Global estimates of daily ambient fine particulate matter concentrations and unequal spatiotemporal distribution of population exposure: a machine learning modelling study

被引:56
|
作者
Yu, Wenhua [1 ]
Ye, Tingting
Zhang, Yiwen [1 ]
Xu, Rongbin [1 ]
Lei, Yadong [4 ]
Chen, Zhuying [2 ]
Yang, Zhengyu [1 ]
Zhang, Yuxi [1 ]
Song, Jiangning [3 ]
Yue, Xu [5 ]
Li, Shanshan [1 ]
Guo, Yuming [1 ]
机构
[1] Monash Univ, Sch Publ Hlth & Prevent Med, Climate Air Qual Res Unit, Melbourne, Vic 3004, Australia
[2] Monash Univ, Turner Inst Brain & Mental Hlth, Sch Psychol Sci, Melbourne, Vic, Australia
[3] Monash Univ, Monash Biomed Discovery Inst, Dept Biochem & Mol Biol, Melbourne, Vic, Australia
[4] Chinese Acad Meteorol Sci, State Key Lab Severe Weather, Key Lab Atmospher Chem CMA, Beijing, Peoples R China
[5] Nanjing Univ Informat Sci & Technol, Jiangsu Collaborat Innovat Ctr Atmospher Environm, Sch Environm Sci & Engn, Jiangsu Key Lab Atmospher Environm Monitoring & Po, Nanjing, Peoples R China
来源
LANCET PLANETARY HEALTH | 2023年 / 7卷 / 03期
基金
澳大利亚研究理事会; 英国医学研究理事会;
关键词
D O I
10.1016/S2542-5196(23)00008-6
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Background Short-term exposure to ambient PM2 center dot 5 is a leading contributor to the global burden of diseases and mortality. However, few studies have provided the global spatiotemporal variations of daily PM2 center dot 5 concentrations over recent decades. Methods In this modelling study, we implemented deep ensemble machine learning (DEML) to estimate global daily ambient PM2 center dot 5 concentrations at 0.1 degrees x 0.1 degrees spatial resolution between Jan 1, 2000, and Dec 31, 2019. In the DEML framework, ground-based PM2 center dot 5 measurements from 5446 monitoring stations in 65 countries worldwide were combined with GEOS-Chem chemical transport model simulations of PM2 center dot 5 concentration, meteorological data, and geographical features. At the global and regional levels, we investigated annual population-weighted PM2 center dot 5 concentrations and annual population-weighted exposed days to PM2 center dot 5 concentrations higher than 15 mu g/m(3) (2021 WHO daily limit) to assess spatiotemporal exposure in 2000, 2010, and 2019. Land area and population exposures to PM2 center dot 5 above 5 mu g/m(3) (2021 WHO annual limit) were also assessed for the year 2019. PM2 center dot 5 concentrations for each calendar month were averaged across the 20-year period to investigate global seasonal patterns. Findings Our DEML model showed good performance in capturing the global variability in ground-measured daily PM2 center dot 5, with a cross-validation R-2 of 0.91 and root mean square error of 7.86 mu g/m(3). Globally, across 175 countries, the mean annual population-weighted PM2 center dot 5 concentration for the period 2000-19 was estimated at 32.8 mu g/m(3) (SD 0.6). During the two decades, population-weighted PM2 center dot 5 concentration and annual population-weighted exposed days (PM2.(5) >15 mu g/m(3)) decreased in Europe and northern America, whereas exposures increased in southern Asia, Australia and New Zealand, and Latin America and the Caribbean. In 2019, only 0.18% of the global land area and 0.001% of the global population had an annual exposure to PM2 center dot 5 at concentrations lower than 5 mu g/m(3), with more than 70% of days having daily PM2.(5) concentrations higher than 15 mu g/m(3). Distinct seasonal patterns were indicated in many regions of the world. Interpretation The high-resolution estimates of daily PM2.(5) provide the first global view of the unequal spatiotemporal distribution of PM2 center dot 5 exposure for a recent 20-year period, which is of value for assessing short-term and long-term health effects of PM2 center dot 5, especially for areas where monitoring station data are not available.
引用
收藏
页码:e209 / e218
页数:10
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