EPA National Research Articles

Estimates of Lake Nitrogen, Phosphorus, and Chlorophyll‐a Concentrations to Characterize Harmful Algal Bloom Risk Across the United States

AbstractExcess nutrient pollution contributes to the formation of harmful algal blooms (HABs) that compromise fisheries and recreation and that can directly endanger human and animal health via cyanotoxins. Efforts to quantify the occurrence, drivers, and severity of HABs across large areas is difficult due to the resource intensive nature of field monitoring of lake nutrient and chlorophyll‐a concentrations. To better characterize how nutrients interact with other environmental factors to produce algal blooms in freshwater systems, we used spatially explicit and temporally matched climate, landscape, in‐lake characteristic, and nutrient inventory data sets to predict nutrients and chlorophyll‐a across the conterminous US (CONUS). Using a nested modeling approach, three random forest (RF) models were trained to explain the spatiotemporal variation in total nitrogen (TN), total phosphorus (TP), and chlorophyll‐a concentrations across US EPA's National Lakes Assessment (n = 2,062). Concentrations of TN and TP were the most important predictors and, with other variables, the RF model accounted for 68% of variation in chlorophyll‐a. We then used these RF models to extrapolate lake TN and TP predictions to lakes without nutrient observations and predict chlorophyll‐a for ∼112,000 lakes across the CONUS. Risk for high chlorophyll‐a concentrations is highest in the agriculturally dominated Midwest, but other areas of risk emerge in nutrient pollution hot spots across the country. These catchment and lake‐specific results can help managers identify potential nutrient pollution and chlorophyll‐a hot spots that may fuel blooms, prioritize at‐risk lakes for additional monitoring, and optimize management to protect human health and other environmental end goals.

Development of a source-specific biomass burning emissions inventory for Washington, Oregon, and California

While wildfires are the dominant source of biomass burning emissions across the U.S., prescribed and agricultural burns also contribute to emissions and ambient air quality. Understanding the differential impacts that these different sources of biomass burning have on air quality and public health is important in the development of effective exposure reduction strategies. We leverage the high-resolution Fire INventory from NCAR (FINN) to develop a source-specific biomass burning emission inventory that distinguishes between wildfire, prescribed burn, and agricultural burn sources across Washington, Oregon, and California. We describe the methodology for reclassifying FINN using multiple national and state-level fire and fuel treatment inventories and present the results of the emissions reclassification process for these three states from 2012 to 2020. We matched 72%, 78% and 81% of FINN emissions event locations to fire locations from the fire type input datasets in Washington, Oregon, and California, respectively. When compared to county-level fire type-specific PM2.5 emissions estimates from the 2014, 2017, and 2020 EPA National Emissions Inventory, we found greater agreement among wildfire-specific estimates across years and states (R2 range: 0.59–0.98), relative to prescribed (R2 range: 0.12–0.73) and agricultural burns (R2 range: 0.43–0.95). This fire type-specific biomass burning emissions inventory can be used in air pollution transport models to better understand the impacts of each of these sources on air quality across the region along with downstream public health impacts.

1210-P: Associations of Community-Level Social Determinants of Health and Hypertensive Disorders of Pregnancy

Objective: To determine whether community-level social determinants of health are associated with hypertensive disorders of pregnancy (HDP). Methods: This is a secondary analysis from the prospective Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-To-Be. We evaluated three community-level exposures using home addresses geocoded at the census-tract level: 1) socioeconomic disadvantage by the 2015 Area Deprivation Index (ADI); 2) food insecurity by the USDA Food Access Research Atlas; and 3) less walkability by the EPA National Walkability Score. The outcome was new onset HDP. Poisson regression was used to estimate adjusted relative risks (aRR). Results: Of 9,062 individuals, 33.6% were in the highest tertile of ADI, 24.5% lived with food insecurity, and 66.3% lived in a less walkable neighborhood. 13.0% were diagnosed with HDP. Individuals living in a community with higher socioeconomic disadvantage, (aRR T2: 1.26; 95% CI: 1.10, 1.44; and T3: 1.19; 95% CI: 1.02, 1.38), food insecurity (aRR: 1.15; 95% CI: 1.02, 1.29), and less walkability (aRR: 1.21; 95 CI: 1.07, 1.36) were at higher risk of developing HDP compared with those who did not. Conclusions: Community-level social determinants of health, including socioeconomic disadvantage, food insecurity, and low walkability, were associated with increased risk of HDP among nulliparous individuals. Disclosure T.Bank: None. W.Grobman: None. J.Wu: None. C.Lynch: None. K.K.Venkatesh: None.

