Skip to main content

Advertisement

Log in

Exploring necessary and sufficient conditions for carbon emission intensity: a comparative analysis

  • Research Article
  • Published:
Environmental Science and Pollution Research Aims and scope Submit manuscript

Abstract

This research investigates the factors influencing carbon emission intensity in 94 countries during 2018 using two qualitative methods: necessary condition analysis (NCA) and fuzzy-set qualitative comparative analysis (fsQCA). The study covers variables related to economics, human geography, energy, and institutions, showing significant variations among them. The NCA model identifies economic complexity and fossil energy consumption as necessary conditions for high-carbon emission intensity. On the other hand, the fsQCA model reveals sufficient conditions for both high- and low-carbon emission intensity, presenting different causal combinations of variables. For high-carbon emission intensity, nine causal solutions are identified, emphasizing the roles of economic growth, urbanization, fossil energy consumption, and institutional quality. Reducing carbon emission intensity requires addressing economic complexity and reducing reliance on fossil energy consumption. Policymakers should focus on sustainable economic development, environmentally friendly urbanization, and transitioning to renewable energy sources. This research’s originality lies in its qualitative approach, going beyond traditional regression methods to explore necessary and sufficient conditions for carbon emission intensity. It offers valuable insights into the complex interplay of variables, providing multiple causal configurations for both high- and low-carbon emission intensity.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

Data availability

The corresponding authors can provide the data used in the study on appropriate requests.

References

  • Acemoglu D, Johnson S, Robinson JA, Yared P (2012) Income and democracy. Am Econ J Macroecon 4(3):217–245. https://doi.org/10.1257/mac.4.3.217

    Article  Google Scholar 

  • Ali HS, Zeqiraj V, Lin WL, Law SH, Yusop Z, Bare UAA, Chin L (2019) Does quality institutions promote environmental quality? Environ Sci Pollut Res 26:10446–10456

    Article  Google Scholar 

  • Ali J, Akram V, Burhan M (2022a) Does economic complexity lead to global carbon emissions convergence? Environ Sci Pollut Res 29(30):45646–45655

    Article  Google Scholar 

  • Ali U, Guo Q, Kartal MT, Nurgazina Z, Khan ZA, Sharif A (2022b) The impact of renewable and non-renewable energy consumption on carbon emission intensity in China: fresh evidence from novel dynamic ARDL simulations. J Environ Manage 320:115782

    Article  CAS  Google Scholar 

  • Ali U, Guo Q, Nurgazina Z, Sharif A, Kartal MT, Depren SK, Khan A (2023) Heterogeneous impact of industrialization, foreign direct investments, and technological innovation on carbon emissions intensity: evidence from Kingdom of Saudi Arabia. Appl Energy 336:120804

    Article  Google Scholar 

  • Alonso-Dos-Santos M, Llanos-Contreras O (2019) Family business performance in a post-disaster scenario: the influence of socioemotional wealth importance and entrepreneurial orientation. J Bus Res 101:492–498. https://doi.org/10.1016/j.jbusres.2018.12.057

    Article  Google Scholar 

  • Amin N, Shabbir MS, Song H, Farrukh MU, Iqbal S, Abbass K (2023) A step towards environmental mitigation: do green technological innovation and institutional quality make a difference? Technol Forecast Soc Chang 190:122413

    Article  Google Scholar 

  • Ang BW (2007) Monitoring changes in economy-wide energy efficiency: from energy–GDP ratio to composite efficiency index. Energy Policy 35(4):2544–2551. https://doi.org/10.1016/j.enpol.2006.10.003

    Article  Google Scholar 

  • Awodumi OB, Adewuyi AO (2020) The role of non-renewable energy consumption in economic growth and carbon emission: evidence from oil producing economies in Africa. Energ Strat Rev 27:100434

    Article  Google Scholar 

  • Azam M, Liu L, Ahmad N (2021) Impact of institutional quality on environment and energy consumption: evidence from developing world. Environ Dev Sustain 23:1646–1667

