Annotated Bibliography for Environmental Justice Research 2016-2019
Health Disparities and Cumulative Impacts
Links below, where available, lead directly to citations in EPA's Science Inventory. Scroll down for annotations for each entry.
Children from tribes are disproportionately burdened with adverse respiratory well-being outcomes. Respiratory disease is a leading cause of hospitalizations for American Indian/Alaska Native (AI/AN) children between ages 1-14. According to the U.S. Department of Health and Human Services, as of 2015, AI/AN children had a 60% higher likelihood of having asthma than non-Hispanic White children. Physical, chemical, social, or biological stressors from AI/AN children’s everyday environment may contribute to this increased burden of adverse respiratory health and well-being outcomes.
In this study, researchers investigated potential stressors from the built and natural environments for tribal school-aged children at nine school sites across three ecoregions: North American Deserts, Northern Forests, and Mediterranean California. Outdoor air concentrations around the 9 tribal schools (across 7 tribes, 5 U.S. States) were linked to National Emission Inventories, ecoregions and National Land Cover Database, and American Community Survey and school map layers.
Researchers identified the closest emission sources to the schools as oil, gas, airport, and manufacturing facilities. Outdoor air pollutant monitoring was conducted at the nine school sites by tribal staff with technical support from the Tribal Air Monitoring Support Center. Maximum annual outdoor air concentrations for toluene were at a school located four miles from a solid waste landfill (29 ppb in 2011). Maximum annual concentrations of metals in particulate matter 10 micrometers and smaller were highest for manganese (68 ng/m3 in 2011). Air quality measurements were limited, and closest emissions sources were primarily off tribal lands. Compared to schools off tribal lands, schools on tribal lands were further away from roadway sources.
Future research may examine indoor air quality and outdoor air quality around schools with more developed land to characterize tribal children’s total exposure to potential stressors.
Smoke from wildland fires has become one of the leading sources of short-term exposure to poor air quality in the United States. Exposure to fine particulate matter (PM2.5), the air pollutant found in smoke with the highest concern for human health, is correlated with adverse cardiovascular and respiratory effects. Specific demographic groups, including children and older adults, may be particularly susceptible to the effects of poor air quality and exposure to PM2.5. The effects of exposure to air pollution during wildland fires as compared to exposures from other sources are not well understood.
This study investigated the health effects of wildland fire smoke exposure in older adults. Researchers evaluated associations between cardiopulmonary hospitalizations among Medicare recipients ≥65 y of age, and exposure to PM2.5 during and outside wildland fire smoke periods across 692 counties. To determine exposure to PM2.5, researchers used the Community Multiscale Air Quality (CMAQ) model and daily PM2.5 concentrations from monitoring sites. Air quality with and without emissions from wildland fires was simulated using the CMAQ framework, and “smoke days” were defined as indicators when the wildland fire-specific contribution of PM2.5 was greater than 5 μg/m3.
The percentage difference in all-cause cardiovascular and respiratory hospitalizations associated with a 10-μg/m3 increase PM2.5 related to wildland fire smoke (smoke days) was similar to the percentage difference associated with a 10-μg/m3 increase in non-wildfire related PM2.5 (non-smoke days). However, for asthma, bronchitis, and wheezing hospitalizations, the association with PM2.5 was greater during periods of wildland fire smoke compared with non-smoke ambient PM2.5.
The finding that that asthma and respiratory effects of PM2.5 from wildland smoke are stronger than those of PM2.5 from other sources can help inform targeted risk-messaging during wildland fires.
Urban areas face challenges including vehicular emissions, stormwater runoff, and sedentary lifestyles. Communities recognize the value of trees in mitigating these challenges by absorbing pollution and enhancing walkability. Siting trees to optimize multiple benefits requires a systems approach that may cross sectors of management and expertise.
This study presents a spatially-explicit method to optimize tree planting in Durham, NC, a rapidly growing urban area with an aging tree stock. Using GIS data and a ranking approach, researchers explored how Durham could augment its current stock of willow oaks with 10,000 mid-sized deciduous trees. Census block groups were ranked for tree planting according to single and multiple objectives including stormwater reduction, emissions buffering, walkability, and protection of vulnerable populations. Prioritizing tree planting based on single objectives led to four sets of locations with limited geographic overlap. Prioritizing tree planting based on multiple objectives tended to favor historically disadvantaged census block groups.
Results showed that the multiple-objective strategy met the largest proportion of estimated regional need, and that any strategy which included the protection of vulnerable populations generated more benefits than others. The City of Durham implemented a seven-year plan to plant 10,000 trees in priority neighborhoods based on the study’s findings.
Citizen science provides quantitative results to support environmental health assessments, but standardized approaches do not currently exist to translate findings into actionable solutions. Data collection, analysis, interpretation, visualization, and communication are subjective processes that need to be tailored to an audience capable of making decisions to improve environmental health, such as community groups or local policy makers.
In this study, researchers analyzed two case studies of citizen science-based EHAs; a citizen science air quality sensor project in Newark, NJ, and an assessment of possible environmental stressors in Newport News, VA. The two citizen-science projects, alongside decades of experience in collaborative projects, contributed to three lessons learned and a set of frequently asked questions (FAQs). The lessons and FAQs address the complexities of environmental health and interpersonal relations often found in multi-partner citizen science efforts.
While data can characterize environmental health conditions, people are the impetus for change. These lessons and FAQs provide advice to translate citizen science research into actionable solutions in the context of the diverse range of environmental health issues and local stakeholders.
Metabolic syndrome is a combination of cardiovascular traits including hypertension, insulin resistance, and abdominal obesity which lead to an increased risk for cardiovascular disease, Type 2 diabetes, and other serious conditions. Development of metabolic syndrome can be linked to both chemical and nonchemical factors, including socioeconomic status. Phthalates, synthetic chemicals found commonly in consumer products such as food packaging, have been linked to several risk factors for metabolic syndrome. However, research on the association between phthalates and metabolic syndrome is limited.
This study explored the association between phthalates and metabolic syndrome. To accomplish this, researchers investigated relationships between urinary phthalate metabolite concentrations (i.e., mono-ethyl phthalate (MEP), mono-n-butyl phthalate (MnBP), mono-isobutyl phthalate (MiBP), mono-benzyl phthalate (MBzP), mono-(3-carboxylpropyl) phthalate (MCPP), and di(2-ethylhexyl phthalate (DEHP)) and metabolic syndrome in adolescents. Next, they examined the relationships for variations related to economic adversity, a measurement of socioeconomic status.
