Consolidation of presentations and discussions at the 2015 UFP Workshop held in RTP, NC Feb, 2015 as reported by workshop session chairs consisting of EPA and non-EPA employees
Non-targeted analysis (NTA) workflows in high-resolution mass spectrometry require mechanisms for compound identification. One strategy for tentative identification is the use of online chemical databases such as ChemSpider. Databases like this use molecular formulae and monoisotopic mass-based searching and rank-ordering of results by the associated number of data supplier sources, bringing the most likely candidate “known unknowns” to the top of the list. The U.S. EPA’s iCSS CompTox Dashboard (https://comptox.epa.gov) is a highly curated and freely available resource containing more than 720,000 chemicals of relevance to environmental health science. In this research, we evaluated the performance of the Dashboard relative to ChemSpider for the identification of “known unknowns” using 162 chemicals representing a number of previously studied datasets from peer-reviewed literature. Molecular formulae and monoisotopic masses were searched using both applications and ordered using their different ranking approaches. A greater percentage of chemicals ranked in the top position when using the Dashboard and offered better overall performance for identifying “known unknowns.” Additional data will be presented evaluating alternative sources for tentative identification of chemicals. For example, the presence of chemicals in consumer products was incorporated into the tentative identification process and evaluated via the Dashboard. Weight-ordering of identification ranking for inclusion into a non-targeted analysis workflow as part of the CompTox Dashboard is being developed. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.
Progress towards the development and translation of alternative testing methods to safety-related decision making is a common goal that crosses organizational, stakeholder, and international boundaries. The challenge is that different organizations have different missions, different regulatory frameworks, and need to apply alternative methods to different decision contexts. Advancing the development and application of alternative methods will require focusing on common goals that address key challenges in advancing toxicology testing in the 21st century and provide common benefit across organizations and international boundaries. The talk will describe the global cooperation activities by the EPA across multiple stakeholder groups for development of alternative testing methods and the lessons learned in translating the methods to decision making. This abstract does not necessarily reflect U.S. EPA policy.
While ecosystem services research has become common, few efforts are directed toward in-depth understanding of the specific ecological quantities people value. Environmental communications as well as ecological monitoring and analysis efforts could be enhanced by such information. For example, small changes in the way ecosystems are described could strongly influence relevance to the public and improve the foundation for environmental decision-making. Clarifying valued attributes is particularly important for nonmarket ecosystem services, since price and quantity data cannot be readily observed as with goods and services bought and sold in traditional markets. Focusing on rivers and streams, we conducted a content analysis of existing publications to document the breadth and frequency with which various measurable attributes, such as flooding, water quality characteristics, and wildlife appeared in different news sources over a multiyear timeline. In addition to attributes, motivations for human interest in river-related resources were also coded, such as recreation or preservation for future generations. To allow testing of differences between materials written for different audiences, three sources were sampled: a blog hosted by National Geographic, New York Times articles, and Wall Street Journal articles. The coding approach was rigorously tested in a pilot phase, with measures developed to ensure high data quality, including use of two independent coders. Results show numerous similarities across sources with some notable differences in emphasis. Significant relationships between groups of attribute and motivation codes were also found, one outcome of which is further support for the importance of “non-use” values for fish and wildlife. Besides offering insight on ecosystem services, the project demonstrates an in-depth quantitative approach to analyzing preexisting qualitative data.
Mapping the geographic distribution of non-native aquatic species is a critically important precursor to understanding the anthropogenic and environmental factors that drive freshwater biological invasions. Such efforts are often limited to local scales and/or to single species, due to the challenges of data acquisition at larger scales. Here, we map the distribution of non-native freshwater species richness across the continental United States and investigate the role of human activity in driving macroscale patterns of aquatic invasion.
The continental United States.
We assembled maps of non-native aquatic species richness by compiling occurrence data on exotic animal and plant species from publicly accessible databases. Using a dasymetric model of human population density and a spatially explicit model of recreational freshwater fishing demand, we analysed the effect of these metrics of human influence on the degree of invasion at the watershed scale, while controlling for spatial and sampling bias. We also assessed the effects that a temporal mismatch between occurrence data (collected since 1815) and cross-sectional predictors (developed using 2010 data) may have on model fit.
Non-native aquatic species richness exhibits a highly patchy distribution, with hotspots in the Northeast, Great Lakes, Florida, and human population centres on the Pacific coast. These richness patterns are correlated with population density, but are much more strongly predicted by patterns of recreational fishing demand. These relationships are strengthened by temporal matching of datasets and are robust to corrections for sampling effort.
Distributions of aquatic non-native species across the continental US are better predicted by freshwater recreational fishing than by human population density. This suggests that observed patterns are driven by a mechanistic link between recreational activity and aquatic non-native species richness and are not merely the outcome of sampling bias associated with human population density.
