Environmental and Cost Impact Assessment of Pavement Materials Using IBEES Method

Abstract
For road pavements, hot-mix asphalt (HMA) and Portland cement concrete (PCC) are the materials most commonly used. In the selection of one of these materials, their economic performance and environmental performance are evaluated to determine which material exhibits excellent overall performance. However, no overall performance assessment exists in the construction community attributed to the lack of method providing easy-to-use and informative criteria for the decision-making process. Thus, in this paper, a new method that enables a comprehensive overall performance assessment is proposed, which is called Improved Building for Environmental and Economic Sustainability. After an eco-economic life-cycle assessment is performed, along with environmental performance and economic performance evaluation, the best-fit pavement material can be selected. This method has proven that the use of HMA for road pavements reduces the environmental impact by 27.1%P (i.e., percentage point), whereas the use of PCC reduces cost by 19.7%P. The existing Building for Environmental and Economic Sustainability (BEES) method shows that the performances of both HMA and PCC were over-assessed by 4.6%P and 7.4%P, respectively, since the environmental performance and economic performance cannot be computed quantitatively by incorporating the environmental and cost impact index into existing BEES model, the Improved BEES method accurately projects environmental performance and economic performance attained through the application of the environmental and cost impact index, hence, encouraging more informed decision. This method facilitates in articulating a quality decision making through the consideration of both the environmental performance and economic performance, hence reducing unnecessary costs generated from the trial and error due to the use of the existing method. Moreover, it promotes the development of a sustainable construction technology.
Funding Information
  • National Research Foundation of Korea (NRF-2018R1A5A1025137; NRF-2019R1C1C1010222)

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