Study results showed that adolescents with metabolic syndrome had marginally higher concentrations of phthalate metabolites than adolescents without metabolic syndrome. Some relationships between pthalate metabolite concentrations and odds of metabolic syndrome varied by sex. Economic adversity was not shown to influence the relationships between phthalate metabolites and metabolic syndrome among adolescents.
The researchers emphasized the need for further research in this area, given the ubiquitous exposure to phthalates and the increase in obesity and metabolic dysfunction observed among adolescents in recent years.
Asthma is a persistent public health challenge; the number of people with asthma in the U.S. increased 12.3% between 2001–2009, and in 2014 approximately 7.4% of U.S. adults had current asthma. Asthma has increasingly been linked to environmental factors such as allergens and ambient air pollution. Genetic and behavioral factors are major drivers as well. Environmental factors can contribute in concert to health disparities in low-income, underrepresented minority and vulnerable populations, potentially worsening asthma occurrence and symptoms.
This study explored the association between cumulative environmental quality and asthma prevalence in U.S. adults using the Environmental Quality Index (EQI), a summary measure estimating overall environmental quality at the county level. Researchers used the MarketScan® Commercial Claims and Encounters Database to geocode medical claims to county of residence, defining asthma as having at least 2 claims during the study period, 2003-2013. In addition to cumulative environmental quality, researchers examined examine the association between individual environmental domains (air, water, land, built and sociodemographic environments) and asthma prevalence in rural and urban counties.
Worse environmental quality was associated with increased asthma prevalence using the cumulative EQI and comparing the worst to best EQI quintile (PR:1.27; 95% Cl: 1.21,1.34). Patterns varied among different EQI domains (air, water, land, etc), as well as by rural/urban status.
Poor environmental quality may increase asthma prevalence, but specific environmental drivers may operate differently depending on rural/urban status.
Despite considerable healthcare spending and continual advancements in medicine and public health, the United States (U.S.) suffers from one of the highest infant mortality rates among the world’s developed nations. There are significant racial/ethnic differences in these rates; in 2013, the infant mortality rate was nearly double for infants of Non-Hispanic black mothers compared to Non-Hispanic white mothers. A better understanding of factors contributing to infant mortality and the observed racial/ethnic disparity remains an important public health target in the United States.
Prior studies on the environment and infant mortality are generally limited to singular exposures. In this study, researchers used the Environmental Quality Index (EQI), a measure of cumulative environmental exposure (across air, water, land, sociodemographic, and land domains) for U.S. counties from 2000 to 2005, to investigate associations between ambient environment and infant mortality across maternal race/ethnicity. Researchers linked 2000–2005 infant data from the U.S. Centers for Disease Control and Prevention to the EQI (n = 22,702,529; 144,741 deaths), and controlled for rural-urban status, maternal age, maternal education, marital status, infant sex, and stratified on race/ethnicity.
Results showed a mix of positive, negative, and null associations and varied across environmental domain and race/ethnicity. Poorer air quality was monotonically associated with increased odds of infant mortality among Non-Hispanic whites and blacks, and rural status was associated with increased infant mortality odds among Hispanics. Poorer overall environmental quality was associated with decreased odds of infant mortality among Non-Hispanic whites. Researchers noted the counterintuitive nature of this finding and the need for further research regarding how drivers function differently across the sociodemographic environment.
These findings corroborated prior research suggesting an association between air pollution and infant mortality and identified residence in rural areas as a potential risk factor towards infant amongst Hispanics.
In many demographic groups, the prevalence of asthma has leveled off or declined slightly in recent years. However, the prevalence of asthma in those with family income below the Federal Poverty Line continues to rise. It is well-known that asthma prevalence is often high in low income, urban communities. The prevalence and drivers of asthma in low-income families living in rural areas are less understood.
Exposures in damp and moldy buildings increase the risk of asthma and respiratory illness. In this study, researchers investigated respiratory illness, asthma and indoor mold contamination in two low-income, Hispanic communities, Mecca and Coachella City, in the Eastern Coachella Valley (ECV) of California. Teams consisting of Loma Linda University Public-Health graduate students and local community health “promotoras” administered a questionnaire to assess asthma/respiratory illness and collected dust samples in homes. The dust samples were used to determine the level of mold exposures in the various types of housing in these communities, as defined by their Environmental Relative Moldiness Index (ERMI) values.
Based on questions related to asthma and respiratory health, about 11% of the adults and 17% of the children in both Coachella City and Mecca had asthma/respiratory illness. The average ERMI value for Mecca housing (n=50) was 10.3, which was significantly greater than the average ERMI value of 6.0 for Coachella City housing (n=61). The combined percentages of children and adults assessed with asthma/respiratory illness was significantly correlated (Pearson, p<0.05) with the average ERMI values in ECV housing types.
The study concluded that residents of the Eastern Coachella Valley are exposed to very high levels of mold contamination in their homes. This may be one reason for the high prevalence of asthma/respiratory illness in the area, especially for children.
Researchers aimed to quantify nationwide disparities in the distribution of PM-emitting facilities by the characteristics of the surrounding residential populations and to illustrate various spatial scales at which to consider such disparities.
Researchers assigned facilities emitting PM in the 2011 National Emissions Inventory to nearby block groups across the 2009 to 2013 American Community Survey population. They calculated the burden from these emissions for racial/ethnic groups and by poverty status. They then quantified disparities nationally and for each state and county in the country.
For PM of 2.5 micrometers in diameter or less, those in poverty had 1.35 times higher burden than did the overall population, and non-Whites had 1.28 times higher burden. Blacks, specifically, had 1.54 times higher burden than did the overall population. These patterns were relatively unaffected by sensitivity analyses, and disparities held not only nationally but within most states and counties as well.
Disparities in burden from PM-emitting facilities exist at multiple geographic scales. Disparities for Blacks are more pronounced than are disparities based on poverty status. Strictly socioeconomic considerations may be insufficient to reduce PM burdens equitably across populations.
