US Environmental Protection Agency Research Articles

Early life exposure to mercury and relationships with telomere length and mitochondrial DNA content in European children

BackgroundTelomere length (TL) and mitochondrial function expressed as mitochondrial DNA copy number (mtDNAcn) are biomarkers of aging and oxidative stress and inflammation, respectively. Methylmercury (MeHg), a common pollutant in fish, induces oxidative stress. We hypothesized that elevated oxidative stress from exposure to MeHg decreases mtDNAcn and shortens TL. MethodsStudy participants are 6–11-year-old children from the HELIX multi-center birth cohort study, comprising six European countries. Prenatal and postnatal total mercury (THg) concentrations were measured in blood samples, TL and mtDNAcn were determined in child DNA. Covariates and confounders were obtained by questionnaires. Robust regression models were run, considering sociodemographic and lifestyle covariates, as well as fish consumption. Sex, ethnicity, and fish consumption interaction models were also run. ResultsWe found longer TL with higher pre- and postnatal THg blood concentrations, even at low-level THg exposure according to the RfD proposed by the US EPA. The prenatal association showed a significant linear relationship with a 3.46 % increase in TL for each unit increased THg. The postnatal association followed an inverted U-shaped marginal non-linear relationship with 1.38 % an increase in TL for each unit increased THg until reaching a cut-point at 0.96 μg/L blood THg, from which TL attrition was observed. Higher pre- and postnatal blood THg concentrations were consistently related to longer TL among cohorts and no modification effect of fish consumption nor children's sex was observed. No association between THg exposure and mtDNAcn was found. DiscussionWe found evidence that THg is associated with TL but the associations seem to be time- and concentration-dependent. Further studies are needed to clarify the mechanism behind the telomere changes of THg and related health effects.

[Pollution Characteristics, Source, and Health Risk Assessment of Metal Elements in PM2.5 Between Winter and Spring in Zhengzhou].

A total of 18 metal elements in ambient PM2.5 in Zhengzhou were continuously determined using an online heavy metal observation instrument in January and April, 2021, and the changes in element concentrations were analyzed. Metal elements were traced via enrichment factors, positive matrix factorization (PMF), and a characteristic radar chart. The US EPA health risk assessment model was used to assess the health risks of heavy metals, and the backward trajectory method and the concentration-weighted trajectory (CWT) method were used to evaluate the potential source regions of health risks. The results showed that the element concentrations were higher in spring, and the sum of Fe, Ca, Si, and Al concentrations accounted for 89.8% and 87.5% of the total element concentrations in winter and spring, respectively. Cd was enriched significantly, which was related to human activities. The concentrations of Pb, Se, Zn, Ni, Sb, and K in winter and Cr, Ni, Fe, Mn, V, Ba, Ca, K, Si, and Al in spring increased with the increasing pollution level. The results of PMF and the characteristic radar chart showed that the main sources of metal elements in winter and spring were industry, crust, motor vehicles, and mixed combustion, with industry and mixed combustion pollution occurring more often in winter and crust pollution occurring more often in spring. Significant non-carcinogenic risks existed in both winter and spring with more severe health risks in winter, and Mn caused significant non-carcinogenic risks. The health risks in winter were mainly influenced by Zhengzhou and surrounding cities and long-distance transport in the northwest, and the health risks in spring were mainly influenced by Zhengzhou and surrounding cities.

Heavy Metal Ion Adsorbent in Aqueous Solution: A Review on Chitosan and Chitosan Composites

One prominent contributor to environmental degradation is the presence of heavy metal ions, which are commonly introduced into ecosystems through diverse channels, including mining operations, paint manufacturing, battery production, and agricultural practises. The unprocessed waste from these industries typically undergoes direct discharge into rivers and seas, thereby adversely influencing the potable water supply and marine ecosystem. This results in the accumulation of heavy metals within living organisms and subsequent environmental degradation that poses a significant risk to human health, as their prolonged consumption can harm various organs and the nervous system. Therefore, the United States Environmental Protection Agency (US-EPA) and the World Health Organisation (WHO) have established stringent regulations regarding the allowable levels of heavy metal intake, particularly concerning potable water consumption. The imperative lies in surmounting this challenge by discovering the optimal technique for extracting heavy metals. This paper examines the primary methods of eliminating heavy metal ions using chitosan-based materials. Specifically, the methods under scrutiny include electrocoagulation (E.C.), bioremediation, ion-exchange, membrane filtration (purification), and adsorption. Adsorption, as a highly efficient method, presents itself as a viable strategy for the remediation of dyes in textile wastewater due to its advantageous characteristics. Notably, this approach obviates the need for extensive spatial requirements and exhibits a commendably swift treatment duration. Chitosan exhibits promising adsorptive characteristics owing to its advantageous physical attributes, including crystalline structure, porous nature, and particle dimensions, all of which synergistically enhance the adsorption capacity of chitosan. Research findings indicate that the adsorption characteristics of chitosan are subject to variation contingent upon the distinct heavy metal ions under consideration and the specific experimental parameters employed. Hence, optimising these parameters becomes imperative to attain enhanced chitosan adsorption capabilities for heavy metal ion removal.

