EPA National Research Articles

Evaluation of a regional air-quality model with bidirectional NH<sub>3</sub> exchange coupled to an agroecosystem model

Abstract. Atmospheric ammonia (NH3) is the primary atmospheric base and an important precursor for inorganic particulate matter and when deposited NH3 contributes to surface water eutrophication, soil acidification and decline in species biodiversity. Flux measurements indicate that the air–surface exchange of NH3 is bidirectional. However, the effects of bidirectional exchange, soil biogeochemistry and human activity are not parameterized in air quality models. The US Environmental Protection Agency's (EPA) Community Multiscale Air-Quality (CMAQ) model with bidirectional NH3 exchange has been coupled with the United States Department of Agriculture's (USDA) Environmental Policy Integrated Climate (EPIC) agroecosystem model. The coupled CMAQ-EPIC model relies on EPIC fertilization timing, rate and composition while CMAQ models the soil ammonium (NH4+) pool by conserving the ammonium mass due to fertilization, evasion, deposition, and nitrification processes. This mechanistically coupled modeling system reduced the biases and error in NHx (NH3 + NH4+) wet deposition and in ambient aerosol concentrations in an annual 2002 Continental US (CONUS) domain simulation when compared to a 2002 annual simulation of CMAQ without bidirectional exchange. Fertilizer emissions estimated in CMAQ 5.0 with bidirectional exchange exhibits markedly different seasonal dynamics than the US EPA's National Emissions Inventory (NEI), with lower emissions in the spring and fall and higher emissions in July.

Developmental programming: Impact of prenatal exposure to bisphenol-A and methoxychlor on steroid feedbacks in sheep

Bisphenol-A (BPA), a polymer used in plastics manufacturing, and methoxychlor (MXC), a pesticide, are endocrine disrupting compounds with estrogenic and anti-androgenic properties. Prenatal BPA or MXC treatment induces reproductive defects in sheep with BPA causing prepubertal luteinizing hormone (LH) hypersecretion and dampening of periovulatory LH surges and MXC lengthening follicular phase and delaying the LH surge. In this study, we addressed the underlying neuroendocrine defects by testing the following hypotheses: 1) prenatal BPA, but not MXC reduces sensitivity to estradiol and progesterone negative feedback, 2) prenatal BPA, but not MXC increases pituitary responsiveness to gonadotropin releasing hormone (GnRH), and 3) prenatal BPA dampens LH surge response to estradiol positive feedback challenge while prenatal MXC delays the timing of the LH surge. Pregnant sheep were treated with either 1) 5mg/kg/day BPA (produces approximately twice the level found in human circulation, n=8), 2) 5mg/kg/day MXC (the lowest observed effect level stated in the EPA National Toxicology Program's Report; n=6), or 3) vehicle (cotton seed oil: C: n=6) from days 30 to 90 of gestation. Female offspring of these ewes were ovariectomized at 21months of age and tested for progesterone negative, estradiol negative, estradiol positive feedback sensitivities and pituitary responsiveness to GnRH. Results revealed that sensitivity to all 3 feedbacks as well as pituitary responsiveness to GnRH were not altered by either of the prenatal treatments. These findings suggest that the postpubertal reproductive defects seen in these animals may have stemmed from ovarian defects and the steroidal signals emanating from them.

Flue gas desulphurisation in Serbia: Technologies, legal and economic aspects

Combustion of coal results in sulfur dioxide (SO2) emissions which cause detrimental impacts on the environment and human health. Electric power generating units account for the majority of SO2 emissions in Serbia. Environmental regulations in Serbia require gradual implementation of flue gas treatment technologies for control the emissions of pollutants into the atmosphere. As far as Serbian thermal power plants are concerned, the basic design of systems for flue gas desulphurisation has been developed for two thermal power plants. As wet limestone-based FGD technologies dominate in the world because of high SO2 removal efficiency, cost effectiveness, and gypsum as the by-product, it is expected that Serbian thermal power plants will use this technology. This paper presents a review of commercially available FGD technologies, as well as legal and economic perspective of the process. U.S. EPA's National Risk Management Research Laboratory has published the Coal Utility Environmental Cost Workbook which provides the rough-order-of-magnitude budgetary cost estimates as the starting point for the limestone forced oxidation cost model that might be a good starting point for cost estimates for Serbian electric utilities.

