Publications

You can also find my articles on my Google Scholar profile.

Journal Articles

It’s getting hot in here: Spatial impact of humidity on heat wave severity in the United States

Published in Science of the Total Environment, 2025

This study introduces an enhancement to the existing Heat Severity and Coverage Index that incorporates humidity to provide a more robust assessment of heat wave severity.

Recommended citation: Narayanan, A., Rezaali, M., Bunting, E., & Keellings, D. (2025). It's getting hot in here: Spatial impact of humidity on heat wave severity in the United States. Science of the Total Environment, 963, 178397.
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Assessment of AERMOD and ADMS for NOx dispersion modeling with a combination of line and point sources

Published in Environmental Science and Pollution Research, 2025

Investigation of two popular Gaussian pollution dispersion models for analyzing their behavior under specific conditions with point and line sources.

Recommended citation: Rezaali, M., Fouladi-Fard, R., O'Shaughnessy, P., & Karimi, A. (2025). Assessment of AERMOD and ADMS for NOx dispersion modeling with a combination of line and point sources. Environmental Science and Pollution Research.

Human and ecological risk assessment, geo-accumulation, and source apportionment of road dust heavy metals in a semi-arid region of central Iran

Published in International Journal of Environmental Analytical Chemistry, 2024

Assessment of heavy metal concentrations, spatial distribution patterns, and ecological and health risks from road dust samples in Qom, Iran.

Recommended citation: Rezaali, M., et al. (2024). Human and ecological risk assessment, geo-accumulation, and source apportionment of road dust heavy metals in a semi-arid region of central Iran. International Journal of Environmental Analytical Chemistry, 104(18), 6495-6518.
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An ensemble deep learning approach to spatiotemporal tropospheric ozone forecasting: A case study of Tehran, Iran

Published in Urban Climate, 2024

This study proposes a novel framework for spatiotemporal forecasting of ground-level ozone concentration using advanced machine learning techniques.

Recommended citation: Rezaali, M., Jahangir, M. S., Fouladi-Fard, R., & Keellings, D. (2024). An ensemble deep learning approach to spatiotemporal tropospheric ozone forecasting: A case study of Tehran, Iran. Urban Climate, 55, 101950.
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