Papers

10

Total Citations

391

H-Index

8

About

Md. Arfan Ali is a leading environmental remote sensing scientist whose research focuses on aerosol characterization, air quality assessment, and satellite-based atmospheric monitoring. His major contributions span the development of advanced aerosol retrieval algorithms and the classification of aerosol types across diverse geographic regions. Notably, his work on the SEMARA approach—integrating surface reflectance and aerosol retrieval algorithms—enables high-resolution (30 m) aerosol optical depth (AOD) retrieval from Landsat 8, significantly improving urban air quality monitoring. He also pioneered the AEROSA framework, a novel satellite-based method for classifying aerosols into desert dust, biomass burning, clean continental, and maritime types, advancing beyond traditional AOD-Ångström exponent approaches. His most cited paper, “Air pollution scenario over Pakistan” (141 citations), identifies and ranks extremely polluted cities using long-term aerosol and trace gas data. With over 390 total citations, his research has been instrumental in mapping aerosol pollution hotspots in South Asia, the Arabian Peninsula, and China, and in evaluating satellite retrieval uncertainties during the COVID-19 lockdown. His work has direct implications for climate change studies, public health, and environmental policy.

Research Focus

Key Achievements

8
H-Index
10
Papers
391
Total Citations
39
Avg Citations/Paper
🏆 Most Cited Paper
Air pollution scenario over Pakistan: Characterization and ranking of extremely polluted cities using long-term concentrations of aerosols and trace gases
141 citations · 2021
📈 Most Prolific Year: 2021 (3 Papers)
🤝 Key Collaborators: 28
🏛 Institutions: Nanjing University of Information Science and Technology, King Abdulaziz University, Ain Shams University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago