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''This page is about the intersection of negative emissions technologies and machine learning in the context of climate change mitigation. For an overview of carbon dioxide removal as a whole, please see the [https://en.wikipedia.org/wiki/Carbon_dioxide_removal Wikipedia page] on this topic.''
 
Negative Emission Technologies (NETs), often referred to as Carbon Dioxide Removal (CDR), aim to artificially remove carbon dioxide (CO<sub>2</sub>) from the atmospere<ref>{{Cite journal|last=Minx|first=Jan C|last2=Lamb|first2=William F|last3=Callaghan|first3=Max W|last4=Fuss|first4=Sabine|last5=Hilaire|first5=Jérôme|last6=Creutzig|first6=Felix|last7=Amann|first7=Thorben|last8=Beringer|first8=Tim|last9=de Oliveira Garcia|first9=Wagner|last10=Hartmann|first10=Jens|last11=Khanna|first11=Tarun|date=2018-05-21|title=Negative emissions—Part 1: Research landscape and synthesis|url=https://iopscience.iop.org/article/10.1088/1748-9326/aabf9b|journal=Environmental Research Letters|language=en|volume=13|issue=6|pages=063001|doi=10.1088/1748-9326/aabf9b|issn=1748-9326}}</ref>, in addition to the natural removal of the atmospheric CO<sub>2</sub> by the natural carbon sinks (such as land and ocean)<ref>IPCC, 2018: Annex I: Glossary [Matthews, J.B.R. (ed.)]. In: Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty [Masson-Delmotte, V., P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T. Waterfield (eds.)]. In Press</ref>. NETs are not a substitution for climate mitigation and reducing global emission ratedrate, but can be used together with mitigation efforts to speed up the reduction of emissions and reaching the net-zero emission targets sooner, depending on the [[Emission scenarios|emission scenario]]. The mitigation pathways consistent with reaching the 1.5C5 °C target (reported by the IPCC Special Report on 1.5 Degrees<ref name=":3">Rogelj, J., D. Shindell, K. Jiang, S. Fifita, P. Forster, V. Ginzburg, C. Handa, H. Kheshgi, S. Kobayashi, E. Kriegler, L. Mundaca, R. Séférian, and M.V. Vilariño, 2018: Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development. In: Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty [Masson-Delmotte, V., P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T. Waterfield (eds.)].</ref>) entail low to moderate levels of CDR (up to 1000 PgC removed; IPCC SR1.5 Chapter 2<ref>Rogelj, J., D. Shindell, K. Jiang, S. Fifita, P. Forster, V. Ginzburg, C. Handa, H. Kheshgi, S. Kobayashi, E. Kriegler, L. Mundaca, R. Séférian, and M.V. Vilariño, 2018: Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development. In: Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty [Masson-Delmotte, V., P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T. Waterfield (eds.)].</ref>). NETs are also an underlying assumption of overshoot scenarios -where a given temperature target is temporarily exceeded and then returned to with the aid of negative emission. While global mean temperature has shown to be largely reversible in response to NETsartifical carbon dioxide removal, other components of climate change (such as sea-level rise, ocean acidification, and other terrestrial and marine ecosystem changes) are not easily reversible on human time-scales, even if extremely large amounts of NETs were implemented<ref>{{Cite journal|last=Jones|first=C D|last2=Ciais|first2=P|last3=Davis|first3=S J|last4=Friedlingstein|first4=P|last5=Gasser|first5=T|last6=Peters|first6=G P|last7=Rogelj|first7=J|last8=van Vuuren|first8=D P|last9=Canadell|first9=J G|last10=Cowie|first10=A|last11=Jackson|first11=R B|date=2016-09-01|title=Simulating the Earth system response to negative emissions|url=https://doi.org/10.1088/1748-9326/11/9/095012|journal=Environmental Research Letters|language=en|volume=11|issue=9|pages=095012|doi=10.1088/1748-9326/11/9/095012|issn=1748-9326}}</ref><ref>{{Cite journal|last=Tokarska|first=Katarzyna B|last2=Zickfeld|first2=Kirsten|date=2015-09-01|title=The effectiveness of net negative carbon dioxide emissions in reversing anthropogenic climate change|url=https://doi.org/10.1088/1748-9326/10/9/094013|journal=Environmental Research Letters|language=en|volume=10|issue=9|pages=094013|doi=10.1088/1748-9326/10/9/094013|issn=1748-9326}}</ref><ref>{{Cite journal|last=Hofmann|first=M.|last2=Mathesius|first2=S.|last3=Kriegler|first3=E.|last4=Vuuren|first4=D. P. van|last5=Schellnhuber|first5=H. J.|date=2019-12-06|title=Strong time dependence of ocean acidification mitigation by atmospheric carbon dioxide removal|url=https://www.nature.com/articles/s41467-019-13586-4|journal=Nature Communications|language=en|volume=10|issue=1|pages=5592|doi=10.1038/s41467-019-13586-4|issn=2041-1723}}</ref>.
[[File:NETs hr.jpg|alt=|thumb|Different groups of negative emission technologies<ref>{{Cite journal|last=Minx|first=Jan C|last2=Lamb|first2=William F|last3=Callaghan|first3=Max W|last4=Bornmann|first4=Lutz|last5=Fuss|first5=Sabine|date=2017-03-01|title=Fast growing research on negative emissions|url=https://iopscience.iop.org/article/10.1088/1748-9326/aa5ee5|journal=Environmental Research Letters|language=en|volume=12|issue=3|pages=035007|doi=10.1088/1748-9326/aa5ee5|issn=1748-9326}}</ref> (Source: Figure 1 from Jan C Minx ''et al'' 2017 ''Environ. Res. Lett.'' '''12''' 035007)]]
Different groups of negative emission technologies<ref>{{Cite journal|last=Minx|first=Jan C|last2=Lamb|first2=William F|last3=Callaghan|first3=Max W|last4=Bornmann|first4=Lutz|last5=Fuss|first5=Sabine|date=2017-03-01|title=Fast growing research on negative emissions|url=https://iopscience.iop.org/article/10.1088/1748-9326/aa5ee5|journal=Environmental Research Letters|volume=12|issue=3|pages=035007|doi=10.1088/1748-9326/aa5ee5|issn=1748-9326}}</ref>:
 
