Characterizing the effects of structural fires on fine particulate matter with a dense sensing network

被引:2
作者
Anyachebelu, Ayina [1 ]
Cabral, Alex [2 ]
Abdin, Marah I. I. [3 ]
Choudhury, Pallavi [3 ]
Daepp, Madeleine I. G. [3 ]
机构
[1] UCL, Dept Civil Environm & Geomat Engn, London WC1E 7HB, England
[2] Harvard Univ, John A Paulson Sch Engn & Appl Sci, Boston, MA 02134 USA
[3] Microsoft Res, Redmond, WA 98052 USA
关键词
AIR-POLLUTION; ANOMALY DETECTION; SENSOR NETWORKS; MORTALITY; EXPOSURE; POLLUTANTS; RISK;
D O I
10.1038/s41598-023-38392-3
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Short-term increases in air pollution levels are linked to large adverse effects on health and productivity. However, existing regulatory monitoring systems lack the spatial or temporal resolution needed to capture localized events. This study uses a dense network of over 100 sensors, deployed across the city of Chicago, Illinois, to capture the spread of smoke from short-term structural fire events. Examining all large structural fires that occurred in the city over a year (N = 21), we characterize differences in PM (2.5) concentrations downwind versus upwind of the fires. On average, we observed increases of up to 10.7 mu g/m (3) (95% CI 5.7-15.7) for sensors within 2 km and up to 7.7 mu g/m (3) (95% CI 3.4-12.0) for sensors 2-5 km downwind of fires. Statistically significant elevated concentrations were evident as far as 5 km downwind of the location of the fire and persisted over approximately 2 h on average. This work shows how low-cost sensors can provide insight on local and short-term pollution events, enabling regulators to provide timely warnings to vulnerable populations.
引用
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页数:10
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