Journal
ATMOSPHERIC ENVIRONMENT
Volume 227, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.atmosenv.2020.117410
Keywords
Satellite; PM2.5; Low-cost sensor; Siberia; Air quality
Funding
- Science and Technology Plan Project of Guangdong Province of China [2017A050506003]
- Research Grants Council of Hong Kong Government [T24/504/17]
- NSFC/RGC [N_HKUST638/19]
- Fok Ying Tung Graduate School [NRC06/07.SC01]
- Natural Environment Research Council of the UK [NE/N005406/1]
- Korean Meteorological Administration Research and the Development Program Development and Assessment of IPCC AR6 Climate Change Scenario [1365003000]
- NERC [NE/N005406/1] Funding Source: UKRI
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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 mu g/m(3) in the summer 2018. The average PM2.5 concentrations in the urban districts could reach 35 mu g/m(3), 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.
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