Tropospheric aerosol optical depth (AOD) over India was simulated by Goddard Earth Observing System (GEOS)-Chem, a global 3-D chemical-transport model, using SMOG (Speciated Multi-pOllutant Generator from Indian Institute of Technology Bombay) and GEOS-Chem (GC) (current inventories used in the GEOS-Chem model) inventories for 2012. The simulated AODs were ~80% (SMOG) and 60% (GC) of those measured by the satellites (Moderate Resolution Imaging Spectroradiometer and Multi-angle Imaging SpectroRadiometer). There is no strong seasonal variation in AOD over India. The peak AOD values are observed/simulated during summer. The simulated AOD using SMOG inventory has particulate black and organic carbon AOD higher by a factor ~5 and 3, respectively, compared to GC inventory. The model underpredicted coarse-mode AOD but agreed for fine-mode AOD with Aerosol Robotic Network data. It captured dust only over Western India, which is a desert, and not elsewhere, probably due to inaccurate dust transport and/or noninclusion of other dust sources. The calculated AOD, after dust correction, showed the general features in its observed spatial variation. Highest AOD values were observed over the Indo-Gangetic Plain followed by Central and Southern India with lowest values in Northern India. Transport of aerosols from Indo-Gangetic Plain and Central India into Eastern India, where emissions are low, is significant. The major contributors to total AOD over India are inorganic aerosol (41-64%), organic carbon (14-26%), and dust (7-32%). AOD over most regions of India is a factor of 5 or higher than over the United States.
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http://dx.doi.org/10.1002/2017JD027719 | DOI Listing |
Environ Sci Pollut Res Int
December 2024
Space Applications Centre, Indian Space Research Organization (ISRO), Ahmedabad, India.
In the present work, it is the first time an interpretable machine learning model has been developed for the estimation of Particulate Matter 10 µm (PM) concentrations over India using Aerosol Optical Depth (AOD) from two different satellites, i.e. INSAT-3D and Moderate Resolution Imaging Spectroradiometer (MODIS) for the period of 7 years (2014 to 2020).
View Article and Find Full Text PDFEnviron Monit Assess
November 2024
Department of Civil Engineering, National Aerosol FacilityIndian Institute of TechnologyUttar Pradesh, Kanpur, 208016, India.
Environ Pollut
December 2024
Center for Water and Atmospheric Research, Kathmandu Institute of Applied Sciences (KIAS), Bagdol, Lalitpur, Nepal. Electronic address:
Forest fires have become more intense and frequent in recently changing climates. The wide variety of pollutants released by forest fire include greenhouse gases, photochemically reactive compounds, and fine and coarse particulate matter. This study investigated the impact of forest fire events on air quality in the Kathmandu Valley during March-April 2021 using ground air quality monitoring stations and satellite data.
View Article and Find Full Text PDFIndian J Ophthalmol
February 2025
Department of Paediatric Ophthalmology and Squint Services, Aravind Eye Hospital and Post Graduate Institute of Ophthalmology, Tirunelveli, Tamil Nadu, India.
J Hazard Mater
November 2024
State Key Laboratory of Environmental Criteria and Risk Assessment, National Engineering Laboratory for Lake Pollution Control and Ecological Restoration, State Environmental Protection Key Laboratory for Lake Pollution Control, Chinese Research Academy of Environmental Science, Beijing, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China. Electronic address:
China and India are two of the fastest-growing developing economies covering about 35 % of the world's population. Due to the extensive prevalence of air pollution across cities in China and India, contemporary assessment of atmospheric pollution through real-time and remote sensing observations is inadequate. The study aims to determine the spatial distribution and temporal variation of hazardous atmospheric pollutants across cities in China (Shanghai, Nanjing, Jinan, Zhengzhou and Beijing) and India (Kolkata, Asansol, Patna, Kanpur and Delhi).
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