自然资源学报 ›› 2021, Vol. 36 ›› Issue (3): 737-751.doi: 10.31497/zrzyxb.20210315
收稿日期:
2019-09-05
修回日期:
2020-03-25
出版日期:
2021-03-28
发布日期:
2021-05-28
通讯作者:
周年兴
E-mail:junzailinyi@gmail.com;09182@njnu.edu.cn
作者简介:
李在军(1989- ),男,山东临沂人,博士,助理研究员,研究方向为区域经济发展。E-mail: 基金资助:
LI Zai-jun1(), HU Mei-juan2, ZHANG Ai-ping3, ZHOU Nian-xing2(
)
Received:
2019-09-05
Revised:
2020-03-25
Online:
2021-03-28
Published:
2021-05-28
Contact:
ZHOU Nian-xing
E-mail:junzailinyi@gmail.com;09182@njnu.edu.cn
摘要:
针对2004—2016年中国地级市工业生态效率与PM2.5的时空关联特征和影响作用关系的研究表明:(1)工业生态效率与PM2.5呈时空交错分布特征,PM2.5高污染区连片分布于华北平原及长江中下游城市,工业生态效率高等级区集中分布于长三角、珠三角和环渤海经济区等沿海地市及中西部城市群内部分中心地市;(2)工业生态效率对PM2.5的冲击表现出“U型”变化的负向累积效应,PM2.5对工业生态效率的冲击则表现为“倒U型”变化的正向累积效应;(3)工业生态效率与PM2.5呈稳定时空关联演化特征,高高关联类型区集中分布于京津冀城市群、山东半岛城市群和长三角城市群内大部分城市,低低关联类型区多分布于鄱阳湖城市群、关中城市群及西部地市;(4)工业生态效率对PM2.5总体上具有显著且稳健的正向影响,但表现出明显的空间异质性,工业集聚水平、科技创新及城市绿化率起到显著负向影响,而城市规模、环保监督及产业结构系数影响并不显著。
李在军, 胡美娟, 张爱平, 周年兴. 工业生态效率对PM2.5污染的影响及溢出效应[J]. 自然资源学报, 2021, 36(3): 737-751.
LI Zai-jun, HU Mei-juan, ZHANG Ai-ping, ZHOU Nian-xing. Influence and spillover effect of industrial eco-efficiency on PM2.5 pollution[J]. JOURNAL OF NATURAL RESOURCES, 2021, 36(3): 737-751.
表1
各变量的描述性统计"
变量 | 指标 | 变量代码 | 均值 | 标准差 | 最大值 | 最小值 | 观测值 |
---|---|---|---|---|---|---|---|
雾霾污染 | PM2.5平均浓度 | PM2.5 | 36.85 | 16.39 | 90.86 | 4.52 | 3679 |
工业生态效率 | 随机前沿效率 | Iee | 0.67 | 0.11 | 0.99 | 0.31 | 3679 |
城市规模水平 | 人口密度/(人/km2) | Den | 424.79 | 327.69 | 2661.54 | 4.7 | 3679 |
工业集聚水平 | 工业密度/(万元/km2) | Aggl | 0.01 | 0.23 | 13.92 | 0.001 | 3679 |
环境保护监督 | 信息化水平/(数/万人) | Lit | 1.09 | 1.09 | 13.09 | 0.03 | 3679 |
科学技术创新 | 科技与教育支出占财政支出占比/% | Tec | 19.88 | 5.62 | 186.86 | 1.58 | 3679 |
产业结构系数 | 第三产业产值/第二产业产值 | Ind | 82.12 | 41.29 | 948.22 | 0.09 | 3679 |
生态环境禀赋 | 建成区绿化覆盖率/% | Gcba | 37.24 | 14.53 | 386.64 | 0.36 | 3679 |
表4
2004—2016年PM2.5与工业生态效率空间相关系数"
年份 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Moran's I | 0.0813 | 0.0702 | 0.0729 | 0.0664 | 0.0873 | 0.0806 | 0.0715 | 0.0811 | 0.0714 | 0.0727 | 0.0782 | 0.0780 | 0.0793 |
Z | 3.385 | 2.942 | 3.001 | 2.726 | 3.912 | 3.490 | 3.099 | 3.698 | 2.971 | 3.250 | 3.494 | 3.805 | 3.748 |
P | 0.001 | 0.001 | 0.001 | 0.001 | 0.001 | 0.001 | 0.001 | 0.001 | 0.001 | 0.001 | 0.001 | 0.001 | 0.001 |
表5
SDM模型估计结果"
变量 | 空间固定效应 | 时间固定效应 | 时空固定效应 |
---|---|---|---|
