Development and Analysis of a High-Resolution Aerosol Optical Depth Dataset for Long-Term Atmospheric Study over India -2000-2024

The research focuses on the advancement of a high-resolution Aerosol Optical Depth dataset for India, from 2000 to 2024, to strengthen the understanding of aerosol dynamics and their impact on air quality, public health, and climate change. The data from MERRA-2 and MODIS are included in the study and it includes the main research metrics of aerosol such as total extinction aerosol optical depth, black carbon column mass density , and black carbon Angstrom exponent. In addition to this other meteorological variables like surface pressure, temperature at 2 meters, and specific humidity are considered. The downloaded data is preprocessed by using techniques such as data normalization, outlier removal, and gap-filling, to ensure the reliability of datasets. Machine learning algorithms, including k-means clustering and PCA, are used in classifying aerosols and analyzing their interactions with meteorological conditions. The dataset provides critical spatial and temporal insights into aerosols over India, thereby supporting climate modeling and evidence-based policymaking against air pollution and its adverse impacts. This validated and accessible dataset contributes significantly to atmospheric science and long-term environmental research.