1183-P: Association of Community-Level Social Determinants of Health and Pregestational and Gestational Diabetes

Objective: To determine whether community-level adverse social determinants of health are associated with increased risk of pregestational and gestational diabetes (DM, GDM). Methods: We conducted a secondary analysis from the prospective cohort Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-To-Be. We evaluated three community-level exposures using home addresses geocoded at the census-tract level: 1) socioeconomic disadvantage by 2015 Area Deprivation Index (ADI); 2) food insecurity by USDA Food Access Research Atlas; and 3) walkability by EPA National Walkability Score. The outcomes were DM and GDM. Results: Of 9,155 assessed individuals, 33.6% were in the highest tertile (T3) of ADI, 24.4% lived in a food-insecure community, and 33.7% lived in a less walkable neighborhood; 1.5% (n=137) had DM and 4.2% (n=380) developed GDM. Individuals living in a community in the highest tertile of ADI were more likely to have DM (aOR: 2.49; 95% CI: 1.48, 4.18) and GDM (aOR: 1.49; 95% CI: 1.13, 1.97). Individuals living in a food-insecure community (aOR: 1.49; 95% CI: 1.17, 1.89) and living in a less walkable neighborhood (aOR: 1.29; 95% CI: 1.03, 1.62) were more likely to have GDM, but not DM. Conclusions: Multiple measures of community-level adverse social determinants of health were associated with an increased risk of developing GDM. Only socioeconomic disadvantage was associated with DM. Disclosure C.P.Field: None. W.Grobman: None. J.Wu: None. C.Lynch: None. K.K.Venkatesh: None. Funding Eunice Kennedy Shriver National Institute of Child Health and Human Development

Hazardous and contaminated sites within salt marsh migration corridors in Rhode Island, USA

As salt marshes attempt to migrate upland due to sea level rise, they will encounter many kinds of land development and infrastructure in highly populated, urbanized coastal communities. Hazardous and contaminated sites (HCSs) -- facilities and infrastructure that store, use, or release harmful substances -- are particularly concerning obstacles to salt marsh migration because of their potential to release contaminants if their structural integrity is compromised. Inventorying HCSs within migration pathways can inform coastal resilience planning. To understand what kinds of HCSs migrating marsh may encounter in Rhode Island, USA, we inventoried sites from federal and state sources, assigned contaminant hazard rankings to most sites, and overlayed them with projected marsh migration corridors. We found that HCSs are extensive across marsh migration corridors in the state, especially in urban areas. Among the most common HCSs in and around Rhode Island salt marshes are stormwater outfalls, underground storage tanks, and facilities registered with EPA's Resource Conservation and Recovery Act (RCRA) or EPA's National Pollutant Discharge Elimination System (NPDES). These sites pose varying hazards to human and aquatic life if breached, with some sites representing little or no threat but most posing some degree of hazard to their surroundings. This coastal HCSs inventory can inform prioritization and management of coastal salt marshes subject to accelerated sea level rise. Management decisions such as allowing marsh migration, implementing adaptation actions to build salt marsh elevation, or erecting physical barriers at marsh sites will influence future salt marsh extent, marshes' ability to provide ecosystem services, and public health exposures to toxic releases. In addition, as Rhode Island and other coastal states work to promote coastal resiliency, this type of inventory can inform decisions about which HCSs to prioritize for remediation and other climate adaptation actions. Marsh migration is just one potential consequence of sea level rise, so many of the considerations outlined here are widely applicable to the broader goal of preparing coastal communities for rising seas.

