Comparing safety climate factors as predictors of work-related driving behavior

INTRODUCTION: Research suggests safety climate (SC) is a strong predictor of safety-related outcomes in organizations. This study explores the relationship between six SC dimensions and four aspects of work-related driving. METHOD: The SC factors measured were "communication and procedures," "work pressures," "relationships," "safety rules," "driver training," and "management commitment." The aspects of self-reported occupational driving measured were traffic violations, driver error, driving while distracted, and pre-trip vehicle maintenance. RESULTS: Hierarchical regression analyses revealed that the SC factors accounted for significant amounts of variance in all four aspects of work-related driving, over and above the control factors of age, sex, and work-related driving exposure. However, further investigation indicated certain SC factors (particularly safety rules, communication, and management commitment) were more strongly related to specific aspects of work-related driving behavior than others. Together, the SC factors were better able to predict self-reported distraction from the road than the other aspects of driving behavior measured. Implications for occupational safety, particularly for the management of work-related drivers are discussed.     

Comparison of continuous and filter-based carbon measurements at the Fresno supersite

Results from six continuous and semicontinuous black carbon (BC) and elemental carbon (EC) measurement methods are compared for ambient samples collected from December 2003 through November 2004 at the Fresno Supersite in California. Instruments included a multi-angle absorption photometer (MAAP; lambda = 670 nm); a dual-wavelength (lambda = 370 and 880 nm) aethalometer; seven-color (lambda = 370, 470, 520, 590, 660, 880, and 950 nm) aethalometers; the Sunset Laboratory carbon aerosol analysis field instrument; a photoacoustic light absorption analyzer (lambda = 1047 nm); and the R&P 5400 ambient carbon particulate monitor. All of these acquired BC or EC measurements over periods of 1 min to 1 hr. Twenty-four-hour integrated filter samples were also acquired and analyzed by the Interagency Monitoring of Protected Visual Environments (IMPROVE) thermal/optical reflectance carbon analysis protocol. Site-specific mass absorption efficiencies estimated by comparing light absorption with IMPROVE EC concentrations were 5.5 m2/g for the MAAP, 10 m2/g for the aethalometer at a wavelength of 880 nm, and 2.3 m2/g for the photoacoustic analyzer; these differed from the default efficiencies of 6.5, 16.6, and 5 m2/g, respectively. Scaling absorption by inverse wavelength did not provide equivalent light absorption coefficients among the instruments for the Fresno aerosol measurements. Ratios of light absorption at 370 nm to those at 880 nm from the aethalometer were nearly twice as high in winter as in summer. This is consistent with wintertime contributions from vehicle exhaust and from residential wood combustion, which is believed to absorb more shorter-wavelength light. To reconcile BC and EC measurements obtained by different methods, a better understanding is needed of the wavelength dependence of light-absorption and mass-absorption efficiencies and how they vary with different aerosol composition.     

Further validation of artificial neural network-based emissions simulation models for conventional and hybrid electric vehicles

With the advent of hybrid electric vehicles, computer-based vehicle simulation becomes more useful to the engineer and designer trying to optimize the complex combination of control strategy, power plant, drive train, vehicle, and driving conditions. With the desire to incorporate emissions as a design criterion, researchers at West Virginia University have developed artificial neural network (ANN) models for predicting emissions from heavy-duty vehicles. The ANN models were trained on engine and exhaust emissions data collected from transient dynamometer tests of heavy-duty diesel engines then used to predict emissions based on engine speed and torque data from simulated operation of a tractor truck and hybrid electric bus. Simulated vehicle operation was performed with the ADVISOR software package. Predicted emissions (carbon dioxide [CO2] and oxides of nitrogen [NO(x)]) were then compared with actual emissions data collected from chassis dynamometer tests of similar vehicles. This paper expands on previous research to include different driving cycles for the hybrid electric bus and varying weights of the conventional truck. Results showed that different hybrid control strategies had a significant effect on engine behavior (and, thus, emissions) and may affect emissions during different driving cycles. The ANN models underpredicted emissions of CO2 and NO(x) in the case of a class-8 truck but were more accurate as the truck weight increased.     

Nanoparticle and ultrafine particle events at the Fresno supersite

Continuous measurements of particle size distributions of 3-407 nm were collected from August 2002 to July 2004 at the Fresno Supersite to understand their number concentrations, size distributions, and formation processes. Measurements for fine particulate matter (PM2.5) mass, sulfate (SO4(2-)), nitrate (NO3-), black carbon (BC), particle-bound polycyclic aromatic hydrocarbons (PAHs), nitrogen oxides (NOx), carbon monoxide (CO), ozone (O3), and meteorological data (wind speed, wind direction, temperature [T], relative humidity [RH], and solar radiation) were used to determine the causes of nanoparticle (3-10 nm) and ultrafine (10-100 nm) particle events. These events were found to be divided into four types: (1) 3- to 10-nm morning nucleation; (2) 10- to 30-nm morning traffic; (3) 10- to 30-nm afternoon photochemical; and (4) 50- to 84-nm evening home heating, including residential wood combustion. Intense examples of the first type (>10(4) number [#]/cm3) were observed on 29 days, nearly always during the summer. The second type of event was observed on more than 73 days and occurred throughout the year. The third type was observed on 36 days, from spring through summer. The fourth type was found on 109 days, all of them during the winter. Although sulfur dioxide (SO2) emissions in Central California are low, the small residual amounts in gasoline and diesel fuel are apparently sufficient to initiate nucleation events. These were measured in the morning, soon after the shallow surface inversion coupled with layers aloft where nucleation probably was initiated. PM2.5 concentrations were poorly correlated with nanoparticle number.     

