The temporal and spatial differences have no significant impact on the development of the facility- and speed-specific VSP distributions for the vehicle emission estimation. The database of the specific VSP distributions in the VSP-based emission models can maintain in terms of time. Thus, it is unnecessary to update the database regularly, and it is reliable to use the history vehicle activity data to forecast the emissions in the future. In one city, the areas with less data can still develop accurate VSP distributions based on better data from other areas.
This work introduces a parallelly distributed computing technique to quantify the traffic‐related pollutant concentrations at regional scales. The U.S. Environmental Protection Agency (EPA)‐recommended dispersion model AERMOD involves complex model setup that requires extensive data inputs with strict formatting rules. These strict requirements increase the likelihood of human errors, especially in larger‐scale high‐resolution dispersion modeling. The paper presents a streamlined framework that integrates the processes of data preparation, link and receptor configuration, and mobile source emissions modeling. The emissions model is then connected with dispersion model through a parallel computing system. Such linkages allow high‐resolution traffic‐related air quality impacts to be estimated at the regional scales with high computational efficiency. The tool can be used by a broad audience, including any stakeholders interested in mobile source emissions modeling, and near‐road pollutant concentration modeling under the National Environmental Policy Act, and Clean Air Act transportation and air quality conformity analysis.
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