{"title":"Long-term variation in aerosol optical depth and normalized difference vegetation index in Jaipur, India","authors":"Ruchi Dangayach, Ronak Jain , Ashutosh Kumar Pandey","doi":"10.1016/j.totert.2023.100027","DOIUrl":null,"url":null,"abstract":"<div><p>Aerosol particles are a significant source of air pollution, particularly in developing countries. Urbanization, commercialization, and overpopulation are all key contributors to rising air pollution levels. The goal of this research is to examine long-term variations in Aerosol Optical Depth (AOD), vegetation, built-up, and their relationship in Jaipur, India using remote sensing and GIS techniques. For the present study, Multi-Angle Implementation of Atmospheric Correction (MAIAC), a combined Aqua and Terra MODIS product from 2000 to 2020 was obtained from Google Earth Engine (GEE). Results revealed the minimum and maximum AOD during the rainy and winter season respectively. Correlation analysis revealed that NO<sub>2</sub>, PM<sub>2.5</sub>, and PM<sub>10</sub> moderately correlated to AOD. Significant increase of more than 100 % during the winters was observed from 2000 to 2020, thus it becomes important to reduce the concentration of pollutants. Population growth has led to land consumption at a faster rate and therefore Land-use and Land-cover (LULC) changing patterns must be understood for efficient environmental management. Utilizing multispectral satellite images offers a thorough understanding of changes in the area. The Landsat series’ multitemporal satellite imagery (Landsat – 7 ETM+ and Landsat – 8 OLI) was used to map decadal LULC variations from 2000 to 2020. The overall accuracy of LULC classified maps is ranging from 78 % to 84 %, with a kappa coefficient from 0.72 to 0.80. Results showed that built-up land increased from 22.80 % to 44.2 %. A significant decline was observed for agricultural land (47.20 % to 25.5 %) in the last 20 years. The LULC change patterns for the years 2000, 2010, and 2020 varied significantly. For environmental sustainability, the LULC change should be continuously monitored in the future, thus it becomes important to monitor the changes and take steps to reduce the upsurge in air pollution for strategic planning, management, and informed decision-making.</p></div>","PeriodicalId":101255,"journal":{"name":"Total Environment Research Themes","volume":"5 ","pages":"Article 100027"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Total Environment Research Themes","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772809923000047","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Aerosol particles are a significant source of air pollution, particularly in developing countries. Urbanization, commercialization, and overpopulation are all key contributors to rising air pollution levels. The goal of this research is to examine long-term variations in Aerosol Optical Depth (AOD), vegetation, built-up, and their relationship in Jaipur, India using remote sensing and GIS techniques. For the present study, Multi-Angle Implementation of Atmospheric Correction (MAIAC), a combined Aqua and Terra MODIS product from 2000 to 2020 was obtained from Google Earth Engine (GEE). Results revealed the minimum and maximum AOD during the rainy and winter season respectively. Correlation analysis revealed that NO2, PM2.5, and PM10 moderately correlated to AOD. Significant increase of more than 100 % during the winters was observed from 2000 to 2020, thus it becomes important to reduce the concentration of pollutants. Population growth has led to land consumption at a faster rate and therefore Land-use and Land-cover (LULC) changing patterns must be understood for efficient environmental management. Utilizing multispectral satellite images offers a thorough understanding of changes in the area. The Landsat series’ multitemporal satellite imagery (Landsat – 7 ETM+ and Landsat – 8 OLI) was used to map decadal LULC variations from 2000 to 2020. The overall accuracy of LULC classified maps is ranging from 78 % to 84 %, with a kappa coefficient from 0.72 to 0.80. Results showed that built-up land increased from 22.80 % to 44.2 %. A significant decline was observed for agricultural land (47.20 % to 25.5 %) in the last 20 years. The LULC change patterns for the years 2000, 2010, and 2020 varied significantly. For environmental sustainability, the LULC change should be continuously monitored in the future, thus it becomes important to monitor the changes and take steps to reduce the upsurge in air pollution for strategic planning, management, and informed decision-making.