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Evaluation of the Transport Environmental Effects of an Urban Road Network in a Medium-Sized City in a Developing Country

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  • Warunvit Auttha

    (Sustainable Infrastructure Research and Development Center (SIRDC), Department of Civil Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, Thailand)

  • Pongrid Klungboonkrong

    (Sustainable Infrastructure Research and Development Center (SIRDC), Department of Civil Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, Thailand)

Abstract

A decision support model (DSM) involving a combination of five different prediction models for the environmental effects of transport and the powerful HMADM approach was introduced for the first time to assess the multiple criteria environmental effects of transport in an urban road network of the Khon Kaen Metropolitan Municipality (KKMM) in Khon Kaen City, Thailand. Five mathematical models were adopted to quantify the CO 2 emissions (CO2Es), PM 2.5 concentration (PM2.5C), CO concentrations (COCs), noise levels (NOLs), and pedestrian accident risk (PAR) values of all road segments in the study area. The FAHP, FSM, and TOPSIS were integrated into the HMADM to estimate the composite transport environmental effect scores (CTEESs) of each road segment. The FAHP was applied to determine the relative weights of each environmental criterion for three land use types, and the FSM was utilized to transform linguistic (fuzzy) scores into numerical (crisp) scores. Both the FAHP and FSM are principally used to deal with uncertain, incomplete, and ambiguous (fuzzy) information that appears during decision-making processes. Finally, TOPSIS was used to estimate the CTEESs of each road segment. An integrated DSM was applied to comprehend and evaluate each individual environmental criterion and the combined environmental criteria for each road segment in the study area. The DSM was employed to rank the problematic locations of all road segments. For instance, the ranking of the top 12 road segments with the greatest CTEESs was 75, 80, 48, 89, 76, 5, 64, 59, 60, 16, 65, and 62. In addition, this DSM can also be used to identify the possible causes of such locations and allocate limited government budgets for the implementation of appropriate remedial measures for resolving such environmental problems due to transport in an urban road network in the study area.

Suggested Citation

  • Warunvit Auttha & Pongrid Klungboonkrong, 2023. "Evaluation of the Transport Environmental Effects of an Urban Road Network in a Medium-Sized City in a Developing Country," Sustainability, MDPI, vol. 15(24), pages 1-34, December.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:24:p:16743-:d:1298152
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    References listed on IDEAS

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