Can Column Formaldehyde Observations Inform Air Quality Monitoring Strategies for Ozone and Related Photochemical Oxidants?

AbstractFormaldehyde column density (ΩHCHO) showed a potentially useful correlation with surface ozone during the LISTOS campaign on Long Island Sound and the KORUS‐AQ campaign in Seoul, South Korea. This builds on previous work that identified this relationship from in situ aircraft observations with similar findings for ground‐based and airborne remote sensing of ΩHCHO. In the Long Island Sound region, ΩHCHO and surface ozone exhibited strong temporal (r2 = 0.66) and spatial (r2 = 0.73) correlation. The temporal variability in ΩHCHO (∼1 Dobson units [DU]) was larger than the range in the spatial average (∼0.1 DU). The spatial average is most useful for informing ozone monitoring strategies, demonstrating the challenge in using ΩHCHO satellite data sets for this purpose. In Seoul, high levels of NO2 resulted in Ox better correlating with ΩHCHO than surface ozone due to titration effects. The ΩHCHO–Ox relationship may therefore reflect the sum of surface ozone and related photochemical oxidants, relevant to air quality standards set to regulate this quantity such as the U.S. EPA National Ambient Air Quality Standard (NAAQS). The relationship of ΩHCHO to Ox shifted in Seoul during the campaign demonstrating the need to evaluate this relationship over longer time periods. With sufficient precision in future satellite retrievals, ΩHCHO observations could be useful for evaluating the adequacy of surface air quality monitoring strategies.

Geospatial Patterns of Antimicrobial Resistance Genes in the US EPA National Rivers and Streams Assessment Survey.

Antimicrobial resistance (AR) is a serious global problem due to the overuse of antimicrobials in human, animal, and agriculture sectors. There is intense research to control the dissemination of AR, but little is known regarding the environmental drivers influencing its spread. Although AR genes (ARGs) are detected in many different environments, the risk associated with the spread of these genes to microbial pathogens is unknown. Recreational microbial exposure risks are likely to be greater in water bodies receiving discharge from human and animal waste in comparison to less disturbed aquatic environments. Given this scenario, research practitioners are encouraged to consider an ecological context to assess the effect of environmental ARGs on public health. Here, we use a stratified, probabilistic survey of nearly 2000 sites to determine national patterns of the anthropogenic indicator class I integron Integrase gene (intI1) and several ARGs in 1.2 million kilometers of United States (US) rivers and streams. Gene concentrations were greater in eastern than in western regions and in rivers and streams in poor condition. These first of their kind findings on the national distribution of intI1 and ARGs provide new information to aid risk assessment and implement mitigation strategies to protect public health.

Curation of a list of chemicals in biosolids from EPA National Sewage Sludge Surveys & Biennial Review Reports

Section 405(d) of the Clean Water Act requires the US Environmental Protection Agency to review sewage sludge regulations every two years to identify any additional pollutants that may occur in biosolids and to set regulations for pollutants identified in biosolids if sufficient scientific evidence shows they may harm human health or the environment. To date, EPA has conducted eight biennial reviews to identify chemical and microbial pollutants and three national sewage sludge surveys to identify pollutants and obtain concentration data for chemicals found in biosolids. Prior to 2021, there was inconsistent reporting of chemicals identified and EPA did not cumulatively track chemicals in biosolids. Through the efforts presented here, EPA produced a list of 726 chemicals and structure-based classes found in biosolids based on biennial reviews and national sewage sludge surveys. Summary statistics of concentration data are also reported for the 484 chemicals found in the three national sewage sludge surveys. The creation of the Biosolids List supports EPA in assessing the potential risk of chemical pollutants found in biosolids.

