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Predictability of fossil fuel CO(2) from air quality emissions
Quantifying the coevolution of greenhouse gases and air quality pollutants can provide insight into underlying anthropogenic processes enabling predictions of their emission trajectories. Here, we classify the dynamics of historic emissions in terms of a modified Environmental Kuznets Curve (MEKC),...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10034258/ https://www.ncbi.nlm.nih.gov/pubmed/36959192 http://dx.doi.org/10.1038/s41467-023-37264-8 |
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author | Miyazaki, Kazuyuki Bowman, Kevin |
author_facet | Miyazaki, Kazuyuki Bowman, Kevin |
author_sort | Miyazaki, Kazuyuki |
collection | PubMed |
description | Quantifying the coevolution of greenhouse gases and air quality pollutants can provide insight into underlying anthropogenic processes enabling predictions of their emission trajectories. Here, we classify the dynamics of historic emissions in terms of a modified Environmental Kuznets Curve (MEKC), which postulates the coevolution of fossil fuel CO(2) (FFCO(2)) and NOx emissions as a function of macroeconomic development. The MEKC broadly captures the historic FFCO(2)-NO(x) dynamical regimes for countries including the US, China, and India as well as IPCC scenarios. Given these dynamics, we find the predictive skill of FFCO2 given NO(x) emissions constrained by satellite data is less than 2% error at one-year lags for many countries and less than 10% for 4-year lags. The proposed framework in conjunction with an increasing satellite constellation provides valuable guidance to near-term emission scenario development and evaluation at time-scales relevant to international assessments such as the Global Stocktake. |
format | Online Article Text |
id | pubmed-10034258 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-100342582023-03-23 Predictability of fossil fuel CO(2) from air quality emissions Miyazaki, Kazuyuki Bowman, Kevin Nat Commun Article Quantifying the coevolution of greenhouse gases and air quality pollutants can provide insight into underlying anthropogenic processes enabling predictions of their emission trajectories. Here, we classify the dynamics of historic emissions in terms of a modified Environmental Kuznets Curve (MEKC), which postulates the coevolution of fossil fuel CO(2) (FFCO(2)) and NOx emissions as a function of macroeconomic development. The MEKC broadly captures the historic FFCO(2)-NO(x) dynamical regimes for countries including the US, China, and India as well as IPCC scenarios. Given these dynamics, we find the predictive skill of FFCO2 given NO(x) emissions constrained by satellite data is less than 2% error at one-year lags for many countries and less than 10% for 4-year lags. The proposed framework in conjunction with an increasing satellite constellation provides valuable guidance to near-term emission scenario development and evaluation at time-scales relevant to international assessments such as the Global Stocktake. Nature Publishing Group UK 2023-03-23 /pmc/articles/PMC10034258/ /pubmed/36959192 http://dx.doi.org/10.1038/s41467-023-37264-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Miyazaki, Kazuyuki Bowman, Kevin Predictability of fossil fuel CO(2) from air quality emissions |
title | Predictability of fossil fuel CO(2) from air quality emissions |
title_full | Predictability of fossil fuel CO(2) from air quality emissions |
title_fullStr | Predictability of fossil fuel CO(2) from air quality emissions |
title_full_unstemmed | Predictability of fossil fuel CO(2) from air quality emissions |
title_short | Predictability of fossil fuel CO(2) from air quality emissions |
title_sort | predictability of fossil fuel co(2) from air quality emissions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10034258/ https://www.ncbi.nlm.nih.gov/pubmed/36959192 http://dx.doi.org/10.1038/s41467-023-37264-8 |
work_keys_str_mv | AT miyazakikazuyuki predictabilityoffossilfuelco2fromairqualityemissions AT bowmankevin predictabilityoffossilfuelco2fromairqualityemissions |