Spatial spillover effect of carbon emission efficiency in the construction industry of China.
Carbon emission efficiency
Construction industry
Spatial Markov chain
Spatial dependence
Spatial spillover effect
Temporal and spatial distribution
Journal
Environmental science and pollution research international
ISSN: 1614-7499
Titre abrégé: Environ Sci Pollut Res Int
Pays: Germany
ID NLM: 9441769
Informations de publication
Date de publication:
Jan 2022
Jan 2022
Historique:
received:
09
04
2021
accepted:
27
07
2021
pubmed:
10
8
2021
medline:
11
1
2022
entrez:
9
8
2021
Statut:
ppublish
Résumé
The construction industry plays an important role in energy saving and carbon emissions mitigation of China. Promoting carbon emission efficiency is seen as an efficient way to abate carbon emissions. Using 2005-2016 data, the carbon emission efficiency of the construction sector in 30 provinces is estimated, and the spatial distribution characteristics of the carbon emission efficiency of the construction industry is explored. The spatial Markov transition probability matrix is employed to investigate the influence of the spatial spillover effect on the regional distribution pattern of carbon emission efficiency. The results demonstrate that the carbon emission efficiency of the construction industry exhibits an unbalanced regional distribution, which is high in the east and low in the west. The spatial autocorrelation indicates that the carbon emission efficiency has a spatial dependence and is characterized by spatial agglomeration. Markov Chain results show a significant spatial spillover effect in carbon emission efficiency. The provinces with higher carbon emission efficiency have a positive effect on their neighbors, while the provinces with lower efficiency have a negative effect on neighbors. The findings are of great importance to understand the differences in and interactions of carbon emission efficiency between regions.
Identifiants
pubmed: 34370200
doi: 10.1007/s11356-021-15747-9
pii: 10.1007/s11356-021-15747-9
doi:
Substances chimiques
Carbon Dioxide
142M471B3J
Carbon
7440-44-0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
2466-2479Subventions
Organisme : social science foundation of shaanxi province
ID : 2020R008
Organisme : fundamental research funds for the central universities
ID : 300102239617, 300102230615
Informations de copyright
© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
Références
Anselin L (1988) Spatial econometrics: methods and models. Econ Geogr 65(2):160–162
Anselin L, Griffith DA (2010) Do spatial effects really matter in regression analysis? Pap Reg Sci 65(1):11–34
Burnett JW, Bergstrom JC, Dorfman JH (2013) A spatial panel data approach to estimating U.S. state-level energy emissions. Energy Econ 40(2):396–404
Chen J, Xu C, Managi S, Song M (2019) Energy-carbon performance and its changing trend: an example from China’s construction industry. Resour Conserv Recycl 145:379–388
Chen P, Xie R, Lu M, Huang Z (2020) The impact of the spatio-temporal neighborhood effect on urban eco-efficiency in China. J Clean Prod 285:124860
Cheng Z, Li L, Liu J, Zhang H (2018) Total-factor carbon emission efficiency of China’s provincial industrial sector and its dynamic evolution. Renew Sust Energ Rev 94:330–339
Cheng Z, Liu J, Li L, Gu X (2020) Research on meta-frontier total-factor energy efficiency and its spatial convergence in Chinese provinces. Energy Econ 86:104702
Dissanayake S, Mahadevan R, Asafu-Adjaye J (2020) Evaluating the efficiency of carbon emissions policies in a large emitting developing country. Energy Policy 136:111080
Du Q, Shao L, Zhou J, Huang N, Bao T, Hao C (2019a) Dynamics and scenarios of carbon emissions in China’s construction industry. Sust Cities and Society 48:111080
Du Q, Zhou J, Pan T, Sun Q, Wu M (2019b) Relationship of carbon emissions and economic growth in China’s construction industry. J Clean Prod 220:99–109
Du Q, Han X, Li Y, Li Z, Xia B, Guo X (2021) The energy rebound effect of residential buildings: evidence from urban and rural areas in China. Energy Policy 153:112235
Hong J, Gu J, He R, Wang X, Shen Q (2020) Unfolding the spatial spillover effects of urbanization on interregional energy connectivity: evidence from province-level data. Energy 196:116990
Huo T, Tang M, Cai W, Ren H, Liu B, Hu X (2020) Provincial total-factor energy efficiency considering floor space under construction: an empirical analysis of China’s construction industry. J Clean Prod 244:118749
Koch E, Robert CY (2019) Geometric ergodicity for some space–time max-stable Markov chains. Statistics & Probability Letters 145:43–49
Li J, Li S (2020) Energy investment, economic growth and carbon emissions in China—empirical analysis based on spatial Durbin model. Energy Policy 140:111425
Li W, Sun W, Li G, Cui P, Wu W, Jin B (2017) Temporal and spatial heterogeneity of carbon intensity in China’s construction industry. Resour Conserv Recycl 126:162–173
Li W, Yang G, Li X, Sun T, Wang J (2019a) Cluster analysis of the relationship between carbon dioxide emissions and economic growth. J Clean Prod 225:459–471
Li Y, Du Q, Lu X, Wu J, Han X (2019b) Relationship between the development and CO
Li W, Huang Y, Lu C (2020a) Exploring the driving force and mitigation contribution rate diversity considering new normal pattern as divisions for carbon emissions in Hebei province. J Clean Prod 243:118559
Li W, Wang W, Gao H, Zhu B, Gong W, Liu Y, Qin Y (2020b) Evaluation of regional metafrontier total factor carbon emission performance in China’s construction industry: analysis based on modified non-radial directional distance function. J Clean Prod 256:120425
