Investigating the applicability of ADAPTS activity-based model in air quality analysis

Abstract

The growing recognition of negative impacts of vehicular emissions on global warming and public health is one of the main factors that led transportation policymakers to devise congestion/pollution mitigation strategies. However, in order to attain the best perception of potential results of implementing these policies, it would be essential to understand the response of people in terms of changing their travel behaviors. Activity-based travel demand models provide comprehensive platforms to simulate individuals’ travel behavior at very fine scale and examine the impact of various policies on population. This paper explores the applicability of activity-based models in evaluating the small- and large-scale environmental consequences of transportation policies. To provide a holistic and policy sensitive platform for estimating mobile source emissions, we integrate an activity-based travel demand model with a mesoscopic dynamic traffic assignment (DTA) module and a microscopic emission simulator. Accordingly, the ADAPTS model is extended with an agent-based DTA component, which allows for dynamic interaction between the demand model and network simulator. Then, the US EPA’s mobile source emission model, MOVES, is leveraged to estimate emissions produced by passenger cars. The main challenge in developing such an integrated framework is compatibility of the data among its different components. The performance of this framework is analyzed through two county- and project-level case studies in Chicago metropolitan area. In the county-level analysis, the base-year replication results show a drastic rise in emissions during peak periods, that is, around 14.8% and 27.2% of total daily NOx emission are produced during morning and evening rush hours, respectively. Further, as the project-level analysis, a capacity improvement in a critical ramp in the network is implemented in the DTA model. The simulation results show 24% reduction in VHT and 2.3% increase in VMT in 10-h simulation period in that link.