* [[Direct Air Capture]] (DAC) with sequestration of the captured CO<sub>2</sub> in underground geologic formations.
* [[Bioenergy carbon capture and sequestration]] (BECCS)
* [[Biochar and soil carbon sequestration]] (SDS)
* [[Forestry and Other Land Use|afforestationAfforestation]] and reforestation (growing more trees and storing carbon in this biomass)
* [[Agriculture|regenerativeRegenerative farming]] practices
* [[Enhanced weathering]]
* [[Ocean fertilisation]]
AsMany describedDAC intechnologies the paper "Tackling Climate Change with Machine Learning"<ref name=":2">{{Cite journal|last=Rolnick|first=David|last2=Donti|first2=Priya L.|last3=Kaack|first3=Lynn H.|last4=Kochanski|first4=Kelly|last5=Lacoste|first5=Alexandre|last6=Sankaran|first6=Kris|last7=Ross|first7=Andrew Slavin|last8=Milojevic-Dupont|first8=Nikola|last9=Jaques|first9=Natasha|last10=Waldman-Brown|first10=Anna|last11=Luccioni|first11=Alexandra|date=2019-11-05|title=Tackling Climate Change with Machine Learning|url=http://arxiv.org/abs/1906.05433|journal=arXiv:1906.05433 [cs, stat]}}</ref>:<blockquote>Although there has been significant progressare in negativeearly emissionsstages researchof commercialization<ref name=":0">{{Cite book|last=National Academies of Sciences|first=Engineering|url=https://www.nap.edu/catalog/25259/negative-emissions-technologies-and-reliable-sequestration-a-research-agenda|title=Negative Emissions Technologies and Reliable Sequestration: A Research Agenda|date=2018-10-24|isbn=978-0-309-48452-7|language=en}}</ref><ref name=":1">{{Cite web|last=ICEF|first=|date=|title=Direct Air Capture of Carbon Dioxide: ICEF Roadmap 2018|url=https://www.icef-forum.org/|url-status=live|archive-url=|archive-date=|access-date=2020-09-12|website=www.icef-forum.org}}</ref><ref>{{Cite web|title=ShieldSquare Captcha|url=http://stacks.iop.org/1748-9326/13/i=6/a=063001?key=crossref.9b8e1db79e5bb89326008b4b6859ede0|access-date=2020-09-12|website=stacks.iop.org|language=en}}</ref><ref>{{Cite journal|last=Fuss|first=Sabine|last2=Lamb|first2=William F.|last3=Callaghan|first3=Max W.|last4=Hilaire|first4=Jérôme|last5=Creutzig|first5=Felix|last6=Amann|first6=Thorben|last7=Beringer|first7=Tim|last8=Garcia|first8=Wagner de Oliveira|last9=Hartmann|first9=Jens|last10=Khanna|first10=Tarun|last11=Luderer|first11=Gunnar|date=2018-05|title=Negative emissions—Part 2: Costs, potentials and side effects|url=https://doi.org/10.1088%2F1748-9326%2Faabf9f|journal=Environmental Research Letters|language=en|volume=13|issue=6|pages=063002|doi=10.1088/1748-9326/aabf9f|issn=1748-9326}}</ref><ref>{{Cite web|title=ShieldSquare Captcha|url=http://stacks.iop.org/1748-9326/13/i=6/a=063003?key=crossref.a329c88fc7b90b61b136cf0c66c67240|access-date=2020-09-12|website=stacks.iop.org|language=en}}</ref>, the actual CO<sub>2</sub> removal industry is still in its infancy. As such, many of the ML applications we outline in this section are either speculative or in the early stages of development or commercialization<ref name=":2" />.</blockquote>Many DAC technologies are in early stages of commercialization<ref name=":0" /><ref name=":1" />, though there is still large uncertainty regarding geological storage of captured CO<sub>2</sub> on long time-scales, and deployment of negative emission technologies on large-scales and in a sustainable way is unlikely<ref>{{Cite journal|last=Minx|first=Jan C.|last2=Lamb|first2=William F.|last3=Callaghan|first3=Max W.|last4=Fuss|first4=Sabine|last5=Hilaire|first5=Jérôme|last6=Creutzig|first6=Felix|last7=Amann|first7=Thorben|last8=Beringer|first8=Tim|last9=Garcia|first9=Wagner de Oliveira|last10=Hartmann|first10=Jens|last11=Khanna|first11=Tarun|date=2018-05|title=Negative emissions—Part 1: Research landscape and synthesis|url=https://doi.org/10.1088/1748-9326/aabf9b|journal=Environmental Research Letters|language=en|volume=13|issue=6|pages=063001|doi=10.1088/1748-9326/aabf9b|issn=1748-9326}}</ref><ref>{{Cite journal|last=Fuss|first=Sabine|last2=Lamb|first2=William F|last3=Callaghan|first3=Max W|last4=Hilaire|first4=Jérôme|last5=Creutzig|first5=Felix|last6=Amann|first6=Thorben|last7=Beringer|first7=Tim|last8=de Oliveira Garcia|first8=Wagner|last9=Hartmann|first9=Jens|last10=Khanna|first10=Tarun|last11=Luderer|first11=Gunnar|date=2018-05-21|title=Negative emissions—Part 2: Costs, potentials and side effects|url=https://iopscience.iop.org/article/10.1088/1748-9326/aabf9f|journal=Environmental Research Letters|language=en|volume=13|issue=6|pages=063002|doi=10.1088/1748-9326/aabf9f|issn=1748-9326}}</ref><ref>{{Cite journal|last=Nemet|first=Gregory F|last2=Callaghan|first2=Max W|last3=Creutzig|first3=Felix|last4=Fuss|first4=Sabine|last5=Hartmann|first5=Jens|last6=Hilaire|first6=Jérôme|last7=Lamb|first7=William F|last8=Minx|first8=Jan C|last9=Rogers|first9=Sophia|last10=Smith|first10=Pete|date=2018-05-21|title=Negative emissions—Part 3: Innovation and upscaling|url=https://iopscience.iop.org/article/10.1088/1748-9326/aabff4|journal=Environmental Research Letters|language=en|volume=13|issue=6|pages=063003|doi=10.1088/1748-9326/aabff4|issn=1748-9326}}</ref>. The underlying chemical processes are fairly well understood and the design of these systems generally does not require machine learning; however, ML may be useful in designing more effective CO<sub>2</sub> sorbents. ML also may have a number of applications in CO<sub>2</sub> sequestration, namely in identifying, modeling, and monitoring CO<sub>2</sub> sequestration sites.
 