An integrated uncrewed aerial vehicle platform with sensing and sampling systems for the measurement of air pollutant concentrations

Abstract. In this study, an uncrewed aerial vehicle (UAV) platform with sensing and sampling systems was developed for three-dimensional (3D) measurements of air pollutant concentrations. The sensing system of this platform contains multiple microsensors and Internet of Things devices for determining the 3D distributions of four critical air pollutants and two meteorological parameters in real time. Moreover, the sampling system comprises remote-controllable gas sampling kits, each of which contains a 1 L Tedlar bag for the 3D measurement of volatile organic compound (VOC) concentrations according to the Toxic Organics-15 (TO-15) method of the US Environmental Protection Agency. The performance of the developed UAV platform was verified in experiments where it was used to detect air pollutant emissions from a large industrial zone in Taiwan that included a traditional industrial park, a precision machinery park, and a municipal waste incineration plant. Three locations were selected as field measurement sites according to the prevailing local wind direction. The vertical distributions of four critical air pollutants, the ambient temperature, and the relative humidity were determined from data gathered at the aforementioned sites in March and May 2023. A total of 56 and 72 chemical species were qualitatively and quantitatively analyzed in these two periods, respectively. The experimental results verified the feasibility of using the proposed UAV platform for accurately evaluating the air pollutant concentration distribution and transport in an industrial zone. The sampling system can be used as the sampling part of the TO-15 method, thus extending the method to measure the 3D distribution of VOCs in an area. The UAV platform can serve as a useful tool in the management of and decision-making process for air pollution in industrial areas.

Revisiting the quantification of power plant CO2 emissions in the United States and China from satellite: A comparative study using three top-down approaches

Top-down constraints of CO2 emissions from coal-fired power plants are critical to improving the accuracy of CO2 emission inventory and designing carbon reduction strategies. Different top-down models based on satellite observation have been proposed in previous studies, but discrepancies between these models and the underlying drivers are rarely explored, limiting the confidence of their application for monitoring point-source CO2 emissions from satellite. Here, we apply three top-down models to estimate CO2 emissions from individual coal-fired power plants in the United States (US) and China in 2014–2021 from Orbiting Carbon Observatory 2 (OCO-2) satellite observations. The first one applies the Gaussian plume model to optimize emissions by fitting modeled CO2 enhancement to the observation. The second and third methods apply the same inversion framework using the maximum likelihood estimation, but with WRF-Chem and WRF-FLEXPART as forward models, respectively. We evaluate consistency between the three methods in estimating emissions of 10 power plants in the US, using daily reported values from the US Environmental Protection Agency (EPA) as a benchmark, and then apply the three methods to quantify emissions of 13 power plants in China. Results show that the WRF-Chem and WRF-FLEXPART based inversion results are consistent with the EPA reported emission rates, with correlation coefficients (r) of 0.76 and 0.85 and mean biases (MB) of 4.06 and 3.97 ktCO2/d relative to EPA reports at all 10 power plants, respectively. The Gaussian plume model driven by wind fields from WRF-Chem model without the wind rotation shows comparable ability in reproducing the EPA reported emission rates at 7 power plants (r = 0.82, MB = 6.17), but is not applicable for the other three cases. We find that application of the high-resolution three-dimensional wind fields can better capture the shape of observed plumes, especially under complex wind conditions, compared to the Gaussian plume model which relies on wind field at a single point, and thus the Gaussian plume model has difficulty to optimize emissions under inhomogeneous wind fields or when observations are far away from the power plant. In general, using the WRF-FLEXPART model as the forward model in the inverse analysis shows advanced capability to simulate narrow-shape plumes in the absence of numerical diffusion which is inherent in Eulerian model such as WRF-Chem. Emissions estimated by the three top-town methods show a moderate consistency at 13 coal-fired power plant cases in China, with 8 of 13 cases showing differences of <30% between at least two methods. However, large differences emerge when wind fields are inhomogeneous and number of available observations is limited. Using different meteorological wind fields and OCO-2 data versions can also bring substantial differences to the posterior emissions for all three approaches. We find that the posterior CO2 emissions, though only reflecting instantaneous emission rates at satellite overpass time, are not proportional to the reported capacities of these power plants, indicating that attributing CO2 emissions simply based on the capacity of power plants in some bottom-up approaches may have significant discrepancies. Our study exposes the capability and limitation of different top-down approaches in quantifying point-source CO2 emissions, advancing their application for better serving increasing constellations of point-source imagers in the future.

