Casson Stallings

A Probabilistic Arsenic Exposure Assessment for Children who Contact CCA-Treated Playsets and Decks, Part 1: Model Methodology, Variability Results, and Model Evaluation

Concerns have been raised regarding the safety of young children who may contact arsenic residues while playing on and around chromated copper arsenate (CCA)-treated wood playsets and decks. Although CCA registrants voluntarily canceled the production of treated wood for residential use in 2003, the potential for exposure from existing structures and surrounding soil still poses concerns. The EPAs Office of Research and Development developed and applied the probabilistic Stochastic Human Exposure and Dose Simulation model for wood preservatives (SHEDS-Wood) to estimate childrens absorbed dose of arsenic from CCA. Skin contact with, and nondietary ingestion of, arsenic in soil and wood residues were considered for the population of children in the United States who frequently contact CCA-treated wood playsets and decks. Model analyses were conducted to assess the range in population estimates and the impact of potential mitigation strategies such as the use of sealants and hand washing after play events. The results show predicted central values for lifetime annual average daily dose values for arsenic ranging from 10(-6) to 10(-5) mg/kg/day, with predicted 95th percentiles on the order of 10(-5) mg/kg/day. There were several orders of magnitude between lower and upper percentiles. Residue ingestion via hand-to-mouth contact was determined to be the most significant exposure route for most scenarios. Results of several alternative scenarios were similar to baseline results, except for the scenario with greatly reduced residue concentrations through hypothetical wood sealant applications; in this scenario, exposures were lower, and the soil ingestion route dominated. SHEDS-Wood estimates are typically consistent with, or within the range of, other CCA exposure models.

A Probabilistic Arsenic Exposure Assessment for Children Who Contact Chromated Copper Arsenate (CCA)‐Treated Playsets and Decks, Part 2: Sensitivity and Uncertainty Analyses

A probabilistic model (SHEDS-Wood) was developed to examine childrens exposure and dose to chromated copper arsenate (CCA)-treated wood, as described in Part 1 of this two-part article. This Part 2 article discusses sensitivity and uncertainty analyses conducted to assess the key model inputs and areas of needed research for childrens exposure to CCA-treated playsets and decks. The following types of analyses were conducted: (1) sensitivity analyses using a percentile scaling approach and multiple stepwise regression; and (2) uncertainty analyses using the bootstrap and two-stage Monte Carlo techniques. The five most important variables, based on both sensitivity and uncertainty analyses, were: wood surface residue-to-skin transfer efficiency; wood surface residue levels; fraction of hand surface area mouthed per mouthing event; average fraction of nonresidential outdoor time a child plays on/around CCA-treated public playsets; and frequency of hand washing. In general, there was a factor of 8 for the 5th and 95th percentiles and a factor of 4 for the 50th percentile in the uncertainty of predicted population dose estimates due to parameter uncertainty. Data were available for most of the key model inputs identified with sensitivity and uncertainty analyses; however, there were few or no data for some key inputs. To evaluate and improve the accuracy of model results, future measurement studies should obtain longitudinal time-activity diary information on children, spatial and temporal measurements of residue and soil concentrations on or near CCA-treated playsets and decks, and key exposure factors. Future studies should also address other sources of uncertainty in addition to parameter uncertainty, such as scenario and model uncertainty.

Spatial analysis and land use regression of VOCs and NO2 from school-based urban air monitoring in Detroit/Dearborn, USA