Greenspace has been increasingly recognized as having numerous health benefits. However, its effects are unknown concerning Sudden Unexpected Death (SUD), commonly referred to as sudden cardiac death, which makes up a large proportion of mortality in the United States. Because greenspace can promote physical activity, reduce stress and buffer air pollutants, it may have beneficial effects for people at risk of SUD, such as those with heart disease, hypertension, and diabetes mellitus.
Using several spatial techniques, this study explored the relationship between SUD and greenspace. Researchers looked at 396 out-of-hospital SUD cases that occurred from March 2013 to February 2015 in Wake County (central North Carolina, USA). Multiple greenspace metrics were used in each census tract, including the percentages of forest, grassland, average tree canopy, tree canopy diversity, near-road tree canopy and greenway density. The associations were examined using Poisson regression (non-spatial) and Bayesian spatial models.
The results from both models indicated that SUD incidence was inversely associated with both greenway density and the percentage of forest. This suggests that increases in greenway density by 1 km/km2 and in forest by 10% were associated with a decrease in SUD risk of 18% and 10%, respectively. The inverse relationship was not observed between SUD incidence and other metrics, including grassland, average tree canopy, near-road tree canopy and tree canopy diversity.
This study implies that greenspace, specifically greenways and forest, may have beneficial effects for people at risk of SUD. Further studies are needed to investigate potential causal relationships between greenspace and SUD, and potential mechanisms such as promoting physical activity and reducing stress.
Researchers found that one standard deviation increase in the overall EQI (worse environment) was associated with a mean 3.22% increase in all-cause mortality, a 0.54% increase in heart disease mortality, a 2.71% increase in cancer mortality, and a 2.25% increase in stroke mortality. Among environmental domains, air had the largest associations with all-cause, heart disease, and cancer mortality, whereas the sociodemographic index had the largest association with stroke mortality. Across the urbanicity gradient, no consistent trend was found. For the climate analysis, larger associations were generally found in dry areas for both overall EQI and environmental domain.
The influences of different environmental factors on mortality often occur in tandem; however, few studies have explored the impact on mortality of multiple exposures across environmental domains. Mortality has also been observed to vary spatially, and some of that spatial variability occurs across rural–urban differences. Associations between cumulative environmental quality and mortality may also be influenced by climate.
The Environmental Quality Index (EQI) was used to assess the cumulative environmental effect on mortality and the spatial patterns of that effect. In this study researchers investigated the associations between the overall EQI and all-cause and cause-specific (heart disease, cancer, and stroke) mortality rates for the contiguous United States. Further, associations between mortality and specific EQI domains were examined. Finally, spatial patterns of associations by climate and by how urban/rural status (urbanicity) were considered.
These results suggest that poor environmental quality, particularly poor air quality, are associated with increased mortality, although the strength of these associations vary by urbanicity and climate region.
Association rule mining (ARM) has been widely used to identify associations between various entities in many fields. Although some studies have utilized it to analyze the relationship between chemicals and human health effects, fewer have used this technique to identify and quantify associations between environmental and social stressors.
Socio-demographic variables were generated based on 2010-2014 U.S. Census tract-level income, race/ethnicity population percentage, education level, and age information from the American Community Survey (ACS) database, and chemical variables were generated by utilizing the 2011 National-Scale Air Toxics Assessment (NATA) census tract-level air pollutant exposure concentration data. Six mobile- and industrial-source pollutants were chosen for analysis, including acetaldehyde, benzene, cyanide, particulate matter components of diesel engine emissions (namely, diesel PM), toluene, and 1,3-butadiene. ARM was then applied to quantify and visualize the associations between the chemical and socio-demographic variables.
Census tracts with a high percentage of racial/ethnic minorities and populations with low income tended to have higher estimated chemical exposure concentrations (fourth quartile), especially for diesel PM, 1,3-butadiene, and toluene. In contrast, census tracts with an average population age of 40–50 years, a low percentage of racial/ethnic minorities, and moderate-income levels were more likely to have lower estimated chemical exposure concentrations (first quartile).
Unsupervised data mining methods can be used to evaluate potential associations between environmental inequalities and social disparities, while providing support in public health decision-making contexts.
Asthma is a major public health problem affecting nearly 23 million persons in the United States, including 7 million children. Fungi are ubiquitous in indoor and outdoor environments and have been associated with respiratory diseases, including childhood and adult asthma. There is overwhelming and mounting evidence linking fungal exposure to asthma. Although this has often been explained by thinking of fungi as an allergen, fungi might be affecting immune responses that modify allergic asthma.
This study investigated the mechanisms by which health is affected through exposure to fungi alone and when combined with an allergen. Researchers used an integrated approach combining epidemiologic and basic mechanistic studies to better understand the complex relationship between fungal exposure and asthma outcomes.
Results show that fungal exposure enhances allergen-driven responses, promoting severe allergic asthma. This effect is independent of fungal sensitization (fungi as an allergen).
This study demonstrates that fungi can have powerful effects on asthma independent of their potential to act as antigens. Furthermore, the study provides a strong rationale for combination treatment strategies that target IL-17A (a type of fungus) for subgroups of fungus-exposed patients with difficult-to-treat asthma.
Individual environmental exposures are associated with cancer development; however, these exposures occur simultaneously. The Environmental Quality Index (EQI) is a county-level measure of cumulative environmental exposures that occur in 5 domains (air, water, land, built, and sociodemographic).
For this study, the EQI was linked to county-level annual age-adjusted cancer incidence rates from the Surveillance, Epidemiology, and End Results(SEER) Program state cancer profiles. All-site cancer and the top 3 site-specific cancers for male and female subjects were considered. Associations with the environmental domains were assessed and analyses were stratified by rural/urban status.
Comparing the highest quintile/poorest environmental quality with the lowest quintile/best environmental quality for overall EQI, all-site county-level cancer incidence rate was positively associated with poor environmental quality overall (an estimated 38.55 more cases per 100,000 people per year) and for male (32.60 more cases) and female (30.34-40.21 more cases) subjects. This indicates a potential increase in cancer incidence with decreasing environmental quality. Prostate and breast cancer demonstrated the strongest positive associations with poor environmental quality.
This study demonstrates that focusing on single environmental exposures in cancer development, though necessary to understand specific mechanisms, may not address the broader environmental context in which cancers develop and that future research should address the impact of cumulative environmental exposures.
