Prediction and analysis of near-road concentrations using a reduced-form emission/dispersion model

<p>Abstract</p> <p>Background</p> <p>Near-road exposures of traffic-related air pollutants have been receiving increased attention due to evidence linking emissions from high-traffic roadways to adverse health outcomes. To date, most epidemiological and risk analyses have utilized simple but crude exposure indicators, most typically proximity measures, such as the distance between freeways and residences, to represent air quality impacts from traffic. This paper derives and analyzes a simplified microscale simulation model designed to predict short- (hourly) to long-term (annual average) pollutant concentrations near roads. Sensitivity analyses and case studies are used to highlight issues in predicting near-road exposures.</p> <p>Methods</p> <p>Process-based simulation models using a computationally efficient reduced-form response surface structure and a minimum number of inputs integrate the major determinants of air pollution exposures: traffic volume and vehicle emissions, meteorology, and receptor location. We identify the most influential variables and then derive a set of multiplicative submodels that match predictions from "parent" models MOBILE6.2 and CALINE4. The assembled model is applied to two case studies in the Detroit, Michigan area. The first predicts carbon monoxide (CO) concentrations at a monitoring site near a freeway. The second predicts CO and PM_2.5concentrations in a dense receptor grid over a 1 km²area around the intersection of two major roads. We analyze the spatial and temporal patterns of pollutant concentration predictions.</p> <p>Results</p> <p>Predicted CO concentrations showed reasonable agreement with annual average and 24-hour measurements, e.g., 59% of the 24-hr predictions were within a factor of two of observations in the warmer months when CO emissions are more consistent. The highest concentrations of both CO and PM_2.5were predicted to occur near intersections and downwind of major roads during periods of unfavorable meteorology (e.g., low wind speeds) and high emissions (e.g., weekday rush hour). The spatial and temporal variation among predicted concentrations was significant, and resulted in unusual distributional and correlation characteristics, including strong negative correlation for receptors on opposite sides of a road and the highest short-term concentrations on the "upwind" side of the road.</p> <p>Conclusions</p> <p>The case study findings can likely be generalized to many other locations, and they have important implications for epidemiological and other studies. The reduced-form model is intended for exposure assessment, risk assessment, epidemiological, geographical information systems, and other applications.</p

Effectiveness of waste minimisation projects in reducing water demand by UK industry

There is growing interest in managing water demand in the UK. A series of waste minimization clubs have been set up within the country and this paper identifies the effectiveness of these clubs in reducing the demand for water within industry. Membership of these clubs is voluntary and the only incentive for industry to reduce water consumption, and consequently the production of effluent, is the almost immediate financial saving made by the company, often achieved by accounting for the water consumption and loss within site from the point of input from the water supplier to output in the form of effluent. On average, companies are able to reduce water consumption by up to 30 percent. If the entire industrial sector within the UK were to achieve this degree of savings, it is possible that approximately 1300Ml/d could be saved

Development of a modified floristic quality index as a rapid habitat assessment method in the northern Everglades

Floristic quality assessments (FQA) using floristic quality indices (FQIs) are useful tools for assessing and comparing vegetation communities and related habitat condition. However, intensive vegetation surveys requiring significant time and technical expertise are necessary, which limits the use of FQIs in environmental monitoring programs. This study modified standard FQI methods to develop a rapid assessment method for characterizing and modeling change in wetland habitat condition in the northern Everglades. Method modifications include limiting vegetation surveys to a subset of taxa selected as indicators of impact and eliminating richness and/or abundance factors from the equation. These modifications reduce the amount of time required to complete surveys and minimizes misidentification of species, which can skew results. The habitat characterization and assessment tool (HCAT) developed here is a FQA that uses a modified FQI to detect and model changes in habitat condition based on vegetation communities, characterize levels of impact as high, moderate, or low, provide predictive capabilities for assessing natural resource management or water management operation alternatives, and uniquely links a FQI with readily accessible environmental data. For application in the northern Everglades, surface water phosphorus concentrations, specific conductivity, distance from canal, and days since dry (5-year average) explained 67% of the variability in the dataset with \u3e 99.9% confidence. The HCAT approach can be used to monitor, assess, and evaluate habitats with the objective of informing management decisions (e.g., as a screening tool) to maximize conservation and restoration of protected areas and is transferable to other wetlands with additional modification

Before and after study of bar workers' perceptions of the impact of smoke-free workplace legislation in the Republic of Ireland

<p>Abstract</p> <p>Background</p> <p><it>Objectives</it>: To compare support for, and perceptions of, the impacts of smoke-free workplace legislation among bar workers in the Republic of Ireland (ROI) pre- and post-implementation, and to identify predictors of support for the legislation.</p> <p>Methods</p> <p><it>Setting</it>: Public houses (pubs) in three areas of the ROI.</p> <p><it>Design</it>: Comparisons pre- and post-implementation of smoke-free workplace legislation.</p> <p><it>Participants</it>: From a largely non-random selection, 288 bar workers volunteered for the baseline survey; 220 were followed up one year later (76.4%).</p> <p><it>Outcome measures: </it>Level of support for the legislation, attitude statements concerning potential impacts of the law and modelled predictors of support for the legislation.</p> <p>Results</p> <p>Pre-implementation 59.5% of participants supported the legislation, increasing to 76.8% post-implementation. Support increased among smokers by 27.3 percentage points from 39.4% to 66.7% (p < 0.001) and among non-smokers by 12.4% percentage points from 68.8% to 81.2% (p = 0.003).</p> <p>Pre-legislation three-quarters of participants agreed that the legislation would make bars more comfortable and was needed to protect workers' health. Post-legislation these proportions increased to over 90% (p < 0.001). However, negative perceptions also increased, particularly for perceptions that the legislation has a negative impact on business (from 50.9% to 62.7%, p = 0.008) and that fewer people would visit pubs (41.8% to 62.7%, p < 0.001). After adjusting for relevant covariates, including responses to the attitude statements, support for the ban increased two to three-fold post-implementation. Regardless of their views on the economic impact, most participants agreed, both pre- and post-implementation, that the legislation was needed to protect bar workers' health.</p> <p>Conclusion</p> <p>Smoke-free legislation had the support of three-quarters of a large sample of bar workers in the ROI. However, this group holds complex sets of both positive and negative perspectives on the legislation. Of particular importance is that negative economic perceptions did not diminish the widely held perception that the ban is needed to protect workers' health.</p