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.
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.
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.
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.
Chen Q, 2014. Advanced Econometrics and Stata Applications. Bei**g: Higher Education Press. (in Chinese)
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.
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)
Guan D, Shan Y, Liu Z, 2016. CO2 emissions from China’s lime industry. Applied Energy, 166: 245–252.
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.
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.
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)
Kenny T, Gray N F, 2009. A preliminary survey of household and personal carbon dioxide emissions in Ireland. Environment International, 35(2): 259–272.
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)
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.
Mancini M S, Galli A, Niccolucci V et al., 2016. Ecological footprint: Refining the carbon footprint calculation. Ecological Indicators, 61: 390–403.
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.
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)
Rees W E, 1992. Ecological footprints and appropriated carrying capacity: What urban economics leaves out. Environment and Urbanization, 4(2): 121–130.
Rey S J, Janikas M V, 2006. STARS: Space-time analysis of regional systems. Geographical Analysis, 38(1): 67–86.
Röös E, Karlsson H, 2013. Effect of eating seasonal on the carbon footprint of Swedish vegetable consumption. Journal of Cleaner Production, 59: 63–72.
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.
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)
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.
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)
Wiedmann T M J, 2007. A definition of carbon footprint. Journal of the Royal Society of Medicine, 4(92): 193–195.
Wolfram P, Wiedmann T, Diesendorf M, 2016. Carbon footprint scenarios for renewable electricity in Australia. Journal of Cleaner Production, 124: 236–245.
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)
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)
**ao 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.
Xu J J, **ong 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)
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)
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)
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)
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.
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)
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)
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 **linhot City. Journal of Cleaner Production, 232: 408–416.
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)
Zhou D, Wu Z W, 2019. Potentialities and paths of Chinese industrial carbon emission reduction. China Environmental Science, 39(3): 412–420. (in Chinese)
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.
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)
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)
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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