment 
accretion 
on 
bare 
and 
vegetated 
coastal 
areas 
or 
finely 
resolved 
hydrological 
models 
for 
comparison. 


Given 
the 
above 
investments, 
we 
believe 
a 
modest 
investment 
of 
approximately 
$4–6 
million 
could 
deliver 
the 
additional 
capability 
required 
to 
undertake 
blue 
carbon 
assessments. 


60 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Figure 
6-6: 
Reintroduction 
of 
tidal 
flow 
site, 
Maroochy 
flood 
plain, 
Queensland. 
Photo 
credit 
Blue 
Heart. 


One 
of 
the 
first 
projects 
to 
apply 
for 
accreditation 
under 
the 
blue 
carbon 
method 
is 
the 
approximately 
5000-ha 
Blue 
Heart 
project 
located 
on 
the 
Maroochy 
flood 
plain, 
Queensland. 
This 
project 
proposes 
the 
reintroduction 
of 
tidal 
flow 
to 
an 
area 
of 
approximately 
480 
ha 
through 
the 
removal 
of 
17 
tidal 
barriers. 
A 
feasibility 
study 
estimated 
that 
the 
proposed 
blue 
carbon 
area 
could 
generate 
93,394 
tCO2e 
over 
a 
25-year 
period 
(Whitehead 
and 
Lipsett-Moore 
2022). 
Assuming 
a 
carbon 
price 
of 
$35 
per 
tCO2e, 
a 
return 
of 
$3.269 
million 
could 
be 
expected. 
The 
costs 
associated 
with 
the 
project 
were 
estimated 
to 
be 
about 
$2.8 
million, 
with 
more 
than 
90% 
(up 
to 
$2.25 
million) 
being 
associated 
with 
the 
on-ground 
engineering 
works 
for 
tide 
gate 
removal. 
Startup 
costs, 
including 
hydrological 
assessments 
and 
various 
approvals, 
of 
$240,000 
were 
a 
relatively 
minor 
overhead. 
Importantly, 
this 
study 
also 
identified 
that 
the 
economic 
value 
of 
co-benefits 
could 
generate 
about 
$25,000 
ha 
per 
year 
and 
contribute 
significantly 
to 
the 
project’s 
profitability. 


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Cost 
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Workshops 
Report 
| 
61 



6.6 
References 
Bayraktarov 
E, 
Saunders 
MI, 
Abdullah 
S, 
Mills 
M, 
Beher 
J, 
Possingham 
HP, 
Mumby 
PJ, 
Lovelock 
CE 
(2016) 
The 
cost 
and 
feasibility 
of 
marine 
coastal 
restoration. 
Ecological 
Applications, 
26(4):1055–1074. 
https://doi.org/10.1890/151077 


Clean 
Energy 
Regulator 
(2022) 
Tidal 
restoration 
of 
blue 
carbon 
ecosystems 
method, 
https://www.cleanenergyregulator.gov.au/ERF/Choosing-a-project-type/Opportunities-for-the-landsector/
Vegetation-methods/tidal-restoration-of-blue-carbon-ecosystems-method. 


Fitch 
P, 
Battaglia 
M, 
Lenton 
A, 
Feron 
P, 
Gao 
L, 
Mei 
Y, 
Hortle 
A, 
Macdonald 
L, 
Pearce 
M, 
Occhipinti 
S, 
Roxburgh 
S, 
Steven 
A 
(2022) 
Australia’s 
carbon 
sequestration 
potential: 
a 
stocktake 
and 
analysis 
of 
sequestration 
technologies, 
CSIRO, 
Canberra. 


Lou, 
J., 
Hultman, 
N., 
Patwardhan, 
A., 
& 
Qiu, 
Y. 
L. 
(2022). 
Integrating 
sustainability 
into 
climate 
finance 
by 
quantifying 
the 
co-benefits 
and 
market 
impact 
of 
carbon 
projects. 
Communications 
Earth 
& 
Environment, 
3(1), 
137. 


Hagger 
V, 
Waltham 
NJ, 
Lovelock 
CE 
(2022a) 
Opportunities 
for 
coastal 
wetland 
restoration 
for 
blue 
carbon 
with 
co-
benefits 
for 
biodiversity, 
coastal 
fisheries, 
and 
water 
quality. 
Ecosystem 
Services, 
55:101423. 


Hagger 
V, 
Stewart-Sinclair 
P, 
Rossini 
R, 
Waltham 
NJ, 
Ronan 
M, 
Adame 
MF, 
Lavery 
P, 
Glamore 
W, 
Lovelock 
CE 
(2022b) 
Coastal 
wetland 
restoration 
for 
blue 
carbon 
in 
Australia. 
Values-based 
approach 
for 
selecting 
restoration 
sites. 
Report 
to 
the 
National 
Environmental 
Science 
Program, 
The 
University 
of 
Queensland. 


Strassburg 
BBN, 
Beyer 
HL, 
Crouzeilles 
R, 
Iribarrem 
A, 
Barros 
F, 
de 
Siqueira 
MF, 
Sánchez-Tapia 
A, 
Balmford 
A, 
Sansevero 
JBB, 
Brancalion 
PHS, 
Broadbent 
EN, 
Chazdon 
RL, 
Filho 
AO, 
Gardner 
TA, 
Gordon 
A, 
Latawiec 
A, 
Loyola 
R, 
Metzger 
JP, 
Mills 
M, 
Possingham 
HP, 
Rodrigues 
RR, 
Scaramuzza 
CAdM, 
Scarano 
FR, 
Tambosi 
L, 
Uriarte 
M 
(2019) 
Strategic 
approaches 
to 
restoring 
ecosystems 
can 
triple 
conservation 
gains 
and 
halve 
costs. 
Nature 
Ecology 
and 
Evolution, 
3(1):62–70. 
https://doi.org/10.1038/s41559-018-0743-8 


Whitehead, 
Lipsett-Moore 
(2022) 
Blue 
Heart 
– 
Feasibility 
assessment 
of 
blue 
carbon 
pilot 
sites, 
The 
Nature 
Conservancy. 


Waltham 
NJ, 
Wegscheidl 
C, 
Volders 
A, 
Smart 
JCR, 
Hasan 
S, 
Lédée 
E, 
Waterhouse 
J 
(2021) 
Land 
use 
conversion 
to 
improve 
water 
quality 
in 
high 
DIN 
risk, 
low-lying 
sugarcane 
areas 
of 
the 
Great 
Barrier 
Reef 
catchments. 
Marine 
Pollution 
Bulletin, 
167, 
112373. 
https://doi.org/10.1016/j.marpolbul.2021.112373. 


62 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



7 
Direct 
air 
capture 


The 
direct 
air 
capture 
workshop 
was 
held 
14 
December 
2022 
with 
11 
participants. 
Appendix 
C, 
section 
C.1.3, 
includes 
a 
list 
of 
workshop 
participants. 


One 
pre-workshop 
question 
was 
sent 
to 
participants: 
‘Please 
list 
up 
to 
five 
technological 
innovations 
or 
barrier 
removals 
that 
will 
drive 
cost 
reduction 
of 
carbon 
abatement 
using 
this 
sequestration 
approach.’ 
The 
three 
technological 
innovations 
that 
have 
the 
most 
significant 
impact 
on 
cost 
reduction 
were 
reviewed 
in 
detail. 


For 
this 
workshop, 
a 
fourth 
continuum 
was 
added 
to 
the 
Miro 
boards. 
The 
continuums 
discussed 
were: 


 
Cost 
reduction 
potential: 
What 
is 
the 
cost 
reduction 
of 
each 
technological 
innovation 
in 
$ 
per 
tonne? 
 
Maturity 
timeframe: 
What 
year 
in 
the 
future 
could 
we 
reasonably 
expect 
this 
innovation 
to 
be 
routinely 
used 
and 
the 
cost 
reduction 
to 
occur? 
 
Uptake 
scaling 
potential: 
If 
this 
price 
reduction 
for 
delivered 
abatement 
could 
be 
achieved, 
what 
is 
the 
potential 
supply 
of 
abatement 
compared 
with 
current 
levels 
of 
delivered 
abatement? 
(Unit 
is 
a 
multiplier 
of 
current 
uptake 
rate 
– 
if 
0 
is 
current, 
assume 
1 
tonne.) 
 
Investment 
required: 
How 
much 
is 
it 
going 
to 
cost 
to 
realise 
the 
potential 
of 
this 
technological 
innovation? 
(Unit 
is 
millions 
of 
dollars.) 
In 
the 
third 
round 
of 
the 
workshop, 
the 
implementation 
steps 
required 
to 
realise 
the 
potential 
of 
each 
technological 
innovation 
were 
explored. 
The 
participants 
were 
asked 
to 
indicate 
how 
much 
investment 
would 
be 
necessary 
to 
develop 
that 
innovation 
to 
maturity. 


7.1 
Workshop 
results 
7.1.1 
Technology 
list 
Table 
7.1 
presents 
the 
technical 
innovation 
opportunities 
collated 
during 
the 
workshop, 
together 
with 
a 
brief 
definition 
of 
the 
opportunity. 
Note 
that 
the 
specifics 
of 
each 
technical 
innovation 
area 
were 
not 
discussed 
or 
agreed 
to 
at 
the 
workshop 
and 
so 
are 
indicative. 
Apart 
from 
the 
technical 
innovations 
in 
direct 
air 
capture 
(DAC) 
technologies, 
the 
considerations 
around 
energy 
supply 
to 
operate 
the 
DAC 
process 
were 
also 
considered 
as 
important. 


The 
technology 
innovation 
areas 
are 
closely 
linked 
to 
each 
other. 
The 
performance 
of 
materials 
in 
DAC 
will 
be 
influenced 
by 
the 
process 
and 
equipment 
design 
and 
the 
method 
of 
energy 
supply. 


Table 
7.1: 
Technical 
innovation 
opportunities 
for 
carbon 
sequestration 
through 
direct 
air 
capture. 


TechnologyinnovationareaDescriptionCostreductionarea
Materials 


Robust, 
low-cost, 
fast-reacting 
CO2 
Stability 
of 
capture 
agents 
in 
service 
over 
time. 
capture 
agents. 


Capture 
equipment 
size 
and 
costs. 


Scale 
of 
manufacturing 
of 
affordable 
capture 
agents 
including 
supply 
chains. 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
63 



Energy 
requirement 
for 
regeneration 
of 
capture 
agents. 



Energy 
supply 


Integration 
of 
DAC 
system 
with 
zero-emission, 
most 
likely 
variable, 
energy 
supply. 


Process 
and 
equipment 


Scalable 
low-cost 
process 
and 
equipment 
designs 
that 
minimise 
process 
energy 
requirements. 



Storage 
of 
heat, 
electricity 
or 
CO2. 
Electricity-driven 
DAC 
systems. 
Physical 
integration 
option 
of 
DAC 
system 
with 


zero-emission 
energy 
supply. 


Low 
pressure 
drop 
air 
contactors. 
High 
specific 
surface 
area 
air 
contactors. 
Design 
and 
construction 
of 
large-scale 
plants. 
Manufacturing 
and 
equipment 
supply 
chain. 


7.1.2 
Workshop 
outputs 
All 
detailed 
outputs 
are 
presented 
in 
Appendix 
A. 
The 
methodology 
used 
to 
develop 
the 
outputs 
is 
detailed 
in 
Chapter 
3. 
Table 
7.2 
presents 
an 
overview 
of 
workshop 
outputs, 
indicating 
the 
cost 
reduction 
potential, 
anticipated 
year 
of 
maturity, 
scaling 
factor 
and 
required 
investment 
(average, 
minimum 
and 
maximum). 
The 
experts 
expressed 
a 
wide 
range 
of 
cost 
reduction 
potentials 
for 
each 
technical 
innovation 
area. 
At 
the 
maximum, 
the 
cost 
reduction 
potential 
was 
approximately 
double 
the 
average 
for 
all 
technical 
innovation 
areas. 
At 
the 
minimum, 
the 
cost 
reduction 
potential 
could 
be 
zero 
(energy 
supply) 
or 
half 
the 
average 
cost 
reduction 
potential 
(process 
and 
equipment). 
We 
used 
the 
average 
data 
in 
our 
subsequent 
analysis. 
Significant 
variation 
was 
also 
encountered 
in 
the 
required 
investment 
discussions. 


Table 
7.2: 
Summary 
of 
outputs 
from 
the 
direct 
air 
capture 
workshop. 


TechnicalinnovationareaCostreductionpotential(%)
Maturity(Year)ScalingfactorInvestmentrequired($)
AvgMinMaxAvgMinMaxAvgMinMaxAvgMinMax
Materials 
27 
6 
50 
2031 
2027 
2035 
6.7 
1 
10.5 
530 
45 
1500 
Energy 
supply 
8 
0 
17 
2032 
2028 
2037 
7.8 
0 
10 
500 
225 
7500 


Process 
and 
34 
17 
67 
2033 
2030 
2038 
9 
3 
10 
1065 
3200 
15000 
equipment 


64 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Figure 
7-1: 
Plot 
of 
average 
cost 
reduction 
percentages 
versus 
scaling 
factor 
for 
direct 
air 
capture 
technical 
innovation 
areas. 


In 
Figure 
7-1, 
cost 
reduction 
estimates 
are 
plotted 
against 
the 
scaling 
factors. 
The 
lack 
of 
a 
relationship 
between 
the 
scaling 
factor 
and 
cost 
reduction 
is 
likely 
an 
artefact 
of 
the 
workshop 
and 
is 
a 
signal 
to 
interpret 
the 
results 
with 
care. 
This 
could 
be 
due 
to 
insufficient 
time 
to 
work 
through 
to 
a 
consensus 
or 
due 
to 
lack 
of 
a 
consensus 
process 
to 
compare 
scaling 
factors 
to 
cost 
reduction. 


7.1.3 
Cost 
analysis 
Workshop 
participants 
used 
a 
baseline 
figure 
of 
$900 
per 
tonne 
(equivalent 
to 
US$600 
per 
tonne) 
to 
estimate 
cost 
reduction. 
This 
analysis 
is 
different 
to 
other 
chapters 
as 
no 
modelling 
was 
done; 
instead, 
the 
cost 
reduction 
estimates 
were 
applied 
directly 
to 
the 
baseline 
cost 
to 
yield 
the 
figures 
below. 
The 
original 
percentage 
reductions 
can 
be 
seen 
in 
Table 
7.2. 
The 
future 
average 
cost 
reductions 
for 
each 
technical 
innovation 
area 
are 
shown 
in 
Table 
7.3. 


Table 
7.3: 
Cost 
reductions 
for 
direct 
air 
capture 
technical 
innovation 
areas. 


TechnicalinnovationareaCostreductionfrombaseline($pertonne)
Cost($pertonne)
Baselinecost0900
Materials 
–243 
657 
Energy 
supply 
–72 
828 


Process 
and 
equipment 
–306 
694 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
65 



Figure 
7-2: 
Bar 
graph 
of 
cost 
reductions 
for 
direct 
air 
capture 
technical 
innovation 
areas. 


From 
Figure 
7.2 
and 
Table 
7.3 
above, 
innovations 
in 
process 
and 
equipment 
were 
estimated 
to 
have 
the 
most 
significant 
effect 
(cost 
reduction 
of 
$306 
per 
t 
CO2), 
followed 
by 
innovations 
in 
materials 
(cost 
reduction 
of 
$243 
per 
t 
CO2). 
Innovations 
with 
energy 
supply 
had 
the 
least 
impact 
on 
cost 
(cost 
reduction 
of 
$72 
per 
t 
CO2). 
In 
total, 
an 
average 
cost 
reduction 
of 
$621 
per 
t 
CO2 
was 
deemed 
cumulatively 
feasible 
through 
the 
three 
innovation 
areas, 
equivalent 
to 
a 
69% 
reduction. 
Note 
that 
the 
cost 
reductions 
described 
above 
are 
not 
necessarily 
additive, 
as 
there 
will 
be 
dependencies 
and 
feedback 
with 
the 
implementations. 


7.1.4 
Cost 
reduction, 
maturity 
and 
scale 
Figure 
7-3 
summarises 
the 
outputs 
of 
the 
workshop 
on 
one 
chart. 
The 
x-axis 
represents 
the 
year 
of 
maturity, 
the 
y-axis 
the 
cost 
reduction 
per 
tonne 
of 
CO2 
sequestration, 
and 
the 
size 
of 
the 
bubble 
represents 
the 
scaling 
factor. 


66 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Figure 
7-3: 
Comparison 
of 
technology 
cost 
reduction, 
year 
of 
maturity 
and 
scaling 
factor 
for 
direct 
air 
capture 
technical 
innovation 
areas. 


7.1.5 
Sensitivity 
analysis 
of 
cash 
flow 
model 
The 
assessment 
of 
global 
direct 
air 
capture 
potential 
provides 
a 
sensitivity 
analysis 
for 
a 
model 
used 
for 
estimating 
costs 
for 
different 
configurations 
of 
direct 
air 
capture 
facilities 
(IEAGHG 
2021). 
Figure 
7-4 
is 
adapted 
from 
figure 
12 
on 
page 
18 
of 
the 
IEAGHG 
(2021) 
report 
and 
is 
a 
sensitivity 
analysis 
for 
the 
major 
cost 
drivers 
for 
a 
direct 
Nth-of-a-kind 
hybrid 
solid 
sorbent 
system 
with 
a 
1 
Mt 
per 
year 
capacity. 



Figure 
7-4: 
Sensitivity 
of 
sequestration 
costs 
to 
relative 
changes 
in 
different 
cost 
drivers, 
adapted 
from 
global 
assessment 
of 
direct 
air 
capture 
costs 
based 
on 
sensitivity 
of 
1 
Mt 
CO2 
per 
year 
capacity 
Nth-of-a-

Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
67 



kind 
hybrid 
solid 
sorbent 
system 
costs 
($ 
per 
t 
CO2 
net). 
Capex 
= 
capital 
expenditure. 
Adapted 
from 
IEAGHG 
(2021). 


The 
sensitivities 
reported 
in 
Figure 
7-4 
are 
expected 
to 
differ 
slightly 
for 
other 
configurations 
of 
DAC 
technologies 
and 
in 
locations 
where 
the 
cost 
drivers 
are 
different. 
However, 
these 
figures 
are 
indicative 
and 
can 
be 
used 
to 
derive 
general 
conclusions. 
Extending 
the 
lifetime 
of 
a 
plant 
has 
the 
greatest 
potential 
to 
reduce 
project 
lifetime 
costs, 
followed 
by 
lowering 
the 
cost 
of 
the 
materials 
(adsorbent) 
and 
then 
the 
cost 
of 
the 
initial 
establishment 
(capital 
expenditure). 


7.1.6 
Assumption 
and 
limitations 
of 
the 
analysis 
The 
modelling 
for 
cost 
reduction 
was 
based 
on 
the 
averages 
determined 
from 
the 
experts’ 
input, 
which 
showed 
a 
wide 
range 
of 
opinions 
on 
the 
achievable 
cost 
reductions 
for 
each 
technology 
innovation 
area. 
The 
average 
cost 
reduction 
was 
deemed 
representative, 
but 
this 
can 
only 
be 
considered 
indicative 
and 
does 
not 
represent 
a 
consensus 
opinion. 


7.2 
Analysis 
of 
implementation 
steps 
The 
results 
in 
this 
section 
were 
obtained 
by 
asking 
workshop 
participants 
to 
attempt 
to 
define 
the 
steps 
required 
for 
the 
implementation 
of 
the 
technical 
innovations. 
The 
participants 
were 
asked 
to 
provide 
cost 
estimates, 
but 
due 
to 
time 
limitations, 
these 
were 
not 
captured. 
The 
cost 
of 
the 
steps 
warrants 
further 
investigation, 
though 
some 
of 
the 
steps 
are 
a 
wish 
list 
and 
not 
grounded. 
The 
outputs 
have 
been 
reviewed 
and 
grouped, 
with 
some 
analysis 
of 
the 
feasibility 
of 
the 
steps. 


7.2.1 
Materials 
The 
innovations 
in 
materials 
for 
CO2 
capture 
are 
broad, 
ranging 
from 
materials 
that 
are 
more 
robust 
in 
the 
DAC 
operation, 
materials 
that 
release 
CO2 
at 
relatively 
low 
temperatures, 
which 
enables 
the 
use 
of 
waste 
heat, 
and 
materials 
that 
require 
a 
lower 
heat 
input 
for 
the 
release 
of 
the 
CO2. 
The 
capture 
materials 
also 
need 
to 
be 
low 
cost 
and 
their 
supply 
chains 
secure. 


7.2.2 
Energy 
supply 
Innovation 
in 
the 
energy 
supply 
would 
enable 
the 
use 
of 
low-carbon 
energy 
sources 
to 
operate 
the 
DAC 
process. 
Variable 
renewable 
energy 
requires 
storage 
to 
increase 
capacity 
factors 
where 
integrating 
a 
DAC 
unit 
with 
the 
energy 
supply 
could 
benefit 
as 
CO2 
could 
be 
stored 
with 
the 
capture 
agent 
and 
regenerated 
at 
a 
time 
when 
energy 
was 
available 
at 
lowest 
cost. 
Other 
benefits 
might 
be 
derived 
from 
integration 
with 
other 
sequestration 
options. 


7.2.3 
Process 
and 
equipment 
Innovations 
in 
process 
and 
equipment 
would 
result 
in 
DAC 
unit 
designs 
and 
components 
that 
are 
easy 
to 
mass 
produce, 
transport 
and 
install 
on 
location. 
The 
process 
and 
equipment 
design 
needs 
to 
enable 
low-energy 
operation. 
Apart 
from 
the 
unit 
design, 
the 
overall 
spatial 
design 
of 
a 
large-
scale 
DAC 
plant 
needs 
to 
be 
optimised 
for 
the 
best 
system 
performance. 


68 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



7.3 
Discussion 
The 
key 
messages 
from 
the 
direct 
air 
capture 
workshop 
are 
summarised 
below: 


 
Analysis 
of 
workshop 
participants’ 
inputs 
indicated 
that 
average 
overall 
cost 
reductions 
of 
69% 
are 
anticipated 
through 
technology 
innovation 
and 
scale-up. 
There 
was 
considerable 
variation 
in 
the 
individual 
responses. 
 
Two 
of 
the 
innovation 
areas 
identified 
(materials 
and 
process 
and 
equipment) 
were 
considered 
most 
effective 
in 
reducing 
the 
DAC 
cost 
and 
should 
be 
pursued 
to 
achieve 
optimum 
performance. 
 
Achievement 
of 
these 
cost 
reductions 
is 
anticipated 
in 
the 
early 
2030s. 
7.4 
References 
IEAGHG 
(2021) 
Global 
assessment 
of 
direct 
air 
capture 
costs: 
technical 
report 
2021-05, 
December 
2021, 
IEA 
Greenhouse 
Gas 
R&D 
Programme, 
Cheltenham, 
UK 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
69 



8 
Savanna 
fire 
management 


8.1 
Background 
and 
methodology 
The 
Climate 
Change 
Authority 
requested 
a 
2–4-page 
synthesis 
derived 
from 
consultation 
with 
subject 
matter 
experts 
on 
two 
topics. 
The 
two 
topics 
identified 
for 
the 
review 
were: 


 
the 
opportunity 
for 
remotely 
sensed 
fire 
severity 
to 
remove 
the 
need 
for 
an 
early 
dry 
season/late 
dry 
season 
cut-off 
date 
 
improved 
provision 
of 
fire 
risk 
information 
to 
inform 
prescribed 
burn 
planning. 
Consulted 
for 
this 
synthesis 
were 
the 
following 
scientists 
recommended 
by 
the 
Climate 
Change 
Authority 
: 


 
Dr 
Shaun 
Levick, 
CSIRO, 
https://people.csiro.au/L/S/Shaun-Levick 
 
Dr 
Anna 
Richards, 
CSIRO, 
https://people.csiro.au/R/A/Anna-Richards 
 
Dr 
Garry 
Cook, 
CSIRO, 
https://people.csiro.au/C/G/Garry-Cook 
 
Dr 
Andrew 
Sullivan, 
CSIRO, 
https://people.csiro.au/S/A/Andrew-Sullivan 
 
Dr 
Adam 
Liedloff, 
CSIRO, 
https://people.csiro.au/L/A/Adam-Liedloff 
The 
consultation 
consisted 
of 
an 
extended 
question 
and 
answer 
session, 
commentary 
on 
notes 
and 
recommended 
literature 
to 
consider 
for 
the 
topics 
of 
concern. 
Parties 
were 
invited 
to 
review 
the 
content. 


