A New Coupling Method for PM<sub>2.5</sub> Concentration Estimation by the Satellite-Based Semiempirical Model and Numerical Model
Aerosol optical and chemical properties play a major role in the retrieval of PM<sub>2.5</sub> concentrations based on aerosol optical depth (AOD) data from satellites in the conventional semiempirical model (SEM). However, limited observation information hinders the high-resolution esti...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-05-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/14/10/2360 |
| _version_ | 1797495990619471872 |
|---|---|
| author | Shuyun Yuan Ying Li Jinhui Gao Fangwen Bao |
| author_facet | Shuyun Yuan Ying Li Jinhui Gao Fangwen Bao |
| author_sort | Shuyun Yuan |
| collection | DOAJ |
| description | Aerosol optical and chemical properties play a major role in the retrieval of PM<sub>2.5</sub> 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<sub>2.5</sub>. Therefore, a new method for evaluating near-surface PM<sub>2.5</sub> 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<sub>2.5</sub> concentrations. Therefore, the two crucial aerosol characteristic parameters, including the coefficient integrated humidity effect (γ′) and the comprehensive reference value of aerosol properties (<i>K</i>) 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<sub>2.5</sub> by CSEN indicated the effect of hygroscopic growth and aerosol properties affected by the meteorology on the relationship between AOD and estimated PM<sub>2.5</sub> 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. |
| first_indexed | 2024-03-10T01:57:19Z |
| format | Article |
| id | doaj.art-de90f3c19bd142c3bd96e6922eb5cffe |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T01:57:19Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-de90f3c19bd142c3bd96e6922eb5cffe2023-11-23T12:54:53ZengMDPI AGRemote Sensing2072-42922022-05-011410236010.3390/rs14102360A New Coupling Method for PM<sub>2.5</sub> Concentration Estimation by the Satellite-Based Semiempirical Model and Numerical ModelShuyun Yuan0Ying Li1Jinhui Gao2Fangwen Bao3School of Environment, Harbin Institute of Technology, Harbin 150059, ChinaCenter for Oceanic and Atmospheric Science at SUSTech (COAST), Department of Ocean Sciences and Engineering, Southern University of Science and Technology, Shenzhen 518055, ChinaPlateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu 610225, ChinaCenter for Oceanic and Atmospheric Science at SUSTech (COAST), Department of Ocean Sciences and Engineering, Southern University of Science and Technology, Shenzhen 518055, ChinaAerosol optical and chemical properties play a major role in the retrieval of PM<sub>2.5</sub> 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<sub>2.5</sub>. Therefore, a new method for evaluating near-surface PM<sub>2.5</sub> 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<sub>2.5</sub> concentrations. Therefore, the two crucial aerosol characteristic parameters, including the coefficient integrated humidity effect (γ′) and the comprehensive reference value of aerosol properties (<i>K</i>) 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<sub>2.5</sub> by CSEN indicated the effect of hygroscopic growth and aerosol properties affected by the meteorology on the relationship between AOD and estimated PM<sub>2.5</sub> 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.https://www.mdpi.com/2072-4292/14/10/2360PM<sub>2.5</sub>WRF-Chemhygroscopicitycoupling methodCSEN model |
| spellingShingle | Shuyun Yuan Ying Li Jinhui Gao Fangwen Bao A New Coupling Method for PM<sub>2.5</sub> Concentration Estimation by the Satellite-Based Semiempirical Model and Numerical Model Remote Sensing PM<sub>2.5</sub> WRF-Chem hygroscopicity coupling method CSEN model |
| title | A New Coupling Method for PM<sub>2.5</sub> Concentration Estimation by the Satellite-Based Semiempirical Model and Numerical Model |
| title_full | A New Coupling Method for PM<sub>2.5</sub> Concentration Estimation by the Satellite-Based Semiempirical Model and Numerical Model |
| title_fullStr | A New Coupling Method for PM<sub>2.5</sub> Concentration Estimation by the Satellite-Based Semiempirical Model and Numerical Model |
| title_full_unstemmed | A New Coupling Method for PM<sub>2.5</sub> Concentration Estimation by the Satellite-Based Semiempirical Model and Numerical Model |
| title_short | A New Coupling Method for PM<sub>2.5</sub> Concentration Estimation by the Satellite-Based Semiempirical Model and Numerical Model |
| title_sort | new coupling method for pm sub 2 5 sub concentration estimation by the satellite based semiempirical model and numerical model |
| topic | PM<sub>2.5</sub> WRF-Chem hygroscopicity coupling method CSEN model |
| url | https://www.mdpi.com/2072-4292/14/10/2360 |
| work_keys_str_mv | AT shuyunyuan anewcouplingmethodforpmsub25subconcentrationestimationbythesatellitebasedsemiempiricalmodelandnumericalmodel AT yingli anewcouplingmethodforpmsub25subconcentrationestimationbythesatellitebasedsemiempiricalmodelandnumericalmodel AT jinhuigao anewcouplingmethodforpmsub25subconcentrationestimationbythesatellitebasedsemiempiricalmodelandnumericalmodel AT fangwenbao anewcouplingmethodforpmsub25subconcentrationestimationbythesatellitebasedsemiempiricalmodelandnumericalmodel AT shuyunyuan newcouplingmethodforpmsub25subconcentrationestimationbythesatellitebasedsemiempiricalmodelandnumericalmodel AT yingli newcouplingmethodforpmsub25subconcentrationestimationbythesatellitebasedsemiempiricalmodelandnumericalmodel AT jinhuigao newcouplingmethodforpmsub25subconcentrationestimationbythesatellitebasedsemiempiricalmodelandnumericalmodel AT fangwenbao newcouplingmethodforpmsub25subconcentrationestimationbythesatellitebasedsemiempiricalmodelandnumericalmodel |