Passive ambient air sampling for nitrogen dioxide (NO(2)) and volatile organic compounds (VOCs) was conducted at 25 school and two compliance sites in Detroit and Dearborn, Michigan, USA during the summer of 2005. Geographic Information System (GIS) data were calculated at each of 116 schools. The 25 selected schools were monitored to assess and model intra-urban gradients of air pollutants to evaluate impact of traffic and urban emissions on pollutant levels. Schools were chosen to be statistically representative of urban land use variables such as distance to major roadways, traffic intensity around the schools, distance to nearest point sources, population density, and distance to nearest border crossing. Two approaches were used to investigate spatial variability. First, Kruskal-Wallis analyses and pairwise comparisons on data from the schools examined coarse spatial differences based on city section and distance from heavily trafficked roads. Secondly, spatial variation on a finer scale and as a response to multiple factors was evaluated through land use regression (LUR) models via multiple linear regression. For weeklong exposures, VOCs did not exhibit spatial variability by city section or distance from major roads; NO(2) was significantly elevated in a section dominated by traffic and industrial influence versus a residential section. Somewhat in contrast to coarse spatial analyses, LUR results revealed spatial gradients in NO(2) and selected VOCs across the area. The process used to select spatially representative sites for air sampling and the results of coarse and fine spatial variability of air pollutants provide insights that may guide future air quality studies in assessing intra-urban gradients.

A review of air exchange rate models for air pollution exposure assessments.

A critical aspect of air pollution exposure assessments is estimation of the air exchange rate (AER) for various buildings where people spend their time. The AER, which is the rate of exchange of indoor air with outdoor air, is an important determinant for entry of outdoor air pollutants and for removal of indoor-emitted air pollutants. This paper presents an overview and critical analysis of the scientific literature on empirical and physically based AER models for residential and commercial buildings; the models highlighted here are feasible for exposure assessments as extensive inputs are not required. Models are included for the three types of airflows that can occur across building envelopes: leakage, natural ventilation, and mechanical ventilation. Guidance is provided to select the preferable AER model based on available data, desired temporal resolution, types of airflows, and types of buildings included in the exposure assessment. For exposure assessments with some limited building leakage or AER measurements, strategies are described to reduce AER model uncertainty. This review will facilitate the selection of AER models in support of air pollution exposure assessments.

Association of Roadway Proximity with Fasting Plasma Glucose and Metabolic Risk Factors for Cardiovascular Disease in a Cross-Sectional Study of Cardiac Catheterization Patients

Background The relationship between traffic-related air pollution (TRAP) and risk factors for cardiovascular disease needs to be better understood in order to address the adverse impact of air pollution on human health. Objective We examined associations between roadway proximity and traffic exposure zones, as markers of TRAP exposure, and metabolic biomarkers for cardiovascular disease risk in a cohort of patients undergoing cardiac catheterization. Methods We performed a cross-sectional study of 2,124 individuals residing in North Carolina (USA). Roadway proximity was assessed via distance to primary and secondary roadways, and we used residence in traffic exposure zones (TEZs) as a proxy for TRAP. Two categories of metabolic outcomes were studied: measures associated with glucose control, and measures associated with lipid metabolism. Statistical models were adjusted for race, sex, smoking, body mass index, and socioeconomic status (SES). Results An interquartile-range (990 m) decrease in distance to roadways was associated with higher fasting plasma glucose (β = 2.17 mg/dL; 95% CI: –0.24, 4.59), and the association appeared to be limited to women (β = 5.16 mg/dL; 95% CI: 1.48, 8.84 compared with β = 0.14 mg/dL; 95% CI: –3.04, 3.33 in men). Residence in TEZ 5 (high-speed traffic) and TEZ 6 (stop-and-go traffic), the two traffic zones assumed to have the highest levels of TRAP, was positively associated with high-density lipoprotein cholesterol (HDL-C; β = 8.36; 95% CI: –0.15, 16.9 and β = 5.98; 95% CI: –3.96, 15.9, for TEZ 5 and 6, respectively). Conclusion Proxy measures of TRAP exposure were associated with intermediate metabolic traits associated with cardiovascular disease, including fasting plasma glucose and possibly HDL-C. Citation Ward-Caviness CK, Kraus WE, Blach C, Haynes CS, Dowdy E, Miranda ML, Devlin RB, Diaz-Sanchez D, Cascio WE, Mukerjee S, Stallings C, Smith LA, Gregory SG, Shah SH, Hauser ER, Neas LM. 2015. Association of roadway proximity with fasting plasma glucose and metabolic risk factors for cardiovascular disease in a cross-sectional study of cardiac catheterization patients. Environ Health Perspect 123:1007–1014; http://dx.doi.org/10.1289/ehp.1306980

Volatile organic compounds at two oil and natural gas production well pads in Colorado and Texas using passive samplers.