Many of the ML applications we discuss below are either speculative or in the early stages of development or commercialization<ref name=":2">{{Cite journal|last=Rolnick|first=David|last2=Donti|first2=Priya L.|last3=Kaack|first3=Lynn H.|last4=Kochanski|first4=Kelly|last5=Lacoste|first5=Alexandre|last6=Sankaran|first6=Kris|last7=Ross|first7=Andrew Slavin|last8=Milojevic-Dupont|first8=Nikola|last9=Jaques|first9=Natasha|last10=Waldman-Brown|first10=Anna|last11=Luccioni|first11=Alexandra|date=2019-11-05|title=Tackling Climate Change with Machine Learning|url=http://arxiv.org/abs/1906.05433|journal=arXiv:1906.05433 [cs, stat]}}</ref>.
It must be captured: there are many ways of atmospheric carbon removal.| Photo: [https://www.mcc-berlin.net/en/news/information/information-detail/article/future-of-carbon-removal-becomes-tangible.html MCC]
 
'''Different types of NETs:'''
 
Direct Air Capture (DAC) with sequestration of the captured CO<sub>2</sub> in underground geologic formations.
 
Biomass Combustion with Carbon cCapture and Sequestration (BECCS)
 
'''Nature-based solutions:'''
 
[[Forestry and Other Land Use|afforestation]] (growing more trees and storing carbon in this biomass)
 
[[Agriculture|regenerative farming]] practices
 
'''Ocean-based solutions:'''
 
