Estimation of Surface Particulate Matter (PM2.5 and PM10) Mass Concentrations from Ceilometer Backscattered Profiles
Abstract In this study, we used remotely sensed backscattered profiles from a ceilometer to characterize the vertical and horizontal mixing of aerosols in the polluted planetary boundary layer (PBL). These profiles revealed the structure of the boundary layer, which included the mixed layer, the noc...
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| Format: | Article |
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Springer
2020-04-01
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| Series: | Aerosol and Air Quality Research |
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| Online Access: | https://doi.org/10.4209/aaqr.2019.08.0371 |
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| author | Avinash N. Parde Sachin D. Ghude Prakash Pithani Narendra G. Dhangar Sandip Nivdange Gopal Krishna D. M. Lal R. Jenamani Pankaj Singh Chinmay Jena Ramakrishna Karumuri P. D. Safai D. M. Chate |
| author_facet | Avinash N. Parde Sachin D. Ghude Prakash Pithani Narendra G. Dhangar Sandip Nivdange Gopal Krishna D. M. Lal R. Jenamani Pankaj Singh Chinmay Jena Ramakrishna Karumuri P. D. Safai D. M. Chate |
| author_sort | Avinash N. Parde |
| collection | DOAJ |
| description | Abstract In this study, we used remotely sensed backscattered profiles from a ceilometer to characterize the vertical and horizontal mixing of aerosols in the polluted planetary boundary layer (PBL). These profiles revealed the structure of the boundary layer, which included the mixed layer, the nocturnal residual layer and the elevated aerosol layer far above the mixed layer over Delhi. The accumulation of aerosols near the surface during feeble turbulence and the mixing of aerosols from the residual layer into the surface layer during convection was captured very well by a ceilometer. The backscattered signal from a height of 45 m above the ground was strongly correlated (82%) with the observed surface PM2.5 and PM10 mass concentrations. We developed an empirical regression model based on this relationship, which was then tested and validated against independent measurements of the concentrations from November 2018. Although local meteorological conditions, particularly cloudiness and rain, influenced the strength of the correlation between the observed PM2.5 and PM10 mass concentrations and the backscattered signal, the magnitude of the mean bias between the observed and the values for PM2.5 (−21 µg m−3, RMSE = 75) and PM10 (31 µg m−3, RMSE = 118) indicated that the predicted values were fairly accurate. The model overestimated the PM2.5 by 7% and underestimated the PM10 by 6% on clear days. |
| format | Article |
| id | doaj-art-6207c567eb0e436c810bebc6c398c90f |
| institution | DOAJ |
| issn | 1680-8584 2071-1409 |
| language | English |
| publishDate | 2020-04-01 |
| publisher | Springer |
| record_format | Article |
| series | Aerosol and Air Quality Research |
| spelling | doaj-art-6207c567eb0e436c810bebc6c398c90f2025-08-20T03:10:47ZengSpringerAerosol and Air Quality Research1680-85842071-14092020-04-012071640165010.4209/aaqr.2019.08.0371Estimation of Surface Particulate Matter (PM2.5 and PM10) Mass Concentrations from Ceilometer Backscattered ProfilesAvinash N. Parde0Sachin D. Ghude1Prakash Pithani2Narendra G. Dhangar3Sandip Nivdange4Gopal Krishna5D. M. Lal6R. Jenamani7Pankaj Singh8Chinmay Jena9Ramakrishna Karumuri10P. D. Safai11D. M. Chate12Department of Atmospheric and Space Sciences, Savitribai Phule Pune UniversityIndian Institute of Tropical MeteorologyIndian Institute of Tropical MeteorologyIndian Institute of Tropical MeteorologyDepartment of Environmental Science, Savitribai Phule Pune UniversityIndian Institute of Tropical MeteorologyIndian Institute of Tropical MeteorologyIndia Meteorological DepartmentDepartment of Physics, Deshbandhu College, University of DelhiIndian Institute of Tropical MeteorologyIndian Institute of Tropical MeteorologyIndian Institute of Tropical MeteorologyIndian Institute of Tropical MeteorologyAbstract In this study, we used remotely sensed backscattered profiles from a ceilometer to characterize the vertical and horizontal mixing of aerosols in the polluted planetary boundary layer (PBL). These profiles revealed the structure of the boundary layer, which included the mixed layer, the nocturnal residual layer and the elevated aerosol layer far above the mixed layer over Delhi. The accumulation of aerosols near the surface during feeble turbulence and the mixing of aerosols from the residual layer into the surface layer during convection was captured very well by a ceilometer. The backscattered signal from a height of 45 m above the ground was strongly correlated (82%) with the observed surface PM2.5 and PM10 mass concentrations. We developed an empirical regression model based on this relationship, which was then tested and validated against independent measurements of the concentrations from November 2018. Although local meteorological conditions, particularly cloudiness and rain, influenced the strength of the correlation between the observed PM2.5 and PM10 mass concentrations and the backscattered signal, the magnitude of the mean bias between the observed and the values for PM2.5 (−21 µg m−3, RMSE = 75) and PM10 (31 µg m−3, RMSE = 118) indicated that the predicted values were fairly accurate. The model overestimated the PM2.5 by 7% and underestimated the PM10 by 6% on clear days.https://doi.org/10.4209/aaqr.2019.08.0371Pollution eventPM2.5 and PM10Ceilometer backscatter |
| spellingShingle | Avinash N. Parde Sachin D. Ghude Prakash Pithani Narendra G. Dhangar Sandip Nivdange Gopal Krishna D. M. Lal R. Jenamani Pankaj Singh Chinmay Jena Ramakrishna Karumuri P. D. Safai D. M. Chate Estimation of Surface Particulate Matter (PM2.5 and PM10) Mass Concentrations from Ceilometer Backscattered Profiles Aerosol and Air Quality Research Pollution event PM2.5 and PM10 Ceilometer backscatter |
| title | Estimation of Surface Particulate Matter (PM2.5 and PM10) Mass Concentrations from Ceilometer Backscattered Profiles |
| title_full | Estimation of Surface Particulate Matter (PM2.5 and PM10) Mass Concentrations from Ceilometer Backscattered Profiles |
| title_fullStr | Estimation of Surface Particulate Matter (PM2.5 and PM10) Mass Concentrations from Ceilometer Backscattered Profiles |
| title_full_unstemmed | Estimation of Surface Particulate Matter (PM2.5 and PM10) Mass Concentrations from Ceilometer Backscattered Profiles |
| title_short | Estimation of Surface Particulate Matter (PM2.5 and PM10) Mass Concentrations from Ceilometer Backscattered Profiles |
| title_sort | estimation of surface particulate matter pm2 5 and pm10 mass concentrations from ceilometer backscattered profiles |
| topic | Pollution event PM2.5 and PM10 Ceilometer backscatter |
| url | https://doi.org/10.4209/aaqr.2019.08.0371 |
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