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Frontiers in Energy

Front. Energy    2020, Vol. 14 Issue (1) : 57-70     https://doi.org/10.1007/s11708-019-0654-7
RESEARCH ARTICLE
Does environmental infrastructure investment contribute to emissions reduction? A case of China
Xiaoqian SONG1, Yong GENG2(), Ke LI3, Xi ZHANG4, Fei WU4, Hengyu PAN4, Yiqing ZHANG5
1. China Institute of Urban Governance, Shanghai Jiao Tong University, Shanghai 200030
2. School of International and Public Affairs, Shanghai Jiao Tong University, Shanghai 200030, China; China Institute of Urban Governance, Shanghai Jiao Tong University, Shanghai 200030, China; School of Management, China University of Mining and Technology, Xuzhou 221116, China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, China
3. College of Mathematics & Computer Science, Hunan Normal University, Changsha 410081, China
4. School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
5. Collaborative Innovation Centre for Energy Economy of Shandong, Shandong Technology and Business University, Yantai 264005, China
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Abstract

Environmental infrastructure investment (EII) is an important environmental policy instrument on responding to greenhouse gas (GHG) emission and air pollution. This paper employs an improved stochastic impact by regression on population, affluence and technology (STRIPAT) model by using panel data from 30 Chinese provinces and municipalities for the period of 2003–2015 to investigate the effect of EII on CO2 emissions, SO2 emissions, and PM2.5 pollution. The results indicate that EII has a positive and significant effect on mitigating CO2 emission. However, the effect of EII on SO2 emission fluctuated although it still contributes to the reduction of PM2.5 pollution through technology innovations. Energy intensity has the largest impact on GHG emissions and air pollution, followed by GDP per capita and industrial structure. In addition, the effect of EII on environmental issues varies in different regions. Such findings suggest that policies on EII should be region-specific so that more appropriate mitigation policies can be raised by considering the local realities.

Keywords environmental infrastructure investment (EII)      CO2 emission      SO2 emission      PM2.5 pollution      stochastic impact by regression on population      affluence and technology (STIRPAT) model      governance     
Corresponding Authors: Yong GENG   
Online First Date: 19 December 2019    Issue Date: 16 March 2020
 Cite this article:   
Xiaoqian SONG,Yong GENG,Ke LI, et al. Does environmental infrastructure investment contribute to emissions reduction? A case of China[J]. Front. Energy, 2020, 14(1): 57-70.
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http://journal.hep.com.cn/fie/EN/10.1007/s11708-019-0654-7
http://journal.hep.com.cn/fie/EN/Y2020/V14/I1/57
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Xiaoqian SONG
Yong GENG
Ke LI
Xi ZHANG
Fei WU
Hengyu PAN
Yiqing ZHANG
Fig.1  CO2 emission, SO2 emission, PM2.5 pollution, and EII in China in 2003, 2009, and 2015.

(a) 2003; (b) 2009; (c) 2015.

