Vehicle Emission and Near-Road Air Quality Modeling in Shanghai, China, Based on Taxi GPS Data and MOVES Revised Emission Inventory

摘要

In China, motor vehicle emission has been identified as the major source of urban airpollution, thus the study of emission estimation and its impact on air quality is necessary.Vehicle emission varies for its strong regional characteristics, depending on local vehicleoperation and emission performance. This paper employs MOVES model released by U.S.Environment Protection Agency (EPA) for Shanghai vehicle emission factors estimation. Toachieve a convincing emission result, vehicle operation is extracted from massive taxi GPSdata in Shanghai, and emission inventory from MOVES is revised according to China’smotor vehicle emission standards. In addition, deterioration factors are calculated based onvehicle use condition. Comprehensive emission factors of Shanghai light-duty vehicles indifferent average speed level are generated. The result shows that emission factors for HC,CO and NOX of in-use light vehicles in China are 0.1-0.25g/km, 4-7g/km and 0.4-0.8g/km,with 15, 1.9 and 5.9 times higher than those in US respectively. By 2012, the EnvironmentalProtection Bureau has set 10 monitoring sites in Shanghai and released real-time PM2.5, PM10,NO2 and SO2 concentrations to the public. Using the new release of data, a field study ofestimating near-road air quality is conducted with MOVES and air dispersion modelAERMOD. The concentration result shows that the accuracy of near-road NO2 estimation isimproved with taxi GPS data and MOVES revised emission inventory. The result shows thatthe proposed method has the potential of providing policy-making support on near-road landuse and vehicle management. The study also explores the extended application of MOVES byoffering a procedure of applying MOVES in non-US regions.