Study on Emission Reduction Effect of Urban Agglomeration Network Spatial Structure on Air Pollution
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摘要: 探究城市群网络化空间结构演化及减排效应是提升城市群环境质量的重要支撑. 本文基于2004—2020年中国14个城市群的动态面板数据，采用社会网络分析方法总结城市群网络空间结构及多重嵌套特征，进而构建实证模型纠偏最小二乘法(LSDVC)检验城市群网络空间结构的大气污染减排效应，并引入嵌套型与非嵌套型城市群的异质性分析，最后探讨了城市群产业分工水平的中介影响机制. 结果表明：①我国城市群空间结构具有明显的网络化趋势，但各城市群之间存在显著差距，其中长三角城市群、长江中游城市群和珠三角城市群的网络空间结构已经出现了多重嵌套特征. ②城市群网络空间结构具有显著的大气污染减排效应，且相对于非嵌套型城市群，嵌套型城市群的减排效应更显著. ③产业分工水平对于城市群的大气污染减排效应存在中介影响机制，优化城市群产业分工布局有利于大气污染减排. 研究显示，发展多重嵌套、分工明确、联系紧密、功能互补的城市群网络空间结构有助于强化区域协同合作，提升环境污染治理能力，推动城市群绿色发展.Abstract: Exploring the evolution of network spatial structure and emission reduction effect of urban agglomerations is an indispensable support to improve the environmental quality of urban agglomerations. Based on the dynamic panel data of 14 urban agglomerations in China from 2004 to 2020, this paper uses social network analysis to summarize the network spatial structure and multiple nesting characteristics of urban agglomerations, constructs the empirical model LSDVC to test the air pollution emission reduction effect of urban agglomerations network spatial structure, and introduce the heterogeneity analysis of nested and non-nested urban agglomerations. Ultimately, the paper shows the intermediary influence mechanism of industrial division of labor in urban agglomerations. The results show that: (1) The spatial structure of urban agglomerations in China has an obvious trend of networking, but there are significant gaps between urban agglomerations. Among them, the Yangtze River Delta urban agglomeration, the middle reaches of Yangtze River urban agglomeration, and the Pearl River Delta urban agglomeration, etc., have multiple nested characteristics. (2) The network spatial structure of urban agglomerations has a critical air pollution emission reduction effect, and the emission reduction effect of nested urban agglomerations is more significant than non-nested ones. (3) The level of industrial division of labor has a mediating influence mechanism on the air pollution emission reduction effect of urban agglomerations, and optimizing the industrial division of labor in urban agglomerations is conducive to reducing air pollution. Therefore, the development of multiple nested, clear division of labor, close connection, and complementary functions of the network spatial structure of urban agglomerations can help strengthen regional cooperation, enhance the capacity of environmental pollution management, and promote the green development of urban agglomerations.
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图 1 2004—2020年中国14个城市群PM2.5年均浓度变化情况
注：圈中数值表示各城市群PM2.5年均浓度，单位为μg/m3.
