Automobile injury trends in the contemporary fleet: Belted occupants in frontal collisions

Objective: As vehicle safety technologies and evaluation procedures advance, it is pertinent to periodically evaluate injury trends to identify continuing and emerging priorities for intervention. This study examined detailed injury distributions and injury risk trends in belted occupants in frontal automobile collisions (10 o’clock to 2 o’clock) using NASS-CDS (1998–2015).

Methods: Injury distributions were examined by occupant age and vehicle model year (stratified at pre- and post-2009). Logistic regression models were developed to examine the effects of various factors on injury risk (by body region), controlling for delta-V, sex, age, height, body mass index (BMI), vehicle model year (again stratified at 2009).

Results: Among other observations, these analyses indicate that newer model year vehicles (model year [MY] 2009 and later) carry less risk of Abbreviated Injury Scale (AIS) 2+ and AIS 3+ injury compared to older model year vehicles, with odds ratios of 0.69 (AIS 2+) and 0.45 (AIS 3+). The largest reductions in risk between newer model year vehicles and older model year vehicles occur in the lower extremities and in the risk of skull fracture. There is no statistically significant change in risk of AIS 3+ rib fracture or sternum injury between model year categories. Females are at greater risk of AIS 2+ and AIS 3+ injury compared to males, with increased risk across most injury types.

Conclusions: For belted occupants in frontal collisions, substantial reductions in injury risk have been realized in many body regions in recent years. Risk reduction in the thorax has lagged other body regions, resulting in increasing prevalence among skeletal injuries in newer model year vehicles (especially in the elderly). Injuries also remain common in the arm and hand/wrist for all age ranges studied. These results provide insight into where advances in the field have made gains in occupant protection and what injury types remain to be addressed.     

Using spatially explicit,time-dependent analysis to understand how social factors influence conservation outcomes

Conservation across human-dominated landscapes requires an understanding of the social and ecological factors driving outcomes. Studies that link conservation outcomes to social and ecological factors have examined temporally static patterns. However, there may be different social and ecological processes driving increases and decreases in conservation outcomes that can only be revealed through temporal analyses. Through a case study of the invasion of Falcataria moluccana in Hawaii, we examined the association of social factors with increases and decreases in invader distributions over time and space. Over 7 years, rates of invader decrease varied substantially (66–100%) relative to social factors, such as building value, whether land was privately or publically owned, and primary residence by a homeowner, whereas rates of increase varied only slightly (<0.1–3.6%) relative to such factors. These findings suggest that links between social factors and invasion in the study system may be driven more by landowners controlling existing invasive species, rather than by landowners preventing the spread of invasive species. We suggest that spatially explicit, time-dependent analyses provide a more nuanced understanding of the way social factors influence conservation outcomes. Such an understanding can help managers develop outreach programs and policies targeted at different types of landowners in human-dominated landscapes.     

Dissecting the spatial scales of mercury accumulation in Ontario lake sediment

Total mercury concentration was analyzed in 171 lakes from pre-industrial (>30 cm depth; Hg_{pre-industrial}) and present-day sediments (0.5–1 cm; Hg_present-day). Numerous hot or cold spots of sediment mercury enrichment (Hg EF; Hg_{pre-industrial}/Hg_present-day) were evident as determined by local tests of autocorrelation, although in most cases, the maximum correlation among sites was not the nearest neighbor, indicating a strong influence of watershed characteristics. Hg EF was correlated with the area of open water (ha) (r = 0.91, p = 0.035), mine tailings (r = 0.94, p = 0.019), and organic deposits in surficial geology of the watershed (r = −0.91, p = 0.034). Through use of local rather than global regression coefficients, R² increased from 0.20 (p = 0.005) to 0.60 (p = 0.013). A broad spatial pattern (>500 km) observed only in Hg_{pre-industrial} was best explained by mean annual precipitation (shared variance = 3.5%), while finer spatial patterns only observed in Hg_present-day and Hg EF were best explained by pH (average shared variance = 10.8%).     

