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The Development of a CO 2 Emission Coefficient for Medium- and Heavy-Duty Vehicles with Different Road Slope Conditions Using Multiple Linear Regression, and Considering the Health Effects

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  • Natthakrit Bamrungwong

    (Graduate School, University of the Thai Chamber of Commerce, 126/1 Vibhavadi Rangsit Road, Dindaeng District, Bangkok 10400, Thailand)

  • Varin Vongmanee

    (School of Engineering, University of the Thai Chamber of Commerce, Dindaeng District, Bangkok 10400, Thailand)

  • Wanchai Rattanawong

    (School of Engineering, University of the Thai Chamber of Commerce, Dindaeng District, Bangkok 10400, Thailand)

Abstract

The current studies on carbon dioxide (CO 2 ) emissions and the impacts on public health focus mainly on evaluating CO 2 emissions from two types of emission sources. The first is a fixed source type from industrial plants, which can be controlled or easily evaluated. The second is a mobile source type from the transport sector, especially from medium- and heavy-duty vehicles (MHDVs), which produce high emissions. However, the common methods of evaluation of the average value of CO 2 emissions per kilometer of a vehicle use a general Intergovernmental Panel on Climate Change (IPCC) model that does not consider the topography or road conditions. This affects the accuracy of CO 2 emission assessments and, in turn, affects the accuracy of any analysis needed to establish health policies and the management of public health within the affected area. In this paper, therefore, we present the development of emission coefficient calculations with varying topography conditions for MHDVs with consideration of the health effects on the populace. The study area was the Asian highway network in Thailand that passes through all regions and is geographically diverse. Data were collected from the Department of Highway’s records, global positioning system (GPS) and electronic control unit (ECU) with data consisting of road data, slope, distance, traffic level and vehicle weight, as well as fuel consumption along the transportation route. To analyze and map out the correlation of the CO 2 emission coefficients for each road slope, we determined the coefficient of the CO 2 emissions using multiple linear regression analysis and validated this using Huber–White robust standard errors for heteroscedasticity. This method was more cost-efficient and time-efficient compared to the conventional approaches. We also created CO 2 emission maps with risk points for health effects, and we propose policy designs and plans to manage the traffic level in each of these areas prone to higher levels of such emissions.

Suggested Citation

  • Natthakrit Bamrungwong & Varin Vongmanee & Wanchai Rattanawong, 2020. "The Development of a CO 2 Emission Coefficient for Medium- and Heavy-Duty Vehicles with Different Road Slope Conditions Using Multiple Linear Regression, and Considering the Health Effects," Sustainability, MDPI, vol. 12(17), pages 1-21, August.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:17:p:6994-:d:405002
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    References listed on IDEAS

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    1. Mode Vasuaninchita & Varin Vongmanee & Wanchai Rattanawong, 2020. "The Novel Paradigm of Economics Driven for Local Smart Sustain Cities Modeling Using Exploratory Factor Analysis and Planning Technique Using Fuzzy Evaluation Decision Making," Sustainability, MDPI, vol. 12(3), pages 1-20, January.
    2. McKeil A.C., 2018. "Tim Dunne and Christian Reus-Smit: The Globalization of International Society," New Global Studies, De Gruyter, vol. 12(1), pages 119-121, April.
    3. Yaping Dong & Jinliang Xu & Xingliang Liu & Chao Gao & Han Ru & Zhihao Duan, 2019. "Carbon Emissions and Expressway Traffic Flow Patterns in China," Sustainability, MDPI, vol. 11(10), pages 1-12, May.
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