2000年—2018年中国和印度的长期PM2.5污染暴露的疾病负担研究
Disease burden assessment exposure to long-term PM2.5 pollution in China and India （2000—2018）
- 2023年27卷第8期 页码：1834-1843
纸质出版日期： 2023-08-07
DOI： 10.11834/jrs.20231758
扫 描 看 全 文
浏览全部资源
扫码关注微信
摘要
PM
2.5
作为空气污染物，对人体健康构成了潜在威胁。中国和印度是全球人口最多的两个发展中国家，PM
2.5
污染造成的疾病负担问题尤为严重。因此，本文基于长时间序列高分辨率（0.01°×0.01°）卫星反演的PM
2.5
浓度数据，分析了中国和印度19年（2000年—2018年）的PM
2.5
时空格局变化和人口暴露情况；基于综合暴露响应模型全面评估了两个国家因PM
2.5
长期暴露导致的6种疾病（急性下呼吸道感染、慢性阻塞性肺病、二型糖尿病、缺血性心脏病、肺癌和中风）的过早死亡人数。结果表明，中国PM
2.5
浓度的高值区集中在新疆、四川盆地、华北平原以及长江经济带等地区，年人口加权浓度总体呈减少趋势（2000年为50 μg∙m
-3
，2018年为40.8 μg∙m
-3
）；印度PM
2.5
浓度的高值区集中在北部地区，年人口加权浓度一直呈上升趋势（2000年为51.5 μg∙m
-3
，2018年为76.4 μg∙m
-3
）。对于中国而言，PM
2.5
暴露造成的过早死亡人数从2000年的90.8万人增长至2018年的137.8万人，增长了47万人；中风是导致过早死亡的主要疾病终端，占总死亡人数的45.9%（56.3万人）。印度PM
2.5
暴露造成的过早死亡人数从2000年的34.3万人增长至2018年的75万人，增长了40.7万人；缺血性心脏病和中风是导致过早死亡的主要疾病终端，分别占比39.9%（20.2万人）和25.5%（12.9万人）。研究结果有望为决策者和污染控制机构提供参考，有助于制定空气污染治理政策。
Abstract
With the increasing frequency of air pollution incidents worldwide
many studies have focused on the disease burden from long-term exposure to PM
2.5
pollution. In China and India
the two most populous developing countries in the world
the disease burden attributable to PM
2.5
exposure are particularly serious. Therefore
these countries need to develop a multi-year and comprehensive dataset of PM
2.5
-related premature deaths to support their future air pollution prevention policies. However
only few studies have explored this topic over the past years. To fill this gap
this study analyzed the spatial and temporal patterns of PM
2.5
concentrations and changes of population exposure to PM
2.5
in China and India over the past 19 years (2000—2018) using high-resolution (0.01°×0.01°) satellite data. Combined with the Integrated Exposure Response (IER) model
this study comprehensively assessed the premature deaths from six diseases due to long-term PM
2.5
exposure
including acute lower respiratory infection
(ALRI)
Chronic Obstructive Pulmonary Disease
(COPD)
type 2 diabetes (DIA)
Ischemic Heart Disease (IHD)
lung cancer (LNC)
and stroke (STR).
Results show that those areas with high levels of PM
2.5
concentrations in China were concentrated in Xinjiang
Sichuan Basin
North China Plain
and the Yangtze River Economic Belt. The annual population-weighted PM
2.5
concentrations showed a decreasing trend (50 μg∙m
-3
in 2000 and 40.8 μg∙m
-3
in 2018). In India
high levels of PM
2.5
concentrations were concentrated in the north
including Punjab
Haryana
and Uttar Pradesh. The annual population-weighted PM
2.5
concentrations increased from 51.5 μg∙m
-3
in 2000 to 76.4 μg∙m
-3
in 2018. The number of premature deaths caused by PM
2.5
exposure in China increased by 34.1% from 908000 in 2000 to 1378000 in 2018
with the annual average premature deaths totaling 1228000. STR was the major contributor to total premature deaths in the country
accounting for 45.9% (563000) of all fatalities. In India
the number of premature deaths attributable to PM
2.5
increased rapidly from 343000 in 2000 to 750000 in 2018
with a net increase of 407000. The annual average premature deaths were 506000
the majority of which were attributed to IHD and STR
which accounted for 39.9% (202000) and 25.5% (129000) of all deaths
respectively. Moreover
DIA was responsible for 29000 (2.3%) and 30000 (6%) premature deaths in China and India
respectively
and therefore should not be ignored.
