Preparation, certification and interlaboratory analysis of workplace air filters spiked with high-fired beryllium oxide

Occupational sampling and analysis for multiple elements is generally approached using various approved methods from authoritative government sources such as the National Institute for Occupational Safety and Health (NIOSH), the Occupational Safety and Health Administration (OSHA) and the Environmental Protection Agency (EPA), as well as consensus standards bodies such as ASTM International. The constituents of a sample can exist as unidentified compounds requiring sample preparation to be chosen appropriately, as in the case of beryllium in the form of beryllium oxide (BeO). An interlaboratory study was performed to collect analytical data from volunteer laboratories to examine the effectiveness of methods currently in use for preparation and analysis of samples containing calcined BeO powder. NIST SRM(?) 1877 high-fired BeO powder (1100 to 1200 °C calcining temperature; count median primary particle diameter 0.12 μm) was used to spike air filter media as a representative form of beryllium particulate matter present in workplace sampling that is known to be resistant to dissolution. The BeO powder standard reference material was gravimetrically prepared in a suspension and deposited onto 37 mm mixed cellulose ester air filters at five different levels between 0.5 μg and 25 μg of Be (as BeO). Sample sets consisting of five BeO-spiked filters (in duplicate) and two blank filters, for a total of twelve unique air filter samples per set, were submitted as blind samples to each of 27 participating laboratories. Participants were instructed to follow their current process for sample preparation and utilize their normal analytical methods for processing samples containing substances of this nature. Laboratories using more than one sample preparation and analysis method were provided with more than one sample set. Results from 34 data sets ultimately received from the 27 volunteer laboratories were subjected to applicable statistical analyses. The observed performance data show that sample preparations using nitric acid alone, or combinations of nitric and hydrochloric acids, are not effective for complete extraction of Be from the SRM 1877 refractory BeO particulate matter spiked on air filters; but that effective recovery can be achieved by using sample preparation procedures utilizing either sulfuric or hydrofluoric acid, or by using methodologies involving ammonium bifluoride with heating. Laboratories responsible for quantitative determination of Be in workplace samples that may contain high-fired BeO should use quality assurance schemes that include BeO-spiked sampling media, rather than solely media spiked with soluble Be compounds, and should ensure that methods capable of quantitative digestion of Be from the actual material present are used.     

Statistical Simulation to Estimate Uncertain Behavioral Parameters of Hybrid Energy-Economy Models

In energy-economy modeling, new hybrid models attempt to combine the technological explicitness of bottom-up models with the macroeconomic feedbacks and statistically estimated behavioral parameters of top-down models. However, statistical estimation of behavioral parameters (portraying firm and household technology choices) with such models is challenged by the number of uncertain variables and the lack of historical data on technologies in terms of capital costs, operating costs, and market shares. Multiple combinations of parameter values might equally explain past technology choices. This paper reports on the application of a Bayesian statistical simulation approach for estimating the most likely values for these key behavioral parameters in order to best explain past technology choices and then simulate policies to influence future technology choices. The method included (1) data collection of key technology market shares, capital costs, and operating costs over the past; (2) backcasting a hybrid energy-economy model over a historical time period; and (3) the application of Markov chain Monte Carlo statistical simulation using the Metropolis–Hastings algorithm as a tool for estimating distributions for key parameters in the model. The results provide a means of indicating the uncertainty bounds around key behavioral parameters when generating forecasts of the effect of certain policies. However, the results also indicate that this approach may have limited applicability, given that future available technologies may differ substantially from past technologies and that it is difficult to separate the effects of parameter uncertainty from model structure uncertainty.     

Assessing health impacts in complex eco-epidemiological settings in the humid tropics: Modular baseline health surveys

The quantitative assessment of health impacts has been identified as a crucial feature for realising the full potential of health impact assessment (HIA). In settings where demographic and health data are notoriously scarce, but there is a broad range of ascertainable ecological, environmental, epidemiological and socioeconomic information, a diverse toolkit of data collection strategies becomes relevant for the mainly small-area impacts of interest. We present a modular, cross-sectional baseline health survey study design, which has been developed for HIA of industrial development projects in the humid tropics. The modular nature of our toolkit allows our methodology to be readily adapted to the prevailing eco-epidemiological characteristics of a given project setting. Central to our design is a broad set of key performance indicators, covering a multiplicity of health outcomes and determinants at different levels and scales. We present experience and key findings from our modular baseline health survey methodology employed in 14 selected sentinel sites within an iron ore mining project in the Republic of Guinea. We argue that our methodology is a generic example of rapid evidence assembly in difficult-to-reach localities, where improvement of the predictive validity of the assessment and establishment of a benchmark for longitudinal monitoring of project impacts and mitigation efforts is needed.     

Sorption and Biodegradation of Vapor-Phase Organic Compounds with Wastewater Sludge and Food Waste Compost

ABSTRACT

To test the possible use of composted food waste and wastewater sludge as biofilters to treat gas-phase volatile organic compounds (VOCs), batch experiments were conducted with an isolated strain that could degrade aromatic compounds under aerobic conditions. A benzene and trichloroethylene (TCE) mixture was used as the gas-phase pollutant in experiments with composted food waste, sludge, and soil. Under aerobic conditions, benzene was degraded as a primary substrate and TCE was degraded cometabolically, with water contents varying from 6 to 60% (volume of water added/volume of solid). Optimal water content for VOC removal was 12% for the soil, 36% for the composted food waste, and 48% for the sludge.