ABSTRACT A pilot study was conducted in application of the U.S. Environmental Protection Agency (EPA) Methods 325A/B variant for monitoring volatile organic compounds (VOCs) near two oil and natural gas (ONG) production well pads in the Texas Barnett Shale formation and Colorado Denver–Julesburg Basin (DJB), along with a traffic-dominated site in downtown Denver, CO. As indicated in the EPA method, VOC concentrations were measured for 14-day sampling periods using passive-diffusive tube samplers with Carbopack X sorbent at fenceline perimeter and other locations. VOCs were significantly higher at the DJB well pad versus the Barnett well pad and were likely due to higher production levels at the DJB well pad during the study. Benzene and toluene were significantly higher at the DJB well pad versus downtown Denver. Except for perchloroethylene, VOCs measured at passive sampler locations (PSs) along the perimeter of the Barnett well pad were significantly higher than PSs farther away. At the DJB well pad, most VOC concentrations, except perchloroethylene, were significantly higher prior to operational changes than after these changes were made. Though limited, the results suggest passive samplers are precise (duplicate precision usually ≤10%) and that they can be useful to assess spatial gradients and operational conditions at well pad locations over time-integrated periods. Implications: Recently enacted EPA Methods 325A/B use passive-diffusive tube samplers to measure benzene at multiple fenceline locations at petrochemical refineries. This pilot study presents initial data demonstrating the utility of Methods 325A/B for monitoring at ONG facilities. Measurements revealed elevated concentrations reflective of production levels and spatial gradients of VOCs relative to source proximity at the Barnett well pad, as well as operational changes at the DJB well pad. Though limited, these findings indicate that Methods 325A/B can be useful in application to characterize VOCs at well pad boundaries.

Post-Hurricane Katrina passive sampling of ambient volatile organic compounds in the greater New Orleans area

On August 29, 2005, Hurricane Katrina made landfall near New Orleans, Louisiana, a major metroplex with petroleum industries. In response to the potential impact of the storm on air quality and to assess the exposures to toxic air pollutants of public health concern, the United States Environmental Protection Agency conducted passive monitoring of air toxics for three months, starting in late October 2005 through early February 2006, at up to 18 sites in the New Orleans area affected by Hurricane Katrina. The overall results of the passive ambient monitoring are summarized with the concentrations for the twenty-nine observed volatile organic chemicals, which include benzene, toluene, ethylbenzene, and xylenes, and the measured concentrations are compared with available health-based screening levels. The results of passive monitoring are also compared with those of the collocated canister sampling at one of the sites. The overall results showed that the outdoor levels of atmospheric volatile organic chemcals in the post-Katrina New Orleans area were very low and far below the available screening levels. The results also confirm the effectiveness of passive monitoring in a large geographical area where conventional methods are not feasible, electrical power is not available, and the need for sampling is urgent, as in the aftermath of natural disasters and other catastrophes.

Spatial analysis of volatile organic compounds in South Philadelphia using passive samplers.