-Ocean alkalanisation
 
As described in the paper "Tackling Climate Change with Machine Learning"<ref name=":2">{{Cite journal|last=Rolnick|first=David|last2=Donti|first2=Priya L.|last3=Kaack|first3=Lynn H.|last4=Kochanski|first4=Kelly|last5=Lacoste|first5=Alexandre|last6=Sankaran|first6=Kris|last7=Ross|first7=Andrew Slavin|last8=Milojevic-Dupont|first8=Nikola|last9=Jaques|first9=Natasha|last10=Waldman-Brown|first10=Anna|last11=Luccioni|first11=Alexandra|date=2019-11-05|title=Tackling Climate Change with Machine Learning|url=http://arxiv.org/abs/1906.05433|journal=arXiv:1906.05433 [cs, stat]}}</ref>:<blockquote>Although there has been significant progress in negative emissions research <ref name=":0">{{Cite book|last=National Academies of Sciences|first=Engineering|url=https://www.nap.edu/catalog/25259/negative-emissions-technologies-and-reliable-sequestration-a-research-agenda|title=Negative Emissions Technologies and Reliable Sequestration: A Research Agenda|date=2018-10-24|isbn=978-0-309-48452-7|language=en}}</ref><ref name=":1">{{Cite web|last=ICEF|first=|date=|title=Direct Air Capture of Carbon Dioxide: ICEF Roadmap 2018|url=https://www.icef-forum.org/|url-status=live|archive-url=|archive-date=|access-date=2020-09-12|website=www.icef-forum.org}}</ref><ref>{{Cite web|title=ShieldSquare Captcha|url=http://stacks.iop.org/1748-9326/13/i=6/a=063001?key=crossref.9b8e1db79e5bb89326008b4b6859ede0|access-date=2020-09-12|website=stacks.iop.org|language=en}}</ref><ref>{{Cite journal|last=Fuss|first=Sabine|last2=Lamb|first2=William F.|last3=Callaghan|first3=Max W.|last4=Hilaire|first4=Jérôme|last5=Creutzig|first5=Felix|last6=Amann|first6=Thorben|last7=Beringer|first7=Tim|last8=Garcia|first8=Wagner de Oliveira|last9=Hartmann|first9=Jens|last10=Khanna|first10=Tarun|last11=Luderer|first11=Gunnar|date=2018-05|title=Negative emissions—Part 2: Costs, potentials and side effects|url=https://doi.org/10.1088%2F1748-9326%2Faabf9f|journal=Environmental Research Letters|language=en|volume=13|issue=6|pages=063002|doi=10.1088/1748-9326/aabf9f|issn=1748-9326}}</ref><ref>{{Cite web|title=ShieldSquare Captcha|url=http://stacks.iop.org/1748-9326/13/i=6/a=063003?key=crossref.a329c88fc7b90b61b136cf0c66c67240|access-date=2020-09-12|website=stacks.iop.org|language=en}}</ref>, the actual CO<sub>2</sub> removal industry is still in its infancy. As such, many of the ML applications we outline in this section are either speculative or in the early stages of development or commercialization<ref name=":2" />.</blockquote>Many DAC technologies are in early stages of commercialization<ref name=":0" /><ref name=":1" />, though there is still large uncertainty regarding geological storage of captured CO<sub>2</sub> on long time-scales, and deployment of negative emission technologies on large-scales and in a sustainable way is unlikely<ref>{{Cite journal|last=Minx|first=Jan C.