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Economic development and multiple air pollutant emissions from the industrial sector

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Abstract

This study analyzed the relationship between economic growth and emissions of eight environmental air pollutants (carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), nitrogen oxide (NOx), sulfur oxide (SOx), carbon monoxide (CO), non-methane volatile organic compound (NMVOC), and ammonia (NH3)) in 39 countries from 1995 to 2009. We tested an environmental Kuznets curve (EKC) hypothesis for 16 individual industry sectors and for the total industrial sector. The results clarified that at least ten individual industries do not have an EKC relationship in eight air pollutants even though this relationship was observed in the country and total industrial sector level data. We found that the key industries that dictated the EKC relationship in the country and the total industrial sector existed in CO2, N2O, CO, and NMVOC emissions. Finally, the EKC turning point and the relationship between economic development and trends of air pollutant emissions differ among industries according to the pollution substances. These results suggest inducing new environmental policy design such as the sectoral crediting mechanism, which focuses on the industrial characteristics of emissions.

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Notes

  1. The EKC hypothesis has been tested in many countries using various pollutant data. EKC studies addressing SO2 emission and NOx emission are mainly from the 1990s and early 2000s (see Dinda 2004; Stern 2004). In recent EKC studies, most focus on CO2 emissions, such as in Scotland (Turner and Hanley 2011), Spain (Esteve and Tamarit 2012), 27 EU countries (Lopez-Menendez et al. 2014), 7 Arctic countries (Baek 2015), 19 OECD countries (Wang 2013), Turkey (de Vita et al. 2015), Vietnam (Al-Mulali et al. 2015), 14 Asian countries (Apergis and Ozturk 2015), and Tunisia (Jebli and Youssef 2015).

  2. Under a nominal distribution, 99.7 % of data are located between mean value ± three times of standard deviation. Therefore, the score located out of this data range can be understood as an extreme value.

  3. Only Luxembourg has a GDPper beyond the mean value plus three \( \sigma \). The mean value minus three \( \sigma \) is US$−27,607.

  4. The US EPA (2015) notes that “Ruminant animals (e.g., cattle, buffalo, sheep, goats, and camels) are the major emitters of CH4 because of their unique digestive system. Ruminants possess a rumen, or large ‘fore-stomach,’ in which microbial fermentation breaks down the feed they consume into products that can be absorbed and metabolized.” Behera et al. (2013) explain that most of the NH3 emissions are from the agricultural sector.

  5. Several control variables are defined as the ratio scale. In these example cases, we deduct both the numerator and denominator country data by the same for food industry data.

References

  • Al-Mulali U, Saboori B, Ozturk I (2015) Investigating the environmental Kuznets curve hypothesis in Vietnam. Energ Policy 76:123–131

    Article  Google Scholar 

  • Apergis N, Ozturk I (2015) Testing environmental Kuznets curve hypothesis in Asian countries. Ecol Indic 52:16–22

    Article  Google Scholar 

  • Baek J. (2015) Environmental Kuznets curve for CO2 emissions: the case of Arctic countries. Energy Economics 50:13–17

  • Balsalobre D, Álvarez A, Cantos JM (2015) Public budgets for energy RD & D and the effects on energy intensity and pollution levels. Environ Sci Pollut Res 22(7):4881–4892

    Article  Google Scholar 

  • Barros CP, Gil-Alana LA, Payne JE (2012) Evidence of long memory behavior in U.S. renewable energy consumption. Energ Policy 41:822–826

    Article  Google Scholar 

  • Barros CP, Alana LG, Payne JE (2013) U.S. disaggregated renewable energy consumption: persistence and long memory behavior. Energy Econ 40:425–432

    Article  Google Scholar 

  • Behera SN, Sharma M, Aneja VP, Balasubramanian R (2013) Ammonia in the atmosphere: a review on emission sources, atmospheric chemistry and deposition on terrestrial bodies. Environ Sci Pollut Res 20:8092–8131

    Article  CAS  Google Scholar 

  • Bhupendra KV, Sangle S (2015) What drives successful implementation of pollution prevention and cleaner technology strategy? The role of innovative capability. J Environ Manag 155:184–192

    Article  Google Scholar 

  • Cai W, Wang C, Chen J, Wang S (2012) Sectoral crediting mechanism: how far China has to go. Energ Policy 48:770–778

    Article  Google Scholar 

  • Cole MA, Rayner AJ, Bates JM (1997) The environmental Kuznets curve: an empirical analysis. Environ Dev Econ 2(4):401–416

    Article  Google Scholar 

  • de Leeuw FAAM (2002) A set of emission indicators for long-range transboundary air pollution. Environ Sci Pol 5:135–145

    Article  Google Scholar 

  • de Vita G, Katircioglu S, Altinay L, Fethi S, Mercan M (2015) Revisiting the environmental Kuznets curve hypothesis in a tourism development context. Environmental Science and Pollution Research (forthcoming)

  • Dinda S (2004) Environmental Kuznets curve hypothesis: a survey. Ecol Econ 49(4):431–455

    Article  Google Scholar 

  • Esteve V, Tamarit C (2012) Threshold cointegration and nonlinear adjustment between CO2 and income: the environmental Kuznets curve in Spain, 1857–2007. Energy Econ 34:2148–2156

    Article  Google Scholar 

  • Farzin YH, Bond CA (2006) Democracy and environmental quality. J Dev Econ 81:213–235