Do US Ambient Air Lead Levels Have a Significant Impact on Childhood Blood Lead Levels: Results of a National Study

Introduction. Although lead paint and leaded gasoline have not been used in the US for thirty years, thousands of US children continue to have blood lead levels (BLLs) of concern. Methods. We investigated the potential association of modeled air lead levels and BLLs ≥ 10 μg/dL using a large CDC database with BLLs on children aged 0–3 years. Percent of children with BLLs ≥ 10 μg/dL (2000–2007) by county and proportion of pre-50 housing and SES variables were merged with the US EPA's National Air Toxics Assessment (NATA) modeled air lead data. Results. The proportion with BLL ≥ 10 μg/dL was 1.24% in the highest air lead counties, and the proportion with BLL ≥ 10 μg/dL was 0.36% in the lowest air lead counties, resulting in a crude prevalence ratio of 3.4. Further analysis using multivariate negative binomial regression revealed that NATA lead was a significant predictor of % BLL ≥ 10 μg/dL after controlling for percent pre-l950 housing, percent rural, and percent black. A geospatial regression revealed that air lead, percent older housing, and poverty were all significant predictors of % BLL ≥ 10 μg/dL. Conclusions. More emphasis should be given to potential sources of ambient air lead near residential areas.

EPA's National Nutrient Strategy – Fifteen Years Later

EPA's National Nutrient Strategy – Fifteen Years Later

Development of EPA Method 525.3 for the analysis of semivolatiles in drinking water

The United States Environmental Protection Agency's (EPA) Office of Ground Water and Drinking Water (OGWDW) collects nationwide occurrence data on contaminants in drinking water using the Unregulated Contaminant Monitoring Regulations (UCMRs). The unregulated contaminants, which are potential candidates for future regulation, may be selected from the Drinking Water Contaminant Candidate List (CCL), or may be emerging contaminants, with the potential for inclusion on future CCLs. In October 2009, OGWDW published the third Drinking Water CCL (CCL 3). Not all of the chemicals on CCL 3 are included in existing analytical methods with sufficient sensitivity and specificity for UCMR monitoring. Some of the chemicals that require method development research fall into the category known as semi-volatile organic chemicals (SVOCs). Currently, EPA Method 525.2 is used to measure SVOCs for both drinking water compliance and UCMR monitoring. The method utilizes C-18 solid-phase extraction (SPE) for contaminant isolation and concentration, followed by full scan gas chromatography-mass spectrometry (GC-MS) detection. A group of 27 contaminants from CCL 3, a list of chemicals from EPA's National Homeland Security Research Center (NHSRC), as well as other emerging compounds of interest, were evaluated for inclusion into a new revision of the method, EPA Method 525.3. Method improvements include: (1) utilizing a polymeric-based SPE sorbent for greater retention across sample pH range, (2) enhanced method sensitivity using GC-MS with selected ion monitoring (SIM), (3) safer and more user-friendly sample preservatives, and (4) sample preparation techniques that help overcome matrix-induced chromatographic response enhancement. To be used for nationwide monitoring, the new method must be rugged across a range of drinking water sources, sensitive and highly specific to minimize false positives. It must also be cost effective and simple enough for commercial lab settings. Accuracy and precision data using full scan GC-MS mode are presented for 125 contaminants. Multi-laboratory data obtained in selected ion mode (SIM) are presented for a subset of priority analytes. Lowest Concentration Minimum Reporting Limits (LCMRLs) of priority analytes obtained from four separate laboratories ranged from 0.0006 to 0.28 μg L−1, with an average LCMRL of 0.035 μg L−1 and median LCMRL of 0.011 μg L−1, under SIM conditions.

Developing a robust geochemical and reactive transport model to evaluate possible sources of arsenic at the CO2 sequestration natural analog site in Chimayo, New Mexico