lnIee | 0.1942(1.73) * | -0.1114(-2.46) ** | 0.2430(2.13) ** |
lnDen | -0.0032(-0.30) | 0.2890(18.85) *** | -0.0065(-0.60) |
lnAggl | -0.0089(-1.27) | 0.1134(7.81) *** | -0.0151(-2.08) ** |
lnLit | -0.0037(-0.43) | -0.3112(-17.74) *** | -0.0089(-0.99) |
lnTec | -0.0366(-3.99) *** | -0.0184(-0.86) | -0.0435(-4.63) *** |
lnInd | -0.0003(-0.05) | 0.0635(4.22) *** | 0.0001(0.00) |
lnGcba | -0.0092(-1.70) * | 0.0704(4.92) ** | -0.0124(-2.27) ** |
W×lnIee | -0.3316(-1.86) * | -0.3810(-2.82) | 0.2148(0.77) |
W×lnDen | -0.0622(-2.38) ** | -0.0685(-1.77) | -0.0725(-2.74) *** |
W×lnAggl | 0.0074(0.95) | 0.067(2.06) | -0.0879(-3.52) *** |
W×lnLit | 0.0239(1.99) ** | -0.0636(-1.34) | -0.0224(-0.92) |
W×lnTec | -0.0159(-0.86) | -0.3249(-5.62) | -0.0771(-3.11) *** |
W×lnInd | 0.049(3.54) *** | 0.091(2.16) | 0.0535(2.30) ** |
W×lnGcba | 0.0254(1.77) * | 0.0154(0.37) | -0.0032(-0.21) |
Rho | 0.852(59.89) *** | 0.362(13.38) | 0.7190(36.04) *** |
σ2 | 0.0071 | 0.0870 | 0.0072 |
R2 | 0.9716 | 0.6540 | 0.9713 |
LMlag | 3618.142*** | 310.805*** | 991.272*** |
R-LMlag | 34.758*** | 83.192*** | 49.643*** |
LMerror | 3591.523*** | 227.845*** | 968.440*** |
R-LMerror | 8.138*** | 0.232 | 26.811*** |
LR检验 | 9039.461*** | 1300.739*** |
表6
SDM直接效应和间接效应估计"
变量 | 直接效应 | 间接效应 | 总效应 |
---|---|---|---|
lnIee | 0.2919(2.442) ** | 1.3598(1.446) | 1.6517(1.682) * |
lnDen | -0.0162(-1.350) | -0.2645(-2.815) *** | -0.2807(-2.809) ** |
lnAggl | -0.0284(-3.427) *** | -0.3462(-4.012) *** | -0.3745(-4.122) *** |
lnLit | -0.0122(-1.213) | -0.0940(-1.072) | -0.1063(-1.143) |
lnTec | -0.0576(-5.530) *** | -0.3738(-4.367) *** | -0.4315(-4.787) *** |
lnInd | 0.0068(0.787) | 0.1812(2.264) ** | 0.1879(2.223) ** |
lnGcba | -0.014(-2.285)** | -0.0409(-0.749) | -0.0549(-0.945) |
表7
动态SDM模型估计结果"
变量 | 空间固定效应 | 时间固定效应 | 时空固定效应 |
---|---|---|---|
lnPM2.5(t-1) | 1.0571(158.55) *** | 0.3137(17.68) *** | |
W×lnPM2.5(t-1) | 0.2621(11.66) *** | -0.0821(-2.05) ** | |
lnIee | 0.1395(2.19) ** | 0.0357(3.84) *** | 0.1308(2.08) ** |
lnDen | 0.0057(0.53) | -0.0080(-1.24) | 0.0019(0.18) |
lnAggl | -0.0083(-1.13) | -0.0271(-4.58) *** | -0.0119(-1.62) |
lnLit | -0.0126(-1.40) | 0.0110(1.50) | -0.0124(-1.36) |
lnTec | -0.0380(-4.00) *** | 0.0011(0.13) | -0.0473(-4.99) *** |
lnInd | -0.0031(-0.40) | -0.0006(-0.09) | 0.0048(0.61) |
lnGcba | -0.0132(-2.26) ** | 0.0008(0.14) | -0.0116(-2.00) ** |
