Patterns of drinking four weeks prior to an alcohol-related vehicular crash

OBJECTIVE: The primary objective of the study was to determine if drinking patterns on the days immediately prior to an alcohol-related motor vehicle crash (ARMVC) were significantly different than drinking patterns in the weeks prior to the crash. METHODS: Following ARMVC, 187 hospitalized non-alcohol dependent young-adults (43 females, 144 males) were enrolled. Mean age was 29.03 years, mean blood alcohol level was 165.18 mg/dL, and mean injury severity score was 10.50. When alcohol-free, subjects were interviewed by nurse clinicians to determine the quantity/frequency of alcohol consumption during the 28 days prior to the crash. Subjects reported the number of standard drinks using the Timeline Followback procedure. Total drinks/day were determined, with day 1 considered 4 weeks prior to the crash and day 28 the day of the crash. A random-intercepts general linear mixed model (GLMM) was used to test the effect of several covariates (segment 1 [days 1-26], segment 2 [days 27-28], age, sex, race, holiday/non-holiday period, driver/passenger status, and weekend/weekday crash) on the amount of standard drinks/day. RESULTS: There was no significant interaction among the covariates. The only significant predictors of drinks/day were segment 2 (b = .322, p < .0001) and gender (b = -.221, p = .016). The positive, statistically significant slope for segment 2 indicated an increase in consumption of drinks/day in the two-day period prior to the ARMVC and the negative slope for gender indicated greater consumption of drinks/day for men than women. CONCLUSION: Persons injured in an ARMVC had a significant increase in alcohol consumption on the day before and the day of vehicular crashes (days 27 and 28) as compared to the first 26 days in the 28-day period preceding the crash. When non-alcohol-dependent subjects are counseled to reduce their risk of traffic crashes, they should be alerted that when their patterns of drinking change, they are at higher risk than usual for a crash.     

Global and regional potential for bioenergy from agricultural and forestry residue biomass

As co-products, agricultural and forestry residues represent a potential low cost, low carbon, source for bioenergy. A method is developed for estimating the maximum sustainable amount of energy potentially available from agricultural and forestry residues by converting crop production statistics into associated residue, while allocating some of this resource to remain on the field to mitigate erosion and maintain soil nutrients. Currently, we estimate that the world produces residue biomass that could be sustainably harvested and converted into nearly 50 EJ yr⁻¹ of energy. The top three countries where this resource is estimated to be most abundant are currently net energy importers: China, the United States (US), and India. The global potential from residue biomass is estimated to increase to approximately 50–100 EJ yr⁻¹ by mid- to late- century, depending on physical assumptions such as of future crop yields and the amount of residue sustainably harvestable. The future market for biomass residues was simulated using the Object-Oriented Energy, Climate, and Technology Systems Mini Climate Assessment Model (O^bjECTS MiniCAM). Utilization of residue biomass as an energy source is projected for the next century under different climate policy scenarios. Total global use of residue biomass is estimated to be 20–100 EJ yr⁻¹ by mid- to late- century, depending on the presence of a climate policy and the economics of harvesting, aggregating, and transporting residue. Much of this potential is in developing regions of the world, including China, Latin America, Southeast Asia, and India.     

Defining the Diurnal Pattern of Snowmelt Using a Beta Distribution Function

Snow is an important component of the hydrologic cycle for many regions worldwide. In addition to vital water resources, snowmelt can be important for forest ecosystem dynamics and flood risk. However, standard design events in the United States lack a design snowmelt event, including only precipitation events, though snowmelt has been shown to be larger than rainfall. In this article, we present a method using hourly snow water equivalent data to develop and test a function for representing the diurnal pattern of snowmelt. A two‐parameter beta distribution function is modified for the purposes of this study and found to fit the pattern of snowmelt well with a root mean squared error of 0.008. Soil moisture sensors were additionally utilized to assess the timing of the snowmelt water outflow from the base of the snowpack that supports the shape of the function, but suggests that the timing of losses recorded on snow pillows lag as much as 3 h. Further testing of the function showed the shape of the function to be accurate. The methods developed and tested in this paper can be applied for design purposes comparing snowmelt and rainfall events or to improve hydrological models investigating processes such as streamflow or groundwater recharge.     

Method for Rapidly Assessing the Overtopping Risk of Bridges Due to Flooding over a Large Geographic Region

Hydraulic events are a leading cause of bridge failures. While these hydraulic events are accounted for in bridge design, changing environmental and land use conditions require continual updating of this risk. For example, after a bridge has been constructed, streamflow can change in unanticipated ways as a result of land use changes, geomorphic changes, and climate change. The objective of this research was to create a screening method able to quickly and inexpensively estimate overtopping risk across a collection of bridges based on the current streamflow conditions. The method uses a geographic information system, nationally available and standardized datasets, and recent regression equations to quantify bridge vulnerability to overtopping for flooding with varying return periods. This screening method could also be used to assist decision makers in updating the Waterway Adequacy field in the National Bridge Inventory, which indicates the overtopping risk of bridges. The method was applied to a portion of the Hampton Roads region of Virginia, United States that includes 475 bridges. The results of the analysis, when combined with transportation data for bridges, aid decision makers to assign further resources to complete more detailed analyses of bridges identified as being at risk for overtopping.     

