【摘要】 基于重庆市主城区动态交通流数据、机动车实际行驶数据以及车辆检测数据,采用国际机动车排放（IVE）模型结合道路长度的方法,建立了重庆市主城区机动车污染物的排放清单,并利用ADMS-Urban扩散模型对NO_x排放数据进行了验证。结果表明:2017年主城区机动车CO、VOCs、NO_x和PM₁₀的排放量分别为22.80万、1.25万、4.18万、0.42万t/a,小型客车、轻型货车和重型货车对各类污染物的贡献总和均超过85%;机动车污染物排放集中在内环以内的核心区域,呈现由中心向四周放射状递减的趋势。27个监测站点的NO₂监测值与模拟值具有较好的相关性,说明NO_x模拟结果基本合理,机动车NO_x排放对重庆市主城区大气NO₂的贡献显著,开展机动车污染防治专项工作可成为重庆市主城区NO_x削减的有效途径。更多还原

【Abstract】 Based on dynamic traffic flow data, actual driving data and vehicle detection data, this paper established the emission inventory of pollutants from motor vehicle exhaust in Chongqing urban area using international vehicle emission（IVE） model and the length of urban road. The inventory of NO_x emission was then verified with ADMS-Urban dispersion model. The results indicated that the total vehicle emissions of CO,VOCs, NO_x and PM₁₀ in Chongqing urban area in 2017 was 22.80×10⁴,1.25×10⁴,4.18×10⁴ and 0.42×10⁴ t/a respectively. The total pollutant emissions of small passenger cars, light-duty vehicles and heavy-duty vehicles accounted for more than 85% of the pollutant emissions of all motor vehicles. The emission intensity of pollutants from motor vehicle exhaust decreased progressively from the inner rings to outwards of urban area, and the emissions mainly concentrated in core-area of the inner rings. There was a good agreement between simulated and measured values for NO₂ of 27 air quality monitoring stations, indicating that the NO_x simulation results were basically reasonable. The NO_x emissions from motor vehicles in the Chongqing urban area contributed significantly to NO₂ in the regional atmospheric environment. The special project of motor vehicle emission control might serve as an effective way to reduce NO_x in Chongqing urban area.更多还原