globalchange  > 气候变化与战略
DOI: 10.1016/j.atmosenv.2020.117410
论文题名:
Observation of PM2.5 using a combination of satellite remote sensing and low-cost sensor network in Siberian urban areas with limited reference monitoring
作者: Lin C.; Labzovskii L.D.; Mak H.W.L.; Fung J.C.H.; Lau A.K.H.; Kenea S.T.; Bilal M.; Vande Hey J.D.; Lu X.; Ma J.
刊名: Atmospheric Environment
ISSN: 1352-2310
出版年: 2020
卷: 227
语种: 英语
英文关键词: Air quality ; Cost benefit analysis ; Costs ; Developing countries ; Radiosondes ; Satellites ; Sensor networks ; Smoke ; Ground based sensors ; Low-cost sensors ; Meteorological observation ; PM2.5 ; Radiosonde observations ; Satellite remote sensing ; SIBERIA ; World Health Organization ; Remote sensing ; air quality ; concentration (composition) ; ground-based measurement ; industrial emission ; long-term change ; network analysis ; particulate matter ; radiosonde ; remote sensing ; satellite altimetry ; sensor ; urban area ; air monitoring ; air quality ; Article ; atmospheric transport ; calibration ; comparative study ; concentration (parameter) ; forest ; humidity ; meteorology ; particulate matter ; physical model ; practice guideline ; priority journal ; Russian Federation ; satellite imagery ; smoke ; summer ; uncertainty ; urban area ; visibility ; wildfire ; winter ; World Health Organization ; Krasnoyarsk [Russian Federation] ; Russian Federation ; Siberia
学科: Air quality ; Low-cost sensor ; PM2.5 ; Satellite ; Siberia
中文摘要: The lack of reference ground-based PM2.5 observation leads to large gaps in air quality information, particularly in many areas of the developing world. This study investigated a new solution for urban air-quality monitoring in regions with limited reference ground-based monitoring. We developed an observation-based method by combining satellite remote-sensing techniques and a newly established low-cost sensor network to estimate long-term PM2.5 concentrations over Krasnoyarsk, a highly industrialized Siberian city. First, a physical model was developed to estimate PM2.5 concentrations using satellite remote-sensing with the aid of ground-based meteorological and radiosonde observations. Observations from the ground-based sensor network were then used to calibrate the deviations in the satellite-derived PM2.5 concentrations. The results show that the satellite-based PM2.5 concentrations obtained by our physical model were in good agreement with the sensor observations (R = 0.78 on the monthly scale). The deviation in satellite-derived annual PM2.5 concentrations resulted from data restrictions that occurred at noon and data loss in winter were identified as 20% and 30%, respectively. The regional transport of smoke from forest wildfires increased PM2.5 concentration to 150 μg/m3 in the summer 2018. The average PM2.5 concentrations in the urban districts could reach 35 μg/m3, which far exceeded the World Health Organization air quality guideline. These results underscore the good ability of our new method to determine PM2.5 concentrations in regions with limited reference ground-based monitoring. Use of sensor and meteorological observations greatly improved satellite detection of PM2.5 concentration. In addition, our method has the potential for global application to improve determination of PM2.5 concentrations, especially in sparsely monitored regions. © 2020 Elsevier Ltd
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/160853
Appears in Collections:气候变化与战略

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作者单位: Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Hong Kong; Climate Research Division, National Institute of Meteorological Sciences (NIMS), Seogwipo, Jeju-Do 63568, South Korea; Faculty of Engineering, The Chinese University of Hong Kong, Hong Kong; Department of Mathematics, Hong Kong University of Science and Technology, Hong Kong; Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Hong Kong; School of Marine Science, Nanjing University of Information Science and Technology, Nanjing, 210044, China; School of Physics and Astronomy, Earth Observation Science Group, University of Leicester, Leicester, United Kingdom

Recommended Citation:
Lin C.,Labzovskii L.D.,Mak H.W.L.,et al. Observation of PM2.5 using a combination of satellite remote sensing and low-cost sensor network in Siberian urban areas with limited reference monitoring[J]. Atmospheric Environment,2020-01-01,227
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