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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[1] IPCC. Climate change 2022: mitigation of climate change (summary for policymakers)[EB/OL]. [2022-04-04]. https://report.ipcc.ch/ar6wg3/pdf/IPCC_AR6_WGIII_SummaryForPolicymakers.pdf. [2] 李昭阳, 汤洁, 孙平安, 等.长春市城市道路交通CO污染的空间分布模拟研究[J]. 环境科学研究,2005,18(1):78-82.LI Z Y, TANG J, SUN P A, et al. The simulating research on spatial distribution of CO pollution from urban traffic in Changchun City[J]. Research of Environmental Sciences,2005,18(1):78-82. [3] 谷秀, 赵志勇, 任阵海, 等.现代物流绿色运输模式的节能减排潜力分析[J]. 环境工程技术学报,2014,4(6):474-480.GU X, ZHAO Z Y, REN Z H, et al. Analysis of energy conservation and emission reduction potential for green transportation mode of modern logistics[J]. Journal of Environmental Engineering Technology,2014,4(6):474-480. [4] 黄莹, 郭洪旭, 廖翠萍, 等.基于LEAP模型的城市交通低碳发展路径研究: 以广州市为例[J]. 气候变化研究进展,2019,15(6):670-683.HUANG Y, GUO H X, LIAO C P, et al. Study on low-carbon development path of urban transportation sector based on LEAP model: take Guangzhou as an example[J]. Climate Change Research,2019,15(6):670-683. [5] 黄志辉, 纪亮, 尹洁, 等.中国道路交通二氧化碳排放达峰路径研究[J]. 环境科学研究,2022,35(2):385-393.HUANG Z H, JI L, YIN J, et al. Peak pathway of China's Road traffic carbon emissions[J]. Research of Environmental Sciences,2022,35(2):385-393. [6] 肖劲松, 杨聪.大气污染物和温室气体排放协同控制在交通行业的实践[J]. 绿叶,2012(6):111-118. [7] 冯相昭, 赵梦雪, 王敏, 等.中国交通部门污染物与温室气体协同控制模拟研究[J]. 气候变化研究进展,2021,17(3):279-288.FENG X Z, ZHAO M X, WANG M, et al. Simulation research on co-controlling pollutants and greenhouse gases emission in China's transportation sector[J]. Climate Change Research,2021,17(3):279-288. [8] 谭琦璐, 杨宏伟.京津冀交通控制温室气体和污染物的协同效应分析[J]. 中国能源,2017,39(4):25-31.TAN Q L, YANG H W. Synergistic effect analysis of greenhouse gases and pollutants in Beijing-Tianjin-Hebei traffic control[J]. Energy of China,2017,39(4):25-31. [9] 王碧云, 刘永红, 廖文苑, 等.非珠三角机动车尾气控制措施协同效果评估[J]. 环境科学与技术,2019,42(6):176-183.WANG B Y, LIU Y H, LIAO W Y, et al. Assessment of vehicle emission reduction measures based on the analysis of co-control in the non-Pearl River Delta region[J]. Environmental Science & Technology,2019,42(6):176-183. [10] 李云燕, 宋伊迪.碳中和目标下的北京城市道路移动源CO2和大气污染物协同减排效应研究[J]. 中国环境管理,2021,13(3):113-120.LI Y Y, SONG Y D. Study on the synergetic emission reduction effect of CO2 and air pollutants from the mobile source of urban roads in Beijing under the target of carbon neutralization[J]. Chinese Journal of Environmental Management,2021,13(3):113-120. [11] 许光清, 温敏露, 冯相昭, 等.城市道路车辆排放控制的协同效应评价[J]. 北京社会科学,2014(7):82-90.XU G Q, WEN M L, FENG X Z, et al. Co-benefits of road transport policy in reducing air pollutants and greenhouse gas emissions in China[J]. Social Sciences of Beijing,2014(7):82-90. [12] 阿迪拉·阿力木江, 蒋平, 董虹佳, 等.推广新能源汽车碳减排和大气污染控制的协同效益研究: 以上海市为例[J]. 环境科学学报,2020,40(5):1873-1883.ADILA A, JIANG P, DONG H J, et al. Synergy and co-benefits of reducing CO2 and air pollutant emissions by promoting new energy vehicles: a case of Shanghai[J]. Acta Scientiae Circumstantiae,2020,40(5):1873-1883. [13] 汽车空调HFCs制冷剂减排绿皮书[R]. 