Effect of Urban Double Restoration Pilot Project for Coordinated Control of PM2.5 and O3 Pollution: A Case Study of Sanya, China
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摘要: 我国大气环境进入PM2.5污染依然严峻和臭氧(O3)污染日益突出的新阶段，“十四五”规划纲要提出要推进PM2.5和臭氧(O3)污染协同控制. 在大气污染防治领域，减排长期以来被视作污染防治的唯一出路. 本文借鉴应对气候变化问题所采用的减排与适应的两种治理模式，探索适应模式的污染防治效果. 选取我国首个“生态修复、城市修补”(简称“城市双修”)试点城市——三亚市作为研究对象，以城市月均空气质量作为评价指标，采用准试验法评估试点效果. 以海口市作为三亚市的空间对照，以试点前1.5年作为试点后1.5年的时间对照，采用依次添加气象、固定效应、1阶、2阶时间趋势控制的双倍差异模型，识别“城市双修”试点对三亚市空气污染的防治效果. 结果表明：①“城市双修”试点大幅降低了三亚市的PM和O3污染，其中，O3浓度降低约30 μg/m3，PM2.5、PM10浓度分别降低约7、10 μg/m3，三者降幅分别达47%、39%、28%；②“城市双修”对O3浓度的影响是持续的，对PM浓度的影响滞后半年；③将“城市双修”试点分别提前6、9、12个月的安慰剂试点均未发现对三亚市空气质量有任何显著影响. 研究显示，“城市双修”试点对三亚市PM2.5和O3协同控制具有意外显著的效果；甄别“城市双修”在不同时段所采取的修复细节有助于实现PM2.5和O3的精准治理，推广这些修复措施至其他城市有利于缓解我国当前面临的大气环境问题.Abstract: China's air environment has entered a new phase of severe PM2.5 pollution and increasingly worsened O3 pollution. Thus, the outline of the ‘14th Five-Year Plan’ proposed to promote the coordinated control of PM2.5 and O3 pollution. In contrast to the dual governance model of mitigation and adaptation being used in reaction to climate change, China has long regarded emission reduction as the only way to prevent pollution. Exploring the effect of adaptation besides abatement may be an economic approach for current pollution control. In June 2015, China's first Ecological Restoration and Urban Repair (also known as Urban Double Restoration (UDR)) pilot was launched in the city of Sanya, Hainan Province, which provides a natural experiment to examine the effect of adaptation on pollution. Using monthly urban air quality data from 2014-2016 as the measure, and based on geography, climate, and economic dimensions to screen Haikou from other cities in Hainan as a control city for Sanya, a difference-in-differences (DD) method has been built after performing the parallel trend test. Using the pre-pilot period as a temporal control for the post-pilot period, the DD specifications gradually controlling for atmospheric factors, fixed effects, a linear time trend, and a quadratic time trend identify the causal impact of the UDR pilot on air quality in Sanya. The results show that: (1) The UDR pilot significantly reduced Sanya's PM and O3 pollution. The O3 concentration was reduced by 30 μg/m3, PM2.5 concentration was reduced by 7 μg/m3, and PM10 concentration was reduced by 10 μg/m3, which was equivalent to a 47%, 39% and 28% reduction. (2) The UDR's effect on the reduction of O3 concentration was persistent, and the effect on the reductions of PM was postponed for half a year. (3) The placebos that moved the URD pilot 6 months, 9 months, and 12 months ahead of schedule were found to not affect Sanya's air quality. This research suggests that the UDR pilot has an unexpected significant effect on the coordinated control of PM2.5 and O3 pollution in Sanya. Identifying the details of the restoration in different UDR phrases will help to accurately control PM2.5 and O3, and the promotion of these restoration details to other cities may facilitate mitigating the new air environment problems currently facing China.
