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Evaluation and Projection of Surface PM(2.5) and Its Exposure on Population in Asia Based on the CMIP6 GCMs

This paper evaluates the historical simulated surface concentrations of particulate matter small than 2.5 µm in diameter (PM(2.5)) and its components (black carbon (BC), dust, SO(4), and organic aerosol (OA)) in Asia, which come from Coupled Model Intercomparison Project Phase 6 (CMIP6). In addition...

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Autores principales: Xu, Ying, Wu, Jie, Han, Zhenyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9566559/
https://www.ncbi.nlm.nih.gov/pubmed/36231393
http://dx.doi.org/10.3390/ijerph191912092
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author Xu, Ying
Wu, Jie
Han, Zhenyu
author_facet Xu, Ying
Wu, Jie
Han, Zhenyu
author_sort Xu, Ying
collection PubMed
description This paper evaluates the historical simulated surface concentrations of particulate matter small than 2.5 µm in diameter (PM(2.5)) and its components (black carbon (BC), dust, SO(4), and organic aerosol (OA)) in Asia, which come from Coupled Model Intercomparison Project Phase 6 (CMIP6). In addition, future projected changes of surface PM(2.5) and its components, as well as their exposure to population, under the different Shared Socioeconomic Pathway (SSP) scenarios are also provided. Results show that the simulated spatial distribution of surface PM(2.5) concentrations is consistent with the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) and Socioeconomic Data and Applications Center (SEDAC). The model spreads are small/large over the regions with low/high climatic mean surface PM(2.5) concentrations, i.e., Northern Asia/Saudi Arabia, Iran, and Xinjiang Province of China. The multi-model ensemble of CMIP6 reproduces the main features of annual cycles and seasonal variations in Asia and its sub-regions. Under the scenarios of SSP1-2.6, SSP2-4.5, and SSP5-8.5, compared to the present-day period of 1995–2014, annual mean surface PM(2.5) concentrations are projected to decrease in Asia, with obvious differences among the scenarios. Meanwhile, the magnitudes and timings of changes at the regional scale are quite different, with the largest decreases in South Asia (SAS). Under SSP3-7.0, the increase of surface PM(2.5) concentrations in SAS is the largest, with the increase value of 8 μg/m(3) in 2050; while under SSP370-lowNTCF, which assumes stronger levels of air quality control measures relative to the SSP3-7.0, the decreases of surface PM(2.5) concentrations in SAS, East Asia (EAS) and Southeast Asia (SEAS) are the largest. The characteristics of seasonal trends are consistent with that of the annual trend. The trends in the concentrations of surface PM(2.5) and its components are similar. The population-weighted average values of surface PM(2.5) concentrations are projected to decrease in Central Asia (CAS), EAS, North Asia (NAS), and SEAS, and it indicates that the surface PM(2.5) concentrations over the most populated area of Asia will decrease. In SAS, because of its large population, the impact of air pollutants on human health is still disastrous in the future. In summary, the surface PM(2.5) concentrations over the most area of Asia will decrease, which is beneficial to air quality and human health; under SSP370-lowNTCF, the reduction of short-lived climate forcers (SLCFs) will further improve air quality.
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spelling pubmed-95665592022-10-15 Evaluation and Projection of Surface PM(2.5) and Its Exposure on Population in Asia Based on the CMIP6 GCMs Xu, Ying Wu, Jie Han, Zhenyu Int J Environ Res Public Health Article This paper evaluates the historical simulated surface concentrations of particulate matter small than 2.5 µm in diameter (PM(2.5)) and its components (black carbon (BC), dust, SO(4), and organic aerosol (OA)) in Asia, which come from Coupled Model Intercomparison Project Phase 6 (CMIP6). In addition, future projected changes of surface PM(2.5) and its components, as well as their exposure to population, under the different Shared Socioeconomic Pathway (SSP) scenarios are also provided. Results show that the simulated spatial distribution of surface PM(2.5) concentrations is consistent with the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) and Socioeconomic Data and Applications Center (SEDAC). The model spreads are small/large over the regions with low/high climatic mean surface PM(2.5) concentrations, i.e., Northern Asia/Saudi Arabia, Iran, and Xinjiang Province of China. The multi-model ensemble of CMIP6 reproduces the main features of annual cycles and seasonal variations in Asia and its sub-regions. Under the scenarios of SSP1-2.6, SSP2-4.5, and SSP5-8.5, compared to the present-day period of 1995–2014, annual mean surface PM(2.5) concentrations are projected to decrease in Asia, with obvious differences among the scenarios. Meanwhile, the magnitudes and timings of changes at the regional scale are quite different, with the largest decreases in South Asia (SAS). Under SSP3-7.0, the increase of surface PM(2.5) concentrations in SAS is the largest, with the increase value of 8 μg/m(3) in 2050; while under SSP370-lowNTCF, which assumes stronger levels of air quality control measures relative to the SSP3-7.0, the decreases of surface PM(2.5) concentrations in SAS, East Asia (EAS) and Southeast Asia (SEAS) are the largest. The characteristics of seasonal trends are consistent with that of the annual trend. The trends in the concentrations of surface PM(2.5) and its components are similar. The population-weighted average values of surface PM(2.5) concentrations are projected to decrease in Central Asia (CAS), EAS, North Asia (NAS), and SEAS, and it indicates that the surface PM(2.5) concentrations over the most populated area of Asia will decrease. In SAS, because of its large population, the impact of air pollutants on human health is still disastrous in the future. In summary, the surface PM(2.5) concentrations over the most area of Asia will decrease, which is beneficial to air quality and human health; under SSP370-lowNTCF, the reduction of short-lived climate forcers (SLCFs) will further improve air quality. MDPI 2022-09-24 /pmc/articles/PMC9566559/ /pubmed/36231393 http://dx.doi.org/10.3390/ijerph191912092 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Xu, Ying
Wu, Jie
Han, Zhenyu
Evaluation and Projection of Surface PM(2.5) and Its Exposure on Population in Asia Based on the CMIP6 GCMs
title Evaluation and Projection of Surface PM(2.5) and Its Exposure on Population in Asia Based on the CMIP6 GCMs
title_full Evaluation and Projection of Surface PM(2.5) and Its Exposure on Population in Asia Based on the CMIP6 GCMs
title_fullStr Evaluation and Projection of Surface PM(2.5) and Its Exposure on Population in Asia Based on the CMIP6 GCMs
title_full_unstemmed Evaluation and Projection of Surface PM(2.5) and Its Exposure on Population in Asia Based on the CMIP6 GCMs
title_short Evaluation and Projection of Surface PM(2.5) and Its Exposure on Population in Asia Based on the CMIP6 GCMs
title_sort evaluation and projection of surface pm(2.5) and its exposure on population in asia based on the cmip6 gcms
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9566559/
https://www.ncbi.nlm.nih.gov/pubmed/36231393
http://dx.doi.org/10.3390/ijerph191912092
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