8.2 
Remotely 
sensed 
fire 
severity 
to 
remove 
the 
need 
for 
an 
early 
dry 
season/late 
dry 
season 
cut-off 
date 
The 
‘Savanna 
fire 
management 
– 
emissions 
avoidance 
method’ 
(DCCEEW 
2022) 
defines 
the 
late 
dry 
season 
start 
date 
as 
1 
August 
and 
the 
end 
date 
as 
31 
December. 
The 
1 
August 
cut-off 
date 
is 
used 
for 
the 
division 
of 
areas 
burnt 
into 
early 
and 
late 
dry 
season 
fires, 
which 
are 
then 
included 
in 
SavBAT4 
to 
compare 
the 
area 
burnt 
in 
each 
period 
to 
a 
baseline 
period 
and 
thereafter 
estimate 
emissions 
avoidance. 


There 
is 
high 
agreement 
among 
those 
consulted 
and 
also 
from 
the 
literature 
that 
this 
cut-off 
date 
could 
be 
improved 
or 
replaced 
with 
a 
more 
appropriate 
measure. 


Fire 
severity 
in 
the 
tropical 
savanna 
is 
strongly 
driven 
by 
rainfall 
in 
the 
preceding 
months 
and 
fuel 
availability 
and 
temperature 
at 
the 
time 
of 
the 
fire 
(strong 
agreement, 
strong 
evidence) 
(Beringer 
et 
al. 
2015; 
Williams 
et 
al. 
1998, 
2009). 


There 
is 
high 
agreement 
that 
fire 
severity 
increases 
in 
the 
late 
season, 
and 
that 
early-season 
fires 
may 
be 
patchier 
than 
late-season 
fires 
(Price 
et 
al. 
2003; 
Williams 
et 
al. 
2003; 
Murphy 
and 
Russell-
Smith 
2010). 


Northern 
Territory 
government 
climate 
analysis 
shows 
that 
northern 
Australia 
is 
already 
experiencing 
the 
impact 
of 
climate 
change, 
showing 
warmer 
temperatures, 
a 
wetter 
December 
to 


4 
SavBAT 
Savanna 
Burning 
Abatement 
Tool 
(environment.gov.au) 


70 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



February 
period 
and 
drier 
June 
to 
August 
period, 
and 
an 
increased 
number 
of 
days 
with 
high 
fire 
danger 
(NESP 
Earth 
Systems 
and 
Climate 
Change 
Hub 
2020). 
The 
latter 
implies 
that 
we 
may 
see 
an 
earlier 
cut-off 
to 
the 
fire 
season, 
in 
July 
rather 
than 
1 
August, 
as 
outlined 
in 
the 
Savanna 
fire 
management 
methodology. 
However, 
climate 
change 
effects 
on 
the 
timing 
and 
amount 
of 
rainfall 
in 
the 
longer 
term 
are 
uncertain 
(Whetton 
et 
al, 
2016). 


In 
addition 
to 
climate-induced 
increases 
in 
fire 
severity, 
the 
spread 
of 
invasive 
grasses 
such 
as 
gamba 
grass 
(Andropogon 
gayanus) 
and 
Mission 
grass 
(Cenchrus 
spp.) 
will 
increase 
fine 
fuel 
loads 
(up 
to 
four-fold) 
and 
hence 
fire 
intensity 
where 
it 
has 
invaded 
(Rossiter-Rachor 
et 
al. 
2008). 
The 
phenology 
of 
gamba 
grass 
means 
that 
it 
stays 
greener 
longer 
into 
the 
dry 
season 
and 
cures 
later 
than 
native 
grasses 
(Rossiter-Rachor 
et 
al. 
2009; 
Setterfield 
et 
al. 
2013). 


The 
impacts 
of 
a 
changing 
climate 
described 
above 
and 
the 
effect 
of 
vegetation 
composition 
on 
curing 
(noting 
that 
these 
weeds 
described 
make 
areas 
where 
they 
occur 
ineligible 
for 
carbon 
projects 
under 
the 
ACCU 
scheme) 
suggest 
that 
a 
cut-off 
based 
on 
vegetation 
curing 
rather 
than 
a 
hard 
date 
is 
desirable. 
Ideally, 
the 
severity 
of 
a 
burn 
(and 
thus 
its 
greenhouse 
gas 
consequences) 
would 
not 
be 
linked 
to 
whether 
it 
occurred 
before 
or 
after 
1 
August 
but 
to 
the 
local 
site 
fuel 
and 
weather 
conditions 
(at 
the 
time 
of 
fire 
and 
in 
preceding 
weeks/months), 
the 
change 
that 
is 
imparted 
on 
the 
vegetation, 
and 
the 
gasses 
released. 


Fire 
behaviour 
can 
also 
be 
manipulated 
using 
different 
ignition 
patterns 
to 
reduce 
overall 
intensity 
and 
emissions 
(Queensland 
Government 
2013). 
Use 
of 
judiciously 
spaced 
point 
ignitions 
on 
a 
grid 
(such 
as 
incendiaries 
from 
a 
helicopter) 
can 
consume 
fuel 
without 
creating 
high-intensity 
flames 
– 
basically, 
each 
fire 
completes 
its 
build-up 
phase 
from 
ignition 
just 
as 
it 
runs 
into 
its 
neighbour 
and 
then 
goes 
out. 
This 
way, 
you 
avoid 
having 
a 
large 
propagating 
fire 
that 
can 
become 
high 
intensity. 
This 
would 
be 
useful 
for 
late-season 
ignitions 
required 
for 
gamba 
grass, 
for 
example, 
which 
does 
not 
cure 
until 
late 
in 
the 
season. 


Fire 
extent 
and 
severity 
mapping 
in 
northern 
Australia 
could 
be 
greatly 
improved 
through 
a 
more 
robust 
analysis 
of 
Sentinel-2 
and 
Sentinel-1 
time 
series 
data 
(Grivei 
et 
al. 
2020; 
Gaveau 
et 
al. 
2021), 
using 
machine 
learning 
approaches 
(Belenguer-Plomerm 
et 
al. 
2019; 
Zhang 
et 
al. 
2021) 
to 
examine 
trends 
in 
spectral 
indices 
rather 
than 
thresholds. 
The 
use 
of 
C-and 
L-band 
synthetic 
aperture 
radar, 
which 
is 
not 
impeded 
in 
its 
capability 
by 
cloud, 
can 
help 
overcome 
limitations 
from 
optical 
sensors 
due 
to 
cloud 
(Phillip 
and 
Levick 
2020). 
Fire 
patchiness 
can 
be 
determined 
by 
combining 
different 
remote 
sensing 
products 
(e.g. 
Sentinel, 
Landsat 
and 
MODIS/VIIRS) 
and 
mapped 
pyrodiversity 
(Williamson 
et 
al. 
2022). 
This 
was 
not 
possible 
when 
the 
savanna 
burning 
methodology 
was 
first 
developed, 
but 
we 
now 
have 
the 
satellite 
and 
datacube 
infrastructure 
to 
accomplish 
these 
tasks. 
Synthetic 
aperture 
radar 
and 
passive 
microwave 
observation 
can 
estimate 
water 
content 
within 
vegetation, 
matched 
with 
hyperspectral 
sensing, 
and 
may 
be 
able 
to 
form 
the 
basis 
of 
remote 
sensing 
of 
vegetation 
curing 
(how 
green 
the 
fuel 
is, 
Owe 
et 
al. 
2001; 
Liu 
et 
al. 
2011). 
Additional 
investment 
would 
be 
required 
to 
set 
up 
an 
operational 
system 
to 
utilise 
these 
approaches. 


The 
best 
prospect 
for 
assessing 
the 
burnt 
area, 
patchiness 
of 
burns 
and 
potential 
curing 
status 
of 
vegetation 
is 
to 
combine 
complementary 
datasets 
of 
various 
spatial, 
temporal 
and 
radiometric 
differences 
(Levick 
et 
al. 
2018; 
Abdi 
et 
al. 
2022). 
Further 
research 
is 
required 
over 
a 
range 
of 
spatial 
scales 
and 
across 
a 
broader 
spectrum 
of 
fire 
regime 
conditions 
before 
automated 
products 
can 
be 
developed. 


8.3 
Improved 
provision 
of 
fire 
risk 
information 
to 
inform 
prescribed 
burn 
planning 
The 
agreed 
unifying 
framework 
for 
patterns 
of 
fire 
regime 
in 
Australia 
is 
the 
Bradstock 
‘four 
switches’ 
model 
(Bradstock 
2010). 
In 
this 
model, 
variations 
in 
area 
burned 
and 
fire 
frequency 
result 
from 
differences 
in 
the 
rates 
of 
‘switching’ 
of 
biomass 
growth, 
availability 
to 
burn, 
fire 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
71 



weather 
and 
ignition. 
To 
a 
large 
extent, 
fire 
risk 
intensity 
in 
tropical 
savannas 
is 
seasonal, 
with 
early 
dry 
season 
fires 
being 
of 
low 
intensity 
(<1000 
kW 
per 
m) 
and 
late 
dry 
season 
fires 
being 
up 
to 
a 
magnitude 
higher 
in 
intensity 
(Beringer 
et 
al. 
2015). 
The 
principal 
difference 
is 
rate 
of 
fuel 
consumption 
and 
fire 
continuity. 
Late-season 
fires 
are 
characterised 
by 
higher 
fuel 
levels 
and 
higher 
temperatures. 


The 
current 
practice 
is 
to 
use 
the 
Australian 
Fire 
Danger 
Rating 
System, 
which 
identifies 
eight 
fuel 
types 
across 
the 
country. 
The 
relevant 
model 
for 
tropical 
savanna 
is 
the 
Australian 
Fire 
Danger 
Rating 
System 
Grassy 
Woodland 
Model, 
which 
is 
based 
on 
the 
CSIRO 
Grassland 
Fire 
Spread 
Model 
(Bureau 
of 
Meteorology 
2022). 
In 
this 
model, 
strong 
drivers 
of 
fire 
risk 
(severity 
and 
rate 
of 
spread) 
are 
fuel 
load, 
wind 
speed, 
degree 
of 
grass 
curing 
and 
dead 
fuel 
moisture 
content, 
which 
is 
determined 
by 
air 
temperature 
and 
humidity. 
The 
model 
applies 
to 
three 
pasture 
states: 
natural, 
grazed 
and 
eaten 
out. 
The 
grassland 
layer 
strongly 
influences 
fire 
behaviour 
based 
on 
observations 
that 
grass 
structure, 
height 
and 
continuity 
strongly 
influence 
grassfire 
propagation. 


The 
veracity 
and 
fidelity 
of 
this 
new 
system 
in 
predicting 
fire 
danger 
for 
northern 
Australia 
is 
unknown 
and 
will 
take 
time 
to 
determine, 
particularly 
for 
early 
and 
late 
season 
conditions 
and 
for 
regions 
affected 
by 
exotic 
grass 
species 
such 
as 
gamba 
and 
Buffel. 
The 
Australian 
Fire 
Danger 
Rating 
System 
will 
likely 
undergo 
extensive 
refinement 
and 
updating 
to 
improve 
its 
applicability 
across 
the 
continent, 
but 
much 
of 
the 
initial 
focus 
of 
this 
work 
is 
likely 
to 
be 
in 
the 
populated 
south 
rather 
than 
the 
north. 


There 
are 
no 
data 
available 
on 
the 
accuracy 
of 
this 
system, 
but 
a 
recent 
analysis 
of 
the 
MacArthur 
Fire 
Danger 
rating 
system 
shows 
no 
relationship 
between 
elevated 
fire 
danger 
classes 
and 
burned 
area 
(Shah 
et 
al. 
2023). 
This 
result 
is 
not 
to 
say 
that 
the 
models 
do 
not 
predict 
fire 
intensity 
and 
rate 
of 
spread 
well, 
rather 
that 
fire 
weather 
does 
not 
correlate 
well 
with 
burned 
area 
(Preisler 
et 
al. 
2008). 


8.4 
Conclusion 
There 
is 
high 
agreement 
the 
1 
August 
cut-off 
date 
for 
early/late 
dry 
season 
could 
be 
replaced 
with 
a 
more 
appropriate 
measure 
by 
combining 
different 
remote 
sensing 
products 
and 
using 
machine 
learning. 


What 
is 
needed 
is: 


 
further 
research 
over 
a 
range 
of 
spatial 
scales 
and 
across 
a 
broad 
spectrum 
of 
fire 
conditions 
 
investment 
to 
set 
up 
an 
operational 
system 
 
combination 
of 
complementary 
datasets 
of 
various 
spatial, 
temporal 
and 
radiometric 
differences 
for 
assessing 
the 
burnt 
area, 
patchiness 
of 
burns 
and 
potential 
curing 
status 
of 
vegetation. 
Fire 
risk 
information 
has 
undergone 
a 
recent 
transformation 
with 
the 
implementation 
of 
the 
Australian 
Fire 
Danger 
Rating 
System. 


 
The 
veracity 
and 
fidelity 
of 
this 
new 
system 
in 
predicting 
fire 
danger 
for 
northern 
Australia 
is 
unknown 
and 
will 
take 
time 
to 
determine, 
particularly 
for 
early 
and 
late 
season 
conditions 
and 
regions 
affected 
by 
exotic 
grass 
species 
such 
as 
gamba 
and 
Buffel. 
 
Good 
data 
for 
the 
north 
needs 
to 
be 
acquired 
for 
this 
task. 
8.5 
References 
Abdi 
AM, 
Brandt 
M, 
Abel 
C, 
Fensholt 
R 
(2022) 
Satellite 
remote 
sensing 
of 
savannas: 
current 
status 
and 
emerging 
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Journal 
of 
Remote 
Sensing, 
2022:9835284. 
doi:10.34133/2022/9835284 


72 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Belenguer-Plomerm 
MA, 
Tanase 
MA, 
Fernandez-Carrillo 
A, 
Chuvieco 
E 
(2019) 
Burned 
area 
detection 
and 
mapping 
using 
Sentinel-1 
backscatter 
coefficient 
and 
thermal 
anomalies. 
Remote 
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of 
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233, 
111345. 
https://doi.org/10.1016/j.rse.2019.111345 


Beringer 
J, 
Hutley 
L, 
Tapper 
N, 
Cernusak 
L, 
Lynch 
A, 
Goergen 
K, 
Abramson 
D, 
Uotila 
P 
(2015) 
Fire 
in 
Australian 
savannas: 
from 
leaf 
to 
landscape. 
Global 
Change 
Biology, 
21, 
62–81. 
doi: 
10.1111/gcb.12686 


Bradstock 
RA 
(2010) 
A 
biogeographic 
model 
of 
fire 
regimes 
in 
Australia: 
current 
and 
future 
implications. 
Global 
Ecology 
and 
Biogeography, 
19(2):145–158. 
doi:10.1111/j.1466-8238.2009.00512 


Bureau 
of 
Meteorology 
(2022) 
AFDRS 
Grassy 
Woodland 
Model 
Guide, 
Bureau 
of 
Meteorology 
Fire 
Behaviour 
Model 
Guides, 
https://www.afac.com.au/initiative/afdrs/article/bom-fire-behaviour-model-guides. 


DCCEEW 
(2022) 
Savanna 
fire 
management 
– 
emissions 
avoidance 
method, 
Department 
of 
Climate 
Change, 
Energy, 
Environment 
and 
Water, 
Canberra, 
https://www.dcceew.gov.au/climate-change/emissionsreduction/
emissions-reduction-fund/methods/savanna-fire-management-emissions-avoidance. 


Gaveau 
D, 
Descals 
A, 
Salim 
M, 
Sheil 
D, 
Sloan 
S 
(2021) 
Refined 
burned-area 
mapping 
protocol 
using 
Sentinel-2 
data 
increases 
estimate 
of 
2019 
Indonesian 
burning. 
Earth 
System 
Science 
Data, 
13, 
5353–5368. 
doi:10.5194/essd13-
5353-2021 


Grivei 
A-C, 
Văduva 
C, 
Datcu 
M 
(2020) 
‘Assessment 
of 
burned 
area 
mapping 
methods 
for 
smoke 
covered 
Sentinel-2 
data,’ 
13th 
International 
Conference 
on 
Communications 
(COMM), 
Bucharest, 
Romania, 
pp. 
189–192. 
doi: 
10.1109/COMM48946.2020.9141999 


Levick 
SR, 
Shendryk 
Y, 
Setterfield 
SA, 
Rossiter-Rachor 
NA 
(2018) 
Evaluation 
of 
satellite 
remote 
sensing 
pathways 
for 
mapping 
and 
monitoring 
of 
gamba 
grass 
for 
the 
Savanna 
Fire 
Management 
Methodology, 
CSIRO 
and 
Charles 
Darwin 
University, 
Darwin. 


Liu 
YY, 
de 
Jeu 
RAM, 
McCabe 
MF, 
Evans 
JP, 
van 
Dijk 
AIJM 
(2011) 
Global 
long-term 
passive 
microwave 
satellite-based 
retrievals 
of 
vegetation 
optical 
depth. 
Geophysical 
Research 
Letters, 
38(18): 
L18402. 
doi:10.1029/2011GL048684 


Murphy 
BP, 
Russell-Smith 
J 
(2010) 
Fire 
severity 
in 
a 
northern 
Australia 
savanna 
landscape: 
the 
importance 
of 
time 
since 
previous 
fire. 
International 
Journal 
of 
Wildland 
Fire, 
19:46–51. 


NESP 
Earth 
Systems 
and 
Climate 
Change 
Hub 
(2020) 
Climate 
change 
in 
the 
Northern 
Territory: 
state 
of 
the 
science 
and 
climate 
change 
impacts, 
NESP 
ESCC 
Hub, 
Melbourne. 


Owe 
M, 
de 
Jeu 
R, 
Walker 
J 
(2001) 
A 
methodology 
for 
surface 
soil 
moisture 
and 
vegetation 
optical 
depth 
retrieval 
using 
the 
microwave 
polarization 
difference 
index. 
IEEE 
Transactions 
on 
Geoscience 
and 
Remote 
Sensing, 
39(8):1643– 
1654. 


Phillip 
MB, 
Levick 
SR 
(2020) 
Exploring 
the 
potential 
of 
C-Band 
SAR 
in 
contributing 
to 
burn 
severity 
mapping 
in 
tropical 
savanna. 
Remote 
Sensing, 
12(1), 
49. 
https://doi.org/10.3390/rs12010049 


Preisler 
HK, 
Chen 
S-C, 
Fujioka 
F, 
Benoit 
JW, 
Westerling 
AL 
(2008) 
Wildland 
fire 
probabilities 
estimated 
from 
weather 
model-deduced 
monthly 
mean 
fire 
danger 
indices. 
International 
Journal 
of 
Wildland 
Fire, 
17:305–316. 
https://doi.org/10.1071/WF06162 


Price 
O, 
Russell-Smith 
J, 
Edwards 
A 
(2003) 
Fine-scale 
patchiness 
of 
different 
fire 
intensities 
in 
sandstone 
heath 
vegetation 
in 
northern 
Australia. 
International 
Journal 
of 
Wildland 
Fire, 
12:227–236. 
doi:10.1071/WF03040 


Queensland 
Government 
(2013) 
‘Common 
issues,’ 
in 
Planned 
Burn 
Guidelines: 
Gulf 
Plains 
Bioregion 
of 
Queensland, 
Department 
of 
National 
Parks, 
Recreation, 
Sport 
and 
Racing, 
Brisbane, 
https://parks.des.qld.gov.au/__data/assets/pdf_file/0016/153610/pbg-gulf-plains-2.pdf. 


Rossiter-Rachor 
NA, 
Setterfield 
SA, 
Douglas 
MM, 
Hutley 
LB, 
Cook 
GD 
(2008) 
Andropogon 
gayanus 
(gamba 
grass) 
invasion 
alters 
fire-mediated 
nitrogen 
losses 
in 
the 
tropical 
savanna 
of 
Northern 
Australia. 
Ecosystems, 
11:77– 
88. 


Rossiter-Rachor 
NA, 
Setterfield 
SA, 
Douglas 
MM, 
Hutley 
LB, 
Cook 
GD, 
Schmidt 
S 
(2009) 
Invasive 
Andropogon 
gayanus 
(gamba 
grass) 
is 
an 
ecosystem 
transformer 
of 
nitrogen 
relations 
in 
Australian 
savanna. 
Ecological 
Applications, 
19:1546–1560. 


Setterfield 
SA, 
Rossiter-Rachor 
NA, 
Douglas 
MM, 
Wainger 
L, 
Petty 
AM, 
Barrow 
P, 
Shepherd 
IJ, 
Ferdinands 
KB 
(2013) 
Adding 
fuel 
to 
the 
fire: 
the 
impacts 
of 
non-native 
grass 
invasion 
on 
fire 
management 
at 
a 
regional 
scale. 
PLoS 
ONE 
8(5): 
e59144. 
doi:10.1371/journal.pone.0059144 


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Shah 
SU, 
Yebra 
M, 
Van 
Dijk 
AIJM, 
Cary 
GJ 
(2023) 
Relating 
McArthur 
fire 
danger 
indices 
to 
remote 
sensing 
derived 
burned 
area 
across 
Australia. 
International 
Journal 
of 
Wildland 
Fire, 
32:133–148. 


Whetton, 
P. 
H., 
Grose, 
M. 
R., 
& 
Hennessy, 
K. 
J. 
(2016). 
A 
short 
history 
of 
the 
future: 
Australian 
climate 
projections 
1987–2015. 
Climate 
Services, 
2, 
1-14. 


Williams 
RJ, 
Gill 
AM, 
Moore 
PHR 
(1998) 
Seasonal 
changes 
in 
fire 
behaviour 
in 
a 
tropical 
savanna 
in 
Northern 
Australia. 
International 
Journal 
of 
Wildland 
Fire, 
8:227–239. 


Williams 
RJ, 
Gill 
AM, 
Moore 
PHR 
(2003) 
‘Fire 
behaviour,’ 
in 
Andersen 
AN, 
Cook 
GD 
and 
Williams 
RJ 
(eds) 
Fire 
in 
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Savannas: 
the 
Kapalga 
Experiment, 
pp. 
33–46, 
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New 
York. 


Williams 
RJ, 
Bradstock 
RA, 
Cary 
GJ, 
Enright 
NJ, 
Gill 
AM, 
Liedloff 
AC, 
Lucas 
C, 
Whelan 
RJ, 
Andersen 
AN, 
Bowman 
DJMS, 
Clarke 
PJ, 
Cook 
GD, 
Hennessy 
KJ, 
York 
A 
(2009) 
Interactions 
between 
climate 
change, 
fire 
regimes 
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biodiversity 
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Williamson 
GJ, 
Todd 
ME, 
Bowman 
DMJS 
(2022) 
Double-differenced 
dNBR: 
combining 
MODIS 
and 
Landsat 
imagery 
to 
map 
fine-grained 
fire 
MOSAICS 
in 
lowland 
Eucalyptus 
savanna 
in 
Kakadu 
National 
Park, 
Northern 
Australia. 
Fire, 
5(5): 
160. 
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Zhang 
Q, 
Ge 
L, 
Zhang 
R, 
Metternicht 
GI, 
Du 
Z, 
Kuang 
J, 
Xu 
M 
(2021) 
Deep-learning-based 
burned 
area 
mapping 
using 
the 
synergy 
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Remote 
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Science 
Agency 



9 
Combined 
biomass/biochar 


The 
combined 
biomass/biochar 
workshop 
was 
held 
on 
2 
March 
2023 
with 
10 
participants. 
The 
workshop 
focused 
on 
a 
process 
flow 
requiring 
biomass 
as 
an 
input, 
and 
generating 
electricity, 
syngas 
and 
char/biochar 
by 
a 
pyrolysis 
process 
as 
outputs. 
A 
key 
challenge 
for 
this 
workshop 
was 
the 
breadth 
of 
activities 
covering 
both 
biomass 
for 
bioenergy 
and 
biomass 
for 
production 
of 
char/biochar. 
The 
multiple 
process 
flows 
encompassed 
in 
this 
breadth 
meant 
that 
the 
initial 
part 
of 
the 
workshop 
was 
dedicated 
to 
ensuring 
participants 
had 
a 
common 
understanding 
of 
the 
concepts, 
terms 
and 
the 
scope 
of 
the 
system 
under 
consideration. 
Appendix 
C.1.4 
includes 
a 
complete 
list 
of 
participants. 
Participants 
explored 
five 
technical 
innovations 
during 
the 
workshop. 
The 
current 
quantity 
of 
carbon 
sequestration 
from 
pyrolysis 
biochar 
is 
approximately 


0.01 
Mt 
per 
year 
at 
$80–$120 
per 
tonne 
(Fitch 
et 
al. 
2022, 
p. 
160). 
9.1 
Workshop 
results 
9.1.1 
Technology 
list 
Table 
9.1 
presents 
the 
technical 
innovation 
opportunities 
identified, 
and 
a 
brief 
definition 
of 
the 
opportunities 
explored 
for 
cost 
reduction. 
Note 
that 
the 
specifics 
of 
the 
technical 
innovation 
areas 
were 
not 
discussed 
or 
agreed 
to 
during 
the 
workshop 
and 
are 
the 
authors’ 
definitions. 


