Analysis of synergic reduction of greenhouse gases and air pollutants emission in the urban transportation sector: taking Tangshan City as an example
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摘要:
以唐山市为例开展交通部门温室气体协同大气污染物减排潜力评估，首次在协同减排中考虑汽车空调制冷剂泄漏引起的温室效应，指出淘汰老旧车辆的附带效应，并借用协同发展理论中的协同度指标来测算各项措施减少污染物和温室气体排放的协同减排潜力。结果表明：在实施全部减排措施情况下，全市交通部门温室气体排放将于2030年达峰，大气污染物排放将在“十四五”末期达到峰值；全市当前因汽车制冷剂泄漏产生温室气体排放效应达28.08万t（以CO2计），占全部温室气体排放比例约4.7%，其中50%的排放来自汽车运行过程，且排放量将随汽车保有量上升而提高，需要针对运营、维修和报废过程的空调制冷剂泄漏量制定相应方案；采用协同度评价标准能有效区分不同措施的协同减排力度；淘汰国3及以下车辆时，绝对减排量大、协同度好，尽管在实施期内可能引起制冷剂泄漏量增加，但整体仍能实现协同减排；柴油货车改天然气和提高“公转水”比例，综合减排协同度好，但其在单一大气污染物与温室气体减排方面存在负向协同，需要配合其他减排措施同步推行。
Abstract:The evaluation of the potential of the synergic reduction of greenhouse gases (GHG) and air pollutants emissions was carried out in the transportation sector, with Tangshan City as a case study, taking into account the GHG emission caused by refrigerant leakage in automobile air conditioning in the synergic emission reduction for the first time. The side effects of phasing out old vehicles were pointed out, and the indicator of synergy degree in the synergic theory was adopted to quantify the synergic reduction capability of the corresponding measures to reduce pollutants and GHG emissions. The results showed that under the implementation of all emission reduction measures, GHG emission from the transportation sector would peak in 2030, and the emission of air pollutants would achieve peak value at the end of the 14th Five-Year Plan. The GHG emission effect of current automobile refrigerant leakage in Tangshan City reached 280 800 tons of CO2 equivalent, accounting for about 4.7% of the total GHG emission. 50% of the leakage came from automobiles, and the leakage would ramp up with the increase in automobile ownership. Therefore, specified measures should be taken to mitigate the leakage of the air conditioning refrigerant in the operation, maintenance, and scrapping processes. The degree of synergic reduction could be effectively distinguished by using synergy evaluation criteria. The absolute emission reduction of phasing out vehicles of national stage Ⅲ and below was large and had good synergy. Although it may cause an increase in refrigerant leakage during the implementation period, it was able to achieve a synergic reduction of GHG and air pollutants overall. Replacing diesel trucks with natural gas ones and improving the "road to water" ratio had a good reduction synergy degree. However, they had a negative synergy in reducing single air pollutant and GHG emissions, which needed to be carried out simultaneously with other emission reduction measures.
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图 2 2019年唐山市汽车HFCs排放工序组成
Figure 2. Automobile HFCs emission composition by processes of Tangshan in 2019
图 3 2019年唐山市汽车HFCs排放分车型组成
Figure 3. Automobile HFCs emission composition by types of vehicles of Tangshan in 2019
图 5 交通部门主要大气污染物排放分担情况
Figure 5. Emission sharing of major air pollutants by transportation sector
图 6 唐山市交通部门GHG排放变化趋势及相应措施碳减排效果
Figure 6. Trend of GHG emissions and CO2 emission reduction effect of corresponding measures in transportation sector in Tangshan
图 7 唐山市交通部门HFCs泄漏引起的GHG排放变化趋势及ELI减排效果
Figure 7. Trend of GHG effect by HFCs leakage and reduction effect of ELI in transportation sector in Tangshan
图 8 唐山市交通部门SO2排放变化趋势及相应措施减排效果
Figure 8. Trend of SO2 emission and emission reduction effect of corresponding measures in transportation sector in Tangshan