Groundwater Denitrification Capacity of Riparian Zones in Suburban and Agricultural Watersheds1

Watson, Tara K., Dorothy Q. Kellogg, Kelly Addy, Arthur J. Gold, Mark H. Stolt, Sean W. Donohue, and Peter M. Groffman, 2010. Groundwater Denitrification Capacity of Riparian Zones in Suburban and Agricultural Watersheds. Journal of the American Water Resources Association (JAWRA) 46(2):237-245. DOI: 10.1111/j.1752-1688.2010.00418.x Abstract: We evaluated the relationship of dominant watershed land use to the structure and nitrogen (N) sink function of riparian zones. We focused on groundwater denitrification capacity, water table dynamics, and the presence and pattern of organically enriched deposits. We used the push-pull method (measurement of ¹⁵N-enriched denitrification gases derived from an introduced groundwater plume of ¹⁵N-enriched nitrate) to evaluate groundwater denitrification capacity on nine forested wetland riparian sites developed in alluvial or outwash parent materials in southern New England. Three replicate sites were located in each of the three watershed types, those with substantial (1) irrigated agriculture, (2) suburban development, and (3) forest. Soil morphology and water table dynamics were assessed at each site. We found significantly lower mean annual water tables at sites within watersheds with substantial irrigated agriculture or suburban development than forested watersheds. Water table dynamics were more variable at sites within suburban watersheds, especially during the summer. Groundwater denitrification capacity was significantly greater at sites within forested watersheds than in watersheds with substantial irrigated agriculture. Because of the high degree of variability observed in riparian sites within suburban watersheds, groundwater denitrification capacity was not significantly different from either forested or agricultural watersheds. The highly variable patterns of organically enriched deposits and water tables at sites within suburban watersheds suggests that depositional events are irregular, limiting the predictability of groundwater N dynamics in these riparian zones. The variability of riparian N removal in watersheds with extensive suburbia or irrigated agriculture argues for N management strategies emphasizing effective N source controls in these settings.     

Factors Influencing the Effectiveness of Wildlife Underpasses in Banff National Park, Alberta, Canada

Abstract: Wildlife crossing structures are intended to increase permeability and habitat connectivity across roads. Few studies, however, have assessed the effectiveness of these mitigation measures in a multispecies or community level context. We used a null model to test whether wildlife crossing structures serve large mammal species equally or whether such structures limit habitat connectivity across roads in species-specific ways. We also modeled species responses to 14 variables related to underpass structure, landscape features, and human activity. Species performance ratios (observed crossing frequency to expected crossing frequency) were evaluated for four large carnivore and three ungulate species in 11 underpass structures in Banff National Park, Alberta, Canada. Observed crossing frequencies were collected in 35 months of underpass monitoring. Expected frequencies were developed from three independent models: radio telemetry, pellet counts, and habitat-suitability indices. The null model showed that species responded to underpasses differently. In the presence of human activity carnivores were less likely to use underpasses than were ungulates. Apart from human activity, carnivore performance ratios were better correlated to landscape variables, and ungulate performance ratios were better correlated to structural variables. We suggest that future underpasses designed around topography, habitat quality, and location will be minimally successful if human activity is not managed.     

Projections of hospitalised fall-related injury in NSW, Australia: impacts on the hospital and aged care sectors

Projections of the number, rate and cost of fall-related hospitalised injuries for individuals aged 65 years and older in New South Wales (NSW), Australia were estimated to 2051 for two scenarios: (1) demographic change only using 2008 admission rates; and (2) modelled change using negative binominal regression taking into account current trends in admission rates. Based on demographic change alone, the number and cost of fall injury hospitalisations among older people is expected to increase almost three-fold by 2051. Transfers to permanent residential aged care will also increase 3.2 fold. However, if the fall-related hospitalisation rate sustains its current trend, these increases are projected to be more than ten-fold by 2051. Even with demographic change alone, there will be a significant impact on the resources required to care for older people suffering a fall injury hospitalisation over the next forty years in NSW. The impact on the hospital and aged care sectors will be considerable unless significant improvements occur in the prevention and treatment of fall-related injury in older people.     

Work-related driving safety in light vehicle fleets: A review of past research and the development of an intervention framework

This paper presents a critical review of past research in the work-related driving field in light vehicle fleets (e.g., vehicles < 4.5 tonnes) and an intervention framework that provides future direction for practitioners and researchers. Although work-related driving crashes have become the most common cause of death, injury, and absence from work in Australia and overseas, very limited research has progressed in establishing effective strategies to improve safety outcomes. In particular, the majority of past research has been data-driven, and therefore, limited attention has been given to theoretical development in establishing the behavioural mechanism underlying driving behaviour. As such, this paper argues that to move forward in the field of work-related driving safety, practitioners and researchers need to gain a better understanding of the individual and organisational factors influencing safety through adopting relevant theoretical frameworks, which in turn will inform the development of specifically targeted theory-driven interventions. This paper presents an intervention framework that is based on relevant theoretical frameworks and sound methodological design, incorporating interventions that can be directed at the appropriate level, individual and driving target group.