Table 
9.1: 
Technical 
innovation 
opportunities 
for 
carbon 
sequestration 
through 
biomass/biochar. 


TechnicalinnovationareaDescriptionCostreductionarea
Technology 
at 
scale 
Innovations 
that 
enable 
technology 
implementation 
at 
scale, 
generally 
requiring 
larger 
plant. 
A 
larger 
plant 
means 
more 
than 
1000 
tonnes 
per 
year 
biochar 
plant. 
Decreases 
the 
cost 
of 
char 
by 
improving 
the 
efficiency 
of 
production. 
Biochar 
conversion 
Lower-cost 
methods 
of 
biochar 
conversion 
result 
in 
lower 
costs 
per 
tonne 
to 
land 
users. 
Lower 
costs 
of 
operating 
the 
plant. 
Transportation 
Lower 
cost 
transportation 
for 
both 
transport 
of 
feedstocks 
and 
products 
such 
as 
syngas. 
Lower 
costs 
of 
feedstock 
by 
reducing 
transport 
costs. 


Pre-processing 
of 
feed 
Different 
feedstocks 
have 
different 
requirements 
for 
Lower 
overall 
cost 
of 
feedstock. 
for 
pyrolysis 
pre-processing 
(e.g. 
drying 
or 
pelletising). 
Innovation 


that 
reduces 
costs 
of 
pre-processing. 
Emission 
calculation 
Net 
Green 
House 
and 
other 
emissions 
associated 
Emission 
and 
calculation 
and 
standards 
with 
the 
process, 
calculation 
and 
reporting 
protocols, 
standards. 


standards 
etc. 


Syngas 
to 
liquid 
form 
Converting 
syngas 
to 
a 
readily 
transportable 
form 
(liquid). 


Large-scale 
modular 
Hub 
of 
plants 
for 
biomass 
processing 
and 
pyrolysis 
plants 
for 
biochar 
at 
significant 
volume. 


Allows 
for 
plant 
location 
in 
regional 
areas, 
close 
to 
biomass 
sources, 
potentially 
lowering 
biomass 
cost 
and 
increasing 
revenue 
from 
by-product 
production. 


Lowers 
costs 
of 
producing 
char, 
as 
well 
as 
making 
regional 
production 
hub 
costs 
economically 
viable. 


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Workshops 
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Inventory 
of 
high-
quality 
biomass 
Production 
of 
maps 
and 
types 
of 
high-quality 
biomass 
availability. 
Answers 
the 
question 
of 
what 
biomass 
is 
available 
where. 
Supports 
the 
pre-evaluation 
and 
financing 
of 
char 
production 
plants, 
perhaps 
lowering 
the 
cost 
of 
establishing 
a 
char 
production 
plant. 
Utilisation 
cases 
Identification 
of 
biochar 
utilisation 
cases 
where 
Increases 
demand 
for 
biochar. 
carbon 
will 
be 
locked 
up 
and 
generate 
demand 
and 
provide 
value. 


Guidelines 
Guidelines 
on 
choosing 
and 
making 
the 
‘right’ 
biochar. 
Increases 
efficiency 
of 
production 
and 
increase 
demand. 
Quantifying 
additional 
value 
or 
avoided 
emissions 
in 
Australian 
landscapes 
of 
biochar 
application 
The 
panel 
felt 
that 
there 
was 
value 
in 
better 
quantifying 
the 
avoided 
emissions 
and 
other 
agricultural 
benefits 
of 
the 
application 
of 
biochar 
to 
the 
land. 
Increases 
demand 
for 
biochar. 


Participants 
chose 
to 
add 
technology 
themes 
during 
the 
first 
round 
of 
the 
workshop. 
The 
themes 
added 
were: 


 
syngas 
to 
liquid 
form 
 
guidelines 
on 
choosing/making 
the 
right 
biochar 
 
additional 
value 
generated 
by 
application 
to 
soil 
to 
enhance 
productivity. 
 
Industry 
roadmap 
9.1.2 
Workshop 
outputs 
The 
most 
significant 
innovations 
were 
determined 
by 
voting 
to 
be: 


 
technology 
at 
scale 
(7 
votes) 
 
utilisation 
cases 
(5 
votes) 
 
guidelines 
(4 
votes) 
 
large-scale 
modular 
plants 
(3 
votes) 
 
emission 
calculation 
and 
standards 
(2 
votes) 
 
transportation, 
syngas 
to 
liquid 
form 
and 
roadmap 
(all 
1 
vote). 
 
biochar 
conversion 
(0 
votes) 
The 
workshop 
continuum 
results 
are 
summarised 
in 
Table 
9.2 
below. 
To 
help 
interpret 
the 
results, 
please 
see 
the 
definitions 
in 
section 
3.6. 


Table 
9.2: 
Summary 
of 
outputs 
from 
the 
biomass/biochar 
workshop. 


TechnicalinnovationareaCostreduction(%)Maturity(Year)ScalingfactorInvestmentrequired($billion)
AvgMinMaxAvgMinMaxAvgMinMaxAvgMinMax
Technology 
at 
scale 
38.8 
20 
65 
2029 
2026 
2032 
67 
6 
110 
1 
1 
1 
Large-scale 
modular 
48.2 
29 
62 
2032 
2030 
2037 
54 
4.4 
100 
1.05 
0.8 
1.2 
plants 


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Utilisation 
cases 
49 
69 
100 
2033 
2030 
2035 
10.5 
7.4 
12 
0.66 
0.1 
1.14 
Biochar 
conversion 
54.5 
50 
65 
2028 
2027 
2030 
10 
10 
10 
0.9 
0.5 
1.1 


Guidelines 
31.7 
17 
50 
2027 
2027 
2029 
10 
10 
10 
0.03 
0.01 
0.06 


The 
average 
cost 
factors 
vary 
from 
31 
to 
54%, 
with 
significant 
variation. 
For 
example, 
technology 
at 
scale 
cost 
reduction 
estimates 
range 
from 
20 
to 
65%, 
with 
an 
average 
of 
39% 
compared 
to 
current 
costs. 
Similarly, 
the 
estimates 
vary 
with 
maturity 
timeframes 
but 
are 
generally 
more 
consistent 
than 
the 
cost 
reduction 
factors. 
Most 
of 
the 
maturity 
estimates 
are 
less 
than 
10 
years. 



Figure 
9-1: 
Plot 
of 
average 
cost 
reduction 
percentages 
versus 
scaling 
factor 
for 
biomass/biochar 
technical 
innovation 
areas. 


There 
is 
no 
clear 
trend 
between 
the 
scaling 
factor 
and 
cost 
reduction 
(Figure 
9-1). 
This 
may 
an 
artefact 
of 
how 
the 
workshop 
was 
run, 
possibly 
relating 
to 
insufficient 
time 
for 
participants 
to 
reach 
consensus. 


9.1.3 
Cost 
reduction 
analysis 
Combined 
biomass/biochar 
sequestration 
cost 
areas 
or 
drivers 


The 
following 
cost 
and 
revenue 
categories 
were 
defined 
in 
preparation 
for 
the 
cost 
modelling: 


 
Establishment: 
costs 
of 
establishing 
the 
technology 
at 
a 
location, 
plant 
equipment 
and 
construction. 
 
Operations: 
ongoing 
maintenance 
costs, 
maintenance 
and 
labour. 
 
Transport: 
costs 
of 
transporting 
feedstock 
to 
pyrolysis 
plant. 
 
Feedstocks: 
costs 
of 
feedstock. 
 
Yield: 
the 
conversion 
efficiency 
of 
converting 
feedstock 
to 
char 
(tonnes 
of 
feedstock 
per 
tonne 
of 
char). 
 
Revenue: 
revenue 
obtained 
from 
selling 
the 
char 
produced, 
electricity 
and 
gas 
co-
produced, 
and 
carbon 
credits. 
The 
workshop 
cost 
factors 
were 
then 
assigned 
to 
the 
cost 
areas 
defined 
above 
and 
presented 
in 
Table 
9.3. 
Where 
the 
technical 
innovation 
areas 
do 
not 
change 
any 
of 
the 
cost 
of 
revenue 
areas, 
the 
cell 
in 
the 
table 
is 
left 
blank. 


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Workshops 
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Table 
9.3: 
Cost 
reduction 
factors 
for 
biomass/biochar 
technical 
innovation 
areas. 
All 
factors 
are 
percentage 
reductions 
(costs) 
or 
increases 
(revenues) 
relative 
to 
current 
costs. 


Technical 
innovation 
area 
Costs 
Revenues 
Establishment 
Operations 
Transport 
Biochar 
Technology 
at 
scale 
(%) 
–39 
(%) 
39 
(%) 
– 
price 
(%) 
– 
Large-scale 
modular 
–48 
– 
–48 
– 
plants 
Utilisation 
cases 
– 
– 
– 
49 
Biochar 
conversion 
– 
–55% 
– 
– 
Guidelines 
– 
– 
– 
32 


Where 
a 
cost 
reduction 
factor 
can 
reduce 
several 
cost 
reduction 
areas, 
it 
is 
applied 
to 
all 
applicable 
areas. 
For 
example, 
technology 
at 
scale 
has 
the 
potential 
to 
lower 
both 
the 
establishment 
and 
operational 
costs 
of 
projects. 


Cost 
model 


The 
outputs 
from 
the 
biomass/biochar 
workshop 
are 
translated 
into 
comparable 
results 
using 
a 
simplified 
cash 
flow 
model 
to 
determine 
changes 
to 
NPV 
and 
the 
cost 
per 
tonne 
of 
sequestration 
for 
an 
indicative 
project. 
The 
model 
allows 
the 
partitioning 
of 
costs 
to 
cost 
areas 
(as 
defined 
above), 
allowing 
cost 
reductions 
to 
be 
applied 
selectively 
to 
the 
relevant 
cost 
area 
and 
for 
the 
lifetime 
cost 
reductions 
(in 
this 
case, 
over 
25 
years) 
to 
be 
converted 
to 
NPVs. 


There 
are 
many 
possible 
feedstock 
and 
process 
flows 
that 
can 
lead 
to 
production 
of 
char/biochar 
and 
bioenergy. 
For 
the 
purpose 
of 
this 
report, 
a 
medium-sized 
biochar 
production 
system 
located 
in 
NSW 
with 
a 
feedstock 
of 
sawmill 
residue 
was 
modelled. 
It 
is 
not 
possible 
to 
model 
all 
possibilities 
and 
having 
an 
indicative 
scenario 
allows 
the 
cost 
reductions 
and 
cost 
sensitivities 
to 
be 
determined. 


The 
hypothetical 
biochar 
production 
system 
is 
a 
medium 
sized 
(1 
MWh) 
slow-pyrolysis 
system 
with 
fixed 
bed 
twin-fire 
pyrolyser. 
We 
assume 
this 
type 
of 
system 
because:(1) 
its 
medium 
size 
means 
that 
there 
is 
likely 
sufficient 
feedstock 
to 
run 
the 
system 
in 
several 
Australian 
regions; 
and 


(2) 
Homagain 
et 
al. 
(2016) 
used 
this 
type 
of 
system 
for 
their 
economic 
assessment 
of 
biochar 
production 
in 
Canada, 
providing 
some 
cost 
data 
for 
this 
analysis. 
We 
assume 
that 
the 
biochar 
produced 
is 
applied 
into 
agricultural 
fields. 
Rajabi 
Hamedani 
et 
al. 
(2019) 
provide 
the 
following 
inventory 
for 
1 
tonne 
of 
biochar 
obtained 
via 
willow 
pyrolysis 
and 
applied 
into 
fields. 
Note, 
in 
our 
analysis 
we 
assume 
that 
woodchips 
from 
sawmill 
residue 
log 
rather 
than 
willow 
woodchips 
are 
used 
as 
a 
feedstock 
and 
assume 
that 
the 
pyrolysis 
requirements 
are 
the 
the 
same. 


 
Inputs: 
willow 
woodchips 
3.73 
t; 
heat 
(pyrolysis) 
1.92 
GJ 
 
Outputs: 
biochar 
1 
t; 
syngas 
(SO2 
0.015 
kg; 
NOx 
0.2 
kg) 
 
Avoided 
products: 
natural 
gas 
0.37 
t; 
electricity 
1.01 
GJ; 
N 
fertiliser 
0.66 
kg; 
K 
fertiliser 
0.13 
kg; 
P 
fertiliser 
0.1 
kg 
 
Avoided 
emissions 
from 
the 
application 
of 
1 
t 
of 
biochar 
into 
fields: 
2.2 
t 
CO2 
and 
2.6 
kg 
N20, 
which 
combine 
for 
total 
avoided 
emissions 
of 
2.975 
t 
CO2-e 
We 
assume 
that 
the 
production 
plant 
will 
be 
operational 
for 
25 
years 
(Homagain 
et 
al. 
2016) 
and 
will 
have 
7000 
working 
hours 
per 
year 
(Rajabi 
Hamedani 
et 
al. 
2019). 
As 
such, 
the 
plant 
produces 


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| 
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13,125 
tonnes 
of 
biochar 
per 
year, 
which 
requires 
48,956 
tonnes 
of 
sawmill 
residue 
log 
per 
year 
as 
feedstock. 
Based 
on 
NSW 
sawmill 
residues 
data,5 
there 
are 
several 
regions 
in 
NSW 
that 
have 
over 
50,000 
tonnes 
of 
sawmill 
residue 
log 
within 
a 
few 
hundred 
kilometres 
of 
a 
hypothetical 
production 
plant. 


We 
assume 
that 
the 
production 
system 
starts 
with 
the 
purchase 
and 
transportation 
of 
the 
feedstock 
to 
the 
plant 
and 
ends 
with 
the 
production 
of 
biochar, 
which 
is 
then 
stored 
on 
site. 
That 
is, 
we 
exclude 
the 
sale 
and 
transportation 
of 
biochar 
and 
its 
co-products 
(fertilisers, 
SO2, 
NOx) 
from 
the 
model, 
as 
the 
feasibility 
and 
costs 
of 
selling 
these 
products 
in 
different 
regions 
are 
unknown. 


Full 
details 
of 
the 
model 
used 
are 
described 
in 
Appendix 
D. 


Cost 
analysis 


The 
results 
of 
the 
modelling 
are 
listed 
in 
Table 
9.4. 
The 
cost 
reductions 
are 
the 
difference 
in 
cost 
in 
$ 
per 
tonne 
compared 
to 
the 
baseline. 


Table 
9.4: 
Cost 
reductions 
for 
biomass/biochar 
technical 
innovation 
areas. 


TechnicalinnovationareaCostreductionfrombaseline($pertonne)
Netcost($pertonne)
Baselinecost060
Technology 
at 
scale 
–10.2 
49 
Large-scale 
modular 
plants 
–14.7 
45 
Utilisation 
cases 
0 
60 
Biochar 
conversion 
–11 
48 
Guidelines 
0 
60 


From 
the 
modelling, 
the 
baseline 
cost 
was 
determined 
to 
be 
$60 
per 
tonne. 
This 
compares 
well 
to 
the 
estimate 
provided 
in 
the 
phase 
1 
report 
of 
$80 
to 
$120 
per 
tonne 
(Fitch 
et 
al. 
2022, 
p. 
160), 
noting 
that 
the 
modelled 
scenario 
is 
for 
a 
plant 
producing 
approximately 
13,000 
tonnes 
of 
biochar 
per 
year, 
which 
is 
similar 
in 
magnitude 
to 
the 
current 
national 
production. 


The 
innovation 
area 
with 
the 
greatest 
potential 
to 
lower 
the 
cost 
of 
carbon 
sequestration 
over 
the 
life 
of 
a 
project 
is 
large-scale 
modular 
plants, 
with 
a 
cost 
reduction 
of 
$14.70 
per 
tonne 
compared 
to 
the 
baseline, 
followed 
by 
biochar 
conversion 
methods, 
with 
a 
cost 
reduction 
of 
$11 
per 
tonne 
(Figure 
9-2). 
Utilisation 
cases 
and 
guidelines 
were 
modelled 
as 
having 
benefits 
to 
the 
demand 
for 
char/biochar, 
so 
there 
was 
no 
effect 
on 
cost 
reduction. 


5 
https://spatial.industry.nsw.gov.au/arcgis/rest/services/Bioenergy_Assessment/Forestry_SawmillResidues/MapServer 


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Workshops 
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Figure 
9-2: 
Bar 
graph 
of 
cost 
reductions 
for 
biomass/biochar 
technical 
innovation 
areas. 


9.1.4 
Cost 
reduction, 
maturity 
and 
scale 
Figure 
9-3 
summarises 
the 
outputs 
of 
the 
workshop 
on 
one 
chart. 
The 
x-axis 
represents 
the 
year 
of 
maturity, 
the 
y-axis 
the 
cost 
reduction 
per 
tonne 
of 
CO2 
sequestration, 
and 
the 
size 
of 
the 
bubble 
represents 
the 
scaling 
factor. 
As 
described 
in 
1.1 
the 
most 
beneficial 
innovation 
are 
those 
that 
mature 
early 
with 
higher 
scaling 
factor. 
Innovation 
that 
enable 
Technology 
at 
scale 
and 
Large 
scale 
modular 
plants 
both 
have 
good 
cost 
reduction 
potential. 



80 
| 
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Agency 



Figure 
9-3: 
Comparison 
of 
technology 
cost 
reduction, 
year 
of 
maturity 
and 
scaling 
factor 
for 
biomass/biochar 
technical 
innovation 
areas. 


9.1.5 
Sensitivity 
analysis 
of 
cash 
flow 
model 
The 
sensitivity 
analysis 
presented 
below 
identifies 
those 
cost 
areas 
with 
the 
greatest 
potential 
to 
improve 
economic 
viability. 
The 
results 
represent 
pyrolysis/char 
production 
systems 
and 
are 
useful 
in 
understanding 
the 
key 
opportunities 
to 
improve 
profitability 
and 
cost 
reductions. 


In 
the 
analysis 
presented 
in 
Figure 
9-4, 
different 
model 
cost 
parameters 
were 
varied 
in 
four 
steps 
relative 
to 
the 
baseline: 
–10%, 
–5%, 
+5% 
and 
+10%. 
The 
changes 
to 
NPV 
as 
a 
percentage 
of 
the 
baseline 
are 
presented 
as 
a 
colour-coded 
heatmap. 
In 
addition 
to 
the 
cost 
areas 
defined 
in 
section 
9.1.3, 
other 
costs 
and 
revenues 
included 
in 
the 
modelling 
are: 


 
electricity: 
cost 
of 
electricity 
required 
for 
pyrolysis 
 
natural 
gas: 
revenue 
for 
syngas 
produced. 
Figure 
9-4: 
Sensitivity 
analysis 
of 
the 
cash 
flow 
model 
for 
biomass/biochar 
sequestration 
projects. 


An 
interesting 
outcome 
of 
this 
modelling 
analysis 
is 
that 
the 
establishment 
costs 
have 
a 
relatively 
small 
impact 
on 
NPV, 
which 
is 
different 
to 
planted 
vegetation 
where 
these 
costs 
are 
a 
significant 
driver. 
NPV 
is 
most 
sensitive 
to 
changes 
in 
yield, 
that 
is, 
feedstock 
conversion 
efficiency 
to 
char. 
Feedstock 
costs, 
natural 
gas 
prices 
and 
electricity 
costs 
are 
also 
significant 
drivers. 


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Workshops 
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| 
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Figure 
9-5: 
Sensitivity 
analysis 
of 
sequestration 
costs 
for 
biomass/biochar 
sequestration 
projects. 


Regarding 
cost 
reduction 
drivers, 
conversion 
yield 
has 
the 
most 
significant 
opportunity 
to 
reduce 
costs, 
followed 
by 
feedstock 
costs. 
Transport 
costs 
are 
also 
a 
driver, 
with 
the 
implication 
that 
it 
is 
important 
to 
select 
the 
plant’s 
location 
such 
that 
a 
suitable 
supply 
of 
low-cost 
feedstock 
is 
proximally 
available 
in 
order 
to 
keep 
transport 
costs 
low. 


9.1.6 
Scaling 
and 
maturity 
analysis 
The 
relative 
sequestration 
benefit 
compares 
the 
different 
technology 
options 
to 
identify 
the 
option 
that 
generates 
the 
greatest 
additional 
sequestration 
at 
different 
end 
years. 
The 
method 
to 
derive 
this 
metric 
is 
detailed 
in 
4.2. 
The 
relative 
sequestration 
benefit 
is 
calculated 
using 
scaling 
factors 
and 
maturity 
time 
frames 
determined 
during 
the 
workshop. 


Table 
9.5: 
Relative 
sequestration 
benefit 
for 
each 
biomass/biochar 
technical 
innovation 
area. 


Technicalinnovationarea2030203520402050
Technology 
at 
scale 
1.0 
1.0 
1.0 
1.0 
Large-scale 
modular 
plants 
0.0 
0.4 
0.6 
0.7 
Utilisation 
cases 
0.1 
0.0 
0.1 
0.1 


Biochar 
conversion 
0.2 
0.2 
0.2 
0.1 
Guidelines 
0.4 
0.2 
0.2 
0.2 


The 
technology 
option 
with 
the 
potential 
to 
deliver 
the 
greatest 
additional 
sequestration 
benefit 
in 
all 
possible 
end 
years 
is 
technology 
at 
scale, 
followed 
by 
large-scale 
modular 
plants. 
The 
scaling 
factor 
(64) 
and 
early 
maturity 
date 
(2029) 
are 
the 
drivers. 


9.1.7 
Assumptions 
and 
limitations 
of 
the 
analysis 
The 
modelling 
used 
in 
this 
section 
assumes 
that 
the 
production 
system 
starts 
with 
the 
purchase 
and 
transportation 
of 
the 
feedstock 
to 
the 
plant 
and 
ends 
with 
the 
production 
of 
biochar, 
which 
is 
then 
stored 
on 
site. 
That 
is, 
we 
exclude 
the 
sale 
and 
transportation 
of 
biochar 
and 
its 
co-products 
(fertilisers, 
SO2, 
NOx) 
from 
the 
model 
as 
the 
feasibility 
and 
costs 
of 
selling 
these 
products 
in 


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| 
CSIRO 
Australia’s 
National 
Science 
Agency 



different 
regions 
are 
unknown. 
NSW 
is 
used 
as 
an 
exemplar 
study 
region, 
with 
results 
indicative 
for 
the 
national 
context. 
The 
feedstock 
used 
is 
sawmill 
residue, 
and 
a 
full 
list 
of 
costs 
and 
parameters 
can 
be 
seen 
in 
Appendix 
E.3. 
Like 
all 
modelling, 
it 
is 
sensitive 
to 
the 
selection 
of 
parameters. 


9.2 
Analysis 
of 
implementation 
steps 
As 
with 
previous 
chapters, 
this 
section 
reviews 
the 
implementation 
steps 
captured 
during 
the 
workshop. 


9.2.1 
Technology 
at 
scale 
The 
first 
implementation 
steps 
for 
technology 
at 
scale 
are 
exemplars 
or 
pilots. 
These 
steps 
are 
relatively 
straightforward 
to 
implement 
and 
were 
rated 
very 
easy 
to 
easy. 
The 
investment 
required 
is 
$10–25 
million. 
Two 
scaling 
hurdles 
were 
identified: 
the 
need 
to 
convert 
syngas 
into 
a 
liquid 
form 
to 
reduce 
transport 
costs 
and 
improve 
the 
economic 
viability 
of 
the 
plant, 
and 
the 
scale-up 
opportunity 
to 
convert 
syngas 
to 
hydrogen. 
These 
steps 
are 
rated 
as 
moderate 
to 
hard 
in 
complexity. 
Overall, 
the 
implementation 
is 
rated 
as 
moderate. 


