Mapping dynamic road emissions for a megacity by using open-access traffic congestion index data

The high populations of vehicles in global megacities have raised serious mobility and sustainability challenges, such as traffic congestion, air pollution deterioration and energy consumption issues. Detailed emission inventories at the link level are a prerequisite to accurately quantifying ambient pollution concentrations and identifying hotspots of human exposure within urban areas. The increasing adoption of intelligent transportation system data in smart-city initiatives worldwide has offered unprecedented opportunities for improving transportation air quality management. Based on the open-access traffic congestion index, we construct a high-resolution emission inventory of hourly fluxes of air pollutants and carbon dioxide from on-road vehicles over the whole road network in Shenzhen, China. Fine-grained quantification of 'excess' emissions from rush-hour traffic is explored, finding varied emission enhancement (14.3-30.4%) for different pollutants, as well as 24.3-26.8% and 19.6-22.0% 'excess' consumption for gasoline and diesel, respectively, in a central business district of Shenzhen during the rush hour periods. Also, we quantified the impacts of freight activities on pollutant emissions that freight activities can largely increase the street-level emission rates of nitrogen oxides, fine particulate matter and carbon dioxide, in which heavy-duty trucks share up to 50% of the total emissions of these species. This study provides a novel approach of high-resolution traffic emission inventory construction that can be potentially utilized in many types of cities, particularly for cities suffering from data-sparse situations, and further strengthen the intelligence and accuracy of vehicle emission management.