Green Commute: Reducing Carbon Footprint in Commuting Scenarios in Karaj | ||
| Sustainable Earth Trends | ||
| دوره 4، شماره 1، 2024، صفحه 29-37 اصل مقاله (543.85 K) | ||
| نوع مقاله: Original Research Article | ||
| شناسه دیجیتال (DOI): 10.48308/set.2024.235335.1046 | ||
| نویسندگان | ||
| Shima Oveisi1؛ Mazaher Moeinaddini* 2 | ||
| 1Institute of Space and Atmospheric Studies, University of Saskatchewan, Saskatoon, Canada | ||
| 2Department of Environmental Sciences, Faculty of Natural Resources, University of Tehran, Karaj, Iran | ||
| چکیده | ||
| This study addresses the substantial contribution of mobile sources in commuting to greenhouse gas (GHG) emissions in megacities and underscores strategies for carbon footprint emission reduction. Field interviews and questionnaires facilitate data collection, enabling the classification of the studied vehicle fleet based on various parameters. The scenarios aim to minimize GHGs from the commute, utilizing the International Vehicle Emission (IVE) model to establish a primary carbon footprint emission inventory for commuting in Karaj. The base scenario reveals that commuting in Karaj produces 1579423 grams of CO2e, with CO2, N2O, and CH4 emissions at 1389039 grams, 43.74 grams, and 6385.38 grams, respectively. Three carbon footprint reduction scenarios, involving removing diesel vehicles, adopting natural gas-fueled vehicles, and replacing Euro 4 and 5 with older vehicles, demonstrate that the removal of diesel vehicles (S1) and adopting natural gas-fueled vehicles, and replacing Euro 4 and 5 with older vehicles (S3) are the most effective strategies, achieving a 99% efficiency rate in reducing CO2e. This study highlights the substantial impact of curbing carbon emissions from GHGs. S1 and S3 show significant reductions in carbon footprint emissions, emphasizing the crucial role of strategic planning and greenhouse gas minimization in controlling emissions from commuting. These findings underscore the critical importance of reducing carbon footprints and commuting to effectively mitigate GHGs in congested urban areas. | ||
| کلیدواژهها | ||
| Air pollution؛ Carbon footprint؛ Commute؛ IVE؛ Karaj | ||
| مراجع | ||
|
Bun, R., Nahorski, Z., Horabik-Pyzel, J., Danylo, O., See, L., Charkovska, N., Topylko, P., Halushchak, M., Lesiv, M., Valakh, M. & Kinakh, V., 2019. Development of a high-resolution spatial inventory of greenhouse gas emissions for Poland from stationary and mobile sources. Mitigation and Adaptation Strategies for Global Change, 24(6), 853-880.
Caetano, A.C., da Costa, A.M.S., Janeiro, V., Soares, P.H., Cancino, L.R. & Andrade, C.M.G., 2023. Fugitive Emissions from Mobile Sources— Experimental Analysis in Buses Regulated by the Euro 5 Standard. Atmosphere, 14(4), 613.
Crayton, T.J. & Meier, B.M., 2017. Autonomous vehicles: Developing a public health research agenda to frame the future of transportation policy. Journal of Transport & Health, 6, 245-252.
deSouza, P., Lu, R., Kinney, P. & Zheng, S., 2021. Exposures to multiple air pollutants while commuting: Evidence from Zhengzhou, China. Atmospheric Environment, 247, 118168.
Geng, N., Wang, J., Xu, Y., Zhang, W., Chen, C. & Zhang, R., 2013. PM2.5 in an industrial district of Zhengzhou, China: Chemical composition and source apportionment. Particuology, 11(1), 99-109
Geng, Y., Ma, Z., Xue, B., Ren, W., Liu, Z. & Fujita, T., 2013. Co-benefit evaluation for urban public transportation sector – a case of Shenyang, China. Journal of Cleaner Production, 58, 82-91.
Hamzacebi, C.K.I., 2015. Forecasting the energy-related CO2 emissions of Turkey using a grey prediction model. Energy Source, 37(9):1, 1023–1103.
Hao, P., Wu, G. & Saikaly, P., 2015. Evaluation of sampling strategies for vehicular emission estimation 2 using probe vehicles 3.
Hassani, A. & Maleki, A., 2021. Projection of passenger cars’ fuel demand and greenhouse gas emissions in Iran by 2050. Energy Conversion and Management: X, 12, 100126.
Holian, M.J. & Kahn, M.E., 2015. Household carbon emissions from driving and center city quality of life. Ecological Economics, 116, 362-368.