W×lnIee | 0.1526(1.53) | 0.2823(10.14) *** | 0.0440(0.29) |
W×lnDen | -0.0331(-1.27) | -0.0608(-3.97) *** | -0.0511(-1.99) ** |
W×lnAggl | 0.0064(0.78) | -0.1335(-9.77) *** | -0.0398(-1.51) |
W×lnLit | -0.0453(-3.36) *** | 0.2367(11.60) *** | -0.0247(-0.99) |
W×lnTec | 0.0006(0.03) | 0.1813(7.51) *** | -0.0338(-1.32) |
W×lnInd | 0.0204(1.44) | -0.0434(-2.49) ** | 0.0396(1.65) * |
W×lnGcba | 0.0101(0.63) | 0.0479(2.74) *** | 0.0003(0.02) |
Rho | 0.8598(46.29) *** | 0.3815(22.46) *** | 0.6910(28.92) *** |
σ2 | 0.0074 | 0.0142 | 0.0073 |
R2 | 0.1650 | 0.9910 | 0.7530 |
表8
动态空间杜宾模型效应分解"
变量 | 短期直接效应 | 短期间接效应 | 长期直接效应 | 长期间接效应 |
---|---|---|---|---|
lnIee | 0.3077(2.53)** | 0.8701(0.96) | 0.5108(2.45) ** | 6.1439(0.32) |
lnDen | -0.0043(-0.39) | -0.1607(-2.00)** | -0.0145(-0.63) | -0.9902(-0.25) |
lnAggl | -0.0174(-2.12)** | -0.1467(-1.68)* | -0.0333(-2.13) ** | -0.8240(-0.55) |
lnLit | -0.0162(-1.60) | -0.1100(-1.37) | -0.0293(-1.55) | -0.4930(-0.29) |
lnTec | -0.0551(-5.12)*** | -0.2054(-2.58)*** | -0.0940(-3.15) *** | -1.4578(-0.22) |
lnInd | 0.0099(1.20) | 0.1362(1.71)* | 0.0223(0.75) | 1.0015(0.15) |
lnGcba | -0.0120(-1.84)* | -0.0226(-0.42) | -0.0193(-1.61) | -0.1552(-0.20) |
表9
分地区空间滞后回归结果"
变量 | 东部 | 中部 | 西部 | 东北 |
---|---|---|---|---|
lnIee | -0.5477(-4.68) *** | 0.0191(0.31) | 0.1668(2.61) *** | 0.4361(4.60) *** |
lnDen | 0.1853(8.39) *** | 0.4342(33.66) *** | 0.4111(27.27) *** | 0.2798(16.08) *** |
lnAggl | 0.1284(10.41) *** | 0.0014(0.18) | -0.0362(-3.03) *** | 0.0985(8.77) *** |
lnLit | -0.2079(-8.28) *** | -0.1071(-6.53) *** | -0.0722(-3.04) *** | -0.0802(-2.62) *** |
lnTec | -0.3653(-7.14) *** | -0.0043(-0.17) | 0.2415(7.5) *** | -0.0516(-1.58) |
lnInd | -0.3425(-9.46) *** | -0.0037(-0.27) | -0.0276(-1.36) | 0.1078(5.38) *** |
lnGcba | 0.1541(3.22) ** | 0.0925(3.93) *** | 0.0099(0.56) | -0.078(-2.55) ** |
Rho | -0.087(-1.72) ** | 0.137(3.43) *** | -0.04(-1.06) | 0.008(0.19) |
σ2 | 0.1132 | 0.0260 | 0.0684 | 0.0241 |
R2 | 0.4324 | 0.7335 | 0.7305 | 0.8328 |
LR | 336.4115*** | 252.6049*** | 167.4672*** | 219.2451*** |
Hausman | -492.7477*** | 14.8111* | 60.1267*** | 2695.1631*** |
[1] |
SUN Y L, ZHUANG G S, TANG A H, et al. Chemical characteristics of PM2.5 and PM10 in haze-fog episodes in Beijing. Environmental Science and Technology, 2006,40(10):3148-3155.