Variables Mean Std. Dev. Min Max
CO2 emissions/(106t) 277.73 230.32 0.0005 155.38
SO2 emissions/(106t) 6.410 3.860 0.210 17.200
PM2.5 pollution/(105t) 54.70 33.00 3.09 167.00
EII/(109 yuan) 78.025 89.492 1.167 1047.230
A/(104yuan) 2.491 1.634 0.369 8.731
U/% 0.504 0.145 0.248 0.896
IS/% 0.469 0.078 0.197 0.590
EI/(104 yuan) 1.449 0.743 0.362 4.535
P× 104 4402.10 2647.71 534.00 10849
T 3.385 3.065 0.362 16.192
Tab.1  Descriptive statistical data associated with these variables
Variables (1) (2) (3) (4) (5) (6)
CO2 emission SO2 emission PM2.5 pollution CO2 emission SO2 emission PM2.5 pollution
EII 0.0470** 0.0104 - 0.0405*** - - -
(0.0220) (0.0227) (0.0143) - - -
A 0.827*** 0.526*** 0.240*** 1.107*** 0.424*** 0.345**
(0.127) (0.131) (0.0822) (0.132) (0.150) (0.141)
A2 - - - -0.447*** -0.431*** -0.593***
- - - (0.0807) (0.0916) (0.0864)
IS - 0.00156 0.413*** - 0.0657 - - -
(0.131) (0.135) (0.0849) - - -
EI 1.221*** 0.930*** 0.0620 - - -
(0.113) (0.116) (0.0730) - - -
P 0.696*** - 0.617*** - 0.124 - - -
(0.221) (0.228) (0.143) - - -
T 0.273*** - 0.102 - 0.111** - - -
(0.0835) (0.0862) (0.0542) - - -
U 0.276 - 0.253 - 0.0190 - - -
(0.186) (0.192) (0.121) - - -
Constant - 1.494 17.70*** 16.23*** 4.926*** 13.18*** 15.51***
(1.721) (1.775) (1.117) (0.0596) (0.0677) (0.0639)
F-test 249.42*** 24.57*** 2.47** - - -
Hausman 309.7*** 35197.04*** - 11.3 - - -
Observations 390 390 390 390 390 390
Number of no 30 30 30 30 30 30
R-squared 0.832 0.328 0.047 0.184 0.072 0.217
Tab.2  Regression analysis of effects of EII on CO2 emission, SO2 emission, and PM2.5 pollution
Variables CO2 emission SO2 emission PM2.5 pollution
(1) (2) (3) (4) (5) (6) (7) (8) (9)
EII 0.0829*** 0.774*** 0.0732*** 0.0747*** 0.706*** 0.0462* -0.0504*** -0.0965 -0.0515***
(0.0245) (0.160) (0.0248) (0.0245) (0.165) (0.0255) (0.0161) (0.107) (0.0162)
A 0.980*** 0.779*** 0.797*** 0.800*** 0.480*** 0.484*** 0.198** 0.244*** 0.253***
(0.134) (0.124) (0.127) (0.134) (0.128) (0.130) (0.0878) (0.0825) (0.0825)
IS - 0.0534 -0.0108 - 0.0513 0.320** 0.405*** 0.346** -0.0513 -0.0650 - 0.0448
(0.130) (0.127) (0.132) (0.130) (0.132) (0.135) (0.0854) (0.0850) (0.0860)
EI 1.158*** 1.069*** 1.199*** 0.816*** 0.785*** 0.900*** 0.0796 0.0737 0.0713
(0.113) (0.114) (0.112) (0.113) (0.118) (0.115) (0.0741) (0.0764) (0.0732)
P 0.883*** 0.739*** 0.822*** -0.282 -0.576** -0.445* -0.176 -0.127 -0.177
(0.226) (0.215) (0.227) (0.226) (0.223) (0.233) (0.148) (0.144) (0.148)
T 0.278*** 0.237*** 0.409*** - 0.0946 -0.137 0.0828 -0.113** -0.109** -0.169**
(0.0825) (0.0817) (0.103) (0.0825) (0.0846) (0.105) (0.0542) (0.0545) (0.0669)
U 0.243 0.447** 0.235 -0.312* -0.0892 -0.310 -0.00983 -0.0322 -0.00141
(0.184) (0.185) (0.186) (0.184) (0.191) (0.191) (0.121) (0.123) (0.121)
EII × A -0.0518*** -0.0929*** 0.0144
(0.0161) (0.0161) (0.0106)
EII × P -0.0892*** -0.0854*** 0.00687
(0.0194) (0.0201) (0.0130)
EII × T -0.0312** -0.0426*** 0.0131
(0.0139) (0.0142) (0.00903)
Constant -3.149* -1.579 -2.664 14.73*** 17.61*** 16.10*** 16.69*** 16.23*** 16.72***
