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Economic development and multiple air pollutant emissions from the industrial sector

Environmental Science and Pollution Research volume 23, pages 2802–2812 (2016)Cite this article

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.

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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.

Author information

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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Keywords

  • Environmental Kuznets curve
  • Air pollution
  • Industrial sector
  • Key industry
  • Sectoral crediting mechanism
  • Industrial characteristics