doi: 10.1021/es051533g pmid: 16749674 |
[2] | LU H Y, WU Y L, MUTUKU J K, et al. Various sources of PM2.5 and their impact on the air quality in Tainan city, Taiwan. Aerosol and Air Quality Research, 2019,19(3):601-619. |
[3] | GEHRIG R, BUCHMANN B. Characterising seasonal variations and spatial distribution of ambient PM10 and PM2.5 concentrations based on long-term Swiss monitoring data. Atmospheric Environment, 2003,37(19):2571-2580. |
[4] | 王振波, 方创琳, 许光, 等. 2014年中国城市PM2.5浓度的时空变化规律. 地理学报, 2015,70(11):1720-1734. |
[ WANG Z B, FANG C L, XU G, et al. Spatial-temporal characteristics of the PM2.5 in China in 2014. Acta Geographica Sinica, 2015,70(11):1720-1734.] | |
[5] |
YORIFUJI T, BAE S, KASHIMA S, et al. Health impact assessment of PM10 and PM2.5 in 27 Southeast and East Asian cities. Journal of Occupational and Environmental Medicine, 2015,57(7):751-756.
doi: 10.1097/JOM.0000000000000485 pmid: 26147543 |
[6] | 徐冬, 黄震方, 黄睿. 基于空间面板计量模型的雾霾对中国城市旅游流影响的空间效应. 地理学报, 2019,74(4):814-830. |
[ XU D, HUANG Z F, HUANG R. The spatial effects of haze on tourism flows of Chinese cities: Empirical research based on the spatial panel econometric model. Acta Geographica Sinica, 2019,74(4):814-830.] | |
[7] | HAO Y, LIU Y M. The influential factors of urban PM2.5 concentrations in China: A spatial econometric analysis. Journal of Cleaner Production, 2016,112:1443-1453. |
[8] | 刘海猛, 方创琳, 黄解军, 等. 京津冀城市群大气污染的时空特征与影响因素解析. 地理学报, 2018,73(1):177-191. |
[ LIU H M, FANG C L, HUANG J J, et al. The spatial-temporal characteristics and influencing factors of air pollution in Beijing-Tianjin-Hebei Urban Agglomeration. Acta Geographica Sinica, 2018,73(1):177-191.] | |
[9] | FENG X, LI Q, ZHU Y J, et al. Artificial neural networks forecasting of PM2.5 pollution using air mass trajectory based geographic model and wavelet transformation. Atmospheric Environment, 2015,107:118-128. |
[10] | PUI D Y H, CHEN S C, ZUO Z. PM2.5 in China: Measurements, sources, visibility and health effects, and mitigation. Particuology, 2014,13:1-26. |
[11] | 邵帅, 李欣, 曹建华, 等. 中国雾霾污染治理的经济政策选择: 基于空间溢出效应的视角. 经济研究, 2016,51(9):73-88. |
[ SHAO S, LI X, CAO J H, et al. China's economic policy choices for governing smog pollution based on spatial spillover effects. Economic Research Journal, 2016,51(9):73-88.] | |
[12] | 邵帅, 李欣, 曹建华. 中国的城市化推进与雾霾治理. 经济研究, 2019,54(2):148-165. |
[ SHAO S, LI X, CAO J H. Urbanization promotion and haze pollution governance in China. Economic Research Journal, 2019,54(2):148-165.] | |
[13] | 东童童, 李欣, 刘乃全. 空间视角下工业集聚对雾霾污染的影响: 理论与经验研究. 经济管理, 2015,37(9):29-41. |
