No one knows which city has the highest concentration of fine particulate matter

被引:82
作者
Martin, Randall, V [1 ,2 ,3 ]
Brauer, Michael [4 ,5 ]
van Donkelaar, Aaron [1 ]
Shaddick, Gavin [6 ]
Narain, Urvashi [7 ]
Dey, Sagnik [8 ,9 ]
机构
[1] Dalhousie Univ, Dept Phys & Atmospher Sci, Halifax, NS, Canada
[2] Harvard Smithsonian Ctr Astrophys, 60 Garden St, Cambridge, MA 02138 USA
[3] Washington Univ, Dept Energy Environm & Chem Engn, St Louis, MO 63110 USA
[4] Univ British Columbia, Sch Populat & Publ Hlth, Vancouver, BC, Canada
[5] Univ Washington, Inst Hlth Metr & Evaluat, Seattle, WA 98195 USA
[6] Univ Exeter, Dept Math, Exeter, Devon, England
[7] World Bank, Environm & Nat Resources Global Practice, 1818 H St NW, Washington, DC 20433 USA
[8] Indian Inst Technol Delhi, Ctr Atmospher Sci, Delhi, India
[9] Indian Inst Technol Delhi, Sch Publ Policy, Delhi, India
来源
ATMOSPHERIC ENVIRONMENT-X | 2019年 / 3卷
基金
加拿大自然科学与工程研究理事会;
关键词
Fine particulate matter; PM2.5; Air quality; NETWORK; HEALTH; PM2.5;
D O I
10.1016/j.aeaoa.2019.100040
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Exposure to ambient fine particulate matter (PM2.5) is the leading global environmental risk factor for mortality and disease burden, with associated annual global welfare costs of trillions of dollars. Examined within is the ability of current data to answer a basic question about PM2.5, namely the location of the city with the highest PM2.5 concentration. The ability to answer this basic question serves as an indicator of scientific progress to assess global human exposure to air pollution and as an important component of efforts to reduce its impacts. Despite the importance of PM2.5, we find that insufficient monitoring data exist to answer this basic question about the spatial pattern of PM2.5 at the global scale. Only 24 of 234 countries have more than 3 monitors per million inhabitants, while density is an order of magnitude lower in the vast majority of the world's countries, with 141 having no regular PM2.5 monitoring at all. The global mean population distance to nearest PM2.5 monitor is 220 km, too large for exposure assessment. Efforts to fill in monitoring gaps with estimates from satellite remote sensing, chemical transport modeling, and statistical models have biases at individual monitor locations that can exceed 50 mu g m(-3). Progress in advancing knowledge about the global distribution of PM2.5 will require a harmonized network that integrates different types of monitoring equipment (regulatory networks, low-cost monitors, satellite remote sensing, and research-grade instrumentation) with atmospheric and statistical models. Realization of such an integrated framework will facilitate accurate identification of the location of the city with the highest PM2.5 concentration and play a key role in tracking the progress of efforts to reduce the global impacts of air pollution.
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页数:5
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