图 9 唐山市交通部门NOx排放变化趋势及相应措施减排效果
Figure 9. Trend of NOx emission and emission reduction effect of corresponding measures in transportation sector in Tangshan
图 10 唐山市交通部门PM排放变化趋势及相应措施减排效果
Figure 10. Trend of PM emission and emission reduction effect of corresponding measures in transportation sector in Tangshan
图 11 唐山市交通部门VOCs排放变化趋势及相应措施减排效果
Figure 11. Trend of VOCs emission and emission reduction effect of corresponding measures in transportation sector in Tangshan
表 1 协同度等级
Table 1. Classification of different degrees of synergic index
协同度类型 协同度指数得分 优质协同 0.90~1.00 良好协同 0.80~0.89 中级协同 0.70~0.79 初级协同 0.60~0.69 接近协同 0.50~0.59 协同较差 0.01~0.49 不协同 0 
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表 2 不同减排措施在各情景下应用情况
Table 2. Application of different reduction measures under different scenarios
减排类别 减排措施 基准情景（BAU） 绿色低碳情景（GLC） 结构调整 提高公交出行比例（PTR） 保持基年水平 “十四五”“十五五”“十六五”期间分别提高5、4、3个百分点 淘汰国3及以下车辆（ELI） 2030年前全部淘汰 提高“公转铁”比例（RTR） “十四五”“十五五”“十六五”期间分别提高5个百分点 提高“公转水”比例（RTW） “十四五”“十五五”“十六五”期间分别提高3个百分点 燃料升级 柴油货车改天然气（DTN） 保持基年水平 “十四五”“十五五”“十六五”期间分别提高10、15、20个百分点 柴油货车改纯电（DTE） “十四五”“十五五”“十六五”期间分别提高10、15、20个百分点 公交车天然气改纯电（PNE） “十四五”“十五五”“十六五”期间分别提高5、10、15个百分点 出租车改纯电（TTE） “十四五”“十五五”“十六五”期间分别提高5、10、15个百分点 私家车改纯电（PTE） “十四五”“十五五”“十六五”期间分别提高5、10、15个百分点 水运改纯电（STE） “十四五”“十五五”“十六五”期间分别提高1、3、5个百分点
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表 3 唐山市各类客运工具年行驶里程数以及货运工具基准年货物周转量
Table 3. Annual mileage of all kinds of passenger vehicles and the base year cargo turnover of freight vehicles in Tangshan City
机动车类型 年行驶里程/km 货物周转量/（亿t·km） 微型客车-出租车 50 000 微型客车-社会车辆 22 000 小型客车-出租车 80 000 小型客车-社会车辆 18 000 中型客车-公交车 54 000 中型客车-社会车辆 32 000 大型客车-公交车 54 000 大型客车-社会车辆 62 000 摩托车 6 000 微型货车 1 小型货车 419 中型货车 30 大型货车 680 低速货车 27 水运 338 铁路 812
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表 4 不同排放标准车型排放因子 [27]
Table 4. Emission factors of different kinds of vehicles under various vehicular emission standards
g/km 车辆类型 排放标准 SO2 NOx VOCs PM CO2 私家车-汽油 国0 0.01 0.56 0.43 0.05 340.1 国1 0.01 0.56 0.43 0.03 340.1 国2 0.01 0.20 0.40 0.01 300.4 国3 0.01 0.06 0.12 0.01 269.5 国4 0.01 0.03 0.07 0 216.5 国5 0.01 0.02 0.07 0 216.5 国6 0.01 0.02 0.06 0 216.5 公交车-汽油 国0 0.02 12.86 6.97 0.13 521.3 国1 0.02 6.43 6.51 0.06 521.3 国2 0.02 0.21 0.22 0.02 461.6 国3 0.02 0.11 0.11 0.01 419.7 国4 0.02 0.08 0.08 0.01 340.1 国5 0.02 0.05 0 0.01 340.1 国6 0.02 0.04 0 0.01 340.1 公交车-柴油 国0 0.14 8.52 2.90 1.31 648.6 国1 0.14 7.02 1.88 0.99 648.6 国2 0.14 6.17 0.56 0.35 574.4 国3 0.14 4.15 0.48 0.33 522.2 国4 0.14 2.56 0.12 0.14 423.3 国5 0.14 1.49 0.12 0.08 423.3 国6 0.14 1.34 0.11 0.08 423.3
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表 5 各类货物周转量变化参数
Table 5. The parameters of freight turnover change
% 时间段 公路货物周转量 铁路货物周转量 水路货物周转量 “十四五” 年均+4 年均+6 年均+2 “十五五” 年均+3 年均+4 年均+1 “十六五” 年均+2 年均+3 年均+0.8
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表 6 各措施减排协同度
Table 6. Degree of reduction synergy of various measures
情景 $S_{{\rm{NI{S{O_2}/C{O_2}eq}}} }$ $S_{ { {{{\rm{NI{NO}}} }_x}/{\rm{C{O_2}eq} } } }$ $S_{{\rm{NI{PM/C{O_2}eq}}} }$ $S_{{\rm{NI{VOCs/C{O_2}eq}}} }$ $S_{ {\rm{NI{AP /C{O_2}eq} } } }$ DTE 0.99 0.70 0.70 0.83 0.73 DTN 0.99 0.81 0.60 0.90 ELI 0.48 0.94 0.76 0.72 0.92 PNE 0.50 0.38 0.55 0.52 PTE 0.45 0.37 0.79 0.99 0.65 PTR 0.33 0.02 0.51 0.90 0.27 RTR 0.97 0.73 0.75 0.86 0.77 RTW 0.80 0.77 0.89 0.87 STE 0.01 0.49 0.93 0.41 0.06 TTE 0.29 0.13 0.01 0.10 0.13 注：灰色、浅绿、深绿表示协同度依次提高，橙色格子表示不协同。
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