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Urban planning and design

Spatiotemporal evolution of carbon emissions and influencing factors in county-level based on nighttime lighting data: a case study in Huaihai economic zone core city

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Received 07 Nov 2023, Accepted 25 Jun 2024, Published online: 12 Jul 2024

References

  • Cai, B. F., X. Q. Mao, J. N. Wang, and M. D. Wang. 2019. “Fine Resolution Carbon Dioxide Emission Gridded Data and Their Application for China.” Journal of Environmental Informatics 33 (2): 82–95. http://doi.org/10.3808/jei.201800390.
  • Cao, C., B. Zhang, F. Xia, and Y. Bai. 2022. “Exploring VIIRS Night Light Long-Term Time Series with CNN/SI for Urban Change Detection and Aerosol Monitoring.” Remote Sensing 14 (13): 3126. https://doi.org/10.3390/rs14133126.
  • Cao, X., J. Wang, J. Chen, and F. Shi. 2014. “Spatialization of Electricity Consumption of China Using Saturation-Corrected DMSP-OLS Data.” International Journal of Applied Earth Observation and Geoinformation 28:193–200. https://doi.org/10.1016/j.jag.2013.12.004.
  • Chen, H., X. Zhang, R. Wu, and T. Cai. 2020. “Revisiting the Environmental Kuznets Curve for City-Level CO2 Emissions: Based on Corrected NPP-VIIRS Nighttime Light Data in China.” Journal of Cleaner Production 268:121575. https://doi.org/10.1016/j.jclepro.2020.121575.
  • Chen, L., and Z. Yang. 2015. “A Spatio-Temporal Decomposition Analysis of Energy-Related CO2 Emission Growth in China.” Journal of Cleaner Production 103:49–60. https://doi.org/10.1016/j.jclepro.2014.09.025.
  • Chen, Y., and K. Rajakani. 2022. “Analysis on the Pattern of County Carbon Emission Intensity and the Evolution of Influencing Factors in China Based on LMDI Model.” Wireless Communications and Mobile Computing 2022:1–9. https://doi.org/10.1155/2022/3658679.
  • Chu, Y., L. Xie, and Z. Yuan. 2018. “Composition and Spatiotemporal Distribution of the Agro-Ecosystem Carbon Footprint: A Case Study in Hebei Province, North China.” Journal of Cleaner Production 190:838–846. https://doi.org/10.1016/j.jclepro.2018.04.111.
  • Cirilli, A., and P. Veneri. 2014. “Spatial Structure and Carbon Dioxide (CO2) Emissions Due to Commuting: An Analysis of Italian Urban Areas.” Regional Studies 48 (12): 1993–2005. https://doi.org/10.1080/00343404.2013.827333.
  • Ding, Z. L. 2021. “Realization of the Paris Agreement Depends on Adherence to the Original Spirit.” National Science Review 8 (12): 215. https://doi.org/10.1093/nsr/nwab215.
  • Du, X., L. Shen, S. W. Wong, C. Meng, and Z. Yang. 2021. “Night-Time Light Data Based Decoupling Relationship Analysis Between Economic Growth and Carbon Emission in 289 Chinese Cities.” Sustainable Cities and Society 73:103119. https://doi.org/10.1016/j.scs.2021.103119.
  • Ehrlich, P. R., and J. P. Holdren. 1971. “Impact of Population Growth.” Science 171 (3977): 1212–1217. https://doi.org/10.1126/science.171.3977.1212.
  • Fan, J. S., and L. Zhou. 2019. “Impact of Urbanization and Real Estate Investment on Carbon Emissions: Evidence from China’s Provincial Regions.” Journal of Cleaner Production 209:309–323. https://doi.org/10.1016/j.jclepro.2018.10.201.
  • Fan, Y., S. D. Zhang, Z. Y. He, B. He, H. C. Yu, X. X. Ye, H. Yang, X. M. Zhang, and Z. F. Chi. 2018. “Spatial Pattern and Evolution of Urban System Based on Gravity Model and Whole Network Analysis in the Huaihe River Basin of China.” Discrete Dynamics in Nature & Society 10:3698071. https://doi.org/10.1155/2018/3698071.
  • Fang, C. L., S. J. Wang, and G. D. Li. 2015. “Changing Urban Forms and Carbon Dioxide Emissions in China: A Case Study of 30 Provincial Capital Cities.” Applied Energy 158:519–531. https://doi.org/10.1016/j.apenergy.2015.08.095.
