TY - JOUR
T1 - Assessing the effects of unit cost uncertainty on flexible road pavement economics under the influence of climate change
AU - Qiao, Yaning
AU - Zhang, Shuyue
AU - Guo, Yaru
AU - Wang, Yaxin
AU - Santos, João
AU - Stoner, Anne
AU - Dawson, Andrew
AU - Ma, Tao
N1 - Funding Information:
The authors acknowledge the financial support from the National Natural Science Foundation of China (No. 52008388 and No. 51922030 ); and the National Key Research and Development Program of China (No. 2021YFB2600601 and No. 2021YFB2600600 ).
Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/8/15
Y1 - 2023/8/15
N2 - Pavement researchers typically adopt life cycle cost analysis (LCCA) to quantify changes in the economic performance of road pavements due to the effects of climate change. As uncertainty exists in the unit cost of materials, fuels, and machinery operation, the assessment of climate change-induced pavement costs invariably involves uncertainty. If such uncertainties remain unaddressed, the assessment of pavement costs will not be accurate. Therefore, this study develops a stochastic pavement LCCA framework to account for the effects of such uncertainties on climate change-induced pavement life cycle cost. This is achieved by integrating a sensitivity analysis methodology and Monte Carlo simulation. To demonstrate the applicability of the framework case studies are performed for standard interstate and standard primary road pavement sections in four climate zones in the United States under a high climate change Representative Concentration Pathway (RCP8.5) for four different periods between 1981 and 2100. The results show that pavement maintenance, end-of-life (EOL), and transportation costs are most affected by climate change. To assess climate change-induced pavement costs more accurately, it is important to improve the accuracy of gasoline, diesel, and hot mix asphalt (HMA) unit costs, as they are the most sensitive input to the pavement LCCA model.
AB - Pavement researchers typically adopt life cycle cost analysis (LCCA) to quantify changes in the economic performance of road pavements due to the effects of climate change. As uncertainty exists in the unit cost of materials, fuels, and machinery operation, the assessment of climate change-induced pavement costs invariably involves uncertainty. If such uncertainties remain unaddressed, the assessment of pavement costs will not be accurate. Therefore, this study develops a stochastic pavement LCCA framework to account for the effects of such uncertainties on climate change-induced pavement life cycle cost. This is achieved by integrating a sensitivity analysis methodology and Monte Carlo simulation. To demonstrate the applicability of the framework case studies are performed for standard interstate and standard primary road pavement sections in four climate zones in the United States under a high climate change Representative Concentration Pathway (RCP8.5) for four different periods between 1981 and 2100. The results show that pavement maintenance, end-of-life (EOL), and transportation costs are most affected by climate change. To assess climate change-induced pavement costs more accurately, it is important to improve the accuracy of gasoline, diesel, and hot mix asphalt (HMA) unit costs, as they are the most sensitive input to the pavement LCCA model.
KW - Climate change
KW - Monte Carlo simulation
KW - Pavement life cycle cost
KW - Sensitivity analysis
KW - Uncertainty
KW - n/a OA procedure
UR - http://www.scopus.com/inward/record.url?scp=85160447738&partnerID=8YFLogxK
U2 - 10.1016/j.jclepro.2023.137597
DO - 10.1016/j.jclepro.2023.137597
M3 - Article
AN - SCOPUS:85160447738
SN - 0959-6526
VL - 414
JO - Journal of cleaner production
JF - Journal of cleaner production
M1 - 137597
ER -