    Article  Google Scholar 

  • Bakhsh S, Yin H, Shabir M (2021) Foreign investment and CO2 emissions: do technological innovation and institutional quality matter? Evidence from system GMM approach. Environ Sci Pollut Res 28(15):19424–19438

    Article  Google Scholar 

  • Boleti E, Garas A, Kyriakou A, Lapatinas A (2021) Economic complexity and environmental performance: evidence from a world sample. Environ Model Assess 26:251–270

    Article  Google Scholar 

  • Burke PJ, von Haldenwang C, Birkmann J (2009) Conflict and natural disasters: exploring the links between poverty and disaster vulnerability in Honduras. Disasters 33(4):559–580. https://doi.org/10.1111/j.1467-7717.2009.01110.x

    Article  Google Scholar 

  • Creutzig F, Goldschmidt JC, Lehmann P, Schmid E, von Blücher F (2015) The underestimated potential of solar energy to mitigate climate change. Nat Energy 1:16140. https://doi.org/10.1038/nenergy.2016.140

    Article  Google Scholar 

  • Ding H (2022) What kinds of countries have better innovation performance?–A country-level fsQCA and NCA study. J Innov Knowl 7(4):100215

    Article  Google Scholar 

  • Doğan B, Driha OM, Balsalobre Lorente D, Shahzad U (2021) The mitigating effects of economic complexity and renewable energy on carbon emissions in developed countries. Sustain Dev 29(1):1–12

    Article  Google Scholar 

  • Dong F, Yu B, Hadachin T, Dai Y, Wang Y, Zhang S, Long R (2018) Drivers of carbon emission intensity change in China. Resour Conserv Recycl 129:187–201

    Article  Google Scholar 

  • Dul J (2016) Necessary condition analysis (NCA): logic and methodology of “necessary but not sufficient” causality. Organ Res Methods 19(1):10–52. https://doi.org/10.1177/1094428115584005

    Article  Google Scholar 

  • Dul J, van der Laan E, Kuik R (2020) A statistical significance test for necessary condition analysis. Organ Res Methods 23(2):385–395. https://doi.org/10.1177/1094428118795272

    Article  Google Scholar 

  • Elahi E, Khalid Z, Zhang Z (2022) Understanding farmers’ intention and willingness to install renewable energy technology: a solution to reduce the environmental emissions of agriculture. Applied Energy 309:118459. https://doi.org/10.1016/j.apenergy.2021.118459

    Article  Google Scholar 

  • Elahi E, Khalid Z, Tauni MZ, Zhang H, Lirong X (2022) Extreme weather events risk to crop-production and the adaptation of innovative management strategies to mitigate the risk: a retrospective survey of rural Punjab, Pakistan. Technovation 117:102255. https://doi.org/10.1016/j.technovation.2021.102255

    Article  Google Scholar 

  • Energy Information Administration (EIA) (2023) Non-renewable energy consumption (million tone oil equivalent). Available online: https://www.eia.gov/international/data/world/

  • Fan G, Zhu A, Xu H (2023) Analysis of the impact of industrial structure upgrading and energy structure optimization on carbon emission reduction. Sustainability 15(4):3489. https://doi.org/10.3390/su15043489

    Article  CAS  Google Scholar 

  • Fischer C, Newell RG (2008) Environmental and technology policies for climate mitigation. J Environ Econ Manag 55(2):142–162. https://doi.org/10.1016/j.jeem.2007.08.005

    Article  Google Scholar 

  • Fiss PC (2011) Building better causal theories: a fuzzy set approach to typologies in organization research. Acad Manag J 54(2):393–420. https://doi.org/10.5465/amj.2011.60263120

    Article  Google Scholar 

  • Fragile States Index (FSI) (2023) Available online: https://fragilestatesindex.org/excel/

  • Godil DI, Sharif A, Agha H, Jermsittiparsert K (2020) The dynamic nonlinear influence of ICT, financial development, and institutional quality on CO2 emission in Pakistan: new insights from QARDL approach. Environ Sci Pollut Res 27:24190–24200

