Literature DB >> 31605867

Spatiotemporal distributions of ambient SO2 across China based on satellite retrievals and ground observations: Substantial decrease in human exposure during 2013-2016.

Hanyue Zhang1, Baofeng Di2, Dongren Liu1, Jierui Li1, Yu Zhan3.   

Abstract

Multiyear spatiotemporal distributions of daily ambient sulfur dioxide (SO2) are essential for evaluating management effectiveness and assessing human health risk. In this study, we estimate the daily SO2 levels across China on 0.1o grid from 2013 to 2016 by assimilating satellite- and ground-based SO2 observations using the random-forest spatiotemporal kriging (RF-STK) model. The cross-validation R2 is 0.64 and 0.81 for predicting the daily and multiyear averages, respectively. The multiyear population-weighted average of SO2 for China is 28.1 ± 14.0 μg/m3, and the severest SO2 pollution occurs in the northern China (45.1 ± 14.7 μg/m3). The SO2 concentration shows a strong seasonality, i.e., highest in winter (41.6 ± 26.4 μg/m3) and lowest in summer (19.6 ± 8.3 μg/m3). During 2013-2016, the annual SO2 decreases from 34.4 ± 18.2 to 22.7 ± 11.1 μg/m3, and the population% exposed for more than 100 nonattainment days (SO2 > 20 μg/m3) drops from 86% to 48%. While the seasonality of SO2 is mainly determined by the meteorological variation, the substantial decrease attributes to the reduced emissions such as from coal consumption. The effectiveness of SO2 emission reduction varies widely in different prefectures of China. In Shandong province, the SO2 concentration decreases by -45% while the coal consumption increases by 9%. In Shanxi province, the SO2 concentration decreases by -15% while the coal consumption decreases by -3%. The contrasting effectiveness between these two provinces is associated with the much fewer waste gas disposal facilities in Shanxi than Shandong. Stricter regulation is required to further lower the SO2 concentration in order to protect the public health, especially in the northern China.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  China; Human exposure; Remote sensing; SO(2); Spatiotemporal distribution

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Year:  2019        PMID: 31605867     DOI: 10.1016/j.envres.2019.108795

Source DB:  PubMed          Journal:  Environ Res        ISSN: 0013-9351            Impact factor:   6.498


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