• Click to edit Master text styles— Second level• Third level• Fourth level• Fifth level
David Sandalow, Colin McCormick, Alp Kucukelbir, Julio Friedmann,Trishna Nagrani, Zhiyuan Fan, Antoine Halff, Alexandre d'Aspremont,Ruben Glatt, Elena Méndez Leal, Kevin Karl, Alex Ruane

1INNOVATION ROADMAPPROJECT
Artificial
Intelligence
for Climate
ChangeMitigation• Clickto edit
Mastertextstyles(draft for comment released today)— Second level▪

Low-Carbon Ammonia (2022)▪
▪

Blue Carbon (2022)• Fourth level
Carbon Mineralization (2021)• Fifth level
Biomass Carbon Removal & Storage (BiCRS) (2020)▪

Industrial Heat Decarbonization (2019)▪

Direct Air Capture (2018)▪

Carbon Dioxide Utilization 2.0 (2017)▪

Energy Storage Roadmap (2017)▪

Carbon Dioxide Utilization (2016)▪

Zero Energy Buildings (2016)▪

Solar And Storage (2015)▪

• Third level2

ICEF AI FOR CLIMATE CHANGE MITIGATION ROADMAP• Click to edit Master text styles— Second level

Topic:•• Third level
HOW• CAN
AIlevelHELP REDUCE EMISSIONS OF GREENHOUSE GASES?
Fourth• Fifth level(Not:••

How can AI help adapt to climate change?
On balance, will AI help or hinder the fight against climate change?)

3ICEF AI FOR CLIMATE CHANGE MITIGATION ROADMAPPART I: BACKGROUND• Clickto edit Master text styles—Chapter 1. INTRODUCTION TO ARTIFICIAL INTELLIGENCESecondlevel TO CLIMATE CHANGE——Chapter
2. INTRODUCTION

Third level
PART II:•HIGH-POTENTIALOPPORTUNITIES• Fourth— Chapter
3. GHG level
EMISSIONS MONITORINGlevel— Chapter•4.Fifth
POWER
GRID

— Chapter 5. MANUFACTURING— Chapter 6. MATERIALS INNOVATION— Chapter 7. FOOD SYSTEMS— Chapter 8. ROAD TRANSPORTPART III: CROSS-CUTTING TOPICS— Chapter 9. BARRIERS— Chapter 10. RISKS— Chapter 11. POLICY— Chapter 12. FINDINGS AND RECOMMENDATIONS

4• Click to edit Master text styles— Second level• Third level• Fourth level• Fifth level

Part I: BACKGROUND

5

Chapter 1: INTRODUCTION TO AI▪

Artificial Intelligence (AI) is the science of making•computers
Click toedit Master text styles
perform complex tasks— Second level▪

• Thirdlevel learning (ML) to detect
AI relies
on machine
Fourthlevelpatterns• fromlargedatasets• Fifth level▪

AI differs from traditional software— Instead of relying on explicit programming,
AI replies on historical data and simulation
to “train” models and “learn” patterns

6Chapter 1: INTRODUCTION TO AI
AI/ML rely on three things:▪

•Data
Click to edit Master text styles▪

——Observations
that pertain to a problem at hand
Second level— Example: historical weather patterns• Third level— Data availability and accessibility are essential• Fourth level
Model • Fifth level— Describes the objective of the AI system— Describes patterns that lie in data
— Enables the detection of patterns from data toachieve its objective▪

Computation— Set of mathematical and statistical algorithms andcomputer hardware— “Trains” the model on the data7

Chapter 2: INTRODUCTION TO CLIMATE CHANGE• Atmospheric concentrations of heat-trapping gases arenow
higher tothanedit
any time
in humantext
history.
• Click
Masterstyles— Second level• In terms of global average temperatures:• Third level▪ July 6,
the warmest day ever recorded• 2023
Fourthwaslevel▪ July 2023
waslevelthe warmest month ever recorded• Fifth▪ The warmest 9 years ever recorded were the last 9 years• This summer’s heat waves, drought, fires and floods are all consistent
with scientists’ predictions of the impacts of climate change.
• Policies currently in place are not sufficient to reach the goals set
in the Paris Agreement result – and those policies are not being
fully implemented. The world is not on a path to meet its
climate-related goals.
8Chapter 2: AI CONTRIBUTIONS TO CLIMATE SCIENCE
AI is making important contributions to• Click toclimate
edit Master
understanding
change: text styles— Second level▪ improvingclimate• Thirdlevel model performance• Fourth level▪ identifying
newlevelclimate processes and feedback• Fifth▪ attributing extreme events to human influence,and▪ revealing additional climate drivers.