Figure 1. Annual average PM2.5 concentration change in 14 urban agglomerations in China from 2004 to 2020
图 2 长三角城市群、长江中游城市群及珠三角城市群的网络空间格局分析
Figure 2. Analysis of the network spatial pattern of the Yangtze River Delta urban agglomeration, the middle reaches of the Yangtze River and the Pearl River Delta urban agglomeration
表 1 相关变量的描述性统计
Table 1. Descriptive statistics of related variables
变量名称 定义 单位 平均值 标准差 最小值 最大值 $ \ln\;{\rm{AP}} $ PM2.5浓度 μg/m3 3.768 0.265 3.028 4.300 $ \ln\;{\rm{ND}} $ 网络密度 % −1.254 0.731 −3.367 0.000 $ \ln\;{\rm{PD}} $ 人口密度 人/km2 6.608 0.430 5.371 7.345 $ \ln\;{\rm{EO}} $ 经济开放程度 % −3.533 0.615 −5.521 −1.957 $ \ln\;{\rm{ST}} $ 科技进步水平 % −3.657 1.072 −7.419 −2.152 $ \ln\;{\rm{ER}} $ 环境规制水平 % −0.396 0.588 −1.347 1.887 $ \ln\;{\rm{IP}} $ 产业结构水平 % −0.779 0.147 −1.280 −0.492 $ \ln\;{\rm{DIV}} $ 产业分工水平 % 0.630 0.588 −1.347 1.887 
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表 2 中国14个城市群整体网络密度
Table 2. Overall network density of 14 urban agglomerations in China
城市群 网络密度 2004年 2008年 2012年 2016年 2020年 长三角城市群 0.232 0.346 0.485 0.605 0.674 长江中游城市群 0.057 0.093 0.179 0.220 0.287 成渝城市群 0.142 0.238 0.350 0.467 0.588 山东半岛城市群 0.188 0.342 0.454 0.629 0.700 珠三角城市群 0.764 0.889 0.931 1.000 1.000 海峡西岸城市群 0.055 0.076 0.113 0.221 0.313 哈长城市群 0.133 0.200 0.300 0.322 0.278 京津冀城市群 0.203 0.275 0.330 0.462 0.528 中原城市群 0.035 0.089 0.150 0.249 0.365 关中平原城市群 0.056 0.133 0.244 0.244 0.256 辽中南城市群 0.431 0.556 0.708 0.667 0.694 北部湾城市群 0.044 0.122 0.222 0.378 0.522 呼包鄂榆城市群 0.083 0.250 0.417 0.417 0.500 晋中城市群 0.200 0.200 0.350 0.350 0.400
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表 3 城市群网络空间结构对大气污染的实证检验结果
Table 3. Empirical test results of urban agglomeration network spatial structure on air pollution
解释变量 差分GMM 系统GMM LSDVC $ \ln\;{\rm{A}}{{\rm{P}}_{{y} ,t - 1}} $ 0.346***
(0.149)0.481***
(0.334)0.579***
(0.056)$ \ln\;{\rm{ND}} $ −0.035
(0.065)0.059
(0.052)−0.040***
(0.016)$ \ln\;{\rm{PD}} $ −0.789
(0.504)−0.252
(0.161)−0.034
(0.062)$ \ln\;{\rm{EO}} $ 0.012
(0.013)0.072
(0.062)0.009
(0.011)$ \ln\;{\rm{ST}} $ 0.011
(0.011)0.022**
(0.010)0.023***
(0.006)$ \ln\;{\rm{ER}} $ −0.277**
(0.138)−0.210
(0.185)−0.070**
(0.030)$ \ln\;{\rm{IP}} $ 0.977***
(0.327)0.489
(0.435)0.384***
(0.079)常数项 4.330*
(2.584)AR(1) Test 0.025 0.051 AR(2) Test 0.916 0.809 Sargan Tset 0.025 0.336 城市群数 14 14 14 观测值数 210 224 224 注：***、**、*分别代表在1%、5%、10%的水平下显著. 括号内数值为标准差. AR(1) Test与AR(2) Test均为自相关检验. Sargan Test为过度识别检验. 下同.