Modern urban life style is associated with chronic stress, insufficient physical activity and exposure to anthropogenic environmental hazards. Urban green space, such as parks, playgrounds, and residential greenery, can promote mental and physical health and reduce morbidity and mortality in urban residents by providing psychological relaxation and stress alleviation, stimulating social cohesion, supporting physical activity, and reducing exposure to air pollutants, noise and excessive heat.
This chapter summarizes the pathways that link green spaces to health and well-being, and discusses available evidence of specific beneficial effects such as improved mental health, reduced risks of cardiovascular disease, obesity, diabetes and death, and improved pregnancy outcomes.
Specific attention is given to benefits of urban green space for disadvantaged groups and their impacts on health equity. Potential health risks associated with urban green spaces are also discussed along with approaches to reducing or eliminating these risks through proper design and maintenance of green spaces.
How effective public health initiatives and interventions are at identifying and reducing health disparities depends upon the appropriate analysis of how health inequalities are distributed across subgroups. Yet, little research has comprehensively analyzed how a broad range of health risk indicators are distributed by gender, race, and ethnicity.
This study explored potential gender and racial/ethnic disparities in overall health risk related to 24 health risk indicators selected across six domains: socioeconomic, health status and health care, lifestyle, nutritional, clinical, and environmental. Using the 2003-2006 National Health and Nutrition Examination Surveys (NHANES), it evaluated cross-sectional data for 5,024 adults in the United States, controlling for smoking, health insurance status, and age. Using these 24 indicators, comparisons were made between females and males and between racial/ethnic groups.
Non-Hispanic Blacks and Mexican Americans were at greater risk for at least 50% of the 24 health risk indicators, including measures of socioeconomic status, health risk behaviors, poor/fair self-reported health status, multiple nutritional and clinical indicators, and blood lead levels. This demonstrates that cumulative health risk is unevenly distributed across racial/ethnic groups. A similarly high percentage (46%) of the risk factors was observed in females. Females as compared to males were more likely to have lower income, lower blood calcium, poor/fair self-reported health, more poor mental health days/month, higher medication usage and hospitalizations, and higher serum levels of some clinical indicators and blood cadmium.
This analysis of cumulative health risk is a response to calls for broader-based, more integrated assessments of health disparities that can help inform community assessments and public health policy.
Individual-level characteristics, including socioeconomic status, have been associated with poor metabolic and cardiovascular health. However, residential area-level characteristics may also independently contribute to health status.
In this study, researchers used a novel application of hierarchical clustering to aggregate 444 US Census block groups in Durham, Orange, and Wake Counties, NC, USA into six homogeneous clusters of similar characteristics based on 12 demographic factors. Some of these factors include: percentage unemployed, percentage with bachelor’s degree, and percentage under poverty level. Cardiac catheterization patients were assigned to these clusters based on residence at first catheterization.
After controlling for individual-level demographic factors including age, sex, smoking status, and race, significant differences in disease status were found based on a residents’ cluster designation. There were elevated odds of patients being obese, having diabetes, congestive heart failure, and hypertension in a cluster that was urban, impoverished, and unemployed, compared to a cluster that was urban with a low percentage of people that were impoverished or unemployed
The findings demonstrate the feasibility of applying hierarchical clustering to an assessment of area-level characteristics and that living in impoverished, urban residential clusters may have an adverse impact on health. When combined with health data, the method used can provide significant insight into the relation of neighborhood factors and health status. For example, how might housing age influence asthma prevalence.
Minorities and economically-disadvantaged communities continue to bear a disproportionately large burden of the exposures to environmental stressors that are associated with adverse health outcomes. Federal efforts to alleviate such health disparities began in the early 1990s.
The focus of this report, is to summarize the collaborative research agreement between the Environmental Protection Agency (EPA) and the National Institute on Minority Health and Health Disparities (NIMHD), which funded 10 pilot transdisciplinary academic research on environment and health disparities, including the biological, physical, chemical, social, psychosocial, economic, and environmental determinants.
The Pilot EPA-NIMHD EHD Centers of Excellence have focused on research and tool development, community outreach and engagement, as well as education and training. The centers have conducted research to identify environmental health disparities, develop solutions to these disparities, and collect and synthesize disparity data. Pilot EHD Center research staff have engaged with their communities in order to form collaborations to inform evidence-based policies, involve the communities in the research process to empower sustainable solutions, and developed community education resources. The Pilot EHD Centers supported the education and training of students, professionals, and the community in several ways, including involving students in their research and community outreach, training professionals and community members on topics related to EHDs, incorporating EHD research and topics into their university’s curriculum, and sharing EHD research at meetings, workshops, and conferences around the world. Specific examples of these impacts from each of the centers are highlighted in this report.
Medicaid data can be useful in quantifying asthma prevalence at the county and state levels. This study examined whether Medicaid data could be used to determine prevalence at the zip code level. Researchers examined whether there was a correlation between Medicaid services used that relate to asthma, and mold levels in homes in Detroit.
Dust was collected from homes of Detroit asthmatic children and from a representative group of Michigan homes. The mold contamination for each home was measured using the Environmental Relative Moldiness Index (ERMI) scale and the mean ERMI values in Detroit and non-Detroit homes were statistically compared. Michigan Medicaid data in each of the 25 zip codes in Detroit were tested for correlation to ERMI values for homes in those zip codes.
The mean ERMI value for Detroit asthmatic children’s homes was significantly greater than for the non-Detroit homes. Detroit homes > 60 years old had significantly greater mean ERMI values than Detroit homes ≤ 60 years old. The percentage of children that underwent spirometry testing for their persistent asthma (based on Medicaid data) was significantly, positively correlated with the mean ERMI values of the homes in the 25 zip codes.
Applying Medicaid-use data for spirometry testing and locating a city's older housing stock might help public health officials locate areas of homes with high ERMI values.
Environmental exposures often occur in tandem; however, epidemiological research often focuses on singular exposures. Statistical interactions between environmental domains have not yet been evaluated in association with health.