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Key words:
- adaptation /
- Urban Double Restoration /
- PM2.5 and O3 /
- coordinated control /
- difference-in-differences /
- program evaluation /
- Sanya
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图 1 2010—2019年三亚市和海口市经济发展状况对比
Figure 1. The annual economic development conditions of Sanya and Haikou from 2010 to 2019
图 2 “城市双修”试点前三亚市和海口市空气质量月均值的变化趋势
Figure 2. The monthly air quality trends in Sanya and Haikou before the UDR pilot
表 1 2014—2016年三亚市与海口市空气质量状况的描述性统计
Table 1. Summary statistics of air quality in Sanya and Haikou from 2014 to 2016
变量 试点前 试点后 三亚市 海口市 三亚市 海口市 平均值 标准差 平均值 标准差 平均值 标准差 平均值 标准差 AQI 41.058 8 13.259 3 41.941 2 14.393 9 36.368 4 7.987 6 42.684 2 9.741 4 PM2.5浓度/(μg/m3) 19.235 3 9.685 9 23.235 3 12.437 5 13.947 4 4.048 0 20.263 2 7.278 9 PM10浓度/(μg/m3) 35.470 6 12.258 3 41.235 3 15.130 8 28.210 5 5.422 0 38.105 3 8.943 6 SO2浓度/(μg/m3) 2.117 7 0.857 5 5.117 7 1.576 5 3.157 9 0.688 3 5.736 8 0.991 2 CO浓度/(mg/m3) 0.604 1 0.084 6 0.697 3 0.100 2 0.638 4 0.080 5 0.636 1 0.094 9 NO2浓度/(μg/m3) 13.294 1 2.931 8 13.529 4 2.648 5 12.894 7 2.536 3 15.526 3 2.715 6 O3浓度/(μg/m3) 73.411 8 20.808 8 58.352 9 19.397 0 68.421 1 13.898 0 76.105 3 14.813 3 
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表 2 “城市双修”试点对三亚市AQI月均值的平均处理效应
Table 2. The average treatment effect of the UDR on monthly AQI in Sanya
自变量 因变量（AQI月均值） 模型1 模型2 模型3 模型4 模型5 CT −5.433
(5.552)−13.37***
(2.870)−10.60***
(2.711)−10.92***
(2.686)−11.03***
(2.762)相对湿度 −2.333***
(0.269)−2.089***
(0.282)−2.075***
(0.274)−2.096***
(0.286)风速 −1.878*
(1.054)−2.680**
(1.257)−2.271*
(1.275)−2.268*
(1.290)能见度 −2.057***
(0.337)−1.406***
(0.387)−1.373***
(0.333)−1.404***
(0.349)时间固定效应 是 是 是 时间趋势 1阶 2阶 R2 0.048 0.866 0.892 0.905 0.905 注：括号内数值为稳健标准差. ***、**、*分别代表在0.01、0.05、0.10的水平上显著. 仅列出了回归系数显著的气象要素变量. 样本数量为72个.
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表 3 “城市双修”试点对三亚市6种大气污染物月均浓度的平均处理效应(基于模型5)
Table 3. The average treatment effect of the UDR pilot on monthly concentrations of six pollutants in Sanya (based on Specification 5)
自变量 因变量(月均浓度) PM2.5 PM10 SO2 CO NO2 O3 CT −7.068***
(1.713)−9.935***
(2.423)−0.335
(0.419)0.097 4***
(0.020 5)−2.266*
(1.239)−30.14***
(4.839)R2 0.931 0.925 0.889 0.906 0.645 0.892 注：括号内数值为稳健标准差. ***、**、*分别代表在0.01、0.05、0.10的水平上显著. 样本数量为72个. 下同.
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表 4 “城市双修”在试点后3个半年的动态处理效应(基于模型5)
Table 4. The dynamic treatment effect of the UDR on three half-year post-pilot phases (based on Specification 5)
自变量 因变量（月均值） AQI PM2.5 PM10 SO2 CO NO2 O3 CT1 −9.186* −4.261 −6.358 −0.118 0.0865*** −0.728 −29.08*** (4.722) (3.040) (4.136) (0.620) (0.0301) (1.723) (8.048) CT2 −11.35*** −8.578*** −12.73*** −0.204 0.113*** −3.033** −29.45*** (3.249) (1.899) (2.601) (0.561) (0.0245) (1.476) (5.578) CT3 −13.09*** −8.745*** −10.83*** −0.816 0.0904*** −3.270* −32.58*** (3.438) (1.943) (3.054) (0.510) (0.0248) (1.685) (5.753) R2 0.907 0.937 0.930 0.892 0.908 0.665 0.893
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表 5 将“城市双修”试点提前6、9、12个月的安慰剂检验(基于模型5)
Table 5. The placebo tests of advancing the UDR pilot by 6, 9, 12 months (based on Specification 5)
自变量 因变量(月均值) AQI PM2.5 PM10 SO2 CO NO2 O3 CB6 1.591 −2.340 −2.943 0.487 0.0432 3.350 9.395 (4.850) (3.770) (4.608) (0.810) (0.0414) (2.770) (6.343) [0.961] [0.966] [0.962] [0.962] [0.957] [0.800] [0.963] CB9 3.450 −0.755 0.104 0.929 0.0381 2.348 7.110 (5.146) (4.204) (5.240) (0.693) (0.0482) (2.725) (7.761) [0.963] [0.965] [0.960] [0.968] [0.954] [0.765] [0.959] CB12 6.395 1.118 4.257 0.953 0.0398 1.469 4.616 (4.864) (4.275) (4.915) (0.780) (0.0501) (2.418) (9.672) [0.967] [0.965] [0.963] [0.967] [0.954] [0.749] [0.957] 注：括号、方括号内数值分别为稳健标准差、R2. ***、**、*分别代表在0.01、0.05、0.10的水平上显著. 样本数量为34个.