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表 4 嵌套与非嵌套城市群划分
Table 4. Division of nested and non-nested urban agglomeration
城市群类型 城市群名称 嵌套城市群 长三角城市群、长江中游城市群、成渝城市群、山东半岛城市群、珠三角城市群、海峡西岸城市群、哈长城市群、京津冀城市群、辽中南城市群 非嵌套城市群 中原城市群、关中平原城市群、北部湾城市群、呼包鄂榆城市群、晋中城市群
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表 5 嵌套与非嵌套型城市群实证结果分析
Table 5. Empirical analysis of nested and non-nested urban agglomerations
解释变量 ln AP $ \ln\;{\rm{A}}{{\rm{P}}_{{y} ,t - 1}} $ 0.570***
(0.056)$ \ln\;{\rm{ND}} $ −0.068***
(0.022)$ \ln\;{\rm{ND}} $×F 0.047*
(0.026)$ \ln\;{\rm{{\rm{PD}}}} $ −0.081
(0.067)$ \ln\;{\rm{EO}} $ 0.009
(0.011)$ \ln\;{\rm{ST}} $ 0.024***
(0.006)$ \ln\;{\rm{ER}} $ −0.069**
(0.030)$ \ln\;{\rm{IP}} $ 0.388***
(0.079)观测值数 224
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表 6 产业分工水平的中介效应检验结果分析
Table 6. Analysis of the mediating effect test results of industrial division level
解释变量 ln AP(模型5) ln DIV(模型6) ln AP(模型7) $ \ln\;{\rm{A}}{{\rm{P}}_{{y} ,t - 1}} $ 0.579***
(0.056)0.554***
(0.056)$ \ln\;{\rm{ND}} $ −0.040***
(0.156)0.111**
(0.043)−0.036**
(0.016)$ \ln\;{\rm{DIV}} $ −0.053**
(0.023)$ \ln\;{\rm{PD}} $ −0.034
(0.062)0.639***
(0.179)−0.003
(0.063)$ \ln\;{\rm{EO}} $ 0.009
(0.011)−0.015
(0.032)0.010
(0.010)$ \ln\;{\rm{ST}} $ 0.023***
(0.006)0.044**
(0.018)0.027***
(0.007)$ \ln\;{\rm{ER}} $ −0.070**
(0.299)0.156**
(0.079)−0.061**
(0.030)$ \ln\;{\rm{IP}} $ 0.384***
(0.079)0.640***
(0.224)0.364***
(0.079)常数项 −3.782***
(1.229)观测值数 224 238 224 $ {{R} ^2} $ 0.214
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[1] LI L,MA S J,ZHENG Y L,et al.Integrated regional development:comparison of urban agglomeration policies in China[J].Land Use Policy,2022,114:105939. doi: 10.1016/j.landusepol.2021.105939 [2] LIU P,QIN Y,LUO Y Y,et al.Structure of low-carbon economy spatial correlation network in urban agglomeration[J].Journal of Cleaner Production,2023,394:136359. doi: 10.1016/j.jclepro.2023.136359 [3] LIU K,XUE Y T,CHEN Z F,et al.Economic spatial structure of China ′s urban agglomerations:regional differences,distribution dynamics,and convergence[J].Sustainable Cities and Society,2022,87:104253. doi: 10.1016/j.scs.2022.104253 [4] 束韫,李海生,张文杰,等.2030年京津冀及周边城市群PM2.5污染控制路径[J].环境科学研究,2023,36(3):439-448.SHU Y,LI H S,ZHANG W J,et al.PM2.5 pollution control pathways in Beijing-Tianjin-Hebei and surrounding urban areas in 2030[J].Research of Environmental Sciences,2023,36(3):439-448. [5] 徐雯丽,陈强强.黄河流域城市PM2.5时空分异特征及污染物解析[J].环境科学研究,2023,36(4):637-648.XU W L,CHEN Q Q.Spatial-temporal variation characteristics and pollutants analysis of urban PM2.5 in the Yellow River Basin[J].Research of Environmental Sciences,2023,36(4):637-648. [6] ZHANG Z H,ZHANG G X,SONG S F,et al.Spatial heterogeneity influences of environmental control and informal regulation on air pollutant emissions in China[J].International Journal of Environmental Research and Public Health,2020,17(13):4857. doi: 10.3390/ijerph17134857 [7] LI H,LU J.Can inter-governmental coordination inhibit cross-border illegal water pollution?a test based on cross-border ecological compensation policy[J].Journal of Environmental Management,2022,318:115536. doi: 10.1016/j.jenvman.2022.115536 [8] SONG J H,ABUDUWAYITI A,GOU Z H.The role of subway network in urban spatial structure optimization:Wuhan City as an example[J].Tunnelling and Underground Space Technology,2023,131:104842. doi: 10.1016/j.tust.2022.104842 [9] SONG Y,ZHU J,YUE Q,et al.Industrial agglomeration,technological innovation and air pollution:empirical evidence from 277 prefecture-level cities in China[J].Structural Change and Economic Dynamics,2023,66:240-252. doi: 10.1016/j.strueco.2023.05.003 [10] 李国平.