AI Article Synopsis

  • Communities near roads suffer from high traffic-related air pollution, presenting significant public health and environmental justice challenges.
  • Roadside green infrastructure, like trees and bushes, can help lower pollution levels, but current Gaussian-based models don't account for these vegetation barriers, making pollution reduction efforts less effective.
  • A new multi-regime Gaussian-based model has been developed to incorporate the effects of vegetation on pollutant dispersion and deposition, demonstrating promising accuracy in evaluating air quality improvements for various particle sizes and conditions.

Article Abstract

Communities located in near-road environments experience elevated levels of traffic-related air pollution. Near-road air pollution is a major public health concern, and an environmental justice issue. Roadside green infrastructure such as trees, hedges, and bushes may help reduce pollution levels through enhanced deposition and mixing. Gaussian-based dispersion models are widely used by policymakers to evaluate mitigation strategies and develop regulatory actions. However, vegetation barriers are not included in those models, hindering air quality improvement at the community level. The main modeling challenge is the complexity of the deposition and mixing process within and downwind of the vegetation barrier. We propose a novel multi-regime Gaussian-based model that describes the parameters of the standard Gaussian equations in each regime to account for the physical mechanisms by which the vegetation barrier deposits and disperses pollutants. The four regimes include vegetation, a downwind wake, a transition, and a recovery zone. For each regime, we fit the relevant Gaussian plume equation parameters as a function of the vegetation properties and the local wind speed. Furthermore, the model captures particle deposition, a major factor in pollutant reduction by vegetation barriers. We parameterized the multi-regime model using data generated from a fields-validated computational fluid dynamics (CFD) model, covering a wide range of vegetation properties and meteorological conditions. The proposed multi-regime Gaussian-based model was evaluated across 9 particle sizes and a tracer gas to assess its capability of capturing dispersion and deposition. The multi-regime model's normalized mean error (NME) ranged between 0.18 and 0.3, the fractional bias (FB) ranged between -0.12 and 0.09, and value ranged from 0.47 to 0.75 across all particle sizes and the tracer gas for ground level concentrations, which are within acceptable ranges for air quality dispersion modeling. Even though the multi-regime model is parameterized for coniferous trees, our sensitivity study indicates that it can provide useful predictions for hedges/bushes vegetative barriers as well.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11373375PMC

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