Overall
this study established a long-term series of high-resolution datasets on premature deaths due to PM
2.5
exposure in China and India. The number of premature deaths caused by air pollution remain high in China and India
both of which have high PM
2.5
concentrations and population density
thus necessitating stricter air pollution control policies. These results provide a reference for the formulation of air pollution policies in these countries. However
in estimating premature deaths due to PM
2.5
the baseline mortality rate did not consider the differences caused by the level of development and medical treatment within a country. Therefore
in a future study
the researchers will incorporate the sub-national baseline mortality rate when assessing premature deaths.
关键词
遥感PM2.5疾病负担过早死亡中国印度长时序
Keywords
remote sensingPM2.5disease burdenpremature deathsChinaIndialong time series
references
Brauer M, Amann M, Burnett R T, Cohen A, Dentener F, Ezzati M, Henderson S B, Krzyzanowski M, Martin R V, Van Dingenen R, van Donkelaar A and Thurston G D. 2012. Exposure assessment for estimation of the global burden of disease attributable to outdoor air pollution. Environmental Science and Technology, 46(2): 652-660 [DOI: 10.1021/es2025752http://dx.doi.org/10.1021/es2025752]
Chowdhury S and Dey S. 2016. Cause-specific premature death from ambient PM2.5 exposure in India: estimate adjusted for baseline mortality. Environment International, 91: 283-290 [DOI: 10.1016/j.envint.2016.03.004http://dx.doi.org/10.1016/j.envint.2016.03.004]
Ding D, Xing J, Wang S X, Liu K Y and Hao J M. 2019. Estimated contributions of emissions controls, meteorological factors, population growth, and changes in baseline mortality to reductions in ambient PM2.5 and PM2.5-related mortality in China, 2013—2017. Environmental Health Perspectives, 127(6): 067009 [DOI: 10.1289/EHP4157http://dx.doi.org/10.1289/EHP4157]
Fang D, Wang Q G, Li H M, Yu Y Y, Lu Y and Qian X. 2016. Mortality effects assessment of ambient PM2.5 pollution in the 74 leading cities of China. Science of the Total Environment, 569-570: 1545-1552 [DOI: 10.1016/j.scitotenv.2016.06.248http://dx.doi.org/10.1016/j.scitotenv.2016.06.248]
Global Burden of Disease Collaborative Network. 2018. Global Burden of Disease Study 2017 (GBD 2017) Population Estimates 1950—2017. Seattle, United States of America: Institute for Health Metrics and Evaluation (IHME)
Guan Y, Kang L, Wang Y, Zhang N N and Ju M T. 2019. Health loss attributed to PM2.5 pollution in China’s cities: economic impact, annual change and reduction potential. Journal of Cleaner Production, 217: 284-294 [DOI: 10.1016/j.jclepro.2019.01.284http://dx.doi.org/10.1016/j.jclepro.2019.01.284]
Hammer M S, van Donkelaar A, Li C, Lyapustin A, Sayer A M, Hsu N C, Levy R C, Garay M J, Kalashnikova O V, Kahn R A, Brauer M, Apte J S, Henze D K, Zhang L, Zhang Q, Ford B, Pierce J R and Martin R V. 2020. Global estimates and long-term trends of fine particulate matter concentrations (1998—2018). Environmental Science and Technology, 54(13): 7879-7890 [DOI: 10.1021/acs.est.0c01764http://dx.doi.org/10.1021/acs.est.0c01764]
Huang J, Pan X C, Guo X B and Li G X. 2018. Health impact of China’s Air Pollution Prevention and Control Action Plan: an analysis of national air quality monitoring and mortality data. The Lancet Planetary Health, 2(7): e313-e323 [DOI: 10.1016/S2542-5196(18)30141-4http://dx.doi.org/10.1016/S2542-5196(18)30141-4]
Jain V, Dey S and Chowdhury S. 2017. Ambient PM2.5 exposure and premature mortality burden in the holy city Varanasi, India. Environmental Pollution, 226: 182-189 [DOI: 10.1016/j.envpol.2017.04.028http://dx.doi.org/10.1016/j.envpol.2017.04.028]