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[1] 生态环境部.中国生态环境状况公报:2020[R].北京:生态环境部,2021. [2] 杨东峰,刘正莹,殷成志.应对全球气候变化的地方规划行动:减缓与适应的权衡抉择[J].城市规划,2018,42(1):35-42.YANG D F,LIU Z Y,YIN C Z.Local planning action for addressing global climate change:dilemmas between mitigation and adaptation[J].City Planning Review,2018,42(1):35-42. [3] 李红,彭良,毕方,等.我国PM2.5与臭氧污染协同控制策略研究[J].环境科学研究,2019,32(10):1763-1778.LI H,PENG L,BI F,et al.Strategy of coordinated control of PM2.5 and ozone in China[J].Research of Environmental Sciences,2019,32(10):1763-1778. [4] 马国霞,於方,张衍燊,等.《大气污染防治行动计划》实施效果评估及其对我国人均预期寿命的影响[J].环境科学研究,2019,32(12):1966-1972.MA G X,YU F,ZHANG Y S,et al.Effect of implementation of the Action Plan on Prevention and control of air pollution and its impact on life expectancy in China[J].Research of Environmental Sciences,2019,32(12):1966-1972. [5] 王晓元,江飞,徐圣辰,等.长三角区域大气重污染应急减排效果评估[J].环境科学研究,2020,33(4):783-791.WANG X Y,JIANG F,XU S C,et al.Assessment of emergency emission reduction effect during a severe air pollution episode in Yangtze River Delta Region[J].Research of Environmental Sciences,2020,33(4):783-791. [6] 杜雯翠,夏永妹.京津冀区域雾霾协同治理措施奏效了吗?基于双重差分模型的分析[J].当代经济管理,2018,40(9):53-59.DU W C,XIA Y M.Did the measures of haze cooperative governance in Beijing-Tianjin-Hebei Region work:an analysis based on the DID model[J].Contemporary Economic Management,2018,40(9):53-59. [7] 杨斯悦,王凤,刘娜.《大气污染防治行动计划》实施效果评估:双重差分法[J].中国人口·资源与环境,2020,30(5):110-117.YANG S Y,WANG F,LIU N.Assessment of the air pollution prevention and control action plan in China:a difference-in-difference analysis[J].China Population,Resources and Environment,2020,30(5):110-117. [8] 毛显强,张庆勇.“2+26”城市治霾方案效果评估:以山东省为案例的研究[J].中国人口·资源与环境,2020,30(3):83-92.MAO X Q,ZHANG Q Y.Evaluation of the effectiveness of ‘2 + 26’ cities' haze control scheme:a case study of Shandong Province[J].China Population,Resources and Environment,2020,30(3):83-92. [9] 赵肖肖,唐湘博.区域大气污染防治特护期实施方案效果评估[J].环境科学与技术,2020,43(3):221-227.ZHAO X X,TANG X B.Evaluation of the effect of the implementation scheme for special protection period of regional air pollution prevention and control[J].Environmental Science & Technology (China),2020,43(3):221-227. [10] DAVIS L W.The effect of driving restrictions on air quality in Mexico City[J].Journal of Political Economy,2008,116(1):38-81. doi: 10.1086/529398 [11] GALLEGO F,MONTERO J P,SALAS C.The effect of transport policies on car use:evidence from Latin American cities[J].Journal of Public Economics,2013,107:47-62. doi: 10.1016/j.jpubeco.2013.08.007 [12] 曹静,王鑫,钟笑寒.限行政策是否改善了北京市的空气质量?[J].经济学,2014,13(3):1091-1126.CAO J,WANG X,ZHONG X H.Did driving restriction improve air quality in Beijing?[J].China Economic Quarterly,2014,13(3):1091-1126. [13] CARRILLO P E,MALIK A S,YOO Y.Driving restrictions that work? Quito's Pico y Placa Program[J].Canadian Journal of Economics,2016,49(4):1536-1568. doi: 10.1111/caje.12243 [14] CHEN Y Y,JIN G Z,KUMAR N,et al.The promise of Beijing:evaluating the impact of the 2008 Olympic Games on air quality[J].Journal of Environmental Economics and Management,2013,66(3):424-443. doi: 10.1016/j.jeem.2013.06.005 [15] VIARD V B,FU S H.The effect of Beijing's driving restrictions on pollution and economic activity[J].Journal of Public Economics,2015,125:98-115. doi: 10.1016/j.jpubeco.2015.02.003 [16] LIU Z,KONG H Y.New evidence of the effect of Beijing's driving restriction and other Olympic-year policies on air pollution[J].The B. E. Journal of Economic Analysis & Policy,2021,21(1):241-272. [17] LI S J,LIU Y Y,PUREVJAV A O,et al.Does subway expansion improve air quality?