The extent of VOC sorption and biodegradation at the optimal water content was different for each material. With the same initial VOC concentration, more VOCs were removed by sorption onto the composted food waste and the sludge, while less VOCs were biodegraded in comparison with the results using soil. The reason the biodegradation in the soil was greater may be partly attributed to the fact that, due to less sorption, the aqueous-phase concentration of VOCs, which microorganisms could utilize as a carbon source or cometabolize, was higher. We also speculate that the distribution of microorganisms in each medium affects the rate of biodegradation. A large number of microorganisms were attached to the composted food waste and sludge. Mass transfer of VOCs and oxygen to these microorganisms, which appear to have been heterogeneously distributed in clusters, may have been limited, resulting in hindered biodegradation.     

Resolving the interactions between population density and air pollution emissions controls in the San Joaquin Valley,USA

The effectiveness of emissions control programs designed to reduce concentrations of airborne particulate matter with an aerodynamic diameter <2.5 μm (PM_2.5) in California's San Joaquin Valley was studied in the year 2030 under three growth scenarios: low, medium, and high population density. Base-case inventories for each choice of population density were created using a coupled emissions modeling system that simultaneously considered interactions between land use and transportation, area source, and point source emissions. The ambient PM_2.5 response to each combination of population density and emissions control was evaluated using a regional chemical transport model over a 3-week winter stagnation episode. Comparisons between scenarios were based on regional average and population-weighted PM_2.5 concentrations. In the absence of any emissions control program, population-weighted concentrations of PM_2.5 in the future San Joaquin Valley are lowest under growth scenarios that emphasize low population density. A complete ban on wood burning and a 90% reduction in emissions from food cooking operations and diesel engines must occur before medium- to high-density growth scenarios result in lower population-weighted concentrations of PM_2.5. These trends partly reflect the fact that existing downtown urban cores that naturally act as anchor points for new high-density growth in the San Joaquin Valley are located close to major transportation corridors for goods movement. Adding growth buffers around transportation corridors had little impact in the current analysis, since the 8-km resolution of the chemical transport model already provided an artificial buffer around major emissions sources.

Assuming that future emissions controls will greatly reduce or eliminate emissions from residential wood burning, food cooking, and diesel engines, the 2030 growth scenario using “as-planned” (medium) population density achieves the lowest population-weighted average PM_2.5 concentration in the future San Joaquin Valley during a severe winter stagnation event.

Implications: The San Joaquin Valley is one of the most heavily polluted air basins in the United States that are projected to experience strong population growth in the coming decades. The best plan to improve air quality in the region combines medium- or high-density population growth with rigorous emissions controls. In the absences of controls, high-density growth leads to increased population exposure to PM_2.5 compared with low-density growth scenarios (urban sprawl).     

Multiple-year black carbon measurements and source apportionment using Delta-C in Rochester,New York

Black carbon (BC), an important component of the atmospheric aerosol, has climatic, environmental, and human health significance. In this study, BC was continuously measured using a two-wavelength aethalometer (370 nm and 880 nm) in Rochester, New York, from January 2007 to December 2010. The monitoring site is adjacent to two major urban highways (I-490 and I-590), where 14% to 21% of the total traffic was heavy-duty diesel vehicles. The annual average BC concentrations were 0.76 μg/m³, 0.67 μg/m³, 0.60 μg/m³, and 0.52 μg/m³ in 2007, 2008, 2009, and 2010, respectively. Positive matrix factorization (PMF) modeling was performed using PM_2.5 elements, sulfate, nitrate, ammonia, elemental carbon (EC), and organic carbon (OC) data from the U.S. Environmental Protection Agency (EPA) speciation network and Delta-C (UVBC_370nm – BC_880nm) data. Delta-C has been previously shown to be a tracer of wood combustion factor. It was used as an input variable in source apportionment models for the first time in this study and was found to play an important role in separating traffic (especially diesel) emissions from wood combustion emissions. The result showed the annual average PM_2.5 concentrations apportioned to diesel emissions in 2007, 2008, 2009, and 2010 were 1.34 μg/m³, 1.25 μg/m³, 1.13 μg/m³, and 0.97 μg/m³, respectively. The BC conditional probability function (CPF) plots show a large contribution from the highway diesel traffic to elevated BC concentrations. The measurements and modeling results suggest an impact of the U.S Environmental Protection Agency (EPA) 2007 Heavy-Duty Highway Rule on the decrease of BC and PM_2.5 concentrations during the study period.

Implications: This study suggests that there was an observable impact of the U.S EPA 2007 Heavy-Duty Highway Rule on the ambient black carbon concentrations in Rochester, New York. Aethalometer Delta-C was used as an input variable in source apportionment models and it allowed the separation of traffic (especially diesel) emissions from wood combustion emissions.     

Elimination kinetics of perfluorohexanoic acid in humans and comparison with mouse,rat and monkey

Major fluorinated chemical manufacturers have developed new short-chain per- and polyfluorinated substances with more favorable environmental, health and safety profiles. This study provides the first evaluation of the elimination half-life of perfluorohexanoic acid (PFHxA) from the blood of humans. PFHxA biomonitoring data were obtained from a recently published study of professional ski wax technicians. These data were analyzed to provide estimates of the apparent half-life of PFHxA from humans, and comparisons were made with kinetic studies of PFHxA elimination from mice, rats and monkeys. The apparent elimination half-life of PFHxA in highly exposed humans ranged between 14 and 49 d with a geomean of 32 d. The half-lives of PFHxA in mice, rats, monkeys and humans were proportional to body weight with no differences observed between genders, indicating similar volumes of distribution and similar elimination mechanisms among mammalian species. Compared to long-chain perfluoroalkyl acid analogs, PFHxA is rapidly cleared from biota. The consistent weight-normalized elimination half-lives for PFHxA in mammalian species indicates that results obtained from animal models are suitable for establishment of PFHxA benchmark dose and reference dose hazard endpoints for use in human risk assessments.