Assessment of potential health risks associated with heavy metal concentrations in leafy vegetables in Kerman, Iran

ABSTRACT Despite the growing awareness of the nutritional benefits of leafy vegetables, there is a lack of information about the presence of heavy metals and the associated risks in these products. This study aimed to investigate the concentration of heavy metals in leafy vegetables in Kerman City. The research also assessed the intake of heavy metals and the associated drisks for children and adults who consume these vegetables. The study followed the recommended methods by the US Environmental Protection Agency (USEPA) to evaluate both carcinogenic and non-carcinogenic diseases. A total of 400 leafy vegetable samples, including parsley, coriander, Persian leek, and basil, were randomly collected from agricultural farms in the outskirts of Kerman City. The samples were analysed using a graphite furnace atomic absorption spectrometer to measure the concentrations of lead (Pb), cadmium (Cd), iron (Fe), and copper(Cu). The results revealed that the levels of heavy metals in leafy vegetable samples exceeded the recommended standards set by international organisations such as FAO/WHO, European countries, and Iran. The total target hazard quotient (THQ) for non-carcinogenic diseases resulting from the consumption of leafy vegetables was higher than one for both children and adults in all studied areas, indicating a potential risk of non-carcinogenic diseases associated with the consumption of these vegetables. Furthermore, the average Incremental Lifetime Cancer Risk (ILCR) resulting from exposure to agricultural soil through leafy vegetable consumption exceeded the hazardous and unacceptable range of 104− × 10−6 in both children and adults. This suggests the possibility of carcinogenic diseases caused by Pb and Cd through the consumption of leafy vegetables in all studied areas, with a higher overall risk observed in children compared to adults. In conclusion, while leafy vegetables are widely recognised for their nutritional benefits, our study underscores a critical gap in understanding the presence of heavy metals and the associated risks in these products. The findings reveal that the concentrations of heavy metals in leafy vegetables from Kerman City exceed international standards, posing potential health risks, particularly in children. Further research and regulatory actions are warranted to address this pressing issue and ensure the safety of our food supply.

211 Analysis of microbial communities from a commercial-size swine manure pit and their association with production of volatile organic compounds

Abstract Global pollution and emission concerns have been linked to concentrated animal feeding operations (CAFOs). Indeed, the U.S Environmental Protection Agency (US EPA) warns that there is a significant danger to human health, soil, and water quality from CAFOs. Volatile organic compounds (VOCs), which are amongst air contaminants that pose a serious risk, are abundantly produced in swine manure pits. While VOC emissions from swine manure have been well studied, the microbial species responsible for their production remain mostly uncharacterized. Thus, a deeper comprehension of the microorganisms responsible for VOC production in swine manure pits may help in the development of management approaches that target the microbiome in these environments. In this context, this study aimed to identify the major bacterial species populating the manure pit of a commercial-size swine wean-to-finish research facility. Manure collected from two sampling locations at different time points were analyzed using the 16S rRNA gene through PCR-amplification of the V1-V3 regions from microbial genomic DNA, followed by Illumina MiSeq 2X300 sequencing. An analysis of the most highly represented microorganisms identified 24 bacterial Operational Taxonomic Units (OTUs), with only four showing a species-level nucleotide sequence identity to currently known or valid species. As these results indicated that the majority of bacterial species from this manure pit were unknown, a metagenomics approach was used to assemble partial to full length genomes from the two most abundant OTUs: Pit_9-00239 [5.09% - 19.44%; Clostridium saccharoperbutylacetonicum (96.60%)] and Pit_ 7-00035 [5.58% - 17.30%; Bacteroides eggerthii (87.66%)]. From genome assembly analysis, 979 contigs were generated for a combined length of 12,367,510 bp, which together included 21,776 coding sequences. Predicted metabolic functions from these contig sets included pathways involved in carbohydrate utilization (glycolysis), vitamin synthesis (riboflavin), and butyrate production (volatile fatty acids). Notably, an enzyme responsible for the production of indole, a common VOC produced from swine manure pits, was also identified. Together, the results from this analysis provide insights on metabolic capabilities of abundant bacterial species from manure pits. These can in turn be used for the future development of management strategies or products that can reduce VOC emissions that result from swine CAFO manure storage.

