Ambient Atmospheric Aerosol Extinction Coefficient Reconstruction from PM2.5 Mass Concentrations and Application to Haze Identification in China
Abstract This study developed a method of reconstructing the aerosol extinction coefficient based on hourly observations of the fine-particle (PM2.5) mass concentration, relative humidity (RH), and visibility at 9 stations in China between 2014 and 2015. First, we applied κ-Kӧhler theory to evaluate...
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| Format: | Article |
| Language: | English |
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Springer
2021-02-01
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| Series: | Aerosol and Air Quality Research |
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| Online Access: | https://doi.org/10.4209/aaqr.200386 |
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| author | Lina Gao Peng Yan Jietai Mao Xiaochun Zhang Xiaoling Zhang Yongxue Wu Junshan Jing Jianming Xu Xuejiao Deng Wenxue Chi |
| author_facet | Lina Gao Peng Yan Jietai Mao Xiaochun Zhang Xiaoling Zhang Yongxue Wu Junshan Jing Jianming Xu Xuejiao Deng Wenxue Chi |
| author_sort | Lina Gao |
| collection | DOAJ |
| description | Abstract This study developed a method of reconstructing the aerosol extinction coefficient based on hourly observations of the fine-particle (PM2.5) mass concentration, relative humidity (RH), and visibility at 9 stations in China between 2014 and 2015. First, we applied κ-Kӧhler theory to evaluate the number concentration distribution of the fine particles under ambient conditions from the PM2.5 mass and then used Mie theory to calculate the aerosol extinction coefficient. Second, we established the reconstruction model and identified reference values for the relevant parameters. After sensitivity tests confirmed good agreement between the extinction coefficients obtained through combinations of various values and those resulting from the reference values, linear regression was employed to reduce the discrepancy between the reconstructed and the observed coefficients. A closure study enabled us to determine the threshold of the extinction ratio (β/βObs) and identify haze and fog weather phenomena at the stations. Finally, we assessed the bias in the predicted number of hours with haze for 61 stations in China by comparing the estimates derived from different values for the model’s parameters with those derived from the reference values and found a relative bias of less than 15% for approximately 99.8% of the stations, indicating the feasibility of our approach for detecting haze. |
| format | Article |
| id | doaj-art-366ff854424747bf9cac11dc9787545c |
| institution | Kabale University |
| issn | 1680-8584 2071-1409 |
| language | English |
| publishDate | 2021-02-01 |
| publisher | Springer |
| record_format | Article |
| series | Aerosol and Air Quality Research |
| spelling | doaj-art-366ff854424747bf9cac11dc9787545c2025-02-09T12:19:42ZengSpringerAerosol and Air Quality Research1680-85842071-14092021-02-0121611810.4209/aaqr.200386Ambient Atmospheric Aerosol Extinction Coefficient Reconstruction from PM2.5 Mass Concentrations and Application to Haze Identification in ChinaLina Gao0Peng Yan1Jietai Mao2Xiaochun Zhang3Xiaoling Zhang4Yongxue Wu5Junshan Jing6Jianming Xu7Xuejiao Deng8Wenxue Chi9Meteorological Observation Center, China Meteorological AdministrationMeteorological Observation Center, China Meteorological AdministrationSchool of Physics, Peking UniversityMeteorological Observation Center, China Meteorological AdministrationBeijing Meteorological ServiceBeijing Meteorological ServiceMeteorological Observation Center, China Meteorological AdministrationYangtze River Delta Center for Environmental Meteorology Prediction and WarningInstitute of Tropical and Marine Meteorology, China Meteorological AdministrationMeteorological Observation Center, China Meteorological AdministrationAbstract This study developed a method of reconstructing the aerosol extinction coefficient based on hourly observations of the fine-particle (PM2.5) mass concentration, relative humidity (RH), and visibility at 9 stations in China between 2014 and 2015. First, we applied κ-Kӧhler theory to evaluate the number concentration distribution of the fine particles under ambient conditions from the PM2.5 mass and then used Mie theory to calculate the aerosol extinction coefficient. Second, we established the reconstruction model and identified reference values for the relevant parameters. After sensitivity tests confirmed good agreement between the extinction coefficients obtained through combinations of various values and those resulting from the reference values, linear regression was employed to reduce the discrepancy between the reconstructed and the observed coefficients. A closure study enabled us to determine the threshold of the extinction ratio (β/βObs) and identify haze and fog weather phenomena at the stations. Finally, we assessed the bias in the predicted number of hours with haze for 61 stations in China by comparing the estimates derived from different values for the model’s parameters with those derived from the reference values and found a relative bias of less than 15% for approximately 99.8% of the stations, indicating the feasibility of our approach for detecting haze.https://doi.org/10.4209/aaqr.200386Aerosol extinction reconstructionHaze and fogIdentification |
| spellingShingle | Lina Gao Peng Yan Jietai Mao Xiaochun Zhang Xiaoling Zhang Yongxue Wu Junshan Jing Jianming Xu Xuejiao Deng Wenxue Chi Ambient Atmospheric Aerosol Extinction Coefficient Reconstruction from PM2.5 Mass Concentrations and Application to Haze Identification in China Aerosol and Air Quality Research Aerosol extinction reconstruction Haze and fog Identification |
| title | Ambient Atmospheric Aerosol Extinction Coefficient Reconstruction from PM2.5 Mass Concentrations and Application to Haze Identification in China |
| title_full | Ambient Atmospheric Aerosol Extinction Coefficient Reconstruction from PM2.5 Mass Concentrations and Application to Haze Identification in China |
| title_fullStr | Ambient Atmospheric Aerosol Extinction Coefficient Reconstruction from PM2.5 Mass Concentrations and Application to Haze Identification in China |
| title_full_unstemmed | Ambient Atmospheric Aerosol Extinction Coefficient Reconstruction from PM2.5 Mass Concentrations and Application to Haze Identification in China |
| title_short | Ambient Atmospheric Aerosol Extinction Coefficient Reconstruction from PM2.5 Mass Concentrations and Application to Haze Identification in China |
| title_sort | ambient atmospheric aerosol extinction coefficient reconstruction from pm2 5 mass concentrations and application to haze identification in china |
| topic | Aerosol extinction reconstruction Haze and fog Identification |
| url | https://doi.org/10.4209/aaqr.200386 |
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