Migration of carbon dioxide (CO2) from deep storage formations into shallow drinking water aquifers is a possible system failure related to geologic CO2 sequestration. A CO2 leak may cause mineral precipitation/dissolution reactions, changes in aqueous speciation, and alteration of pH and redox conditions leading to potential increases of trace metal concentrations above EPA National Primary Drinking Water Standards. In this study, the Chimayo site (NM) was examined for site-specific impacts of shallow groundwater interacting with CO2 from deep storage formations. Major ion and trace element chemistry for the site have been previously studied. This work focuses on arsenic (As), which is regulated by the EPA under the Safe Drinking Water Act and for which some wells in the Chimayo area have concentrations higher than the maximum contaminant level (MCL). Statistical analysis of the existing Chimayo groundwater data indicates that As is strongly correlated with trace metals U and Pb indicating that their source may be from the same deep subsurface water. Batch experiments and materials characterization, such as: X-ray diffraction (XRD), scanning electron microscopy (SEM), and synchrotron micro X-ray fluorescence (μ-XRF), were used to identify As association with Fe-rich phases, such as clays or oxides, in the Chimayo sediments as the major factor controlling As fate in the subsurface. Batch laboratory experiments with Chimayo sediments and groundwater show that pH decreases as CO2 is introduced into the system and buffered by calcite. The introduction of CO2 causes an immediate increase in As solution concentration, which then decreases over time. A geochemical model was developed to simulate these batch experiments and successfully predicted the pH drop once CO2 was introduced into the experiment. In the model, sorption of As to illite, kaolinite and smectite through surface complexation proved to be the key reactions in simulating the drop in As concentration as a function of time in the batch experiments. Based on modeling, kaolinite precipitation is anticipated to occur during the experiment, which allows for additional sorption sites to form with time resulting in the slow decrease in As concentration. This mechanism can be viewed as trace metal “scavenging” due to sorption caused secondary mineral precipitation. Since deep geologic transport of these trace metals to the shallow subsurface by brine or CO2 intrusion is critical to assessing environmental impacts, the effective retardation of trace metal transport is an important parameter to estimate and it is dependent on multiple coupled reactions. At the field scale, As mobility is retarded due to the influence of sorption reactions, which can affect environmental performance assessment studies of a sequestration site.

Nested-grid simulation of mercury over North America

Abstract. We have developed a new nested-grid mercury (Hg) simulation over North America with a 1/2° latitude by 2/3° longitude horizontal resolution employing the GEOS-Chem global chemical transport model. Emissions, chemistry, deposition, and meteorology are self-consistent between the global and nested domains. Compared to the global model (4° latitude by 5° longitude), the nested model shows improved skill at capturing the high spatial and temporal variability of Hg wet deposition over North America observed by the Mercury Deposition Network (MDN) in 2008–2009. The nested simulation resolves features such as higher deposition due to orographic precipitation, land/ocean contrast and and predicts more efficient convective rain scavenging of Hg over the southeast United States. However, the nested model overestimates Hg wet deposition over the Ohio River Valley region (ORV) by 27%. We modify anthropogenic emission speciation profiles in the US EPA National Emission Inventory (NEI) to account for the rapid in-plume reduction of reactive to elemental Hg (IPR simulation). This leads to a decrease in the model bias to −2.3% over the ORV region. Over the contiguous US, the correlation coefficient (r) between MDN observations and our IPR simulation increases from 0.60 to 0.78. The IPR nested simulation generally reproduces the seasonal cycle in surface concentrations of speciated Hg from the Atmospheric Mercury Network (AMNet) and Canadian Atmospheric Mercury Network (CAMNet). In the IPR simulation, annual mean gaseous and particulate-bound Hg(II) are within 140% and 11% of observations, respectively. In contrast, the simulation with unmodified anthropogenic Hg speciation profiles overestimates these observations by factors of 4 and 2 for gaseous and particulate-bound Hg(II), respectively. The nested model shows improved skill at capturing the horizontal variability of Hg observed over California during the ARCTAS aircraft campaign. The nested model suggests that North American anthropogenic emissions account for 10–22% of Hg wet deposition flux over the US, depending on the anthropogenic emissions speciation profile assumed. The modeled percent contribution can be as high as 60% near large point sources in ORV. Our results indicate that the North American anthropogenic contribution to dry deposition is 13–20%.