In this first of its kind study, researchers address this gap by conducting a county-level cross-sectional analysis of interactions between Environmental Quality Index (EQI) domain indices on preterm birth in the Unites States from 2000 to 2005. Researchers compared worse environmental quality to the better quality to assess (a) each individual domain’s main effect, (b) the interaction contrast between domains, and (c) the two main effects plus interaction effect (i.e., the “net effect”) to show departure from additivity for all U.S. counties. Analyses were also performed for subgroupings by four urban/rural strata.
Results suggest some antagonistic interactions but no synergism, that is, a given environmental domain may dampen the effect on preterm birth of another domain, but there wasn’t any evidence showing that they amplify the effect of another.
Observed antagonistic associations may indicate that those living in areas with multiple detrimental domains have other interfering factors reducing the burden of environmental exposure. This study is the first to explore interactions across different environmental domains and demonstrates the utility of the EQI to examine the relationship between environmental domain interactions and human health. While results indicated some departure from additivity, many observed effects were additive.
This study advances methods for analysis of cumulative environmental factors and demonstrates that interactions between environmental domains should be considered in future analyses.
Over several decades, asthma has evolved from being recognized as a single disease to include a diverse group of phenotypes with dissimilar natural histories, functional changes, responses to treatment, and distinctive molecular pathways.
This study hypothesizes that there is one cause underlying the numerous phenotypes of this disease and that the responsible molecular pathway is a deficiency of iron in the lung tissues. Iron homeostasis is an essential mechanism whereby the body manages the impact of environmental agents on overall health.
This deficiency can be either absolute (e.g. asthma in the neonate and during both pregnancy and menstruation) or functional (e.g. asthma associated with infections, smoking, and obesity). Therapies directed at asthma have been shown to impact iron homeostasis as well. Finally, functional changes producing asthma (including inflammation and muscle contraction) can correlate with iron availability.
Recognition of a potential association between asthma and an absolute and/or functional iron deficiency suggests that there may be specific therapeutic interventions, including inhaled iron to curb the severity of this disease. This can improve health outcomes for communities with higher prevalence of obesity and smoking, often the same communities with environmental health disparities.
Mold can adversely impact indoor air quality and cause health issues. Neighborhoods that are prone to flooding and homes with leaky pipes are at greater risk of developing mold which can increase asthma prevalence.
To address community concerns about potential health effects of flooding in English Avenue and Vine City, two low-income communities in Atlanta, a survey of homes was conducted to examine the prevalence of mold and mold-associated health conditions. Teams consisting of a public-health graduate student and a resident from one of the two communities administered a questionnaire, inspected residences for mold growth, and collected a dust sample for quantifying mold contamination. The dust samples were analyzed for the 36 molds that make up the Environmental Relative Moldiness Index (ERMI).
Although only 12% of occupants reported a history of flooding, 46% reported at least one water leak. Homes with visible mold (35%) had significantly higher mean ERMI values compared to homes without. When controlling for indoor smoking, among participants residing at their current residence for two years or less, a positive association was observed between asthma and the homes' ERMI values.
Researchers presented the findings on exposures and asthma prevalence to the communities and public officials. Community-based organizations have taken responsibility for planning and implementing activities in response to the study findings. This kind of community-partnered research could be a model for other communities.
Asthma control depends on many factors, including access and adherence to medications and exposure to asthma triggers. Studies of inner-city minority children with asthma show that exacerbations decrease when household allergen exposure is reduced or with aggressive therapy. African-Americans are at higher risk of poorly controlled asthma compared with other races and experience higher rates of asthma-related morbidity and mortality.
This observational study of African-American adolescents between August 2013 and October 2014 examined factors that influence asthma control. Researchers hypothesized that allergic status can influence asthma control despite guidelines-based therapy. Data was gathered on 25 African-American teens with well characterized moderate to severe persistent asthma, and comparisons were drawn between those with poorly controlled and well controlled asthma.
Results showed a significant association between loss of asthma control and sensitization to aeroallergens, particularly seasonal outdoor allergens, despite optimized guidelines-directed therapy in African-American teens with moderate to severe persistent asthma
The findings suggest that in addition to guidelines-directed asthma therapies, targeting the allergic component, particularly tree and weed pollen, is critical to achieving optimal asthma control in this at-risk population.
Exposure Risk Assessment
Links below, where available, lead directly to citations in EPA's Science Inventory. Scroll down for annotations for each entry.
Arsenic (As) and lead (Pb) are two contaminants of concern associated with urban gardening. In Puerto Rico, data currently is limited on As and Pb levels in urban garden soils, soil metal (loid) bioaccessibility, and uptake of As and Pb in soil by edible plants grown in the region.
This study examined total and bioaccessible soil As and Pb concentrations and accumulation in 10 commonly grown garden plants collected from three urban community gardens in Puerto Rico. Bioavailability values were predicted using bioaccessibility data to compare site-specific bioavailability estimates to commonly used default exposure assumptions.
Total and bioaccessible As levels in study soils ranged from 2 to 55 mg/kg and 1 to 18 mg/kg, respectively. Total and bioaccessible Pb levels ranged from 19 to 172 mg/kg and 17 to 97 mg/kg, respectively. Measured bioaccessibility values corresponded to 19% to 42% bioaccessible As and 61% to 100% bioaccessible Pb when expressed as a percent of total As and Pb respectively. Transfer factors (TFs) measuring uptake of As in plants from soil ranged from 0 to 0.073 in the edible flesh (fruit or vegetable) of plant tissues analyzed and 0.073 to 0.444 in edible leaves. Pb TFs ranged from 0.002 to 0.012 in flesh and 0.023 to 0.204 in leaves. Consistent with TF values, leaves accumulated higher concentrations of As and Pb than the flesh, with the highest tissue concentrations observed in the culantro leaf (3.2 mg/kg dw of As and 8.9 mg/kg dw of Pb). Leaves showed a general but not statistically-significant (α = 0.05) trend of increased As and Pb concentration with increased soil levels, while no trend was observed for flesh tissues.
These findings provide critical data that can improve accuracy and reduce uncertainty when conducting site-specific risk determination of As and Pb exposure while gardening or consuming garden produce in the understudied region of Puerto Rico.
Prior knowledge about community health vulnerability can help guide deliberate awareness building and outreach among the most sensitive populations. However, identifying communities at the greatest risk from exposure to wildfire smoke is currently based solely on the predicted risk of fire—the composition of the communities is not considered. As such, public health messaging and actions may not be appropriately scaled to communities with high numbers of sensitive individuals.