Recommendations on statistics and benchmarks to assess photochemical model performance

Photochemical grid models are addressing an increasing variety of air quality related issues, yet procedures and metrics used to evaluate their performance remain inconsistent. This impacts the ability to place results in quantitative context relative to other models and applications, and to inform the user and affected community of model uncertainties and weaknesses. More consistent evaluations can serve to drive improvements in the modeling process as major weaknesses are identified and addressed. The large number of North American photochemical modeling studies published in the peer-reviewed literature over the past decade affords a rich data set from which to update previously established quantitative performance “benchmarks” for ozone and particulate matter (PM) concentrations. Here we exploit this information to develop new ozone and PM benchmarks (goals and criteria) for three well-established statistical metrics over spatial scales ranging from urban to regional and over temporal scales ranging from episodic to seasonal. We also recommend additional evaluation procedures, statistical metrics, and graphical methods for good practice. While we primarily address modeling and regulatory settings in the United States, these recommendations are relevant to any such applications of state-of-the-science photochemical models. Our primary objective is to promote quantitatively consistent evaluations across different applications, scales, models, model inputs, and configurations. The purpose of benchmarks is to understand how good or poor the results are relative to historical model applications of similar nature and to guide model performance improvements prior to using results for policy assessments. To that end, it also remains critical to evaluate all aspects of the model via diagnostic and dynamic methods. A second objective is to establish a means to assess model performance changes in the future. Statistical metrics and benchmarks need to be revisited periodically as model performance and the characteristics of air quality change in the future.

Implications: We address inconsistent procedures and metrics used to evaluate photochemical model performance, recommend a specific set of statistical metrics, and develop updated quantitative performance benchmarks for those metrics. We promote quantitatively consistent evaluations across different applications, scales, models, inputs, and configurations, thereby (1) improving the user’s ability to quantitatively place results in context and guide model improvements, and (2) better informing users, regulators, and stakeholders of model uncertainties and weaknesses prior to using results for policy assessments. While we primarily address U.S. modeling and regulatory settings, these recommendations are relevant to any such applications of state-of-the-science photochemical models.     

Contextualising risk within enterprise risk management through the application of systems thinking

New and emerging risks create growing uncertainty and unpredictability within enterprise risk management. While ISO 31000:2009 is a progressive risk management framework, it is limited in its guidance on how to contextualise complex risks. The application of systems thinking to risk management provides the opportunity to better understand complexity by viewing risk and the consequence of change as part of overall system behaviour. System modelling tools enable organisations to better contextualise their risk landscape. These tools assist organisations to identify vulnerabilities between social and ecological variables in the system within they exist. Determining drivers of change leading to system vulnerabilities can assist in understanding threshold limits of the system, thus enabling the organisation to build system resilience and organisational sustainability.     

Trends in on-road vehicle emissions and ambient air quality in Atlanta,Georgia, USA,from the late 1990s through 2009

On-road vehicle emissions of carbon monoxide (CO), nitrogen oxides (NO_x), and volatile organic compounds (VOCs) during 1995–2009 in the Atlanta Metropolitan Statistical Area were estimated using the Motor Vehicle Emission Simulator (MOVES) model and data from the National Emissions Inventories and the State of Georgia. Statistically significant downward trends (computed using the nonparametric Theil-Sen method) in annual on-road CO, NO_x, and VOC emissions of 6.1%, 3.3%, and 6.0% per year, respectively, are noted during the 1995–2009 period despite an increase in total vehicle distance traveled. The CO and NO_x emission trends are correlated with statistically significant downward trends in ambient air concentrations of CO and NO_x in Atlanta ranging from 8.0% to 11.8% per year and from 5.8% to 8.7% per year, respectively, during similar time periods. Weather-adjusted summertime ozone concentrations in Atlanta exhibited a statistically significant declining trend of 2.3% per year during 2001–2009. Although this trend coexists with the declining trends in on-road NO_x, VOC, and CO emissions, identifying the cause of the downward trend in ozone is complicated by reductions in multiple precursors from different source sectors.

Implications:Large reductions in on-road vehicle emissions of CO and NO_x in Atlanta from the late 1990s to 2009, despite an increase in total vehicle distance traveled, contributed to a significant improvement in air quality through decreases in ambient air concentrations of CO and NO_x during this time period. Emissions reductions in motor vehicles and other source sectors resulted in these improvements and the observed declining trend in ozone concentrations over the past decade. Although these historical trends cannot be extrapolated to the future because pollutant concentration contributions due to on-road vehicle emissions will likely become an increasingly smaller fraction of the atmospheric total, they provide an indication of the benefits of past control measures.     