着力打造长三角多中心网络化空间结构[J].人民论坛·学术前沿,2019(4):20-26.LI G P.Focus on building a multi-center networked spatial structure in the Yangtze River Delta[J].Frontiers,2019(4):20-26. [11] 李国平,孙铁山.网络化大都市:城市空间发展新模式[J].城市发展研究,2013,20(5):83-89.LI G P,SUN T S.Networked metropolis:a new urban spatial development model[J].Urban Development Studies,2013,20(5):83-89. [12] FUJITA M,THISSE J F,ZENOU Y.On the endogeneous formation of secondary employment centers in a city[J].Journal of Urban Economics,1997,41(3):337-357. doi: 10.1006/juec.1996.2002 [13] 胡小武.城市群的空间嵌套形态与区域协同发展路径:以长三角城市群为例[J].上海城市管理,2017,26(2):18-23.HU X W.Spatial nested form of urban agglomeration and path of regional coordinated development:a case study of Yangtze River Delta urban agglomeration[J].Shanghai Urban Management,2017,26(2):18-23. [14] QIU P P,ZHANG L,WANG X S,et al.A new approach of air pollution regionalization based on geographically weighted variations for multi-pollutants in China[J].Science of the Total Environment,2023,873:162431. doi: 10.1016/j.scitotenv.2023.162431 [15] ALBERTI M.The effects of urban patterns on ecosystem function[J].International Regional Science Review,2005,28(2):168-192. doi: 10.1177/0160017605275160 [16] ZHAO L Y,LIU C X,LIU X J,et al.Urban spatial structural options for air pollution control in China:evidence from provincial and municipal levels[J].Energy Reports,2021,7:93-105. doi: 10.1016/j.egyr.2021.10.050 [17] 彭梦杰,柳力玮,周毓文,等.山东半岛城市群空间结构演化的大气环境效应研究[J].环境与发展,2020,32(5):8-9.PENG M J,LIU L W,ZHOU Y W,et al.Study on the atmospheric environmental effect of the spatial structure evolution of Shandong peninsula urban agglomeration[J].Environment and Development,2020,32(5):8-9. [18] ZHANG W X,WANG B,WANG J,et al.How does industrial agglomeration affect urban land use efficiency?a spatial analysis of Chinese cities[J].Land Use Policy,2022,119:106178. doi: 10.1016/j.landusepol.2022.106178 [19] LIU X M,REN T,GE J,et al.Heterogeneous and synergistic effects of environmental regulations:theoretical and empirical research on the collaborative governance of China´s haze pollution[J].Journal of Cleaner Production,2022,350:131473. doi: 10.1016/j.jclepro.2022.131473 [20] WU K,FANG C L,HUANG H B,et al.Comprehensive delimitation and ring identification on urban spatial radiation of regional central cities:case study of Zhengzhou[J].Journal of Urban Planning and Development,2013,139(4):258-273. doi: 10.1061/(ASCE)UP.1943-5444.0000120 [21] 赵勇,白永秀.中国城市群功能分工测度与分析[J].中国工业经济,2012(11):18-30.ZHAO Y,BAI Y X.Measuring and analyzing the functional specialization of Chinese urban agglomeration[J].China Industrial Economics,2012(11):18-30. [22] SCOTT A J.Global city-regions:trends,theory,policy[J].Progress in Human Geography,2002,26(5):712-713. doi: 10.1177/030913250202600533 [23] 张懿华.长三角地区PM2.5区域性污染时空变化特征[J].环境科学研究,2022,35(1):1-10.ZHANG Y H.Spatial-temporal characteristics of PM2.5 regional pollution in Yangtze River Delta Region[J].Research of Environmental Sciences,2022,35(1):1-10. [24] 宋德勇,李东方.