Somatic and F+ coliphages are promising alternative fecal indicators, but current detection methods are hindered by lower levels of coliphages in surface waters compared to traditional bacterial fecal indicators. We evaluated the ability of dead-end hollow fiber ultrafiltration (D- HFUF) and single agar layer (SAL) procedure to concentrate and enumerate coliphages from 1L and 10L volumes of ambient surface waters (lake, river, marine), river water with varying turbidities (3.74–118.7 NTU), and a simulated combined sewer overflow (CSO) event. Percentage recoveries for surface waters were 40–79% (somatic) and 35–94% (F + ). The method performed equally well in all three matrices at 1L volumes, but percent recoveries were significantly higher in marine waters at 10L volumes when compared to freshwater. Percent recoveries at 1L and 10L were similar, except in river water where recoveries were significantly lower at higher volume. In highly turbid waters, D-HFUF-SAL had a recovery range of 25–77% (somatic) and 21–80% (F + ). The method produced detectable levels of coliphages in diluted wastewater and in unspiked surface waters, emphasizing its applicability to CSO events and highlighting its utility in recovery of low coliphage densities from surface waters. Thus D-HFUF-SAL is a good candidate method for routine water quality monitoring of coliphages.
Dogs have been studied for many years as a medical diagnostic tool to detect a pre-clinical disease state by sniffing emissions directly from a human or an in vitro biological sample. Some of the studies report high sensitivity and specificity in blinded case-control studies. However, in these studies it is completely unknown as to which suites of chemicals the dogs detect and how they ultimately interpret this information amidst confounding background odors. Herein, we consider the advantages and challenges of canine olfaction for early (meaningful) detection of cancer, and propose an experimental concept to narrow the molecular signals used by the dog for sample classification to laboratory-based instrumental analysis. This serves two purposes; first, in contrast to dogs, analytical methods could be quickly up-scaled for high throughput sampling. Second, the knowledge gained from identifying probative chemicals could be helpful in learning more about biochemical pathways and disease progression. We focus on exhaled breath aerosol, arguing that the semi-volatile fraction should be given more attention. Ultimately, we conclude that the interaction between dog-based and instrument-based research will be mutually beneficial and accelerate progress towards early detection of cancer by breath analysis.
Human biomonitoring is an indispensable tool for establishing the systemic effects from external stressors including environmental pollutants, chemicals from consumer products, and pharmaceuticals. This article uses a combination of new results and meta-data from previous work to explore environmental exposures to diesel exhaust (DE) and ozone (O3) and interpret these parameters from the perspective of in vitro to in vivo extrapolation. The ultimate goal is to use cytokine expression at the cellular level as a biomarker for physiological systemic responses such as blood pressure and lung function. This study investigates human co- exposures to combinations of DE and O3 and the response correlations between forced exhaled volume in 1 second (FEV1), forced vital capacity (FVC), systolic and diastolic blood pressure (SBP and DBP,respectively), and 10 inflammatory cytokines (interleukins 1β, 2, 4, 5, 8, 10, 12p70 and 13, IFN-γ, and TNF-α) for 15 healthy human volunteers. DE exposure demonstrated a significant negative Spearman correlation between the Th1 cytokine IL-12p70 and DBP (ρ=-0.529). The O3 exposure results showed a negative DBP correlation with the Th2 cytokine IL-5 (ρ=-0.546).Significant positive correlations were found between IFN-γ and both FEV1 (ρ=0.843) and FVC (ρ=0.711) for the O3 exposure. Although the DE+O3 co-exposure results had no globally statistically significant correlations between cytokines or blood pressure values with lung function measurements, results showed that SBP had strong negative correlations with both IL-8(ρ=-0.675) and IFN-γ (ρ=-0.729). Results across all exposures revealed that certain individuals had a much greater inflammatory response compared to the group and, generally, there was more between-person variation in the response; individuals are more stable within themselves and are more likely to have responses independent of one another. Stratification of these responses by GSTM1 genotype did not elucidate any underlying patterns. This work suggests that in vitro work could be implemented to help elucidate the underlying mechanistic pathways observed in this study and to ultimately serve as part of an adverse outcome pathway (AOP) for linking high-throughput toxicity tests to physiological in vivo responses.
