Analyzing Urban Microclimate (UMC) Parameters and Comprehensive Review of UHI and Air Quality Interconnections

This review analyzes the relationship between Urban Heat Island (UHI) microclimate parameters and poor air quality in urban environments, focusing on how temperature variations, wind dynamics, and urban morphology influence pollutant concentrations. Experimental studies and numerical simulations emphasize the necessity of pedestrian-level sensing combined with computational fluid dynamics (CFD) simulations to accurately capture spatial variations in UHI-related parameters. Ozone concentrations have been observed to increase by up to 4 ppbv, while PM2.5 levels rise by 1–2 µg/m3 in response to UHI effects. Additionally, ANSYS Fluent 2020.R1. simulations demonstrate a 0.93 °C error in temperature predictions and a 1.35 m/s error in wind speed estimations. These findings highlight the critical role of sustainable urban planning strategies in mitigating UHI effects and improving air quality in densely populated areas.

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Publication Details

Journal
Environments
Published
2025-03-29
DOI
https://doi.org/10.3390/environments12040104
Citations
4
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
Field-Weighted Citation Impact
3.20

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article

Analyzing Urban Microclimate (UMC) Parameters and Comprehensive Review of UHI and Air Quality Interconnections

Lirane Mandjoupa, Max Denis, Kibria K. Roman, Hossain Azam
4 citations
Environments
Air Quality Monitoring and Forecasting
3.20
article

Analyzing Urban Microclimate (UMC) Parameters and Comprehensive Review of UHI and Air Quality Interconnections

Lirane Mandjoupa, Max Denis, Kibria K. Roman, Hossain Azam
article en
4 citations

Abstract

This review analyzes the relationship between Urban Heat Island (UHI) microclimate parameters and poor air quality in urban environments, focusing on how temperature variations, wind dynamics, and urban morphology influence pollutant concentrations. Experimental studies and numerical simulations emphasize the necessity of pedestrian-level sensing combined with computational fluid dynamics (CFD) simulations to accurately capture spatial variations in UHI-related parameters. Ozone concentrations have been observed to increase by up to 4 ppbv, while PM2.5 levels rise by 1–2 µg/m3 in response to UHI effects. Additionally, ANSYS Fluent 2020.R1. simulations demonstrate a 0.93 °C error in temperature predictions and a 1.35 m/s error in wind speed estimations. These findings highlight the critical role of sustainable urban planning strategies in mitigating UHI effects and improving air quality in densely populated areas.

EnvironmentsVol. 12(4)
SUNY Canton (US), University of the District of Columbia (US)
Army Research Laboratory
Openalex Percentile: Top 9%
Air Quality Monitoring and Forecasting
3.20
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Analyzing Urban Microclimate (UMC) Parameters and Comprehensive Review of UHI and Air Quality Interconnections — Lirane Mandjoupa, Max Denis, et al. · Environments (2025) | TGRS Research Map | TGRS