北京: 北京大学环境科学与工程学院, 2018. [14] Stockholm Environment Institute, Tellus Institute. LEAP: long range energy alternatives planning system, user guide for LEAP 2005[EB/OL]. [2016-09-18]. http://forums.seib.org/leap/documents/Leap 2005 User Guide English.pdf. [15] IPCC. IPCC guidelines for national greenhouse gas inventories[R]. Kanagawa: Institute for Global Environmental Strategies (IGES) for the IPCC, 2006. [16] XIANG X Y, ZHAO X C, JIANG P N, et al. Scenario analysis of hydrofluorocarbons emission reduction in China's mobile air-conditioning sector[J]. Advances in Climate Change Research,2022,13(4):578-586. doi: 10.1016/j.accre.2022.04.006 [17] 陈元华, 杨沿平, 胡纾寒, 等.我国报废汽车回收利用现状分析与对策建议[J]. 中国工程科学,2018,20(1):113-119.CHEN Y H, YANG Y P, HU S H, et al. Analysis and countermeasures for the status quo of the recycling and utilization of end-of-life vehicles in China[J]. Engineering Science,2018,20(1):113-119. [18] WU T, ZHANG M B, OU X M. Analysis of future vehicle energy demand in China based on a gompertz function method and computable general equilibrium model[J]. Energies,2014,7(11):7454-7482. doi: 10.3390/en7117454 [19] YANG R P, WANG M, ZHAO M X, et al. Synergic benefits of air pollutant reduction, CO2 emission abatement, and water saving under the goal of achieving carbon emission peak: the case of Tangshan City, China[J]. International Journal of Environmental Research and Public Health,2022,19(12):7145. doi: 10.3390/ijerph19127145 [20] 毛显强, 邢有凯, 高玉冰, 等.温室气体与大气污染物协同控制效应评估与规划[J]. 中国环境科学,2021,41(7):3390-3398.MAO X Q, XING Y K, GAO Y B, et al. Study on GHGs and air pollutants co-control: assessment and planning[J]. China Environmental Science,2021,41(7):3390-3398. [21] HAKEN H. Synergetics: An introduction nonequilibrium phase transitions and self- organization in physics, chemistry and biology[M]. Berlin: Springer Berlin Heidelberg, 1977. [22] 汪明月, 刘宇, 李梦明, 等.区域碳减排能力协同度评价模型构建与应用[J]. 系统工程理论与实践,2020,40(2):470-483.WANG M Y, LIU Y, LI M M, et al. Construction and application of evaluation model for coordinated degree of regional carbon emission[J]. Systems Engineering:Theory & Practice,2020,40(2):470-483. [23] 陈艳, 袁春来.长江中游城市群绿色低碳协同发展分析[J]. 环境保护,2019,47(10):57-61.CHEN Y, YUAN C L. Evaluation on green and low-carbon development of urban agglomeration in the middle reaches of the Yangtze River[J]. Environmental Protection,2019,47(10):57-61. [24] 王涵, 李慧, 王涵, 等.我国减污降碳与地区经济发展水平差异研究[J]. 环境工程技术学报,2022,12(5):1584-1592.WANG H, LI H, WANG H, et al. Research on the difference in air pollution and carbon dioxide reduction and regional economic development levels in China[J]. Journal of Environmental Engineering Technology,2022,12(5):1584-1592. [25] TOLLEFSEN P, RYPDAL K, TORVANGER A, et al. Air pollution policies in Europe: efficiency gains from integrating climate effects with damage costs to health and crops[J]. Environmental Science & Policy,2009,12(7):870-881. [26] 中国电力行业年度发展报告2020[R]. 北京: 中国电力企业联合会, 2020. [27] 贺克斌. 城市大气污染源排放清单编制技术手册[R]. 北京: 清华大学, 2018. [28] 高玉冰, 毛显强, CORSETTI G, 等.城市交通大气污染物与温室气体协同控制效应评价: 以乌鲁木齐市为例[J]. 中国环境科学,2014,34(11):2985-2992.GAO Y B, MAO X Q, CORSETTI G, et al. Assessment of co-control effects for air pollutants and green house gases in urban transport: a case study in Urumqi[J]. China Environmental Science,2014,34(11):2985-2992. □ -
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