The Korean National Environmental Health Survey (KoNEHS 2009–2011) tracks levels of environmental pollutants in biological samples from the adult Korean population (age 19–88). Recent survey results for blood mercury (Hg) suggest some exceedance above existing blood Hg reference levels. Because total blood Hg represents both organic and inorganic forms, and methylmercury (MeHg) has been specifically linked to several adverse health outcomes, a need exists to quantify MeHg intake for this population. Gender, age, and frequency of fish consumption were first identified as important predictors of KoNEHS blood Hg levels using generalized linear models. Stratified distributions of total blood Hg were then used to estimate distributions of blood MeHg using fractions of MeHg to total Hg from the literature. Next, a published physiologically based pharmacokinetic (PBPK) model was used to predict distributions of blood MeHg as a function of MeHg intake; ratios of MeHg intake to model-predicted blood MeHg were then combined with KoNEHS-based blood MeHg values to produce MeHg intake estimates. These intake estimates were ultimately compared with the Reference Dose (RfD) for MeHg (0.1 µg/kg/day) and reported as margin of exposure (MOE) estimates for specific KoNEHS subgroups. The derived MOEs across all subgroups, based on estimated geometric mean intake, ranged from 1.6 to 4.1. These results suggest MeHg exposures approaching the RfD for several subgroups of the Korean population, and not just for specific subgroups (eg, those who eat fish very frequently).
The present study investigates primary and secondary sources of organic carbon for Bakersfield, CA, USA as part of the 2010 CalNex study. The method used here involves integrated sampling that is designed to allow for detailed and specific chemical analysis of particulate matter (PM) in the Bakersfield airshed. To achieve this objective, filter samples were taken during thirty-four 23-hr periods between 19 May and 26 June 2010 and analyzed for organic tracers by gas chromatography – mass spectrometry (GC-MS). Contributions to organic carbon (OC) were determined by two organic tracer-based techniques: primary OC by chemical mass balance and secondary OC by a mass fraction method. Radiocarbon (14C) measurements of the total organic carbon were also made to determine the split between the modern and fossil carbon and thereby constrain unknown sources of OC not accounted for by either tracer-based attribution technique.
From the analysis, OC contributions from four primary sources and four secondary sources were determined, which comprised three sources of modern carbon and five sources of fossil carbon. The major primary sources of OC were from vegetative detritus (9.8%), diesel (2.3%), gasoline (<1.0%), and lubricating oil impacted motor vehicle exhaust (30%); measured secondary sources resulted from isoprene (1.5%), α-pinene (<1.0%), toluene (<1.0%), and naphthalene (<1.0%, as an upper limit) contributions. The average observed organic carbon (OC) was 6.42 ± 2.33 μgC m−3. The 14C derived apportionment indicated that modern and fossil components were nearly equivalent on average; however, the fossil contribution ranged from 32 to 66% over the five week campaign. With the fossil primary and secondary sources aggregated, only 25% of the fossil organic carbon could not be attributed. Whereas, nearly 80% of the modern carbon could not be attributed to primary and secondary sources accessible to this analysis, which included tracers of biomass burning, vegetative detritus and secondary biogenic carbon. The results of the current study contributes source-based evaluation of the carbonaceous aerosol at CalNex Bakersfield.
Characterization of uncertainty and sensitivity of model parameters is an essential and often overlooked facet of hydrological modeling. This paper introduces an algorithm called MOESHA that combines input parameter sensitivity analyses with a genetic algorithm calibration routine to dynamically sample parameter space as an alternative to traditional static space-sampling methods, such as stratified sampling or Latin hypercube sampling. In addition to calibrating input parameters to a hydrologic model, MOESHA determines the optimal distribution of input parameters that maximizes model robustness and minimizes error. Subsequently, the variance of the input parameter distributions are used to differentiate between impactful and non-impactful input parameters. In this way, an optimally calibrated model is produced, and estimations of model uncertainty as well as the relative impact of input parameters on model output (i.e., sensitivity) are determined. A case study using a single-cell hydrological model (EXP-HYDRO) is used to test the method using river discharge data from the Dee River catchment in Wales. We compare the results of MOESHA with Sobol’s global sensitivity analysis method and demonstrate that the algorithm is able to pinpoint non-impactful parameters while achieving excellent calibration results.
presentation at Michigan State University Dept. of Pharmacology and Toxicology Alternative Approaches to Chemical Risk Assessment: Assays, Databases, Models
As part of “Ongoing EDSP Directions & Activities” I will present CSS research on high throughput toxicokinetics, including in vitro data and models to allow rapid determination of the real world doses that may cause endocrine disruption.
An increase in the frequency and intensity of storms and flooding events are adversely impacting coastal wetlands. Coastal wetlands provide flood abatement, carbon and nutrient sequestration, water quality maintenance, and habitat for fish, shellfish, and wildlife, including species of concern, such as the saltmarsh sparrow (Ammodramus caudacutus). A framework and methodology adopted by scientific, management, and policy stakeholders for restoration and adaptation actions to manage coastal marshes in Northeastern, USA is described. A traditional adaptive management approach was modified to identify extreme event vulnerabilities and propose adaptation actions to build coastal resiliency. When possible an experimental BACI (Before-After, Control-Impact) design was incorporated into the implementation plans. Specific adaptation actions and monitoring plans are described, and include protecting marsh shoreline, restoring hydrological drainage patterns, increasing marsh elevation, and enabling upland marsh migration. The restoration framework is presented as a demonstration of adaptation actions to build coastal resiliency in tidal marsh systems subject to extreme weather events.