    Article  CAS  Google Scholar 

  • Haldar A, Sethi N (2021) Effect of institutional quality and renewable energy consumption on CO2 emissions− an empirical investigation for developing countries. Environ Sci Pollut Res 28(12):15485–15503

    Article  CAS  Google Scholar 

  • Huang Y, Zhu H, Zhang Z (2020) The heterogeneous effect of driving factors on carbon emission intensity in the Chinese transport sector: evidence from dynamic panel quantile regression. Sci Total Environ 727:138578

    Article  CAS  Google Scholar 

  • Huang Y, Li S, Xiang X, Bu Y, Guo Y (2022) How can the combination of entrepreneurship policies activate regional innovation capability? A comparative study of Chinese provinces based on fsQCA. J Innov Knowl 7(3):100227. https://doi.org/10.1016/j.jik.2022.100227

    Article  Google Scholar 

  • Jiao B (2019) Research of environmental assessment model based on fragile state index. In IOP Conf Ser: Mater Sci Eng 493(1):012038 (IOP Publishing)

    Article  Google Scholar 

  • Kazemzadeh E, Fuinhas JA, Salehnia N, Koengkan M, Shirazi M, Osmani F (2022) Factors driving CO2 emissions: the role of energy transition and brain drain. Environ Dev Sustain pp 1–28. https://doi.org/10.1007/s10668-022-02780-y

  • Kazemzadeh E, Fuinhas JA, Salehnia N, Koengkan M, Silva N (2023) Assessing influential factors for ecological footprints: a complex solution approach. J Clean Prod 414:137574. https://doi.org/10.1016/j.jclepro.2023.137574

  • Khezri M, Heshmati A, Khodaei M (2022) Environmental implications of economic complexity and its role in determining how renewable energies affect CO2 emissions. Appl Energy 306:117948

    Article  CAS  Google Scholar 

  • Koengkan M, Silva N, Fuinhas JA (2023) Assessing energy performance certificates for buildings: a fuzzy set qualitative comparative analysis (fsQCA) of Portuguese municipalities. Energies 2023(16):3240. https://doi.org/10.3390/en16073240

    Article  Google Scholar 

  • Kraus S, Ribeiro-Soriano D, Schussler M (2018) Fuzzy-set qualitative comparative analysis (fsQCA) in entrepreneurship and innovation research−the rise of a method. Int Entrep Manag J 14(1):15–33. https://doi.org/10.1007/s11365-017-0461-8

    Article  Google Scholar 

  • Kumpel E, Albert J, Peletz R, de Waal D, Hirn M, Danilenko A, ..., Khush R (2016) Urban water services in fragile states: an analysis of drinking water sources and quality in Port Harcourt, Nigeria, and Monrovia, Liberia. Am J Trop Med Hyg 95(1):229

  • Li W, Fan Y (2023) Influence of green finance on carbon emission intensity: empirical evidence from China based on spatial metrology. Environ Sci Pollut Res 30(8):20310–20326. https://doi.org/10.1007/s11356-022-23523-6

    Article  Google Scholar 

  • Li X, Ou X, Zhang X, Zhang Q, Zhang X (2013) Life-cycle fossil energy consumption and greenhouse gas emission intensity of dominant secondary energy pathways of China in 2010. Energy 50:15–23

    Article  CAS  Google Scholar 

  • Li HS, Geng YC, Shinwari R, Yangjie W, Rjoub H (2021) Does renewable energy electricity and economic complexity index help to achieve carbon neutrality target of top exporting countries? J Environ Manage 299:113386

    Article  CAS  Google Scholar 

  • Liu C, Zhao G (2021) Can global value chain participation affect embodied carbon emission intensity? J Clean Prod 287:125069

    Article  Google Scholar 

  • Maino R, Emrullahu D (2022) Climate change in Sub-Saharan Africa fragile states: evidence from panel estimations. International Monetary Fund. https://www.imf.org/en/Publications/WP/Issues/2022/03/18/Climate-Change-in-Sub-Saharan-Africa-Fragile-States-Evidence-from-Panel-Estimations-515159

