Emission pattern mining based on taxi trajectory data in Beijing

Abstract

Traffic-related air pollution has been one of the major environmental problems in China. It is urgent to explore the urban traffic emission patterns for the low-carbon urban planning and traffic management. With this purpose, a new urban traffic emission analysis model is proposed in this paper. The traffic analysis zones (TAZs) are treated as the analysis unit. Then the spatial and temporal dynamic emission patterns are studied based on taxi GPS data in Beijing. The whole urban area of Beijing is divided into 33 TAZs depending on the feature of road networks. And the trip patterns of TAZs are extracted. The instantaneous emissions of CO2, NOx, VOC and PM within and between TAZs are estimated. The relationships between emissions and road densities are studied. The results demonstrated that (1) the highest taxi trips during the day occur at 10:00, 16:00 and 20:00. (2) The variations of the 4 pollutants within and between TAZs are similar. The emissions of TAZs with business centers, entertainment centers and transportation hubs are obviously higher than others. For TAZs within the 5th Ring Road, the northern emissions are stronger than the southern. Emission patterns can be divided into 3 types, corresponding to the time periods of 0:00–3:00, 3:00–6:00 and 6:00–24:00. (3) There is a positive relationship between emissions within and between TAZs and road densities. And when the road densities of TAZs are bigger than 0.6, emissions within TAZs will rise up obviously with the increasing road densities. The policy implications of results include the region function planning, traffic planning, the public transport improvement, optimal design of charging stations and new energy vehicles promotion.