Abstract
Understanding the relationship between carbon emissions and vegetation carbon sequestration is essential for reducing the greenhouse effect. In this study, we constructed a carbon balance pressure index to measure the eco-environment pressure caused by carbon emissions in 77 countries from 2000 to 2015, and the logarithmic mean Divisia index decomposition method was used to identify the key factors related to carbon balance pressure. As the change in vegetation carbon sequestration is relatively stable, carbon emissions have become the direct cause of the rise in the global carbon balance pressure. The carbon balance pressure in advanced economies decreased slowly, while that in emerging economies increased but the growth rate decreased. The decomposition results showed that carbon intensity is the main factor restraining the rise of carbon balance pressure, while GDP per capita and land population pressure are the main driving forces, and vegetation carbon sequestration intensity plays only a small role. Further analysis showed that the restraining effect of carbon intensity can offset the incremental effect of GDP per capita in advanced economies, and the vegetation carbon sequestration intensity also has a positive impact, but not in emerging economies. Besides, different factors play different roles depending on the country. The conclusions were also supported by various robustness tests.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
The datasets used during the current study are available from the corresponding author on reasonable request.
Notes
BP Statistical Review of World Energy, available from https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html.
World Bank Open Data, available from https://data.worldbank.org.
Food and Agriculture Organization of the United Nations, available from http://www.fao.org/.
NPP Data, available from https://lpdaac.usgs.gov/products/mod17a3v055.
Environmental Performance Index 2018, available from https://sedac.ciesin.columbia.edu/data/set/epi-environmental-performance-index-2018.
IMF-World Economic Outlook 2019, available from https://www.imf.org/en/Publications/WEO/Issues/2019/10/01/world-economic-outlook-october-2019.
WMO, the global climate in 2011–2015, available from https://public.wmo.int/en.
References
Ali G (2018) Climate change and associated spatial heterogeneity of Pakistan: empirical evidence using multidisciplinary approach. Sci Total Environ 634:95–108. https://doi.org/10.1016/j.scitotenv.2018.03.170
Ang BW (2004) Decomposition analysis for policymaking in energy: which is the preferred method? Energy Policy 32:1131–1139. https://doi.org/10.1016/S0301-4215(03)00076-4
Ang BW (2015) LMDI decomposition approach: a guide for implementation. Energy Policy 86:233–238. https://doi.org/10.1016/j.enpol.2015.07.007
Ang BW, Liu N (2007a) Handling zero values in the logarithmic mean Divisia index decomposition approach. Energy Policy 35:238–246. https://doi.org/10.1016/j.enpol.2005.11.001
Ang BW, Liu N (2007b) Negative-value problems of the logarithmic mean Divisia index decomposition approach. Energy Policy 35:739–742. https://doi.org/10.1016/j.enpol.2005.12.004
Bin Mahbub R, Ahmedb N, Rahmana S, Hossainc MM, Suiauddina M (2019) Human appropriation of net primary production in Bangladesh, 1700–2100. Land Use Policy 87:104067. https://doi.org/10.1016/j.landusepol.2019.104067
Chang CP, Dong MY, Sui B, Chu Y (2019) Driving forces of global carbon emissions: from time- and spatial-dynamic perspectives. Econ Model 77:70–80. https://doi.org/10.1016/j.econmod.2019.01.021
Chen JD, Cheng SL, Song ML, Wu YY (2016) A carbon emissions reduction index: integrating the volume and allocation of regional emissions. Appl Energy 184:1154–1164. https://doi.org/10.1016/j.apenergy.2016.03.032
Chen JD, Cheng SL, Nikic V, Song ML (2018) Quo vadis? Major players in global coal consumption and emissions reduction. Transform Bus Econ 17:112–132