9.2.2 
Large-scale 
modular 
plant 
Large-scale 
modular 
plants 
require 
both 
technological 
and 
commercial/financial 
implementation 
steps. 
The 
implementation 
steps 
identified 
for 
large-scale 
modular 
plants 
most 
relate 
to 
improving 
the 
commercial 
readiness 
level 
through 
economic 
studies 
and 
commercial-scale 
demonstrations. 
Strictly 
speaking, 
these 
implementation 
steps 
are 
outside 
the 
scope 
of 
the 
workshop. 
There 
are 
a 
couple 
of 
technical 
challenges 
though 
they 
were 
not 
articulated. 
These 
are: 


 
cost-effective 
design 
of 
a 
modular 
plant 
 
development 
of 
cost-effective 
conversion 
approaches 
for 
syngas 
to 
hydrogen 
and 
a 
liquid 
form 
suitable 
for 
transportation. 
9.2.3 
Utilisation 
cases 
The 
utilisation 
cases 
aim 
to 
grow 
the 
market 
for 
char 
and 
biochar 
by 
identifying 
biochar 
utilisation 
cases 
where 
carbon 
will 
be 
locked 
up 
but 
provided 
demand 
and 
value. 
The 
implementation 
steps 
listed 
varied 
in 
difficulty, 
investment 
and 
timeframe. 
Most 
implementation 
steps 
focused 
on 
the 
idea 
of 
building 
exemplars 
from 
field 
trials 
to 
commercial-scale 
demonstrators. 
No 
specific 
technology 
steps 
were 
identified 
other 
than 
cost-effective 
design, 
rated 
as 
easy 
with 
an 
investment 
required 
of 
$200,000 
to 
$450 
million. 
Implementation 
complexity 
is 
rated 
as 
low. 


9.2.4 
Biochar 
conversion 
Implementation 
steps 
for 
biochar 
conversion 
approaches 
were 
not 
discussed 
during 
the 
workshop. 


9.2.5 
Guidelines 
This 
area 
relates 
to 
utilisation 
cases 
in 
which 
guidelines 
are 
needed 
for 
each 
utilisation 
case. 
Guidelines 
are 
required 
to 
choose 
and 
make 
the 
‘right’ 
biochar. 
The 
implementation 
steps 
listed 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
83 



are 
all 
rated 
as 
easy 
and 
range 
from 
identifying 
knowledge 
gaps 
to 
researching 
to 
fill 
those 
gaps. 
The 
need 
for 
standards 
was 
also 
raised 
to 
ensure 
that 
the 
properties 
of 
the 
product 
(and 
therefore 
the 
benefits) 
can 
be 
guaranteed. 
Implementation 
complexity 
is 
rated 
as 
low. 


9.3 
Ranking 
Table 
9.6: 
Ranking 
of 
technical 
innovation 
areas 
for 
biomass/biochar 
carbon 
sequestration. 


TechnicalinnovationareaCostreduction($pertonne)
Scalingandmaturityrelativebenefit(2050)
ImplementationcomplexityRanking
Large-scale 
modular 
plants 
–14.7 
0.7 
Moderate 
1 


Technology 
at 
scale 
–10.2 
1.0 
Moderate 
2 
Biochar 
conversion 
–11 
0.1 
Not 
discussed 
3 


Guidelines 
0 
0.2 
Not 
discussed 
4 
Utilisation 
cases 
0 
0.1 
Low 
5 


The 
final 
ranking 
for 
technology 
options 
is 
listed 
above. 
Although 
large-scale 
modular 
plants 
have 
the 
most 
significant 
potential 
to 
reduce 
carbon 
sequestration 
costs, 
technology 
at 
scale 
can 
potentially 
deliver 
the 
greatest 
additional 
sequestration 
due 
to 
the 
more 
significant 
scaling 
factor. 


9.4 
Discussion 
The 
four 
options 
reviewed 
during 
the 
workshop 
combine 
technical 
and 
non-technical 
(mainly 
financial 
or 
economic) 
aspects. 
It 
is 
not 
surprising 
that 
much 
of 
the 
discussion 
during 
the 
workshop 
centred 
on 
the 
need 
for 
medium-to 
large-scale 
demonstrators 
to 
facilitate 
building 
scale 
and 
lowering 
the 
costs 
of 
production 
rather 
than 
any 
specific 
technology 
needs. 
Increased 
scaling 
can 
be 
driven 
by 
both 
reducing 
costs, 
and 
increasing 
demand 
for 
char 
and 
biochar. 
The 
development 
of 
utilisation 
(use) 
cases 
will 
support 
market 
expansion 
for 
char 
products 
by 
clarifying 
the 
economic 
viability 
and 
co-benefits 
of 
early 
stage 
investments. 


Technical 
innovation 
needs 
or 
barriers 
were 
identified 
during 
the 
workshop 
but 
were 
not 
explicitly 
discussed. 
The 
need 
to 
develop 
cost-effective 
approaches 
to 
convert 
syngas 
to 
a 
more 
readily 
transportable 
form, 
as 
well 
as 
technical 
innovation 
to 
support 
hydrogen 
generation, 
were 
both 
identified 
as 
needs 
by 
the 
participants. 
Other 
needs 
regarding 
scaling 
are 
related 
to 
engineering 
existing 
approaches 
and 
making 
the 
plants 
more 
cost-effective. 
Other 
technical 
areas 
for 
progress 
that 
were 
identified 
but 
not 
explicitly 
discussed 
were 
determining 
the 
optimal 
location 
of 
plants 
in 
relation 
to 
biomass 
for 
feedstock, 
transport 
and 
electrical 
networks 
to 
support 
distribution 
and 
input 
needs, 
and 
decision 
support 
for 
feedstock 
selection 
and 
for 
optimising 
the 
pyrolysis 
process 
to 
produce 
outputs 
with 
the 
required 
properties. 


Key 
messages 


 
All 
options 
looked 
to 
have 
the 
potential 
to 
lower 
costs 
either 
through 
reducing 
costs 
or 
improving 
the 
overall 
economic 
viability 
of 
char 
production. 
The 
cost 
reductions 
ranged 
from 
$11 
to 
$14.70 
per 
tonne, 
with 
large-scale 
modular 
plants 
having 
the 
largest 
cost 
reduction 
potential. 
84 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



 
The 
baseline 
cost 
($60 
per 
tonne) 
used 
in 
this 
analysis 
is 
lower 
than 
the 
$80 
to 
$120 
per 
tonne 
reported 
in 
chapters 
of 
Fitch 
et 
al. 
(2022). 
The 
lower 
cost 
reflects 
the 
larger-scale 
plant 
used 
for 
this 
analysis 
(13,000 
tonnes 
per 
year). 
 
There 
was 
a 
sentiment 
during 
the 
workshop 
that 
most 
of 
the 
technical 
challenges 
have 
been 
solved 
(i.e. 
the 
industry 
knows 
how 
to 
produce 
char) 
and 
that 
the 
obstacles 
to 
scaling 
the 
output 
relate 
to 
increasing 
the 
commercial 
readiness 
level 
and 
confidence 
in 
economic 
viability. 
 
There 
are 
opportunities 
to 
grow 
the 
demand 
for 
biochar 
by 
better 
identifying 
utilisation 
cases 
and 
articulating 
the 
co-benefits 
of 
use. 
 
There 
are 
specific 
technical 
areas 
identified 
during 
the 
workshop 
that 
could 
aid 
in 
lower 
sequestration 
costs. 
These 
are: 
o 
cost-effective 
methods 
to 
convert 
syngas 
to 
a 
more 
readily 
transportable 
product 
o 
decision 
support 
for 
process 
optimisation 
o 
decision 
support 
for 
plant 
location, 
including 
as 
part 
of 
a 
regional 
hub. 
9.5 
References 
Fitch 
P, 
Battaglia 
M, 
Lenton 
A, 
Feron 
P, 
Gao 
L, 
Mei 
Y, 
Hortle 
A, 
Macdonald 
L, 
Pearce 
M, 
Occhipinti 
S, 
Roxburgh 
S, 
Steven 
A 
(2022) 
Australia’s 
carbon 
sequestration 
potential: 
a 
stocktake 
and 
analysis 
of 
sequestration 
technologies, 
CSIRO, 
Canberra. 


Homagain 
K, 
Shahi 
C, 
Luckai 
N, 
Sharma 
M 
(2016) 
Life 
cycle 
cost 
and 
economic 
assessment 
of 
biochar-based 
bioenergy 
production 
and 
biochar 
land 
application 
in 
Northwestern 
Ontario, 
Canada. 
Forest 
Ecosystems, 
3:21. 


Rajabi 
Hamedani 
S, 
Kuppens 
T, 
Malina 
R, 
Bocci 
E, 
Colantoni 
A, 
Villarini 
M 
(2019) 
Life 
cycle 
assessment 
and 
environmental 
valuation 
of 
biochar 
production: 
two 
case 
studies 
in 
Belgium, 
Energies, 
12(11): 
2166. 


Roxburgh 
S, 
England 
J, 
Evans 
D, 
Nolan 
M, 
Opie 
K, 
Paul 
K, 
Reeson 
A, 
Cook 
G, 
Thomas 
D 
(2020) 
Potential 
future 
supply 
of 
carbon 
offsets 
in 
the 
land 
sector 
in 
Australia, 
CSIRO, 
Canberra. 


Young 
P, 
Lawrence 
J, 
Batista 
R, 
Jensen-Fellows 
A, 
Richard 
B, 
Sheridan 
T 
(2019) 
Biochar 
market 
profile 
report. 
Worccester 
Polytechnic 
Institute 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
85 



10 
Carbon 
capture 
and 
storage 


This 
chapter 
reports 
on 
the 
carbon 
capture 
and 
storage 
(CCS) 
workshop 
held 
on 
8 
March 
2023 
with 
11 
participants 
from 
industry, 
academia 
and 
government. 
Appendix 
C, 
section 
C1., 
includes 
a 
list 
of 
workshop 
participants. 
This 
section 
of 
the 
report 
is 
different 
to 
the 
other 
chapters 
due 
to 
some 
differences 
with 
how 
the 
workshop 
proceeded. 
As 
for 
the 
combined 
biomass/biochar 
workshop, 
considerable 
time 
was 
taken 
up 
developing 
a 
common 
language 
and 
understanding 
of 
the 
concepts 
and 
scope 
for 
discussion. 


10.1Workshop 
differences 


The 
Delphi 
process 
is 
predicated 
on 
the 
assumption 
that 
a 
clear 
set 
of 
propositions 
can 
be 
identified 
early 
on, 
followed 
by 
a 
cycle 
of 
voting–discussion–voting. 
In 
discussion 
with 
the 
panel 
of 
CCS 
experts, 
this 
proved 
challenging 
with 
good 
cause. 


In 
initial 
polling, 
the 
panel 
identified 
three 
topics 
as 
important. 
These 
were 
cheaper 
CO2 
capture, 
optimised 
storage, 
and 
hubs 
(a 
CCS 
hub 
is 
a 
central 
collection 
or 
distribution 
point 
for 
CO2, 
Global 
CCS 
Institute, 
2016) 
. 
In 
a 
later 
discussion, 
a 
panel 
member 
argued 
that 
the 
transport 
of 
CO2 
should 
also 
have 
been 
discussed. 
Accepting 
this 
point, 
the 
panel 
identified 
that 
improvements 
were 
desirable 
in 
the 
main 
components 
of 
the 
CCS 
chain 
– 
capture, 
transport, 
storage 
and 
system 
integration. 
The 
subsequent 
discussion 
failed 
to 
reach 
a 
consensus 
on 
key 
topics 
within 
these 
general 
areas. 
This 
was 
not 
a 
failure 
– 
rather, 
it 
revealed 
complex 
interactions 
that 
will 
guide 
the 
process 
going 
forward. 
Whenever 
discussion 
began 
to 
isolate 
a 
topic, 
a 
typical 
response 
from 
a 
panel 
member 
was 
to 
point 
out, 
in 
effect, 
that 
‘context 
is 
everything’ 
and 
that 
it 
made 
little 
sense 
to 
treat 
one 
technology 
as 
important 
in 
isolation 
from 
others. 


This 
reflects 
the 
fact 
that 
CCS 
is 
an 
industry 
made 
of 
mature 
components. 
Most 
have 
been 
used 
in 
oil 
and 
gas 
or 
chemical 
engineering 
for 
a 
long 
time. 
Integrating 
these 
components, 
at 
a 
large 
scale, 
for 
the 
entire 
CCS 
chain 
is 
a 
less 
mature 
process 
but 
far 
from 
novel 
or 
unproven. 
Cost 
reductions 
in 
CCS 
will 
likely 
come 
about 
by 
numerous 
small 
improvements 
throughout 
the 
processing 
chain: 


it 
is 
the 
execution 
of 
large 
projects 
that 
is 
the 
key 
to 
‘learning 
by 
doing’ 
and 
consequent 
cost 
reduction. 
While 
breakthrough 
technologies 
cannot 
be 
ruled 
out, 
it 
is 
significant, 
for 
example, 
that 
one 
promising 
new 
component 
of 
the 
CCS 
chain 
is 
nothing 
more 
than 
the 
development 
of 
economically 
viable 
transport 
of 
CO2 
by 
ship 
– 
scarcely 
a 
new 
technology. 


It 
follows 
that 
improvements 
in 
CCS 
may 
be 
expected 
to 
be 
incremental 
(which 
is 
not 
the 
same 
as 
unimportant), 
to 
occur 
throughout 
the 
processing 
chain 
and 
to 
produce 
relatively 
modest 
cost 
reductions. 
None 
of 
this 
will 
occur 
without 
executing 
large 
projects. 


Although 
large-scale 
projects 
will 
be 
needed 
to 
achieve 
technological 
maturity, 
there 
are 
nonetheless 
narrower 
technical 
areas 
that 
may 
be 
important. 
The 
panel 
debated 
these 
at 
some 
length, 
noting 
forcefully 
the 
importance 
of 
project 
context. 


The 
emphasis 
on 
learning 
by 
doing, 
context 
and 
incremental 
improvement 
in 
costs 
is 
reflected 
in 
a 
horizon-scanning 
exercise 
undertaken 
as 
an 
IEAGHG 
study 
(Orchard 
et 
al. 
2021). 
This 
study 
projected 
operational 
cost 
reductions 
by 
2040 
in 
the 
20–30% 
range, 
resulting 
from 
a 
combination 
of 
factors, 
including 
smarter 
materials, 
additive 
manufacturing, 
and 
more 
effective 
operations 
and 
maintenance, 
resulting 
from 
the 
use 
of 
the 
Internet 
of 
Things, 
virtual 
reality 
and 
artificial 
intelligence. 
However, 
no 
breakthrough 
technologies 
were 
identified. 


86 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



10.2Workshop 
findings 


10.2.1 
CO2 
capture 


In 
the 
Australian 
context, 
much 
CCS 
will 
be 
part 
of 
natural 
gas 
processing, 
and 
the 
capture 
technologies 
are 
mature. 
‘Hard 
to 
abate’ 
emitters, 
especially 
steel 
and 
cement 
processing, 
are 
a 
research 
opportunity. 
Direct 
air 
capture 
is 
emerging 
as 
an 
unavoidable 
technology. 
Research 
into 
capture 
technologies 
is 
an 
extensive 
area 
worldwide. 
Research 
and 
development 
within 
Australia, 
with 
more 
modest 
resources, 
would 
need 
to 
be 
focused 
on 
solving 
distinctively 
Australian 
problems. 
An 
example 
of 
a 
specific 
problem 
is 
the 
high 
SO2 
level 
in 
Australian 
coal-fired 
power 
flue 
gas, 
a 
consequence 
more 
of 
regulations 
than 
chemistry. 


10.2.2 
Optimised 
storage 
Optimised 
storage 
is 
a 
good 
example 
of 
context 
being 
everything. 
Optimised 
with 
respect 
to 
what? 
Any 
actual 
project 
will 
have 
many 
constraints 
and 
multiple 
objectives. 
There 
are 
opportunities 
for 
the 
much 
narrower 
objectives 
of 
improving 
injectivity 
and 
sweep 
(and 
hence 
attainable 
storage 
capacity). 
However, 
‘capacity’ 
itself 
is 
a 
context-dependent 
concept: 
a 
project 
may 
only 
need 
to 
store 
what 
can 
feasibly 
be 
captured. 
If 
current 
storage 
methods 
can 
achieve 
that, 
no 
improvements 
are 
required. 
Likewise, 
monitoring 
and 
verification 
of 
storage 
could 
conceivably 
be 
improved, 
but 
the 
objectives 
are 
diverse 
– 
lower 
cost, 
more 
social 
acceptance 
or 
greater 
sensitivity 
are 
potential 
objectives 
among 
many. 


10.2.3 
CO2 
hubs 


By 
connecting 
multiple 
sources 
with 
multiple 
sinks, 
hubs 
reduce 
operational 
risks 
by 
adding 
redundancy 
and 
giving 
economies 
of 
scale 
for 
infrastructure. 
The 
development 
of 
hubs 
is 
at 
an 
early 
stage, 
but 
international 
examples 
are 
already 
progressing. 
Hubs 
are 
clear 
examples 
of 
system-level 
improvement 
involving 
developments 
and 
enhancements 
across 
the 
entire 
CCS 
chain. 
They 
are 
public-good 
infrastructures 
that 
must 
be 
initiated, 
designed 
and 
built 
with 
strong 
leadership 
from 
governments 
at 
all 
levels. 


Finally, 
while 
‘institutional 
factors’ 
were 
out 
of 
scope 
for 
this 
workshop, 
they 
are 
inseparable 
from 
the 
consideration 
of 
large 
CCS 
projects 
and 
especially 
hubs. 
Accepting 
that 
the 
primary 
need 
is 
for 
‘learning 
by 
doing’ 
means 
that 
large 
projects 
need 
to 
be 
facilitated 
by 
governments 
both 
financially 
and 
institutionally. 
This 
would 
include 
matters 
such 
as 
sustained 
and 
consistent 
policy 
objectives, 
stable 
carbon 
pricing 
and 
trading, 
and 
a 
well 
understood 
and 
predictable 
regulatory 
framework 
for 
CCS. 
These 
are 
not 
more 
important 
than 
technology, 
but 
they 
are 
as 
essential. 


10.2.4 
Indicative 
costs 
Several 
think 
tanks 
(e.g. 
the 
International 
Energy 
Agency 
and 
the 
Clean 
Air 
Task 
Force, 
among 
others) 
have 
provided 
estimates 
of 
the 
costs 
per 
tonne 
of 
CO2 
at 
which 
various 
types 
of 
CCS 
could 
break 
even 
financially. 
These 
are 
costs 
for 
Nth-of-a-kind 
projects 
and 
presume 
incremental 
improvement. 
This 
is 
the 
expectation 
for 
a 
mature 
technology 
(see 
Orchard 
et 
al. 
2021). 
These 
estimates 
focus 
on 
capture, 
which 
(apart 
from 
the 
nature 
of 
the 
source) 
is 
less 
affected 
by 
contingent 
factors. 
Transport 
and 
storage 
will 
depend 
more 
strongly 
on 
local 
conditions, 
mainly 
the 
distance 
to 
a 
suitable 
storage 
site. 
The 
key 
message 
is 
that 
capture 
costs 
can 
vary 
widely, 
depending 
on 
the 
source. 
Within 
the 
USA, 
many 
types 
of 
projects 
will 
become 
viable 
now 
that 
the 
US$85/tonne 
tax 
credit 
is 
in 
force. 
The 
longevity 
of 
this 
crediting 
arrangement 
is 
important 
as 
it 


Sequestration 
Cost 
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Workshops 
Report 
| 
87 



extends 
to 
projects 
commenced 
by 
2033. 
This 
certainty 
is 
extremely 
important 
for 
project 
developers, 
especially 
as 
permitting 
delays 
are 
feared 
to 
be 
considerable. 
In 
Europe, 
CO2 
prices 
have 
risen 
to 
100 
Euro/tonne 
but 
are 
very 
volatile; 
hence, 
there 
is 
a 
risk 
premium 
that 
increases 
the 
carbon 
price 
at 
which 
project 
developers 
will 
embark 
on 
CCS. 


10.3References 


Global 
CCS 
Institute 
2016, 
The 
Global 
Status 
of 
CCS. 
Special 
Report: 
Understanding 
Industrial 
CCS 
Hubs 
and 
Clusters, 
Melbourne, 
Australia. 


Orchard 
K, 
Simon 
R, 
Durusut 
E, 
Neades 
S, 
Kemper 
J 
(2021) 
‘Value 
of 
emerging 
and 
enabling 
technologies 
in 
reducing 
costs, 
risks 
and 
timescales 
for 
CCS,’ 
15th 
International 
Conference 
on 
Greenhouse 
Gas 
Control 
Technologies, 
GHGT-15 
proceedings. 


88 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



11 
Mineral 
carbonation 


This 
chapter 
outlines 
the 
activities 
and 
outcomes 
of 
the 
mineral 
carbonation 
workshop, 
which 
was 
held 
on 
5 
April 
2023 
with 
14 
participants. 
Appendix 
C, 
C.1.6, 
includes 
a 
full 
list 
of 
workshop 
participants. 
Section 
3 
presents 
the 
detailed 
workshop 
methodology. 


Mineral 
carbonation 
is 
a 
term 
used 
to 
describe 
the 
formation 
of 
stable 
carbonate 
minerals 
by 
the 
reaction 
of 
CO2 
with 
divalent 
alkaline 
earth 
metal 
cations. 
Mineral 
carbonation 
reactions 
occur 
very 
slowly 
in 
nature 
as 
a 
part 
of 
the 
rock 
weathering 
cycle. 
These 
reactions 
can 
be 
‘engineered’ 
or 
accelerated 
by 
injecting 
CO2 
into 
mafic 
or 
ultramafic 
rock 
formations, 
combining 
concentrated 
CO2 
with 
crushed 
silicate 
materials 
or 
ultramafic 
tailings, 
or 
by 
applying 
crushed 
silicate 
rock 
on 
soil 
to 
passively 
interact 
with 
atmospheric 
CO2. 
Considering 
Australia’s 
unique 
geology, 
engineered 
mineral 
carbonation 
is 
an 
emerging 
CO2 
sequestration 
method 
with 
great 
potential, 
which 
requires 
further 
research 
and 
technology 
innovation 
to 
be 
fully 
realised. 


The 
aim 
of 
the 
mineral 
carbonation 
workshop 
was 
to 
understand 
how 
technological 
innovation 
in 
pre-determined 
areas 
of 
mineral 
carbonation 
can 
lead 
to 
a 
reduction 
in 
the 
cost 
per 
tonne 
of 
abatement 
delivered 
and 
provide 
an 
indication 
of 
the 
timeframe 
in 
which 
these 
cost 
reductions 
will 
occur. 
A 
diverse 
selection 
of 
global 
and 
national 
stakeholders 
in 
both 
ex-situ 
and 
in-situ 
mineral 
carbonation 
from 
across 
industry, 
government 
and 
academia 
were 
invited 
to 
participate 
in 
the 
workshop. 


The 
workshop 
was 
split 
into 
two 
themes: 
ex-situ 
mineral 
carbonation 
and 
in-situ 
mineral 
carbonation. 
In 
this 
context, 
ex-situ 
mineral 
carbonation 
refers 
to 
engineered 
reactions 
that 
take 
place 
above 
ground 
or 
outside 
naturally 
occurring 
geological 
formations 
(e.g. 
crushed 
rock). 
In-
situ 
mineral 
carbonation 
refers 
to 
engineered 
reactions 
that 
take 
place 
underground 
or 
within 
geological 
formations 
in 
their 
original 
location 
(e.g. 
bedrock). 


The 
participants 
were 
asked 
to 
answer 
two 
pre-workshop 
questions 
in 
the 
context 
of 
either 
ex-
situ 
or 
in-situ 
mineral 
carbonation: 


1. 
Please 
list 
up 
to 
five 
technological 
innovation 
areas 
that 
you 
think 
will 
drive 
cost 
reduction 
and 
increase 
scalability 
of 
carbon 
abatement 
using 
this 
sequestration 
approach? 
2. 
In 
your 
opinion, 
what 
are 
the 
key 
barriers 
to 
successful 
implementation 
and 
uptake 
of 
this 
sequestration 
approach? 
Eighty 
percent 
of 
participants 
responded 
to 
the 
pre-workshop 
survey. 
Their 
responses 
were 
summarised 
into 
five 
key 
technology 
innovation 
areas, 
which 
are 
presented 
in 
the 
following 
section. 