  • Mendel JM, Korjani MM (2012) Charles Ragin’s fuzzy set qualitative comparative analysis (fsQCA) used for linguistic summarizations. Inf Sci 202:1–23

    Article  Google Scholar 

  • Misangyi VF, Greckhamer T, Furnari S, Fiss PC, Crilly D, Aguilera R (2017) Embracing causal complexity: the emergence of a neo-configurational perspective. J Manag 43(1):255–282. https://doi.org/10.1177/0149206316679252

    Article  Google Scholar 

  • Newman P, Beatley T, Boyer H (2012) Resilient cities: responding to peak oil and climate change. Island Press

    Google Scholar 

  • Observatory of Economic Complexity (OEC) (2023) Economic complexity index. Available online: https://oec.world/en/rankings/eci/hs6/hs96

  • Our World in Data (OWD) (2023) Carbon emission intensity of economies. Available online: https://ourworldindata.org/grapher/co2-intensity

  • Pan X, Uddin MK, Ai B, Pan X, Saima U (2019) Influential factors of carbon emissions intensity in OECD countries: evidence from symbolic regression. J Clean Prod 220:1194–1201

    Article  Google Scholar 

  • Pappas IO, Woodside AG (2021) Fuzzy-set qualitative comparative analysis (fsQCA): guidelines for research practice in information systems and marketing. Int J Inf Manag 58:102310. https://doi.org/10.1016/j.ijinfomgt.2021.102310

    Article  Google Scholar 

  • Ragin CC (1987) The comparative method: moving beyond qualitative and quantitative strategies. Univ, California Press

    Google Scholar 

  • Ragin CC (2008) Redesigning social inquiry: fuzzy sets and beyond. University of Chicago Press, Chicago

    Book  Google Scholar 

  • Rehman A, Ma H, Ozturk I (2021) Do industrialization, energy importations, and economic progress influence carbon emission in Pakistan. Environ Sci Pollut Res 28:45840–45852

    Article  CAS  Google Scholar 

  • Rihoux B, Ragin CC (2009) Configurational comparative methods: qualitative comparative analysis (QCA) and related techniques, vol 51. Sage Publications, Thousand Oaks, CA

    Book  Google Scholar 

  • Romero JP, Gramkow C (2021) Economic complexity and greenhouse gas emissions. World Dev 139:105317

    Article  Google Scholar 

  • Salman M, Long X, Dauda L, Mensah CN (2019) The impact of institutional quality on economic growth and carbon emissions: evidence from Indonesia, South Korea and Thailand. J Clean Prod 241:118331

    Article  Google Scholar 

  • Schneider CQ, Wagemann C (2012) Set-theoretic methods for the social sciences: a guide to qualitative comparative analysis. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Schneider MR, Schulze-Bentrop C, Paunescu M (2010) Mapping the institutional capital of high-tech firms: a fuzzy-set analysis of capitalist variety and export performance. J Int Bus Stud 41(2):246–266

    Article  Google Scholar 

  • Sugiura A, Nagata D, Fujikura R, Nakata T (2020) The causal relationships between energy consumption and carbon dioxide emissions in the ASEAN-5 countries. Environ Sci Pollut Res 27(11):12260–12273. https://doi.org/10.1007/s11356-020-07874-8

    Article  Google Scholar 

  • Taghvaee VM, Nodehi M, Saboori B (2022) Economic complexity and CO2 emissions in OECD countries: sector-wise Environmental Kuznets Curve hypothesis. Environ Sci Pollut Res 29(53):80860–80870

    Article  Google Scholar 

  • Tao M, Sheng MS, Wen L (2023) How does financial development influence carbon emission intensity in the OECD countries: some insights from the information and communication technology perspective. J Environ Manag 335:117553. https://doi.org/10.1016/j.jenvman.2023.117553

    Article  Google Scholar 

  • Woodside AG (2013) Moving beyond multiple regression analysis to algorithms: calling for adoption of a paradigm shift from symmetric to asymmetric thinking in data analysis and crafting theory. J Bus Res 64(4):463–472