国家级城市群高质量平衡增长研究:基于产业分工的视角[J].经济经纬,2021,38(1):5-14.SONG D Y,LI D F.A study on high-quality balanced growth of national urban agglomerations:based on the perspective of industrial division of labor[J].Economic Survey,2021,38(1):5-14. [25] LI L,LIU X M,GE J J,et al.Regional differences in spatial spillover and hysteresis effects:a theoretical and empirical study of environmental regulations on haze pollution in China[J].Journal of Cleaner Production,2019,230:1096-1110. doi: 10.1016/j.jclepro.2019.04.248 [26] 王妤,孙斌栋,李琬.城市规模分布与空气质量的关系:基于LandScan数据的跨国研究[J].地理研究,2021,40(11):3173-3190.WANG Y,SUN B D,LI W.Relationship between city size distribution and air quality:a cross-country study based on LandScan data[J].Geographical Research,2021,40(11):3173-3190. [27] 陈德敏,张瑞,谭志雄.全要素能源效率与中国经济增长收敛性:基于动态面板数据的实证检验[J].中国人口·资源与环境,2012,22(1):130-137.CHEN D M,ZHANG R,TAN Z X.Total factor energy efficiency and regional economic convergence in China:an empirical analysis based on dynamic panel data model[J].China Population,Resources and Environment,2012,22(1):130-137. [28] CHEN J D,WANG B,HUANG S,et al.The influence of increased population density in China on air pollution[J].Science of the Total Environment,2020,735:139456. doi: 10.1016/j.scitotenv.2020.139456 [29] OMRI A,BEL H T.Foreign investment and air pollution:do good governance and technological innovation matter?[J].Environmental Research,2020,185:109469. doi: 10.1016/j.envres.2020.109469 [30] WANG J L,WANG W L,LIU Y,et al.Can industrial robots reduce carbon emissions?based on the perspective of energy rebound effect and labor factor flow in China[J].Technology in Society,2023,72:102208. doi: 10.1016/j.techsoc.2023.102208 [31] ZHANG G X,JIA Y Q,SU B,et al.Environmental regulation,economic development and air pollution in the cities of China:spatial econometric analysis based on policy scoring and satellite data[J].Journal of Cleaner Production,2021,328:129496. doi: 10.1016/j.jclepro.2021.129496 [32] ZHENG Y,PENG J C,XIAO J Z,et al.Industrial structure transformation and provincial heterogeneity characteristics evolution of air pollution:evidence of a threshold effect from China[J].Atmospheric Pollution Research,2020,11(3):598-609. doi: 10.1016/j.apr.2019.12.011 [33] CHEN X L,DI Q B,JIA W H,et al.Spatial correlation network of pollution and carbon emission reductions coupled with high-quality economic development in three Chinese urban agglomerations[J].Sustainable Cities and Society,2023,94:104552. doi: 10.1016/j.scs.2023.104552 [34] 锁利铭,阚艳秋.战略赋能、多重嵌套与区域合作网络结构变迁:以“泛珠三角”和“粤港澳大湾区”为例[J].上海行政学院学报,2021,22(5):78-90.SUO L M,KAN Y Q.Strategic empowerment,multiple nesting and structural change of regional collaborative network:evidence from ‘pan-pearl river delta’ and ‘Guangdong-hong Kong-Macao Greater Bay Area’[J].The Journal of Shanghai Administration Institute,2021,22(5):78-90. [35] 邵帅,张可,豆建民.经济集聚的节能减排效应:理论与中国经验[J].管理世界,2019,35(1):36-60. doi: 10.3969/j.issn.1002-5502.2019.01.004SHAO S,ZHANG K,DOU J M.Effect of economic agglomeration on energy saving and emission reduction:theory and China experience[J].Journal of Management World,2019,35(1):36-60. doi: 10.3969/j.issn.1002-5502.2019.01.004 -
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