11.1Workshop 
results 


11.1.1 
Technology 
list 
Table 
11.1 
and 
Table 
11.2 
present 
the 
technical 
innovation 
opportunities 
collated 
during 
the 
workshop, 
together 
with 
a 
brief 
definition 
of 
the 
opportunity. 
Note 
that 
the 
specifics 
of 
the 
technical 
innovation 
areas 
were 
not 
discussed 
or 
agreed 
to 
during 
the 
workshop 
and 
are 
the 
authors’ 
definitions. 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
89 



Table 
11.1: 
Technical 
innovation 
opportunities 
for 
carbon 
sequestration 
through 
ex-situ 
mineral 


carbonation. 


TechnicalinnovationareaDescriptionCostreductionarea
Characterisation 
of 
A 
consistent 
supply 
of 
material/feedstock 
with 
high 


feedstock 
mineral 
carbonation 
potential 
will 
increase 
return-oninvestment 
due 
to 
overall 
efficiency 
from 
high 
rates 
of 
carbonation; 
this 
needs 
to 
be 
balanced 
against 
the 
volumes 
available, 
and 
the 
opportunity 
for 
continuous 
flowsheet 
operation 
can 
also 
contribute 
towards 
reducing 
overall 
operating 
costs. 


Feedstock/mineral 
pretreatment 
Pre-treatment 
refers 
to 
novel 
mining, 
crushing 
or 
milling, 
metal 
recovery, 
and 
heat 
activation. 
Particle 
size 
plays 
a 
crucial 
role 
in 
determining 
the 
rate 
and 
extent 
of 
carbonation, 
but 
milling 
minerals 
is 
highly 
energy 
intensive. 
Some 
hydrometallurgical 
flowsheets 
employ 
ultra-fine 
grinding 
in 
seeking 
higher 
value 
metal 
extraction, 
but 
it 
is 
also 
well 
known 
that 
different 
grinding 
techniques 
can 
be 
more 
energy 
efficient 
or 
produce 
narrower 
size 
distributions. 
Exploring 
and 
possibly 
even 
developing 
novel 
low-energy 
technologies, 
and 
further 
novel 
mining 
technologies, 
for 
mineral 
pre-treatment 
(including 
heat 
treatment 
for 
engineered 
mineral 
carbonation) 
and 
grinding 
may 
have 
scope 
to 
increase 
the 
efficiency 
of 
the 
mineral 
carbonation 
process. 
Catalyst/additive 
development 
for 
enhancing 
mineral 
carbonation 
kinetics 
Aside 
from 
the 
particle 
size 
effect, 
the 
rate 
of 
reaction 
between 
CO2 
and 
minerals 
in 
surficial 
carbonation 
(i.e. 
silicate 
rock 
or 
tailings 
applied 
to 
land) 
is 
impacted 
by 
the 
surface 
chemistry, 
which 
can 
be 
influenced 
to 
advantage 
by 
pre-treatment 
with 
catalysts 
or 
other 
additives. 
Innovations 
in 
this 
area 
can 
also 
improve 
the 
reaction 
rate 
for 
more 
engineered 
approaches 
to 
the 
leaching 
of 
magnesium, 
moderating 
required 
temperatures 
and 
pressures 
to 
make 
the 
process 
more 
economical. 
Innovations 
in 
lixiviants 
(chemicals 
used 
to 
extract 
or 
dissolve 
elements 
from 
an 
ore 
or 
concentrate) 
may 
also 
be 
significant. 
The 
potential 
for 
some 
to 
be 
recycled 
gives 
scope 
for 
cost 
reduction 
through 
reduced 
waste 
treatment. 


Comminution/particle 
size 
reduction: 
by 
avoiding 
or 
reducing 
processing 
of 
unwanted 
material. 
Energy 
consumption: 
reactive 
materials 
can 
be 
treated 
under 
less 
intense 
conditions. 
Capital/operating: 
as 
a 
default 
by 
achieving 
the 
above 
points. 


Comminution/particle 
size 
reduction: 
by 
avoiding 
the 
need 
for 
any 
grinding 
(or 
overgrinding) 
with 
tailings 
solids. 
Reductions 
in 
heat 
treatment 
costs. 


Energy: 
reactive 
phases 
can 
be 
treated 
under 
less 
aggressive 
conditions. 
Throughput: 
more 
carbon 
captured, 
and 
higher 
quality 
CO2. 
Reagent 
consumption 
and 
waste 
treatment: 
if 
lixiviants 
recycled 
or 
green. 


Creating 
high-value 
end 
Developing 
innovative 
materials 
from 
carbonates. 
Some 
products 
research 
has 
been 
done 
on 
using 
carbonates 
or 
silica 
generated 
from 
mineral 
carbonation 
to 
create 
building 
materials. 
However, 
further 
innovation 
is 
needed 
in 
this 
area 
to 
improve 
the 
economic 
viability 
of 
mineral 
carbonation 
as 
a 
Carbon 
Capture 
Utilisation 
and 
Storage 
(CCUS) 
process 
and 
promote 
circular 
economy 
principles. 


Offsetting 
of 
process 
costs. 
Reduction 
of 
long-term 
storage/rehabilitation 
costs/levies. 


Table 
11.2: 
Technical 
innovation 
opportunities 
for 
carbon 
sequestration 
through 
in-situ 
mineral 
carbonation. 


TechnicalinnovationareaDescriptionCostreductionarea
90 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



In-situ 
mineral 
carbonation 
Offshore 
storage 
can 
unlock 
the 
large-scale 


mapping 
potential 
of 
this 
technology. 
These 
sites 
have 
the 
potential 
to 
offer 
greater 
storage 
capacity 
and 
reduced 
risks 
associated 
with 
storage 
leakage. 


Facilitate 
industrial 
scale 
deployments 
that 
could 
decrease 
the 
overall 
cost 
per 
tonne 
of 
injected 
CO2. 
Cost 
of 
injection 
if 
the 
storage 
site 
has 
a 
good 
injectivity 
rating. 
Cost 
of 
CO2 
fluid 
transport 
if 
the 
storage 
site 
is 
near 
emission 
sources. 
Cost 
of 
carbon 
capture 
if 
CO2 
sources 
are 
near 
the 
injection 
site. 


Innovations 
that 
enable 
use 
of 
seawater 
Large 
volumes 
of 
water 
are 
required 
for 
this 
technology. 
Given 
that 
seawater 
is 
more 
abundant 
and 
readily 
available 
than 
freshwater, 
developing 
effective 
techniques 
for 
using 
seawater 
rather 
than 
freshwater 
or 
low 
salinity 
waters 
from 
aquifers 
would 
save 
operational 
costs 
while 
greatly 
expanding 
the 
large-scale 
potential 
of 
this 
technology. 
Costs 
of 
water 
supply 
and 
transport. 
Understanding 
the 
kinetics 
to 
improve 
the 
efficiency 
Identification 
of 
the 
kinetics, 
optimum 
conditions 
and 
mineralogy 
composition 
for 
mineral 
carbonation 
can 
save 
operational 
costs 
and 
increase 
the 
scale. 
Could 
increase 
the 
scale 
which 
could 
reduce 
the 
net 
cost 
per 
tonne 
of 
CO2 
injected. 


Optimisation 
of 
injection 
To 
save 
operational 
costs 
and 
improve 
the 
scale, 
Injection 
cost 
reduction. 
strategy 
and 
patterns 
injection 
fluid 
and 
strategy 
can 
be 
optimised. 
Furthermore, 
well 
placement 
and 
patterns 
are 
important 
for 
injectivity 
and 
not 
over-pressurising 
the 
reservoir. 
Fractures 
characterisation 
Fractures 
are 
the 
conduits 
for 
fluid 
to 
flow 
and 
for 
Injection 
cost 
and 
monitoring 
cost 
mineral 
carbonation 
to 
occur. 
They 
provide 
the 
reductions. 
surface 
area 
for 
the 
minerals 
to 
react 
with 
the 
injected 
fluid. 
If 
the 
fractures 
are 
not 
well 
connected 
and 
dense 
enough, 
operational 
costs 
and 
large-scale 
applications 
of 
this 
technology 
will 
be 
severely 
impacted. 
As 
such, 
characterising 
the 
fractures 
and 
their 
connectivity 
for 
any 
potential 
storage 
site 
is 
essential. 
Even 
within 
a 
reservoir 
with 
the 
right 
mineralogy 
composition, 
pressure 
and 
temperature 
conditions, 
a 
well-connected 
and 
dense 
fracture 
network 
is 
necessary 
for 
the 
reservoir 
to 
function 
as 
an 
optimal 
site 
for 
operation. 


The 
voting 
results 
for 
the 
technology 
themes 
are 
outlined 
in 
Table 
11.3. 
For 
ex-situ 
mineral 
carbonation, 
three 
technical 
innovation 
areas 
were 
prioritised. 
For 
in-situ 
mineral 
carbonation, 
two 
technical 
innovation 
areas 
were 
prioritised. 
Five 
key 
technical 
innovation 
areas 
across 
both 
themes 
were 
assessed 
as 
priorities 
using 
the 
Delphi 
continuum 
method. 


Table 
11.3: 
Voting 
results 
for 
the 
mineral 
carbonation 
technical 
innovation 
areas. 
The 
technical 
innovation 
areas 
with 
the 
highest 
votes 
for 
each 
theme 
are 
shown 
in 
bold 
font. 
These 
areas 
were 
assessed 
as 
a 
priority 
in 
the 
workshop. 


ThemeTechnicalinnovationareaVotesEx-SituCharacterisationoffeedstock5Feedstock/mineralpre-treatment3Catalyst/additivedevelopmentforenhancingmineralcarbonationkinetics5Creatinghigh-valueendproducts6In-SituIn-situmineralcarbonationmapping3Innovationsthatenableuseofseawater3Understandingthekineticstoimprovetheefficiency6
Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
91 



Optimisationofinjectionstrategyandpatterns5Fracturescharacterisation3Optimisationofinjectionstrategyandpatterns5Fracturescharacterisation3
11.1.2 
Workshop 
outputs 
The 
workshop 
results 
for 
the 
technology 
innovation 
areas 
are 
summarised 
in 
Table 
11.4. 
To 
help 
interpret 
the 
results, 
please 
see 
the 
definition 
of 
terms 
in 
section 
3.6. 


Table 
11.4: 
Summary 
of 
outputs 
from 
the 
mineral 
carbonation 
workshop. 
The 
prioritised 
in-situ 
and 
ex-
situ 
technical 
innovation 
areas 
are 
shown 
in 
bold. 
Note: 
fractures 
characterisation 
was 
not 
included 
in 
the 
workshop. 


TechnicalinnovationareaCostreduction(%)Maturity(Year)Scalingfactor(%)Investmentrequired($
million)
AvgMinMaxAvgMinMaxAvgMinMaxAvgMinMax
Characterisation 
of 
39 
16 
100 
2031 
2027 
2035 
1471 
15 
10000 
398 
200 
59 
feedstock 
(ex-situ) 
0 


Feedstock/mineral 
pre-58 
30 
100 
2033 
2029 
2035 
4035 
40 
15000 
350 
150 
55 
treatment 
(ex-situ) 


0 


Catalyst/additive 
40 
10 
50 
2034 
2030 
2036 
231 
15 
520 
633 
400 
10 
development 
for 
00 
enhancing 
mineral 
carbonation 
kinetics 
(ex-situ) 


Creating 
high-value 
end 
72 
15 
100 
2033 
2028 
2038 
3667 
50 
10000 
650 
400 
90 
products 
(ex-situ) 


0 


In-situ 
mineral 
carbonation 
mapping 
(in-situ) 
53 
50 
60 
2035 
2034 
2035 
99 
95 
100 
250 
200 
30 
0 
Innovations 
that 
enable 
use 
of 
seawater 
(in-situ) 
38.6 
20 
50 
2033.8 
2030 
2035 
7.2 
5 
10 
165 
50 
25 
0 


Understanding 
the 
kinetics 
to 
improve 
the 
efficiency 
(in-situ) 
14 
10 
20 
2033 
2031 
2035 
38 
1 
65 
52 
30 
75 
Optimisation 
of 
injection 
strategy 
and 
patterns 
(in-situ) 
46 
25 
75 
2031 
2028 
2033 
25 
10 
50 
128 
45 
24 
0 


The 
average 
cost 
reduction 
potential 
was 
plotted 
against 
the 
average 
uptake 
scaling 
potential 
(Figure 
11-1). 
If 
the 
technology 
has 
a 
significant 
cost 
reduction 
factor, 
it 
would 
be 
reasonable 
to 


92 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



expect 
that 
the 
scaling 
factor 
would 
similarly 
be 
high. 
Conversely, 
if 
the 
cost 
reduction 
factor 
was 
relatively 
low, 
expecting 
a 
low 
scaling 
factor 
would 
be 
reasonable. 


For 
ex-situ 
mineral 
carbonation 
(Figure 
11-1A), 
the 
technical 
innovation 
areas 
are 
moderately 
correlated 
(R2 
= 
0.72). 
However, 
the 
correlation 
is 
weak 
for 
in-situ 
technical 
innovation 
areas 
(R2= 
0.16; 
Figure 
11-1B). 
This 
is 
likely 
an 
artefact 
of 
the 
workshop; 
therefore, 
the 
results 
should 
be 
interpreted 
with 
care. 
This 
could 
be 
due 
to 
insufficient 
time 
to 
work 
through 
to 
a 
consensus 
or 
lack 
of 
a 
consensus 
process 
to 
compare 
scaling 
factors 
to 
cost 
reduction. 



Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
93 



Figure 
11-1: 
Plot 
of 
average 
cost 
reduction 
percentages 
versus 
scaling 
factor 
for 
(A) 
ex-situ 
and 
(B) 
in-situ 
mineral 
carbonation 
technical 
innovation 
areas. 
Both 
datasets 
have 
a 
positive 
association 
(R2 
> 
0). 
Ex-situ 
data 
are 
moderately 
correlated 
(R2 
= 
0.72); 
in-situ 
data 
are 
weakly 
correlated 
(R2 
= 
0.16). 


11.1.3 
Cost 
analysis 
The 
input 
baseline 
costs 
for 
the 
cost 
model 
and 
analysis 
were 
estimated 
from 
cost 
reports 
in 
the 
available 
literature. 
For 
ex-situ 
mineral 
carbonation, 
cost 
data 
were 
limited. 
The 
baseline 
cost 
estimate 
of 
US$150 
per 
tonne 
was 
taken 
from 
IEAGHG 
(2022). 
For 
in-situ 
mineral 
carbonation, 
the 
baseline 
cost 
estimate 
of 
US$25 
(AUD$37)6 
per 
tonne 
was 
averaged 
from 
cost 
estimates 
provided 
by 
Kelemen 
et 
al. 
(2019). 
These 
baseline 
cost 
estimates 
were 
presented 
to 
and 
agreed 
on 
by 
the 
workshop 
participants 
at 
the 
beginning 
of 
the 
workshop. 


Therefore, 
for 
the 
cost 
model 
and 
analysis, 
we 
will 
apply 
the 
cost 
reductions 
directly 
from 
the 
baseline 
of: 


 
US$150 
(AUD$222) 
per 
tonne, 
for 
ex-situ 
mineral 
carbonation 
 
US$25 
(AUD$37) 
per 
tonne, 
for 
in-situ 
mineral 
carbonation. 
The 
results 
of 
the 
modelling 
are 
listed 
in 
Table 
11.5. 
The 
cost 
reductions 
are 
the 
difference 
in 
cost 
per 
tonne 
(in 
AUD) 
compared 
to 
the 
baseline. 


Table 
11.5: 
Cost 
reductions 
for 
mineral 
carbonation 
technical 
innovation 
areas. 


TechnicalinnovationareaCostreductionfrombaseline($pertonne)
Netcost($pertonne)
Baselinecost(Ex-situ)0222
Characterisation 
of 
feedstock 
–86 
136 
Feedstock/mineral 
pre-treatment 
–128 
94 
Catalyst/additive 
development 
for 
enhancing 
mineral 
–89 
133 
carbonation 
kinetics 
Creating 
high-value 
end 
products 
–159 
63 


Baselinecost(In-situ)037
In-situ 
mineral 
carbonation 
mapping 
–20 
17 
Innovations 
that 
enable 
use 
of 
seawater 
–14 
23 
Understanding 
the 
kinetics 
to 
improve 
the 
efficiency 
–5 
32 
Optimisation 
of 
injection 
strategy 
and 
patterns 
–17 
20 


The 
innovation 
areas 
with 
the 
greatest 
potential 
to 
lower 
the 
cost 
of 
sequestration 
over 
the 
life 
of 
a 
project 
are: 


 
Ex-situ: 
creating 
high 
value 
end 
products, 
with 
a 
reduction 
of 
$159 
from 
the 
baseline 
of 
$222 
per 
tonne 
(72%), 
for 
a 
net 
cost 
of 
$63 
per 
tonne. 
 
In-situ: 
mineral 
carbonation 
mapping, 
with 
a 
reduction 
of 
$20 
from 
the 
baseline 
of 
$37 
per 
tonne 
(53%), 
for 
a 
net 
cost 
of 
$17 
per 
tonne. 
6 
Exchange 
rate 
of 
$.67 
USD 
to 
AUD. 


94 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



All 
cost 
reductions 
are 
presented 
below 
as 
bar 
charts 
(Figure 
11-2 
and 
Figure 
11-3). 
For 
ex-situ 
mineral 
carbonation, 
the 
cost 
reduction 
potential 
ranges 
between 
38 
and 
72%, 
with 
an 
average 
of 
52% 
per 
tonne. 
For 
in-situ 
mineral 
carbonation, 
the 
cost 
reduction 
potential 
ranges 
between 
13 
and 
54%, 
with 
an 
average 
of 
38% 
per 
tonne. 



Figure 
11-2: 
Bar 
graph 
of 
cost 
reductions 
for 
ex-situ 
mineral 
carbonation 
technology 
innovation 
areas. 
The 
cost 
reductions 
are 
from 
a 
baseline 
of 
$222 
per 
tonne. 



Figure 
11-3: 
Bar 
graph 
of 
cost 
reductions 
for 
in-situ 
mineral 
carbonation 
technology 
innovation 
areas. 
The 
cost 
reductions 
are 
from 
a 
baseline 
of 
$37 
per 
tonne. 


11.1.4 
Cost 
reduction, 
maturity 
and 
scale 
To 
allow 
a 
comparison 
between 
technology 
innovation 
areas 
by 
ex-situ 
and 
in-situ 
technologies, 
Figure 
11-4 
and 
Figure 
11-5 
summarise 
the 
outputs 
from 
the 
workshop. 
The 
x-axis 
represents 
the 
year 
of 
maturity, 
the 
y-axis 
the 
cost 
reduction 
per 
tonne 
of 
carbon 
sequestration, 
and 
the 
bubble 


Sequestration 
Cost 
Reduction 
Workshops 
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| 
95 



size 
represents 
the 
scaling 
factor. 
The 
most 
viable 
technologies 
are 
those 
that 
reach 
maturity 
early 
(see 
section 
4.1) 
and 
have 
a 
large 
scaling 
factor 
(bubble 
size). 


For 
ex-situ 
mineral 
carbonation, 
advances 
in 
feedstock 
and 
creating 
high-value 
end 
products 
will 
have 
the 
greatest 
impact 
in 
terms 
of 
cost 
reduction 
per 
tonne 
and 
overall 
scalability 
in 
the 
next 
decade. 
For 
in-situ 
mineral 
carbonation, 
the 
greatest 
impact 
is 
likely 
to 
come 
from 
accurate 
mapping 
of 
in-situ 
carbonation 
sites, 
despite 
the 
timeline 
for 
reaching 
full 
maturity. 



96 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Figure 
11-4: 
Comparison 
of 
technology 
cost 
reduction, 
year 
of 
maturity 
and 
scaling 
factor 
for 
ex-situ 
mineral 
carbonation. 



Figure 
11-5: 
Comparison 
of 
technology 
cost 
reduction, 
year 
of 
maturity 
and 
scaling 
factor 
for 
in-situ 
mineral 
carbonation. 


11.1.5 
Scaling 
and 
maturity 
analysis 
The 
relative 
sequestration 
benefit 
compares 
the 
different 
technology 
options 
to 
identify 
the 
option 
that 
generates 
the 
greatest 
additional 
sequestration 
at 
different 
end 
years. 
The 
relative 
sequestration 
benefit 
is 
calculated 
using 
scaling 
factors 
and 
maturity 
time 
frames 
determined 
during 
the 
workshop. 
Section 
4.2 
has 
more 
detail 
on 
this 
approach. 


The 
greatest 
sequestration 
generated 
by 
2050 
is 
for 
feedstock/mineral 
pre-treatment 
(value 
of 
1), 
and 
the 
other 
technology 
options 
are 
scaled 
relative 
to 
that. 
Characterisation 
of 
feedstocks 
would 
generate 
nearly 
half 
(0.4) 
as 
much 
additional 
sequestration 
by 
2050 
compared 
to 
feedstock 
pretreatment. 


Table 
11.6: 
Relative 
sequestration 
benefit 
of 
each 
ex-situ 
mineral 
carbonation 
technical 
innovation 
area. 


Technicalinnovationarea2030203520402050
Characterisation 
of 
feedstocks 
1.0 
0.7 
0.5 


0.4 


Feedstock/mineral 
pre-treatment 
0.7 
1.0 
1.0 
1.0 
Catalyst 
additive 
development 
0.1 
0.1 
0.1 


0.1 


Creating 
high-value 
end 
products 
0.7 
1.0 
0.9 
0.9 


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Cost 
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Workshops 
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| 
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Table 
11.7: 
Relative 
sequestration 
benefit 
of 
each 
in-situ 
mineral 
carbonation 
technical 
innovation 
area. 


Technicalinnovationarea2030203520402050
In-situ 
mineral 
carbonation 
mapping 
0.9 
1.0 
1.0 


1.0 


Innovations 
that 
enable 
use 
of 
seawater 
0.2 
0.1 
0.1 
0.1 
Understanding 
the 
kinetics 
to 
improve 
the 
efficiency 
0.8 
0.7 
0.5 


0.4 


Optimisation 
of 
injection 
strategy 
and 
patterns 
1.0 
0.7 
0.4 
0.3 


11.1.6 
Assumptions 
and 
limitations 
of 
the 
analysis 
This 
study 
included 
the 
assumption 
that 
the 
baseline 
cost 
of 
ex-situ 
mineral 
carbonation 
is 
consistent 
across 
all 
areas 
(i.e. 
ex-situ 
carbonation 
of 
mine 
tailings, 
ex-situ 
application 
of 
silicate 
rock 
to 
land, 
or 
ex-situ 
carbonation 
of 
industrial 
waste 
streams). 
Therefore, 
variations 
on 
the 
baseline 
costs 
are 
highly 
likely. 


