Considerations for evaluating green infrastructure impacts in microscale and macroscale air pollution dispersion
Arvind Tiwari1, Prashant Kumar2, Richard Baldauf3
1Global Centre for Clean Air Research (GCARE), Department of Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford GU2 7XH, Surrey, United Kingdom.
The Science of the Total Environment
|April 10, 2019
Summary
Green infrastructure (GI) can reduce urban air pollution. Current models struggle to assess GI impacts on pollutant concentrations and health risks, requiring better integration of GI characteristics for accurate simulations.
Area of Science:
- Environmental Science
- Atmospheric Chemistry
- Urban Planning
Background:
- Green infrastructure (GI) is recognized for its potential to mitigate urban air pollution passively.
- Existing air dispersion models have limitations in accurately representing GI's effects on pollutant concentrations.
- Evaluating GI's impact on health risk assessments requires improved modeling capabilities.
Purpose of the Study:
- To review how green infrastructure can be incorporated into dispersion models for evaluating its impact on air pollutant concentrations.
- To assess the current state of modeling for GI's effects on air quality and associated health risks.
- To identify necessary advancements in dispersion modeling for accurate GI impact assessment.
Main Methods:
- Literature review focusing on parameterization of deposition velocities for particulate matter and gaseous pollutants.
- Evaluation of air pollution dispersion model limitations at microscale (10-500m) and macroscale (5-100km) concerning GI.
- Analysis of studies on health risk assessment related to GI and air pollutant concentration changes.
Main Results:
- Detailed deposition schemes for GI are complex, data-intensive, and resource-heavy.
- Accurate simulation of air pollutant concentrations near GI requires incorporating its aerodynamic effects, deposition, and surface roughness.
- Macroscale health risk assessments (e.g., using i-Tree and BenMap) exist for annual pollutant removal by GI, but microscale and short-term exposure impacts are understudied.
Conclusions:
- Current dispersion models need enhanced capabilities to accurately simulate GI's influence on air pollutant concentrations across different spatial scales.
- Further research is vital to understand GI's role in pollutant redistribution and dilution, particularly for short-term exposure and health risk assessments.
- Coupled dispersion-deposition models and validation against real-world data are crucial for reliable health risk evaluations considering GI.
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