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Spatial-temporal characteristics and decoupling effects of China’s carbon footprint based on multi-source data

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Abstract

In 2007, China surpassed the USA to become the largest carbon emitter in the world. China has promised a 60%–65% reduction in carbon emissions per unit GDP by 2030, compared to the baseline of 2005. Therefore, it is important to obtain accurate dynamic information on the spatial and temporal patterns of carbon emissions and carbon footprints to support formulating effective national carbon emission reduction policies. This study attempts to build a carbon emission panel data model that simulates carbon emissions in China from 2000–2013 using nighttime lighting data and carbon emission statistics data. By applying the Exploratory Spatial-Temporal Data Analysis (ESTDA) framework, this study conducted an analysis on the spatial patterns and dynamic spatial-temporal interactions of carbon footprints from 2001–2013. The improved Tapio decoupling model was adopted to investigate the levels of coupling or decoupling between the carbon emission load and economic growth in 336 prefecture-level units. The results show that, firstly, high accuracy was achieved by the model in simulating carbon emissions. Secondly, the total carbon footprints and carbon deficits across China increased with average annual growth rates of 4.82% and 5.72%, respectively. The overall carbon footprints and carbon deficits were larger in the North than that in the South. There were extremely significant spatial autocorrelation features in the carbon footprints of prefecture-level units. Thirdly, the relative lengths of the Local Indicators of Spatial Association (LISA) time paths were longer in the North than that in the South, and they increased from the coastal to the central and western regions. Lastly, the overall decoupling index was mainly a weak decoupling type, but the number of cities with this weak decoupling continued to decrease. The unsustainable development trend of China’s economic growth and carbon emission load will continue for some time.

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References

  • Adewale C, Reganold J P, Higgins S et al., 2019. Agricultural carbon footprint is farm specific: Case study of two organic farms. Journal of Cleaner Production, 229: 795–805.

    Article  Google Scholar 

  • Alvarez S, Sosa M, Rubio A, 2015. Product and corporate carbon footprint using the compound method based on financial accounts. The case of Osorio wind farms. Applied Energy, 139: 196–204.

    Article  Google Scholar 

  • BP plc, 2019. The BP statistical review of world energy published in 2019 (2019-06-20). London: British Petroleum (BP), https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html.

    Google Scholar 

  • Cadarso M, Cadarso M, Gómez N et al., 2015. Quantifying Spanish tourism’s carbon footprint: The contributions of residents and visitors: A longitudinal study. Journal of Industrial Ecology, 23(6): 922–946.

    Google Scholar 

  • Chen Q, 2014. Advanced Econometrics and Stata Applications. Beijing: Higher Education Press. (in Chinese)

    Google Scholar 

  • Chen S, Chen B, 2012. Network environ perspective for urban metabolism and carbon emissions: A case study of Vienna, Austria. Environmental Science & Technology, 46(8): 4498–4506.

    Article  Google Scholar 

  • Gao C C, Liu X Z, Li M K et al., 2014. Spatiotemporal dynamics of carbon emissions by energy consumption in China from 1995 to 2014. Progress in Geography, 35(6): 747–757. (in Chinese)

    Google Scholar 

  • Guan D, Shan Y, Liu Z, 2016. CO2 emissions from China’s lime industry. Applied Energy, 166: 245–252.

    Article  Google Scholar 

  • Harris N L, Brown S, Hagen S C et al., 2012. Baseline map of carbon emissions from deforestation in tropical regions. Science, 336(6088): 1573–1576.

    Article  Google Scholar 

  • IPCC, 2013. The physical science basis. In: Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge and New York: Cambridge University Press.

    Google Scholar 

  • Jiang J L, Xu J G, Wu W J et al., 2014. Patterns and dynamics of China’s human-nature carbon source-sink system. Journal of Natural Resources, 29(5): 757–768. (in Chinese)

    Google Scholar 

  • Kenny T, Gray N F, 2009. A preliminary survey of household and personal carbon dioxide emissions in Ireland. Environment International, 35(2): 259–272.

    Article  Google Scholar 

  • Lu J Y, Huang X J, Cheng Y et al., 2013. Spatiotemporal changes of carbon footprint based on energy consumption in China. Geographical Research, 32(2): 326–336. (in Chinese)

    Google Scholar 

  • Lu W, Chen C, Su M et al., 2013. Urban energy consumption and related carbon emission estimation: A study at the sector scale. Frontiers of Earth Science, 7(4): 480–486.

    Article  Google Scholar 

  • Mancini M S, Galli A, Niccolucci V et al., 2016. Ecological footprint: Refining the carbon footprint calculation. Ecological Indicators, 61: 390–403.

    Article  Google Scholar 

  • NOAA, 2018. Global greenhouse gas reference network (2018-05-29). Boulder, CO, USA: National Oceanic & Atmospheric Administration (NOAA), https://www.esrl.noaa.gov/gmd/ccgg/trends/global.html.

    Google Scholar 

  • Pan J H, Li J F, 2016. Estimate and spatio-temporal dynamics of electricity consumption in China based on DMSP/OLS images. Geographical Research, 35(4): 627–638. (in Chinese)

    Google Scholar 

  • Rees W E, 1992. Ecological footprints and appropriated carrying capacity: What urban economics leaves out. Environment and Urbanization, 4(2): 121–130.

    Article  Google Scholar 

  • Rey S J, Janikas M V, 2006. STARS: Space-time analysis of regional systems. Geographical Analysis, 38(1): 67–86.

    Article  Google Scholar 

  • Röös E, Karlsson H, 2013. Effect of eating seasonal on the carbon footprint of Swedish vegetable consumption. Journal of Cleaner Production, 59: 63–72.

