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Considerations for evaluating green infrastructure impacts in microscale and macroscale air pollution dispersion models
Citation:
Tiwari, A., P. Kumar, R. Baldauf, K. Zhang, F. Pilla, S. Sabatino, E. Brattich, AND B. Pulvirenti. Considerations for evaluating green infrastructure impacts in microscale and macroscale air pollution dispersion models. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, Netherlands, 672:410-426, (2019). https://doi.org/10.1016/j.scitotenv.2019.03.350
Impact/Purpose:
Health effects from exposure to traffic emissions have been identified as a major public health concern. Methods to mitigate these effects that community's can implement has increased in interest in recent years. Roadside vegetation has been shown to mitigate local air pollution; however, methods to model these effects have been a challenge. This paper reviews important parameters needed to model roadside vegetation impacts to incorporate into dispersion models. This information can be used by environmental and urban planners to implement urban green infrastructure for air quality benefits.
Description:
Green infrastructure (GI) in urban areas may be adopted as a passive control system to reduce air pollutant concentrations. However, current dispersion models offers limited modelling options to evaluate its impact on air pollutant concentrations. The aim of this review is to address the following question: How can GI be considered in readily available dispersion models to allow evaluation of its impacts on pollutant concentrations and health risk assessment? We examine the published literature on the parameterisation of deposition velocities and datasets for both particulate matter and gaseous pollutants that are required for deposition schemes. The deposition schemes that represent GI impacts in detail are complex, resource-intensive, and involve an abundant volume of input data. Further, we evaluate the limitations of different air pollution dispersion models at two spatial scales – microscale (i.e. 10-500 m) and macroscale (i.e. 5-100 km) - in considering the effects of GI on air pollutant concentrations and exposure alteration. We conclude that an appropriate handling of GI characteristics (such as aerodynamic effect, deposition of air pollutants and surface roughness) in dispersion models is necessary for understanding the mechanism of air pollutant concentrations simulation in presence of GI at different spatial scales. Several other processes (such as air pollutant transformation due to GI-emitted biogenic volatile organic compounds, the fraction of stomatal blocking water film and changes in uptake rate due to temperature increases) also influence deposition rates and air pollutant concentrations; most of those effects are not treated in dispersion models, mainly because these models are not developed for such purposes. Furthermore, the impacts of GI on air pollutant concentrations and health risk assessment (e.g., mortality, morbidity) are partly explored. The United States Forest Service developed i-Tree tool, which, with the BenMap model developed by the United States Environmental Protection Agency, has been used to estimate the health outcomes of annually-averaged air pollutant removed by deposition over GI canopies at the macroscale. However, studies relating air pollution health risk assessments due to GI-related changes in short-term exposure, via pollutant concentrations redistribution at the microscale and enhanced atmospheric pollutant dilution by increased surface roughness at the macroscale, along with deposition, are rare. Suitable treatments of all physical and chemical processes in coupled dispersion-deposition models and assessments against real-world scenarios are vital for health risk assessments.
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DOI: Considerations for evaluating green infrastructure impacts in microscale and macroscale air pollution dispersion models
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