National Center for Environmental Assessment (EPA)

Differences in environmental exposures-particularly to ambient air pollution-have been consistently documented across communities in the United States (U.S.). However, relatively few studies on air pollution have focused on American Indians. In this paper, we combine demographic data from Phase IV (2001 to 2003) and Phase V (2006 to 2009) of the Strong Heart Study-the largest ongoing longitudinal epidemiologic cohort study of cardiovascular disease in American Indians-and 1 km2 modeled PM2.5 data in the Northern Plains, Southern Plains, and Southwestern United States. We analyzed data at the U.S. ZIP code level to estimate 30-day and annual residential exposures of participants to PM2.5 and assess for regional, temporal, and seasonal variations in PM2.5 exposure. We found significantly higher mean 30-day and annual PM2.5 concentrations among participants in the Southwest and Southern Plains (>7.4 μg/m3 and >7.6 μg/m3, respectively) than in the Northern Plains (<6.6 μg/m3 and <6.2 μg/m3, respectively). We observed heterogeneity in participants' mean 30-day and annual PM2.5 exposure within and across regions. Furthermore, seasonal differences in ambient PM2.5 concentrations among participants varied by region; in the Northern Plains, we generally observed higher mean 30-day PM2.5 exposure levels in the summertime and lower levels in the wintertime, whereas levels remained relatively constant in the Southern Plains and Southwest. These findings offer essential baseline data to advance accurate and equitable exposure assessment across tribal communities in the Northern Plains, Southern Plains, and Southwest regions.

Background Systematic reviews and other types of evidence syntheses use rigorous methods to identify and synthesise all of the relevant evidence to answer a question. A robust search strategy is crucial to conducting a high quality evidence synthesis, as an inadequate search may miss relevant evidence and produce biased findings. Methodological recommendations endorse searching for ‘grey literature’, i.e., reports published outside of traditional commercial publishing. However, there is currently a lack of clarity about what is considered to be the relevant types of grey literature and how to deal with it.Objectives This survey will aim to answer three questions: (1) How do those conducting evidence syntheses on environmental health and toxicology (EHT) topics understand ‘grey literature’; (2) Where do they search for grey literature?; (3) How do they deal with included grey literature evidence?Methods Participants will be individuals who conduct systematic reviews and evidence syntheses in EHT, without restrictions on: previous experience in conducting evidence synthesis, age, gender or geographic location. Survey will be disseminated via relevant professional organisations, systematic review and evidence synthesis organisations, and social media. It will consist of a mix of demographic and content questions. Descriptive statistics will be reported as frequencies and percentages; free-text responses will be analysed thematically.Ethics The survey was exempted from a requirement to undergo ethics review. The first page of the survey will provide the respondents with information about the project and ethics approval; respondents will provide consent by clicking on a button to advance to the survey.

Legacy stores of nitrogen (N) have been proposed as an explanation for time lags between implementation of nutrient management practices and discernable declines in riverine N loads, particularly in agricultural watersheds. Process models that treat the environment as being divided into linked homogeneous pools or compartments have been used recently to estimate legacy N stores and infer time lags. However, questions have been raised regarding equifinality, i.e. the idea that acceptable estimates might be obtained using models with different structures and/or sets of parameters, creating uncertainty in model interpretation. To further advance understanding of legacy stores and lags in watershed N delivery, we developed six fate and transport models that vary in simplicity and physicochemical detail. Using published annual N surplus and riverine N load datasets, we calibrated the models to minimize summed squared errors compared with multidecadal NO3-N (nitrate N) yield time series at 254 riverine sites across the continental United States. All models fit most datasets well, with calibration results suggesting little if any lagged contribution from either biogeochemical or hydrologic legacy stores. The highest quality model in terms of adjusted Akaike information criterion was the simplest, comprising a single, well-mixed compartment that lacks any mechanism to represent time lags between N input and output. Calibrated model results thus fail to provide evidence of influential legacy N stores. However, results using incrementally lagged watershed N inputs (themselves shown to be temporally autocorrelated), also imply that delivery lags of up to about a decade cannot be ruled out.

