Method and Application of Dynamic Emission Inventory for Heavy-Duty Trucks Based on Actual Vehicle Kilometers Travelled
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摘要: 为建立精细化重型货车动态排放清单,通过应用GPS大数据,提出了一种基于实际行驶里程构建重型货车动态排放清单的方法,以山东省潍坊市为例进行方法应用和污染物排放特征分析,并与保有量法进行对比分析. 结果表明:①基于GPS大数据计算的本地和过境单辆重型货车日行驶里程分别为(126.73±15.24)和(107.10±6.14) km,计算结果更接近于实际状况. ②2019年重型货车CO、NOx、SO2、NH3、VOCs、PM2.5、PM10、BC和OC排放量分别为2811.00、7334.06、275.90、33.50、344.70、119.02、130.31、69.18和17.69 t,其中过境重型货车各污染物排放量占比范围为73.07%~76.31%. ③过境重型货车污染物小时排放量呈双峰分布,峰值分别出现在12:00和20:00;本地重型货车小时排放量呈单峰分布,峰值出现在12:00. 过境重型货车在青银高速公路上的污染物排放量明显高于其他道路. ④基于保有量法计算的重型货车污染物排放量高于基于实际行驶里程法的计算结果,2种方法排放量差异在66.80%~74.96%之间. 研究显示,潍坊市重型货车污染物排放量以过境重型货车排放为主,基于实际行驶里程可构建本地和过境重型货车高时空分辨率排放清单.Abstract: In order to establish a refined dynamic emission inventory of heavy-duty trucks (HDTs), a method of actual vehicle kilometers traveled (VKT) based on GPS big data was proposed. Taking Weifang City of Shandong Province as an example, the application of this method and pollutant emission characteristics were analyzed, and a comparison was made with the traditional registered vehicle method. The results indicate that: (1) The daily VKT calculated based on GPS big data for single local and non-local HDTs were (126.73±15.24) and (107.10±6.14) km, respectively, which were closer to the actual situation. (2) The annual emissions of CO, NOx, SO2, NH3, VOCs, PM2.5, PM10, BC and OC from HDTs in 2019 were 2811.00, 7334.06, 275.90, 33.50, 344.70, 119.02, 130.31, 69.18 and 17.69 t/a, respectively. Among these pollutants, the pollutants from non-local HDTs accounted for 73.07% to 76.31% of the total emissions. (3) The hourly emissions of pollutants from non-local HDTs showed a double peak distribution, with peaks at 12:00 and 20:00. The hourly emission from local HDTs showed a single peak distribution, with a peak at 12:00. Furthermore, the non-local HDTs emitted higher levels of pollutant on the G20 (Qingdao-Yinchuan Highway) than on other roads. (4) The pollutant emissions of HDTs calculated based on registered vehicle method were higher than those calculated based on the actual VKT, with emission differences ranging from 66.80% to 74.96%. The research shows that the pollutant emissions of HDTs in Weifang City are mainly from non-local HDTs. By using actual VKT data, we can construct high spatio-temporal resolution emission inventories for both local and non-local HDTs.
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表 1 本地化修正后的排放因子
Table 1. Revised emission factors
车型 排放标准 排放因子/(g/km) CO NOx SO2 NH3 VOCs PM2.5 PM10 BC OC 重型载货
柴油车国Ⅲ 1.63 5.80 0.14 0.02 0.29 0.14 0.15 0.08 0.02 国Ⅳ 1.37 3.29 0.14 0.02 0.14 0.05 0.05 0.03 0.01 国Ⅴ 1.37 2.80 0.14 0.02 0.14 0.01 0.01 0.01 0.00 表 2 潍坊市本地重型货车与过境重型货车污染物日均排放量
Table 2. Daily average emissions of local and non-local HDTs in Weifang City
污染物 本地重型货车 过境重型货车 B/A 日均
排放量(A)/t标准差/t 日均
排放量(B)/t标准差/t CO 2.08 0.67 5.72 1.69 2.75 NOx 5.24 1.61 15.10 4.33 2.88 SO2 0.21 0.07 0.56 0.17 2.67 NH3 0.03 0.01 0.07 0.02 2.33 VOCs 0.25 0.08 0.71 0.21 2.84 PM2.5 0.08 0.02 0.25 0.07 3.13 PM10 0.09 0.02 0.27 0.07 3.00 BC 0.05 0.01 0.15 0.04 3.00 OC 0.01 0.00 0.04 0.01 4.00 表 3 2种方法计算的污染物排放量对比
Table 3. Comparison of pollutant emissions calculated by two methods
项目 基于保有
量法(M)基于实际行驶
里程法(N)(|N−M|/M)×100%1) 保有量(或交通量) 7.92×104 辆/a 4.78×104辆/d 行驶里程/[km/(d·辆)] 205.48 116.92 CO排放量/(t/a) 8 814.03 2 811.00 68.11 NOx排放量/(t/a) 25 209.27 7 334.06 70.91 SO2排放量/(t/a) 831.09 275.90 66.80 NH3排放量/(t/a) 100.92 33.50 66.81 VOCs排放量/(t/a) 1 226.30 344.70 71.89 PM2.5排放量/(t/a) 454.51 119.02 73.81 PM10排放量/(t/a) 504.72 130.31 74.18 BC排放量/(t/a) 265.84 69.18 73.98 OC排放量/(t/a) 70.64 17.69 74.96 注:1)单位为%. -
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