δ15N of Chironomidae: An index of nitrogen sources and processing within watersheds for national aquatic monitoring programs

Nitrogen (N) removal along flowpaths to aquatic ecosystems is an important regulating ecosystem service that can help reduce N pollution in the nation's waterways, but can be challenging to measure at large spatial scales. Measurements that integrate N processing within watersheds would be particularly useful for assessing the magnitude of this vital service. Because most N removal processes cause isotopic fractionation, δ15N from basal food-chain organisms in aquatic ecosystems can provide information on both N sources and the degree of watershed N processing. As part of EPA's National Aquatic Resource Surveys (NARS), we measured δ15N of Chironomidae collected from over 2000 lakes, rivers and streams across the continental USA. Using information on N inputs to watersheds and summer total N concentrations ([TN]) in the water column, we assessed where elevated chironomid δ15N would indicate N removal rather than possible enriched sources of N. Chironomid δ15N values ranged from −4 to +20‰, and were higher in rivers and streams than in lakes, indicating that N in rivers and streams underwent more processing and cycling that preferentially removes 14N than N in lakes. Chironomid δ15N increased with watershed size, N inputs, and water chemical components, and decreased as precipitation increased. In rivers and streams with high watershed N inputs, we found lower [TN] in streams with higher chironomid δ15N values, suggesting high rates of gaseous N loss such as denitrification. At low watershed N inputs, the pattern reversed; streams with elevated chironomid δ15N had higher [TN] than streams with lower chironomid δ15N, possibly indicating unknown sources elevated in δ15N such as legacy N, or waste from animals or humans. Chironomid δ15N values can be a valuable tool to assess integrated watershed-level N sources, input rates, and processing for water quality monitoring and assessment at large scales.

Assessing Evidence of Phosphorus Concentration Trends in North American Fresh Waters.

The U.S. EPA's National Aquatic Resource Surveys (NARS) documented evidence of widespread, unexplained total phosphorus (TP) concentration increases in lakes and streams across the United States during the 2000 - 2012 time period. To examine the robustness of evidence for this trend, we used additional monitoring datasets to calculate rates of TP change in thousands of individual waterbodies across the U.S. during the same time frame, and compared them against TP change rates calculated in the same manner for waterbodies that were resurveyed under NARS in different years. For the additional datasets, median rates of TP change were substantially lower than median rates calculated using NARS data. To further examine differences between NARS and non-NARS results in specific waterbodies, we assembled composite datasets for 52 predominantly northern lakes that by chance had been sampled under both NARS and other sampling programs during the same time frame. Using only NARS data, the median calculated TP change rate for this set of lakes was positive, and similar to that for the larger set of 401 resurveyed NARS lakes. However, when additional sample data were included, the median calculated TP change rate for these lakes was much lower. Results suggest that increasing TP concentrations in waterbodies may not have been as ubiquitous as suggested. They also illustrate a need to supplement randomized continental-scale monitoring with detailed, site-focused investigations.

Long-term air pollution exposure and incident stroke in American elderly population: a national cohort study

BACKGROUND AND AIM: Literature has linked air pollution and cerebrovascular diseases including stroke. However, evidence is limited for the simultaneous effects of multiple air pollutants on stroke incidence. METHODS: A nationwide population-based open cohort study was used to estimate the association between long-term exposure to PM2.5, NO2, ozone, and stroke incidence. The study population included all free-for-service Medicare enrollees (aged ≥65 years) in the contiguous United States from 2000-2017. We estimated the hazard ratios (HRs) for the first diagnosis with stroke using single-, bi-, and tri-pollutant Cox proportional hazards models that controlled for demographic characteristics, Medicaid eligibility, and area-level covariates. We further looked at this relationship in two sub-cohorts of enrollees who were always exposed to pollutant levels below the US EPA National Ambient Air Quality Standards [NAAQS] (annual PM2.5 ≤12 μg/m³, annual NO2 ≤53 ppb, and warm-season ozone ≤50 ppb) and the WHO air quality guideline (annual PM2.5 ≤10 μg/m³, annual NO2 ≤20 ppb, and warm-season ozone ≤40 ppb). RESULTS:Increases of 10 μg/m³ in PM2.5, 10 ppb in NO2, and 10 ppb in ozone were associated with increased risk of first diagnosis with stroke, with HRs of 1.063 (95% CI, 1.048-1.077), 1.048 (1.043-1.052), and 1.031 (1.026-1.037), respectively. Among the below EPA low-exposure sub-cohort, the corresponding HRs were 1.041 (95% CI, 1.008-1.075), 1.067 (1.056-1.077), and 1.123 (1.108-1.138), respectively. When restricting analyses to levels below the WHO air quality guidelines, increasing pollution levels were consistently associated with a greater hazard estimate. CONCLUSIONS:Long-term exposure to air pollution, even at concentrations below NAAQS or international standards, was significantly associated with increased stroke incidence among the US elderly population. KEYWORDS: Air pollution, Multi-pollutant, Stroke