  • García, C. B., J. García, L. Martín, and R. Salmerón. 2015. “Collinearity: Revisiting the Variance Inflation Factor in Ridge Regression.” Journal of Applied Statistics 42 (3): 648–661. https://doi.org/10.1080/02664763.2014.980789.
  • Gaston, K. J., and M. Sánchez. 2022. “A. Environmental Impacts of Artificial Light at Night.” Annual Review of Environment and Resources 47 (1): 373–398. https://doi.org/10.1146/annurev-environ-112420-014438.
  • Ghosh, T., C. D. Elvidge, P. C. Sutton, K. E. Baugh, D. Ziskin, and B. T. Tuttle. 2010. “Creating a Global Grid of Distributed Fossil Fuel CO2 Emissions from Nighttime Satellite Imagery.” Energies 3 (12): 1895–1913. https://doi.org/10.3390/en3121895.
  • Guan, D., D. Wang, S. Hallegatte, S. J. Davis, J. Huo, S. Li, Y. Bai, et al. 2020. “Global Supply-Chain Effects of COVID-19 Control Measures.” Nature Human Behaviour 4 (6): 577–587. https://doi.org/10.1038/s41562-020-0896-8.
  • Guo, F. P., L. J. Zhang, Z. F. Wang, and S. B. Ji. 2022. “Research on Determining the Critical Influencing Factors of Carbon Emission Integrating GRA with an Improved STIRPAT Model: Taking the Yangtze River Delta as an Example.” International Journal of Environmental Research and Public Health 19 (14): 8791. https://doi.org/10.3390/ijerph19148791.
  • Huang, B., B. Wu, and M. Barry. 2010. “Geographically and Temporally Weighted Regression for Modeling Spatio-Temporal Variation in House Prices.” International Journal of Geographical Information Science 24 (3): 383–401. https://doi.org/10.1080/13658810802672469.
  • Lantz, V., and Q. Feng. 2006. “Assessing Income, Population, and Technology Impacts on CO2 Emissions in Canada: Where’s the EKC?” Ecological Economics 57 (2): 229–238. https://doi.org/10.1016/j.ecolecon.2005.04.006.
  • Lee, J., S. Kang, S. Kim, K. H. Kim, and E. C. Jeon. 2015. “Development of Municipal Solid Waste Classification in Korea Based on Fossil Carbon Fraction.” Journal of the Air & Waste Management Association 65 (10): 1256–1260. https://doi.org/10.1080/10962247.2015.1079563.
  • Lee, J. W. 2013. “The Contribution of Foreign Direct Investment to Clean Energy Use, Carbon Emissions and Economic Growth.” Energy Policy 55:483–489. https://doi.org/10.1016/j.enpol.2012.12.039.
  • Li, B. G., G. Thomas, C. Philippe, S. L. Piao, S. Tao, Y. Balkanski, D. Hauglustaine, et al. 2016. “The Contribution of China’s Emissions to Global Climate Forcing.” Nature 531 (7594): 357–361. https://doi.org/10.1038/nature17165.
  • Li, C., H. Li, and X. Qin. 2022. “Spatial Heterogeneity of Carbon Emissions and Its Influencing Factors in China: Evidence from 286 Prefecture-Level Cities.” International Journal of Environmental Research and Public Health 19 (3): 1226. https://doi.org/10.3390/ijerph19031226.
  • Li, C., H. Li, and X. H. Qin. 2022. “Spatial Heterogeneity of Carbon Emissions and Its Influencing Factors in China: Evidence from 286 Prefecture-Level Cities.” International Journal of Environmental Research and Public Health 19 (3): 1226. https://doi.org/10.3390/ijerph19031226.
  • Liddle, B., and S. Lung. 2010. “Age-Structure, Urbanization and Climate Change in Developed Countries: Revisiting STIRPAT for Disaggregated Population and Consumption-Related Environmental Impacts.” Population and Environment 31 (5): 317–343. https://doi.org/10.1007/s11111-010-0101-5.
  • Lin, X. W., J. J. Ma, H. Chen, F. Shen, S. Ahmad, and Z. Q. Li. 2022. “Carbon Emissions Estimation and Spatiotemporal Analysis of China at City Level Based on Multi-Dimensional Data and Machine Learning.” Remote Sensing 14 (13): 3014. https://doi.org/10.3390/rs14133014.
