Assessment of the highway logistics on carbon footprint

Abstract

Developing the quality of the types of greenhouse gasses used within the global environment and reducing carbon emissions are recognized as the main of current logistic changes policies. The paper aims to evaluate the contribution of the impact of highway logistics activity, one of the most important causes of carbon dioxide emissions, on the carbon footprint of the Southern Central Anatolian provinces. In this context, multiple regression analyses were conducted in three locations in the Southern Central Anatolian (Antalya, Kayseri, Konya) involving a total of 12 monthly highway logistics activities and carbon emissions. Before analysis, summarized the status of all logistic activities in the study area and collected data related to carbon emission in these regions. However, the coupling relationship between carbon emissions and logistic conditions in regions was calculated by the regression model. The carbon footprint linked to logistics, for Antalya was 87% (R=0.87), for Kayseri was 94% (R=0.94), and for Konya was 63% (R=0.63). It can be seen that, in the multiple regression analysis, Kayseri has a higher carbon footprint than Antalya and Konya when an estimation of the quantile was carbon footprint. The main academic contribution of this study brings a new perspective to the future assessment of environmental policies and prepares a quantitative principle for the implementation of future carbon footprint policies.

Keywords

• Carbon footprint
• highway logistics
• multiple regression
• logistic
• transportation

References

1. [1]. Xiao, F., Hu, Z. H., Wang, K. X., and Fu, P. H. “Spatial distribution of energy consumption and carbon emission of regional logistics,” Sustainability, 7(7), 9140-9159, 2015.
2. [2]. Friedlingstein, P., Andrew, R.M., Rogelj, J., Peters, G.P., Canadell, J.G., Knutti, R.; Luderer, G., Raupach, M.R., Schaeffer, M. and Vuuren, D.P.V. “Persistent growth of CO2 emissions and implications for reaching climate targets”, Nat. Geosci. 7, 709–715, 2014.
3. [3]. Manabe, S. “Role of greenhouse gas in climate change”, Tellus A: Dynamic Meteorology and Oceanography, 71 (1), 1620078, 2019.
4. [4]. Wang, Q., Wang, S., and Li, R. “Determinants of decoupling economic output from carbon emission in the transport sector: A comparison study of four municipalities in China”, International Journal of Environmental Research and Public Health, 16 (19), 3729, 2019.
5. [5]. Ren, Y., and Fan, T. “Ecological land protection or carbon emission reduction? comparing the value neutrality of mainstream policy responses to climate change”, Forests, 12(12), 1789, 1-17, 2021.
6. [6]. Türk Standartları Enstitüsü (TSE). “Kurumsal karbon ayakizi”, Available: https://www.iso.org.tr/sanayi-kongresi/doc/Kurumsal_Karbon_Ayakizi_ISO_Kongre_TSE.pdf (accessed: 24 April 2022).
7. [7]. Zhang, S., Lee, C.K.M., Chan, H.K., Choy, K.L. and Wu, Z. “Swarm intelligence applied in green logistics: A literature review”, Engineering Applications Artificial Intelligence, 37, 154–169, 2015.
8. [8]. Corbett, C.J. and Klassen, R.D. “Extending the horizons: environmental excellence as key to improving operations”, Manufacturing and Service Operations Management, 8(1), 5-22, 2006.

9. [9]. Gonzalez, C., Korchia, M., Menuet, L. and Urbain, C. “How do socially responsible consumers consider consumption? An approach with the free associations method”, Recherche et Applications en Marketing (English Edition), 24(3), 25-41, 2009.
10. [10]. Mondal, P., Abhishek, K., Varun, A., Nitin, S., Prashant, V., Bhangale, U.D. and Dinesh, T. Critical review of trends in GHG emissions from global automotive sector. British Journal of Environment and Climate Change, 1(1), 1-12, 2011.
11. [11]. Krstanoski, N. "The Problem of Speeding In Macedonia: Reasons And Recommendations." Avaliable: https://scholar.googleusercontent.com/scholar?q=cache:pCupixEUWTkJ:scholar.google.com/+The+Problem+of+Speeding+In+Macedonia:+Reasons+And+Recommendations.%22+&hl=tr&as_sdt=0,5 (accessed: 26 April 2022).
12. [12]. Yang C., McCollum D., McCarthy R., and Leighty W. “Meeting an 80% reduction in greenhouse gas emissions from transportation by 2050: A case study in California”, Transportation Research Part D, 14, 147-156, 2009.
13. [13]. Piecyk, M. I., and McKinnon, A. C. “Forecasting the carbon footprint of road freight transport in 2020”, International Journal of Production Economics, 128(1), 31-42, 2010.
14. [14]. Bouchery, Y., Ghaffari, A., Jemai, Z., and Dallery, Y. (2012). “Including sustainability criteria into inventory models”, European Journal of Operational Research, 222(2), 229-240, 2012.
15. [15]. Chavez-Baeza, C. and Sheinbaum-Pardo, C. “Sustainable passenger road transport scenarios to reduce fuel consumption, air pollutants and GHG (greenhouse gas) emissions in the Mexico City Metropolitan Area”, Energy, 66, 624-634, 2014.
16. [16]. Quiros, DC., Smith, J., Thiruvengadam, A., Huai, T. andHu, SH. “Greenhouse gas emissions from heavy-duty natural gas, hybrid, and conventional diesel on road trucks during freight transport”, Atmospheric Environment, 36-45, 2017.
17. [17]. Gür, N.and Furuncu, Y. “Küresel otomotiv sektörünün değişimi ve yerli otomobil projesinin geleceği”, Siyaset, Ekonomi ve Toplum Araştırmaları Vakfı Yayınları, 127(1), 17-59, 2017.
18. [18]. Argun M. E., Ergüç R., and Sarı Y. “Konya/Selçuklu ilçesi karbon ayak izinin belirlenmesi”, Selçuk Üniversitesi Mühendislik, Bilim ve Teknoloji Dergisi, 7(2), 287-297, 2019.
19. [19]. Bogacki, M. and Bździuch, P. “Predicting the spatial distribution of emissions from urban buses based on previously measured data and scenarios for their modernization in the future. Case study: Krakow, Poland”, Atmospheric Environment, 1-14, 2019.
20. [20]. Bilgili, L., Çetinkaya, A., and Kuzu, S. L. “Life cycle comparison of passenger air and rail transportation”, Environmental Research and Technology, 5(1), 44-49, 2022.
21. [21]. Pedhazur, E.J. “Multiple Regression in Behavioral Research: Explanation and Prediction, 2nd ed., Rinehart and Winston, USA. 1982.
22. [22]. Bewick, V., Cheek, L., and Ball, J. “Statistics review 9: One-way analysis of variance”. Critical Care, 8(2), 1-7, 2004.