Chen C, Park T, Wang XH, Piao SL, Xu BD, Chaturvedi RK, Fuchs R, Brovkin V, Ciais P, Fensholt R, Tommervik H, Bala G, Zhu ZC, Nemani RR, Myneni RB (2019) China and India lead in greening of the world through land-use management. Nat Sustain 2:122–129. https://doi.org/10.1038/s41893-019-0220-7
Chen JD, Fan W, Li D, Liu X, Song ML (2020) Driving factors of global carbon footprint pressure: based on vegetation carbon sequestration. Appl Energy 267:114914. https://doi.org/10.1016/j.apenergy.2020.114914
Choi Y, Liu Y, Lee H (2017) The economy impacts of Korean ETS with an emphasis on sectoral coverage based on a CGE approach. Energy Policy 109:835–844. https://doi.org/10.1016/j.enpol.2017.06.039
Chuai XW, Yuan Y, Zhang XY, Guo XM, Zhang XL, Xie FJ, Zhao RQ, Li JB (2019) Multiangle land use-linked carbon balance examination in Nanjing City, China. Land Use Policy 84:305–315. https://doi.org/10.1016/j.landusepol.2019.03.003
Cialani C (2007) Economic growth and environmental quality: an econometric and a decomposition analysis. Manag Environ Qual Int J 18:568–577. https://doi.org/10.1108/14777830710778328
Davis SJ, Caldeira K (2010) Consumption-based accounting of CO2 emission. PNAS 107:5687–5692. https://doi.org/10.1073/pnas.0906974107
Dubey R, Gunasekaran A, Ali SS (2015) Exploring the relationship between leadership, operational practices, institutional pressures and environmental performance: a framework for green supply chain. Int J Prod Econ 160:120–132. https://doi.org/10.1016/j.ijpe.2014.10.001
Dubey R, Gunasekaran A, Childe SJ, Papadopoulos T, Hazen B, Giannakis M, Roubaud D (2017) Examining the effect of external pressures and organizational culture on shaping performance measurement systems (PMS) for sustainability benchmarking: some empirical findings. Int J Prod Econ 193:63–76. https://doi.org/10.1016/j.ijpe.2017.06.029
Fang X, Chen Z, Guo XL, Zhu SH, Liu T, Li CF, He B (2019) Impacts and uncertainties of climate/CO2 change on net primary productivity in Xinjiang, China (2000–2014): a modelling approach. Ecol Model 408:108742. https://doi.org/10.1016/j.ecolmodel.2019.108742
Feng C, Zheng CJ, Shan ML (2020) The clarification for the features, temporal variations, and potential factors of global carbon dioxide emissions. J Clean Prod 255:120250. https://doi.org/10.1016/j.jclepro.2020.120250
Field CB, Randerson JT, Malmström CM (1995) Global net primary production: combining ecology and remote sensing. Remote Sens Environ 51:74–88. https://doi.org/10.1016/0034-4257(94)00066-V
Field CB, Behrenfeld MJ, Randerson JT, Falkowski P (1998). Primary production of the biosphere: integrating terrestrial and oceanic components. Science 281: 237–240. https://doi.org/10.1126/science.281.5374.237
Galli A, Wiedmann T, Ercin E, Knoblauch D, Ewing B, Giljum S (2012) Integrating ecological, carbon and water footprint into a “footprint family” of indicators: definition and role in tracking human pressure on the planet. Ecol Indic 16:100–112. https://doi.org/10.1016/j.ecolind.2011.06.017
Guo R, Zhao YR, Shi Y, Li FT, Hu J, Yang HZ (2017) Low carbon development and local sustainability from a carbon balance perspective. Resour Conserv Recycl 122:270–279. https://doi.org/10.1016/j.resconrec.2017.02.019
Haberl H, Erb KH, Krausmann F (2014) Human appropriation of net primary production: patterns, trends, and planetary boundaries. Annu Rev Environ Resour 39:363–391. https://doi.org/10.1146/annurev-environ-121912-094620
Hanif I, Raza FMS, Gago-de-Santos P, Abbas Q (2019) Fossil fuels, foreign direct investment, and economic growth have triggered CO2 emissions in emerging Asian economies: some empirical evidence. Energy 171:493–501. https://doi.org/10.1016/j.energy.2019.01.011
Henriques ST, Borowiecki KJ (2017) The drivers of long-run CO2 emissions in Europe, North America and Japan since 1800. Energy Policy 101:537–549. https://doi.org/10.1016/j.enpol.2016.11.005
