Barbara Jane George

Environmental influences on the seasonal distribution of Vibrio parahaemolyticus in the Pacific Northwest of the USA.

Populations of Vibrio parahaemolyticus in the environment can be influenced by numerous factors. We assessed the correlation of total (tl+) and potentially virulent (tdh+) V. parahaemolyticus in water with three harmful algal bloom (HAB) genera (Pseudo-nitzschia, Alexandrium and Dinophysis), the abundance of diatoms and dinoflagellates, chlorophyll-a and temperature, salinity and macronutrients at five sites in Washington State from 2008-2009. The variability in V. parahaemolyticus density was explained predominantly by strong seasonal trends where maximum densities occurred in June, 2 months prior to the highest seasonal water temperature. In spite of large geographic differences in temperature, salinity and nutrients, there was little evidence of corresponding differences in V. parahaemolyticus density. In addition, there was no evident relationship between V. parahaemolyticus and indices of HAB genera, perhaps due to a lack of significant HAB events during the sampling period. The only nutrient significantly associated with V. parahaemolyticus density after accounting for the seasonal trend was silicate. This negative relationship may be caused by a shift in cell wall structure for some diatom species to a chitinous substrate preferred by V. parahaemolyticus. Results from our study differ from those in other regions corroborating previous findings that environmental factors that trigger vibrio and HAB events may differ depending on geographic locations. Therefore caution should be used when applying results from one region to another.

Effects of Cold Temperature and Ethanol Content on VOC Emissions from Light-Duty Gasoline Vehicles

Emissions of speciated volatile organic compounds (VOCs), including mobile source air toxics (MSATs), were measured in vehicle exhaust from three light-duty spark ignition vehicles operating on summer and winter grade gasoline (E0) and ethanol blended (E10 and E85) fuels. Vehicle testing was conducted using a three-phase LA92 driving cycle in a temperature-controlled chassis dynamometer at two ambient temperatures (-7 and 24 °C). The cold start driving phase and cold ambient temperature increased VOC and MSAT emissions up to several orders of magnitude compared to emissions during other vehicle operation phases and warm ambient temperature testing, respectively. As a result, calculated ozone formation potentials (OFPs) were 7 to 21 times greater for the cold starts during cold temperature tests than comparable warm temperature tests. The use of E85 fuel generally led to substantial reductions in hydrocarbons and increases in oxygenates such as ethanol and acetaldehyde compared to E0 and E10 fuels. However, at the same ambient temperature, the VOC emissions from the E0 and E10 fuels and OFPs from all fuels were not significantly different. Cold temperature effects on cold start MSAT emissions varied by individual MSAT compound, but were consistent over a range of modern spark ignition vehicles.

Cold temperature and biodiesel fuel effects on speciated emissions of volatile organic compounds from diesel trucks.

Speciated volatile organic compounds (VOCs) were measured in diesel exhaust from three heavy-duty trucks equipped with modern aftertreatment technologies. Emissions testing was conducted on a chassis dynamometer at two ambient temperatures (-7 and 22 °C) operating on two fuels (ultra low sulfur diesel and 20% soy biodiesel blend) over three driving cycles: cold start, warm start and heavy-duty urban dynamometer driving cycle. VOCs were measured separately for each drive cycle. Carbonyls such as formaldehyde and acetaldehyde dominated VOC emissions, making up ∼ 72% of the sum of the speciated VOC emissions (∑VOCs) overall. Biodiesel use led to minor reductions in aromatics and variable changes in carbonyls. Cold temperature and cold start conditions caused dramatic enhancements in VOC emissions, mostly carbonyls, compared to the warmer temperature and other drive cycles, respectively. Different 2007+ aftertreatment technologies involving catalyst regeneration led to significant modifications of VOC emissions that were compound-specific and highly dependent on test conditions. A comparison of this work with emission rates from different diesel engines under various test conditions showed that these newer technologies resulted in lower emission rates of aromatic compounds. However, emissions of other toxic partial combustion products such as carbonyls were not reduced in the modern diesel vehicles tested.

Carbonaceous aerosols emitted from light-duty vehicles operating on gasoline and ethanol fuel blends.

This study examines the chemical properties of carbonaceous aerosols emitted from three light-duty gasoline vehicles (LDVs) operating on gasoline (e0) and ethanol-gasoline fuel blends (e10 and e85). Vehicle road load simulations were performed on a chassis dynamometer using the three-phase LA-92 unified driving cycle (UDC). Effects of LDV operating conditions and ambient temperature (-7 and 24 °C) on particle-phase semivolatile organic compounds (SVOCs) and organic and elemental carbon (OC and EC) emissions were investigated. SVOC concentrations and OC and EC fractions were determined with thermal extraction-gas chromatography-mass spectrometry (TE-GC-MS) and thermal-optical analysis (TOA), respectively. LDV aerosol emissions were predominantly carbonaceous, and EC/PM (w/w) decreased linearly with increasing fuel ethanol content. TE-GC-MS analysis accounted for up to 4% of the fine particle (PM2.5) mass, showing the UDC phase-integrated sum of identified SVOC emissions ranging from 0.703 μg km(-1) to 18.8 μg km(-1). Generally, higher SVOC emissions were associated with low temperature (-7 °C) and engine ignition; mixed regression models suggest these emissions rate differences are significant. Use of e85 significantly reduced the emissions of lower molecular weight PAH. However, a reduction in higher molecular weight PAH entities in PM was not observed. Individual SVOC emissions from the Tier 2 LDVs and fuel technologies tested are substantially lower and distributed differently than those values populating the United States emissions inventories currently. Hence, this study is likely to influence future apportionment, climate, and air quality model predictions that rely on source combustion measurements of SVOCs in PM.