Li Y, Zhao X G, Liao Q, Tao Y and Bai Y. 2020. Specific differences and responses to reductions for premature mortality attributable to ambient PM2.5 in China. Science of the Total Environment, 742: 140643 [DOI: 10.1016/j.scitotenv.2020.140643http://dx.doi.org/10.1016/j.scitotenv.2020.140643]
Li Y, Liao Q, Zhao X G, Bai Y and Tao Y. 2021. Influence of PM2.5 pollution on health burden and economic loss in China. Environmental Science, 42(4): 1688-1695
李勇, 廖琴, 赵秀阁, 白云, 陶燕. 2021. PM2.5污染对我国健康负担和经济损失的影响. 环境科学, 42(4): 1688-1695 [DOI: 10.13227/j.hjkx.202008313http://dx.doi.org/10.13227/j.hjkx.202008313]
Liang F C, Yang X L, Liu F C, Li J X, Xiao Q Y, Chen J C, Liu X Q, Cao J, Shen C, Yu L, Lu F H, Wu X P, Zhao L C, Wu X G, Li Y, Hu D S, Huang J F, Liu Y, Lu X F and Gu D F. 2019. Long-term exposure to ambient fine particulate matter and incidence of diabetes in China: a cohort study. Environment International, 126: 568-575 [DOI: 10.1016/j.envint.2019.02.069http://dx.doi.org/10.1016/j.envint.2019.02.069]
Limaye V S, Schöpp W and Amann M. 2019. Applying integrated exposure-response functions to PM2.5 pollution in India. International Journal of Environmental Research and Public Health, 16(1): 60 [DOI: 10.3390/ijerph16010060http://dx.doi.org/10.3390/ijerph16010060]
Liu J, Han Y Q, Tang X, Zhu J and Zhu T. 2016. Estimating adult mortality attributable to PM2.5 exposure in China with assimilated PM2.5 concentrations based on a ground monitoring network. Science of the Total Environment, 568: 1253-1262 [DOI: 10.1016/j.scitotenv.2016.05.165http://dx.doi.org/10.1016/j.scitotenv.2016.05.165]
Lu X C, Lin C Q, Li W K, Chen Y A, Huang Y Q, Fung J C H and Lau A K H. 2019. Analysis of the adverse health effects of PM2.5 from 2001 to 2017 in China and the role of urbanization in aggravating the health burden. Science of the Total Environment, 652: 683-695 [DOI: 10.1016/j.scitotenv.2018.10.140http://dx.doi.org/10.1016/j.scitotenv.2018.10.140]
Maji K J. 2020. Substantial changes in PM2.5 pollution and corresponding premature deaths across China during 2015—2019: a model prospective. Science of the Total Environment, 729: 138838 [DOI: 10.1016/j.scitotenv.2020.138838http://dx.doi.org/10.1016/j.scitotenv.2020.138838]
Maji K J, Li V O K and Lam J C K. 2020. Effects of China's current Air Pollution Prevention and Control Action Plan on air pollution patterns, health risks and mortalities in Beijing 2014—2018. Chemosphere, 260: 127572 [DOI: 10.1016/j.chemosphere.2020.127572http://dx.doi.org/10.1016/j.chemosphere.2020.127572]
Manojkumar N and Srimuruganandam B. 2021. Health benefits of achieving fine particulate matter standards in India-A nationwide assessment. Science of the Total Environment, 763: 142999 [DOI: 10.1016/j.scitotenv.2020.142999http://dx.doi.org/10.1016/j.scitotenv.2020.142999]
Sahu S K, Sharma S, Zhang H L, Chejarla V, Guo H, Hu J L, Ying Q, Xing J and Kota S H. 2020. Estimating ground level PM2.5 concentrations and associated health risk in India using satellite based AOD and WRF predicted meteorological parameters. Chemosphere, 255: 126969 [DOI: 10.1016/j.chemosphere.2020.126969http://dx.doi.org/10.1016/j.chemosphere.2020.126969]
Wang H, Yin P, Fan W H, Wang Y, Dong Z M, Deng Q H and Zhou M G. 2021. Mortality risk associated with short-term exposure to particulate matter in China: estimating error and implication. Environmental Science and Technology, 55(2): 1110-1121 [DOI: 10.1021/acs.est.0c05095http://dx.doi.org/10.1021/acs.est.0c05095]
Wang Q, Wang J N, He M Z, Kinney P L and Li T T. 2018. A county-level estimate of PM2.5 related chronic mortality risk in China based on multi-model exposure data. Environment International, 110: 105-112 [DOI: 10.1016/j.envint.2017.10.015http://dx.doi.org/10.1016/j.envint.2017.10.015]
