Green Infrastructure and Air Pollution: Evidence from Highways Connecting Two Megacities in China - Bo Yu; Trang Tran; Wang-Sheng Lee (Institute of Labor Economics (IZA), 2021)
Following market liberalisation, the vehicle population in China has increased dramatically over the past few decades. This paper examines the causal impact of the opening of a heavily used high speed rail line connecting two megacities in China in 2015, Chengdu and Chongqing, on air pollution. We use high-frequency and high spatial resolution data to track pollution along major highways linking the two cities. Our approach involves the use of an augmented regression discontinuity in time approach applied on data that have been through a meteorological normalisation process. This deweathering process involves applying machine learning techniques to account for change in meteorology in air quality time series data. Our estimates show that air pollution is reduced by 7.6% along the main affected highway. We simultaneously find increased levels of ozone pollution which is likely due to the reduction in nitrogen dioxide levels that occurred. These findings are supported using a difference-in-difference approach.
Keywords: L92; O18; Q53; Q54; R41; 330; air pollution; China; green infrastructure; high-speed railway; regression discontinuity; machine learning