Causal Impacts of Transport Interventions on Air Quality
Rapid urbanisation and motorisation in recent decades contribute to increasing concerns about air quality. The transport sector is one of a main air pollution emissions sources. Various interventions have been implemented in the transport sector aimed at mitigating air pollution, such as improving public transport supply, tightening emission standards, managing transport demand with pricing schemes, and encouraging electric vehicles.
The actual impacts caused by transport interventions need to be evaluated to provide guidance for future investment and gradual amendments in policies with systematic considerations. However, the evaluation can be complicated due to various factors, such as the interactions between land use and transport, the different demand elasticities of various passenger groups, the relocations of firms and households, the reactions among air pollutants, the interplay between air pollutants and meteorological factors, and the complex mechanism of air pollution dispersion.
This project focuses on evaluating the causal impacts of transport interventions on air quality and public health with a series of causal inference methods and machine learning methods. An understanding of causal benefits could assist policymakers in making sustainable, efficient, and thorough decisions.