The impact of environmental, vehicle and driver characteristics on injury severity in older drivers hospitalized as a result of a traffic crash

INTRODUCTION: Compared to younger age groups, older people are more likely to be seriously injured or to die as a result of a traffic crash. METHOD: The aim of the study is to examine the impact of environmental, vehicle, crash, and driver characteristics on injury severity in older drivers involved in traffic crashes by using recently linked police crash records and hospitalization data from New South Wales, Australia. The severity of injury resulting from traffic crashes was measured using the International Classification of Diseases, 10th revision (ICD-10) Injury Severity Score (ICISS). RESULTS: Multivariate analysis identified rurality, presence of complex intersections, road speed limit, driver error, speeding, and seat belt use as independent predictors of injury severity in older people. The type of intersection configuration explained over half of the observed variations in injury severity. IMPACT ON INDUSTRY: Environmental modification such as intersection treatments might contribute to a decrease in the severity of injury in older people involved in road crashes.     

Partial stroke testing of process shutdown valves: How to determine the test coverage

Partial stroke testing (PST) has recently been introduced as a semi-automatic means to test process shutdown valves. Normally, this type of testing does not disturb the process and can detect many of the failures that traditionally have been revealed only by functional testing. The fraction of all dangerous failures that are detected by PST is called the PST coverage and is decisive for the effectiveness of the PST. So far, limited guidance on how to determine the PST coverage has been given. This paper discusses the application and limitations of PST and suggests a new procedure for how to determine the PST coverage factor.     

Decision support model for assessing aquifer pollution hazard and prioritizing groundwater resources management in the wet Pampa plain, Argentina

This paper gives an account of the implementation of a decision support system for assessing aquifer pollution hazard and prioritizing subwatersheds for groundwater resources management in the southeastern Pampa plain of Argentina. The use of this system is demonstrated with an example from Dulce Stream Basin (1,000 km² encompassing 27 subwatersheds), which has high level of agricultural activities and extensive available data regarding aquifer geology. In the logic model, aquifer pollution hazard is assessed as a function of two primary topics: groundwater and soil conditions. This logic model shows the state of each evaluated landscape with respect to aquifer pollution hazard based mainly on the parameters of the DRASTIC and GOD models. The decision model allows prioritizing subwatersheds for groundwater resources management according to three main criteria including farming activities, agrochemical application, and irrigation use. Stakeholder participation, through interviews, in combination with expert judgment was used to select and weight each criterion. The resulting subwatershed priority map, by combining the logic and decision models, allowed identifying five subwatersheds in the upper and middle basin as the main aquifer protection areas. The results reasonably fit the natural conditions of the basin, identifying those subwatersheds with shallow water depth, loam–loam silt texture soil media and pasture land cover in the middle basin, and others with intensive agricultural activity, coinciding with the natural recharge area to the aquifer system. Major difficulties and some recommendations of applying this methodology in real-world situations are discussed.     

Bicycle helmet use among children in the United States: The effects of legislation, personal and household factors

Introduction

Children ages 5-14 years have the highest rate of bicycle-related injuries in the country. Bicycle helmets can prevent head and brain injuries, which represent the most serious type of bicycle-related injury.

Objectives

This paper compares children's bicycle helmet use to that estimated from an earlier study, and explores regional differences in helmet use by existing helmet legislation.

Methods

This study was a cross-sectional, list-assisted random-digit-dial telephone survey. Interviews were completed by 9,684 respondents during 2001-2003. The subset with at least one child in the household age 5-14 years (2,409 respondents) answered questions about bicycle helmet use for a randomly selected child in their household.

Results

Almost half (48%) of the children always wore their helmet, 23% sometimes wore their helmet, and 29% never wore their helmet. Helmet wearing was significantly associated with race, ethnicity, and child age but was not associated with the sex of the child. Other significant predictors of use included household income, household education, census region, and bicycle helmet law status. Statewide laws were more effective than laws covering smaller areas. The proportion of children who always wore a helmet increased from 25% in 1994 to 48% in 2001-2002. Significant increases in helmet use from 20% to 26% were seen among both sexes, younger (5-9 years) and older (10-14 years) children, and in all four regions of the country.

Conclusions

While there has been substantial progress in the number of children who always wear their helmets, more than half do not. Further progress will require using a combination of methods that have been shown to successfully promote consistent helmet use. Impact on industry: minimal.     

