Empirical models based on the universal soil loss equation fail to predict sediment discharges from Chesapeake Bay catchments

The Universal Soil Loss Equation (USLE) and its derivatives are widely used for identifying watersheds with a high potential for degrading stream water quality. We compared sediment yields estimated from regional application of the USLE, the automated revised RUSLE2, and five sediment delivery ratio algorithms to measured annual average sediment delivery in 78 catchments of the Chesapeake Bay watershed. We did the same comparisons for another 23 catchments monitored by the USGS. Predictions exceeded observed sediment yields by more than 100% and were highly correlated with USLE erosion predictions (Pearson r range, 0.73-0.92; p < 0.001). RUSLE2-erosion estimates were highly correlated with USLE estimates (r = 0.87; p < 001), so the method of implementing the USLE model did not change the results. In ranked comparisons between observed and predicted sediment yields, the models failed to identify catchments with higher yields (r range, -0.28-0.00; p > 0.14). In a multiple regression analysis, soil erodibility, log (stream flow), basin shape (topographic relief ratio), the square-root transformed proportion of forest, and occurrence in the Appalachian Plateau province explained 55% of the observed variance in measured suspended sediment loads, but the model performed poorly (r(2) = 0.06) at predicting loads in the 23 USGS watersheds not used in fitting the model. The use of USLE or multiple regression models to predict sediment yields is not advisable despite their present widespread application. Integrated watershed models based on the USLE may also be unsuitable for making management decisions.     

A risk-based screening approach for prioritizing contaminants and exposure pathways at Superfund sites

Contamination at Superfund sites can involve mixtures of chemicals and radionuclides in a variety of environmental media. Determining priorities for evaluation and remediation of various contaminants is an important part of the initial phases of any site investigation. An effective screening analysis at the beginning of the project can help by identifying both those situations in need of immediate remedial attention and those which require further sampling and evaluation. The screening approach discussed here is made up of two sets of calculations designed to provide upper- and lower-bound estimates of health risk to individuals likely to receive the highest exposures. This approach allows rapid identification of contaminants which pose a negligible risk and can be assigned a low priority for remedial attention or which pose a substantial risk and should be given the highest priority for appropriate remediation efforts. Contaminants designated as neither high- nor low-priority should be investigated in more detail prior to making decisions regarding the need for or method of remediation. The utility of this approach has already been demonstrated in the evaluation of contamination in the Clinch and Tennessee River systems originating from historical operations of atomic weapons and energy research facilities near Oak Ridge, Tennessee.     

The Role of Abatement Costs in GHG Permit Allocations: A Global Stabilization Scenario Analysis

Our objective is to propose permit allocation schemes that lead to a fair distribution of the net abatement cost among regions in a global greenhouse gas (GHG) stabilization scenario. We use a detailed technology-based energy model, World-MARKAL, to determine efficient abatement decisions, and to calculate the regional gross abatement costs (before permit allocation and trading). The net abatement costs are then calculated and used for different permit allocation schemes.     

Modeling effects of traffic and landscape characteristics on ambient nitrogen dioxide levels in Connecticut

An integrated exposure model was developed that estimates nitrogen dioxide (NO(2)) concentration at residences using geographic information systems (GIS) and variables derived within residential buffers representing traffic volume and landscape characteristics including land use, population density and elevation. Multiple measurements of NO(2) taken outside of 985 residences in Connecticut were used to develop the model. A second set of 120 outdoor NO(2) measurements as well as cross-validation were used to validate the model. The model suggests that approximately 67% of the variation in NO(2) levels can be explained by: traffic and land use primarily within 2 km of a residence; population density; elevation; and time of year. Potential benefits of this model for health effects research include improved spatial estimations of traffic-related pollutant exposure and reduced need for extensive pollutant measurements. The model, which could be calibrated and applied in areas other than Connecticut, has importance as a tool for exposure estimation in epidemiological studies of traffic-related air pollution.     

Characterizing the child passenger safety workforce in Michigan: A statewide survey in 2015

Objective: In this study, we assessed the number of child passenger safety technicians (CPSTs) in Michigan over 4 years and characterized the CPST workforce in 2015 to identify factors associated with high productivity and longevity in the field.

Methods: We determined the number of CPSTs and those newly certified using lists from the Michigan Office of Highway Safety Planning (OHSP) from 2012 to 2015. We conducted a statewide survey of Michigan CPSTs in October 2015. Analyses were conducted in 2016. The survey assessed demographic characteristics, reasons to enter the field and maintain certification, and motivations to conduct seat checks. We used CPST-reported time devoted to seat checks and average number of seats checked per month to create a composite “activity level” variable. We examined activity levels across several characteristics.

Results: The number of CPSTs ranged from 941 to 980 over the study period, with approximately 200 new certifications annually. In 2015, surveys were started by 496 of 962 eligible CPSTs and 427 submitted complete responses. CPST-instructors had a higher response rate than CPSTs in general (89 vs. 49%, P < .0001). The majority of respondents were women (71%) and self-identified as white (88%). More than one third were 35–44 years old. Just 7% were comfortable checking seats using a language other than English. “Personal reasons” were most often cited motivation for becoming a CPST and maintaining certification. Natural fit/job enhancement were more common reasons to maintain certification than become a CPST. Time and distance had the greatest influence on seat check participation. Perceived need, appointments vs. drop-in, and employer factors were very influential for 10–15% of CPSTs. Few CPSTs considered free food and payments/giveaways very influential. About 40% of respondents were considered high-activity (>24 seats checked/year), one third medium-activity (5 to 24 seats checked/year), and one quarter low-activity (<5 seats checked/year). High-activity CPSTs most commonly reported both being paid and volunteering their time to check seats, worked with a Safe Kids coalition, worked in law enforcement or social services, and had recertified at least once. Motivation to participate in seat checks did not vary with activity level.

Conclusions: Understanding the demographic characteristics and motivations of CPSTs can help Michigan OHSP recruit and retain a workforce dedicated to increasing the safety of child passengers. Agencies hosting seat checks can use these results to align the strategies they employ to incentivize CPSTs to serve in their communities with the factors that have the greatest influence on CPST participation.     

The concept of degraded images applied to hazard recognition training in mining for reduction of lost-time injuries

Introduction: This paper discusses the application of a training intervention that uses degraded images for improving the hazard recognition skills of miners. Method: NIOSH researchers, in an extensive literature review, identified fundamental psychological principles on perception that may be employed to enhance the ability of miners to recognize and respond to hazards in their dangerous work environment. Three studies were conducted to evaluate the effectiveness of the degraded image training intervention. A model of hazard recognition was developed to guide the study. Results: In the first study, miners from Pennsylvania, West Virginia and Alabama, who were taught with the aid of degraded images, scored significantly better on follow-up hazard recognition performance measures than those trained using traditional instructional methodologies. The second and third studies investigated the effectiveness of the training intervention at two mining companies. Data collected over a 3-year period showed that lost-time injuries at mines in Alabama and Illinois declined soon after the training intervention was instituted. Impact on Industry: Further exploration of the hazard recognition model and the development of other interventions based on the model could support the validity of the steps in the hazard recognition model.     

The affective foundations of high‐reliability organizing

The factors that compel individuals to exert the extraordinary effort needed to create high reliability—consistent error‐free performance under trying conditions—remain unspecified. Here, we propose that when individuals experience emotional ambivalence and prosocial motivation, it induces the broad thinking and other‐orientation that undergird mindful organizing and high reliability. Copyright © 2014 John Wiley & Sons, Ltd.