Association between chronic obstructive pulmonary disease and long-term ozone and PM2.5 exposure among Medicare participants: a national cohort study

BACKGROUND AND AIM: Chronic obstructive pulmonary disease (COPD) is the third leading cause of death globally and both ozone and PM2.5 exposures are main risk factors. However, few studies have investigated the association of long-term ambient ozone exposure with respiratory morbidity and its simultaneous effect with PM2.5. METHODS: A nationwide population-based open cohort study was used to estimate the association between long-term exposure to ambient ozone, PM2.5 and COPD incidence. The study population included all Medicare enrollees (aged ≥65 years) who were always enrolled in Medicare free-for-service program and in both Medicare Part A (hospital insurance) and Part B (medical insurance) in the contiguous United States from 2000-2016. We estimated the hazard ratios (HRs) for the first diagnosis with COPD using single- and co-pollutant Cox proportional hazards models that controlled for demographic characteristics, Medicaid eligibility, and area-level covariates. We further looked at this relationship at lower pollutant concentrations, restricting Medicare enrollees who were always exposed to pollutant levels below the US EPA National Ambient Air Quality Standards [NAAQS] (annual PM2.5 ≤12 μg/m³ and warm-season ozone ≤50 ppb), and among potentially susceptible subgroups. RESULTS:Among the full cohort of 18.9 million enrollees, increases of 10 ppb in annual warm-season ozone and 10 μg/m³ in annual PM2.5 were associated with increased risk of first diagnosis with COPD, with HRs of 1.048 (1.039-1.057) and 1.054 (95% CI, 1.036-1.072) in the co-pollutant model, respectively. When restricting analyses to the below EPA low-exposure sub-cohort (9.6-million enrollees), the corresponding HRs were 1.160 (1.142-1.178) for exposure to ozone and 1.109 (95% CI, 1.068-1.151) for exposure to PM2.5. CONCLUSIONS:Both long-term ozone and PM2.5 exposures were associated with increased risk of COPD incidence among the US elderly population, even at concentrations below the current NAAQS standards. KEYWORDS: Air pollution, Multi-pollution, Chronic obstructive pulmonary disease

Adaptive management as a foundational framework for developing collaborative estuary management programs

Collaborative nonregulatory programs can benefit the long-term sustainability of environmental resources. Such programs benefit from extensive planning and assessment relative to ecological systems as well as public participation. While many programs use adaptive management as a guiding programmatic framework, few programs successfully integrate social and human context into their adaptive management frameworks. While this adaptive governance framework can be successful, many potential challenges arise when incorporating public stakeholders into the adaptive management framework. To reduce those challenges, programs need participation from diverse stakeholder groups that represent multiple communities of interest, place, and identity. The participatory process benefits from a diverse group of stakeholders and can result in successful management of environmental resources. We highlight the participatory co-management process of three newly developing nonregulatory programs that are modeled after the United States EPA's National Estuary Program in the Perdido and Pensacola Bay systems, Choctawhatchee Bay, and the St. Andrew and St. Joseph Bay systems (Florida USA). This case study illustrates how collaborative nonregulatory programs can be implemented not only in the United States, but also in other regions of the world.