Microbial enzyme stoichiometry and nutrient limitation in US streams and rivers

We analyzed water and sediment chemistry, catchment land cover, and microbial dehydrogenase (DHA) and extracellular enzymes activities (EEA) related to microbial C, N, P, and S acquisition in more than 2100 1st–10th order streams. The streams and their catchments represented gradients in water and sediment chemistry (C, N, P, S) and land cover (% forest, % wetland, % row crop agriculture) against which to compare biofilm and sediment DHA and EEA, and to estimate the extent of nutrient limitation in US streams and rivers. Water chemistry was significantly correlated with catchment land cover. Biofilm and sediment DHA and EEA were inversely correlated with water and sediment chemistry, and positively correlated with % forest. Canonical correlation analysis described two environmental gradients to which biofilm and sediment DHA and EEA were significantly correlated. Structural equation modeling (SEM) revealed a significant causal relationship between catchment land cover, chemistry, and biofilm and sediment EEA and DHA. Biofilm and sediment EEA was dominated by phenol oxidase and peroxidase, enzymes related to the degradation of recalcitrant C. However, the hydrolytic enzymes (those which hydrolyze glycoside, peptide, and ester bonds to release C, N, P, S) were better correlated with the chemical variables. This was reflected in the relative apportionment of enzyme activity toward C, N, P, and S acquisition. We compared molar stoichiometry of C, N, and P in water and sediment with biofilm and sediment ratios of GLYC:PEPT:PHOS to gauge how each measure of nutrient limitation compares with the others. Overall, water chemistry suggested many biofilms were P-limited and this was corroborated by allocation of microbial phosphatase activity. Sediments were found to be predominantly C and N-limited, and this was reflected in sediment EEA. We used these measures of nutrient limitation to assess the extent of N or P-limitation in streams and rivers of the conterminous United States and for nine ecoregions of interest to the US EPA's National Rivers and Streams Assessment (NRSA). Enzymatic stoichiometry provides a biological perspective on the influence of catchment scale anthropogenic disturbances resulting in an imbalance of nutrients being transported from those catchments. Enzyme activities represent the interface between microbial demands for, and environmental supplies of, C, N, and P, effectively linking ecological stoichiometric theory with the concept of threshold elemental ratios. The relative activities of the functional classes of extracellular enzymes provide both a measure of nutrient availability and ecosystem metabolism that may be used to assess large-scale phenomena such as regional impacts of climate change or anthropogenic disturbances.

Predicting Maximum Lake Depth from Surrounding Topography

Information about lake morphometry (e.g., depth, volume, size, etc.) aids understanding of the physical and ecological dynamics of lakes, yet is often not readily available. The data needed to calculate measures of lake morphometry, particularly lake depth, are usually collected on a lake-by-lake basis and are difficult to obtain across broad regions. To span the gap between studies of individual lakes where detailed data exist and regional studies where access to useful data on lake depth is unavailable, we developed a method to predict maximum lake depth from the slope of the topography surrounding a lake. We use the National Elevation Dataset and the National Hydrography Dataset – Plus to estimate the percent slope of surrounding lakes and use this information to predict maximum lake depth. We also use field measured maximum lake depths from the US EPA's National Lakes Assessment to empirically adjust and cross-validate our predictions. We were able to predict maximum depth for ∼28,000 lakes in the Northeastern United States with an average cross-validated RMSE of 5.95 m and 5.09 m and average correlation of 0.82 and 0.69 for Hydrological Unit Code Regions 01 and 02, respectively. The depth predictions and the scripts are openly available as supplements to this manuscript.

PM2.5 source profiles for black and organic carbon emission inventories

Emission inventories for black or elemental (BC or EC) and organic (OC) carbon can be derived by multiplying PM2.5 emission estimates by mass fractions of these species in representative source profiles. This study examines the variability of source profiles and its effect on EC emission estimates. An examination of available profiles shows that EC and OC ranged from 6e13% and 35e40% for agricultural burning, 4e33% and 22e68% for residential wood combustion, 6e38% and 24e75% for on-road gasoline vehicles, and 33e74% and 20e47% for on-road heavy-duty diesel vehicles, respectively. Source profiles from the U.S. EPA SPECIATE data base were applied to PM2.5 emissions from the U.S. EPA National Emissions Inventory for 2005. The total estimated EC emissions of 432 Gg yr � 1 was apportioned as 42.5% from biomass burning, 35.4% from non-road mobile sources,15% from on-road mobile sources, 5.4% from fossil fuel (e.g., coal, oil, and natural gas) combustion in stationary sources, 1% from other stationary industrial sources, and 0.5% from fugitive dust. Considering the variability in available source profiles, BC emission estimates for major sources such as open fires and non-road diesels ranged from 42 to 133 (a factor of 3) and 25 to 100 (a factor of 4) Gg yr �1 , respectively. The choice of source profiles can be

Kriged and modeled ambient air levels of benzene in an urban environment: an exposure assessment study

