Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Relational Study of PM2.5 Surface Concentration with MODIS Level 3 AOD Data Over India
https://orcid.org/http://orcid.org/0000-0002-5327-2697
PM2.5, a principal constituent of particulate matter, is the most deadly form of air pollution attributing to significant number of health problems. For a country like India with a vast topographical distribution, the existing number of ground-based stations for monitoring of pollutant concentration is inadequate. With the advent of technology, remote sensing-based monitors have been able to capture the pollutant concentrations of any region. Using a combined Dark Target and Deep Blue (DTB) Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Level 3 aerosol optical depth (AOD) product and surface PM2.5 measurements from Central Pollution Control Board (CPCB) monitors, we provide a decade (2010–2020) of assessment of AOD–PM2.5 relationships all over India by graphical analysis and simple linear regression analysis. This study analyse the factors which can affect the relationship observed between the two datasets over various regions and at different times. Region-wise, state-wise and season-wise analyses for correlation were carried out. In addition, analyses were also carried out based on pollutant concentration levels and for 2020 lockdown period. Regardless of the classification, the two datasets were found to have a high correlation to one another. In general, Northern regions tend to show higher correlations, however the relation was found to be independent of concentration of pollutants. Post-monsoon and winter season showed comparatively higher correlation. The regression analysis for a general equation all over India yielded a linear equation with R2 = 0.92 and a root mean square error of 26.84 µg/m3. Overall, our evaluation shows that MODIS Level 3 data estimates of PM2.5 on an annual time scale using simple linear models are reliable.
Relational Study of PM2.5 Surface Concentration with MODIS Level 3 AOD Data Over India
https://orcid.org/http://orcid.org/0000-0002-5327-2697
PM2.5, a principal constituent of particulate matter, is the most deadly form of air pollution attributing to significant number of health problems. For a country like India with a vast topographical distribution, the existing number of ground-based stations for monitoring of pollutant concentration is inadequate. With the advent of technology, remote sensing-based monitors have been able to capture the pollutant concentrations of any region. Using a combined Dark Target and Deep Blue (DTB) Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Level 3 aerosol optical depth (AOD) product and surface PM2.5 measurements from Central Pollution Control Board (CPCB) monitors, we provide a decade (2010–2020) of assessment of AOD–PM2.5 relationships all over India by graphical analysis and simple linear regression analysis. This study analyse the factors which can affect the relationship observed between the two datasets over various regions and at different times. Region-wise, state-wise and season-wise analyses for correlation were carried out. In addition, analyses were also carried out based on pollutant concentration levels and for 2020 lockdown period. Regardless of the classification, the two datasets were found to have a high correlation to one another. In general, Northern regions tend to show higher correlations, however the relation was found to be independent of concentration of pollutants. Post-monsoon and winter season showed comparatively higher correlation. The regression analysis for a general equation all over India yielded a linear equation with R2 = 0.92 and a root mean square error of 26.84 µg/m3. Overall, our evaluation shows that MODIS Level 3 data estimates of PM2.5 on an annual time scale using simple linear models are reliable.
Relational Study of PM2.5 Surface Concentration with MODIS Level 3 AOD Data Over India
https://orcid.org/http://orcid.org/0000-0002-5327-2697
PM2.5, a principal constituent of particulate matter, is the most deadly form of air pollution attributing to significant number of health problems. For a country like India with a vast topographical distribution, the existing number of ground-based stations for monitoring of pollutant concentration is inadequate. With the advent of technology, remote sensing-based monitors have been able to capture the pollutant concentrations of any region. Using a combined Dark Target and Deep Blue (DTB) Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Level 3 aerosol optical depth (AOD) product and surface PM2.5 measurements from Central Pollution Control Board (CPCB) monitors, we provide a decade (2010–2020) of assessment of AOD–PM2.5 relationships all over India by graphical analysis and simple linear regression analysis. This study analyse the factors which can affect the relationship observed between the two datasets over various regions and at different times. Region-wise, state-wise and season-wise analyses for correlation were carried out. In addition, analyses were also carried out based on pollutant concentration levels and for 2020 lockdown period. Regardless of the classification, the two datasets were found to have a high correlation to one another. In general, Northern regions tend to show higher correlations, however the relation was found to be independent of concentration of pollutants. Post-monsoon and winter season showed comparatively higher correlation. The regression analysis for a general equation all over India yielded a linear equation with R2 = 0.92 and a root mean square error of 26.84 µg/m3. Overall, our evaluation shows that MODIS Level 3 data estimates of PM2.5 on an annual time scale using simple linear models are reliable.
Relational Study of PM2.5 Surface Concentration with MODIS Level 3 AOD Data Over India
Lecture Notes in Civil Engineering
Nandagiri, Lakshman (Herausgeber:in) / Narasimhan, M. C. (Herausgeber:in) / Marathe, Shriram (Herausgeber:in) / Scaria, Haritha P. (Autor:in) / Avanthika, Premkumar (Autor:in) / Jose, Anna Mary (Autor:in) / Alisa, J. S. (Autor:in) / Sadasivan, Anagha (Autor:in) / Varghese, George K. (Autor:in)
International Conference on Civil Engineering Trends and Challenges for Sustainability ; 2021
27.06.2022
15 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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