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The effect of agency budgets on minimizing greenhouse gas emissions from road rehabilitation policies
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https://doi.org/10.1088/1748-9326/10/11/114007Abstract
Transportation agencies are being urged to reduce their greenhouse gas (GHG) emissions. One possible solution within their scope is to alter their pavement management system to include environmental impacts. Managing pavement assets is important because poor road conditions lead to increased fuel consumption of vehicles. Rehabilitation activities improve pavement condition, but require materials and construction equipment, which produce GHG emissions as well. The agency's role is to decide when to rehabilitate the road segments in the network. In previous work, we sought to minimize total societal costs (user and agency costs combined) subject to an emissions constraint for a road network, and demonstrated that there exists a range of potentially optimal solutions (a Pareto frontier) with tradeoffs between costs and GHG emissions. However, we did not account for the case where the available financial budget to the agency is binding. This letter considers an agency whose main goal is to reduce its carbon footprint while operating under a constrained financial budget. A Lagrangian dual solution methodology is applied, which selects the optimal timing and optimal action from a set of alternatives for each segment. This formulation quantifies GHG emission savings per additional dollar of agency budget spent, which can be used in a cap-and-trade system or to make budget decisions. We discuss the importance of communication between agencies and their legislature that sets the financial budgets to implement sustainable policies. We show that for a case study of Californian roads, it is optimal to apply frequent, thin overlays as opposed to the less frequent, thick overlays recommended in the literature if the objective is to minimize GHG emissions. A promising new technology, warm-mix asphalt, will have a negligible effect on reducing GHG emissions for road resurfacing under constrained budgets.
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