9• Click to edit Master text styles— Second level• Third level

Part II:
HIGH-POTENTIAL OPPORTUNITIES• Fourth level• Fifth level

10Chapter 3: GHG EMISSIONS MONITORING
AI is helping to significantly improve information onsourcesof greenhouse(GHG) emissions.
• Clickto editgasMastertext styles▪

Analyzing vast amounts of data from earth— Second level
observation satellites, airplanes, drones,• Thirdlevel the Internet of things, social
land-basedmonitors,• Fourthmedia andother leveltechnologies• Fifth levelimportant in improving methane
AI has been particularly
emissions monitoring.
▪

Processing data from methane sensors at scale▪

Combining input from multiple satellites▪

Integrating satellite information with data generated
by other types of sensors

Japanese IBUKI-2 GHG monitoring satellite

AI is also being used to better understand sources of CO2emissions.
▪ AI algorithms can be trained to survey the world’s
vegetation at high spatial resolution.

11

Chapter 3: GHG EMISSIONS MONITORINGBarriers
to usingfor emissions
monitoringinclude• ClicktoAIedit
Mastertext styles• lack—of AIliteracy, levelSecond• conflictingdata,level• Third• sovereignty
concerns,• Fourthleveland• Fifth level• uncertain financialmodels.
Measures to help address these barriers include• promoting AI literacy,• establishing mechanisms to validate AI-enabled GHG

emissions data,• setting up one or more global “owners” ofAI-enabled GHG emissions data, and• elevating AI for climate in international dialogue, andnegotiations.

12

Chapter 4: POWER GRID
• AI is becoming an essential part of power grid infrastructure.

• Clickto edit Mastertextgridstyles• AI canmake decarbonizationof the power
cheaper,
faster and smoother, helping with:— Second level▪ predictions,Third level▪ scenario• generation,• Fourth▪ optimization,and level▪ system planningandlevel
integration.
• Fifth• AI can help in all parts of the power grid, including:▪ generation,▪ transmission and distribution▪ end use, and▪ energy storage.

• Barriers include:▪ lack of well-developed models, and▪ lack of trained personnel.

• Using AI in real-time operations creates security and safetyrisks.
13

Chapter 5: MANUFACTURING▪

Manufacturing responsible for ⅓ ofglobalemissions• Click
to edit Master text styles— Second level▪

Decarbonizing manufacturing is hard because of• Third level
physical (e.g., heat) and chemical (e.g., reactions• Fourththat produce
CO2level) constraints• Fifth level▪

Decarbonizing manufacturing requires long-term
investment like:— hardware changes / carbon capture— process changes (e.g., recycled feedstock)— switch to electrification▪

But, AI can provide a complementary benefit
today on existing hardware
14

Chapter 5: MANUFACTURING
AI can help in many ways:▪
▪
▪

• Click to edit
Mastertext
stylesDecarbonizing
the processof makingthings——
Enabling
recycling/circularfeedstock
Secondlevel
Decarbonizing
supply chains• Third level— Optimizing
manufacturingschedules• Fourthlevel• Fifthlevel
Implementing
dematerialization
strategies— Designing stronger/lighter materials▪

Decarbonizing maintenance of equipment— Forecasting process conditions

Important barriers and risks include:▪

Lack of manufacturer incentive to decarbonize▪

Additional safety risk of adopting AI-based workflows
15

Chapter 6: MATERIALS INNOVATION▪

High-performance materials are essential
decarbonization•forClickto edit Master text styles— Second level▪

Historically, new materials were discovered by• Third level
accident or exhaustive, expensive experiments• Fourth(e.g. Edison’slightlevelbulb)• Fifth level▪

In recent decades, it has become possible tocomputationally predict whether new materials will
have useful properties - but it is slow▪

AI can dramatically accelerate this capability

The incredible durability of Roman concrete is why the Pantheonhas stood for almost two millennia.

