Literature DB >> 35120956

Air pollutant spatiotemporal evolution characteristics and effects on human health in North China.

Chuanqi Xu1, Zhi Zhang2, Guangjiu Ling3, Guoqiang Wang4, Mingzhu Wang5.   

Abstract

North China, the political, economic, and cultural center of China, has been greatly harmed by frequent air pollution incidents. Therefore, it is vital to study air pollution characteristics and clarify their impact on human health. In this study, we first analyzed the spatiotemporal variations of air pollutants (PM2.5, PM10, CO, SO2, NO2, and O3) in North China from 2016 to 2019. Then, the air quality index (AQI), aggregate air quality index (AAQI), and health risk based air quality index (HAQI) were used to assess health risks. Based on these, the AirQ2.2.3 model was used to quantify health effects. The results showed that the major pollutant in the cities surrounding Beijing was PM2.5, while PM10 dominated in distant cities. Annual concentrations decreased (except for O3), which is related to governmental emission reduction policies. However, O3 concentrations increased owing to the complex precursor emissions. The AQI underestimated air pollution, while the AAQI and HAQI were accurate; the latter indicated that 55% of the study region population was exposed to polluted air. The AirQ2.2.3 model quantified the total mortality proportions attributable to PM2.5, PM10, SO2, CO, NO2, and O3, which were 1.87%, 3.12%, 1.11%, 1.40%, 4.19%, and 2.52%, respectively. In high concentrations, PM10 and PM2.5 pose significant health risks. The health effects of SO2, NO2, CO, and O3 at lower concentrations were more obvious, indicating that the expected mortality rate due to low concentrations of some pollutants was much higher than that due to high concentrations of other pollutants.
Copyright © 2022 Elsevier Ltd. All rights reserved.

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Keywords:  Air pollutants; Air quality index; Exposure-response relationship; Health effects; North China

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Year:  2022        PMID: 35120956     DOI: 10.1016/j.chemosphere.2022.133814

Source DB:  PubMed          Journal:  Chemosphere        ISSN: 0045-6535            Impact factor:   7.086


  1 in total

1.  An air quality index prediction model based on CNN-ILSTM.

Authors:  Jingyang Wang; Xiaolei Li; Lukai Jin; Jiazheng Li; Qiuhong Sun; Haiyao Wang
Journal:  Sci Rep       Date:  2022-05-19       Impact factor: 4.996

  1 in total

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