Liao FHF, Wei YD (2012) Dynamics, space, and regional inequality in provincial China: a case study of Guangdong province. Appl Geogr 35:71–83
Liu F, Liu C (2019) Regional disparity, spatial spillover effects of urbanisation and carbon emissions in China. J Clean Prod 241:118226
Liu Z, Kodamana H, Afacan A, Huang B (2019) Dynamic prediction of interface level using spatial temporal Markov random field. Comput Chem Eng 128:301–311
Long R, Shao T, Chen H (2016) Spatial econometric analysis of China’s province-level industrial carbon productivity and its influencing factors. Appl Energy 166:210–219
Morales-Lage R, Bengochea-Morancho A, Camarero M, Martínez-Zarzoso I (2019) Club convergence of sectoral CO
Moran (1950) Notes on continuous stochastic phenomena. Biometrika 37:17–23
Pan X, Liu Q, Peng X (2015) Spatial club convergence of regional energy efficiency in China. Ecol Indic 51:25–30
Peng Z, Wu Q, Wang D, Li M (2019) Temporal-spatial pattern and influencing factors of China’s province-level transport sector carbon emissions efficiency. Pol J Environ Stud 29:233–247
Qi X, Guo P, Guo Y, Liu X, Zhou X (2020) Understanding energy efficiency and its drivers: an empirical analysis of China’s 14 coal intensive industries. Energy 190:116354
Qin Q, Yan H, Liu J, Chen X, Ye B (2020) China’s agricultural GHG emission efficiency: regional disparity and spatial dynamic evolution. Environ Geochem Health
Rey SJ (2001) Spatial empirics for economic growth and convergence. Geogr Anal 33(3):195–214
Rios V, Gianmoena L (2018) Convergence in CO
Song M, Wu J, Song M, Zhang L, Zhu Y (2020) Spatiotemporal regularity and spillover effects of carbon emission intensity in China’s Bohai Economic Rim. Sci Total Environ 740:140184
Tang K, Xiong C, Wang Y, Zhou D (2020) Carbon emissions performance trend across Chinese cities: evidence from efficiency and convergence evaluation. Environ Sci & Pollut R 28(2):1533–1544
Tian K, Dietzenbacher E, Yan B, Duan Y (2020) Upgrading or downgrading: China’s regional carbon emission intensity evolution and its determinants. Energy Econ 91:104891
Tobler W (1970) A computer movie simulating urban growth in the Detroit region[J]. Econ Geogr 46(02): 234–240
Tone K (2002) A slacks-based measure of super-efficiency in data envelopment analysis. Eur J Oper Res 143(1):32–41
Torres Preciado VH, Polanco Gaytán M, Tinoco Zermeño MA (2017) Dynamic of foreign direct investment in the states of Mexico: an analysis of Markov’s spatial chains. Contaduría y Administración 62:163–183
Wang M, Feng C (2018) Exploring the driving forces of energy-related CO
Wang S, Huang Y, Zhou Y (2019a) Spatial spillover effect and driving forces of carbon emission intensity at the city level in China. J Geogr Sci 29:231–252
Wang S, Wang J, Fang C, Feng K (2019b) Inequalities in carbon intensity in China: a multi-scalar and multi-mechanism analysis. Appl Energy 254:113720
Wang S, Gao S, Huang Y, Shi C (2020) Spatiotemporal evolution of urban carbon emission performance in China and prediction of future trends. J Geogr Sci 30(5):757–774
Wang L, Song X, Song X (2021) Research on the measurement and spatial-temporal difference analysis of energy efficiency in China’s construction industry based on a game cross-efficiency model. J Clean Prod 278:123918
Wen Q, Chen Y, Hong JK, Chen Y, Ni DF, Shen QP (2020a) Spillover effect of technological innovation on CO
Wen Q, Hong J, Liu G, Xu P, Tang M, Li Z (2020b) Regional efficiency disparities in China’s construction sector: a combination of multiregional input–output and data envelopment analyses. Appl Energy 257:113964
Xie ZH, Wu R, Wang SJ (2021) How technological progress affects the carbon emission efficiency? Evidence from national panel quantile regression. J Clean Prod 307:127133
Xu G, Wang W (2020) China’s energy consumption in construction and building sectors: an outlook to 2100. Energy 195:117045
Yang G, Zhang F, Zhang F, Ma D, Gao L (2021) Spatiotemporal changes in efficiency and influencing factors of China’s industrial carbon emissions. Environ Sci & Pollut R 28(27):36288–36302
You W, Lv Z (2018) Spillover effects of economic globalization on CO
Yu YT, Zhang N (2021) Low-carbon city pilot and carbon emission efficiency: quasi-experimental evidence from China. Energy Econ 96:105125
Zeng C, Stringer LC, Lv TY (2021) The spatial spillover effect of fossil fuel energy trade on CO
Zhang J, Zeng W, Wang J, Yang F, Jiang H (2017) Regional low-carbon economy efficiency in China: analysis based on the Super-SBM model with CO
Zhang Y, Yan D, Hu S, Guo S (2019) Modelling of energy consumption and carbon emission from the building construction sector in China, a process-based LCA approach. Energy Policy 134:110949
Zhang Q, Zhang F, Wu G, Mai Q (2021) Spatial spillover effects of grain production efficiency in China: measurement and scope. J Clean Prod 278:121062
Zhao Xg (2019) Spatial distribution characteristics and convergence of China’s regional energy intensity: an industrial transfer perspective. J Clean Prod 233:903–917
Zhou Y, Kong Y, Sha J, Wang H (2019) The role of industrial structure upgrades in eco-efficiency evolution: spatial correlation and spillover effects. Sci Total Environ 687:1327–1336
Zhu L, Wang Y, Shang P, Qi L, Yang G, Wang Y (2019) Improvement path, the improvement potential and the dynamic evolution of regional energy efficiency in China: based on an improved nonradial multidirectional efficiency analysis. Energy Policy 133:110883