ABSTRACT Select volatile organic compounds (VOCs) were measured in the vicinity of a petroleum refinery and related operations in South Philadelphia, Pennsylvania, USA, using passive air sampling and laboratory analysis methods. Two-week, time-integrated samplers were deployed at 17 sites, which were aggregated into five site groups of varying distances from the refinery. Benzene, toluene, ethylbenzene, and xylene isomers (BTEX) and styrene concentrations were higher near the refinery’s fenceline than for groups at the refinery’s south edge, mid-distance, and farther removed locations. The near fenceline group was significantly higher than the refinery’s north edge group for benzene and toluene but not for ethylbenzene or xylene isomers; styrene was lower at the near fenceline group versus the north edge group. For BTEX and styrene, the magnitude of estimated differences generally increased when proceeding through groups ever farther away from the petroleum refining. Perchloroethylene results were not suggestive of an influence from refining. These results suggest that emissions from the refinery complex contribute to higher concentrations of BTEX species and styrene in the vicinity of the plant, with this influence declining as distance from the petroleum refining increases. Implications: Passive sampling methodology for VOCs as discussed here is employed in recently enacted U.S. Environmental Protection Agency Methods 325A/B for determination of benzene concentrations at refinery fenceline locations. Spatial gradients of VOC concentration near the refinery fenceline were discerned in an area containing traffic and other VOC-related sources. Though limited, these findings can be useful in application of the method at such facilities to ascertain source influence.

Associations Between Residential Proximity to Traffic and Vascular Disease in a Cardiac Catheterization Cohort

Objective— Exposure to mobile source emissions is nearly ubiquitous in developed nations and is associated with multiple adverse health outcomes. There is an ongoing need to understand the specificity of traffic exposure associations with vascular outcomes, particularly in individuals with cardiovascular disease. Approach and Results— We performed a cross-sectional study using 2124 individuals residing in North Carolina, United States, who received a cardiac catheterization at the Duke University Medical Center. Traffic-related exposure was assessed via 2 metrics: (1) the distance between the primary residence and the nearest major roadway; and (2) location of the primary residence in regions defined based on local traffic patterns. We examined 4 cardiovascular disease outcomes: hypertension, peripheral arterial disease, the number of diseased coronary vessels, and recent myocardial infarction. Statistical models were adjusted for race, sex, smoking, type 2 diabetes mellitus, body mass index, hyperlipidemia, and home value. Results are expressed in terms of the odds ratio (OR). A 23% decrease in residential distance to major roadways was associated with higher prevalence of peripheral arterial disease (OR=1.29; 95% confidence interval, 1.08–1.55) and hypertension (OR=1.15; 95% confidence interval, 1.01–1.31). Associations with peripheral arterial disease were strongest in men (OR=1.42; 95% confidence interval, 1.17–1.74) while associations with hypertension were strongest in women (OR=1.21; 95% confidence interval, 0.99–1.49). Neither myocardial infarction nor the number of diseased coronary vessels were associated with traffic exposure. Conclusions— Traffic-related exposure is associated with peripheral arterial disease and hypertension while no associations are observed for 2 coronary-specific vascular outcomes.

Probabilistic estimation of residential air exchange rates for population-based human exposure modeling.

Residential air exchange rates (AERs) are a key determinant in the infiltration of ambient air pollution indoors. Population-based human exposure models using probabilistic approaches to estimate personal exposure to air pollutants have relied on input distributions from AER measurements. An algorithm for probabilistically estimating AER was developed based on the Lawrence Berkley National Laboratory Infiltration model utilizing housing characteristics and meteorological data with adjustment for window opening behavior. The algorithm was evaluated by comparing modeled and measured AERs in four US cities (Los Angeles, CA; Detroit, MI; Elizabeth, NJ; and Houston, TX) inputting study-specific data. The impact on the modeled AER of using publically available housing data representative of the region for each city was also assessed. Finally, modeled AER based on region-specific inputs was compared with those estimated using literature-based distributions. While modeled AERs were similar in magnitude to the measured AER they were consistently lower for all cities except Houston. AERs estimated using region-specific inputs were lower than those using study-specific inputs due to differences in window opening probabilities. The algorithm produced more spatially and temporally variable AERs compared with literature-based distributions reflecting within- and between-city differences, helping reduce error in estimates of air pollutant exposure.