Wang Q, Zhu H H, Du P, Zhao L and Li T T. 2021. Health benefit of ‘14th Five-Year’ and medium and long-term PM2.5 control targets in Beijing-Tianjin-Hebei and its surrounding areas. Research of Environmental Sciences, 34(1): 220-228
王情, 朱欢欢, 杜鹏, 赵靓, 李湉湉. 2021. 京津冀及周边地区“十四五”及中长期PM2.5污染控制目标的健康效益预估研究. 环境科学研究, 34(1): 220-228 [DOI: 1.13198/j.issn.1001-6929.2020.11.21http://dx.doi.org/1.13198/j.issn.1001-6929.2020.11.21]
Wei J, Li Z Q, Lyapustin A, Sun L, Peng Y R, Xue W H, Su T N and Cribb M. 2021. Reconstructing 1-km-resolution high-quality PM2.5 data records from 2000 to 2018 in China: spatiotemporal variations and policy implications. Remote Sensing of Environment, 252: 112136 [DOI: 10.1016/j.rse.2020.112136http://dx.doi.org/10.1016/j.rse.2020.112136]
Xiang J, Tao M H, Guo L, Chen L F, Tao J H and Gui L. 2022. Progress of near-surface PM2.5 concentration retrieve based on satellite remote sensing. National Remote Sensing Bulletin, 26(9): 1757-1776
向娟, 陶明辉, 郭玲, 陈良富, 陶金花, 桂露. 2022. 基于卫星遥感的近地面PM2.5浓度反演进展. 遥感学报, 26(9): 1757-1776 [DOI: 10.11834/jrs.20210438http://dx.doi.org/10.11834/jrs.20210438]
Xiao Q Y, Geng G N, Xue T, Liu S G, Cai C L, He K B and Zhang Q. 2022. Tracking PM2.5 and O3 pollution and the related health burden in China 2013—2020. Environmental Science and Technology, 56(11): 6922-6932 [DOI: 10.1021/acs.est.1c04548http://dx.doi.org/10.1021/acs.est.1c04548]
Xue T, Zhu T, Zheng Y X, Liu J, Li X and Zhang Q. 2019. Change in the number of PM2.5-attributed deaths in China from 2000 to 2010: comparison between estimations from census-based epidemiology and pre-established exposure-response functions. Environment International, 129: 430-437 [DOI: 10.1016/j.envint.2019.05.067http://dx.doi.org/10.1016/j.envint.2019.05.067]
Yang W and Jiang X L. 2021. Evaluating the influence of land use and land cover change on fine particulate matter. Scientific Reports, 11: 17612 [DOI: 10.1038/s41598-021-97088-8http://dx.doi.org/10.1038/s41598-021-97088-8]
Yang X C, Wang Y, Zhao C F, Fan H, Yang Y K, Chi Y L, Shen L X and Yan X. 2022. Health risk and disease burden attributable to long-term global fine-mode particles. Chemosphere, 287: 132435 [DOI: 10.1016/j.chemosphere.2021.132435http://dx.doi.org/10.1016/j.chemosphere.2021.132435]
Yue H B, He C Y, Huang Q X, Yin D and Bryan B A. 2020. Stronger policy required to substantially reduce deaths from PM2.5 pollution in China. Nature Communications. 1462. [DOI: 10.1038/s41467-020-15319-4http://dx.doi.org/10.1038/s41467-020-15319-4]
Zhang Y Q. 2021. All-Cause Mortality Risk and Attributable Deaths Associated with Long-Term Exposure to Ambient PM2.5 in Chinese Adults.Environmental Science & Technology, 55(9): 6116-6127. [DOI: 10.1021/acs.est.0c08527http://dx.doi.org/10.1021/acs.est.0c08527]
Zhou M G, Wang H D, Zhu J, Chen W Q, Wang L H, Liu S W, and Li Y C. 2016. Cause-specific mortality for 240 causes in China during 1990—2013: a systematic subnational analysis for the Global Burden of Disease Study 2013. The Lancet, 387 (10015): 251-272. [DOI: 10.1016/S0140-6736(15)00551-6http://dx.doi.org/10.1016/S0140-6736(15)00551-6]
Zou B, You J W, Lin Y, Duan X L, Zhao X G, Fang X, Matthew J C, and Li S X. 2019. Air pollution intervention and life-saving effect in China.Environment International, 125: 529-541. [DOI: 10.1016/j.envint.2018.10.045http://dx.doi.org/10.1016/j.envint.2018.10.045]
文章被引用时，请邮件提醒。
提交
相关作者
暂无数据
相关机构
国家卫星气象中心(国家空间天气监测预警中心) 中国气象局中国遥感卫星辐射测量和 定标重点开放实验室
许健民气象卫星创新中心
南京大学 国际地球系统科学研究所
信息工程大学 地理空间信息学院
北京遥感信息研究所
选择翻译语言
- 地址：北京市海淀区北四环西路19号 《遥感学报》编辑部 邮编：100190
- 联系电话：010-58887052 Email：nrsb@aircas.ac.cn
- 技术支持由北京北大方正电子有限公司提供 京ICP备20021838号-9
京公网安备11010802024621 - 本系统建议在Chrome、 IE9+ 以上版本浏览器阅读本站内容，360浏览器请切换至极速模式
- Cookies帮助我们提供服务并提供个性化体验。使用本网站，即表示您同意我们使用Cookies
0
回到顶部