Compensation for risks: host community benefits in siting locally unwanted facilities

This article analyzes the recent negotiations connected with siting 24 solid-waste landfills in Wisconsin. We examine the association between the type and amount of compensation paid to host communities by facility developers and the size of facilities, certain facility characteristics, the timing of negotiated agreements, the size of the host community, and the socioeconomic status of the host area. Our findings suggest that the level of compensation after adjusting for landfill capacity is positively associated with the percentage of total facility capacity dedicated to host community use, positively associated with the percentage of people of the host area who are in poverty, and larger for public facilities that accept municipal wastes. Other explanatory variables we examined, whose association with levels of compensation proved statistically insignificant, were facility size, facility status (new vs expansion), facility use (countyonly vs multicounty), timing of negotiation, host community size, and the host area education level, population density, and per capita income. We discuss the policy implications of our principal findings and future research questions in light of the persistent opposition surrounding the siting of solid-waste and other waste-management facilities.     

Implications of indicator aggregation methods for global change vulnerability reduction efforts

Composite indices are used to assess and prioritize mitigation and adaptation strategies for addressing the impacts of global environmental change. We evaluate different aggregation tools for creating these indices and their potential effects on mitigation and adaptation efforts. We assess the association of each aggregation tool with different types of trade-offs, risk strategies, and the resulting spatial and statistical distribution of their composite scores. Four aggregation tools are investigated (Weighted Linear Combination, WLC; Ordered Weighted Average, OWA; Data Envelopment Analysis, DEA; Compromise Programming, CP) using an example of vulnerability to flooding in the eastern United States. The choice of aggregation tool affects vulnerability outcomes, decision risk strategies, and the prioritization of vulnerability reduction strategies. DEA produces the highest vulnerability scores, representing a risk averse strategy associated with pessimistic outcomes. WLC implies a neutral and fixed risk strategy. CP produces a range of outcomes from neutral (equivalent to the WLC) to pessimistic, depending on its parameters. OWA offers the highest flexibility to adjust the levels of trade-off and risk strategy, producing a range of vulnerability outcomes, from optimistic to pessimistic. The units of analysis, when prioritized across the different aggregation tools, are more consistent for the top ranked units. However, the differences in rank become substantial as the selection threshold score decreases. To obtain better informed vulnerability reduction strategies, we recommend to (i) address how trade-off and decision risk are embedded in the aggregation tool chosen, and (ii) evaluate their effect in the prioritization of mitigation and adaptation strategies being considered.     

Assessing the Vulnerability of Coastal Communities to Extreme Storms: The Case of Revere,MA., USA

Climate change may affect the frequency, intensity, and geographic distribution of severe coastal storms. Concurrent sea-level rise would raise the baseline of flooding during such events. Meanwhile, social vulnerability factors such as poverty and disability hinder the ability to cope with storms and storm damage. While physical changes are likely to remain scientifically uncertain into the foreseeable future, the ability to mitigate potential impacts from coastal flooding may be fostered by better understanding the interplay of social and physical factors that produce human vulnerability. This study does so by integrating the classic causal model of hazards with social, environmental, and spatial dynamics that lead to the differential ability of people to cope with hazards. It uses Census data, factor analysis, data envelopment analysis, and floodplain maps to understand the compound social and physical vulnerability of coastal residents in the city of Revere, MA, USA. This revised version was published online in August 2006 with corrections to the Cover Date.     

A multi-criteria geographic information systems approach for the measurement of vulnerability to climate change

A flexible procedure for the development of a multi-criteria composite index to measure relative vulnerability under future climate change scenarios is presented. The composite index is developed using the Weighted Ordered Weighted Average (WOWA) aggregation technique which enables the selection of different levels of trade-off, which controls the degree to which indicators are able to average out others. We explore this approach in an illustrative case study of the United States (US), using future projections of widely available indicators quantifying flood vulnerability under two scenarios of climate change. The results are mapped for two future time intervals for each climate scenario, highlighting areas that may exhibit higher future vulnerability to flooding events. Based on a Monte Carlo robustness analysis, we find that the WOWA aggregation technique can provide a more flexible and potentially robust option for the construction of vulnerability indices than traditionally used approaches such as Weighted Linear Combinations (WLC). This information was used to develop a proof-of-concept vulnerability assessment to climate change impacts for the US Army Corps of Engineers. Lessons learned in this study informed the climate change screening analysis currently under way.