Bidding against the wind: A choice experiment in green energy, green jobs and offshore views in North Carolina, USA.

Offshore wind development is in its nascent stages in the United States. Recent research indicates that the visual impacts of offshore wind farms are viewed negatively by the general population. This North Carolina application is the first US-focused discrete choice experiment that explicitly asks respondents to consider the positive local and global benefits from offshore wind development, such as job creation and greenhouse gas emission reductions, simultaneously with their visual impacts.

Valuing improvements in the ecological integrity of local and regional waters using the biological condition gradient.

Scientific knowledge related to quantifying the monetized benefits for landscape-wide water quality improvements does not meet current regulatory and benefit-cost analysis needs in the United States. In this study we addressed this knowledge gap by incorporating the Biological Condition Gradient (BCG) as a water quality metric into a stated preference survey capable of estimating the total economic value (use and nonuse) for aquatic ecosystem improvements. The BCG is grounded in ecological principles and generalizable and transferable across space.

Short-term impact of PM on contemporaneous asthma medication use: Behavior and the value of pollution reductions.

Asthma ranks among the most costly of chronic diseases, accounting for over $50 billion annually in direct medical expenditures in the United States. At the same time, evidence has accumulated that fine particulate matter pollution can exacerbate asthma symptoms and generate substantial economic costs. To measure these costs, we use a unique nationwide panel dataset tracking asthmatic individuals' use of rescue medication and their exposure to PM (particulate matter with an aerodynamic diameter of <2.

Estimating the effects of urban residential development on water quality using microdata.

In this study, we examine the impact on water quality of urbanization using disaggregate data from Wake County, North Carolina. We use a unique panel data set tracing the conversion of individual residentially zoned land parcels to relate the density of residential development and the change in residential land use to three measures of water quality. Using a spatial econometrics model, we relate spatially and temporally referenced monitoring station readings to our measures of residential land use while controlling for other factors affecting water quality.