Harmful cyanobacterial blooms (HCBs) are a public health concern and require ongoing surveillance to monitor the negative water quality effects and cyanotoxins associated with these blooms. (+)-Anatoxin-a (ATX) is a potent neurotoxin produced by select cyanobacteria during HCB formation. Many HCB toxins are commonly associated with discolored water; however, ATX can be present in clear water, which results in a high risk of exposure by accidental ingestion for humans and animals. In this work, we used a qualitative, semitargeted liquid chromatography high resolution mass spectrometry (LC-HRMS) method and a discovery data analysis workflow to detect and identify ATX and its predicted mammalian metabolites in urine samples from ATX-dosed mice. Potential compounds were evaluated for identification with product-ion spectral matching to a local library, accurate mass list matching, further data processing and interpretation, and comparison to undosed mice urine samples. As a result, ATX and dihydroanatoxin-a (dhATX) were successfully identified in the dosed mice samples through retention time (RT) and product-ion spectral matching to their respective commercial standards. The positive identification of dhATX suggests its formation as an abundant metabolic product of ATX within mammalian systems. Additionally, multiple chromatographic peaks were observed that matched the exact mass of 3-OH ATX and were further identified by the presence of diagnostic product ions and comparison to a standard synthesized in-house. In total, seven potential ATX metabolites, including dhATX and 3-OH ATX, were detected and characterized in the dosed mice samples. All identified metabolites were either oxidized or reduced forms of ATX, which suggests that oxidation and reduction are the main pathways for endogenous ATX metabolism in mice. These results are among the first reports of metabolic products of ATX in biological samples and provide a metabolic profile of ATX for higher confidence screening for ATX after a suspected exposure event.

ABSTRACT Exposures to pollutants rarely occur in isolation, often coexisting with other environmental stressors such as diet and may be particularly insidious in early life. The aim of this study was to examine effects of maternal exposure to cadmium (Cd) and consumption of a high-fructose diet (HFrD) on development of mouse offspring. Female CD-1 mice were administered either 0.5 or 5 ppm Cd in drinking water with or without an approximate 60% fructose diet for 3 weeks prior to mating. Dams were maintained on the same treatment until postnatal day (PND) 16. Cadmium concentrations in maternal, fetal, and neonatal liver increased in a concentration-dependent manner irrespective of diet. Endpoints known to be associated with Cd or HFrD adverse effects were assessed longitudinally in offspring from birth to young adulthood, including growth trajectory, pubertal development, body composition, glycemic tolerance and hepatic lipid accumulation. Maternal exposure to either Cd or HFrD alone significantly advanced onset of puberty, hypoglycemia, and reduced adiposity in adulthood. HFrD rarely exacerbated metal-initiated effects in most of the endpoints examined outside of pubertal timing. Because of chronic effects attributed to Cd or HFrD on metabolic function (e.g. glucose tolerance), transcriptomics and gene methylation analyses were performed on livers from neonatal and adult offspring. Data were largely consistent with phenotypic findings. In summary, maternal exposure to Cd or HFrD alone perturbed growth and development, producing long-lasting changes in metabolic function in adult offspring. HFrD did not appear to significantly exaggerate adverse outcomes attributed to metal exposure in the endpoints examined.

ABSTRACTIncreasing human population and anthropogenic activities pose immense pressure on natural water resources in terms of quantity and quality. In order to replenish, wastewater generated from various activities needs to be suitably treated before discharging into these resources. Sewage is one of the major sources of wastewater in urban settings. Moreover, if properly treated in sewage treatment plants (STPs), sewage may also serve as the source of recycled water. Considering this, the performance evaluation of five STPs located in Varanasi, India, was done in three sampling periods, and their treatment efficacy was assessed. Maximum pollutants' reduction percentage based on the weighted arithmetic water quality index of influent and effluent was calculated to be 93.64% and 97.76% (in sampling period III). Unsettlingly, it was also found that none of the STPs performed as per the notified standards in all three sampling periods. Therefore, strict vigilance and supervisory actions are inevitable for making STPs compliant with regulatory standards.