Researchers developed a Community Health-Vulnerability Index (CHVI) based on factors known to increase the risks of health effects from air pollution and wildfire smoke exposures. These factors included county prevalence rates for: asthma in children and adults, chronic obstructive pulmonary disease, hypertension, diabetes, and obesity, percent of population 65 years of age and older, and indicators of socioeconomic status including poverty, education, income and unemployment. Using air quality simulated for the period between 2008 and 2012 over the continental U.S., researchers also characterized the population size at risk with respect to the level and duration of exposure to fire-originated fine particulate matter (fire-PM2.5) and CHVI.
Using the index, researchers estimate that 10% of the population (30.5 million) lived in areas where the contribution of fire-PM2.5 to annual average ambient PM2.5 was high. They also found that 10.3 million individuals experienced unhealthy air quality levels for more than 10 days due to smoke.
Identifying communities vulnerable to adverse health effects from exposure to wildfire smoke may help prepare responses, increase the resilience to smoke, and improve public health outcomes during smoke days.
Manganese is both an essential element and neurotoxicant. Exposure can occur from various sources and routes.
This University of Cincinnati-led study used structural equation modeling to examine routes of exposure to manganese among children residing near a ferromanganese refinery in Marietta, Ohio. A model of ambient manganese inhalation pathways was hypothesized. In 2009, data to evaluate the model were obtained from participants in the Communities Actively Researching Exposure Study (CARES) by researchers and community members, and included levels of manganese in residential soil and dust, levels of manganese in children's hair, information on the amount of time the child spent outside, heat and air conditioning in the home, and level of parent education.
The concentration of manganese in hair was the primary endogenous variable used to assess theoretical inhalation exposure pathways. The model indicated that household dust manganese was a significant contributor to child hair manganese levels. Stepping back further, researchers found that annual ambient air manganese concentration, the amount of time children spend outside, and manganese levels in soil contribute significantly to the amount of manganese in household dust.
These results, the first to use structural equation modeling to evaluate inhalation pathways of manganese exposure in children, provide a potential framework for understanding such a pathway for children who live in proximity to industrial emission sources. These findings suggest that indoor air quality is an important part of controlling exposure to manganese.
Many different quantitative techniques have been developed to either assess Environmental Justice (EJ) issues or estimate exposure and dose for risk assessment. However, very few approaches link EJ factors to exposure dose estimates and quantify potential impacts of EJ factors on dose-related variables.
On the U.S. nationwide census tract-level, researchers defined and quantified two EJ indicators (poverty and race/ethnicity) to examine their relation to multi-chemical exposure dose estimates. Pollutant doses for each tract were calculated using the average-daily-dose (ADD) model, and EJ scores were assigned to each tract based on poverty- or race-related population percentages. Single- and multiple-chemical ADD values were matched to the tract-level EJ scores to analyze disproportionate dose relationships and contributing EJ factors.
When both EJ indicators were examined simultaneously, exposure for all pollutants generally increased with larger (poorer, greater percentage minority populations) EJ scores. To demonstrate the utility of using the EJ-ADD approach on the local scale, exposure levels of lead were approximated via soil/dust ingestion for simulated communities with different EJ-related scenarios. The local-level simulation indicates substantially greater exposure-dose levels for EJ communities when compared to wealthy communities.
The application of the EJ-ADD approach can link EJ factors to exposure dose estimate and identify potential EJ impacts on dose-related variables.
Exposure-based risk assessment employs large cross-sectional data sets of environmental and biomarker measurements to predict population statistics for adverse health outcomes. The underlying assumption is that long-term latency health problems including cancer, autoimmune and cardiovascular disease, diabetes, and asthma are triggered by lifetime exposures to environmental stressors that interact with the genome.
The aim of this study was to develop a way to predict chronic exposure of individuals based upon a single biomarker measurement (blood pressure, blood lead level, etc.) and knowledge of global statistics derived from large data sets. The methodology developed enables one to (1) utilize large databases of spot measures to assess an individual’s risk, and (2) estimate risks using smaller measurement sets made at the community level.
This is a profound shift in exposure and health statistics in that it begins to answer the question “How large is my personal risk?” rather than just providing an overall population-based estimate. This approach also holds value for interpreting exposure-based risks for small groups of individuals within a community in comparison to random individuals from the general population. This study’s findings are in line with the 2014 National Environmental Justice Advisory Council (NEJAC) report which recommended increased support of biomonitoring research (recommendation 1-4).
Air Pollution Monitoring and Modeling
Links below, where available, lead directly to citations in EPA's Science Inventory. Scroll down for annotations for each entry.
Air pollution is a worldwide contributor to cardiovascular disease, mortality, and morbidity. Traffic-related air pollution is a widespread environmental exposure and is associated with multiple cardiovascular concerns such as coronary atherosclerosis, peripheral arterial disease, and myocardial infarction. Despite recognizing the importance of both genetic and environmental exposures, studies of how these two contributors operate jointly are rare.
Researchers performed a genome-wide interaction study (GWIS) to examine gene-traffic exposure interactions associated with coronary atherosclerosis. Study participants were broken up into race-stratified cohorts of 538 African-Americans (AA) and 1562 European-Americans (EA) from a cardiac catheterization cohort (CATHGEN).
Researchers found five interactions in the AA cohort, of which two replicated in the EA cohort. In the EA cohort, there were three interactions; none of these replicated in the AA cohort.
This study has uncovered several novel genes associated with coronary atherosclerosis in individuals chronically exposed to increased ambient concentrations of traffic air pollution. These genes point towards inflammatory pathways that may modify the effects of air pollution on cardiovascular disease risk.
The Community model for near-PORT applications (C-PORT) is a screening tool that calculates differences in annual averaged concentration patterns and relative contributions of various air emission sources over the spatial domain within about 10 km of a port.
C-PORT can help decision-makers and concerned citizens better understand how mobile source emissions related to commercial port activities relate to local air quality. It allows users to visualize and evaluate different planning scenarios, helping them identify the best alternatives for making long-term decisions that protect community health and sustainability. The web-based, easy-to-use interface currently includes data from 21 seaports primarily in the Southeastern U.S., and has a map-based interface based on Google Maps.
