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Satellite‐Based Long‐Term Spatiotemporal Trends in Ambient NO(2) Concentrations and Attributable Health Burdens in China From 2005 to 2020
Despite the recent development of using satellite remote sensing to predict surface NO(2) levels in China, methods for estimating reliable historical NO(2) exposure, especially before the establishment of NO(2) monitoring network in 2013, are still rare. A gap‐filling model was first adopted to impu...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10190124/ https://www.ncbi.nlm.nih.gov/pubmed/37206379 http://dx.doi.org/10.1029/2023GH000798 |
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author | Huang, Keyong Zhu, Qingyang Lu, Xiangfeng Gu, Dongfeng Liu, Yang |
author_facet | Huang, Keyong Zhu, Qingyang Lu, Xiangfeng Gu, Dongfeng Liu, Yang |
author_sort | Huang, Keyong |
collection | PubMed |
description | Despite the recent development of using satellite remote sensing to predict surface NO(2) levels in China, methods for estimating reliable historical NO(2) exposure, especially before the establishment of NO(2) monitoring network in 2013, are still rare. A gap‐filling model was first adopted to impute the missing NO(2) column densities from satellite, then an ensemble machine learning model incorporating three base learners was developed to estimate the spatiotemporal pattern of monthly mean NO(2) concentrations at 0.05° spatial resolution from 2005 to 2020 in China. Further, we applied the exposure data set with epidemiologically derived exposure response relations to estimate the annual NO(2) associated mortality burdens in China. The coverage of satellite NO(2) column densities increased from 46.9% to 100% after gap‐filling. The ensemble model predictions had good agreement with observations, and the sample‐based, temporal and spatial cross‐validation (CV) R (2) were 0.88, 0.82, and 0.73, respectively. In addition, our model can provide accurate historical NO(2) concentrations, with both by‐year CV R (2) and external separate year validation R (2) achieving 0.80. The estimated national NO(2) levels showed a increasing trend during 2005–2011, then decreased gradually until 2020, especially in 2012–2015. The estimated annual mortality burden attributable to long‐term NO(2) exposure ranged from 305 thousand to 416 thousand, and varied considerably across provinces in China. This satellite‐based ensemble model could provide reliable long‐term NO(2) predictions at a high spatial resolution with complete coverage for environmental and epidemiological studies in China. Our results also highlighted the heavy disease burden by NO(2) and call for more targeted policies to reduce the emission of nitrogen oxides in China. |
format | Online Article Text |
id | pubmed-10190124 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-101901242023-05-18 Satellite‐Based Long‐Term Spatiotemporal Trends in Ambient NO(2) Concentrations and Attributable Health Burdens in China From 2005 to 2020 Huang, Keyong Zhu, Qingyang Lu, Xiangfeng Gu, Dongfeng Liu, Yang Geohealth Research Article Despite the recent development of using satellite remote sensing to predict surface NO(2) levels in China, methods for estimating reliable historical NO(2) exposure, especially before the establishment of NO(2) monitoring network in 2013, are still rare. A gap‐filling model was first adopted to impute the missing NO(2) column densities from satellite, then an ensemble machine learning model incorporating three base learners was developed to estimate the spatiotemporal pattern of monthly mean NO(2) concentrations at 0.05° spatial resolution from 2005 to 2020 in China. Further, we applied the exposure data set with epidemiologically derived exposure response relations to estimate the annual NO(2) associated mortality burdens in China. The coverage of satellite NO(2) column densities increased from 46.9% to 100% after gap‐filling. The ensemble model predictions had good agreement with observations, and the sample‐based, temporal and spatial cross‐validation (CV) R (2) were 0.88, 0.82, and 0.73, respectively. In addition, our model can provide accurate historical NO(2) concentrations, with both by‐year CV R (2) and external separate year validation R (2) achieving 0.80. The estimated national NO(2) levels showed a increasing trend during 2005–2011, then decreased gradually until 2020, especially in 2012–2015. The estimated annual mortality burden attributable to long‐term NO(2) exposure ranged from 305 thousand to 416 thousand, and varied considerably across provinces in China. This satellite‐based ensemble model could provide reliable long‐term NO(2) predictions at a high spatial resolution with complete coverage for environmental and epidemiological studies in China. Our results also highlighted the heavy disease burden by NO(2) and call for more targeted policies to reduce the emission of nitrogen oxides in China. John Wiley and Sons Inc. 2023-05-17 /pmc/articles/PMC10190124/ /pubmed/37206379 http://dx.doi.org/10.1029/2023GH000798 Text en © 2023 The Authors. GeoHealth published by Wiley Periodicals LLC on behalf of American Geophysical Union. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Huang, Keyong Zhu, Qingyang Lu, Xiangfeng Gu, Dongfeng Liu, Yang Satellite‐Based Long‐Term Spatiotemporal Trends in Ambient NO(2) Concentrations and Attributable Health Burdens in China From 2005 to 2020 |
title | Satellite‐Based Long‐Term Spatiotemporal Trends in Ambient NO(2) Concentrations and Attributable Health Burdens in China From 2005 to 2020 |
title_full | Satellite‐Based Long‐Term Spatiotemporal Trends in Ambient NO(2) Concentrations and Attributable Health Burdens in China From 2005 to 2020 |
title_fullStr | Satellite‐Based Long‐Term Spatiotemporal Trends in Ambient NO(2) Concentrations and Attributable Health Burdens in China From 2005 to 2020 |
title_full_unstemmed | Satellite‐Based Long‐Term Spatiotemporal Trends in Ambient NO(2) Concentrations and Attributable Health Burdens in China From 2005 to 2020 |
title_short | Satellite‐Based Long‐Term Spatiotemporal Trends in Ambient NO(2) Concentrations and Attributable Health Burdens in China From 2005 to 2020 |
title_sort | satellite‐based long‐term spatiotemporal trends in ambient no(2) concentrations and attributable health burdens in china from 2005 to 2020 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10190124/ https://www.ncbi.nlm.nih.gov/pubmed/37206379 http://dx.doi.org/10.1029/2023GH000798 |
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