  • Liu, D. N., and B. W. Xiao. 2018. “Can China Achieve Its Carbon Emission Peaking? A Scenario Analysis Based on STIRPAT and System Dynamics Model.” Ecological Indicators 93:647–657. https://doi.org/10.1016/j.ecolind.2018.05.049.
  • Liu, H., L. Ma, and L. Xu. 2021. “Estimating Spatiotemporal Dynamics of County-Level Fossil Fuel Consumption Based on Integrated Nighttime Light Data.” Journal of Cleaner Production 278:123427. https://doi.org/10.1016/j.jclepro.2020.123427.
  • Liu, J. G., S. J. Li, and Q. Ji. 2021. “Regional Differences and Driving Factors Analysis of Carbon Emission Intensity from Transport Sector in China.” Energy 224:120178. https://doi.org/10.1016/j.energy.2021.120178.
  • Liu, J. L., S. W. Liu, X. G. Tang, Z. Ding, M. G. Ma, and P. J. Yu. 2022. “The Response of Land Surface Temperature Changes to the Vegetation Dynamics in the Yangtze River Basin.” Remote Sensing 14 (20): 5093. https://doi.org/10.3390/rs14205093.
  • Long, Z., J. Pang, S. Li, J. Zhao, T. Yang, X. Chen, Z. Zhang, et al. 2022. “Spatiotemporal Variations and Structural Characteristics of Carbon Emissions at the County Scale: A Case Study of Wu’an City.” Environmental Science and Pollution Research 29 (43): 65466–65488. https://doi.org/10.1007/s11356-022-20433-5.
  • Long, Z., Z. Zhang, S. Liang, X. Chen, B. Ding, B. Wang, Y. Chen, Y. Sun, S. Li, and T. Yang. 2021. “Spatially Explicit Carbon Emissions at the County Scale.” Resources, Conservation and Recycling 173:105706. https://doi.org/10.1016/j.resconrec.2021.105706.
  • Luo, P., X. Zhang, J. Cheng, and Q. Sun. 2019. “Modeling Population Density Using a New Index Derived from Multi-Sensor Image Data.” Remote Sensing 11 (22): 2620. https://doi.org/10.3390/rs11222620.
  • Lv, Q., H. Liu, J. Wang, H. Liu, and Y. Shang. 2020. “Multiscale Analysis on Spatiotemporal Dynamics of Energy Consumption CO2 Emissions in China: Utilizing the Integrated of DMSP-OLS and NPP-VIIRS Nighttime Light Datasets.” Science of the Total Environment 703:134394. https://doi.org/10.1016/j.scitotenv.2019.134394.
  • Mallapaty, S. 2020. “How China Could Be Carbon Neutral by Mid-Century.” Nature 586 (7830): 482–484. https://doi.org/10.1038/d41586-020-02927-9.
  • Meng, H., X. Zhang, X. Du, and K. Du. 2023. “Spatiotemporal Heterogeneity of the Characteristics and Influencing Factors of Energy-Consumption-Related Carbon Emissions in Jiangsu Province Based on DMSP-OLS and NPP-VIIRS.” The Land 12 (7): 1369. https://doi.org/10.3390/land12071369.
  • Meng, Z. S., H. Wang, and B. N. Wang. 2018. “Empirical Analysis of Carbon Emission Accounting and Influencing Factors of Energy Consumption in China.” International Journal of Environmental Research and Public Health 15 (11): 2467. https://doi.org/10.3390/ijerph15112467.
  • Mi, Z., D. Guan, Z. Liu, J. Liu, V. Viguié, N. Fromer, and Y. Wang. 2019. “Cities: The Core of Climate Change Mitigation.” Journal of Cleaner Production 207:582–589. https://doi.org/10.1016/j.jclepro.2018.10.034.
  • National Bureau of Statistics. 2020. Preliminary Accounting Results of GDP for the First Quarter of 2020. Beijing: China Statistics Press.
  • Oda, T., and S. Maksyutov. 2011. “A Very High-Resolution (1 km×1 Km) Global Fossil Fuel CO2 Emission Inventory Derived Using a Point Source Database and Satellite Observations of Nighttime Lights.” Atmospheric Chemistry and Physics 11 (2): 543–556. https://doi.org/10.5194/acp-11-543-2011.