Huang XT, Luo GP, Han QF (2018) Temporospatial patterns of human appropriation of net primary production in Central Asia grasslands. Ecol Indic 91:555–561. https://doi.org/10.1016/j.ecolind.2018.04.045
Imhoff ML, Bounoua L, DeFries R, Lawrence WL, Sturzer D, Tucker CJ, Ricketts T (2004) The consequences of urban land transformation on net primary productivity in America. Remote Sens Environ 89:434–443. https://doi.org/10.1016/j.rse.2003.10.015
Ito A (2011) A historical meta-analysis of global terrestrial net primary productivity: are estimates converging. Glob Chang Biol 17:3161–3175. https://doi.org/10.1111/j.1365-2486.2011.02450.x
Jonek-Kowalska I (2019) Transformation of energy balances with dominant coal consumption in European economies and Turkey in the years 1990-2017. Oeconomia Copernicana 10:627–647. https://doi.org/10.24136/oc.2019.030
Li X, Xiong SZ, Li ZH, Zhou MX, Li HG (2019) Variation of global fossil-energy carbon footprints based on regional net primary productivity and the gravity model. J Clean Prod 213:225–241. https://doi.org/10.1016/j.jclepro.2018.12.044
Li J, Wang ZL, Lai CG (2020) Severe drought events inducing large decrease of net primary productivity in mainland China during 1982–2015. Sci Total Environ 703:135541. https://doi.org/10.1016/j.scitotenv.2019.135541
Liu Y, Lu YY (2015) The economic impact of different carbon tax revenue recycling schemes in China: a model-based scenario analysis. Appl Energy 141:95–105. https://doi.org/10.1016/j.apenergy.2014.12.032
Liu Y, Meng B, Hubacek K, Xue JJ, Feng KS, Gao YN (2016) ‘Made in China’: a reevaluation of embodied CO2 emissions in Chinese exports using firm heterogeneity information. Appl Energy 184:1106–1113. https://doi.org/10.1016/j.apenergy.2016.06.088
Liu Y, Tan XJ, Yu Y, Qi SZ (2017) Assessment of impacts of Hubei pilot emission trading schemes in China – a CGE-analysis using TermCO2 model. Appl Energy 189:762–769. https://doi.org/10.1016/j.apenergy.2016.05.085
Liu YY, Yang Y, Wang Q, Du XL, Li JL, Gang CC, Zhou W, Wang ZQ (2019) Evaluating the responses of net primary productivity and carbon use efficiency of global grassland to climate variability along an aridity gradient. Sci Total Environ 652:671–682. https://doi.org/10.1016/j.scitotenv.2018.10.295
Lu YY, Liu Y, Zhou MF (2017) Rebound effect of improved energy efficiency for different energy types: a general equilibrium analysis for China. Energy Econ 62:248–256. https://doi.org/10.1016/j.eneco.2017.01.010
Luo ZW, Gunasekaran A, Dubey R, Childe SJ, Papadopoulos T (2017) Antecedents of low carbon emissions supply chains. Int J Clim Change Strategies Manag 9:707–727. https://doi.org/10.1108/IJCCSM-09-2016-0142
Medková H, Vackár D, Weinzettel J (2017) Appropriation of potential net primary production by cropland in terrestrial ecoregions. J Clen Prod 150:294–300. https://doi.org/10.1016/j.jclepro.2017.03.002
Meng B, Liu Y, Andrew R, Zhou MF, Hubacek K, Xue JJ, Peters G, Gao YN (2018) More than half China’s CO2 emissions are form micro, small and medium-sized enterprises. Appl Energy 230:712–725. https://doi.org/10.1016/j.apenergy.2018.08.107
Milesi C, Elvidge CD, Nemaini RR, Running SW (2003) Assessing the impact of urban land development on net primary productivity in the Southeastern United States. Remote Sens Environ 86:401–410. https://doi.org/10.1016/S0034-4257(03)00081-6
Nabernegg S, Bednar-Friedl B, Munoz P, Titz M, Vogel J (2019) National policies for global emission reductions: effectiveness of carbon emission reductions in international supply chains. Ecol Econ 158:146–157. https://doi.org/10.1016/j.ecolecon.2018.12.006
Nejat P, Jomehzadeh F, Taheri MM, Gohari M, Majid MZA (2015) A global review of energy consumption, CO2 emissions and policy in the residential sector (with an overview of the top ten CO2 emitting counties). Renew Sust Energ Rev 43:843–862. https://doi.org/10.1016/j.rser.2014.11.066