11.2Discussion 


While 
innovation 
within 
all 
identified 
technical 
innovation 
areas 
will 
reduce 
the 
cost 
per 
tonne 
of 
CO2 
sequestered, 
at 
the 
current 
rate 
of 
investment 
in 
mineral 
carbonation 
research 
and 
development, 
the 
most 
impactful 
outcomes 
will 
not 
reach 
maturity 
for 
at 
least 
a 
decade. 
The 
delay 
in 
realising 
the 
more 
significant 
cost 
reduction 
outcomes 
puts 
industry 
adoption 
and 
investment 
into 
Australian-owned 
mineral 
carbonation 
technologies 
and 
methodologies 
at 
risk. 
International 
carbon 
crediting 
methodologies 
for 
the 
voluntary 
market 
are 
currently 
available 


(e.g. 
enhanced 
rock 
weathering 
methodologies), 
and 
are 
likely 
to 
form 
part 
of 
Australia’s 
emerging 
enhanced 
rock 
weathering 
industry. 
International 
investment 
in 
such 
initiatives 
and 
the 
small 
number 
of 
initiatives 
existing 
nationally 


(i.e. 
BHP 
Nickel 
West, 
MCi 
Carbon, 
and 
Boral 
Limited) 
indicate 
the 
potential 
of 
mineral 
carbonation 
as 
a 
(Carbon 
Dioxide 
Removal 
(CDR) 
technique 
(Fitch 
et 
al. 
2022). 
Further, 
an 
opportunity 
exists 
for 
the 
development 
of 
technology 
and 
Monitoring, 
Reporting 
and 
verification 
(MRV) 
methodologies. 
International 
Organization 
for 
Standardization–certified 
methodologies 
for 
mineral 
carbonation 
CDR 
techniques 
are 
currently 
limited. 
The 
design 
of 
future 
methodologies 
around 
MRV 
for 
CDR 
(and 
storage) 
are 
critical. 
They 
may 
have 
an 
impact 
on 
the 
cost 
reduction 
and 
uptake 
scaling 
potential 
for 
mineral 
carbonation 
techniques 
if 
they 
are 
highly 
complex 
and 
time 
intensive. 
Accessible 
and 
cost-effective 
methodologies 
will 
promote 
uptake 
of 
mineral 
carbonation 
techniques 
and 
proponents 
of 
future 
emissions 
reduction 
funds 
or 
other 
carbon 
crediting 
schemes. 
Additionally, 
consideration 
of 
scope 
4 
emissions 
(avoided 
emissions) 
is 
also 
important; 
validation 
of 
emissions 
that 
reduce 
CO2 
intensity 
in 
supply 
chains 
(beyond 
CO2 
storage) 
currently 
does 
not 
exist. 
Further, 
recognising 
industrial 
integration 
and 
novel 
business 
models 
that 
champion 
Environmental, 
Social 
and 
Governance 
(ESG) 
criteria 
in 
this 
area 
is 
important. 
Environmental 
and 
health 
and 
safety 
considerations 
(and 
mitigation) 
will 
play 
an 
important 
role 
in 
mineral 
carbonation 
methodology 
development 
and 
pilot 
deployments. 
An 
example 
of 
risk 
mitigation 
within 
ex-situ 
carbonation 
relates 
to 
tailings. 
During 
mineral/tailings 
dissolution 
(or 
partial 
dissolution) 
to 
solubilise 
magnesium, 
there 
is 
little 
understanding 
about 
what 
occurs 
in 
the 
process 
liquor 
after 
the 
reaction 
of 
magnesium 
to 
form 
a 
product 
or 
about 
what 
residues 
remain. 
In 
some 
cases, 
it 
is 
possible 
that 
the 
mass 
of 
the 
starting 
minerals/tailings 
is 
significantly 
reduced 
but 
changes 
in 
particle 
size 
or 
residue 
phase 
may 
lead 
to 
a 
net 
increase 
in 
the 
residue 
volume. 


98 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Leaching 
of 
magnesium 
can 
also 
liberate 
other 
metals 
that 
may 
be 
toxic 
or 
have 
other 
downstream 
implications. 
Consideration, 
therefore, 
needs 
to 
be 
given 
as 
to 
whether 
the 
mineral 
carbonation 
process 
may 
create 
a 
new 
problem, 
which 
may 
in 
turn 
introduce 
additional 
costs. 


Conversely, 
with 
improved 
feedstock 
characterisation, 
some 
of 
these 
risks 
will 
be 
mitigated 
or 
removed 
entirely. 
Exploring 
new 
feedstock 
options 
from 
industrial 
waste 
streams 
may 
expand 
the 
capability 
of 
engineered 
ex-situ 
mineral 
carbonation 
methods. 
Expanding 
existing 
feedstock 
options 
to 
include 
novel 
feedstocks 
from 
industrial 
waste 
streams 
in 
Australia 
may 
significantly 
increase 
the 
cost 
reduction 
potential 
for 
this 
mineral 
carbonation 
technique. 
Industrial 
waste 
streams 
might 
include 
steel 
slags 
or 
incinerator 
bottom 
ash. 
The 
addition 
of 
new 
feedstocks 
and 
waste 
streams 
may 
see 
the 
scale 
of 
the 
product 
market 
become 
much 
larger 
than 
existing 
markets; 
the 
exact 
intent 
of 
these 
product 
markets 
needs 
additional 
work. 


Mapping 
mafic 
and 
ultramafic 
units 
for 
in-situ 
mineral 
carbonation 
will 
require 
detailed 
characterisation 
of 
the 
host 
rocks 
with 
careful 
and 
ongoing 
monitoring 
to 
manage 
and 
mitigate 
risks 
(Fitch 
et 
al. 
2022). 
Monitoring 
and 
risk 
mitigation 
requirements 
of 
offshore 
in-situ 
carbonation 
remain 
poorly 
elucidated. 


Finally, 
the 
lack 
of 
a 
globally 
agreed 
list 
of 
definitions 
for 
each 
area 
of 
mineral 
carbonation 
remains 
an 
ongoing 
challenge; 
an 
opportunity 
exists 
to 
develop 
these 
guidelines. 
While 
it 
is 
easier 
for 
people 
working 
in 
mineral 
carbonation 
to 
understand 
what 
commonly 
used 
terms 
mean 
in 
each 
context, 
this 
is 
not 
always 
the 
case 
for 
non-subject 
matter 
experts. 


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11.3References 


Fitch 
P, 
Battaglia 
M, 
Lenton 
A, 
Feron 
P, 
Gao 
L, 
Mei 
Y, 
Hortle 
A, 
Macdonald 
L, 
Pearce 
M, 
Occhipinti 
S, 
Roxburgh 
S, 
Steven 
A 
(2022) 
Australia’s 
carbon 
sequestration 
potential: 
a 
stocktake 
and 
analysis 
of 
sequestration 
technologies, 
CSIRO, 
Canberra. 


IEAGHG 
(2022) 
Mineral 
carbonation 
using 
mine 
tailings 
– 
a 
strategic 
overview 
of 
potential 
and 
opportunities. 
IEAGHG 
Technical 
Report 
2022-10, 
July 
2022, 
IEA 
Greenhouse 
Gas 
R&D 
Programme, 
Cheltenham, 
UK 


Kelemen 
P, 
Benson 
SM, 
Pilorgé 
H, 
Psarras 
P, 
Wilcox 
J 
(2019) 
An 
overview 
of 
the 
status 
and 
challenges 
of 
CO2 
storage 
in 
minerals 
and 
geological 
formations. 
Frontiers 
in 
Climate, 
1:9. 


100 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Appendix 



Workshop 
outputs 


This 
section 
contains 
digitised 
outputs 
from 
the 
workshops. 
No 
analysis 
has 
been 
done; 
it 
is 
simply 
a 
translation 
from 
the 
Miro 
board 
to 
box 
and 
whisker 
plots 
for 
the 
numerical 
results 
and 
tables 
for 
the 
implementation 
steps. 


A.1 
Workshop 
results 
A.1.1 
Planted 
vegetation 
workshop 
Low-cost 
imagery 



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Figure 
A1.1: 
Translated 
Miro 
results 
for 
low-cost 
imagery. 
Table 
A1.1: 
Implementation 
steps 
for 
low-cost 
imagery. 


Technologyimplementationsteps
Timeframe 
Difficulty 
Implementation 
step 
2025–2030 
Very 
easy 
Field 
calibration/validation 
for 
remote 
sensed 
data 
2025–2030 
Easy 
High 
resolution 
optical 
CubeSats 


2025–2030 
Easy 
High 
altitude 
autonomous 
drones 
with 
updated 
MSS 
packages 
or 
LEO 
satellites 
2030–2035 
Easy 
Multispectral 
sensors 
to 
species 
ID 
calibration 
AI/ML 


2030–2035 
Easy 
Easy-to-understand 
tools 
related 
to 
spatial 
monitoring 
2025–2030 
Moderate 
Price 
accessibility 
to 
existing 
technologies 


2025–2030 
Moderate 
LiDAR 
everything, 
everywhere, 
all 
the 
time 
2025–2030 
Moderate 
Models 
correlating 
indicator/data 
collected 
to 
question 
2030–2035 
Moderate 
Improved 
vegetation 
recognition 
for 
Australian 
species 
2030–2035 
Moderate 
Improved 
resolution 
(spatial 
and 
spectral) 
wall-to-wall 
high 
frequency 
imagery 
= 
Planet 
labs, 
but 
at 
50 
cm 


2035–2040 
Moderate 
LiDAR-done 
fleet/network 
for 
calibration/validation 
2025–2030 
Somewhat 
hard 
NASA 
NISAR 
mission 
(L-band 
SAR 
at 
10 
m) 


2030–2035 
Somewhat 
hard 
High 
altitude 
drone/dirigible-based 
LiDAR 
with 
1 
m 
resolution 
2025–2030 
Hard 
Australia-wide 
publicly 
available 
LiDAR 
mission 
2030–2035 
Hard 
GEDI 
follow-on 
mission 
(wall-to-wall 
spaceborne 
LiDAR 
at 
25 
m) 
2040–2045 
Hard 
Space 
based 
LiDAR 
with 
1 
m 
resolution 


102 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Zero 
or 
low 
emission 
fuels 



Figure 
A1.2: 
Translated 
Miro 
results 
for 
zero 
or 
low 
emission 
fuels. 
Table 
A1.2: 
Implementation 
steps 
for 
low 
emission 
fuels. 


Technologyimplementationsteps
Timeframe 
Difficulty 
Implementation 
step 


2025–2030 
Very 
easy 
Industry 
buy-in 
2025–2030 
Easy 
Low 
or 
zero 
emissions 
biofuels 
can 
be 
available 
from 
regional 
agroforestry 


2025–2030 
Moderate 
Regional 
co-op 
investment 
in 
low 
emission 
fleets 
(vehicles, 
drones, 
other 
agricultural 
equipment) 
2035–2040 
Moderate 
Fossil 
fuel 
equipment 
lifecycle/replacement 
cycle/sunk 
cost 


Sequestration 
Cost 
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Workshops 
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| 
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2040–2045 
Somewhat 
More 
efficient 
and 
safer 
batteries 
hard 
2025–2030 
Hard 
Better 
policy 


Small-scale 
equipment 
for 
agroforestry 



Figure 
A1.3: 
Translated 
Miro 
results 
for 
small-scale 
equipment 
for 
agroforestry. 


Table 
A1.3: 
Implementation 
steps 
for 
small-scale 
equipment 
for 
agroforestry. 


Technologyimplementationsteps
Timeframe 
Difficulty 
Implementation 
step 
2025–2030 
Moderate 
Incentives 
for 
operators 
to 
deploy 
a 
crew 
with 
potential 
to 
harvest 
small-scale 
plantings 


104 
| 
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Australia’s 
National 
Science 
Agency 



2025–2030 
Somewhat 
Case 
studies 
including 
costs 
and 
benefits, 
so 
that 
people 
feel 
comfortable 
to 
hard 
invest 
2030–2035 
Easy 
Aggregation 
of 
biomass 
can 
be 
facilitated 
by 
farm-based 
harvesting 
2030–2035 
Moderate 
Open-source 
hardware/equipment 
sharing/lease 
models 


Pests 
and 
diseases 



Figure 
A1.4: 
Translated 
Miro 
results 
for 
pests 
and 
diseases. 


Table 
A1.4: 
Implementation 
steps 
for 
pests 
and 
diseases. 


Technologyimplementationsteps
Timeframe 
Difficulty 
Implementation 
steps 


2025–2030 
Very 
easy 
Single 
line 
electric 
wire 
with 
solar 


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| 
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2025–2030 
Very 
easy 
In 
the 
Western 
Australian 
wheatbelt 
it 
is 
rare 
to 
fence 
out 
sheep 
or 
pests, 
but 
in 
the 
south 
some 
sheep 
fencing 
is 
required 
2025–2030 
Moderate 
Plant 
breeding 
for 
browsing 
resistance 
2030–2035 
Moderate 
Plant 
breeding 
for 
pest 
resistance 


Decision 
support 
for 
informing 
optimal 
species 
selection 



Figure 
A1.5: 
Translated 
Miro 
results 
for 
decision 
support 
for 
informing 
optimal 
species 
selection. 


Table 
A1.5: 
Implementation 
steps 
for 
decision 
support 
for 
informing 
optimal 
species 
selection. 


Technologyimplementationsteps
Timeframe 
Difficulty 
Implementation 
steps 
2025–2030 
Very 
easy 
Detailed 
case 
studies, 
including 
outcomes 
and 
impacts 
2030–2035 
Very 
easy 
Cal/Val 
carbon 
growth 
forecast 
tools 
2025–2030 
Easy 
Local 
species 
allometric 
database 
2025–2030 
Easy 
Improved 
understanding 
of 
water 
trade-offs 
to 
placate 
water 
authorities 
planning 
processes 
2025–2030 
Easy 
Sharing 
of 
allometric 
datasets 
2025–2030 
Easy 
Soil 
carbon/biomass 
metrics 


106 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



2025–2030 
Moderate 
Comprehensive 
spreadsheets 
providing 
key 
information 
on 
economics 
and 
risks 
2030–2035 
Moderate 
Detailed 
local 
species 
databases 
with 
allometry 
for 
each 
species 


Lower-cost 
fencing 



Figure 
A1.6: 
Translated 
Miro 
results 
for 
low-cost 
fencing. 


Table 
A1.6: 
Implementation 
steps 
for 
low-cost 
fencing. 


Technologyimplementationsteps
Timeframe 
Difficulty 
Implementation 
steps 


2030–2035 
Very 
easy 
Species-specific 
animal 
control 
technology 


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| 
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Genetic 
improvement 



Figure 
A1.7: 
Translated 
Miro 
results 
for 
genetic 
improvements. 


Table 
A1.7: 
Implementation 
steps 
for 
genetic 
improvements. 


Technologyimplementationsteps
Timeframe 
Difficulty 
Implementation 
steps 
2030–2035 
Very 
easy 
For 
some 
leaf 
area 
limit 
(environmental 
limit) 
can 
breed 
for 
taller 
trees 
and 
thicker 
stems, 
i.e. 
more 
biomass 
(carbon 
sequestration) 
and 
more 
timber 
2030–2035 
Somewhat 
Improved 
breeding 
(access 
to 
seed) 
of 
alternative 
hard 
wood 
species 
for 
hard 
agroforestry 


108 
| 
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Australia’s 
National 
Science 
Agency 



New 
products 
for 
biomass 
residues 



Figure 
A1.8: 
Translated 
Miro 
results 
for 
new 
products 
for 
biomass 
residues. 


Table 
A1.8: 
Implementation 
steps 
for 
new 
products 
for 
biomass 
residues. 


Technologyimplementationsteps
Timeframe 
Difficulty 
Implementation 
step 
2025–2030 
Very 
easy 
Biofuel 
development 
business 
being 
promoted 
with 
drop 
in 
fuels. 
Likely 
this 
will 
add 
to 
the 
economics 
and 
lower 
net 
costs 
2025–2030 
Easy 
Low-cost 
veneer 
biomass 
energy 
technologies 
that 
already 
exist 
need 
investment 
linked 
to 
supply 
capacity 
2030–2035 
Moderate 
Important 
to 
develop 
bioenergy 
and 
biofuel 
products. 
Benefits 
include 
improved 
profitability 
of 
timber 
production 
and 
opportunities 
to 
displace 
fossil 
fuels 
2035–2040 
Somewhat 
Lignocellulosic 
ethanol 
hard 


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Driverless 
and 
automated 
vehicles 
and 
machinery 



Figure 
A1.9: 
Translated 
Miro 
results 
for 
driverless 
and 
automated 
vehicles. 


Table 
A1.9: 
Implementation 
steps 
for 
driverless 
and 
automated 
vehicles. 


Technologyimplementationsteps
Timeframe 
Difficulty 
Implementation 
step 
2025–2030 
Easy 
Grants/low 
interest 
finance/concessions 
etc. 
to 
increase 
affordability 
and 
facilitate 
transition 
2025–2030 
Somewhat 
Case 
studies 
including 
costs 
and 
benefits, 
so 
people 
feel 
comfortable 
to 
invest 
hard 


110 
| 
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Australia’s 
National 
Science 
Agency 



2030–2035 
Moderate 
Scope 
for 
autonomous 
operations, 
e.g. 
intelligent 
spraying 
operations, 
site 
preparation 
and 
planting, 
harvesting 
and 
transport 
2030–2035 
Hard 
Lack 
of 
trainer 
operators 
= 
replace 
low-cost 
labourers 
with 
specialists 
2035–2040 
Hard 
More 
efficient 
and 
safer 
batteries 


A.1.2 
Blue 
carbon 
workshop 
Earth 
observation 
technologies 
for 
restoration 
site 
identification 
and 
assessment 



Figure 
A1.10: 
Translated 
Miro 
results 
for 
earth 
observation 
for 
restoration 
site 
identification 
and 
assessment. 


Sequestration 
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Workshops 
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111 



Table 
A1.10: 
Implementation 
steps 
for 
earth 
observation 
for 
restoration 
site 
identification 
and 
assessment. 


Technologyimplementationsteps
Timeframe 
Difficulty 
Implementation 
step 
Investment 


Now–2025 
Very 
easy 
Collate 
drained 
landscape 
data 
(collate, 
digitise, 
harmonise) 
$2 
m 
Now–2025 
Very 
easy 
Consult 
with 
project 
proponents 
to 
determine 
what 
information 
they 
Low 
would 
need 
to 
resolve 
the 
barriers 
to 
identifying 
sites 


Now–2025 
Easy 
Purchase 
of 
high-resolution 
imagery 
and 
maybe 
fill 
in 
gaps 
on 
LiDAR 
$4 
m 
Now–2025 
Easy 
Develop 
vegetation 
condition 
cover 
that 
updates 
weekly 
that 
is 
open 
to 
all 
$4 
m 
Now–2025 
Moderate 
Testing 
and 
calibration 
of 
developed 
tools 
$0.5 
m 
Now–2025 
Moderate 
Developing 
data, 
models 
and 
software 
structures 
to 
analyse 
and 
visualise 
$3 
m 
data 


Now–2025 
Moderate 
Designing 
strategies 
to 
cover 
data 
gaps 
and 
prioritise 
data 
collection 
$250 
k 
efforts 
Now–2025 
Hard 
Developing 
a 
catalogue 
of 
available 
datasets 
$100 
k 
Now–2025 
Very 
hard 
Identifying 
data 
needs 
for 
site 
identification 
and 
assessment 
$250 
k 
2025–2030 
Very 
easy 
Instrumented 
pilot 
sites 
for 
technology 
development 
$100 
m 
2025–2030 
Easy 
Consider 
social 
safeguards 
(FPIC, 
privacy, 
safety 
risks 
related 
data) 
and 
? 
inclusive 
and 
accessible 
design 
(involve 
communities 
and 
consider 
First 
Nations 
voices 
and 
design) 
2025–2030 
Moderate 
Seagrass 
change 
detection 
$1 
m 


2025–2030 
Moderate 
Algorithm 
development 
and 
testing 
$2 
m 
2025–2030 
Moderate 
Build 
a 
data 
cube 
and 
API 
interface 
2025–2030 
Moderate 
AUV 
to 
database 
technologies 
for 
automated 
MRV 
$3 
m 
2025–2030 
Moderate 
Automated 
biodiversity 
monitoring 
(e.g. 
acoustic) 
$3 
m 
2025–2030 
Hard 
Develop 
a 
sensor 
for 
salinised 
land 
$20 
m 
2030–2035 
Hard 
Automated 
methane/GHG 
sensors 
$2 
m 


2030–2035 
Very 
hard 
Building 
carbon 
monitoring 
with 
EO 
$50 
m 
2035–2040 
Hard 
Model 
for 
identifying 
vegetation 
species 
(including 
saltmarshes) 
from 
$50 
m 
satellite 
date 


2035–2040 
Hard 
CO2 
flux 
model 
at 
high 
resolution 
$100 
m 


National 
model 
for 
tidal 
introduction 
and 
feasibility 
assessment 


112 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Figure 
A1.11: 
Translated 
Miro 
results 
for 
a 
national 
model 
for 
tidal 
introduction 
and 
feasibility 
assessment. 


Table 
A1.11: 
Implementation 
steps 
for 
a 
national 
model 
for 
tidal 
introduction 
and 
feasibility 
assessment. 


Technologyimplementationsteps
Timeframe 
Difficulty 
Implementation 
step 
Investment 


Now–2025 
Easy 
Determine 
scope 
of 
feasibility 
assessment 
de 
novo, 
add 
$500 
k 
on, 
e.g. 
LUTO 


Sequestration 
Cost 
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Workshops 
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Now–2025 
Hard 
Accounting 
for 
uncertainties 
impacting 
project 
$200 
k 
feasibility, 
e.g. 
potential 
impacts 
of 
climate 
change 
on 
survival 
rates 


Now–2025 
Very 
hard 
Developing 
a 
modular 
model 
to 
account 
for 
biophysical 
$600 
k 
and 
economic 
factors 
impacting 
project 
feasibility 
2025–2030 
Easy 
Improve 
the 
coastal 
elevation 
model 
(high 
resolution), 
$100 
m 
improve 
under 
vegetation 


2025–2030 
Moderate 
Biodiversity 
– 
what 
gains 
can 
we 
make 
and 
what 
is 
at 
$50 
m 
risk 
2030–2035 
Hard 
Field 
to 
model 
workflows, 
AUV 
flight 
to 
model 
with 
$100 
m 
plug 
and 
play 


2030–2035 
Very 
hard 
Deployment 
of 
water 
level 
data 
in 
high 
resolution 
grid 
$100 
m 
2035–2040 
Easy 
Ideally 
ensure 
final 
outputs 
can 
be 
used 
by 
less 
?? 
sophisticated 
market 
users 
(local 
councils, 
NRM 
groups 
etc.) 


2035–2040 
Moderate 
Nested 
and 
downscaled 
models 
that 
reliably 
predict 
$200 
m 
hydrodynamics 
from 
automated 
DEM/bathymetry 
2035–2040 
Very 
hard 
Hydrodynamic 
high-resolution 
model 
that 
works 
off 
a 
$200 
m 
single 
platform 


Methods 
and 
indices 
for 
measuring 
other 
benefits 



114 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Figure 
A1.12: 
Translated 
Miro 
results 
for 
indices 
for 
measuring 
other 
benefits. 


Table 
A1.12: 
Implementation 
steps 
for 
indices 
for 
measuring 
other 
benefits. 


TechnologyimplementationSteps
Timeframe 
Difficulty 
Implementation 
step 
Investment 


Now–2025 
Easy 
Determination 
of 
what 
metrics 
to 
use 
now 
$1 
m 
Now–2025 
Easy 
If 
non-carbon 
benefits 
are 
being 
viewed 
as 
a 
market-based 
approach 
to 
achieve 
additional 
revenue, 
then 
demand 
for 
these 
benefits 
needs 
to 
be 
assessed 
(or 
policies 
put 
in 
place 
to 
create 
demand) 
before 
they 
are 
relied 
upon 
too 
heavily 
as 
a 
solution 
? 


Now–2025 
Hard 
Engagement 
with 
First 
Nations 
communities 
to 
build 
First 
Nations 
? 
perspectives 
and 
knowledge 
into 
approach 
2025–2030 
Moderate 
Develop 
guidance 
for 
what 
claims 
can 
be 
made 
by 
buyers 
or 
producers 
of 
? 
non-carbon 
benefits 


2025–2030 
Moderate 
For 
water 
quality, 
need 
to 
know 
nitrogen 
(and 
other 
nutrients) 
in 
tidal 
$50 
m 
water 
and 
residence 
time 
(links 
to 
hydro 
models) 
2025–2030 
Hard 
Pilot 
sites 
for 
sensor 
development 
and 
proof 
of 
concept 
to 
market 
$300 
m 


2025–2030 
Hard 
Model 
of 
connectivity 
for 
species 
that 
transition 
through 
landscapes 
$50 
m 
2030–2035 
Very 
hard 
Nested 
and 
downscaled 
models 
to 
predict 
coastal 
resilience 
(could 
be 
? 
linked 
to 
hydrodynamic 
models) 


2035–2040 
Very 
hard 
Automated 
biodiversity 
monitoring, 
e.g. 
acoustics 
for 
birds, 
insects, 
bats 
$100 
m 
etc. 
2035–2040 
Very 
hard 
Detect 
species 
diversity 
of 
vegetation 
from 
satellites 
$100 
m 


2035–2040 
Very 
hard 
Capacity 
to 
analyse 
eDNA 
for 
a 
range 
of 
species 
rapidly 
and 
cheaply 
– 
$200 
m 
national 
platform. 
Can 
detect 
invasives 
and 
disease 
2040–2045 
Hard 
Government 
floor 
prices 
for 
voluntary 
biodiversity 
credits 
? 