Implementation and application of sub-grid-scale plume treatment in the latest version of EPA’s third-generation air quality model,CMAQ 5.01

The Community Multiscale Air Quality (CMAQ) modeling system Version 5.0 (CMAQv5.0) was released by the U.S. Environmental Protection Agency (EPA) in February 2012, with an interim release (v5.01) in July 2012. Because CMAQ is a community model, the EPA encourages the development of proven alternative science treatments by external scientists and developers that can be incorporated as part of an official CMAQ release. This paper describes the implementation, evaluation, and testing of a plume-in-grid (PinG) module in CMAQ 5.01. The PinG module, also referred to as Advanced Plume Treatment (APT), provides the capability of resolving sub-grid-scale processes, such as the transport and chemistry of point-source plumes, in a grid model. The new PinG module in CMAQ 5.01 is applied and evaluated for two 15-day summer and winter periods in 2005 to the eastern United States, and the results are compared with those from the base CMAQ 5.01. Eighteen large point sources of NOx in the eastern United States were selected for explicit plume treatment with APT in the PinG simulation. The results show that overall model performance is negligibly affected when PinG treatment is included. However, the PinG model predicts significantly different contributions of the 18 sources to pollutant concentrations and deposition downwind of the point sources compared to the base model.

Implications: This study describes the incorporation of a plume-in-grid (PinG) capability within the latest version of the EPA grid model, CMAQ. The capability addresses the inherent limitation of the grid model to resolve processes, such as the evolution of point-source plumes, which occur at scales much smaller than the grid resolution. The base grid model and the PinG version predict different source contributions to ozone and PM_2.5 concentrations that need to be considered when source attribution studies are conducted to determine the impacts of large point sources on downwind concentrations and deposition of primary and secondary pollutants.     

Developing an automated risk management tool to minimize bird and bat mortality at wind facilities

A scarcity of baseline data is a significant barrier to understanding and mitigating potential impacts of offshore development on birds and bats. Difficult and sometimes unpredictable conditions coupled with high expense make gathering such data a challenge. The Acoustic and Thermographic Offshore Monitoring (ATOM) system combines thermal imaging with acoustic and ultrasound sensors to continuously monitor bird and bat abundance, flight height, direction, and speed. ATOM’s development and potential capabilities are discussed, and illustrated using onshore and offshore test data obtained over 16 months in the eastern USA. Offshore deployment demonstrated birds tending to fly into winds and activity declining sharply in winds >10 km h^?1. Passerines showed distinct seasonal changes in flight bearing and flew higher than non-passerines. ATOM data could be used to automatically shut down wind turbines to minimize collision mortality while simultaneously providing information for modeling activity in relation to weather and season.     

Biological monitoring of chlorpyrifos exposure to rice farmers in Vietnam

Chlorpyrifos is the most common organophosphate insecticide registered for use in Vietnam and is widely used in agriculture, particularly rice farming. However, chlorpyrifos exposure to and adverse effects on farmers has not been evaluated. In this study, biological monitoring of chlorpyrifos exposure in a group of rice farmers was conducted after a typical application event using back-pack spraying.Urine samples (24 h) were collected from the rice farmers before and post insecticide application. Samples were analysed for 3,5,6-trichloropyridinol (TCP), the major urinary metabolite of chlorpyrifos, using an enzymatic pre-treatment before extraction followed by HPLC-MS/MS. Absorbed Daily Dose (ADD) of chlorpyrifos for farmers were then estimated from urinary TCP levels, expressed as μg g⁻¹ creatinine. The analytical method for urinary TCP had a low detection limit (0.6 μg L⁻¹), acceptable recovery values (80-114%), and low relative percentage differences in duplicate and repeated samples.Post-application chlorpyrifos ADD of farmers varied from 0.4 to 94.2 μg kg⁻¹ (body weight) d⁻¹ with a mean of 19.4 μg kg⁻¹ d⁻¹ which was approximately 80-fold higher than the mean baseline exposure level (0.24 μg kg⁻¹ d⁻¹). Hazard Quotients (ratio of the mean ADD for rice farmers to acute oral reference dose) calculated using acute oral reference doses recommended by United States and Australian agencies varied from 2.1 (Australian NRA), 4.2 (US EPA) to 6.9 (ATSDR).Biological monitoring using HPLC-MS/MS analysis of urinary TCP (24 h) was found to be an effective method for measuring chlorpyrifos exposure among farmers. This case study found that Vietnamese rice farmers had relatively high exposures to chlorpyrifos after application, which were likely to have adverse health effects.