Oliveira JAP, Doll CNH, Balaban O, Jiang P, Dreyfus M, Suwa A, Moreno-Penaranda R, Dirgahayani P (2013) Green economy and governance in cities: assessing good governance in key urban economic processes. J Clean Prod 58:138–152. https://doi.org/10.1016/j.jclepro.2013.07.043
Pachauri RK, Reisingereds A (2007) Climate change 2007: synthesis report. IPCC, Geneva
Pan YD, Birdsey RA, Fang JY, Houghton R, Kauppi PE, Kurz WA, Phillips OL, Shbidenko A, Lewis SL, Canadell JG, Ciais P, Jackon RB, Pacala SW, McGuire AD, Piao SL, Rautiainen A, Sitch S, Hayes D (2011) A large and persistent carbon sink in the world’s forests. Science 333:988–993. https://doi.org/10.1126/science.1201609
Pan XF, Uddin MK, Ai BW, Pan XY, Saima U (2019) Influential factors of carbon emissions intensity in OECD countries: evidence from symbolic regression. J Clean Prod 220:1194–1201. https://doi.org/10.1016/j.jclepro.2019.02.195
Qiu ZX, Feng ZK, Song YN, Li M, Zhang PP (2020) Carbon sequestration potential of forest vegetation in China from 2003 to 2050: predicting forest vegetation growth based on climate and the environment. J Clean Prod 252:119715. https://doi.org/10.1016/j.jclepro.2019.119715
Running SW, Zhao M (2015) Daily GPP and Annual NPP (MOD17A2/A3) Products NASA Earth Observing System MODIS Land Algorithm. In: University of Maryland and MODAPS SIPS – NASA (ed). NASA LP DAAC
Schandl H, Hatfield-Dodds S, Wiedmann T, Geschke A, Cai YY, West J, Newth D, Baynes T, Lenzen M, Owen A (2016) Decoupling global environmental pressure and economic growth: scenarios for energy use, materials use and carbon emissions. J Clean Prod 132:45–56. https://doi.org/10.1016/j.jclepro.06.100
Shi AQ (2003) The impact of population pressure on global carbon dioxide emissions, 1975/1996: evidence from pooled cross-country data. Ecol Econ 44:29–42. https://doi.org/10.1016/S0921-8009(02)00223-9
Shi H, Liu XP, Wang SJ, Liu XJ, Zhang H, Tang DM, L TH (2020) Global protected areas boost the carbon sequestration capacity: evidences from econometric causal analysis. Sci Total Environ 715:137001. https://doi.org/10.1016/j.scitotenv.2020.137001
Shuai CY, Shen LY, Jiao LD, Wu Y, Tan YT (2017) Identifying key impact factors on carbon emission: evidences from panel and time-series data of 125 countries from 1990 to 2011. Appl Energy 187:310–325. https://doi.org/10.1016/j.apenergy.2016.11.029
Steffen W, Richardson K, Rockstrom J, Cornell SE, Fetzer I, Bennett EM, Biggs R, Carpenter SR, De Vries W, De Wit CA, Folke C (2015) Planetary boundaries: guiding human development on a changing planet. Science 348(6240):1259855. https://doi.org/10.1126/science.1259855
Tan XJ, Liu Y, Cui JB, Su B (2018) Assessment of carbon leakage by channels: an approach combining CGE model and decomposition analysis. Energy Econ 74:535–545. https://doi.org/10.1016/j.eneco.2018.07.003
Teng MJ, Zeng LX, Hu WJ, Wang PC, Yan ZG, He W, Zhang Y, Huang ZL, Xiao WF (2020) The impacts of climate changes and human activities on net primary productivity vary across an ecotone zone in Northwest China. Sci Total Environ 714:136691. https://doi.org/10.1016/j.scitotenv.2020.136691
Teubner IE, Forkel M, Camps-Valls G, Jung M, Dorigo WA (2019) A carbon sink-driven approach to estimate gross primary production from microwave satellite observations. Remote Sens Environ 229:100–113. https://doi.org/10.1016/j.rse.2019.04.022
Tseng ML, Chiu SF, Tan RR, Siriban-Manalang AB (2013) Sustainable consumption and production for Asia: sustainability through green design and practice. J Clean Prod 40:1–5. https://doi.org/10.1016/j.jclepro.2012.07.015
Tseng ML, Chiu ASF, Ashton W, Moreau V (2019) Sustainable management of natural resources toward sustainable development goals. Resour Conserve Recy 145:419–421. https://doi.org/10.1016/j.resconrec.2019.03.012
Viglizzo EF, Ricard MF, Taboada MA, Vázquez-Amábile G (2019) Reassessing the role of grazing lands in carbon-balance estimations: meta-analysis and review. Sci Total Environ 661:531–542. https://doi.org/10.1016/j.scitotenv.2019.01.130