Reduction of atmospheric emissions due to switching from fuel oil to natural gas at a power plant in a critical area in Central Mexico

ABSTRACT

A case study was conducted to evaluate the SO₂ emission reduction in a power plant in Central Mexico, as a result of the shifting of fuel oil to natural gas. Emissions of criteria pollutants, greenhouse gases, organic and inorganic toxics were estimated based on a 2010 report of hourly fuel oil consumption at the “Francisco Pérez Ríos” power plant in Tula, Mexico. For SO₂, the dispersion of these emissions was assessed with the CALPUFF dispersion model. Emissions reductions of > 99% for SO₂, PM and Pb, as well as reductions >50% for organic and inorganic toxics were observed when simulating the use of natural gas. Maximum annual (993 µg/m³) and monthly average SO₂ concentrations were simulated during the cold-dry period (152–1063 µg/m³), and warm-dry period (239–432 µg/m³). Dispersion model results and those from Mexico City’s air quality forecasting system showed that SO₂ emissions from the power plant affect the north of Mexico City in the cold-dry period. The evaluation of model estimates with 24 hr SO₂ measured concentrations at Tepeji del Rio suggests that the combination of observations and dispersion models are useful in assessing the reduction of SO₂ emissions due to shifting in fuels. Being SO₂ a major precursor of acid rain, high transported sulfate concentrations are of concern and low pH values have been reported in the south of Mexico City, indicating that secondary SO₂ products emitted in the power plant can be transported to Mexico City under specific atmospheric conditions.

Implications: Although the surroundings of a power plant located north of Mexico City receives most of the direct SO₂ impact from fuel oil emissions, the plume is dispersed and advected to the Mexico City metropolitan area, where its secondary products may cause acid rain. The use of cleaner fuels may assure significant SO₂ reductions in the plant emissions and consequent acid rain presence in nearby populated cities and should be compulsory in critical areas to comply with annual emission limits and health standards.     

Evaluating the Illinois Stream Valley Segment Model as an Effective Management Tool

Stream habitat assessments are conducted to evaluate biological potential, determine anthropogenic impacts, and guide restoration projects. Utilizing these procedures, managers must first select a representative stream reach, which is typically selected based on several criteria. To develop a consistent and unbiased procedure for choosing sampling locations, the Illinois Department of Natural Resources and the Illinois Natural History Survey have proposed a technique by which watersheds are divided into homogeneous stream segments called valley segments. Valley segments are determined by GIS parameters including surficial geology, predicted flow, slope, and drainage area. To date, no research has been conducted to determine if the stream habitat within a valley segment is homogeneous and if different valley segments have varying habitat variables. Two abutting valley segments were randomly selected within 13 streams in the Embarras River watershed, located in east-central Illinois. One hundred meter reaches were randomly selected within each valley segment, and a transect method was used to quantify habitat characteristics of the stream channel. Habitat variables for each stream were combined through a principal components analysis (PCA) to measure environmental variation between abutting valley segments. A multivariate analysis of variance (MANOVA) was performed on PCA axes 1–3. The majority of abutting valley segments were significantly different from each other indicating that habitat variability within each valley segment was less than variability between valley segments (5.37 ≤ F ≤ 245.13; P ≤ 0.002). This comparison supports the use of the valley segment model as an effective management tool for identifying representative sampling locations and extrapolating reach-specific information.     

Recycled Polyethylene Composites Reinforced with Jute Fabric from Sackcloth: Part II-Impact Strength Evaluation

Environmental problems are motivating recycling actions and reuse alternatives for materials with main focus for the application of those renewable and biodegradable materials such as lignocellulosic fibers. Composites reinforced with such fibers are being considered by several industrial sectors, not only from the environmental safety, but also from economic considerations and improved properties. This paper, which is continuation of the work (Part I) by the authors’ use of the recycled polyethylene and used jute fabrics, presents evaluation of its toughness measured by the impact energy using both Izod and Charpy methods. Fabric content used is up to 40 wt. %. It is found that the incorporation of both types (new and used) of jute fabric significantly increased the impact energy of composites, with higher values associated with the new jute fabric. Fractographic analysis revealed that weaved configuration of the jute fibers and their low interfacial resistance with the matrix are responsible for the observed impact performance of these composites.     

Optimization of artificial neural network models through genetic algorithms for surface ozone concentration forecasting

Introduction

This study proposes three methodologies to define artificial neural network models through genetic algorithms (GAs) to predict the next-day hourly average surface ozone (O₃) concentrations. GAs were applied to define the activation function in hidden layer and the number of hidden neurons.

Methods

Two of the methodologies define threshold models, which assume that the behaviour of the dependent variable (O₃ concentrations) changes when it enters in a different regime (two and four regimes were considered in this study). The change from one regime to another depends on a specific value (threshold value) of an explanatory variable (threshold variable), which is also defined by GAs. The predictor variables were the hourly average concentrations of carbon monoxide (CO), nitrogen oxide, nitrogen dioxide (NO₂), and O₃ (recorded in the previous day at an urban site with traffic influence) and also meteorological data (hourly averages of temperature, solar radiation, relative humidity and wind speed). The study was performed for the period from May to August 2004.

Results and discussion

Several models were achieved and only the best model of each methodology was analysed. In threshold models, the variables selected by GAs to define the O₃ regimes were temperature, CO and NO₂ concentrations, due to their importance in O₃ chemistry in an urban atmosphere.

Conclusion

In the prediction of O₃ concentrations, the threshold model that considers two regimes was the one that fitted the data most efficiently.