Estimating the benefits of stream water quality improvements in urbanizing watersheds: An ecological production function approach.

Streams in urbanizing watersheds are threatened by economic development that can lead to excessive sediment erosion and surface runoff. These anthropogenic stressors diminish valuable ecosystem services and result in pervasive degradation commonly referred to as "urban stream syndrome." Understanding how the public perceives and values improvements in stream conditions is necessary to support efforts to quantify the economic benefits of water quality improvements. We develop an ecological production framework that translates measurable indicators of stream water quality into ecological endpoints. Our interdisciplinary approach integrates a predictive hierarchical water quality model that is well suited for sparse data environments, an expert elicitation that translates measurable water quality indicators into ecological endpoints that focus group participants identified as most relevant, and a stated preference survey that elicits the public's willingness to pay for changes in these endpoints. To illustrate our methods, we develop an application to the Upper Neuse River Watershed located in the rapidly developing Triangle region of North Carolina (the United States). Our results suggest, for example, that residents are willing to pay roughly $127 per household and $54 million per year in aggregate (2021 US$) for water quality improvements resulting from a stylized intervention that increases stream bank canopy cover by 25% and decreases runoff from impervious surfaces, leading to improvements in water quality and ecological endpoints for local streams. Although the three components of our analysis are conducted with data from North Carolina, we discuss how our findings are generalizable to urban and urbanizing areas across the larger Piedmont ecoregion of the Eastern United States.

A taxonomic framework for assessing governance challenges and environmental effects of integrated food-energy systems.

Predominant forms of food and energy systems pose multiple challenges to the environment as current configurations tend to be structured around centralized one-way through-put of materials and energy. In addition, these configurations can introduce vulnerability to input material price and supply shocks as well as contribute to localized food insecurity and lost opportunities for less environmentally harmful forms of local economic development. One proposed form of system transformation involves locally integrating "unclosed" material and energy loops from food and energy systems. Such systems, which have been termed integrated food-energy systems (IFES), have existed in diverse niche forms but have not been systematically studied with respect to technological, governance, and environmental differences. As a first step in this process, we have constructed a taxonomy of IFES archetypes by using exploratory data analysis on a collection of IFES cases. We find that IFES may be classified hierarchically first by their primary purpose­food or energy production­and subsequently by degree and direction of vertical supply chain coordination. We then use this taxonomy to delineate potential governance challenges and pose a research agenda aimed at understanding what role IFES may play in food and energy system transformation and ultimately what policies may encourage IFES adoption.

Applying Decision Science to the Prioritization of Healthcare-Associated Infection Initiatives.

OBJECTIVES: Improving patient quality remains a top priority from the perspectives of both patient outcomes and cost of care. The continuing threat to patient safety has resulted in an increasing number of options for patient safety initiatives, making choices more difficult because of competing priorities. This study provides a proof of concept for using low-cost decision science methods for prioritizing initiatives. METHODS: Using multicriteria decision analysis, we developed a decision support model for aiding the prioritization of the four most common types of healthcare-associated infections: surgical site infections, central line-associated bloodstream infections, ventilator-associated events, and catheter-associated urinary tract infections. In semistructured interviews, we elicited structure and parameter values of a candidate model, which was then validated by six participants with different roles across three urban teaching and nonteaching hospitals in the Baltimore, Maryland area. RESULTS: Participants articulated the following structural attributes of concern: patient harm, monetary costs, patient mortality, reputational effects, and patient satisfaction. A quantitative decision-making model with an associated uncertainty report for prioritizing initiatives related to the four most common types of healthcare-associated infections was then created. CONCLUSIONS: A decision support methodology such as our proof of concept could aid hospital executives in prioritizing the quality improvement initiatives within their hospital, with more complete data. Because hospitals continue to struggle in improving quality of care with tighter budgets, a formal decision support mechanism could be used to objectively prioritize patient safety and quality initiatives.

Linking material flow analysis and resource policy via future scenarios of in-use stock: an example for copper.

A key aspect to achieving long-term resource sustainability is the development of methodologies that explore future material cycles and their environmental impact. Using a novel dynamic in-use stock model and scenario analysis, I analyzed the multilevel global copper cycle over the next 100 years. In 1990, the industrialized world had an in-use copper stock about twice as large as the developing world and a per capita in-use stock of about six times as large. By 2100, the developing world will have an in-use copper stock about three times as large as the industrialized world, but the industrialized world will maintain a per capita stock twice that of the developing world. Under a scenario of no material substitution or technological change in copper products, global in-use stock in 2100 will be about as large as currently known copper resources. However, current scrap recycling trends and exploration will alleviate absolute supply pressure but not environmental impacts from decreasing copper are grades. Additionally, unexpected emergent properties of dematerialization are observed from the in-use stock model that arise solely from the properties of stock dynamics, an infrequently discussed cause of dematerialization in the literature.

In-use stocks of metals: status and implications.

The continued increase in the use of metals over the 20th century has led to the phenomenon of a substantial shift in metal stocks from the lithosphere to the anthroposphere. Such a shift raises social, economic, and environmental issues that cannot be addressed without quantifying the amount of stock of "metal capital" utilized by society. Estimation of the in-use stock of metals has occurred for at least 70 years, with over 70% of the publications occurring after the year 2000. Despite the long history, this is the first critical review to consolidate current findings, critique methods, and discuss future avenues of research. Only aluminum, copper, iron, lead, and zinc have been studied to any extent Nonetheless, it is clear that for the more-developed countries, the typical per capita in-use metal stock is between 10 and 15 t (mostly iron). Comparison of the per capita stocks in more-developed countries with those in less-developed countries suggests that if the total world population were to enjoy the same per capita metal stock levels as the more-developed countries, using a similar suite of technologies, the amount of global in-use metal stocks required would be 3-9 times those existing at present.