Year-round monitoring of three water sources in Québec, Canada, reveals site-specific differences in conditions for Cryptosporidium and Giardia contamination.

Cryptosporidium and Giardia are protozoan parasites responsible for gastrointestinal illnesses in humans and in animal species. The main way these parasites are transmitted is by ingestion of their (oo)cysts in drinking water. Monitoring (oo)cysts in water sources is beneficial to evaluate the quality of raw water supplying treatment plants. Currently, the only standardized protocol to enumerate these parasites from water samples is United States Environmental Protection Agency (USEPA) Method 1623.1. With this method, we monitored three major water sources in Quebec over a year to assess temporal and geographical variations of these parasite (oo)cysts. These three water sources have independent watersheds despite being in the same region. We found a general pattern for Giardia, with high concentrations of cysts during cold and transition periods, and significantly lower concentrations during the warm period. Cryptosporidium's concentration was more variable throughout the year. Statistical correlations (Pearson's correlation coefficients) were established between the concentration of each parasite and various environmental parameters. The three study sites each showed unique factors correlating with the presence of both protozoa, supporting the idea that each water source must be seen as a unique entity with its own particular characteristics and therefore, must be monitored independently. Although some environmental parameters could be interesting proxies to the parasitic load, no parameter was strongly correlated throughout the whole sampling year and none of the parameters could be used as a single proxy for all three studies sources.

Enhanced Detection of Heavy Metal Ions using Ag Nanoparticles and Single-Walled Carbon Nanotubes within Cu-based Metal-Organic Frameworks

Heavy metal ions (HMIs) are major water pollutants, and their toxicity for humans is a great concern for scientists and environmentalists. They are harmful to health even at trace levels; therefore, identifying and removing heavy metals from water is critical. Herein, we report highly selective and sensitive multi-analyte detection of HMIs in water using an electrochemical sensor probe based on Ag nanoparticles and single-walled carbon nanotubes incorporating copper benzene tri-carboxylate metal–organic frameworks (Ag/SWNTs@CuBTC-MOFs). The materials were characterized using FTIR, XPS, XRD, and FE-SEM with EDX mapping, TEM, TG-DTA, BET surface area, CV, and EIS. The Ag/SWNTs@CuBTC-MOF electrochemical sensor was tested by differential pulse voltammetry over a pH range of 3–10 for various HMIs. It shows high pH-dependent sensitivity towards Hg2+ (pH-5.0), Ni2+ (pH 7.0), and Fe3+ (pH 10.0) ions and a limit of detection of 1.39nM, 2.6nM, and 3.03nM, respectively. The fabricated sensor probe exhibits high selectivity, good linearity, and a detection limit below the maximum contamination limit, as the US Environmental Protection Agency suggested.

Effects of chemical composition of ambient PM2.5 measured in Seoul on potential health risks and generation of reactive oxygen species

This study assesses the health effects associated with the chemical species of ambient particulate matter (PM) with an aerodynamic diameter ≤ 2.5 μm (PM2.5) in Seoul, focusing on identifying key chemical constituents and their sources. We employed two approaches to estimate health risks: (1) evaluating carcinogenic and noncarcinogenic risks using IRIS (Integrated Risk Information System) data from the US EPA (Environmental Protection Agency), and (2) quantifying the generation of hydroxyl radicals (·OH) following exposure to PM2.5 in surrogate lung fluid (SLF). Our results show a significant impact on human health from certain elements (Cr, Ni, As, and Cd) and polycyclic aromatic hydrocarbons (PAHs) (DaeP, DahA, and BaP for carcinogenic risks; BaP and BeP for noncarcinogenic risks). Notably, Cr and BaP, which are influential in both risk assessment and ·OH generation, highlight their significant roles in human health impacts. However, other components (e.g., CPP, BaP, BghiP, BaA, CHR, PYR, FLT, Ca, Mg, and Cu), though contributors to ·OH generation, were not included in the EPA’s health risk assessment, suggesting a need for a broader PM2.5 compositional analysis to more accurately determine exposure concentrations and assess inhalation risks. These components predominantly originate from anthropogenic sources, such as combustion, vehicles, and industrial activities, underscoring the significant health implications of the pollutants emitted from these sources. The study concluded that focusing solely on the mass reduction of PM2.5 may not suffice; a dual approach that reduces both mass concentration and chemical-specific health risks is imperative for effective public health protection.