Context is Everything: Interacting Inputs and Landscape Characteristics Control Stream Nitrogen.

To understand the environmental and anthropogenic drivers of stream nitrogen (N) concentrations across the conterminous US, we combined summer low-flow data from 4997 streams with watershed information across three survey periods (2000-2014) of the US EPA's National Rivers and Streams Assessment. Watershed N inputs explained 51% of the variation in log-transformed stream total N (TN) concentrations. Both N source and input rates influenced stream NO3/TN ratios and N concentrations. Streams dominated by oxidized N forms (NO3/TN ratio > 0.50) were more strongly responsive to the N input rate compared to streams dominated by other N forms. NO3 proportional contribution increased with N inputs, supporting N saturation-enhanced NO3 export to aquatic ecosystems. By combining information about N inputs with climatic and landscape factors, random forest models of stream N concentrations explained 70, 58, and 60% of the spatial variation in stream concentrations of TN, dissolved inorganic N, and total organic N, respectively. The strength and direction of relationships between watershed drivers and stream N concentrations and forms varied with N input intensity. Model results for high N input watersheds not only indicated potential contributions from contaminated groundwater to high stream N concentrations but also the mitigating role of wetlands.

An Examination of National Cancer Risk Based on Monitored Hazardous Air Pollutants.

Background:Hazardous air pollutants, or air toxics, are pollutants known to cause cancer or other serious health effects. Nationwide cancer risk from these pollutants is estimated by the U.S. EPA National Air Toxics Assessment. However, these model estimates are limited to the totality of the emissions inventory used as inputs, and further, they cannot be used to examine spatial and temporal trends in cancer risk from hazardous air pollutants.Objectives:To complement model estimates of nationwide cancer risk, we examined trends in cancer risk using monitoring data from 2013 to 2017 across the 27 U.S. National Air Toxics Trends Stations.Methods:For each monitoring site, we estimated cancer risk by multiplying the annual concentration for each monitored pollutant by its corresponding unit risk estimate. We examined the 5-y average (2013–2017) cancer risk across sites and the population levels and demographics within 1-mi of the monitors, as well as changes in estimated cancer risk over time. Finally, we examined changes in individual pollutant concentrations and their patterns of covariance.Results:We found that the total estimated cancer risk is higher for urban vs. rural sites, with the risk at seven urban sites (of 21) above 75 in 1 million. Furthermore, while most pollutant concentrations have not changed over the time period explored, we found 38 site-pollutant combinations that significantly declined and 12 that significantly increased between 2013 and 2017. We also identified a positive correlation between estimated cancer risk and percent of the population within 1-mi of a monitor that is low income.Discussion:Long-term trends show that annual mean concentrations of most measured air toxics have declined. Our evaluation of a more recent snapshot in time finds that most pollutant concentrations have not changed from 2013 to 2017. This analysis of cancer risk based on monitored values provides an important complement to modeled nationwide cancer risk estimates and can further inform future approaches to mitigate risk from exposure to hazardous air pollutants. https://doi.org/10.1289/EHP8044

Satellite Formaldehyde to Support Model Evaluation.