Wu YY, Wang P, Liu X, Chen JD, Song ML (2020) Analysis of regional carbon allocation and carbon trading based on net primary productivity in China. China Econ Rev 60:101401. https://doi.org/10.1016/j.chieco.2019.101401
Xu C, Liu M, An S, Chen JM, Yan P (2007) Assessing the impact of urbanization on regional net primary productivity in Jiangyin County, China. J Environ Manag 85:597–606. https://doi.org/10.1016/j.jenvman.2006.08.015
Xu Q, Dong YX, Yang R (2018) Influence of land urbanization on carbon sequestration of urban vegetation: a temporal cooperativity analysis in Guangzhou as an example. Sci Total Environ 635:26–34. https://doi.org/10.1016/j.scitotenv.2018.04.057
Yang Y, Fan MD (2019) Analysis of the spatial-temporal differences and fairness of the regional energy ecological footprint of the Silk Road Economic Belt (China Section). J Clean Prod 215:11246–11261. https://doi.org/10.1016/j.jclepro.2019.01.170
Yu DY, Shao HB, Shi PJ, Zhu WQ, Pan YZ (2009) How does the conversion of land cover to urban use affect net primary productivity? A case study in Shenzhen City, China. Agric For Meteorol 149:2054–2060. https://doi.org/10.1016/j.agrformet.2009.07.012
Yu LJ, Huang Y, Zhang W, Li TT, Sun WJ (2017) Methane uptake in global forest and grassland soils from 1981 to 2010. Sci Total Environ 607–608:1163–1172. https://doi.org/10.1016/j.scitotenv.2017.07.082
Zaidi SAH, Zafar MW, Shahbaz M, Hou F (2019) Dynamic linkages between globalization, financial development and carbon emissions: evidence from Asia Pacific Economic Cooperation countries. J Clean Prod 228:533–543. https://doi.org/10.1016/j.jclepro.2019.04.210
Zhao M, Kong ZH, Escobedo FJ, Gao J (2010) Impacts of urban forests on offsetting carbon emissions from industrial energy use in Hangzhou, China. J Environ Manag 91:807–813. https://doi.org/10.1016/j.jenvman.2009.10.010
Funding
This study was supported by the Major Program of the National Social Science Foundation of China (Grant No. 20ZDA084); the National Natural Science Foundation of China (Grant Nos. 71934001, 71471001, 41771568, 71533004); the National Key Research and Development Program of China (Grant No. 2016YFA0602500); the Strategic Priority Research Program of Chinese Academy of Sciences (Grant No. XDA23070400); and the Sichuan Province Social Science High Level Research Team Building.
Author information
Authors and Affiliations
Contributions
Jiandong Chen: writing–original draft, funding acquisition, formal analysis; Zhiwen Li: writing–review and editing, investigation, software; Malin Song: writing–review and editing, funding acquisition, supervision, validation, project administration; Yizhe Dong: writing–review and editing, methodology, conceptualization, data curation. All authors read and approved the final manuscript.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no competing interests.
Ethical approval
Not applicable.
Consent to participate
Not applicable.
Consent to publish
Not applicable.
Additional information
Responsible editor: Nicholas Apergis
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendices
Appendix A
Based on Eq. (4), CBPI was decomposed again according to the Laspeyres decomposition method, as follows.
Appendix B
Appendix C
Coal- and oil-related carbon emissions were calculated as follows:
where i represents the countries; j represents two types of energy sources (coal and oil); CONS is the total energy consumption; N is the low calorific value of energy; CC indicates the carbon content in the particular energy source; O is the carbon oxidation factor, which is assumed to be fixed at unity; and B is the molecule ratio of carbon dioxide to carbon, i.e., 44/12.
Rights and permissions
About this article
Cite this article
Chen, J., Li, Z., Song, M. et al. Decomposing the global carbon balance pressure index: evidence from 77 countries. Environ Sci Pollut Res 28, 7016–7031 (2021). https://doi.org/10.1007/s11356-020-11042-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11356-020-11042-1