Nasal filter reveal exposure risks of inhalable particulates and heavy metals in urban women

Urban populations, especially women, are vunerable to exposure to airborne pollution, particularly inhalable particulates (PM10). Thus, more accurate measurement of PM10 levels and evaluating their health effects is critical for guiding policy to improve human health. Previous studies obtained personal PM10 with time-weighted average by air filter-based sampling (AFS), which ignores individual differences and behavioral patterns. Here, we used nasal filters instead of AFS to obtain actual inhaled PM10 under short-term exposure for urban dwelling women during a severe haze event in Beijing in 2016. The levels of six heavy metals such as As, Cd, Ni, Cr, Pb, and Co in PM10 were investigated, and carcinogenic and non-carcinogenic risks evaluated based on an adjusted US EPA health risk assessment model. The health endpoints for urban dwelling women were further assessed through an exposure-reponse model. We found that the hourly inhaled dose of PM10 obtained through the nasal filter was about 2.5–17.6 times that obtained by AFS, which also resulted in 4.41–11.30 times more morbidity than estimated by AFS (p < 0.05). Proximity to traffic emissions resulted in greater exposure to particulate matter (>18.8 μg/kg·h) and heavy metals (>2.2 ng/kg·h), and these populations are therefore at greatest risk of developing non-cancer (HI = 4.16) and cancer (Rt = 7.8 × 10−3) related morbities.

High-resolution US methane emissions inferred from an inversion of 2019 TROPOMI satellite data: contributions from individual states, urban areas, and landfills

Abstract. We quantify 2019 annual mean methane emissions in the contiguous US (CONUS) at 0.25° × 0.3125° resolution by inverse analysis of atmospheric methane columns measured by the Tropospheric Monitoring Instrument (TROPOMI). A gridded version of the US Environmental Protection Agency (EPA) Greenhouse Gas Emissions Inventory (GHGI) serves as the basis for the prior estimate for the inversion. We optimize emissions and quantify observing system information content for an eight-member inversion ensemble through analytical minimization of a Bayesian cost function. We achieve high resolution with a reduced-rank characterization of the observing system that optimally preserves information content. Our optimal (posterior) estimate of anthropogenic emissions in CONUS is 30.9 (30.0–31.8) Tg a−1, where the values in parentheses give the spread of the ensemble. This is a 13 % increase from the 2023 GHGI estimate for CONUS in 2019. We find emissions for livestock of 10.4 (10.0–10.7) Tg a−1, for oil and gas of 10.4 (10.1–10.7) Tg a−1, for coal of 1.5 (1.2–1.9) Tg a−1, for landfills of 6.9 (6.4–7.5) Tg a−1, for wastewater of 0.6 (0.5–0.7), and for other anthropogenic sources of 1.1 (1.0–1.2) Tg a−1. The largest increase relative to the GHGI occurs for landfills (51 %), with smaller increases for oil and gas (12 %) and livestock (11 %). These three sectors are responsible for 89 % of posterior anthropogenic emissions in CONUS. The largest decrease (28 %) is for coal. We exploit the high resolution of our inversion to quantify emissions from 70 individual landfills, where we find emissions are on median 77 % larger than the values reported to the EPA's Greenhouse Gas Reporting Program (GHGRP), a key data source for the GHGI. We attribute this underestimate to overestimated recovery efficiencies at landfill gas facilities and to under-accounting of site-specific operational changes and leaks. We also quantify emissions for the 48 individual states in CONUS, which we compare to the GHGI's new state-level inventories and to independent state-produced inventories. Our posterior emissions are on average 27 % larger than the GHGI in the largest 10 methane-producing states, with the biggest upward adjustments in states with large oil and gas emissions, including Texas, New Mexico, Louisiana, and Oklahoma. We also calculate emissions for 95 geographically diverse urban areas in CONUS. Emissions for these urban areas total 6.0 (5.4–6.7) Tg a−1 and are on average 39 (27–52) % larger than a gridded version of the 2023 GHGI, which we attribute to underestimated landfill and gas distribution emissions.