BackgroundThere is increasing concern regarding the potential adverse health effects of air pollution, particularly hazardous air pollutants (HAPs). However, quantifying exposure to these pollutants is problematic.ObjectiveOur goal was to explore the utility of kriging, a spatial interpolation method, for exposure assessment in epidemiologic studies of HAPs. We used benzene as an example and compared census tract-level kriged predictions to estimates obtained from the 1999 U.S. EPA National Air Toxics Assessment (NATA), Assessment System for Population Exposure Nationwide (ASPEN) model.MethodsKriged predictions were generated for 649 census tracts in Harris County, Texas using estimates of annual benzene air concentrations from 17 monitoring sites operating in Harris and surrounding counties from 1998 to 2000. Year 1999 ASPEN modeled estimates were also obtained for each census tract. Spearman rank correlation analyses were performed on the modeled and kriged benzene levels. Weighted kappa statistics were computed to assess agreement between discretized kriged and modeled estimates of ambient air levels of benzene.ResultsThere was modest correlation between the predicted and modeled values across census tracts. Overall, 56.2%, 40.7%, 31.5% and 28.2% of census tracts were classified as having 'low', 'medium-low', 'medium-high' and 'high' ambient air levels of benzene, respectively, comparing predicted and modeled benzene levels. The weighted kappa statistic was 0.26 (95% confidence interval (CI) = 0.20, 0.31), indicating poor agreement between the two methods.ConclusionsThere was a lack of concordance between predicted and modeled ambient air levels of benzene. Applying methods of spatial interpolation for assessing exposure to ambient air pollutants in health effect studies is hindered by the placement and number of existing stationary monitors collecting HAP data. Routine monitoring needs to be expanded if we are to use these data to better assess environmental health risks in the future.

Simulating Particle Size Distributions over California and Impact on Lung Deposition Fraction

Reliable simulations of particle mass size distributions by regional photochemical air quality models are needed in regulatory applications because the U.S. EPA's National Ambient Air Quality Standards specify limits on the mass concentration of particles in a specific size range (i.e., aerodynamic diameter <2.5 μm). Considering the associations between adverse health effects and exposure to ultrafine particles, air quality models may need to accurately simulate particle number size distributions in addition to mass size distributions in future applications. In this study, predictions of particle number and mass size distributions by the Community Multiscale Air Quality model with the standard and an updated emission size distribution are evaluated using wintertime observations in California. Differences in modeled lung deposition fraction for simulated and observed particle number size distributions are also evaluated. Simulated mass size distributions are generally broader and shifted to larger diameter...

Characterization of Valley Winter Woodsmoke Concentrations in Northern NY Using Highly Time-Resolved Measurements

The increasing popularity of wood fired heating appliances in cold winter climates has focused attention on assessment of woodsmoke exposures. Pollution from residential wood combustion (RWC) is a major concern in areas with valley topography where nighttime inversions limit the dispersion of pollutants from ground-level sources. An intensive characterization of ambient particulate mater (PM) from RWC was performed in northern New York State during winter 2008-2009 in an area where the 2005 U.S. EPA National Emissions Inventory shows RWC to be the largest source of PM2.5. Measurements of woodsmoke PM were made using optical scattering and absorption techniques during repeated night-time mobile monitoring to provide data with high spatial and temporal resolution; measurements were also made at six fixed sites for the study period to provide temporal context for the mobile measurements. The difference in optical absorption at near-infrared and near-ultraviolet wavelengths was used as a specific marker for woodsmoke PM. Woodsmoke was the only significant contributor to elevated night-time valley PM concentrations during mobile run nights; short-term (3 minute) PM concentrations frequently exceeded 100 μg/m^3. Concentrations observed with mobile monitoring were consistently elevated at valley bottoms where the majority of the population lives, and approached zero outside of valleys. Data from fixed sites indicated that woodsmoke levels peaked near midnight, with a secondary peak around 7 AM and a mid-day minimum. These patterns are consistent with RWC use and diurnal patterns of atmospheric dispersion.

Do brain cancer rates correlate with ambient exposure levels of criteria air pollutants or hazardous air pollutants (HAPs)?