  • Ou, J. P., X. P. Liu, S. J. Wang, R. Xie, and X. Li. 2019. “Investigating the Differentiated Impacts of Socioeconomic Factors and Urban Forms on CO2 Emissions: Empirical Evidence from Chinese Cities of Different Developmental Levels.” Journal of Cleaner Production 226:601–614. https://doi.org/10.1016/j.jclepro.2019.04.123.
  • Ouyang, X. L., and B. Q. Lin. 2017. “Carbon dioxide (CO2) emissions during urbanization: A comparative study between China and Japan.” Journal of Cleaner Production 143 (1) : 356–368. https://doi.org/10.1016/j.jclepro.2016.12.102.
  • Pei, J., Z. Niu, L. Wang, X. P. Song, N. Huang, J. Geng, Y. B. Wu, and H. H. Jiang. 2018. “Spatial-Temporal Dynamics of Carbon Emissions and Carbon Sinks in Economically Developed Areas of China: A Case Study of Guangdong Province.” Scientific Reports 8 (1): 13383. https://doi.org/10.1038/s41598-018-31733-7.
  • Poumanyvong, P., and S. Kaneko. 2010. “Does Urbanization Lead to Less Energy Use and Lower CO2 Emissions? A Cross-Country Analysis.” Ecological Economics 70 (2): 434–444. https://doi.org/10.1016/j.ecolecon.2010.09.029.
  • Qi, H., X. Shen, F. Long, M. Liu, and X. Gao. 2023. “Spatial–Temporal Characteristics and Influencing Factors of County-Level Carbon Emissions in Zhejiang Province, China.” Environmental Science and Pollution Research 30 (4): 10136–10148. https://doi.org/10.1007/s11356-022-22790-7.
  • Shen, N., Y. Q. Zhao, and Q. W. Wang. 2002. “Diversified Agglomeration, Specialized Agglomeration, and Emission Reduction Effect—A Nonlinear Test Based on Chinese City Data.” Sustainability 2018 (6): 10. https://doi.org/10.3390/su10062002.
  • Shi, K., Y. Chen, B. Yu, T. Xu, Z. Chen, R. Liu, L. Li, and J. Wu. 2016. “Modeling Spatiotemporal CO2 (Carbon Dioxide) Emission Dynamics in China from DMSP-OLS Nighttime Stable Light Data Using Panel Data Analysis.” Applied Energy 168:523–533. https://doi.org/10.1016/j.apenergy.2015.11.055.
  • Shi, K. F., Y. Chen, B. L. Yu, T. B. Xu, Z. Q. Chen, R. Liu, J. P. Wu, and J. Wu. 2016. “Modeling Spatiotemporal CO2 (Carbon Dioxide) Emission Dynamics in China from DMSP-OLS Nighttime Stable Light Data Using Panel Data Analysis.” Applied Energy 168:523–533. https://doi.org/10.1016/j.apenergy.2015.11.055.
  • Song, W. X., S. G. Yin, Y. H. Zhang, L. S. Qi, and X. Yi. 2022. “Spatial-Temporal Evolution Characteristics and Drivers of Carbon Emission Intensity of Resource-Based Cities in China.” Frontiers in Environmental Science 10:1–17. https://doi.org/10.3389/fenvs.2022.972563.
  • Sun, X., and Z. Mi. 2023. “Factors Driving China’s Carbon Emissions After the COVID-19 Outbreak.” Environmental Science & Technology 57 (48): 19125–19136. https://doi.org/10.1021/acs.est.3c03802.
  • Thomas, K., G. Sergey, S. Benedikt, and B. Victor. 2021. “Erratum: Atmospheric Methane Underestimated in Future Climate Projections.” Environmental Research Letters 16 (11): 119502. https://doi.org/10.1088/1748-9326/ac2f66.
  • Tomas, M., and A. Ernest. 2021. “The Evolution of Communicating the Uncertainty of Climate Change to Policymakers: A Study of IPCC Synthesis Reports.” Sustainability 13 (5): 2466. https://doi.org/10.3390/su13052466.
  • Tong, X., L. Tong, and X. S. Li. 2016. “Empirical Study on Spatial Spillover of Provincial Carbon Emissions and Influencing Factors in China.” 2016 Chinese Control and Decision Conference (CCDC): 1009–1013. https://doi.org/10.1109/CCDC.2016.7531131.
  • Urban Survey Organization of the National Bureau of Statistics. 2020. China City Statistical Yearbook 2020. Beijing: China Statistics Press.