16Chapter 6: MATERIALS INNOVATION▪

AI can be used to▪• Click
screen tomillions
possible materials
importanteditof Mastertext forstylesproperties,▪
▪

▪

— Second leveldramatically accelerate materials experiments,• Third level
synthesize published research, and• Fourth level
generate new materials concepts• Fifth level

To accelerate the use of AI for materials innovation,
we need▪ better harmonization of materials databases,▪ semi-automated high-throughput materials
testing facilities, and▪ more focus on embedded (manufacturing)emissions and life-cycle assessment.
17Chapter 7: FOOD SYSTEMS▪

Food systems account for over 30% ofglobalMastergreenhousetext
gas emissions.
•human-caused
Click to edit
styles— Second level▪

Climate change impacts including droughts,• Third level
floods, heat waves and the spread of pests threaten• Fourth level
food systems.
• Fifth level▪

AI can contribute to more sustainable food systems inmany ways, including:— integrating data from soil sensors and satellites tocreate fertilizer management plans that minimize
NOx emissions while maximizing crop yields, and— creating virtual farms that simulate different
crops, weather conditions and soil properties tohelp optimize agriculture practices.
18

Chapter 8: ROAD TRANSPORT▪

▪

18% of global energy-related CO2 emissions.

• Click to edit Master text styles
AI—
hasSecondsignificantlevel
potential to help reduce CO2 emissions byacceleratingin:• Thirdinnovationlevel————batteries• Fourth levelsustainablebiofuels• Fifth level
intelligent transportation systems, andshifts towards modes of transportation that emit
less carbon.

▪

Barriers include a lack of data, the lack of uniform standards
for data and a shortage of personnel with AI training.

▪

Risks include bias, invasions of privacy and increases ingreenhouse gas emissions caused by the deployment ofautonomous vehicles.

19• Click to edit Master text styles— Second level• Third level• Fourth level• Fifth level

Part III: CROSS-CUTTING ISSUES

20

Chapter 9: BARRIERS• Click to edit Master text styles
Five groupsof barriers
impede the use of AI for climate— Secondlevelchange mitigation:• Third level• Fourth level• data • Fifth level• people• computation• cost• institutions

21

Chapter 10: RISKS• Click to edit Master text styles

Risks from AI can include:— Second level▪ bias,• Thirdlevel▪ invasionsof privacy,• Fourth▪ security
threats,level• Fifthandlevel▪ safety issues,▪ increased greenhouse emissions.

These risks exist when using AI for climatechange mitigation.

22

Chapter 10D: GREENHOUSE GAS EMISSIONS FROMCOMPUTING OPERATIONS FOR AI▪ Currently modest—less than 1% of the global totalandlikely muchless than
1% of theglobalstyles
total.
• Clickto edit
Mastertext— Second level▪ Future•GHGemissions
Thirdlevel are very uncertain—couldbe even more modest or could be substantial.
• Fourth level
Depends on:• Fifth level— processes used to manufacture AI equipment— energy efficiency of AI equipment— optimization techniques in AI models— use of zero carbon electricity in AI operations,and— demand for AI applications.
▪ Much better data collection and assessment
methodologies are needed
23Chapter 11: POLICY
Government
withMaster
respect to AI
are styles• Click policies
to edittext
evolving rapidly, addressing topics including— Secondlevelbias, privacy,
security,safety and job• Third level
displacement.
• Fourth level• FifthVery few policies
thatlevel
specifically address theuse of AI for climate.

We explore two broad categories:▪ policies that promote the use of AI forclimate change mitigation, and▪ policies that manage risks related to the useof AI for climate change mitigation
24Chapter 11: POLICY
Governments
couldpromote
the usetextof AI forclimate• Click toedit
Masterstyles
change mitigation with that include:— Second level▪ launching AI skills development programs• Third level▪ funding the collection of climate-related data
• Fourth level▪ encouraging
or requiring
the standardization of• Fifthlevelclimate-related data
▪ creating AI offices within government ministries
and▪ using international institutions such as the Clean
Energy Ministerial and World MeteorologicalOrganization as platforms for international
cooperation on AI for climate change mitigation

25

Chapter 11: POLICY
Governments
could
help Mastermanage riskstext
relatedto• Click toedit
stylesthe use of AI for climate change mitigation with—thatSecondpolicies
include:level• Thirdlevel diverse and representative▪ standards
requiring
Fourthlevel
data sets• forAI models.
• Fifth level▪ legal frameworks
that hold entities
accountable for biased outcomes from
AI applications,▪ independent oversight boards responsible
for monitoring privacy protections,▪ R&D on energy-efficient AI algorithms andhardware, and▪ tax incentives and other policies promoting
low-carbon data centers.