The tool was developed to visualize and assess changes in air quality due to changes in emissions and/or meteorology in order to analyze development scenarios, and is not intended to support or replace any regulatory models or programs.
The general approach for studying health impacts of exposure to fine particulate matter (PM2.5) is to use concentration data from the nearest ground-based air quality monitor(s), which typically have missing data on the temporal and spatial scales due to filter sampling schedules and monitor placement, respectively.
To address these data gaps, this research project uses a model to generate estimates of PM2.5 in areas with and without air quality monitors by combining PM2.5 concentrations measured by monitors, PM2.5 concentration estimates derived from satellite aerosol optical depth (AOD) data, and Community-Multiscale Air Quality (CMAQ) model predictions of PM2.5 concentrations. Researchers focused on the New York City metropolitan and surrounding areas during the 2004-2006 time period, in order to compare health outcome impacts with those from previous studies and focus on any benefits derived from the changes in the HBM model surfaces.
Consistent with previous studies, the results show that high PM2.5 exposure is associated with increased risk of asthma, myocardial infarction and heart failure. The estimates that incorporate AOD data are comparable to those derived from combining monitor and CMAQ data alone.
The use of next-generation, high temporal and spatial resolution data from satellites is expected to improve predictions in epidemiological studies in areas with fewer pollutant monitors or over wider geographic areas.
This study can be used by health researchers to construct their own assessments on impacts of fine particulate matter (PM2.5) concentrations when air monitoring is limited, but data from MODIS satellite overpasses area available. Researchers looking to use satellite data to examine adverse health effects of air pollutants using the case-crossover method with individual health data will want to use this research project as a template.
Fugitive vapor emissions from leaks and process malfunctions in industrial facilities, energy production facilities, and refining operations can be significant sources of air pollution and greenhouse gases. Sources of fugitive emissions are difficult to locate, measure, and model and may go undetected for extended periods. In populated areas with mixtures of complex sources, uncertainty in fugitive emissions of volatile organic compounds (VOCs) and hazardous air pollutants (HAPs) can complicate management of local and regional air quality.
New measurement techniques are emerging to help identify emissions that can be mitigated and further understanding of near source impacts. From June 2013 to March 2015, a total of 41 two-week duration passive sampler deployments were conducted at 17 sites in South Philadelphia.
Using a variation of EPA’s passive sampler refinery fenceline monitoring method, coupled with time-resolved measurements, this multiyear study in South Philadelphia increased knowledge of benzene concentrations near facilities and in communities. The combination of measurement strategies can help facilities to identify and mitigate emissions from fugitive sources and improve information on air quality in complex air sheds. These next generation air measurement approaches may enable advanced fugitive management strategies, providing benefits in the form of improved worker and community safety, reduced environmental impact, and cost savings realized through reduced product loss.
Disparities in the location of overburdened communities in proximity to industrial facilities is well documented. Increasing capacity for fenceline monitoring helps to build data for identifying facilities out of compliance and for devising strategies to address disparities in exposure. This study’s findings are in line with the 2014 NEJAC report which recommended increased focus on research to identify and address air quality “hot spots” (recommendation 1-5). Building on this overview paper, additional analysis from the study will explore topics such as fenceline sensor data, additional chemical species, source transport modeling, and exposure levels.
Water Quality and Modeling
Concerns around lead found in Flint, Michigan’s drinking water and a number of other drinking water systems as well as in the soil in East Chicago, Indiana have led to calls for action. In 2015, the U.S. EPA’s National Drinking Water Advisory Council recommended the establishment of a “health-based, household action level” for lead in drinking water based on children’s exposure.
A modeling approach using the EPA’s SHEDS-Multimedia and IEUBK models was developed using available data. The primary objective of this study was to use the coupled exposure-dose modeling approach to determine what drinking water lead concentrations keep children’s blood lead levels below specified values, considering exposures from water, soil, dust, food, and air. Related objectives were to evaluate the coupled model estimates using real-world blood lead data; to quantify relative contributions by the various media; and to identify key model inputs.
Modeled blood lead levels compared well with nationally representative levels (0%-23% relative error). Analyses revealed relative importance of soil and dust ingestion exposure pathways, and associated lead intake rates; water ingestion was also a main pathway, especially for infants.
This methodology advances scientific understanding of the relationship between lead concentrations in drinking water and blood lead levels in children. This can guide national health-based benchmarks in different exposure media such as soil.
Resilience of Microbial Communities in a Simulated Drinking Water Distribution System Subjected to Disturbances: Role of Conditionally Rare Taxa and Potential Implications for Antibiotic-resistant Bacteria
Changes in the operations of drinking water distribution systems can impact water quality. More than half of US water utilities using chloramine as their secondary disinfectant have experienced nitrification episodes that detrimentally impact water quality in their distribution systems.
A drinking water distribution system simulator was used to evaluate biological stability of the model system and describe the response of microbial communities to disturbances caused by changes in the operational parameters such as switching disinfectants. Results show variations in the structure of the microbial community found in drinking water systems during episodes of disturbance (e.g., disinfectant switching practices, nitrification) and recovery after disturbance. Notably, prevalence of antibiotic-resistant bacteria increased during system failure.
Communities may face multiple pathways of exposure to antibiotic-resistant bacteria. In addition to exposure via nitrification within drinking water systems that lead to antibiotic resistant bacteria, runoff from concentrated animal feeding operations where antibiotics are prescribed may also increase exposure. Rural communities in close proximity to these facilities often depend on well water or small-scale water utilities with limited resources. These overburdened communities may face exposure to antibiotic-resistant bacteria as well as disinfectant byproducts and personal-care products/pharmaceuticals via drinking water.
Understanding changes in microbial communities in disturbed drinking water distribution systems is essential for monitoring biological stability within these systems. When changes and behavior of microbial communities is better understood, risk can be managed properly to ensure public and ecosystem health.
Urban stormwater runoff is a major issue in overburdened communities where it has been documented to result in flooding, mold, environmental degradation, and increased exposure to waterborne pathogens—all of which pose public health threats.
