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Observation of PM2.5 using a combination of satellite remote sensing and low-cost sensor network in Siberian urban areas with limited reference monitoring

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posted on 2020-04-06, 08:08 authored by Changqing Lin, Lev D Labzovskii, Hugo Wai Leung Mak, Jimmy C H Fung, Alexis K H Lau, Samuel T Kenea, Muhhamad Bilal, Josh D Vande Hey, Xingcheng Lu, Jun Ma
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.

History

Citation

Atmospheric Environment Volume 227, 15 April 2020, 117410

Author affiliation

School of Physics and Astronomy, Earth Observation Science Group

Version

  • AM (Accepted Manuscript)

Published in

Atmospheric Environment

Volume

227

Pagination

117410 - 117410

Publisher

Elsevier BV

issn

1352-2310

eissn

1873-2844

Acceptance date

2020-03-12

Copyright date

2020

Available date

2021-03-16

Publisher version

https://www.sciencedirect.com/science/article/pii/S1352231020301497

Language

en

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