Bovine Tuberculosis and Badger Culling in England: An Animal Rights-Based Analysis of Policy Options

Bovine tuberculosis (bovine TB) is an important and controversial animal health policy issue in England, which impacts humans, cattle and badgers. The government policy of badger culling has led to widespread opposition, in part due to the conclusions of a large field trial recommending against culling, and in part because badgers are a cherished wildlife species. Animal rights (AR) theorists argue that sentient nonhumans should be accorded fundamental rights against killing and suffering. In bovine TB policy, however, pro-culling actors claim that badgers must be culled to avoid the slaughter of cattle. The first part of the paper compares AR theories of Regan, Francione, Cochrane, Garner and Donaldson and Kymlicka in the context of wildlife species. The second part of the paper applies these AR theories to bovine TB and badger control. AR theories are applied to badger control policy options of (1) do nothing, (2) badger culling, and (3) badger vaccination. We conclude that AR theories are strongly opposed to badger culling. In general, culling is prohibited due to a badger’s right to life and its rights against suffering. The AR theories support a do-nothing, i.e. non-culling, non-vaccination approach to badger control. In the case of the AR theories of Regan and Francione, this is based on abolitionist positions with respect to farming. For Cochrane, Garner, and Donaldson and Kymlicka, the do-nothing policy option is preferred because badger vaccination causes a degree of suffering which generally is not for the individual’s benefit.     

Review of Pesticide Retention Processes Occurring in Buffer Strips Receiving Agricultural Runoff1

Arora, Kapil, Steven K. Mickelson, Matthew J. Helmers, and James L. Baker, 2010. Review of Pesticide Retention Processes Occurring in Buffer Strips Receiving Agricultural Runoff. Journal of the American Water Resources Association (JAWRA) 46(3):618-647. DOI: 10.1111/j.1752-1688.2010.00438.x Abstract: Review of the published results shows that the retention of the two pesticide carrier phases (runoff volume and sediment mass) influences pesticide mass transport through buffer strips. Data averaged across different studies showed that the buffer strips retained 45% of runoff volume (ranging between 0 and 100%) and 76% of sediment mass (ranging between 2 and 100%). Sorption (soil sorption coefficient, K_oc) is one key pesticide property affecting its transport with the two carrier phases through buffer strips. Data from different studies for pesticide mass retention for weakly (K_oc < 100), moderately (100 < K_oc < 1,000), and strongly sorbed pesticides (K_oc > 1,000) averaged (with ranges) 61 (0-100), 63 (0-100), and 76 (53-100) %, respectively. Because there are more data for runoff volume and sediment mass retention, the average retentions of both carrier phases were used to calculate that the buffer strips would retain 45% of weakly to moderately sorbed and 70% of strongly sorbed pesticides on an average basis. As pesticide mass retention presented is only an average across several studies with different experimental setups, the application of these results to actual field conditions should be carefully examined.     

Relative Importance of School Bus-Related Microenvironments to Children’s Pollutant Exposure

Abstract

Real‐time concentrations of black carbon, particle‐bound polycyclic aromatic hydrocarbons, nitrogen dioxide, and fine particulate counts, as well as integrated and real‐time fine particulate matter (PM_2.5) mass concentrations were measured inside school buses during long commutes on Los Angeles Unified School District bus routes, at bus stops along the routes, at the bus loading/unloading zone in front of the selected school, and at nearby urban “background” sites. Across all of the pollutants, mean concentrations during bus commutes were higher than in any other microenvironment. Mean exposures (mean concentration times time spent in a particular microenvironment) in bus commutes were between 50 and 200 times greater than those for the loading/unloading microenvironment, and 20–40 times higher than those for the bus stops, depending on the pollutant. Although the analyzed school bus commutes represented only 10% of a child’s day, on average they contributed one‐third of a child’s 24‐hr overall black carbon exposure during a school day. For species closely related to vehicle exhaust, the within‐cabin exposures were generally dominated by the effect of surrounding traffic when windows were open and by the bus’s own exhaust when windows were closed. Low‐emitting buses generally exhibited high concentrations only when traveling behind a diesel vehicle, whereas high‐emitting buses exhibited high concentrations both when following other diesel vehicles and when idling without another diesel vehicle in front of the bus. To reduce school bus commute exposures, we recommend minimizing commute times, avoiding caravanning with other school buses, using the cleanest buses for the longest bus routes, maintaining conventional diesel buses to eliminate visible emissions, and transitioning to cleaner fuels and advanced particulate control technologies as soon as possible.