• 关键词：道路移动源  机动车污染  MOVES模型  排放清单  时空分布  渭南市

• 基金项目：国家重点研发计划项目（No.2017YFC0212206）；陕西省重点产业创新链（群）研发计划项目（No.2018ZDCXL-SF-02-05）；陕西省科技统筹创新工程计划项目（No.2016KTZDSF-02-01）

• 张雅瑞
• 长安大学水利与环境学院，西安 710064;长安大学旱区地水文与生态效应教育部重点实验室，西安 710064

• 李光华
• 长安大学水利与环境学院，西安 710064

• 邓顺熙
• 长安大学水利与环境学院，西安 710064;长安大学旱区地水文与生态效应教育部重点实验室，西安 710064

• 孙智钢
• 长安大学水利与环境学院，西安 710064

• 宋慧
• 长安大学水利与环境学院，西安 710064;长安大学建筑工程学院，西安 710061

• 路珍珍
• 长安大学水利与环境学院，西安 710064

• 巴利萌
• 长安大学水利与环境学院，西安 710064

• 李姜豪
• 长安大学水利与环境学院，西安 710064

• 摘要：应用MOVES-2014a模型并对其输入参数进行了本地化修正，计算了2018年渭南市道路移动源污染物的排放因子和排放总量.基于渭南市路网分布和GIS信息及车流分布对污染物总排放量进行了空间和时间分配，建立了1 km×1 km和1 h分辨率的排放清单.结果表明，渭南市机动车排放CO、NMVOCs、NO_x、NO₂、NO、PM_2.5、PM₁₀、NH₃、SO₂和CH₄的总量分别为2.791×10⁴、0.409×10⁴、1.527×10⁴、0.168×10⁴、1.359×10⁴、0.074×10⁴、0.080×10⁴、0.016×10⁴、0.003×10⁴和0.043×10⁴ t.机动车排放的NO_x中NO占89%，NO₂占11%.重型货车是PM_2.5和NO_x的主要排放源，重型货车占机动车保有量的2.1%，排放了48.5%的PM_2.5和52.8%的NO_x.小客车和摩托车是CO和NMVOCs的主要排放源，分别排放了74.6%的CO和64.5%的NMVOCs.机动车排放的颗粒物90%以上是PM_2.5.渭南市国III及以下排放标准的机动车（占总交通量的41%）对PM、NO_x和NMVOCs的排放贡献达60%以上.分配的道路移动源排放清单在空间尺度上呈现明显的“线-面”特征，以渭南市主城区和4条过境高速路高强度排放区向外逐渐降低，道路移动源排放强度的时间变化与车流量的变化特征一致.

• Abstract：In this study， the MOVES-2014a （ MOtor Vehicle Emission Simulator ） model， which was employed to calculate the vehicle emission factors and total emissions of pollutants from road mobile sources in Weinan in 2018. The inputs of model parameters were localized. The spatial and temporal allocations of total pollutants emissions were characterized based on the traffic network distribution， GIS information and traffic flows in Weinan. The emission inventory with a high spatial （1 km×1 km） and temporal （1 h） resolution was thus developed. The results showed that the total emissions of CO， NMVOCs， NO_x， NO₂， NO， PM_2.5， PM₁₀， NH₃， SO₂和CH₄ were 2.791×10⁴， 0.409×10⁴， 1.527×10⁴， 0.168×10⁴， 1.359×10⁴， 0.074×10⁴， 0.080×10⁴， 0.016×10⁴， 0.003×10⁴ and 0.043×10⁴ t， respectively. NO and NO₂ accounted for 89% and 11% of NO_x emission， respectively. Although the fraction of heavy trucks in total vehicle population was only 2.1%， the emissions of PM_2.5 and NO_x by them accounted for 48.5% and 52.8% of total PM_2.5 and NO_x emissions， respectively. Passenger car and motorcycle emissions were the dominant sources of CO and NMVOCs， which accounted for 74.6% and 64.5% of total CO and NMVOCs emissions， respectively. PM_2.5 accounted for more than 90% of PM₁₀ emitted by vehicles. The share of vehicles in total population， which met Chinese III emission standard or lower， was 41%； however， they contributed more than 66% total emissions of PM， NOx and NMVOCs. The spatial distribution of emission inventory had a remarkable “line-plane” feature： the downtown and four expressways of Weinan were hotspots， the emissions of which were intensive； the emission strength gradually decreased outward； the temporal variation of on-road mobile emission strength was consistent with that of traffic flows.

• Key words：road mobile source  vehicle pollution  MOVES model  emission inventory  spatio-temporal allocation  Weinan

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