Formaldehyde (HCHO), a known carcinogen classified as a hazardous pollutant by the United States Environmental Protection Agency (U.S. EPA), is measured through monitoring networks across the U.S. Since these data are limited in spatial and temporal extent, model simulations from the U.S. EPA Community Multiscale Air Quality (CMAQ) model are used to estimate ambient HCHO exposure for the EPA National Air Toxics Assessment (NATA). Here, we employ satellite HCHO retrievals from the Ozone Monitoring Instrument (OMI)-the NASA retrieval developed by the Smithsonian Astrophysical Observatory (SAO), and the European Union Quality Assurance for Essential Climate Variables (QA4ECV) retrieval-to evaluate three CMAQ configurations, spanning the summers of 2011 and 2016, with differing biogenic emissions inputs and chemical mechanisms. These CMAQ configurations capture the general spatial and temporal behavior of both satellite retrievals, but underestimate column HCHO, particularly in the western U.S. In the southeastern U.S., the comparison with OMI HCHO highlights differences in modeled meteorology and biogenic emissions even with differences in satellite retrievals. All CMAQ configurations show low daily correlations with OMI HCHO (r = 0.26 - 0.38), however, we find higher monthly correlations (r = 0.52 - 0.73), and the models correlate best with the OMI-QA4ECV product. Compared to surface observations, we find improved agreement over a 24-hour period compared to afternoon-only, suggesting daily HCHO amounts are captured with more accuracy than afternoon amounts. This work highlights the potential for synergistic improvements in modeling and satellite retrievals to support near-surface HCHO estimates for the NATA and other applications.

Characterization of the effectiveness of a hydrocarbon liquid solidifier

Solidifiers are dry, granular hydrophobic polymers that form physical bonds with hydrocarbons by molecular interactions (hydrogen bonding, London forces), and are used to immobilize hydrocarbon spill propagation and dispersion. CIAgent© is a non-toxic, proprietary polymer blend listed as an “Oil Solidifier” on the EPA's National Contingency Plan Product Schedule for use on hydrocarbon spills in the navigable waterways of United States. CIAgent solidifies the liquid hydrocarbons through a rapid transformation into a cohesive rubber-like inert mass upon contact and retains the liquid for easier removal and disposal. The objective of this paper is to determine the effectiveness of the solidifier with a variety of hydrocarbon liquids that could be encountered in an oil spill scenario. The effectiveness of the solidifier was characterized in terms of the application rate, temperature change, solubility parameters and solidification time for a variety of hydrocarbon liquids (e. g., gasoline, diesel fuel, crude oil) that could be encountered by measuring the heat of solidification using a solution calorimeter. A thermogram was obtained and the heat of solidification was calculated using the temperature difference upon solidification. The temperature change and the degree of swelling in the solidifier were used to determine the solubility parameter of the solidifier (6.77 Hildebrands). The heat of solidification value was used to determine the ease and speed of the solidification of the hydrocarbon liquids. Solidification times ranged from 40 to 120 s for the liquids tested. The average application ratio in weight of solidifier to weight of hydrocarbon ranged was 3.35.

Assessment of the Near-Road (monitoring) Network including comparison with nearby monitors within U.S. cities

Emissions from on-road mobile sources have historically been an important anthropogenic contributor to ambient air pollution leading to high levels of air pollution near major roadways. The U.S. EPA recently implemented the Near-Road (monitoring) Network to measure NO2 concentrations by high-traffic roadways in urban centers throughout the U.S., as these locations were believed to characterize worst-case human exposures to traffic-related air pollutants. Many near-road sites also include PM2.5 and CO measurements, which along with the NO2 observations, were compared in a pairwise manner against non-near-road monitors located within the city-scale boundary. After controlling for primary emissions from the target highways, we found the PM2.5 concentration difference (i.e. near-road concentration minus non-near-road site concentration) between the near-road and non-near-road urban sites to be δ = 0.42 µg m−3( H0: µdiff = 0; Ha: µdiff > 0 (µnon-near-road > µnear-road); p = 0.051; α = 0.05, 95% CI: −0.08–0.90 µg m−3, n = 35 comparisons). NO2 and CO levels were on average higher at the near-road sites compared to the non-near-road urban sites by 5.0 (95% CI: 3.4–6.5) ppb (n = 44 comparisons) and 9.2 × 10−2( 95% CI: 0.04–0.14) ppm (n = 42 comparisons), respectively. The average PM2.5 difference found here is 5%, and at 14 of the 35 (∼40%) urban monitor comparisons and 28 of the 72 (∼39%) overall comparisons, PM2.5 is actually higher at the non-near-road site relative to its near-road pair. Cleaner vehicle fleets, formation of secondary PM from on-road emissions occurring downwind (i.e. away from the road), decreased secondary organic aerosol (SOA) formation rates in the near-road environment, the prevalence of other low-volume vehicular and local, non-vehicular sources of emissions at the non-near-road sites (e.g. railyards, truck yards, ports, biomass-fueled heating, backyard barbecuing, and commercial cooking, etc) and local meteorology (e.g. wind speed and wind direction) explain this finding. The wintertime PM2.5 concentration difference was higher than the other seasons, likely a result of higher primary PM2.5 tailpipe emissions and lower temperatures that both reduced near-road PM volatility and decreased photochemical activity resulting in lower SOA production at the urban scale. Further, all near-road NO2 and CO concentrations were below the annual and hourly NAAQS, while eight (most of which were in wildfire-prone locations) of the 94 PM2.5 sites used in this study were above the annual National Ambient Air Quality Standards. In addition, strong agreement with both annual average daily traffic and fleet-equivalent AADT were found for near-road NO2 and CO concentrations, while weaker, but still positive relationships were found for near-road PM2.5 levels. Lastly, same observational data was used to assess on-road mobile source emission estimates from the EPA National Emission Inventory, and analysis of the observations are in rough agreement with the current ratio of NOx to CO emissions from on-road mobile sources.

