A New Coupling Method for PM2.5 Concentration Estimation by the Satellite-Based Semiempirical Model and Numerical Model

Yuan，Shuyun1,2; Li，Ying2,3; Gao，Jinhui4; Bao，Fangwen2

2022-05-01

10.3390/rs14102360

Remote Sensing   影响因子和分区

2072-4292

Aerosol optical and chemical properties play a major role in the retrieval of PM concentrations based on aerosol optical depth (AOD) data from satellites in the conventional semiempirical model (SEM). However, limited observation information hinders the high-resolution estimation of PM . Therefore, a new method for evaluating near-surface PM at high spatial resolution is developed by coupling the SEM and the chemical transport model (CTM)-based numerical (CSEN) model. The numerical model can provide large-scale information for aerosol properties with high spatial resolution at a large scale based on emissions and meteorology, though it can still be biased in simulating absolute PM concentrations. Therefore, the two crucial aerosol characteristic parameters, including the coefficient integrated humidity effect (γ) and the comprehensive reference value of aerosol properties (K) in SEM, have been redefined using the WRF-Chem numerical model. Improved model performance was observed for these results compared with the original SEM results. The monthly averaged correlation coefficients (R) by CSEN were 0.92, 0.82, 0.84, and 0.83 in January, April, July, and October, respectively, whereas those of the SEM were 0.80, 0.77, 0.72, and 0.72, respectively. All the statistical metrics of the model validation showed significant improvements in all seasons. The reduced biases of estimated PM by CSEN indicated the effect of hygroscopic growth and aerosol properties affected by the meteorology on the relationship between AOD and estimated PM concentrations, especially in winter and summer. The better performance of the CSEN model provides insight for air quality monitoring at different scales, which supplies important information for air pollution control policies and health impact analysis.

coupling method CSEN model hygroscopicity PM2.5 WRF-Chem

SCI ; EI

英语

通讯

National Natural Science Foundation of China[41575106];National Natural Science Foundation of China[41961160728];National Natural Science Foundation of China[42105124];National Natural Science Foundation of China[42105124];

Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology

Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology

WOS:000803447800001

MDPI

20222112159851

Aerosols ; Air quality ; Atmospheric movements ; Image resolution ; Meteorology ; Numerical methods ; Quality control

Atmospheric Properties:443.1 ; Air Pollution Control:451.2 ; Quality Assurance and Control:913.3 ; Mathematics:921 ; Numerical Methods:921.6

2-s2.0-85130569377

Scopus

1.School of Environment,Harbin Institute of Technology,Harbin,150059,China
2.Center for Oceanic and Atmospheric Science at SUSTech (COAST),Department of Ocean Sciences and Engineering,Southern University of Science and Technology,Shenzhen,518055,China
3.Southern Marine Science and Engineering Guangdong Laboratory,Guangzhou,510000,China
4.Plateau Atmosphere and Environment Key Laboratory of Sichuan Province,School of Atmospheric Sciences,Chengdu University of Information Technology,Chengdu,610225,China

Yuan，Shuyun,Li，Ying,Gao，Jinhui,et al. A New Coupling Method for PM2.5 Concentration Estimation by the Satellite-Based Semiempirical Model and Numerical Model[J]. Remote Sensing,2022,14(10).

Yuan，Shuyun,Li，Ying,Gao，Jinhui,&Bao，Fangwen.(2022).A New Coupling Method for PM2.5 Concentration Estimation by the Satellite-Based Semiempirical Model and Numerical Model.Remote Sensing,14(10).

Yuan，Shuyun,et al."A New Coupling Method for PM2.5 Concentration Estimation by the Satellite-Based Semiempirical Model and Numerical Model".Remote Sensing 14.10(2022).