[ DONG T T, LI X, LIU N Q. The effect of industrial agglomeration to haze pollution (PM2.5) based on spatial perspective: Theoretical and empirical research. Economic Management, 2015,37(9):29-41.] | |
[14] | 东童童. 雾霾污染(PM2.5)、工业集聚与工业效率的交互影响研究. 软科学, 2016,30(3):26-30. |
[ DONG T T. Research on the interactive influence among haze pollution (PM2.5), industrial agglomeration and industrial efficiency. Soft Science, 2016,30(3):26-30.] | |
[15] | 胡熠娜, 彭建, 刘焱序, 等. 区域生态效率研究进展. 生态学报, 2018,38(23):8277-8284. |
[ HU Y N, PENG J, LIU Y X, et al. Review on regional eco-efficiency research. Acta Ecologica Sinica, 2018,38(23):8277-8284.] | |
[16] | 关伟, 许淑婷. 中国能源生态效率的空间格局与空间效应. 地理学报, 2015,70(6):980-992. |
[ GUAN W, XU S T. Study on spatial pattern and spatial effect of energy eco-efficiency in China. Acta Geographica Sinica, 2015,70(6):980-992.] | |
[17] | 李在军, 胡美娟, 周年兴. 中国地级市工业生态效率空间格局及影响因素. 经济地理, 2018,38(12):126-134. |
[ LI Z J, HU M J, ZHOU N X. The spatial pattern and influencing factors of industrial eco-efficiency in Chinese prefecture-level cities. Economic Geography, 2018,38(12):126-134.] | |
[18] | 卢燕群, 袁鹏. 中国省域工业生态效率及影响因素的空间计量分析. 资源科学, 2017,39(7):1326-1337. |
[ LU Y Q, YUAN P. Measurement and spatial econometrics analysis of provincial industrial ecological efficiency in China. Resources Science, 2017,39(7):1326-1337.] | |
[19] | 袁荷, 仇方道, 朱传耿, 等. 江苏省工业环境效率时空格局及影响因素. 地理与地理信息科学, 2017,33(5):112-118. |
[ YUAN H, QIU F D, ZHU C G, et al. Spatial-temporal changes and influencing factors of industrial environmental efficiency in Jiangsu province. Geography and Geo-Information Science, 2017,33(5):112-118.] | |
[20] | 张新林, 仇方道, 王长建, 等. 长三角城市群工业生态效率空间溢出效应及其影响因素. 长江流域资源与环境, 2019,28(8):1791-1800. |
[ ZHANG X L, QIU F D, WANG C J, et al. Spatial spillover effects and driving factors of industrial eco-efficiency in Yangtze River Delta Urban Agglomerations. Resources and Environment in the Yangtze Basin, 2019,28(8):1791-1800.] | |
[21] | 任胜钢, 张如波, 袁宝龙. 长江经济带工业生态效率评价及区域差异研究. 生态学报, 2018,38(15):5485-5497. |
[ REN S G, ZHANG R B, YUAN B L. Industrial eco-efficiency evaluation and regional differences of Yangtze River Economic Belt. Acta Ecologica Sinica, 2018,38(15):5485-5497.] | |
[22] | 李成宇, 张士强, 张伟. 中国省际工业生态效率空间分布及影响因素研究. 地理科学, 2018,38(12):1970-1978. |
[ LI C Y, ZHANG S Q, ZHANG W. Spatial distribution characteristics and influencing factors of China's inter provincial industrial eco-efficiency. Scientia Geographica Sinica, 2018,38(12):1970-1978.] | |
[23] | 吴文洁, 刘雪梦, 唐娟莉. FDI与中国工业生态效率: 基于面板联立方程模型的实证分析. 商业研究, 2019, ( 6):63-72. |
[ WU W J, LIU X M, TANG J L. FDI and China's industrial ecological efficiency: An empirical analysis based on panel simultaneous equation model. Commercial Research, 2019, ( 6):63-72.] | |