Impact of COVID-19 Lockdown on Inhaled Toxic Elements in PM2.5 in Beijing: Composition Characterization and Source-Specific Health Risks Assessment

In early 2020, China experienced a mass outbreak of a novel coronavirus disease (COVID-19). With an aim to evaluate the impact of emission variations on toxic element species in PM2.5 and the health risks associated with inhalation exposure during COVID-19, we collected PM2.5 filter samples in Beijing from January 1 to February 28, 2020. Positive matrix factorization (PMF) and a health risk (HR) assessment model were used to assess the health risks of the toxic elements and critical risk sources. The total concentration of eight toxic elements (Se, Cd, Pb, Zn, As, Cu, Ni, and Cr) in Beijing showed a trend of first increasing and then decreasing: full lockdown (322.9 ng m−3) &gt; pre-lockdown (264.2 ng m−3) &gt; partial lockdown (245.3 ng m−3). During the lockdown period, stringent control measures resulted in significant reductions (6−20%) in Zn, Pb, Cd, and Ni levels, while concentrations of Se, As, Cu, and Cr were unexpectedly elevated (14−348%). A total of five sources was identified: traffic emission, coal combustion, dust emission, industrial emission and mixed source of biomass burning and firework combustion. Total carcinogenic risk (TCR) of the selected toxic elements exceeded the US EPA limits for children and adults. As and Cr (IV) were the main contributors to non-carcinogenic and carcinogenic risks, respectively. For source-resolved risks, coal combustion was the main contributor to HI (43%), while industrial emissions were the main cause of TCR (45%). Additionally, increased contributions from coal combustion, biomass burning, and firework combustion during the full lockdown elevated the HI and TCR values.

Receptor model-based sources and risk assessment of metals in sediment of the coastal construction-oriented aquatic system in Bangladesh

Metal pollution in sediment from construction areas raises ecological and health concerns, yet source-based sediment pollution in Bangladesh remains understudied. Our investigation focused on fifteen locations in the Kohelia River and the coastal regions near the Matarbari projects (Matarbari Power Plant, Matarbari Deep Seaport), assessing metal concentrations' sources and impacts on ecology and human well-being. Sediment quality indices indicated high Cd and Cr contamination, with sites near Matarbari projects being the most polluted. The positive matrix factorization model identified three anthropogenic sources and mixed sources. Matarbari projects contributed significantly to As (67.9 %), Mn (50.25 %), Cd (48.35 %), and Cr (41.0 %), while ship-breaking yards contributed Fe (58.0 %), Zn (55.5 %), Pb (53.8 %), and Cu (36.1 %). Ecological indices showed different impacts on aquatic life from metal pollution, but cancer risk levels stayed below the threshold set by the US Environmental Protection Agency. These findings underscore the need for targeted measures to address metal pollution.

Association between particulate air pollution and hypertensive disorders in pregnancy: A retrospective cohort study.

Epidemiological findings regarding the association of particulate matter ≤2.5 μm (PM2.5) exposure with hypertensive disorders in pregnancy (HDP) are inconsistent; evidence for HDP risk related to PM2.5 components, mixture effects, and windows of susceptibility is limited. We aimed to investigate the relationships between HDP and exposure to PM2.5 during pregnancy. A large retrospective cohort study was conducted among mothers with singleton pregnancies in Kaiser Permanente Southern California from 2008 to 2017. HDP were defined by International Classification of Diseases-9/10 (ICD-9/10) diagnostic codes and were classified into 2 subcategories based on the severity of HDP: gestational hypertension (GH) and preeclampsia and eclampsia (PE-E). Monthly averages of PM2.5 total mass and its constituents (i.e., sulfate, nitrate, ammonium, organic matter, and black carbon) were estimated using outputs from a fine-resolution geoscience-derived model. Multilevel Cox proportional hazard models were used to fit single-pollutant models; quantile g-computation approach was applied to estimate the joint effect of PM2.5 constituents. The distributed lag model was applied to estimate the association between monthly exposure and HDP risk. This study included 386,361 participants (30.3 ± 6.1 years) with 4.8% (17,977/373,905) GH and 5.0% (19,381/386,361) PE-E cases, respectively. In single-pollutant models, we observed increased relative risks for PE-E associated with exposures to PM2.5 total mass [adjusted hazard ratio (HR) per interquartile range: 1.07, 95% confidence interval (CI) [1.04, 1.10] p < 0.001], black carbon [HR = 1.12 (95% CI [1.08, 1.16] p < 0.001)] and organic matter [HR = 1.06 (95% CI [1.03, 1.09] p < 0.001)], but not for GH. The population attributable fraction for PE-E corresponding to the standards of the US Environmental Protection Agency (9 μg/m3) was 6.37%. In multi-pollutant models, the PM2.5 mixture was associated with an increased relative risk of PE-E ([HR = 1.05 (95% CI [1.03, 1.07] p < 0.001)], simultaneous increase in PM2.5 constituents of interest by a quartile) and PM2.5 black carbon gave the greatest contribution of the overall mixture effects (71%) among all individual constituents. The susceptible window is the late first trimester and second trimester. Furthermore, the risks of PE-E associated with PM2.5 exposure were significantly higher among Hispanic and African American mothers and mothers who live in low- to middle-income neighborhoods (p < 0.05 for Cochran's Q test). Study limitations include potential exposure misclassification solely based on residential outdoor air pollution, misclassification of disease status defined by ICD codes, the date of diagnosis not reflecting the actual time of onset, and lack of information on potential covariates and unmeasured factors for HDP. Our findings add to the literature on associations between air pollution exposure and HDP. To our knowledge, this is the first study reporting that specific air pollution components, mixture effects, and susceptible windows of PM2.5 may affect GH and PE-E differently.