    Article  Google Scholar 

  • Fujii H, Managi S (2013) Which industry is greener? an empirical study of nine industries in OECD countries. Energ Policy 57:381–388

    Article  Google Scholar 

  • Fujii H, Managi S, Kaneko S (2013) Decomposition analysis of air pollution abatement in China: empirical study for ten industrial sectors from 1998 to 2009. J Clean Prod 59(15):22–31

    Article  CAS  Google Scholar 

  • Galeotti M, Manera M, Lanza A (2009) On the robustness of robustness checks of the environmental Kuznets curve hypothesis. Environ Resour Econ 42:551–574

    Article  Google Scholar 

  • Grossman GM, Krueger AB (1995) Economic growth and the environment. Q J Econ 110:353–377

    Article  Google Scholar 

  • Intergovernmental Panel on Climate Change (IPCC) (2014) Climate change 2014: mitigation of climate change. IPCC Fifth Assessment Report (AR5)

  • Jebli MB, Youssef SM (2015) The environmental Kuznets curve, economic growth, renewable and non-renewable energy, and trade in Tunisia. Renew Sust Energ Rev 47:173–185

    Article  Google Scholar 

  • Kan H, Chen B (2004) Particulate air pollution in urban areas of Shanghai, China: health-based economic assessment. Sci Total Environ 322(1-3):71–79

    Article  CAS  Google Scholar 

  • Leitão A (2010) Corruption and the environmental Kuznets curve: empirical evidence for sulfur. Ecol Econ 69(11):2191–2201

    Article  Google Scholar 

  • Levy JI, Greco SL (2007) Estimating health effects of air pollution in China: an introduction to intake fraction and the epidemiology. In: Ho MS, Nielsen CP (eds) Clearing the air: the health and economic damages of air pollution in China. MIT Press, Cambridge

    Google Scholar 

  • Lopez-Menendez AJ, Perez R, Moreno B (2014) Environmental costs and renewable energy: re-visiting the environmental Kuznets curve. J Environ Manag 145:368–373

    Article  Google Scholar 

  • Selden TM, Song D (1994) Environmental quality and development: is there a Kuznets curve for air pollution? J Environ Econ Manag 27:147–162

    Article  Google Scholar 

  • Steinbuks J (2012) Interfuel substitution and energy use in the U.K. manufacturing sector. Energy J 33(1):1–30

    Article  Google Scholar 

  • Stern DI (2004) The rise and fall of the environmental Kuznets curve. World Dev 32(8):1419–1439

    Article  Google Scholar 

  • Stern DI, Common MS (2001) Is there an environmental Kuznets curve for sulfur? J Environ Econ Manag 41:162–178

    Article  Google Scholar 

  • Timmer MP, Dietzenbacher E, Los B, Stehrer R, de Vries GJ (2015) An illustrated user guide to the world input? Output database: the case of global automotive production. Rev Int Econ 23:575–605

  • Tollefsen P, Rypdal K, Torvanger A, Rive N (2009) Air pollution policies in Europe: efficiency gains from integrating climate effects with damage costs to health and crops. Environ Sci Pol 12(7):870–881

    Article  CAS  Google Scholar 

  • Tsurumi T, Managi S (2010) Decomposition of the environmental Kuznets curve: scale, technique, and composition effects. Environ Econ Policy Study 11:19–36

    Article  Google Scholar 

  • Turner K, Hanley N (2011) Energy efficiency, rebound effects and the environmental Kuznets curve. Energy Econ 33:709–720

    Article  Google Scholar 

  • United Nations Environment Programme (UNEP) (2014) UNEP Year Book 2014 emerging issues update: air pollution: world’s worst environmental health risk. UNEP, Nairobi

  • United State Environmental Protection Agency (US EPA) (2015). DRAFT inventory of U.S. greenhouse gas emissions and sinks: 1990-2013, U.S. EPA

  • Wagner M (2008) The carbon Kuznets curve: a cloudy picture emitted by bad econometrics? Resour Energy Econ 30:388–408

    Article  Google Scholar 

  • Wang YC (2013) Functional sensitivity of testing the environmental Kuznets curve hypothesis. Resour Energy Econ 35:451–466

    Article  Google Scholar 

Download references

Acknowledgments

This research was funded by the Grant-in-Aid for Specially Promoted Research [26000001B]; the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan; and Grant-in-Aid for Research Activity Start-up [26881006B], MEXT, Japan. The results and conclusions of this article do not necessary represent the views of the funding agencies.

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Authors and Affiliations

  1. Graduate School of Fisheries and Environmental Sciences, Nagasaki University, 1-14 Bunkyo-machi, Nagasaki, 852-8521, Japan

    Hidemichi Fujii

  2. Department of Urban and Environmental Engineering, School of Engineering, Kyushu University, 744 Motooka, Nishiku, Fukuoka, 819-0395, Japan

    Shunsuke Managi

  3. QUT Business School, Queensland University of Technology, Level 8, Z Block, Gardens Point, 2 George St, Brisbane, QLD, 4000, Australia

    Shunsuke Managi

Authors
  1. Hidemichi Fujii
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  2. Shunsuke Managi
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Correspondence to Hidemichi Fujii.

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Responsible editor: Philippe Garrigues

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Fujii, H., Managi, S. Economic development and multiple air pollutant emissions from the industrial sector. Environ Sci Pollut Res 23, 2802–2812 (2016). https://doi.org/10.1007/s11356-015-5523-2

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