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. Moreover, as the BCG translates available data on biological condition into a score on a 6-point scale, it provides a simple metric that can be readily communicated to the public. We applied our BCG-based survey instrument to households across the Upper Mississippi, Ohio, and Tennessee river basins and report values for a range of potential improvements that vary by location, spatial scale, and the scope of the water quality change. We found that people are willing to pay twice as much for an improvement policy that targets their home watershed (defined as a four-digit hydrologic unit) versus a more distant one. We also found that extending the spatial scale of a local policy beyond the home watershed does not generate additional benefits to the household. Finally, our results suggest that nonuse sources of value (e.g., bequest value, intrinsic aesthetic value) are an important component of overall benefits.

Improving Private Well Testing Programs: Experimental Evidence from Iowa.

Approximately 23 million U.S. households rely on private wells for drinking water. This study first summarizes drinking water behaviors and perceptions from a large-scale survey of households that rely on private wells in Iowa. Few households test as frequently as recommended by public health experts. Around 40% of households do not regularly test, treat, or avoid their drinking water, suggesting pollution exposure may be widespread among this population. Next, we utilize a randomized control trial to study how nitrate test strips and information about a free, comprehensive water quality testing program influence households' behaviors and perceptions. The intervention significantly increased testing, including high-quality follow-up testing, but had limited statistically detectable impacts on other behaviors and perceptions. Households' willingness to pay for nitrate test kits and testing information exceeds program costs, suggesting that the intervention was welfare-enhancing.

The low but uncertain measured benefits of US water quality policy.

US investment to decrease pollution in rivers, lakes, and other surface waters has exceeded $1.9 trillion since 1960, and has also exceeded the cost of most other US environmental initiatives. These investments come both from the 1972 Clean Water Act and the largely voluntary efforts to control pollution from agriculture and urban runoff. This paper reviews the methods and conclusions of about 20 recent evaluations of these policies. Surprisingly, most analyses estimate that these policies' benefits are much smaller than their costs; the benefit-cost ratio from the median study is 0.37. However, existing evidence is limited and undercounts many types of benefits. We conclude that it is unclear whether many of these regulations truly fail a benefit-cost test or whether existing evidence understates their net benefits; we also describe specific questions that when answered would help eliminate this uncertainty.

Machine learning predicts which rivers, streams, and wetlands the Clean Water Act regulates.

We assess which waters the Clean Water Act protects and how Supreme Court and White House rules change this regulation. We train a deep learning model using aerial imagery and geophysical data to predict 150,000 jurisdictional determinations from the Army Corps of Engineers, each deciding regulation for one water resource. Under a 2006 Supreme Court ruling, the Clean Water Act protects two-thirds of US streams and more than half of wetlands; under a 2020 White House rule, it protects less than half of streams and a fourth of wetlands, implying deregulation of 690,000 stream miles, 35 million wetland acres, and 30% of waters around drinking-water sources. Our framework can support permitting, policy design, and use of machine learning in regulatory implementation problems.

Direct electromagnetic coupling for non-invasive measurements of stability in simulated fracture healing.

Diagnostic monitoring and prediction of bone fracture healing is critical for the detection of delayed union or non-union and provides the requisite information as to whether therapeutic intervention or timely revision are warranted. A promising approach to monitor fracture healing is to measure the mechanical load-sharing between the healing callus and the implanted hardware used for internal fixation. The objectives of this study were to evaluate a non-invasive measurement system in which an antenna electromagnetically couples with the implanted hardware to sense deflections of the hardware due to an applied load and to investigate the efficacy of the system to detect changes in mechanical load-sharing in an ex vivo fracture healing model. The measurement system was applied to ovine metatarsal bones treated with osteotomies, resulting in four different levels of bone stability which simulated various degrees of fracture healing. Computational finite element simulations supplemented these ex vivo experiments to compare the osteotomy model of fracture healing to a more clinically applicable callus stiffening model of healing. In the ex vivo experiments, the electromagnetic coupling system detected significant differences between the four simulated degrees of healing with good repeatability. Computational simulations indicated that the experimental model of fracture healing provided a good surrogate for studying healing during the early time period as the callus stiffness is increasing as well as when diagnostic monitoring of the healing process is most critical. Based upon the data reported herein, the direct electromagnetic coupling method holds strong potential for clinical assessments and predictions of fracture healing. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res.

Air pollution and visitation at U.S. national parks.

Hundreds of millions of visitors travel to U.S. national parks every year to visit America's iconic landscapes. Concerns about air quality in these areas have led to strict, yet controversial pollution control policies. We document pollution trends in U.S. national parks and estimate the relationship between pollution and park visitation. From 1990 to 2014, average ozone concentrations in national parks were statistically indistinguishable from the 20 largest U.S. metropolitan areas. Further, relative to U.S. cities, national parks have seen only modest reductions in days with ozone concentrations exceeding levels deemed unhealthy by the U.S. Environmental Protection Agency. We find a robust, negative relationship between in-park ozone concentrations and park visitation. Still, 35% of all national park visits occur when ozone levels are elevated.