Evaluating Health Risks of Volatile Organic Compounds in Various UK Environments: Insights from Health Indices

The health risks of twelve volatile organic compounds (VOCs) across three sites in the UK were analysed across an 11-year period (2013–2023) using US EPA proposed health indices; Inhalation Unit Risk (IUR) and Reference Concentration (RfC) for carcinogenic and non-carcinogenic risk, respectively. Significant decreases in carcinogenic risk were observed over the study period for 1, 3-butadiene, with reductions of 63%, 36%, and 45% at urban traffic, suburban background and rural background sites, respectively. Similar decreases in the carcinogenic risk associated with benzene (52%, 28% and 27%) and toluene (50%, 38% and 51%) are found for the three site types, respectively. However, the carcinogenic risk of these three pollutants still exceeds the acceptable threshold of 1 × 10-6 at the urban traffic and suburban background sites, necessitating further emission control strategies. Conversely, the carcinogenic risk associated with isoprene has increased at the urban traffic site over the study period. The study revealed a decrease of 51%, 39% and 37% of the total non-carcinogenic risk at all three sites over the study period. The seasonal variations in carcinogenic and non-carcinogenic health risks of pollutants with anthropogenic origin exhibit winter maxima and summer minima. Moreover, diurnal variations of pollutants with anthropogenic origin demonstrate a bimodal distribution reflecting that of traffic flow, e.g., peaks around 08:00 LT and 18:00 LT, corresponding with rush hours. This trend demonstrates the influence of traffic sources supported by the characteristic species ratio whereby Toluene/Benzene (T/B) ratios were less than two (0.72, and 0.42 at suburban and rural background sites, respectively), illustrating the influence of vehicular emissions. Despite following the same bimodal trend suggesting the dominance of vehicular emission sources, mean T/B ratios at urban traffic sites were consistently above 2 for all years considered (average 2.76) suggesting other VOC sources are becoming more dominant at this site.

Applying user-centered design to improve drinking water consumer confidence reports: A Baltimore case study

The US Environmental Protection Agency is revising its policy on drinking water quality reports for consumers. These reports are intended to enhance the public’s “right to know” and to spur action to protect and promote safe water. However, these reports are known to be highly technical and difficult to access compromising their communication value. This study engaged a 10-person focus group to gather evidence on how these reports can be improved. We applied user-centered design principles to understand public drinking water consumer information needs and preferences and to develop new communication tools and methods. Through a set of in-depth interviews, we learned that most participants were unaware of the report until introduced to it during the study. The focus group participants voiced preferences for: better ways to convey technical information; more health information; a clearer understanding of costs and billing; and neighborhood or household level water quality information. Following the interviews, we convened two rounds of small group meetings to create new report designs and to review and refine the designs. The focus group developed a one-page summary statement, water contaminant trend charts, an interactive map, and other recommendations on ways to improve dissemination of the report. The project results, focus group recommendations and designs were submitted to the US Environmental Protection Agency for consideration as the policy for these reports is finalized. We believe these findings provide valuable insights into water quality communication challenges and that this approach is widely applicable and can be informative for water utilities as they prepare future reports.

Environmental assessment of phosphogypsum: A comprehensive geochemical modeling and leaching behavior study