2045–2050 
Very 
hard 
Valuing 
biodiversity 
$50 
m 


2025–2030 
Moderate 
Incentives 
for 
operators 
to 
deploy 
a 
crew 
with 
potential 
to 
harvest 
small-
scale 
plantings 



2025–2030 
Somewhat 
Case 
studies 
including 
costs 
and 
benefits, 
so 
that 
people 
feel 
comfortable 
hard 
to 
invest 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
115 



2030–2035 
Easy 
Aggregation 
of 
biomass 
can 
be 
facilitated 
by 
farm-based 
harvesting 
2030–2035 
Moderate 
Open-source 
hardware/equipment 
sharing/lease 
models 



A.1.3 
Direct 
air 
capture 
workshop 
Materials 


FigureA1.13:TranslatedMiroresultsfornewmaterialsfordirectaircapture.

TableA1.13:Implementationstepsfornewmaterialsfordirectaircapture.


Technologyimplementationsteps
Timeframe 
Difficulty 
Implementation 
step 
Investment 


2025–2030 
Very 
easy 
Evaluation 
of 
existing 
materials 
in 
lab 
and 
demo-plants 
$100 
m 
2025–2030 
Very 
easy 
Establishment 
of 
several 
supply 
chains 
for 
different 
materials 
$100 
m 


2025–2030 
Easy 
Solids 
and 
liquids 
– 
increase 
life 
– 
high 
reactive 
and 
low-cost 
$50 
m 
sorbents 
2025–2030 
Moderate 
Improve 
material 
stability/lifetime 
$100 
m 


2025–2030 
Hard 
Develop 
best 
materials 
(life, 
loading, 
reaction 
rate) 
at 
lab 
scale 
$100 
m 
2025–2030 
Very 
hard 
Reduce 
material 
degradation 
$500 
m 


116 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



2030–2035 
Easy 
Scale 
up 
manufacture 
and 
shaping 
$100 
m 
2035–2040 
Moderate 
Scale 
up 
of 
best 
materials 
to 
operational 
scales 
$100 
m 
2035–2040 
Moderate 
Recycle-regenerate 
spent 
materials 
$100 
m 
2035–2040 
Hard 
Improved 
lifetime 
sorbents 
with 
strong 
supply 
chain 
$1 
b+ 


2035–2040 
Very 
hard 
Continued 
material 
improvements 
$50 
m 
2040–2045 
Moderate 
Reduce 
supply 
chain 
costs 
of 
large 
amounts 
of 
material 
to 
$100 
m 
millions 
of 
tonnes 


2040–2045 
Very 
hard 
Large-scale 
manufacturing 
of 
advanced 
materials 
$1 
b 


Process 
and 
equipment 



Sequestration 
Cost 
Reduction 
Workshops 
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| 
117 



Figure 
A1.14:Translated 
Miro 
results 
for 
process 
and 
equipment. 


Table 
A1.14: 
Implementation 
steps 
for 
process 
and 
equipment. 


Technologyimplementationsteps
Timeframe 
Difficulty 
Implementation 
step 
Investment 
2025–2030 
Very 
easy 
Concept 
evaluation 
in 
demo-plants 
$50 
m 
each 
tech 
2025–2030 
Moderate 
Increase 
surface 
area 
and 
air 
flow 
over 
solids 
$50 
m 
2025–2030 
Hard 
Large, 
low-pressure 
drop 
contractors 
$30 
m 
2030–2035 
Moderate 
Efficient 
high-volume 
manufacturing, 
low-pressure 
drop 
$100 
m 
contractor, 
maximum 
cost 
reduction 
through 
scale-up 
2030–2035 
Moderate 
Systems 
engineering 
and 
control 
$100 
m+ 
2030–2035 
Moderate 
Large-scale 
air 
movement 
with 
low 
energy 
$100 
m+ 
2030–2035 
Very 
hard 
Full 
use 
of 
heat 
pumps 
for 
heat 
supply 
$300 
m 
2035–2040 
Very 
easy 
Demonstration 
of 
advanced 
systems 
$100 
m 
2035–2040 
Easy 
Large-scale 
plant 
design 
and 
construction 
Many 
billions 
2035–2040 
Moderate 
Develop 
advanced 
materials 
into 
processes/equipment 
$50 
m 
2040–2045 
Very 
hard 
Complete 
dynamic 
system 
at 
scale. 
Low 
pressure 
drop. 
Heat 
$1 
b+ 
integration. 
Instrumented 
for 
complex 
process 
control 
to 
account 
for 
changes 
in 
weather 
and 
season 


118 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Energy 
supply 



Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
119 



Figure 
A1.15: 
Translated 
Miro 
results 
for 
energy 
supply. 


Table 
A1.15: 
Implementation 
steps 
for 
energy 
supply. 


Technologyimplementationsteps
Timeframe 
Difficulty 
Implementation 
step 
Investment 


2025–2030 
Easy 
Assess 
different 
integration 
options 
for 
DAC 
plants 
with 
renewable 
In 
energy 
(Solar 
Thermal, 
PV, 
Geothermal) 
or 
nuclear 
energy 
conjunction 
with 
demo-
plants 
2025–2030 
Moderate 
Store 
heat 
instead 
of 
electricity 
$100 
m 
2030–2035 
Easy 
Examine 
large-scale 
use 
of 
gas 
on 
location 
(gas 
supply 
and 
storage 
$50 
m 
without 
transport). 
Needs 
societal 
examination 
2030–2035 
Moderate 
Reduce 
energy 
consumption 
(MWh/t) 
of 
DAC 
equipment 
$100 
m 


2030–2035 
Moderate 
Large 
scale 
24/7 
supply 
of 
renewable 
electricity 


2030–2035 
Moderate 
Assessment 
of 
flexible 
operation 
and 
its 
effect 
on 
cost 
(trade-off 
between 
emission 
reduction 
cost), 
reducing 
the 
energy 
requirement 
of 
the 
process, 
using 
energy 
integration 
between 
various 
processes 
and 
DAC 



2030–2035 
Hard 
Energy 
supply 
could 
be 
integrated 
and 
not 
require 
any 
integration 
with 
$100 
m 
existing 
grids 
(e.g. 
autonomous 
DA 
systems). 
Australia 
would 
be 
ideally 
placed 
here 
given 
large 
areas 
of 
non-arable 
lands 
for 
use 
of 
solar 


2030–2035 
Very 
hard 
Dynamic 
system 
analysis 
$100 
m 


2035–2040 
Very 
hard 
Low-cost 
integration 
of 
intermittent 
renewables 
with 
DAC 
$100 
m+ 


2040–2045 
Moderate 
Development 
of 
~100% 
electrically 
driven 
DAC 
to 
leverage 
increased 
$1 
b+ 
low-cost 
renewable 
energy 


120 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



A.1.4 
Biomass/biochar 
workshop 
Technology 
at 
scale 



Figure 
A1.16:Translated 
Miro 
results 
for 
technology 
at 
scale. 


Table 
A1.16: 
Implementation 
steps 
technology 
at 
scale. 


TimeframeDifficultyImplementationstepInvestment
Now–2025 
Very 
easy 
PyCCS 
targeted 
community 
marketing 
and 
education 
$5 
m 
over 
5 
years 


2025–2030 
Very 
easy 
Demo 
plants 
for 
different 
feedstocks 
and 
co-product 
applications 
$10 
m 
(syngas) 


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Cost 
Reduction 
Workshops 
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| 
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2025–2030 
Easy 
Exemplars 
in 
special 
activation 
precincts 
in 
industrial 
symbiosis 
ecosystem 
2025–2030 
Moderate 
Syngas 
to 
liquids 
at 
1 
MW 
scale 
enables 
use 
of 
remote 
biomass 



2025–2030 
Moderate 
Increase 
CRL 
of 
technologies 
required 
through 
pilot 
and 
$50 
m 
demonstration 
projects. 
Also 
need 
to 
include 
wider 
value 
chains 


2025–2030HardDemonstrationofcommercialscalehydrogenproduction2030–2035EasyExploremarketsforuseofproductsandsetupofftakeagreements
2030–2035 
Moderate 
Community 
and 
stakeholder 
engagement, 
work 
on 
sourcing 
$20 
m 
biomass 
for 
implementation 
2030–2035 
Moderate 
Build 
commercial-scale 
plant 
at 
location 
near 
sources 
of 
biomass 
$200 
m 
and 
utilisation 
– 
a 
hub? 
Based 
on 
lessons 
learnt 
from 
pilot/demo 
scale 


2030–2035 
Very 
hard 
Pilot 
and 
demo 
scale 
plants, 
some 
commercial 
should 
be 
built, 
Billions 
tested 
with 
lots 
of 
data 
to 
generate 
confidence 
about 
the 
technology 


Large-scale 
modular 
plants 



122 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Figure 
A1.17:Translated 
Miro 
results 
for 
development 
of 
large-scale 
modular 
plants. 


Table 
A1.17: 
Implementation 
steps 
for 
development 
of 
large-scale 
modular 
plants. 


TimeframeDifficultyImplementationstepInvestment
2025–2030 
Moderate 
Assessment 
of 
sustainable 
biomass 
in 
Australia 
for 
use 
in 
modular 
$10 
m 
plants 
to 
allow 
for 
locations 
of 
plants 
to 
be 
determined 
2030–2035 
Easy 
Bankable 
feasibility 
studies 
with 
offtakes 
and 
feed 
security 
for 
regional 
hubs 
2035–2040 
Hard 
Detailed 
cost 
calculations 
with 
demonstrations 
to 
the 
investors 
$1 
b 


Utilisation 
cases 
Table 
A1.18: 
Implementation 
steps 
for 
utilisation 
cases. 


TechnologyimplementationstepsTimeframeDifficultyImplementationstepInvestment
Now–2025 
Very 
easy 
Commercial 
scale 
(broadacre) 
demonstrations 
for 
multiple 
soil 
applications 
and 
commercial 
scale 
demonstrations 
for 
non-soil 
(industrial) 
uses 
of 
biochar 
(e.g. 
concrete, 
roads, 
bioplastics, 
batteries 
etc.) 


Sequestration 
Cost 
Reduction 
Workshops 
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| 
123 



Now–2025 
Easy 
Regional 
training 
facilities 
for 
highly 
skilled 
plant 
operators 
and 
$10–$100 
m 
managers 


2025–2030 
Easy 
Standalone 
commercial 
PyCCS 
plants 
online 
– 
self 
funded 
with 
support 
from 
CORCs 
(10–15 
plants 
circa 
200,000 
t/year 
biochar, 
100 
MW) 
$250 
m 
2025–2030 
Hard 
Large-scale 
field 
trials 
of 
use 
of 
biochar 
in 
different 
conditions 
and 
soil 
types 
around 
Australia 
$30 
m 


2030–2035 
Moderate 
Extensive 
community 
and 
potential 
market 
engagement 
on 
the 
use 
$20 
m 
of 
biochar 
in 
agriculture 
and 
other 
use 
cases 
such 
as 
industry 


2030–2035 
Hard 
Industry 
has 
scaled 
up 
to 
allow 
widespread 
use 
of 
biochar 
in 
hubs 
including 
industry 
and 
agriculture 



2035–2040 
Easy 
Various 
products 
need 
to 
have 
specifications 
as 
per 
standard 
and 
$500 
m 
have 
to 
be 
acceptable 
to 
the 
users 
in 
the 
final 
utilisation 
cases 


Guidelines 
Table 
A1.19: 
Implementation 
steps 
for 
the 
development 
of 
guidelines 
and 
best 
practices. 


TechnologyimplementationstepsTimeframeDifficultyImplementationstepInvestment
2025–2030 
Very 
easy 
Identify 
knowledge 
gaps 
(soils, 
ag 
systems, 
formulations) 
$200 
k 
2025–2030 
Easy 
Develop 
standards, 
get 
ratified 
and 
then 
develop 
guidelines 
and 
$50 
m 
implement 
knowledge 
centres 
2025–2030 
Easy 
Regulatory 
sandboxes 
for 
environmental 
approvals 
$5–$20 
m 
2025–2030 
Easy 
Research 
targeted 
to 
fill 
knowledge 
gaps 
(soil 
types/ag 
$20 
m 
systems/biochar 
formulations/climatic 
regions). 
How 
much 
biomass 
can 
be 
removed 
whilst 
maintaining 
soil 
health 
Pre-processing 
of 
feedstocks 
for 
pyrolysis 
Table 
A1.20: 
Implementation 
steps 
for 
the 
pre-processing 
of 
feedstocks 
for 
pyrolysis. 


TechnologyimplementationstepsTimeframeDifficultyImplementationstepInvestment
2025–2030 
Very 
easy 
Develop 
collection 
and 
continuous 
large 
tonnage 
throughput 
$100 
m 
dryer 
and 
feed 
preparation 
technology 
for 
downstream 
conversion 


124 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



A.1.5 
Carbon 
capture 
and 
storage 
workshop 
Improved 
capture 
technologies 



Sequestration 
Cost 
Reduction 
Workshops 
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| 
125 



TechnologyimplementationstepsTimelineDifficultyImplementationstepInvestmentrequired
Now–2025 
Very 
easy 
Tax 
credits, 
funding 
and 
government 
financing 
for 
capturing 
$200 
m 
R&D, 
pilots 
and 
early 
roll 
out 
2025–2030 
Very 
easy 
Collaboration 
internationally 
at 
scale 
rather 
than 
$1 
b 
solo/Australian 
development 
for 
EITE 
Industries 


2025–2030 
Very 
easy 
Availability 
of 
early-stage 
funding 
$100 
m 
2025–2030 
Easy 
Initial 
R&D 
$100 
m 


2025–2030 
Moderate 
Development 
of 
high 
efficiency/low 
energy 
absorption 
$100 
m 
solvents 
2025–2030 
Moderate 
International 
collaboration 
watching 
brief 
$50 
m 


2025–2030 
Hard 
Incentivisation 
of 
carbon 
capture 
trials 
(without 
storage) 
in 
$100 
m 
hard 
to 
abate 
industries 
2030–2035 
Moderate 
Pilot/trial 
capture 
plants 
$500 
m 


2030–2035 
Moderate 
Pilot 
facilities 
$500 
m 
2030–2035 
Moderate 
Pilot 
plants 
$150 
m 
2030–2035 
Moderate 
Identify 
the 
key 
targets 
within 
the 
capture 
technologies 
$100–$500 
m 
(industries 
select 
the 
technology) 
and 
their 
locations 
(cannot 
work 
on 
everything 
– 
target 
the 
key 
needs) 
2030–2035 
Moderate 
Full 
scale 
test 
$300 
m 


126 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



2030–2035 
Hard 
Ability 
to 
stack 
incentives 
2030–2035 
Very 
hard 
CCS 
(Full 
Chain) 
on 
cement 
– 
possibly 
via 
a 
pilot 
plant. 
Timing 
$100 
m 
dependent 
on 
cement 
business 
case, 
technology 
development 
and 
set 
up 
of 
full 
chain 


Storage 
optimisation 
and 
efficiency 



Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
127 



TechnologyimplementationstepsTimelineDifficultyImplementationstepInvestmentrequired
Now–2025 
Hard 
Complete 
site 
appraisal 
early 
and 
then 
develop 
potential 
secondary 
and 
tertiary 
technologies 
which 
may 
then 
be 
suitable 
for 
site 
optimisation 
2025–2030 
Very 
easy 
Evaluate 
existing 
systems 
and 
new 
injection 
technologies 
(MB, 
$50–$200 
m 
micropulsing, 
surfactants 
etc.) 
via 
demonstration 
projects 
to 
establish 
applicability 
into 
high 
quality 
(mostly 
offshore) 
and 
low 
quality 
(often 
onshore) 
storage 
systems. 
New 
modelling 
approaches 
in 
heterogeneous 
systems 
integrated 
with 
new 
MMV 
approaches, 
to 
confirm 
improvements 
in 
efficiency. 
Confirm 
early 
on 
how 
big 
the 
wins 
might 
be, 
therefore 
how 
applicable 
are 
the 
technologies 
– 
do 
they 
make 
a 
difference? 
What 
are 
the 
regulators 
after 
now 
and 
into 
the 
future? 


2025–2030EasyInitialR&D$10m2025–2030EasyMicrobubbleinjectiontechnology
2025–2030 
Easy 
Site 
storage 
in 
the 
best 
location 
and 
highest 
confidence 
locations 
$1 
b 
with 
optionality. 
Understand 
reservoir 
and 
seal 
variation 
and 
impact 
on 
storage 
factors 
– 
highly 
site 
specific 
2025–2030 
Moderate 
Incentives 
to 
pilot 
test 
new 
ideas 
in 
the 
most 
prospective 
and 
$50 
m 
advanced 
development 
reservoirs 


2030–2035 
Easy 
Field 
testing 
$5 
m 


128 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



2030–2035 
Moderate 
Innovative 
injection 
and 
plume 
management 
$200 
m 


2035–2040 
Very 
easy 
Trial 
horizontal 
vs 
vertical 
injection 
wells 
in 
a 
storage 
reservoir 
to 
$50 
m 
investigate 
improved 
storage 
efficiency 
2035–2040 
Fund 
any 
technology 
that 
could 
increase 
efficiency 
of 
individual 
$1 
b 
Hard 
injector 
wells 
– 
assume 
global 
R&D 
across 
academia 
and 
industry 


Implementation 
of 
hubs 



Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
129 



TechnologyimplementationstepsTimelineDifficultyImplementationstepInvestmentrequired
Now–2025 
Very 
hard 
Find 
the 
anchor 
sink(s) 
and 
increase 
confidence, 
then 
optimise 
hub 
(scale, 
sequence, 
routes 
etc.) 
to 
‘match’ 
sink 
is 
the 
unit 
cost 
driver. 
Timing 
depends 
on 
getting 
the 
primary 
appraisal 
done 
2025–2030 
Very 
easy 
Information 
and 
community 
consultation 
$50 
m 
2025–2030 
Very 
easy 
Investigate/model 
shared 
compression 
and 
pipeline 
facility 
costs 
to 
$3–5 
m 
allow 
the 
aggregation 
and 
transportation 
of 
CO2 
captured 
from 
smaller 
industrial 
emitters 
2025–2030 
Easy 
Development 
of 
optimum 
gathering 
CO2 
quality 
standards 
$10 
m 


2025–2030 
Easy 
Develop 
standards 
for 
blow-down/venting 
of 
CO2 
$10 
m 



2025–2030 
Easy 
Use 
NT 
LE 
Hub 
as 
example 
– 
but 
not 
really 
a 
CCS 
investment 
– 
it 
assumes 
we 
have 
located 
it 
in 
the 
right 
place 


2025–2030 
Moderate 
Establish 
required 
permitting 
$100 
m 



2025–2030 
Hard 
Financial 
engineering 


2030–2035 
Very 
easy 
Potential 
government 
investment 
in 
common 
user 
infrastructure, 
i.e. 
Alberta 
trunk 
line 



2030–2035 
Easy 
Reduction 
of 
government 
red 
tape 
to 
facilitate 
growth 
of 
number 
of 
emitters 
in 
hubs 
(sea 
dumping) 


130 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



2030–2035 
Moderate 
Facilitation 
by 
government 
$500 
m 
2030–2035 
Moderate 
Establish 
risk 
sharing 
contractual 
experience 
across 
common 
$500 
m 
stakeholders 


2030–2035 
Hard 
Driven 
by 
industry; 
perhaps 
the 
role 
for 
government 
and 
others 
is 
in 
$20–$100 
m 
framing 
what 
is 
possible 
(middle 
arm 
etc.). 
Learn 
from 
other 
players 
overseas 


Reservoir 
exploration 
and 
identification 


TechnologyimplementationstepsTimelineDifficultyImplementationstepInvestmentrequired
2025–2030 
Very 
easy 
Exploration 
for 
saline 
aquifer 
storage 
around 
Australia 
$20–$25 
m 
per 
annum 
2025–2030 
Moderate 
Better 
assess 
the 
injection 
characteristics 
and 
storage 
potential 
of 
$5 
m 
per 
annum 
heterogeneous 
and 
lower 
permeability 
reservoirs 
in 
onshore 
settings 
(essential 
for 
hard 
to 
abate 
and 
DAC-S) 
– 
what 
storage 
is 
available 
where 
and 
can 
it 
be 
used, 
especially 
with 
new 
injection 
paradigms? 
Align 
the 
sources 
and 
sinks 
onshore 


A.1.6 
Mineral 
carbonation 
workshop 
Still 
to 
come. 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
131 



Miro 
Screens 


B.1.1 
Planted 
vegetation 
workshop 
132 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
133 



134 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
135 



136 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



B.1.2 
Blue 
carbon 
workshop 
Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
137 



B.1.3 
Direct 
air 
capture 
workshop 
138 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
139 



B.1.4 
Biomass/biochar 
workshop 
140 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
141 



142 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



B.1.5 
Carbon 
capture 
and 
storage 
Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
143 



144 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



B.1.6 
Mineral 
Carbonation 
Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
145 



146 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
147 



148 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Workshop 
participants 


C.1.1 
Planted 
vegetation 
Participant 
Company 
Natasa 
Sikman 
AFPA/Forest 
Product 
Association 
Anthony 
Fitzgerald 
Carbon 
Conscious 
Zoe 
Ryan 
Climate 
Friendly 
Tai 
White-Toney 
CO2 
Australia 
Shaun 
Levick 
CSIRO 
Stephen 
Roxburgh 
CSIRO 
Paul 
Ryan 
DCCEEW 
Peter 
Ritson 
FarmWoods 
Jenny 
Sinclair 
GreenCollar 
Beren 
Spencer 
INPEX 
Arjan 
Wilkie 
Landari 
Philipp 
Kilham 
Mullion 
Group 
Annette 
Cowie 
NSW 
DPI 
Simon 
Dawkins 
Oil 
Mallee 
Association 
Martin 
Moroni 
Private 
Forests 
Tasmania 
Tim 
Moore 
RegenCo 
Rod 
Keenan 
University 
of 
Melbourne 
Liam 
Costello 
Vic 
Department 
of 
Jobs, 
Precincts 
and 
Regions 


C.1.2 
Blue 
carbon 
Participant 
Company 
Andy 
Steven 
CSIRO 
Ray 
Marcos 
Martinez 
CSIRO 
Cath 
Lovelock 
University 
of 
Queensland 
Lauren 
Drake 
Pollination 
Mat 
Vanderklift 
CSIRO 
Valerie 
Hagger 
University 
of 
Queensland 
Nikki 
Fitzgerald 
DCCEW 
Veda 
Fitzsimmons 
Pollination 


C.1.3 
Direct 
air 
capture 
Participant 
Company 
Paul 
Feron 
CSIRO 
Roger 
Aines 
Lawrence 
Livermore 
national 
Laboratory 
Timothy 
Fout 
US 
Department 
of 
Energy 
Paul 
Webley 
Monash 
University 
Deanna 
Dalessandro 
University 
of 
Sydney 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
149 



Julian 
Tureck 
Aspiridac 
Ali 
Kiani 
CSIRO 
M 
Lucquiaud 
Sheffield 
University 
Christopher 
Jones 
Georgia 
Tech 


C.1.4 
Biomass/biochar 
Participant 
Company 
Peter 
Burgess 
Rainbow 
Bee 
Eater 
Annette 
Cowie 
NSW 
DPI 
Craig 
Bagnall 
Catalyst 
Environmental 
Management 
Fabiano 
Ximenes 
NSW 
DPI 
Rajinder 
Singh 
Daintree 
Bio 
Ian 
O'Hara 
QUT 
Stephen 
Joseph 
UNSW 
Gustavo 
Fimbres 
Weihs 
University 
of 
Sydney 
Jenny 
Hayward 
CSIRO 
Nawshad 
Haque 
CSIRO 


C.1.5 
Carbon 
capture 
and 
storage 
Participant 
Company 
Peter 
Cook 
Melbourne 
University 
Charles 
Jenkins 
CSIRO 
Darren 
Greer 
Glencore 
Andrew 
Garnett 
University 
of 
Queensland 
Phil 
Grainger 
Inpex 
Geoff 
Obrien 
Co2rc 
Noel 
Simento 
Anlecrd 
Matthew 
Sherwell 
Santos 


C.1.6 
Mineral 
Carbonation 
Participant 
Company 
Renee 
Birchall 
CSIRO 
Andrew 
Lenton 
CSIRO 
John 
Beever 
Green 
Mag 
Group 
Sophia 
Hamblin-Wang 
Mineral 
Carbonation 
Mojtaba 
Seyyedi 
Global 
CCS 
Institute 
Philip 
Fawell 
CSIRO 
Mei 
Yuan 
CSIRO 
Stuart 
Watson 
Rio 
Tinto 
Ralf 
Haese 
Melbourne 
University 


