Meteorologically normalized spatial and temporal variations investigation using a machine learning-random forest model in criteria pollutants across Tehran, Iran-Reference-Cited by-同舟云学术

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Meteorologically normalized spatial and temporal variations investigation using a machine learning-random forest model in criteria pollutants across Tehran, Iran

Published:2024-01 Issue: Volume:53 Page:101790
ISSN:2212-0955
Container-title:Urban Climate
language:en
Short-container-title:Urban Climate

Author:

Ali-Taleshi Mohammad Saleh,Riyahi Bakhtiari Alireza,K. Hopke Philip

Funder

Iran Science Elites Federation

Iran's National Elites Foundation

Publisher

Elsevier BV

Subject

Atmospheric Science,Urban Studies,Environmental Science (miscellaneous),Geography, Planning and Development

Reference80 articles.

1. Road dusts-bound elements in a major metropolitan area, Tehran (Iran): source tracking, pollution characteristics, ecological risks, spatiotemporal and geochemical patterns;Ali-Taleshi;Urban Clim.,2021

2. A one-year monitoring of spatiotemporal variations of PM2.5-bound PAHs in Tehran, Iran: source apportionment, local and regional sources origins and source-specific cancer risk assessment;Ali-Taleshi;Environ. Pollut.,2021

3. Using a hybrid approach to apportion potential source locations contributing to excess cancer risk of PM2.5-bound PAHs during heating and non-heating periods in a megacity in the Middle East;Ali-Taleshi;Environ. Res.,2021

4. Seasonal and spatial variations of atmospheric depositions-bound elements over Tehran megacity, Iran: pollution levels, PMF-based source apportionment and risks assessment;Ali-Taleshi;Urban Clim.,2022

5. Particulate and gaseous pollutants in Tehran, Iran during 2015-2021: factors governing their variability;Ali-Taleshi;Sustain. Cities Soc.,2022

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