NEBRASKA - EPA Map of Radon Zones

The purpose of this map is to assist National, State and local organizations to target their resources and to implement radon-resistant building codes. This map is not intended to determine if a home in a given zone should be tested for radon. Homes with elevated levels of radon have been found in all three zones. All homes should be tested, regardless of zone designation

Understanding the costs of investigating coliform and E. coli detections during routine drinking water quality monitoring

Bacteriological failure investigations are crucial in the provision of safe, clean drinking water as part of a process of quality assurance and continual improvement. However, the financial implications of investigating coliform and Escherichia coli failures during routine water quality monitoring are poorly understood in the industry. The investigations for 737 coliform and E. coli failures across five UK water companies were analysed in this paper. The principal components of investigation costs were staff hours worked, re-samples collected, transportation, and special investigatory activities related to the sample collection location. The average investigation costs ranged from £575 for a customer tap failure to £4,775 for a water treatment works finished water failure. These costs were compared to predictions for US utilities under the Revised Total Coliform Rule. Improved understanding of the financial and staffing implications of investigating bacteriological failures can be used to budget operational expenditures and justify increased funding for preventive strategies

Chemical determinants of occupational hypersensitivity pneumonitis

Background: Workplace inhalational exposures to low molecular weight (LMW) chemicals cause hypersensitivity pneumonitis (HP) as well as the more common manifestation of respiratory hypersensitivity, occupational asthma (OA). Aims: To explore whether chemical causation of HP is associated with different structural and physico-chemical determinants from OA. Methods: Chemical causes of human cases of HP and OA were identified from searches of peer-reviewed literature up to the end of 2011. Each chemical was categorised according to whether or not it had been the attributed cause of at least one case of HP. The predicted asthma hazard was determined for each chemical using a previously developed quantitative structure-activity relationship (QSAR) model. The chemicals in both sets were independently and ‘blindly’ analysed by an expert in mechanistic chemistry for a qualitative prediction of protein cross-linking potential and determination of lipophilicity (log Kow). Results: Ten HP causing chemicals were identified and had a higher median QSAR predicted asthma hazard than the control group of 101 OA causing chemicals (p < 0.005). Nine of ten HP causing chemicals were predicted to be protein cross-linkers compared to 24/92 controls (p<0.0001). The distributions of log Kow indicated higher values for the HP list (median 3.47) compared to controls (median 0.81) (p < 0.05). Conclusion: These findings suggest that chemicals capable of causing HP tend to have higher predicted asthma hazard, are more lipophilic and are more likely to be protein cross-linkers than those causing OA. Key words: hypersensitivity pneumonitis, occupational chemicals, occupational respiratory disease, toxic inhalatio

Using Wind To Power a Groundwater Circulation Well—Preliminary Results

In areas of the country where the U.S. Department of Energy has classified the available wind resources as Class 3 or greater, the use of wind turbines to provide power to relatively small remediation systems such as groundwater circulation wells may be technically and economically feasible. Groundwater circulation wells are a good candidate technology to couple with renewable energy, because the remediation system removes contamination from the subject aquifer with no net loss of the groundwater resource, while the wind turbine does not create potentially harmful air emissions. Wind data collected in the vicinity of the former Nebraska Ordnance Plant Superfund site were used to select a wind turbine system to provide a portion of the energy necessary to power a groundwater circulation well located in an area of high trichloroethylene groundwater contamination. Because utility power was already installed at the remediation system, a 10 kW grid inter-tie wind turbine system supplements the utility system without requiring batteries for energy storage. The historical data from the site indicate that the quantity of energy purchased correlates poorly with the quantity of groundwater treated. Preliminary data from the wind turbine system indicate that the wind turbine provides more energy than the remediation system treatment components and the well submersible pump require on a monthly average. The preliminary results indicate that the coupling of wind turbines and groundwater circulation wells may be an attractive alternative in terms of the system operation time, cost savings, and contaminant mass removal

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

The public health benefits of insulation retrofits in existing housing in the United States

BACKGROUND: Methodological limitations make it difficult to quantify the public health benefits of energy efficiency programs. To address this issue, we developed a risk-based model to estimate the health benefits associated with marginal energy usage reductions and applied the model to a hypothetical case study of insulation retrofits in single-family homes in the United States. METHODS: We modeled energy savings with a regression model that extrapolated findings from an energy simulation program. Reductions of fine particulate matter (PM(2.5)) emissions and particle precursors (SO(2 )and NOx) were quantified using fuel-specific emission factors and marginal electricity analyses. Estimates of population exposure per unit emissions, varying by location and source type, were extrapolated from past dispersion model runs. Concentration-response functions for morbidity and mortality from PM(2.5 )were derived from the epidemiological literature, and economic values were assigned to health outcomes based on willingness to pay studies. RESULTS: In total, the insulation retrofits would save 800 TBTU (8 × 10(14 )British Thermal Units) per year across 46 million homes, resulting in 3,100 fewer tons of PM(2.5), 100,000 fewer tons of NOx, and 190,000 fewer tons of SO(2 )per year. These emission reductions are associated with outcomes including 240 fewer deaths, 6,500 fewer asthma attacks, and 110,000 fewer restricted activity days per year. At a state level, the health benefits per unit energy savings vary by an order of magnitude, illustrating that multiple factors (including population patterns and energy sources) influence health benefit estimates. The health benefits correspond to $1.3 billion per year in externalities averted, compared with$5.9 billion per year in economic savings. CONCLUSION: In spite of significant uncertainties related to the interpretation of PM(2.5 )health effects and other dimensions of the model, our analysis demonstrates that a risk-based methodology is viable for national-level energy efficiency programs

International Frameworks Dealing with Human Risk Assessment of Combined Exposure to Multiple Chemicals

The development of harmonised terminology and frameworks for the human risk assessment of combined exposure to multiple chemicals (“chemical mixtures”) is an important area for EFSA and a number of activities have already been undertaken, i.e. in the fields of pesticides and contaminants. The first step prior to a risk assessment of combined exposure to multiple chemicals is problem formulation defining the relevant exposure, hazard and population to be considered. In practice, risk assessment of multiple chemicals is conducted using a tiered approach for exposure assessment, hazard assessment and risk characterisation. Higher tiers require increasing knowledge about the group of chemicals under assessment and the tiers can range from tier 0 (default values, data poor situation) to tier 3 (full probabilistic models). This scientific report reviews the terminology, methodologies and frameworks developed by national and international agencies for the human risk assessment of combined exposure to multiple chemicals and provides recommendations for future activities at EFSA in this area