Physiologically based pharmacokinetic (PBPK) models describe the absorption, distribution, metabolism, and excretion of chemicals. Probabilistic PBPK models can be used to produce distributional estimates of human equivalent doses (HEDs), which are external measures of human exposure predicted to result in a target internal dose, generated with Monte Carlo sampling and reverse dosimetry calculations. Very low HED percentiles represent individuals that are more sensitive to possible adverse effects of chemical exposures and are therefore frequently used in risk evaluation. Details of the parameter distributions used in probabilistic PBPK models impact HED distributions, but obtaining precise distributional estimates for all the parameters would be challenging. Therefore, we sought to determine methods that can identify the extent of model parameter influence on extreme HED percentiles. We first analyzed published PBPK models for dichloromethane and chloroform (for inhalation and oral exposures given 3 internal target levels each) by identifying the overall relative importance of parameters using global sensitivity analysis (GSA) methods. Then, we used a novel yet computationally expensive method to analyze the stability and sensitivity of extreme HED percentiles to input parameter distributions. Applying the traditional GSA methods allowed us to identify subsets of parameters most influential for accurately determining 1st and 99th percentiles, but the specific parameters included in those subsets varied for different models and exposure scenarios. Our results demonstrate that better characterizing PBPK model uncertainty by using precise distributional details for influential parameters informed by GSA methods may improve confidence in estimates of extreme percentiles of HEDs.

<strong class="journal-contentHeaderColor">Abstract.</strong> High performance computing (HPC) clusters offer an abundance of processors, memory, and data storage that can help meet growing computational demands for large geospatial analyses. Esri&rsquo;s proprietary ArcGIS toolboxes are a common way to develop, document, and share geospatial code; however, these toolboxes are typically developed for use in Esri&rsquo;s ArcGIS Pro for Windows which limits their use in Linux, the dominant HPC operating system. Esri&rsquo;s support of Linux for their server software opens the possibility of using ArcGIS toolboxes in an HPC environment, but use of this software proved problematic for concurrent, parallel processing offering little benefit over a single workstation. We developed a solution using container technology allowing us to run hundreds of concurrent tasks that use ArcGIS toolboxes. This approach is designed to take advantage of the many existing ArcGIS toolboxes and use them in parallel for workflows that can be reasonably divided into independent sub-tasks. With careful setup and use of an HPC job scheduler, we reduced total processing time for one analysis 95.6 % by dividing the analysis into 202 sub-tasks. This solution allows other HPC users to take advantage of parallel use of ArcGIS Toolboxes, avoid the effort of translating existing workflows to Linux native software, and establish a bridge between desktop GIS and HPC systems.

Non-targeted analysis (NTA) methods are integral to environmental monitoring given their ability to expand measurable chemical space beyond that of traditional targeted methods. Such vast quantities of NTA data are generated that exhaustive manual review is generally unfeasible. Computational tools facilitate automated data processing, but cannot always distinguish real signals (i.e., originating from a chemical in a sample) from artifacts. Replicate analysis is recommended to aid data review, but as NTA studies become larger, the cost of analytical replication becomes untenable. A need therefore exists for examination of information penalties associated with reduced replication. To investigate this issue, using an existing NTA dataset, we performed over 70,000 simulations of variable replication designs and calculated false discovery rates (FDRs) and false negative rates (FNRs) for NTA features and occurrences. We used regression models to explore associations between replication percentage and FDR/FNR, and to test whether rates were affected by NTA feature attributes. Inverse relationships were generally observed between replication percentage and FDR/FNR, such that lower replication yielded higher information penalties. Significant increases in FDR/FNR were observed for suspected per- and polyfluoroalkyl substances (PFAS) compared to non-PFAS, highlighting the potential for differences in information penalties across feature groups. Specific quantitative information penalties are expected to be unique for each NTA study based on sample type and workflow. The methods presented here can support future pilot-scale investigations that will inform the required level of replication in full-scale studies.