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Tracking Daily Concentrations of PM(2.5) Chemical Composition in China since 2000

[Image: see text] PM(2.5) chemical components play significant roles in the climate, air quality, and public health, and the roles vary due to their different physicochemical properties. Obtaining accurate and timely updated information on China’s PM(2.5) chemical composition is the basis for resear...

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Autores principales: Liu, Shigan, Geng, Guannan, Xiao, Qingyang, Zheng, Yixuan, Liu, Xiaodong, Cheng, Jing, Zhang, Qiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9670839/
https://www.ncbi.nlm.nih.gov/pubmed/36318737
http://dx.doi.org/10.1021/acs.est.2c06510
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author Liu, Shigan
Geng, Guannan
Xiao, Qingyang
Zheng, Yixuan
Liu, Xiaodong
Cheng, Jing
Zhang, Qiang
author_facet Liu, Shigan
Geng, Guannan
Xiao, Qingyang
Zheng, Yixuan
Liu, Xiaodong
Cheng, Jing
Zhang, Qiang
author_sort Liu, Shigan
collection PubMed
description [Image: see text] PM(2.5) chemical components play significant roles in the climate, air quality, and public health, and the roles vary due to their different physicochemical properties. Obtaining accurate and timely updated information on China’s PM(2.5) chemical composition is the basis for research and environmental management. Here, we developed a full-coverage near-real-time PM(2.5) chemical composition data set at 10 km spatial resolution since 2000, combining the Weather Research and Forecasting–Community Multiscale Air Quality modeling system, ground observations, a machine learning algorithm, and multisource-fusion PM(2.5) data. PM(2.5) chemical components in our data set are in good agreement with the available observations (correlation coefficients range from 0.64 to 0.75 at a monthly scale from 2000 to 2020 and from 0.67 to 0.80 at a daily scale from 2013 to 2020; most normalized mean biases within ±20%). Our data set reveals the long-term trends in PM(2.5) chemical composition in China, especially the rapid decreases after 2013 for sulfate, nitrate, ammonium, organic matter, and black carbon, at the rate of −9.0, −7.2, −8.1, −8.4, and −9.2% per year, respectively. The day-to-day variability is also well captured, including evolutions in spatial distribution and shares of PM(2.5) components. As part of Tracking Air Pollution in China (http://tapdata.org.cn), this daily-updated data set provides large opportunities for health and climate research as well as policy-making in China.
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spelling pubmed-96708392022-11-18 Tracking Daily Concentrations of PM(2.5) Chemical Composition in China since 2000 Liu, Shigan Geng, Guannan Xiao, Qingyang Zheng, Yixuan Liu, Xiaodong Cheng, Jing Zhang, Qiang Environ Sci Technol [Image: see text] PM(2.5) chemical components play significant roles in the climate, air quality, and public health, and the roles vary due to their different physicochemical properties. Obtaining accurate and timely updated information on China’s PM(2.5) chemical composition is the basis for research and environmental management. Here, we developed a full-coverage near-real-time PM(2.5) chemical composition data set at 10 km spatial resolution since 2000, combining the Weather Research and Forecasting–Community Multiscale Air Quality modeling system, ground observations, a machine learning algorithm, and multisource-fusion PM(2.5) data. PM(2.5) chemical components in our data set are in good agreement with the available observations (correlation coefficients range from 0.64 to 0.75 at a monthly scale from 2000 to 2020 and from 0.67 to 0.80 at a daily scale from 2013 to 2020; most normalized mean biases within ±20%). Our data set reveals the long-term trends in PM(2.5) chemical composition in China, especially the rapid decreases after 2013 for sulfate, nitrate, ammonium, organic matter, and black carbon, at the rate of −9.0, −7.2, −8.1, −8.4, and −9.2% per year, respectively. The day-to-day variability is also well captured, including evolutions in spatial distribution and shares of PM(2.5) components. As part of Tracking Air Pollution in China (http://tapdata.org.cn), this daily-updated data set provides large opportunities for health and climate research as well as policy-making in China. American Chemical Society 2022-11-01 2022-11-15 /pmc/articles/PMC9670839/ /pubmed/36318737 http://dx.doi.org/10.1021/acs.est.2c06510 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Liu, Shigan
Geng, Guannan
Xiao, Qingyang
Zheng, Yixuan
Liu, Xiaodong
Cheng, Jing
Zhang, Qiang
Tracking Daily Concentrations of PM(2.5) Chemical Composition in China since 2000
title Tracking Daily Concentrations of PM(2.5) Chemical Composition in China since 2000
title_full Tracking Daily Concentrations of PM(2.5) Chemical Composition in China since 2000
title_fullStr Tracking Daily Concentrations of PM(2.5) Chemical Composition in China since 2000
title_full_unstemmed Tracking Daily Concentrations of PM(2.5) Chemical Composition in China since 2000
title_short Tracking Daily Concentrations of PM(2.5) Chemical Composition in China since 2000
title_sort tracking daily concentrations of pm(2.5) chemical composition in china since 2000
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9670839/
https://www.ncbi.nlm.nih.gov/pubmed/36318737
http://dx.doi.org/10.1021/acs.est.2c06510
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