26

Chapter 12: FINDINGS AND RECOMMENDATIONSFINDINGS• Click to edit Master text styles— Secondlevel
1. Artificial
intelligenceis currently contributing to climate change
mitigation
andlevel
has the potential to make significant additional• Thirdcontributionsin theyears ahead.
• Fourthlevel
2. Artificial intelligence• Fifth levelis not a panacea when it comes toclimate change.
3. The lack of trained personnel and lack of high-quality data are
critical barriers to the use of AI for climate mitigation.
4. Significant resources will be required for artificial intelligence
to reach its potential in helping mitigate climate change.

27

Chapter 12: FINDINGS AND RECOMMENDATIONSFINDINGS• Click to edit Master text styles

5. Risks
using AI include—ofSecondlevel bias, invasions of privacy and security
issues.•These
Thirdrisks
levelexist when using AI for climate mitigation.
6. Greenhousegas emissions
from computing infrastructure for AI are• Fourthlevel
currently modest– significantly less than 1% of the global total.
• Fifth level
7. The amount of future greenhouse gas emissions from AI computing
infrastructure is highly uncertain.

28

Chapter 12: FINDINGS AND RECOMMENDATIONSRECOMMENDATIONS• Click to edit Master text styles

1. AI tools
should belevel
integrated into many aspects of climate change— Secondmitigation.
• Third level
2. AI skills-development• Fourth levelshould be a priority in all institutions with arole in climate
mitigation.
• Fifthlevel— Educational institutions at all levels should offer courses
relevant to AI.
— Government agencies, businesses and civil society should
regularly review the capabilities of their staffs with respect to AI.
3. Governments should assist in the development and standardizationof data for AI applications that mitigate climate change.
4. All government agencies with responsibility for climate change
should create an AI Office.
29

Chapter 12: FINDINGS AND RECOMMENDATIONSRECOMMENDATIONS• Click to edit Master text styles— Secondlevel be incentivized to deploy artificial
5. Electricutilities should
intelligence,regulated returns for investments in AI and• Thirdwith
levelother tools.
• Fourth level
6. Governments
should• Fifthlevellaunch international platforms to support
cooperative work on AI for climate change mitigation.
7. Governments should work to minimize greenhouse gas emissions
from AI’s computing infrastructure.
8. Avoiding unfair bias should be a core, high-priority principle
guiding the development of all AI tools for climatechange mitigation.

30

• Click to edit Master text styles— Second level• Third level• Fourth level• Fifth level

David Sandalow, Colin McCormick,
Alp Kucukelbir, Julio Friedmann,
Trishna Nagrani, Zhiyuan Fan,
Antoine Halff, Elena Méndez Leal,Ruben Glatt, Alexandre d'Aspremont31• Click to edit Master text styles— SecondThis levelroadmap was prepared to facilitate dialogue at the Tenth Innovation for Cool Earth• Third Forumlevel (October 2023), for final release at COP28 in December 2023. We are deeplygrateful• Fourthlevel to the Ministry of Economy, Trade and Industry (METI) and New Energy andIndustrial Technology Development Organization (NEDO), Japan, for launching and• Fifth levelsupporting the ICEF Innovation Roadmap Project of which this is a part.
Ruben Glatt contributed to the technical evaluations in this document.
The policy recommendations were prepared by other contributors.

32INNOVATION ROADMAPPROJECT• Click
to edit Chair,
MastertextICEF
styles
HOESUNG
LEE—former
IPCC: “Theroadmaps provide importantresearcha wide range— onSecondlevelof technologies for helping achieve net zeroemissions. They are an important resource for anyone working on• Third level
these issues.”• Fourth level• Fifth level
VACLAV SMIL—energy
historian: The ICEF roadmaps "provide essential
information on different aspects of our energy systems and how they mightchange over time. I recommend them for anyone interested in thischallenging topic.”
ALISSA PARK—Dean, UCLA School of Engineering: "The ICEF roadmaps...arean excellent resource for researchers and practitioners who cross disciplinary
boundaries to develop transformative solutions for climate change.”

www.icef.go.jp/roadmap
33