Age-adjusted brain cancer rates vary more than fourfold among US counties, but risk factors underlying this variation have not been identified. The only known risk factor for brain cancer is ionizing radiation at therapeutic dose levels. Lifestyle factors are not known to affect brain cancer risk; hypothetical risks from environmental or occupational exposures to numerous chemicals have been suggested, but no consistent results have emerged in populations exposed to chemicals via oral intake or inhalation. We investigated whether county-by-county brain cancer incidence rates and mortality rates were correlated with patterns of local ambient air pollution. We utilized central-site ambient measurement data for criteria air pollutants, and inhalation exposure concentrations of hazardous air pollutants (HAPs) as predicted by the US EPA National Air Toxics Assessment. We selected 30 HAPs that had been variously hypothesized in the context of a link to brain cancer risk. We also included a regression on density of domestic cattle populations given that viruses have been implicated in brain cancer and cattle are a well-known reservoir for a variety of viruses. The analyses yielded correlations that were mostly null or negative, with similar results obtained for brain cancer incidence and mortality rates. The cattle density correlations were slightly positive and statistically significant. Given the limitations of this exploratory analysis, further research is needed to investigate the role of environmental chemical exposures in brain cancer risk. Our findings suggest that county-by-county differences in air pollution exposure concentrations are not likely to be explanatory factors for variations in brain cancer rates.

Multi-year (2004–2008) record of nonmethane hydrocarbons and halocarbons in New England: seasonal variations and regional sources

Abstract. Multi-year time series records of C2-C6 alkanes, C2-C4 alkenes, ethyne, isoprene, C6-C8 aromatics, trichloroethene (C2HCl3), and tetrachloroethene (C2Cl4) from canister samples collected during January 2004–February 2008 at the University of New Hampshire (UNH) AIRMAP Observatory at Thompson Farm (TF) in Durham, NH are presented. The objectives of this work are to identify the sources of nonmethane hydrocarbons (NMHCs) and halocarbons observed at TF, characterize the seasonal and interannual variability in ambient mixing ratios and sources, and estimate regional emission rates of NMHCs. Analysis of correlations and comparisons with emission ratios indicated that a ubiquitous and persistent mix of emissions from several anthropogenic sources is observed throughout the entire year. The highest C2-C8 anthropogenic NMHC mixing ratios were observed in mid to late winter. Following the springtime minimums, the C3-C6 alkanes, C7-C8 aromatics, and C2HCl3 increased in early to mid summer, presumably reflecting enhanced evaporative emissions. Mixing ratios of C2Cl4 and C2HCl3 decreased by 0.7±0.2 and 0.3±0.05 pptv/year, respectively, which is indicative of reduced usage and emissions of these halogenated solvents. Emission rates of C3-C8 NMHCs were estimated to be 109 to 1010 molecules cm−2 s−1 in winter 2006. The emission rates extrapolated to the state of New Hampshire and New England were ~2–60 Mg/day and ~12–430 Mg/day, respectively. Emission rates of benzene, toluene, ethylbenzene, xylenes, and ethyne in the 2002 and 2005 EPA National Emissions Inventories were within ±50% of the TF emission rates.

Differences in exposure assignment between conception and delivery: the impact of maternal mobility

In studies of reproductive outcomes, maternal residence at delivery is often the only information available to characterise environmental exposures during pregnancy. The goal of this investigation was to describe residential mobility during pregnancy and to assess the extent to which change of residence may result in exposure misclassification when exposure is based on the address at delivery. Maternal residential mobility was compared between neural tube defect cases and unaffected controls from Texas participants in the National Birth Defects Prevention Study (NBDPS). Maternal residential information was obtained from the NBDPS interview. Data from the U.S. EPA National Air Toxics Assessment [Assessment System for Population Exposure Nationwide (ASPEN)], modelled at the census tract level, were used to estimate benzene exposure based on address at conception and address at delivery. Quartiles of exposure were assigned based on these estimates and the quartile assignments based on address at conception and address at delivery were compared using traditional methods (kappa statistics) and a novel application of mixed-effects ordinal logistic regression. Overall, 30% of case mothers and 24% of control mothers moved during pregnancy. Differences in maternal residential mobility were not significant between cases and controls, other than case mothers who moved did so earlier during pregnancy than control mothers (P = 0.01). There was good agreement between quartiles of estimated benzene exposure at both addresses (kappa = 0.78, P < 0.0001). Based on the mixed-effects regression model, address at delivery was not significantly different from using address at conception when assigning quartile of benzene exposure based on estimates from ASPEN (odds ratio 1.03, 95% confidence interval 0.85, 1.25). Our results indicate that, in this Texas population, maternal residential movement is generally within short distances, is typically not different between cases and controls, and does not significantly influence benzene exposure assessment.