Community of practice webinar presentation on the Identification of unknowns in non-targeted analyses (NTA) requires the integration of complementary data types to generate a confident consensus structure.
The Region 3 “Making a Visible Difference in Communities” (MVD) initiative for Southeast Newport News, VA has taken a community-centric, place-based approach to identifying and delivering service to the area’s residents and the city as a whole. Beginning with a CARE (Community Action for a Renewed Environment) Level 1 cooperative agreement (a grant with substantial government involvement and required outputs) in 2011, Region 3 funding helped to establish the Southeast CARE Coalition (“the Coalition”), and quickly formed a bond with the organization. Two years later, Region 3, the US EPA Office of Research and Development (ORD) and the Coalition embarked on a scientific, socio-demographic Regional Sustainable Environmental Science (RESES) research project to assess local pollutant sources and their potential impacts to the community. These efforts helped EPA select Newport News as an MVD community, resulting in an expanded partnership that now includes the City of Newport News. Through this association and the MVD designation, the partners have identified and prioritized environmental and other concerns (e.g., improving air and water quality, adapting to extreme weather, promoting equitable development, improving transportation). Newport News has recently held workshops and training on topics such as environmental health, asthma, weather events, and equitable development, and continues to improve the community’s health, its knowledge of the relevant environmental health issues, and its wellbeing.
Weeks Bay is a shallow, microtidal, eutrophic sub-estuary of Mobile Bay, AL. High watershed nutrient inputs to the estuary contribute to a eutrophic condition characterized by frequent summertime diel-cycling hypoxia and dissolved oxygen (DO) oversaturation. Spatial and seasonal variability of microbial communities that contribute to estuarine ecosystem metabolism were characterized using high-throughput DNA sequencing. Surface water samples were collected from spring to fall at three sites along a transect of Weeks Bay from the Fish River to Mobile Bay. Water samples were analyzed for physiochemical properties and were also filtered onto Sterivex filters for DNA extraction. Genes for 16S rRNA and 18S rRNA were amplified and sequenced according to Earth Microbiome Project protocols. Sequences were assembled into contigs and clustered into OTUs with mothur using the Silva database. The prokaryotes were dominated by Cyanobacteria, Actinobacteria, and Spartobacteria, whereas the eukaryotes were dominated by Bacillariophyta (diatoms). Multivariate statistical analysis of microbial community composition and environmental data showed that Bacteria, Archaea and Eukaryota were clustered by season. BEST analysis by station showed that prokaryotic community structure was associated with salinity and CDOM (Rho=0.924), whereas eukaryotic community structure was most associated with salinity (Rho=0.846). Prokaryotic community structure within seasons was associated with six factors (temperature, salinity, CDOM, pH, chlorophyll-a, and ammonium (Rho=0.846)), whereas eukaryotic community structure was associated significantly with five (temperature, DO, CDOM, chlorophyll-a, and TDN (Rho=0.833)). The eukaryotes varied in relation to a different set of water quality factors than did the prokaryotes. These results provide useful information about microbial and algal community dynamics in estuaries like Weeks Bay and could be useful for understanding and predicting ecosystem function in relation to nutrient loading, water quality and other seasonal drivers.
Anticipating chronic effects of contaminant exposure on amphibian species is complicated both by toxicological and ecological uncertainty. Data for both chemical exposures and amphibian vital rates, including altered growth, are sparse. Developmental plasticity in amphibians further complicates evaluation of chemical impacts as metamorphosis is also influenced by other biotic and abiotic stressors, such as temperature, hydroperiod, predation, and conspecific density. Determining the effect of delayed tadpole development on survival through metamorphosis and subsequent recruitment must include possible effects of pond drying accelerating metamorphosis near the end of the larval stage. This model considers the combined influence of delayed onset of metamorphosis in a cohort as well as accelerated metamorphosis toward the end of the hydroperiod and determines the net influence of counteracting forces on tadpole development and survival. Amphibian populations with greater initial density dependence have less capacity for developmental plasticity and are therefore more vulnerable to delayed development and reduced hydroperiod. The consequential reduction in larval survival has a relatively greater impact on species with a shorter lifespan, allowing for fewer breeding seasons during which to successfully produce offspring. In response to risk assessment approaches that consider only survival and reproductive endpoints in population evaluation, we calculate contaminant-related growth effects in terms of reduced survival and present these altered vital rates in the larger context of long-term population consequences for different species.