Investigating the American Time Use Survey from an exposure modeling perspective

This paper describes an evaluation of the US Bureau of Labor Statistics’ American Time Use Survey (ATUS) for potential use in modeling human exposures to environmental pollutants. The ATUS is a large, on-going, cross-sectional survey of where Americans spend time and what activities they undertake in those locations. The data are reported as a series of sequential activities over a 24-h time period — a “diary day” — starting at 0400 hours. Between 12,000 and 13,000 surveys are obtained each year and the Bureau has plans to continue ATUS for the foreseeable future. The ATUS already has about 73,000 diary days of data, more than twice as many as that which currently exists in the US Environmental Protection Agencys (EPA) “Consolidated Human Activity Database” (CHAD) that the Agency uses for exposure modeling purposes. There are limitations for using ATUS in modeling human exposures to environmental pollutants. The ATUS does not report the location for a number of activities regarded as “personal.” For 2006, personal activities with missing location information totaled 572 min/day, on average, for survey participants: about 40% of their day. Another limitation is that ATUS does not distinguish between indoor and outdoor activities at home, two of the traditional locational demarcations used in human exposure modeling. This lack of information affects exposure estimates to both indoor and outdoor air pollutants and potentially affects non-dietary ingestion estimates for children, which can vary widely depending on whether or not a child is indoors. Finally, a detailed analysis of the work travel activity in a subsample from ATUS 2006 indicates that the coding scheme is not fully consistent with a CHAD-based exposure modeling approach. For ATUS respondents in this subsample who reported work as an activity, roughly 48% of their days were missing work travel at one or both ends of the work shift or reported within work-shift travel inconsistently. An extensive effort would be needed to recode work travel data from ATUS for EPAs exposure modeling purposes.

Relationship between PM2.5 collected at residential outdoor locations and a central site.

Abstract Regression models are developed to describe the relationship between ambient PM2.5 (particulate matter [PM] ≤2.5 μm in aerodynamic diameter) mass concentrations measured at a central-site monitor with those at residential outdoor monitors. Understanding the determinants and magnitude of variability and uncertainty in this relationship is critical for understanding personal exposures in the evaluation of epidemiological data. The repeated measures regression models presented here address temporal and spatial characteristics of data measured in the 2004–2007 Detroit Exposure and Aerosol Research Study, and they take into account missing data and other data features. The models incorporate turbulence kinetic energy and planetary boundary layer height, meteorological data that are not routinely considered in models that relate central-site concentrations to exposure to health effects. It was found that turbulence kinetic energy was highly statistically significant in explaining the relationship of PM2.5 measured at a particular stationary outdoor air monitoring site with PM2.5 measured outside nearby residences for the temporal coverage of the data.

Intra- and inter-individual variability in location data for two U.S. health-compromised elderly cohorts.

This study provides descriptive statistical data on daily time spent in three locations of exposure assessment interest for two panel studies of health-compromised elderly individuals >65-year-old having multiple days of human activity data. The panel studies include individuals living in Los Angeles (CA) and Baltimore (MD) in various housing types. Three general locations are evaluated: outdoors, in vehicles, and total indoors. Of particular interest is providing information regarding the within- and between-individual variability in the time use data for the three locations. The data are analyzed using non-parametric statistics and alternative statistical models. Within and between variability are evaluated using intraclass correlation coefficients (ICCs); daily “lag-one” autocorrelation coefficients are also provided for the two samples. There were significant gender differences for selected seasonal and/or day-of-the-week metrics for: (1) outdoor time in Los Angeles, but not in Baltimore, and (2) in-vehicle time in both areas. Elderly women spent more time in these locations than similarly aged men. The ICC statistic indicates that most of the variability in the time spent in the three locations is due to intraindividual variability rather than to inter-individual variability. The results indicate that US Environmental Protection Agency should consider gender, day-of-the-week, and time-of-day data in its exposure modeling of daily activities undertaken by the health-compromised elderly population.