[24] | 童玉芬, 王莹莹. 中国城市人口与雾霾: 相互作用机制路径分析. 北京社会科学, 2014, ( 5):4-10. |
[ TONG Y F, WANG Y Y. The interaction mechanism of urban population and haze in China. Social Sciences of Beijing, 2014, ( 5):4-10.] | |
[25] | 胡志强, 苗健铭, 苗长虹. 中国地市工业集聚与污染排放的空间特征及计量检验. 地理科学, 2018,38(2):168-176. |
[ HU Z Q, MIAO J M, MIAO C H. Spatial characteristics and econometric test of industrial agglomeration and pollutant emissions in China. Scientia Geographica Sinica, 2018,38(2):168-176.] | |
[26] | LI H, FANG K N, YANG W, et al. Regional environmental efficiency evaluation in China: Analysis based on the Super-SBM model with undesirable outputs. Mathematical and Computer Modelling, 2013,58(5-6):1018-1031. |
[27] | WANG Z H, FENG C. A performance evaluation of the energy, environmental, and economy efficiency and productivity in China: An application of global data envelopment analysis. Applied Energy, 2015,147:617-626. |
[28] | DASGUPTA S, LAPLANTE B, MAMINGI N, et al. Inspections, pollution prices, and environmental performance: Evidence from China. Ecological Economics, 2001,36(3):487-498. |
[29] | ZHAO Y B, WANG S J, GE Y J, et al. The spatial differentiation of the coupling relationship between urbanization and the eco-environment in countries globally: A comprehensive assessment. Ecological Modelling, 2017,360(24):313-327. |
[30] | 刘帅宾, 杨山, 王钊. 基于人口流的中国省域城镇化空间关联特征及形成机制. 地理学报, 2019,74(4):648-663. |
[ LIU S B, YANG S, WANG Z. Characteristics and formation mechanism of China's provincial urbanization spatial correlation based on population flow. Acta Geographica Sinica, 2019,74(4):648-663.] | |
[31] | 徐冬, 黄震芳, 黄睿, 等. 中国中东部雾霾污染与入境旅游的时空动态关联分析. 自然资源学报, 2019,34(5):1108-1120. |
[ XU D, HUANG Z F, HUANG R. et al. The spatiotemporal dynamic correlation analysis of haze pollution and inbound tourism in Central and Eastern China. Journal of Natural Resources, 2019,34(5):1108-1120.] | |
[32] | ELHORST J P. Matlab software for spatial panels. International Regional Science Review, 2014,37(3), 389-405. |
[33] | 张国俊, 邓毛颖, 姚洋洋, 等. 广东省产业绿色发展的空间格局及影响因素分析. 自然资源学报, 2019,34(8):1593-1605. |
[ ZHANG G J, DENG M Y, YAO Y Y, et al. Comprehensive level of the green development of industry in Guangdong province and spatial econometric analysis of the influencing factors. Journal of Natural Resources, 2019,34(8):1593-1605.] |
[1] | 湛东升, 吴倩倩, 余建辉, 张文忠, 张娟锋. 中国资源型城市房价时空变化与影响因素分析[J]. 自然资源学报, 2020, 35(12): 2888-2900. |
[2] | 张凡凡, 张启楠, 李福夺, 傅汇艺, 杨兴洪. 中国水足迹强度空间关联格局及影响因素分析[J]. 自然资源学报, 2019, 34(5): 934-944. |
[3] | 鲍超, 陈小杰, 梁广林. 基于空间计量模型的河南省用水效率影响因素分析[J]. 自然资源学报, 2016, 31(7): 1138-1148. |
|