Understanding the variations in the geochemical composition of phosphogypsum (PG) destined for storage or valorization is crucial for assessing the safety and operational efficacy of waste management. The present study aimed to investigate the environmental behavior of PG using different leaching tests and to evaluate its geochemical behavior using geochemical modeling. Regarding the chemical characterization, the PG samples were predominantly composed of Ca (23.03–23.35 wt%), S (17.65–17.71 wt%), and Si (0.75–0.82 wt%). Mineralogically, the PG samples were primarily composed of gypsum (94.2–95.9 wt%) and quartz (1.67–1.76 wt%). Moreover, the automated mineralogy revealed the presence of apatite, fluorine and malladrite phases. The overall findings of the leaching tests showed that PG could be considered as non-hazardous material according to US Environmental Protection Agency limitations. However, a high leachability of elements at a L/S of 2 under acidic conditions ([Ca] = 166.52–199.87 mg/L, [S] = 207.9–233.59 mg/L, [F] = 248.62–286.65 mg/L) is observed. The weathering cell test revealed a considerable cumulative concentration over 90 days indicating potential adverse effects on the nearby environment (S: 8000 mg/kg, F: 3000 mg/kg, P: 700 mg/kg). Based on these results, it could be estimated that the surface storage of PG could have a serious impact on the environment. In this context, a simulation model was developed based on weathering cell results showed encouraging results for treating PG leachate using CaO before its disposal. Additionally, PHREEQC was used to analyze the speciation of major elements and calculate mineral phase saturation indices in PG leaching solutions. The findings revealed pH-dependent speciation for Ca, S, P, and F. The study identified gypsum, anhydrite, and bassanite as the key phases governing the dissolution of these elements.

Hydrothermal Destruction and Defluorination of Trifluoroacetic Acid (TFA).

Per- and polyfluoroalkyl substances (PFAS) have received increased attention due to their environmental prevalence and threat to public health. Trifluoroacetic acid (TFA) is an ultrashort-chain PFAS and the simplest perfluorocarboxylic acid (PFCA). While the US EPA does not currently regulate TFA, its chemical similarity to other PFCAs and its simple molecular structure make it a suitable model compound for studying the transformation of PFAS. We show that hydrothermal processing in compressed liquid water transforms TFA at relatively mild conditions (T = 150-250 °C, P < 30 MPa), initially yielding gaseous products, such as CHF3 and CO2, that naturally aspirate from the solution. Alkali amendment (e.g., NaOH) promotes the mineralization of CHF3, yielding dissolved fluoride, formate, and carbonate species as final products. Fluorine and carbon balances are closed using Raman spectroscopy and fluoride ion selective electrode measurements for experiments performed at alkaline conditions, where gas yields are negligible. Qualitative FTIR gas analysis allows for establishing the transformation pathways; however, the F-balance could not be quantitatively closed for experiments without NaOH amendment. The kinetics of TFA transformation under hydrothermal conditions are measured, showing little to no dependency on NaOH concentration, indicating that the thermal decarboxylation is a rate-limiting step. A proposed TFA transformation mechanism motivates additional work to generalize the hydrothermal reaction pathways to other PFCAs.

Pesticide risk during commercial apple pollination is greater for honeybees than other managed and wild bees

Abstract Most pesticide research has focussed on risk to managed honeybees, but other managed and wild bees are also exposed to pesticides. Critically, we know little about the magnitude and sources of risk to honeybees compared with other bees during crop pollination. To compare pesticide exposure and risk across wild and managed bees, we sampled the main bee groups present during bloom in 20 apple orchards, including managed honeybees (Apis mellifera), managed bumblebee workers (Bombus impatiens), wild mining bees (Andrena spp. and Andrena [Melandrena] spp.), bumblebee foundress queens (Bombus impatiens) and eastern carpenter bees (Xylocopa virginica). We screened all bees for 92 pesticides and computed a Risk Quotient using available toxicity data (honeybee LD50s), adjusting for differences in toxicity known to scale with body mass. To gain insight into exposure origin, we compared residues in bees to those in focal orchard apple and dandelion flowers. Nearly all bee samples contained pesticides (95%), with the average contamination level ranging from 7.1 ± 2.8 parts per billion (ppb) in B. impatiens workers to 388.4 ± 146.2 ppb in Andrena. Exposure profiles were similar for all bees except A. mellifera, whose unique exposure profile included high levels of the neonicotinoid insecticide thiamethoxam. All bee groups except wild B. impatiens queens had at least one sample exceeding a US Environmental Protection Agency or European Food Safety Authority exposure level of concern. Apis mellifera experienced significantly greater risk than other bee groups, with 63% and 81% of samples exceeding an acute or chronic exposure level of concern, respectively. Risk to honeybees was driven primarily by high thiamethoxam levels not found in focal orchard flowers and likely originating outside the orchard. Synthesis and applications: We find that pesticide exposure and risk differ between honeybees and other managed and wild bees during apple pollination. Furthermore, pesticide exposure is a landscape‐scale phenomenon and therefore measures to reduce exposure must consider the surroundings beyond focal farms. Limiting orchard sprays, while reducing on‐farm exposures, will not protect far‐foraging bees from off‐farm exposures such as thiamethoxam, which we hypothesize is coming from nearby seed‐treated corn fields planted during apple bloom.