150 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Review 
Comments 


Workshop 
Participant 
Comment 
Planted 
vegetation 
I 
just 
reviewed 
the 
docs 
provided 
and 
the 
one 
important 
observation 
from 
the 
workshop 
that 
is 
not 
covered 
in 
the 
report 
(that 
I 
can 
see) 
is 
that 
the 
technologies 
and 
hence 
savings 
depend 
on 
the 
specific 
methodology 
being 
used. 
The 
HIR, 
reforestation 
and 
plantations 
methods 
have 
different 
cost 
bases 
and 
different 
requirements, 
hence 
the 
spread 
in 
assessment 
of 
the 
cost/benefit 
for 
each 
technology, 
"despite 
the 
consensus 
building 
exercise". 
Is 
there 
a 
need 
to 
clarify 
what 
is 
covered 
by 
zero 
or 
low 
emission 
fuels, 
in 
relation 
to 
inclusion 
of 
electrification 
as 
part 
of 
this 
technology, 
i.e. 
is 
it 
correct 
to 
describe 
electrification 
as 
zero 
or 
low 
emissions 
fuels, 
or 
should 
the 
category 
description 
to 
changed 
to 
include 
electrification? 
Blue 
Carbon 
I 
understand 
the 
focus 
of 
this 
workshop 
was 
about 
exploring 
technology 
options 
for 
cost 
reduction 
in 
tidal 
restoration 
projects. 
Another 
option 
for 
cost 
reduction 
is 
aggregation 
of 
restoration 
sites 
to 
form 
a 
restoration 
program 
like 
is 
being 
done 
with 
environmental 
plantings 
under 
the 
ERF. 
Although 
we 
didn’t 
identify 
a 
technology 
that 
could 
assist 
this. 
I 
notice 
that 
the 
co-benefits 
receive 
no 
cost 
reduction, 
but 
we 
should 
frame 
this 
as 
how 
it 
can 
build 
the 
regional 
economy 
(i.e. 
through 
enhancing 
natural 
resources), 
which 
could 
build 
the 
capacity/willingness 
of 
the 
community 
to 
undertake 
restoration 
projects. 
CCS 
CCS 
is 
a 
chain 
of 
technologies 
from 
capture, 
transport, 
compression, 
well 
design 
and 
storage 
-each 
has 
its 
own 
challenges 
and 
enablers. 
It 
is 
too 
diverse 
a 
topic 
to 
be 
easily 
captured 
in 
one 
3 
hour 
online 
workshop 
where 
not 
all 
elements 
of 
the 
chain 
were 
represented. 
Thus 
the 
workshop 
findings 
are 
a 
guide 
to 
some 
aspects 
of 
CCS 
but 
not 
comprehensive 
enough 
to 
be 
useful. 
Mineral 
Carbonation 
I 
think 
the 
quoted 
cost 
(from 
Carbfix) 
of 
$25/tonne 
as 
the 
base 
cost 
for 
in-situ 
carbonation 
is 
deeply 
misleading. 
First 
of 
all 
the 
Carbfix 
cost 
is 
only 
part 
of 
the 
system 
e.g. 
it 
doesn’t 
include 
the 
wells 
for 
water 
supply, 
and 
the 
delineation 
of 
the 
boundaries 
around 
costing 
is 
crucial 
for 
any 
comparisons. 
The 
Carbfix 
cost 
also 
doesn’t 
include 
the 
capture 
process, 
and 
that 
to 
me 
is 
not 
a 
fair 
comparison 
to 
other 
technologies. 
Lastly 
and 
most 
crucially, 
the 
Carbfix 
case 
is 
an 
extremely 
favourable 
case 
for 
in-situ 
carbonation 
because 
the 
effective 
permeability 
is 
so 
high 
(around 
a 
Darcy 
for 
Carbfix2). 
The 
costs 
in 
lower 
permeability 
could 
be 
10 
or 
100 
times 
greater. 
So 
the 
whole 
presentation 
of 
how 
particular 
advances 
in 
situ 
carbonation 
might 
reduce 
costs 
(which 
in 
themselves 
are 
incredibly 
speculative) 
are 
subject 
to 
enormous 
error 
based 
on 
a 
scale 
of 
orders 
of 
magnitude. 
I 
don’t 
think 
that’s 
a 
good 
basis 
for 
deciding 
which 
directions 
to 
follow. 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
151 



Cash 
flow 
model 
for 
a 
biochar 
production 
plant 


E.1 
Production 
system 
The 
hypothetical 
biochar 
production 
system 
is 
a 
medium 
sized 
(1 
MWh) 
slow-pyrolysis 
system 
with 
fixed 
bed 
twin-fire 
pyrolyser. 
We 
assume 
this 
type 
of 
system 
because:(1) 
its 
medium 
size 
means 
that 
there 
is 
likely 
sufficient 
feedstock 
to 
run 
the 
system 
in 
several 
Australian 
regions; 
and 


(2) 
Homagain 
et 
al. 
(2016) 
used 
this 
type 
of 
system 
for 
their 
economic 
assessment 
of 
biochar 
production 
in 
Canada, 
providing 
some 
cost 
data 
for 
this 
analysis. 
We 
assume 
that 
the 
biochar 
produced 
is 
applied 
into 
agricultural 
fields. 
Rajabi 
Hamedani 
et 
al. 
(2019) 
provide 
the 
following 
inventory 
for 
1 
tonne 
of 
biochar 
obtained 
via 
willow 
pyrolysis 
and 
applied 
into 
fields. 
Note, 
in 
our 
analysis 
we 
assume 
that 
woodchips 
from 
sawmill 
residue 
rather 
than 
willow 
woodchips 
are 
used 
as 
a 
feedstock. 


 
Inputs: 
willow 
woodchips 
3.73 
t; 
heat 
(pyrolysis) 
1.92 
GJ 
 
Outputs: 
biochar 
1 
t; 
syngas 
(SO2 
0.015 
kg; 
NOx 
0.2 
kg) 
 
Avoided 
products: 
natural 
gas 
0.37 
t; 
electricity 
1.01 
GJ; 
N 
fertiliser 
0.66 
kg; 
K 
fertiliser 
0.13 
kg; 
P 
fertiliser 
0.1 
kg 
 
Avoided 
emissions 
from 
the 
application 
of 
1 
t 
of 
biochar 
into 
fields: 
2.2 
t 
CO2 
and 
2.6 
kg 
N20, 
which 
combine 
for 
total 
avoided 
emissions 
of 
2.975 
t 
CO2-e 
We 
assume 
that 
the 
production 
plant 
will 
be 
operational 
for 
25 
years 
(Homagain 
et 
al. 
2016) 
and 
will 
have 
7000 
working 
hours 
per 
year 
(Rajabi 
Hamedani 
et 
al. 
2019). 
As 
such, 
the 
plant 
produces 
13,125 
tonnes 
of 
biochar 
per 
year, 
which 
requires 
48,956 
tonnes 
of 
sawmill 
residue 
per 
year 
as 
feedstock. 
Based 
on 
NSW 
sawmill 
residues 
data,7 
there 
are 
several 
regions 
in 
NSW 
that 
have 
over 
50,000 
tonnes 
of 
sawmill 
residue 
within 
a 
few 
hundred 
kilometres 
of 
a 
hypothetical 
production 
plant. 


We 
assume 
that 
the 
production 
system 
starts 
with 
the 
purchase 
and 
transportation 
of 
the 
feedstock 
to 
the 
plant 
and 
ends 
with 
the 
production 
of 
biochar, 
which 
is 
then 
stored 
on 
site. 
That 
is, 
we 
exclude 
the 
sale 
and 
transportation 
of 
biochar 
and 
its 
co-products 
(fertilisers, 
SO2, 
NOx) 
from 
the 
model, 
as 
the 
feasibility 
and 
costs 
of 
selling 
these 
products 
in 
different 
regions 
are 
unknown. 


E.2 
Revenues 
In 
the 
above 
inventory 
for 
1 
tonne 
of 
biochar 
production, 
the 
quantities 
of 
carbon, 
electricity 
and 
natural 
gas 
produced 
are 
constants 
multiplied 
by 
the 
quantity 
of 
biochar 
produced 
𝐵􀯧. 
Therefore, 
total 
revenue 
from 
the 
hypothetical 
plant’s 
biochar 
production 
in 
each 
year 
𝑡 
= 
1,2, 
…,25 
can 
be 
expressed 
as: 


𝑅ç 
= 
𝐵􀯧􀵫2.975𝑃􀯖􀯔􀯥􀯕􀯢á 
+ 
0.281𝑃􀯘􀯟􀯘Ö 
+ 
0.37𝑃􀯚􀯔􀯦o 


where: 


7 
https://spatial.industry.nsw.gov.au/arcgis/rest/services/Bioenergy_Assessment/Forestry_SawmillResidues/MapServer 


152 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



 
𝐵ç 
is 
the 
amount 
(tonnes) 
of 
biochar 
produced 
 
𝑃􀯖􀯔􀯥􀯕􀯢á 
is 
the 
price 
per 
t 
CO2-e 
avoided 
 
𝑃􀯘􀯟􀯘Ö 
is 
the 
price 
per 
MWh 
of 
electricity 
 
𝑃􀯚􀯔æ 
is 
the 
price 
per 
tonne 
of 
natural 
gas. 
The 
plant’s 
pyrolysis 
process 
generates 
excess 
energy 
as 
a 
co-product 
in 
the 
form 
of 
bio-oil 
and 
syngas, 
avoiding 
some 
consumption 
and 
production 
of 
electricity 
and 
natural 
gas 
(Rajabi 
Hamedani 
et 
al. 
2019). 
We 
assume 
that 
syngas 
is 
burnt 
to 
provide 
the 
internal 
energy 
requirements 
for 
heat 
and 
electricity 
of 
the 
pyrolysis 
process 
(i.e. 
it 
is 
a 
cost 
offset 
rather 
than 
a 
revenue 
stream). 
We 
also 
assume 
that 
excess 
energy 
from 
burning 
syngas 
on 
top 
of 
internal 
energy 
requirements 
is 
offset 
to 
the 
market 
as 
a 
substitute 
for 
natural 
gas 
and 
electricity. 


E.3 
Costs 
The 
initial 
capital 
cost 
of 
the 
plant 
is: 


𝐶4 
= 
𝐶􀯘􀯤􀯨􀯜ã 
+ 
𝐶􀯕􀯨􀯜􀯟× 
+ 
𝐶􀯢􀯧􀯛Ø 


where 
𝐶􀯘􀯤􀯨􀯜ã 
is 
the 
cost 
of 
plant 
equipment, 
𝐶􀯕􀯨􀯜􀯟× 
is 
the 
construction 
cost 
of 
the 
plant, 
and 
𝐶􀯢􀯧􀯛􀯘å 
is 
the 
cost 
of 
related 
activities 
(feasibility 
study 
etc.). 
Total 
production 
cost 
in 
each 
year 
𝑡 
= 
1,2, 
…,25 
is: 


𝐶ç 
= 
𝐵􀯧[3.73(𝑃􀯪􀯢􀯢× 
+ 
6.2 
+ 
0.16𝐷) 
+ 
0.533𝑃􀯘􀯟􀯘􀯖] 
+ 
𝑀ç 
+ 
𝑆ç 
+ 
𝐿ç 


where: 


 
𝑃􀯪􀯢􀯢× 
is 
the 
price 
of 
sawmill 
residue 
log 
(the 
feedstock) 
 
𝐷 
is 
the 
average 
haulage 
distance 
of 
feedstock 
to 
the 
production 
plant 
for 
processing 
 
6.2 
+ 
0.16𝐷 
is 
the 
cost 
of 
hauling 
1 
tonne 
of 
feedstock 
to 
the 
plant 
(Roxburgh 
et 
al. 
2020) 
 
𝑀ç 
is 
the 
annual 
plant 
maintenance 
cost 
 
𝑆ç 
is 
the 
annual 
cost 
of 
storing 
the 
feedstock 
and 
the 
outputs 
 
𝐿ç 
is 
the 
annual 
labour 
cost 
of 
running 
the 
plant. 
E.4 
Economic 
viability 
Investing 
in 
the 
production 
plant 
is 
economically 
viable 
if 
the 
NPV 
of 
the 
above 
cash 
flows 
exceeds 
zero. 
The 
NPV 
of 
investing 
in 
the 
plant 
is: 


􀬶9 


(𝑅ç 
− 
𝐶􀯧)

𝑁𝑃𝑉 
= 
Í 


(1 
+ 
𝑖)ç 


􀯧􀭀4 


where 
𝑖 
is 
the 
discount 
rate. 


E.5 
Baseline 
parameter 
values 
The 
table 
below 
provides 
the 
baseline 
parameter 
values 
used 
in 
the 
model. 


Param 
eter 
𝐵ç 
Description 
Annual 
amount 
(t) 
of 
biochar 
produced 
Value 
13,125 
t 
Notes 
𝑃􀯖􀯔􀯥􀯕􀯢á 
Price 
per 
t 
CO2e 
emissions 
reduction 
$20 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
153 



𝑃􀯘􀯟􀯘􀯘􀯟􀯘Ö 
Price 
for 
1 
MWh 
electricity 
$100 
Based 
on 
recent 
wholesale 
electricity 
prices 
in 
Australia: 
https://www.aer.gov.au/wholesalemarkets/
wholesale-statistics. 
𝑃􀯚􀯔æ 
Price 
for 
1 
t 
of 
natural 
gas 
$273 
Based 
on 
the 
longer-term 
average 
natural 
gas 
price 
of 
$7 
per 
GJ 
in 
Australia 
(with 
39 
GJ 
per 
tonne 
of 
natural 
gas): 
https://www.aer.gov.au/wholesalemarkets/
wholesale-statistics/gas-market-prices. 
𝑃􀯪􀯢􀯢× 
Price 
for 
1 
t 
of 
wood 
residue 
$40 
We 
assume 
a 
price 
of 
$30 
per 
tonne 
for 
residue 
log 
as 
per 
Roxburgh 
et 
al. 
(2020) 
and 
add 
a 
cost 
of 
$10 
per 
tonne 
to 
convert 
the 
log 
into 
pellets 
as 
feedstock. 
𝐶􀯘􀯤􀯨􀯜ã 
Cost 
of 
plant 
equipment 
$1.6 
m 
Source: 
Homagain 
et 
al. 
(2016), 
adjusted 
for 
inflation 
and 
exchange 
rates. 
𝐶􀯕􀯨􀯜􀯟× 
Cost 
of 
plant 
construction 
and 
installation 
$1 
m 
Source: 
Homagain 
et 
al. 
(2016), 
adjusted 
for 
inflation 
and 
exchange 
rates. 
𝐶􀯢􀯧􀯛􀯘å 
Other 
initial 
costs 
related 
to 
the 
installation 
of 
the 
plant 
$0.2 
m 
Source: 
Homagain 
et 
al. 
(2016), 
adjusted 
for 
inflation 
and 
exchange 
rates. 
𝐷 
Average 
haulage 
distance 
(feedstock 
to 
plant 
and 
biochar 
to 
field) 
100 
km 
Average 
haulage 
distance 
will 
depend 
on 
the 
region. 
Average 
haulage 
distance 
of 
feedstock 
to 
plant 
is 
likely 
to 
be 
less 
than 
100 
km 
for 
several 
regions 
in 
NSW 
based 
on 
this 
map: 
https://spatial.industry.nsw.gov.au/arcgis/rest 
/services/Bioenergy_Assessment/Forestry_Sawmill 
Residues/MapServer 
𝑀ç 
Annual 
plant 
maintenance 
cost 
$5000 
Source: 
Homagain 
et 
al. 
(2016), 
adjusted 
for 
inflation 
and 
exchange 
rates. 
𝑆ç 
Storage 
cost 
for 
feedstock 
and 
biochar 
$10,000 
Source: 
Homagain 
et 
al. 
(2016), 
adjusted 
for 
inflation 
and 
exchange 
rates. 
𝐿ç 
Labour 
cost 
to 
run 
the 
pyrolysis 
process 
$100,000 
Source: 
Homagain 
et 
al. 
(2016), 
adjusted 
for 
inflation 
and 
exchange 
rates. 
To 
account 
for 
inflation, 
we 
assume 
labour 
cost 
increases 
by 
3% 
per 
year 
from 
a 
value 
of 
$100,000 
in 
year 
1. 
𝑟 
Discount 
rate 
7% 
𝑖 
Inflation 
rate 
3% 


[1] 
https://www.soilwealth.com.au/resources/articles-and-publications/nitrogen-fertiliser-price-andsupply-
a-good-reason-to-look-at-legume-covercrops/#:~:
text=As%20a%20result%2C%20the%20cost,tonne%20or%20%243.04%2Fkg%20N 
[2] 
https://www.indexmundi.com/commodities/?commodity=potassiumchloride&
months=60&currency=aud 
[3] 
https://www.farmonline.com.au/story/7512258/phosphorus-fertiliser-could-hit-1500t-port-next-year/ 


154 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



E.6 
Scenario 
analysis 
We 
compute 
the 
cost 
per 
tonne 
of 
carbon 
sequestration 
(including 
electricity 
and 
gas 
cost 
offsets) 
and 
the 
plant’s 
NPV 
under 
the 
scenarios 
below. 
The 
cost 
per 
tonne 
of 
carbon 
sequestration 
is: 


􀬶9 


𝐶ç 
− 
𝐵􀯧(0.281𝑃􀯘􀯟􀯘Ö 
− 
0.37𝑃􀯚􀯔􀯦) 


=􀷍

𝐶􀯦􀯘ä 


𝐵􀯧

􀯧􀭀4 
where 
𝐵􀯧(0.281𝑃􀯘􀯟􀯘Ö 
− 
0.37𝑃􀯚􀯔􀯦) 
is 
the 
electricity 
and 
gas 
cost 
offset. 


The 
scenarios 
we 
test 
are: 


 
Baseline 
scenario. 
All 
parameters 
are 
set 
at 
their 
baseline 
values 
from 
section 
5. 
 
Scenario 
1: 
technology 
at 
scale. 
This 
scenario 
involves 
a 
39% 
reduction 
in 
establishment 
costs 
(𝐶􀬴) 
and 
operational 
costs 
(maintenance 
costs 
𝑀􀯧, 
labour 
costs 
𝐿􀯧, 
and 
electricity 
input 
costs 
0.533𝐵􀯧𝑃􀯘􀯟􀯘􀯖). 
 
Scenario 
2: 
large-scale 
modular 
plants. 
This 
scenario 
involves 
a 
48% 
reduction 
in 
establishment 
costs 
(𝐶􀬴) 
and 
a 
48% 
reduction 
in 
the 
cost 
of 
transporting 
the 
feedstock 
to 
the 
plant 
(which 
is 
6.2 
+ 
0.16𝐷 
per 
tonne). 
 
Scenario 
3: 
biochar 
conversion. 
This 
scenario 
involves 
a 
55% 
decrease 
in 
operational 
costs 
(maintenance 
costs 
𝑀􀯧, 
labour 
costs 
𝐿􀯧, 
and 
electricity 
input 
costs 
0.533𝐵􀯧𝑃􀯘􀯟􀯘􀯖). 
Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
155 



E.7 
Sensitivity 
analysis 
􀬶9 


We 
compute 
𝐶􀯦􀯘ä 
= 
∑ 
𝐶􀯧/𝐵ç 
and 
the 
plant’s 
NPV 
by 
varying 
the 
following 
variables: 
±5% 
and 


􀯧􀭀4 


±10% 
from 
their 
baseline 
values: 


 
establishment 
costs 
𝐶4 
 
operational 
costs: 
maintenance 
costs 
𝑀ç 
and 
labour 
costs 
𝐿ç 
 
the 
electricity 
input 
cost 
0.533𝐵􀯧𝑃􀯘􀯟􀯘Ö 
 
the 
natural 
gas 
price: 
increases 
in 
this 
price 
increase 
the 
value 
of 
the 
plant’s 
cost 
offset 
from 
the 
production 
of 
natural 
gas 
 
the 
cost 
of 
transporting 
feedstock 
to 
the 
plant, 
which 
in 
the 
baseline 
scenario 
is 
6.2 
+ 
0.16𝐷 
per 
tonne, 
where 
𝐷 
= 
100km 
is 
the 
assumed 
haulage 
distance 
 
feedstock 
costs 
𝑝􀯪􀯢􀯢× 
􀬵

 
yield 
(tonnes 
of 
biochar 
per 
tonne 
of 
feedstock). 
In 
the 
baseline 
scenario 
the 
yield 
is 
􀬷.􀬻7 
tonnes 
of 
biochar 
per 
tonne 
of 
wood 
chips. 
Note 
that 
increases 
in 
yield 
reduce 
the 
amount 
of 
feedstock 
required 
and 
therefore 
also 
reduce 
the 
cost 
of 
transporting 
the 
feedstock 
to 
the 
plant 


 
the 
carbon 
price 
𝑃􀯖􀯔􀯥Õ 
. 
E.8 
References 
Homagain 
K, 
Shahi 
C, 
Luckai 
N, 
Sharma 
M 
(2016) 
Life 
cycle 
cost 
and 
economic 
assessment 
of 
biochar-based 
bioenergy 
production 
and 
biochar 
land 
application 
in 
Northwestern 
Ontario, 
Canada. 
Forest 
Ecosystems, 
3:21. 


Rajabi 
Hamedani 
S, 
Kuppens 
T, 
Malina 
R, 
Bocci 
E, 
Colantoni 
A, 
Villarini 
M 
(2019) 
Life 
cycle 
assessment 
and 
environmental 
valuation 
of 
biochar 
production: 
two 
case 
studies 
in 
Belgium, 
Energies, 
12(11):2166. 


Roxburgh 
S, 
England 
J, 
Evans 
D, 
Nolan 
M, 
Opie 
K, 
Paul 
K, 
Reeson 
A, 
Cook 
G, 
Thomas 
D 
(2020) 
Potential 
future 
supply 
of 
carbon 
offsets 
in 
the 
land 
sector 
in 
Australia, 
CSIRO, 
Canberra. 


Young 
P, 
Lawrence 
J, 
Batista 
R, 
Jensen-Fellows 
A, 
Richard 
B, 
Sheridan 
T 
(2019) 
Biochar 
market 
profile 
report. 


156 
| 
CSIRO 
Australia’s 
National 
Science 
Agency 



Shortened 
forms 


ACCU 
Australian 
Carbon 
Credit 
Unit 
AI/ML 
Artificial 
Intelligence 
and 
Machine 
Learning 
AUV 
Autonomous 
Underwater 
Vehicle 
Cal/Val 
Calibration 
and 
Validation 
CCUS 
Carbon 
Capture 
Utilisation 
(Use) 
and 
Storage 
CDR 
– 
Carbon 
Dioxide 
Removal 
CER 
– 
Clean 
Energy 
Regulator 
CRL 
Commercial 
Readiness 
Level 
DAC 
Direct 
Air 
Capture 
DEM 
Digital 
Elevation 
Model 
eDNA 
Environmental 
DNA 
ESG 
Environmental, 
Social 
and 
Governance 
EO 
Earth 
Observation 
FPIC 
Free 
and 
Prior 
Informed 
Consent 
FullCAM 
– 
Full 
Carbon 
Accounting 
model 
GEDI 
Global 
Ecosystem 
Dynamic 
Investigation 
GHG 
Greenhouse 
Ga 
ID 
Identification 
LE 
Low 
Emission 
LEO 
Low 
Earth 
Orbit 
LUTO 
Land 
Use 
Trade-Off 
model 
MSS 
Management 
Support 
Systems 
Mta 
Million 
tonnes 
annually 
NPV 
Net 
Present 
Value 
NRM 
Natural 
Resource 
Management 
PBS 
Pyroloysis 
Biochar 
Systems 
PV 
Photo 
Voltaic 
– 
Solar 
Panels 
PyCSS 
Pyrolytic 
Carbon 
capture 
and 
Storage 
SAR 
Synthetic 
Aperture 
Radar 


Sequestration 
Cost 
Reduction 
Workshops 
Report 
| 
157 



As 
Australia’s 
national 
science 
agency 
and 
innovation 
catalyst, 
CSIRO 
is 
solving 
the 
greatest 
challenges 
through 
innovative 
science 
and 
technology. 


CSIRO. 
Unlocking 
a 
better 
future 
for 
everyone. 



Contact 
us 


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peter.fitch@csiro.au 


Michael 
Battaglia 
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michael.battaglia@csiro.au 


Andrew 
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’