The redevelopment of former industrial sites can have positive impacts on the environment, economic development, and quality of life in a given community. The federal brownfields initiative of the 1990s was intended to encourage environmental remediation of properties that are typically less contaminated than Superfund sites. Additionally, states have adopted programs that limit environmental liability and allow for risk-based cleanup standards, both of which should encourage a would-be investor or developer. Based on the statistical analysis of data collected from two nationwide surveys, this research shows that factors other than environmental concerns can impact the successful redevelopment of a brownfield. Analyses of the data using descriptive statistics, exploratory data analysis, factor analysis, and hypothesis testing indicate that the following are also influential factors: time to occupancy, total development costs, community support, proposed land use, condition of the local infrastructure, wil...

Impact fees are charges paid by developers to defray the costs of capital improvements made necessary by development. The charges are based on the impact a development has on a facility. Fees should be set to cover costs and ensure consistent charges to different developments and over time. The relationship between the fee and usage can be determined to meet these objectives. When several developments occur simultaneously on a congested network or where there are alternative paths between origin and destinations, there are no normative methods for attributing the traffic on a facility to a particular development. This paper describes a consistent approach to setting impact fees based on transportation planning procedures, highway cost allocation methods, and entropy maximization. This approach determines the most likely allocation of link volumes to developments given the origin‐destination matrix and equilibrium flows. The method is demonstrated through its application to a simplified network model of th...

The nation's capacity for maintenance and improvement of infrastructure systems and its ability to maintain and improve infrastructure systems and ensure the continued service of critical infrastructure systems are receiving special attention because recent disasters have had a significant impact on critical infrastructure. These critical infrastructure systems are the foundation of the nation's economic and social systems. Much research and many policy studies have been conducted to develop methods to improve protection of critical infrastructure with a focus on decreased vulnerability. This paper describes the development of a framework for a decision support system. The objective of the decision support system is to reduce the vulnerability of places and infrastructure systems through the use of mitigation strategies that increase system resilience and resistance to the stresses imposed by disasters. The decision support system will also provide an understanding of the many variables involved in developing strategies to improve the resilience of critical infrastructure systems. This decision support system, referred to as the Critical Infrastructure Resilience Decision Support System (CIR-DSS), uses systems dynamics and recognizes the impacts of disasters, including damage and disruption to critical infrastructure. Results include those of risk and cost–benefit analyses of alternative strategies that also recognize U.S. government policies for recovery and mitigation. A case study focused on transportation infrastructure was used to test and validate the CIR-DSS framework.

How and when transportation networks are restored following a natural hazard event plays a key role in post-event recovery. However, determining the optimal repair strategies considering user costs requires intensive computational effort impeding the application in practice. This paper uses a modified network robustness index (MNRI), a measure of resilience, to minimize total costs including the repair cost and the travel cost during the recovery. For each link, the repair program is selected from multiple options using incremental benefit cost analysis. The efficiency and effectiveness of the method is tested for a realistic damaged network in Chur, Switzerland. Three scenarios with different resources in terms of repair budgets and crew availability are investigated. The results demonstrate that the approximations obtained using the proposed method are close to the results using a near optimal heuristic algorithm, and reduce the computational effort and the time needed.

This article discusses the need for a performance measure that compares the efficiencies of subunits within a transportation organization, reflects the diversity of inputs and outputs, and is objective and consistent. The study presents a method for developing such a performance indicator, and illustrates its use with an application to the park-and-ride lots of the Chicago Transit Authority. The proposed method applies Data Envelopment Analysis supplemented by Stochastic Frontier Analysis to estimate efficiency scores for each subunit. The research demonstrates how the scores can provide objective and valid indicators of each subunit’s efficiency, while accounting for key goals and values of internal and external stakeholders. The scores can be practically applied by a transit agency to identify subunit inefficiencies, and, as demonstrated by several brief case studies, this information can be used as the basis for changes that will improve both subunit and system performance.