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Assessment of long-term particulate nitrate air pollution and its health risk in China
Air pollution is a major environmental and public health challenge in China and the Chinese government has implemented a series of strict air quality policies. However, particulate nitrate (NO(3)(−)) concentration remains high or even increases at monitoring sites despite the total PM(2.5) concentra...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9418855/ https://www.ncbi.nlm.nih.gov/pubmed/36039292 http://dx.doi.org/10.1016/j.isci.2022.104899 |
Sumario: | Air pollution is a major environmental and public health challenge in China and the Chinese government has implemented a series of strict air quality policies. However, particulate nitrate (NO(3)(−)) concentration remains high or even increases at monitoring sites despite the total PM(2.5) concentration has decreased. Unfortunately, it has been difficult to estimate NO(3)(−) concentration across China due to the lack of a PM(2.5) speciation monitoring network. Here, we use a machine learning model incorporating ground measurements and satellite data to characterize the spatiotemporal patterns of NO(3)(−), thereby understanding the disease burden associated with long-term NO(3)(−) exposure in China. Our results show that existing air pollution control policies are effective, but increased NO(3)(−) of traffic emissions offset reduced NO(3)(−) of industrial emissions. In 2018, the national mean mortality burden attributable to NO(3)(−) was as high as 0.68 million, indicating that targeted regulations are needed to control NO(3)(−) pollution in China. |
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