What drives long-term PM₂.₅-attributable premature mortality change? A case study in central China using high-resolution satellite data from 2003 to 2018
Ambient PM2.5 was reported to be related to numerous negative health outcomes, leading to adverse public health impacts in many countries such as China. Despite the apparent reduction in PM2.5 levels over China due to its emission control policies in recent years, the health burdens were not reduced...
Saved in:
Main Authors: | , , |
---|---|
Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2022
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/162625 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-162625 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-1626252022-11-05T23:31:15Z What drives long-term PM₂.₅-attributable premature mortality change? A case study in central China using high-resolution satellite data from 2003 to 2018 He, Qingqing Gu, Yefu Yim, Steve Hung Lam Asian School of the Environment Lee Kong Chian School of Medicine (LKCMedicine) Earth Observatory of Singapore Science::Medicine Engineering::Environmental engineering Satellite Remote Sensing Health Burden Ambient PM2.5 was reported to be related to numerous negative health outcomes, leading to adverse public health impacts in many countries such as China. Despite the apparent reduction in PM2.5 levels over China due to its emission control policies in recent years, the health burdens were not reduced as much as expected. This calls for a comprehensive analysis to explain the reasons behind to provide a useful reference for formulating effective emission control strategies. Taking central China as an example due to its large population and high levels of PM2.5, this study quantified the spatiotemporal dynamics of premature mortality associated with PM2.5 pollution in central China for each year during 2003-2018 and applied a decomposition analysis to dissect the contribution of various driving factors including ambient PM2.5 level, demographic distribution and baseline incidence rate of four diseases related to air pollution. Results show significant spatiotemporal variations in PM2.5-attributed health impact in central China, including Henan, Hubei, and Hunan provinces. Five Henan cities had the largest PM2.5-attributable premature mortality (∼8-12 K premature mortalities), while three Hubei cities and one Hebei city had the least chronic PM2.5-related all-cause mortality numbers (<1 K mortalities). Throughout the study period, the PM2.5-caused premature mortality decreased by 54 K, in which changes in PM2.5 levels and baseline incidence rates of stroke and chronic obstructive pulmonary disease contributed to the positive effect, whereas demographic changes and baseline incidence rate change of ischemic heart disease and lung cancer brought a countervailing effect. Our findings suggest more dynamic and comprehensive policies and measures that take into account spatiotemporal variations of health burden for effective alleviation of the health impact of PM2.5 pollution in the country. Published version This research was funded by the Vice-Chancellor’s Discretionary Fund of The Chinese University of Hong Kong (Grant No. 4930744), Dr. Stanley Ho Medicine Development Foundation (Grant No. 8305509), and the National Natural Science Foundation of China (Grant No. 41901324). 2022-11-01T06:19:46Z 2022-11-01T06:19:46Z 2022 Journal Article He, Q., Gu, Y. & Yim, S. H. L. (2022). What drives long-term PM₂.₅-attributable premature mortality change? A case study in central China using high-resolution satellite data from 2003 to 2018. Environment International, 161, 107110-. https://dx.doi.org/10.1016/j.envint.2022.107110 0160-4120 https://hdl.handle.net/10356/162625 10.1016/j.envint.2022.107110 35134714 2-s2.0-85124046821 161 107110 en Environment International © 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). application/pdf |
institution |
Nanyang Technological University |
building |
NTU Library |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
NTU Library |
collection |
DR-NTU |
language |
English |
topic |
Science::Medicine Engineering::Environmental engineering Satellite Remote Sensing Health Burden |
spellingShingle |
Science::Medicine Engineering::Environmental engineering Satellite Remote Sensing Health Burden He, Qingqing Gu, Yefu Yim, Steve Hung Lam What drives long-term PM₂.₅-attributable premature mortality change? A case study in central China using high-resolution satellite data from 2003 to 2018 |
description |
Ambient PM2.5 was reported to be related to numerous negative health outcomes, leading to adverse public health impacts in many countries such as China. Despite the apparent reduction in PM2.5 levels over China due to its emission control policies in recent years, the health burdens were not reduced as much as expected. This calls for a comprehensive analysis to explain the reasons behind to provide a useful reference for formulating effective emission control strategies. Taking central China as an example due to its large population and high levels of PM2.5, this study quantified the spatiotemporal dynamics of premature mortality associated with PM2.5 pollution in central China for each year during 2003-2018 and applied a decomposition analysis to dissect the contribution of various driving factors including ambient PM2.5 level, demographic distribution and baseline incidence rate of four diseases related to air pollution. Results show significant spatiotemporal variations in PM2.5-attributed health impact in central China, including Henan, Hubei, and Hunan provinces. Five Henan cities had the largest PM2.5-attributable premature mortality (∼8-12 K premature mortalities), while three Hubei cities and one Hebei city had the least chronic PM2.5-related all-cause mortality numbers (<1 K mortalities). Throughout the study period, the PM2.5-caused premature mortality decreased by 54 K, in which changes in PM2.5 levels and baseline incidence rates of stroke and chronic obstructive pulmonary disease contributed to the positive effect, whereas demographic changes and baseline incidence rate change of ischemic heart disease and lung cancer brought a countervailing effect. Our findings suggest more dynamic and comprehensive policies and measures that take into account spatiotemporal variations of health burden for effective alleviation of the health impact of PM2.5 pollution in the country. |
author2 |
Asian School of the Environment |
author_facet |
Asian School of the Environment He, Qingqing Gu, Yefu Yim, Steve Hung Lam |
format |
Article |
author |
He, Qingqing Gu, Yefu Yim, Steve Hung Lam |
author_sort |
He, Qingqing |
title |
What drives long-term PM₂.₅-attributable premature mortality change? A case study in central China using high-resolution satellite data from 2003 to 2018 |
title_short |
What drives long-term PM₂.₅-attributable premature mortality change? A case study in central China using high-resolution satellite data from 2003 to 2018 |
title_full |
What drives long-term PM₂.₅-attributable premature mortality change? A case study in central China using high-resolution satellite data from 2003 to 2018 |
title_fullStr |
What drives long-term PM₂.₅-attributable premature mortality change? A case study in central China using high-resolution satellite data from 2003 to 2018 |
title_full_unstemmed |
What drives long-term PM₂.₅-attributable premature mortality change? A case study in central China using high-resolution satellite data from 2003 to 2018 |
title_sort |
what drives long-term pm₂.₅-attributable premature mortality change? a case study in central china using high-resolution satellite data from 2003 to 2018 |
publishDate |
2022 |
url |
https://hdl.handle.net/10356/162625 |
_version_ |
1749179217198710784 |