    Article  Google Scholar 

  • Steen-Olsen K, Wood R, Hertwich E G, 2016. The carbon footprint of Norwegian household consumption 1999–2012. Journal of Industrial Ecology, 20(3): 582–592.

    Article  Google Scholar 

  • Wang J H, Li X, 2015. The effect of sector decoupling between China’s industrial economic growth and carbon dioxide emissions. Economic Geography, 35(5): 105–110. (in Chinese)

    Google Scholar 

  • Wang S, Huang Y, Zhou Y, 2019. Spatial spillover effect and driving forces of carbon emission intensity at the city level in China. Journal of Cleaner Production, 29(2): 231–252.

    Google Scholar 

  • Wang W, Lin J Y, Cui S H et al., 2010. An overview of carbon footprint analysis. Environmental Science & Technology, 33(7): 71–78. (in Chinese)

    Google Scholar 

  • Wiedmann T M J, 2007. A definition of carbon footprint. Journal of the Royal Society of Medicine, 4(92): 193–195.

    Google Scholar 

  • Wolfram P, Wiedmann T, Diesendorf M, 2016. Carbon footprint scenarios for renewable electricity in Australia. Journal of Cleaner Production, 124: 236–245.

    Article  Google Scholar 

  • Wu H, Gu S Z, Gun X L et al., 2013. Analysis on relationship between carbon emissions from fossil energy consumption and economic growth in China. Journal of Natural Resources, 28(3): 381–390. (in Chinese)

    Google Scholar 

  • Wu W J, Jiang J L, Gao Q Z, 2014. Spatiotemporal patterns of carbon emission and carbon footprint in China during 2001–2009. Acta Ecologica Sinica, 34(22): 6722–6733. (in Chinese)

    Google Scholar 

  • Xiao H, Ma Z, Zhang P et al., 2018. Study of the impact of energy consumption structure on carbon emission intensity in China from the perspective of spatial effects. Natural Hazards, 99(3): 1365–1380.

    Article  Google Scholar 

  • Xu J J, Xiong D P, Wang H H, 2008. Panel cointegration test and causality analysis of the relationship between financial development and foreign trade in China. Economic Geography, 28(5): 82–87. (in Chinese)

    Google Scholar 

  • Zhang Q F, Fang K, Xu M et al., 2018. Review of carbon footprint research based on input-output analysis. Journal of Natural Resources, 33(2): 696–708. (in Chinese)

    Google Scholar 

  • Zhang Y H, Zhang P Y, 2012. Energy consumption carbon footprint of metropolitan district of Changchun and Jilin, China. Scientia Geographica Sinica, 32(9): 1099–1105. (in Chinese)

    Google Scholar 

  • Zhang Y N, Pan J H, 2019. Spatio-temporal simulation and differentiation pattern of carbon emissions in China based on DMSP/OLS nighttime light. China Environmental Science, 39(4): 1436–1446. (in Chinese)

    Google Scholar 

  • Zhang Y, Da Y, 2015. The decomposition of energy-related carbon emission and its decoupling with economic growth in China. Renewable & Sustainable Energy Reviews, 41: 1255–1266.

    Article  Google Scholar 

  • Zhao G M, Zhao G Q, Chen L Z et al., 2017. Research on spatial and temporal evolution of carbon emission intensity and its transition mechanism in China. China Population, Resources and Environment, 27(10): 84–93. (in Chinese)

    Google Scholar 

  • Zhao R Q, Huang X J, Zhong T Y, 2010. Research on carbon emission intensity and carbon footprint of different industrial spaces in China. Acta Geographica Sinica, 65(9): 1048–1057. (in Chinese)

    Google Scholar 

  • Zhao Y, Zhang Q, Li F Y, 2019. Patterns and drivers of household carbon footprint of the herdsmen in the typical steppe region of Inner Mongolia, China: A case study in Xilinhot City. Journal of Cleaner Production, 232: 408–416.

    Article  Google Scholar 

  • Zhong T Y, Huang X J, Wang B Y, 2010. On the degrees of decoupling and re-coupling of economic growth and expansion of construction land in China from 2002 to 2007. Journal of Natural Resources, 25(1): 18–31. (in Chinese)

    Google Scholar 

  • Zhou D, Wu Z W, 2019. Potentialities and paths of Chinese industrial carbon emission reduction. China Environmental Science, 39(3): 412–420. (in Chinese)

    Google Scholar 

  • Zhou X, Zhang M, Zhou M et al., 2017. A comparative study on decoupling relationship and influence factors between China’s regional economic development and industrial energy-related carbon emissions. Journal of Cleaner Production, 142: 783–800.

    Article  Google Scholar 

  • Zhu W B, Li S C, Zhu L Q, 2019. Ecosystem service footprint flow and the influencing factors within provinces, China. Geographical Research, 28(2): 337–347. (in Chinese)

    Google Scholar 

  • Zhuo L, Zhang X F, Zheng J et al., 2015. An EVI-based method to reduce saturation of DMSP/OLS nighttime light data. Acta Geographica Sinica, 70(8): 1339–1350. (in Chinese)

    Google Scholar 

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Correspondence to Jinghu Pan.

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Foundation

National Natural Science Foundation of China Youth Science Foundation Project; No.41701170; National Natural Science Foundation of China, No.41661025, No.42071216; Fundamental Research Funds for the Central Universities, No.18LZUJBWZY068

Zhang Yongnian (1991–), specialized in spatial economic analysis and industrial development strategy.

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Zhang, Y., Pan, J., Zhang, Y. et al. Spatial-temporal characteristics and decoupling effects of China’s carbon footprint based on multi-source data. J. Geogr. Sci. 31, 327–349 (2021). https://doi.org/10.1007/s11442-021-1839-7

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  • DOI: https://doi.org/10.1007/s11442-021-1839-7

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