|last2=Lamb|first2=William F.|last3=Callaghan|first3=Max W.|last4=Fuss|first4=Sabine|last5=Hilaire|first5=Jérôme|last6=Creutzig|first6=Felix|last7=Amann|first7=Thorben|last8=Beringer|first8=Tim|last9=Garcia|first9=Wagner de Oliveira|last10=Hartmann|first10=Jens|last11=Khanna|first11=Tarun|date=2018-05|title=Negative emissions—Part 1: Research landscape and synthesis|url=https://doi.org/10.1088/1748-9326/aabf9b|journal=Environmental Research Letters|language=en|volume=13|issue=6|pages=063001|doi=10.1088/1748-9326/aabf9b|issn=1748-9326}}</ref><ref>{{Cite journal|last=Fuss|first=Sabine|last2=Lamb|first2=William F|last3=Callaghan|first3=Max W|last4=Hilaire|first4=Jérôme|last5=Creutzig|first5=Felix|last6=Amann|first6=Thorben|last7=Beringer|first7=Tim|last8=de Oliveira Garcia|first8=Wagner|last9=Hartmann|first9=Jens|last10=Khanna|first10=Tarun|last11=Luderer|first11=Gunnar|date=2018-05-21|title=Negative emissions—Part 2: Costs, potentials and side effects|url=https://iopscience.iop.org/article/10.1088/1748-9326/aabf9f|journal=Environmental Research Letters|language=en|volume=13|issue=6|pages=063002|doi=10.1088/1748-9326/aabf9f|issn=1748-9326}}</ref><ref>{{Cite journal|last=Nemet|first=Gregory F|last2=Callaghan|first2=Max W|last3=Creutzig|first3=Felix|last4=Fuss|first4=Sabine|last5=Hartmann|first5=Jens|last6=Hilaire|first6=Jérôme|last7=Lamb|first7=William F|last8=Minx|first8=Jan C|last9=Rogers|first9=Sophia|last10=Smith|first10=Pete|date=2018-05-21|title=Negative emissions—Part 3: Innovation and upscaling|url=https://iopscience.iop.org/article/10.1088/1748-9326/aabff4|journal=Environmental Research Letters|language=en|volume=13|issue=6|pages=063003|doi=10.1088/1748-9326/aabff4|issn=1748-9326}}</ref>. The underlying chemical processes are fairly well understood and the design of these systems generally does not require machine learning; however, ML may be useful in designing more effective CO<sub>2</sub> sorbents. ML also may have a number of applications in CO<sub>2</sub> sequestration, namely in identifying, modeling, and monitoring CO<sub>2</sub> sequestration sites.
 
==Machine Learning Application Areas==
==Conferences, Journals, and Professional Organizations==
 
*[http://negativeco2emissions2020.com/ The International Conference on Negative CO2 emissions]
*Carbon 180 [[https://carbon180.org/ link]Carbon 180]
 
==Libraries and Tools==
 
==Data==
[https://data.ene.iiasa.ac.at/iamc-1.5c-explorer/#/login?redirect=%2Fworkspaces '''IPCC SR1.5 Scenario Explorer''']- climate change migation pathways used in the IPCC SR1.5 report<ref name=":3" /> (many of the scenarios contain negative emissions).
{{SectionStub}}
 
==References==
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