  • Wang, M., and C. Feng. 2017. “Decomposition of Energy-Related CO2 Emissions in China: An Empirical Analysis Based on Provincial Panel Data of Three Sectors.” Applied Energy 190:772–787. https://doi.org/10.1016/j.apenergy.2017.01.007.
  • Wang, M. S., M. Maden, and X. J. Liu. 2017. “Exploring the Relationship Between Urban Forms and CO2 Emissions in 104 Chinese Cities.” Journal of Urban Planning and Development 143 (4): 04017014. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000400.
  • Wang, P., W. Wu, B. Zhu, and Y. Wei. 2013. “Examining the Impact Factors of Energy-Related CO2 Emissions Using the STIRPAT Model in Guangdong Province, China.” Applied Energy 106:65–71. https://doi.org/10.1016/j.apenergy.2013.01.036.
  • Wang, Q., J. J. Huang, H. Zhou, J. Q. Sun, and M. K. Yao. 2022. “Carbon Emission Inversion Model from Provincial to Municipal Scale Based on Nighttime Light Remote Sensing and Improved STIRPAT.” Sustainability 14 (11): 6813. https://doi.org/10.3390/su14116813.
  • Wang, S., C. Fang, X. Guan, B. Pang, and H. Ma. 2014. “Urbanisation, Energy Consumption, and Carbon Dioxide Emissions in China: A Panel Data Analysis of China’s Provinces.” Applied Energy 136:738–749. https://doi.org/10.1016/j.apenergy.2014.09.059.
  • Wang, S., C. Zhou, G. Li, and K. Feng. 2016. “CO2, Economic Growth, and Energy Consumption in China’s Provinces: Investigating the Spatiotemporal and Econometric Characteristics of China’s CO2 Emissions.” Ecological Indicators 69:184–195. https://doi.org/10.1016/j.ecolind.2016.04.022.
  • Wang, X. X., A. Z. He, and J. Zhao. 2020. “Regional Disparity and Dynamic Evolution of Carbon Emission Reduction Maturity in China’s Service Industry.” Journal of Cleaner Production 244:118926. https://doi.org/10.1016/j.jclepro.2019.118926.
  • Wang, Y., Y. Niu, M. Li, Q. Yu, and W. Chen. 2022. “Spatial Structure and Carbon Emission of Urban Agglomerations: Spatiotemporal Characteristics and Driving Forces.” Sustainable Cities and Society 78:103600. https://doi.org/10.1016/j.scs.2021.103600.
  • Wang, Z., F. Yin, Y. Zhang, and X. Zhang. 2012. “An Empirical Research on the Influencing Factors of Regional CO2 Emissions: Evidence from Beijing City, China.” Applied Energy 100:277–284. https://doi.org/10.1016/j.apenergy.2012.05.038.
  • Wei, W., X. Wang, H. Zhu, J. Li, S. Zhou, Z. Zou, and J. S. Li. 2017. “Carbon Emissions of Urban Power Grid in Jing-Jin-Ji Region: Characteristics and Influential Factors.” Journal of Cleaner Production 168:428–440. https://doi.org/10.1016/j.jclepro.2017.09.015.
  • Wu, J. S., S. B. He, J. Peng, W. Li, and X. Zhong. 2013. “Intercalibration of DMSP/OLS Night-Time Light Data by the Invariant Region Method.” An International Journal 34 (20): 7356–7368. https://doi.org/10.1080/01431161.2013.820365.
  • Wu, Y. Z., K. F. Shi, Z. Q. Chen, S. R. Liu, and Z. J. Chang. 2022. “Developing Improved Time-Series DMSP-OLS-Like Data (1992–2019) in China by Integrating DMSP-OLS and SNPP-VIIRS.” IEEE Transactions on Geoscience and Remote Sensing 60:4407714. https://doi.org/10.1109/TGRS.2021.3135333.
  • Xia, L. L., Y. Zhang, X. X. Sun, and J. J. Li. 2017. “Analyzing the Spatial Pattern of Carbon Metabolism and Its Response to Change of Urban Form.” Ecological Modelling 355:105–115. https://doi.org/10.1016/j.ecolmodel.2017.03.002.
  • Xiao, B. W., D. X. Niu, and H. Wu. 2017. “Exploring the Impact of Determining Factors Behind CO2 Emissions in China: A CGE Appraisal.” Science of the Total Environment 581:559–572. https://doi.org/10.1016/j.scitotenv.2016.12.164.
