2000-2020 年中国京津冀及周边地区（BTHSA）高时空分辨率车载排放清单。
High spatiotemporal resolution vehicular emission inventory in Beijing-Tianjin-Hebei and its surrounding areas (BTHSA) during 2000-2020, China.
机构信息
College of Environment Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China.
College of Environment Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China.
出版信息
Sci Total Environ. 2023 May 15;873:162389. doi: 10.1016/j.scitotenv.2023.162389. Epub 2023 Feb 24.
One comprehensive emission inventory of CO, HC, NO, PM, PM, BC, CH, CO and NO with high spatial resolution (0.01° × 0.01°) for 58 cities in Beijing-Tianjin-Hebei and its surrounding areas (BTHSA) during 2000-2020 are developed by using COPERT model and ArcGIS methodology. The results show that vehicular emissions of CO, HC, NO, PM, PM, BC and CH have begun to decrease or slow their growth rates in recent years due to the implementation of measures to control vehicular emissions. However, vehicular emissions of CO increase rapidly due to little fuel economy improvement. Besides, the usage of selective catalytic reduction (SCR) systems by heavy duty truck (HDT) is the main factor impacting the growth trend of vehicular NO emissions since 2017. By 2020, vehicular emissions of CO, HC, NO, PM, PM, BC, CO, CH and NO are estimated at about 1.65 Mt, 0.35 Mt, 1.39 Mt, 87.44 kt, 55.06 kt, 15.57 kt, 527.71 Mt, 36.20 kt and 8.56 kt, respectively. Therein, China III, IV, IV and IV passenger cars (PCs) are the predominated models for vehicular emissions of CO, HC, CH and CO, accounting for 19.59-28.26 % of the total vehicular emission of corresponding pollutant. Nevertheless, the major contributors of vehicular emissions of NO, PM, PM, BC and NO are China III (29.64 %), III (18.03 %), III (22.81 %), III (42.16 %) and V (22.28 %) HDTs, respectively. The gridded vehicular emissions vary significantly, with emissions of CO, HC, CH and CO being mainly concentrated in central urban areas of cities (e.g., Beijing, Tangshan, Zhengzhou, Tianjin, Qingdao, Jinan). Nevertheless, the grids with high vehicular emissions of NO, PM, PM, BC and NO are mainly distributed along the expressway and the suburban roads of cities (e.g., Linyi, Tangshan, Jining, Weifang, Shijiazhuang, Tianjin, Baoding). Finally, multi-year uncertainties of vehicular emission inventory are discussed.
利用 COPERT 模型和 ArcGIS 方法，为 2000-2020 年京津冀及周边地区 58 个城市（BTHSA）开发了具有高空间分辨率（0.01°×0.01°）的 CO、HC、NO、PM、PM、BC、CH 和 CO 全面排放清单。结果表明，由于实施了车辆排放控制措施，近年来 CO、HC、NO、PM、PM、BC 和 CH 的车辆排放量已经开始减少或减缓其增长率。然而，由于燃油经济性改善不大，CO 的车辆排放量迅速增加。此外，自 2017 年以来，选择性催化还原（SCR）系统在重型卡车（HDT）中的使用是影响车辆 NO 排放增长趋势的主要因素。到 2020 年，CO、HC、NO、PM、PM、BC、CO、CH 和 NO 的车辆排放量估计约为 165 万吨、0.35 万吨、139 万吨、874400 吨、550600 吨、155700 吨、5277100 吨、362000 吨和 85600 吨。其中，中国 III、IV、IV 和 IV 乘用车（PC）是 CO、HC、CH 和 CO 车辆排放的主要车型，占相应污染物总车辆排放量的 19.59-28.26%。然而，NO、PM、PM、BC 和 NO 的主要贡献者分别是中国 III（29.64%）、III（18.03%）、III（22.81%）、III（42.16%）和 V（22.28%）重型卡车。网格化车辆排放量差异显著，CO、HC、CH 和 CO 的排放量主要集中在城市中心城区（如北京、唐山、郑州、天津、青岛、济南）。然而，NO、PM、PM、BC 和 NO 车辆排放量较高的网格主要分布在城市的高速公路和郊区道路沿线（如临沂、唐山、济宁、潍坊、石家庄、天津、保定）。最后，讨论了多年来车辆排放清单的不确定性。
Zotero 插件