Emissions of particulate matter due to Marcellus Shale gas development in Pennsylvania: Mapping the implications

Over the past decade, the shale gas boom has led to increasing public concerns regarding communities' exposure to air pollutants from shale gas development resulting in concentrations higher than the EPA's National Ambient Air Quality Standards. This study investigates the sufficiency of current policy in Pennsylvania to protect people from exposure to fine particulate matter (PM2.5) emissions from such development. We used a Gaussian plume model to simulate PM2.5 concentrations over the Marcellus shale region of Pennsylvania, and using census block data, we estimated the potential number of people who experienced exceedance of the PM2.5 standard between 2005 and 2017. Results demonstrate that these emissions could increase the number of exceedances by more than 36,000 persons in a single year which is almost 1% of the Marcellus shale regional population in Pennsylvania. This number has largely been proportional to the overall number of developed wells, but development histories show that similar levels of development could occur with reduced population exposure. Setback policy is shown to be an effective method to reduce exposure exceedances, but results suggest that it should be revised based on the number of wells per wellpad as well as the local conditions to further limit air quality impacts.

Predicting atrazine concentrations in waterbodies across the contiguous United States: The importance of land use, hydrology, and water physicochemistry

AbstractAtrazine contamination is ubiquitous in North American surface waters, but the dependency of the herbicide's distribution on landscape and within‐lake processes is currently poorly known. We sought to identify novel predictors of atrazine and to build a coherent framework to model its concentration in waterbodies through the development of binomial‐gamma hurdle models and LASSO regression models. We constructed models for over 900 waterbodies in the contiguous United States using data from the 2012 U.S. EPA National Lake Assessment, the 2012 U.S. Department of Agriculture CropScape and the Global HydroLAB HydroLAKES databases. Atrazine was detected in 32% of U.S. waterbodies, with a mean concentration of 0.17 μg L−1 when detected. The two‐part hurdle model explained as much as 75% of the variance in atrazine across a spatially and temporally heterogeneous landscape. Three predictors explained 31% of the variability in atrazine detection in U.S. waterbodies, where the proportion of corn + soy cultures in the watershed was the most important variable. Once atrazine was detected, our models explained an additional 29% of the variability in atrazine concentrations, where the estimated areal weight of atrazine application (kg atrazine km2) in the watershed was the most important predictor. Spatially, water quality variables associated with eutrophication were linked to increased levels of atrazine contamination while cooler water temperatures and natural lakes and landscapes were associated with decreased levels of contamination. Our results suggest that changes in land‐use practices may be the most effective way to mitigate atrazine contamination in waterbodies.