    Article  Google Scholar 

  • Woodside AG, Zhang M (2013) Cultural diversity and marketing transactions: are market integration, large community size, and world religions necessary for fairness in ephemeral exchanges? Psychol Mark 30(3):263–276. https://doi.org/10.1002/mar.20603

    Article  Google Scholar 

  • World Bank Open Data (WBD) (2023a) GDP (constant 2015 US$). Available online: https://data.worldbank.org/indicator/NY.GDP.MKTP.KD. Accessed 7 Jan 2023

  • World Bank Open Data (WBD) (2023b) Urban population (% of total population). Available online: https://data.worldbank.org/indicator/SP.URB.TOTL.IN.ZS. Accessed 7 Jan 2023

  • World Bank Open Data (WBD) (2023c) Industry (including construction), value added (% GDP). Available online: https://data.worldbank.org/indicator/NV.IND.TOTL.ZS. Accessed 7 Jan 2023

  • World Bank Open Data (WBD) (2023d) Worldwide Governance Indicators (WGI). Available online: https://info.worldbank.org/governance/wgi/. Accessed 7 Jan 2023

  • Xiao H, Ma Z, Zhang P, Liu M (2019) Study of the impact of energy consumption structure on carbon emission intensity in China from the perspective of spatial effects. Nat Hazards 99:1365–1380

    Article  Google Scholar 

  • Xiong Q, Sun D (2022) Influence analysis of green finance development impact on carbon emissions: an exploratory study based on fsQCA. Environ Sci Pollut Res 30(22):61369–61380. https://doi.org/10.1007/s11356-021-18351-z

  • Xue LM, Meng S, Wang JX, Liu L, Zheng ZX (2020) Influential factors regarding carbon emission intensity in China: a spatial econometric analysis from a provincial perspective. Sustainability 12(19):8097

    Article  Google Scholar 

  • Zhang YJ, Liu Z, Zhang H, Tan TD (2014) The impact of economic growth, industrial structure and urbanization on carbon emission intensity in China. Nat Hazards 73:579–595

    Article  Google Scholar 

  • Zhang F, Deng X, Phillips F, Fang C, Wang C (2020) Impacts of industrial structure and technical progress on carbon emission intensity: evidence from 281 cities in China. Technol Forecast Soc Chang 154:119949

    Article  Google Scholar 

  • Zhou G, Zhu J, Luo S, Wu Z, Jiang Y (2020) An evaluation method of Fragile States Index based on climate shock: a case of Bangladesh. J Environ Manage 275:111142

    Article  Google Scholar 

Download references

Funding

The research is supported by the postdoctoral project grant of Ferdowsi University of Mashhad (FUM), Economics Department (Faculty of Economics and Administrative Sciences). The research is supported by the CeBER, R&D unit, funded by national funds through FCT–Fundação para a Ciência e a Tecnologia, I.P., project UIDB/05037/2020. UCILeR is an R&D Unit accredited and funded by the FCT–Portugal National Agency within the scope of its strategic project: UIDB/04643/2020.

Author information

Authors and Affiliations

Authors

Contributions

E.K.: writing-original draft and editing, validation, data curation, and project administration, conceptualization, formal analysis, and visualization; J.A.F.: introduction and editing; N.S.: supervision and editing; M.K.: discussion and editing; N.M.S.: data and methodology and editing. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Narges Salehnia.

Ethics declarations

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Responsible Editor: Ilhan Ozturk

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

The authors attested that this paper has not been published elsewhere, the work has not been submitted simultaneously for publication elsewhere, and the results presented in this work are true and not manipulated.

Appendix

Appendix

Please see Tables 8 and 9.

Table 8 Variable definition
Table 9 Country list (94 countries)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kazemzadeh, E., Fuinhas, J.A., Salehnia, N. et al. Exploring necessary and sufficient conditions for carbon emission intensity: a comparative analysis. Environ Sci Pollut Res 30, 97319–97338 (2023). https://doi.org/10.1007/s11356-023-29260-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11356-023-29260-8

Keywords

Navigation