Moderate perinatal thyroid hormone insufficiency alters visual system function in adult rats

HIGHLIGHTSRats were treated developmentally with propylthiouracil (PTU), a thyroid hormone inhibitor.Developmental PTU reduced adult green flicker ERGs, indicating a loss of M‐cones.UV‐flicker ERGS were unchanged, indicating sparing of S‐cones.PTU reduced pattern‐elicited VEPs as a function of the stimulus pattern luminance contrast.Reduced perinatal thyroid hormone impaired function in adult retina and visual cortex. ABSTRACT Thyroid hormone (TH) is critical for many aspects of neurodevelopment and can be disrupted by a variety of environmental contaminants. Sensory systems, including audition and vision are vulnerable to TH insufficiencies, but little data are available on visual system development at less than severe levels of TH deprivation. The goal of the current experiments was to explore dose‐response relations between graded levels of TH insufficiency during development and the visual function of adult offspring. Pregnant Long Evans rats received 0 or 3ppm (Experiment 1), or 0, 1, 2, or 3ppm (Experiment 2) of propylthiouracil (PTU), an inhibitor of thyroid hormone synthesis, in drinking water from gestation day (GD) 6 to postnatal day (PN) 21. Treatment with PTU caused dose‐related reductions of serum T4, with recovery on termination of exposure, and euthyroidism by the time of visual function testing. Tests of retinal (electroretinograms; ERGs) and visual cortex (visual evoked potentials; VEPs) function were assessed in adult offspring. Dark‐adapted ERG a‐waves, reflecting rod photoreceptors, were increased in amplitude by PTU. Light‐adapted green flicker ERGs, reflecting M‐cone photoreceptors, were reduced by PTU exposure. UV‐flicker ERGs, reflecting S‐cones, were not altered. Pattern‐elicited VEPs were significantly reduced by 2 and 3ppm PTU across a range of stimulus contrast values. The slope of VEP amplitude‐log contrast functions was reduced by PTU, suggesting impaired visual contrast gain. Visual contrast gain primarily reflects function of visual cortex, and is responsible for adjusting sensitivity of perceptual mechanisms in response to changing visual scenes. The results indicate that moderate levels of pre‐and post‐natal TH insufficiency led to alterations in visual function of adult rats, including both retinal and visual cortex sites of dysfunction.

Chemical-agnostic hazard prediction: Statistical inference of in vitro toxicity pathways from proteomics responses to chemical mixtures

Toxicity pathways have been defined as normal cellular pathways that, when sufficiently perturbed as a consequence of chemical exposure, lead to an adverse outcome. If an exposure alters one or more normal biological pathways to an extent that leads to an adverse toxicity outcome, a significant correlation must exist between the exposure, the extent of pathway alteration, and the degree of adverse outcome. Biological pathways are regulated at multiple levels, including transcriptional, post-transcriptional, post-translational, and targeted degradation, each of which can affect the levels and extents of modification of proteins involved in the pathways. Significant alterations of toxicity pathways resulting from changes in regulation at any of these levels therefore are likely to be detectable as alterations in the proteome. We hypothesize that significant correlations between exposures, adverse outcomes, and changes in the proteome have the potential to identify putative toxicity pathways, facilitating selection of candidate targets for high throughput screening, even in the absence of a priori knowledge of either the specific pathways involved or the specific agents inducing the pathway alterations. We explored this hypothesis in vitro in BEAS-2B human airway epithelial cells exposed to different concentrations of Ni2+, Cd2+, and Cr6+, alone and in defined mixtures. Levels and phosphorylation status of a variety of signaling pathway proteins and cytokines were measured after 48 hours exposure, together with cytotoxicity. Least Absolute Shrinkage and Selection Operator (LASSO) multiple regression was used to identify a subset of these proteins that constitute a putative toxicity pathway capable of predicting cytotoxicity. The putative toxicity pathway for cytotoxicity of these metals and metal mixtures identified by LASSO is composed of phospho-RPS6KB1, phospho-p53, cleaved CASP3, phospho-MAPK8, IL-10, and Hif-1α. As this approach does not depend on knowledge of the chemical composition of the mixtures, it may be generally useful for identifying sets of proteins predictive of adverse effects for a variety of mixtures, including complex environmental mixtures of unknown composition.

The Importance of Exposure in Addressing Current and Emerging Air Quality Issues

The air quality issues that we face today and will face in the future are becoming increasingly more complex and require an improved understanding of human exposure to be effectively addressed. The objectives of this paper are (1) to discuss how concepts of human exposure and exposure science and should be applied to improve air quality management practices, and (2) to show how air quality modeling tools can be used to improve exposures estimates used for under- standing associations between air quality and human health. Data from a large human exposure monitoring study is presented to demonstrate the value of exposure in understanding important air quality issues, such as health effects associated with exposure to components of particulate matter (PM), to PM of different size fractions (coarse and ultrafine), and to air pollution in near roadway environments. Various approaches for improving estimates of exposure via application of air quality modeling are discussed and results from example modeling applications are pre- sented. These air quality modeling approaches include: the integration of regional scale eulerian air quality models with local scale gaussian dispersion models; the fusion of modeled estimates with air quality observations; the integration of air quality and human exposure modeling tools; and the use of exposure factors, such as housing ventilation, to adjust modeled estimates of ambient air quality.