Spatio-temporal variations of PM2.5 concentrations and the evaluation of emission reduction measures during two red air pollution alerts in Beijing

Abstract

Abstract To effectively improve air quality during pollution episodes, Beijing released two red alerts in 2015. Here we examined spatio-temporal variations of PM2.5 concentrations during two alerts based on multiple data sources. Results suggested that PM2.5 concentrations varied significantly across Beijing. PM2.5 concentrations in southern parts of Beijing were higher than those in northern areas during both alerts. In addition to unfavorable meteorological conditions, coal combustion, especially incomplete coal combustion contributed significantly to the high PM2.5 concentrations. Through the CAMx model, we evaluated the effects of emission-reduction measures on PM2.5 concentrations. Through simulation, emergency measures cut down 10% – 30% of the total emissions and decreased the peaks of PM2.5 concentrations by about 10–20% during two alerts. We further examined the scenario if emergency measures were implemented several days earlier than the start of red alerts. The results proved that the implementation of emission reduction measures 1–2 days before red alerts could lower the peak of PM2.5 concentrations significantly. Given the difficulty of precisely predicting the duration of heavy pollution episodes and the fact that successive heavy pollution episodes may return after red alerts, emergency measures should also be implemented one or two days after the red alerts.