Field turbidity method for the determination of lead in acid extracts of dried paint

Lead, which can be found in old paint, soil, and dust, has been clearly shown to have adverse health effects on the neurological systems of both children and adults. As part of an ongoing effort to reduce childhood lead poisoning, the US Environmental Protection Agency promulgated the Lead Renovation, Repair, and Painting Program (RRP) rule requiring that paint in target housing built prior to 1978 be tested for lead before any renovation, repair, or painting activities are initiated. This rule has led to a need for a rapid, relatively easy, and an inexpensive method for measuring lead in paint. This paper presents a new method for measuring lead extracted from paint that is based on turbidimetry. This method is applicable to paint that has been collected from a surface and extracted into 25% (v/v) of nitric acid. An aliquot of the filtered extract is mixed with an aliquot of solid potassium molybdate in 1 M ammonium acetate to form a turbid suspension of lead molybdate. The lead concentration is determined using a portable turbidity meter. This turbidimetric method has a response of approximately 0.9 NTU per microg lead per mL extract, with a range of 1-1000 Nephelometric Turbidity Units (NTUs). Precision at a concentration corresponding to the EPA-mandated decision point of 1 mg of lead per cm(2) is <2%. This method is insensitive to the presence of other metals common to paint, including Ba(2+), Ca(2+), Mg(2+), Fe(3+), Co(2+), Cu(2+), and Cd(2+), at concentrations of 10 mg mL(-1) or to Zn(2+) at 50 mg mL(-1). Analysis of 14 samples from six reference materials with lead concentrations near 1 mg cm(-2) yielded a correlation to inductively coupled plasma-atomic emission spectroscopy (ICP-AES) analysis of 0.97, with an average bias of 2.8%. Twenty-four sets of either 6 or 10 paint samples each were collected from different locations in old houses, a hospital, tobacco factory, and power station. Half of each set was analyzed using rotor/stator-25% (v/v) nitric acid extraction with measurement using the new turbidimetric method, and the other half was analyzed using microwave extraction and measurement by ICP-AES. The average relative percent difference between the turbidimetric method and the ICP-AES method for the 24 sets measured as milligrams of lead per cm(2) is -0.63 +/- 32.5%; the mean difference is -2.1 +/- 7.0 mg lead per cm(2). Non-parametric and parametric statistical tests on these data showed no difference in the results for the two procedures. At the federal regulated level of 1 mg of lead per cm(2) paint, this turbidimetric method meets the performance requirements for EPA's National Lead Laboratory Accreditation Program (NLLAP) of accuracy within +/-20% and has the potential to meet the performance specifications of EPA's RRP rule.

Air Toxic Emissions from Snowmobiles in Yellowstone National Park

A study on emissions associated with oversnow travel in Yellowstone National Park (YNP) was conducted for the time period of February 13-16, 2002 and February 12-16, 2003. Whole air and exhaust samples were characterized for 85 volatile organic compounds using gas chromatography. The toxics including benzene, toluene, ethylbenzene, xylenes (p-, m-, and o-xylene), and n-hexane, which are major components of two-stroke engine exhaust, show large enhancements during sampling periods resulting from increased snowmobile traffic. Evaluation of the photochemical history of air masses sampled in YNP revealed that emissions of these air toxics were (i) recent, (ii) persistent throughout the region, and (iii) consistent with the two-stroke engine exhaust sample fingerprints. The annual fluxes were estimated to be 0.35, 1.12, 0.24, 1.45, and 0.36 Gg yr(-1) for benzene, toluene, ethylbenzene, xylenes, and n-hexane, respectively, from snowmobile usage in YNP. These results are comparable to the flux estimates of 0.23, 0.77, 0.17, and 0.70 Gg yr(-1) for benzene, toluene, ethylbenzene, and xylenes, respectively, that were derived on the basis of (i) actual snowmobile counts in the Park and (ii) our ambient measurements conducted in 2003. Extrapolating these results, annual emissions from snowmobiles in the U.S. appear to be significantly higher than the values from the EPA National Emissions Inventory (1999). Snowmobile emissions represent a significant fraction ( approximately 14-21%) of air toxics with respect to EPA estimates of emissions by nonroad vehicles. Further investigation is warranted to more rigorously quantify the difference between our estimates and emission inventories.

Annual Reports To Council Ecological Society of America August 2009

<i>Annual Reports To Council</i> Ecological Society of America August 2009