  • Xie, Y., and Q. Weng. 2016. “World Energy Consumption Pattern As Revealed by DMSP-OLS Nighttime Light Imagery.” GIScience & Remote Sensing 53 (2): 265–282. https://doi.org/10.1080/15481603.2015.1124488.
  • Xu, G., P. Schwarz, and H. Yang. 2020. “Adjusting Energy Consumption Structure to Achieve China’s CO2 Emissions Peak.” Renewable and Sustainable Energy Reviews 122:109737. https://doi.org/10.1016/j.rser.2020.109737.
  • Xue, W. B., Y. Lei, X. Liu, X. R. Shi, Z. Y. Liu, Y. L. Xu, X. J. Chen, et al. 2023. “Synergistic Assessment of Air Pollution and Carbon Emissions from the Economic Perspective in China.” Science of the Total Environment 858:159736. https://doi.org/10.1016/j.scitotenv.2022.159736.
  • Yang, F., J. M. Chou, W. J. Dong, M. Y. Sun, and W. X. Zhao. 2020. “Adaption to Climate Change Risk in Eastern China: Carbon Emission Characteristics and Analysis of Reduction Path.” Physics and Chemistry of the Earth 115:102829. https://doi.org/10.1016/j.pce.2019.102829.
  • Yu, B., K. Shi, Y. Hu, C. Huang, Z. Chen, and J. Wu. 2015. “Poverty Evaluation Using NPP-VIIRS Nighttime Light Composite Data at the County Level in China.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 8 (3): 1217–1229. https://doi.org/10.1109/JSTARS.2015.2399416.
  • Zhang, D., Z. Q. Wang, S. C. Li, and H. W. Zhang. 2021. “Impact of Land Urbanization on Carbon Emissions in Urban Agglomerations of the Middle Reaches of the Yangtze River.” International Journal of Environmental Research and Public Health 18 (4): 1403. https://doi.org/10.3390/ijerph18041403.
  • Zhang, X., J. Wu, J. Peng, and Q. Cao. 2017. “The Uncertainty of Nighttime Light Data in Estimating Carbon Dioxide Emissions in China: A Comparison Between DMSP-OLS and NPP-VIIRS.” Remote Sensing 9 (8): 797. https://doi.org/10.3390/rs9080797.
  • Zhao, B. Y., L. C. Sun, and L. Qin. 2022. “Optimization of China’s Provincial Carbon Emission Transfer Structure Under the Dual Constraints of Economic Development and Emission Reduction Goals.” Environmental Science and Pollution Research 29 (33): 50335–50351. https://doi.org/10.1007/s11356-022-19288-7.
  • Zheng, B., G. Geng, P. Ciais, S. J. Davis, R. V. Martin, J. Meng, N. Wu, et al. 2020. “Satellite-Based Estimates of Decline and Rebound in China’s CO2 Emissions During COVID-19 Pandemic.” Science Advances 6 (49): eabd4998. https://doi.org/10.1126/sciadv.abd4998.
  • Zheng, Y., Y. He, Q. Zhou, and H. Wang. 2022. “Quantitative Evaluation of Urban Expansion Using NPP-VIIRS Nighttime Light and Landsat Spectral Data.” Sustainable Cities and Society 76:103338. https://doi.org/10.1016/j.scs.2021.103338.
  • Zheng, Z. Y., Y. M. Zhu, F. D. Qiu, and L. T. Wang. 2022. “Coupling Relationship Among Technological Innovation, Industrial Transformation and Environmental Efficiency: A Case Study of the Huaihai Economic Zone, China.” Chinese Geographical Science 32 (4): 686–706. https://doi.org/10.1007/s11769-022-1294-0.
  • Zhou, C. S., and S. J. Wang. 2018. “Examining the Determinants and the Spatial Nexus of City-Level CO2 Emissions in China: A Dynamic Spatial Panel Analysis of China’s Cities.” Journal of Cleaner Production 171:917–926. https://doi.org/10.1016/j.jclepro.2017.10.096.
  • Zhu, B. Z., M. F. Zhang, Y. H. Zhou, P. Wang, J. C. Sheng, K. J. He, Y. M. Wei, and R. Xie. 2019. “Exploring the Effect of Industrial Structure Adjustment on Interprovincial Green Development Efficiency in China: A Novel Integrated Approach.” Energy Policy 134:110946. https://doi.org/10.1016/j.enpol.2019.110946.