Johnson, T., 2014. Vehicular Emissions in Review. SAE International Journal of Engines, 7(3), 1207-1227.
Kissinger, M. & Reznik, A., 2019. Detailed urban analysis of commute-related GHG emissions to guide urban mitigation measures. Environmental Impact Assessment Review, 76, 26-35.
Litman, T., 2013. Comprehensive evaluation of energy conservation and emission reduction policies. Transportation Research Part A: Policy and Practice, 47, 153-166.
Lynch, J., Cain, M., Pierrehumbert, R. & Allen, M., 2020. Demonstrating GWP*: a means of reporting warming-equivalent emissions that captures the contrasting impacts of short-and long-lived climate pollutants. Environmental Research Letters, 15(4), 044023.
Marais, E.A., Akker, O. & Wiedinmyer, C., 2022. Greenhouse gas and air pollutant emissions from power barges (powerships). Environmental Science: Advances, 1(2), 164-169.
Massar, M., Reza, I., Rahman, S.M., Abdullah, S.M.H., Jamal, A. & Al-Ismail, F.S., 2021. Impacts of Autonomous Vehicles on Greenhouse Gas Emissions—Positive or Negative? International Journal of Environmental Research and Public Health, 18(11), 5567.
Mbandi, A.M., Malley, C.S., Schwela, D., Vallack, H., Emberson, L. & Ashmore, M.R., 2023. Assessment of the impact of road transport policies on air pollution and greenhouse gas emissions in Kenya. Energy Strategy Reviews, 49, 101120.
Moeinaddini, M., Taleshi, A. & Azimi Yancheshmeh, R., 2017. Spatial modeling of air pollutant emissions from mobile sources in Karaj. Department of Human Environment, 70(4), 935-947.
Molina, J.A., Gimenez-Nadal, J.I. & Velilla, J., 2020. Sustainable Commuting: Results from a Social Approach and International Evidence on Carpooling. Sustainability, 12(22), 9587.
Moreira, J.R., Pacca, S.A. & Goldemberg, J., 2022. The reduction of CO2e emissions in the transportation sector: Plug-in electric vehicles and biofuels. Renewable and Sustainable Energy Transition, 2, 100032.
Nanaki, E.A., Koroneos, C.J., Xydis, G.A. & Rovas, D., 2014. Comparative environmental assessment of Athens urban buses—Diesel, CNG and biofuel powered. Transport Policy, 35, 311-318.
Pathak, S.K., Sood, V., Singh, Y. & Channiwala, S., 2016. Real-world vehicle emissions: Their correlation with driving parameters. Transportation Research Part D: Transport and Environment, 44, 157-176.
Rouhi, K., Shafiepour Motlagh, M. & Dalir, F., 2023. Developing a carbon footprint model and environmental impact analysis of municipal solid waste transportation: A case study of Tehran, Iran. Journal of the Air & Waste Management Association, 73(12), 890-901.
Shaarawi, S.I., Abutaleb, K., Aboelmagd, A.R. & Temraz, T., 2023. GHGs emission reductions and economic saving by enhancing switching to natural gas vehicles in Egypt. Bulletin of the National Research Centre, 47(1), 107.
Shahbazi, H., Reyhanian, M., Hosseini, V. & Afshin, H., 2016. The relative contributions of mobile sources to air pollutant emissions in Tehran, Iran: an emission inventory approach. Emission control science and technology, 2, 44-56.
Thøgersen, J., Vatn, A., Aasen, M., Dunlap, R.E., Fisher, D.R., Hellevik, O. & Stern, P., 2021. Why do people continue driving conventional cars despite climate change? Social-psychological and institutional insights from a survey of Norwegian commuters. Energy Research & Social Science, 79, 102168.
Viteri, R., Borge, R., Paredes, M., & Perez, M.A., 2023. A high resolution vehicular emissions inventory for Ecuador using the IVE modelling system. Chemosphere, 315, 137634.
Wang, C., Cai, W., Lu, X. & Chen, J., 2007. CO2 mitigation scenarios in China’s road transport sector. Energy Conversion and Management, 48(7), 2110-2118.
Wang, H., Chen, C., Huang, C. & Fu, L., 2008. On-road vehicle emission inventory and its uncertainty analysis for Shanghai, China. Science of the total Environment, 398(1-3), 60-67.
WHO, A., 2016. World health statistics 2016: monitoring health for the SDGs sustainable development goals. World Health Organization. | ||
|
آمار تعداد مشاهده مقاله: 62,616 تعداد دریافت فایل اصل مقاله: 390 |
||