[J].Journal of Environmental Economics and Management,2019,96:213-235. doi: 10.1016/j.jeem.2019.05.005 [18] 郭施宏,陈丽强.轨道交通运营的大气污染减排效应评估:一个准自然试验设计[J].东北大学学报(社会科学版),2019,21(5):462-469.GUO S H,CHEN L Q.An assessment of rail transit operation effects on air pollution reduction:a quasi-experimentation[J].Journal of Northeastern University (Social Science),2019,21(5):462-469. [19] ZHENG M N,GUO X C,LIU F,et al.Contribution of subway expansions to air quality improvement and the corresponding health implications in Nanjing,China[J].International Journal of Environmental Research and Public Health,2021,18(3):969. doi: 10.3390/ijerph18030969 [20] 杨小聪,彭飞,康丽丽.绿色地铁:轨道交通对空气污染的净化效果评估:基于南京地铁3号线的实证研究[J].甘肃行政学院学报,2017(4):82-94. doi: 10.3969/j.issn.1009-4997.2017.04.009YANG X C,PENG F,KANG L L.Green metro:the effects of new metro line 3 on air quality in Nanjing[J].Journal of Gansu Administration Institute,2017(4):82-94. doi: 10.3969/j.issn.1009-4997.2017.04.009 [21] 谌仁俊,谢欢艳,林宇聪.推行共享单车和轨道交通是否改善了空气质量:以武汉为例[J].中国地质大学学报(社会科学版),2018,18(4):95-110.SHEN R J,XIE H Y,LIN Y C.Can popularity of rail transit and bike-sharing improve air quality?a case study on Wuhan City[J].Journal of China University of Geosciences (Social Sciences Edition),2018,18(4):95-110. [22] ZHENG S Q,ZHANG X N,SUN W Z,et al.The effect of a new subway line on local air quality:a case study in Changsha[J].Transportation Research Part D:Transport and Environment,2019,68:26-38. doi: 10.1016/j.trd.2017.10.004 [23] CHEN Y,WHALLEY A.Green infrastructure:the effects of urban rail transit on air quality[J].American Economic Journal:Economic Policy,2012,4(1):58-97. doi: 10.1257/pol.4.1.58 [24] GOEL D,GUPTA S.The effect of metro expansions on air pollution in Delhi[J].The World Bank Economic Review,2015,31(1):271-294. [25] AUFFHAMMER M,KELLOGG R.Clearing the air?the effects of gasoline content regulation on air quality[J].American Economic Review,2011,101(6):2687-2722. doi: 10.1257/aer.101.6.2687 [26] 王敏,冯相昭,杜晓林,等.基于双重差分模型的清洁取暖补贴效果量化评估[J].环境与可持续发展,2020,45(3):21-27.WANG M,FENG X Z,DU X L,et al.Quantitative evaluation on the effect of clean heating subsidy based on DID estimation[J].Environment and Sustainable Development,2020,45(3):21-27. [27] 柴发合,王晓,罗宏,等.美国与欧盟关于PM2.5和臭氧的监管政策述评[J].环境工程技术学报,2013,3(1):46-52.CHAI F H,WANG X,LUO H,et al.Review of supervision policies of USA and European Union on PM2.5 and O3[J].Journal of Environmental Engineering Technology,2013,3(1):46-52. [28] 王磊,黄利斌,万欣,等.城市森林对大气颗粒物(尤其PM2.5)调控作用研究进展[J].南京林业大学学报(自然科学版),2016,40(5):148-154.WANG L,HUANG L B,WAN X,et al.Progress on the regulating effects of urban forest vegetation on atmospheric particulate matter(especially PM2.5)[J].Journal of Nanjing Forestry University (Natural Sciences Edition),2016,40(5):148-154. [29] 仲崇毅,锺佩伶,李芳胤,等.植物对氮氧化物及硫氧化物净化效能评估[J].中华林学季刊,2007,40(4):497-507. -
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