(1.775) (1.674) (1.788) (1.776) (1.734) (1.835) (1.166) (1.118) (1.166)
Observation 390 390 390 390 390 390 390 390 390
N 30 30 30 30 0.360 0.344 0.052 0.047 0.052
R-squared 0.837 0.841 0.834 0.385 30 30 30 30 30
Tab.3  Path analysis of effects of EII on CO2, SO2 emissions, and PM2.5 pollution
Fig.2  Marginal effects of EII on CO2 emission.
Variables Eastern Central Western
(1) (2) (3) (4) (5) (6) (7) (8) (9)
CO2 emission SO2 emission PM2.5pollution CO2 emission SO2 emission PM2.5 pollution CO2 emission SO2 emission PM2.5 pollution
EII 0.0704* -0.0119 -0.0405* 0.127** - 0.0624* -0.0851** -0.0401 0.0217 -0.0176
(0.0367) (0.0389) (0.0215) (0.0523) (0.0364) (0.0390) (0.0311) (0.0374) (0.0208)
A 1.275*** 0.476** 0.179 0.192 0.332* 0.335* 1.336*** 1.141*** 0.231*
(0.202) (0.214) (0.118) (0.267) (0.186) (0.199) (0.203) (0.244) (0.136)
IS 0.495* 0.630** 0.227 -0.0532 0.514*** -0.343** -0.201 -0.255 0.115
(0.296) (0.313) (0.173) (0.198) (0.138) (0.147) (0.230) (0.277) (0.154)
EI 1.426*** 1.034*** -0.138 1.274*** 0.416*** -0.201 1.010*** 0.750*** 0.315***
(0.245) (0.259) (0.143) (0.213) (0.148) (0.159) (0.173) (0.208) (0.116)
P 1.013*** -0.160 0.0770 3.288*** 0.845 -2.070*** 0.903 2.199*** -0.537
(0.324) (0.343) (0.189) (1.038) (0.722) (0.773) (0.580) (0.698) (0.389)
T -0.115 -0.249 -0.200** 0.717*** 0.0309 -0.124 0.0951 -0.681*** -0.124
(0.147) (0.156) (0.0860) (0.169) (0.118) (0.126) (0.151) (0.182) (0.101)
U 0.268 0.157 0.277* 0.118 -0.729*** -0.0728 -0.641 -0.258 0.0879
(0.259) (0.274) (0.151) (0.330) (0.230) (0.246) (0.527) (0.634) (0.354)
Constant -3.937 14.74*** 14.64*** -23.58*** 5.943 33.23*** -3.824 -5.055 19.51***
(2.530) (2.679) (1.478) (8.700) (6.058) (6.484) (4.331) (5.211) (2.905)
Observation 156 156 156 117 117 117 117 117 117
R-squared 0.804 0.518 0.117 0.865 0.349 0.240 0.906 0.407 0.184
N 12 12 12 9 9 9 9 9 9
Tab.4  Effects of EII on CO2 emission, SO2 emissions, and PM2.5 pollution by region
EII CO2 emission SO2 emission PM2.5 pollution
EII × 2004 0.0721* -0.09612 -0.0562***
(0.0132) (0.0126) (0.00743)
EII × 2005 0.067* 0.11247 -0.0113**
(0.0143) (0.0137) (0.00810)
EII × 2006 0.0525*** 0.103943 0.0065***
(0.0157) (0.0150) (0.00886)
EII × 2007 0.0302*** 0.0758* 0.0143***
(0.0172) (0.0164) (0.00970)
EII × 2008 0.0328*** 0.0431*** 0.0063***
(0.0182) (0.0173) (0.0102)
EII × 2009 0.0323*** 0.0127 0.003***
(0.0191) (0.0183) (0.0108)
EII × 2010 0.022*** 0.005*** 0.0025***
(0.0204) (0.0195) (0.0115)
EII × 2011 0.0196*** 0.0074*** -0.0076*
(0.0223) (0.0213) (0.0126)
EII × 2012 0.0028*** -0.009*** -0.0076
(0.0231) (0.0220) (0.0130)
EII × 2013 0.0129*** -0.013*** 0.0114***
(0.0246) (0.0234) (0.0139)
EII × 2014 0.0041*** -0.029*** 0.0012**
(0.0258) (0.0246) (0.0146)
EII × 2015 -0.017*** -0.164*** 0.0366**
(0.0278) (0.0265) (0.0157)
Constant -4.324** 13.23*** 17.39***
(1.902) (1.816) (1.074)
Control variables Yes Yes Yes
Observations 390 390 390
R-squared 0.843 0.462 0.326
Tab.5  Time-varying effects
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