The use of adaptive management to implement and monitor green infrastructure (GI) projects as experimental attempts to manage stormwater has not been adequately explored as a way to optimize GI performance or increase social and political acceptance. Efforts to improve stormwater management through GI suffer from complex and overlapping jurisdictional boundaries, as well as interacting social and political forces that dictate the flow, consumption, conservation and disposal of urban wastewater flows. Within this urban setting, adaptive management—rigorous experimentation applied as policy—can inform new wastewater management techniques such as the implementation of green infrastructure projects.
This article presents a narrative of scientists and practitioners working together to apply an adaptive management approach to green infrastructure implementation for stormwater management in Cleveland, Ohio. In Cleveland, contextual legal requirements and environmental factors created an opportunity for government researchers, stormwater managers and community organizers to engage in the development of two distinct sets of rain gardens, each borne of unique social, economic and environmental processes. Researchers analyze social and political barriers to applying adaptive management as a framework for implementing green infrastructure experiments as policy.
In addition to their ecological importance, understanding the cultural implications of GI experiments is key to their long-term sustainability. Several studies have examined resident’s perceptions of green space management and provide important insights. Importantly, the aesthetics of rain garden design are critical in their acceptance by citizens and their willingness to implement this tactic, and will inform future policy and planning.
Use of community meetings and social media can inform the community and be used as a mechanism to survey the needs and wants of residents. This process can also aim to engage citizens in the maintenance of GI, a necessary reality given shrinking city budgets.
Adaptive Management and Resilience
Urban aquatic restoration can be difficult to accomplish because of complications like industrial pollutants, population density, infrastructure, and expense. However, unique opportunities in urban settings, including the potential to provide benefits to many diverse people, can make urban restoration especially valuable. Restoration in urban settings offers real opportunities to address environmental justice issues and deliver wide-reaching benefits to an increasingly urban populace.
The success of urban restoration projects—even those focused primarily on ecological targets—depend on community involvement and managers considering community needs. However, research on the social barriers to urban restoration and strategies managers use to overcome them is relatively rare.
This work attempts to fill that gap by presenting barriers for aquatic restoration projects in urban settings and strategies to overcome them. Building from interviews with restoration managers involved in urban aquatic restoration projects in Rhode Island, this research contributes through an adaptive management approach: identifying and synthesizing the lessons learned from managers’ work in urban settings.
Among those interviewed, environmental justice issues were looked at both as a difficulty to overcome, and as something that could be used as a rallying call to help focus attention and resources. Ultimately, the authors suggest potential for a disentangling and critiquing of the frames and policy/power structures that influence decision making in urban aquatic restoration.
The concept of resilience has been evolving over the past decade as a way to address the current and future challenges nations, states, and cities face from a changing climate. Understanding how the environment (both natural and built), climate event risk, societal interactions, and governance affect community resilience is critical for envisioning urban and natural environments that can persist through extreme weather events and longer-term shifts in climate. To be successful, the interaction of these five domains must result in maintaining quality of life and ensuring equal access to the benefits or the protection from harm for all segments of the population.
A literature review of climate resilience approaches examined the two primary elements of resilience—vulnerability and recoverability. While some aspects of a resilience model were covered by existing sources, no comprehensive approach was available.
A new conceptual model for resilience to climate events is proposed that incorporates some available structures and addresses these five domains at a national, regional, state, and county spatial scale for a variety of climate-induced events ranging from superstorms to droughts and their concomitant events such as wildfires, floods, and pest invasions. This conceptual model will be developed in a manner that will permit comparisons among governance units (e.g., counties) and permit an examination of best reliance practices.
The climate resilience screening index (CRSI) will advance the transdisciplinary aspects necessary to holistically address climate resilience. The authors intend to address the application of this approach to the counties of the United States in a subsequent manuscript which will detail the application process and the results.
Good governance focuses on equity and justice and is reflected in legal requirements that the actions of government be legitimate, transparent, and inclusive.
The term “governance” encompasses both governmental and nongovernmental participation in collective choice and action. Law dictates the structure, boundaries, rules, and processes within which governmental action takes place, and in doing so becomes one of the focal points for analysis of barriers to adaptation as the effects of climate change are felt. Adaptive governance must therefore contemplate a level of flexibility and evolution in governmental action beyond that currently found in the heavily administrative governments of many democracies.
The key is to do so in a way that also enhances legitimacy, accountability, and justice, or else such reforms will never be adopted by democratic societies, or if adopted, will destabilize those societies. The authors discuss six necessary aspects to facilitate adaptive governance: (1) legitimacy, (2) procedural justice, (3) problem-solving approach, (4) opportunity for reflection and learning, (5) balancing stability and flexibility, and (6) dispute resolution.
The authors present guidelines for evaluating the role of law in environmental governance to identify the ways in which law can be used, adapted, and reformed to facilitate adaptive governance and to do so in a way that enhances the legitimacy of governmental action.
EPA developed the Human Well-being Index as an integrative measure of economic, social, and environmental contributions to well-being. The HWBI is composed of indicators and metrics representing eight domains of well-being: connection to nature, cultural fulfillment, education, health, leisure time, living standards, safety and security, and social cohesion. The domains and indicators in the HWBI were selected to provide a well-being framework that is broadly applicable to many different populations and communities, and can be customized using community-specific metrics.
A primary purpose of this report is to adapt the HWBI to quantify human well-being for Puerto Rico. Researchers compared well-being across Puerto Rican municipios (county-equivalent) and to the United States, and reflected on the contribution of different indicators and domains to measured well-being.
The adaptation of the HWBI for Puerto Rico provides an example of how the tool can be adapted to different communities. The flexibility of the HWBI framework allows that if different local data is desired or becomes available, it can easily be substituted in while maintaining the overall integrity of the framework. The key is to make sure data is consistent across whatever is being compared (e.g., scenarios, zip codes, counties, years).
Indices, such as HWBI, can help communities to assess and track well-being, and identify decisions and interventions that can contribute to and promote sustainable well-being. This research contributes to EPA’s goal of developing research, data, and tools to expand the capabilities of communities to consider the social, economic, and environmental impacts of decision alternatives on community well-being.
The South Fork Nooksack River (South Fork) is located in northwest Washington State and is home to nine species of Pacific salmon, including Nooksack early Chinook (aka, spring Chinook salmon), an iconic species for the Nooksack Indian Tribe. The quantity of salmon in the South Fork, especially spring Chinook salmon, has dramatically declined from historic levels, due primarily to habitat degradation from the legacy impacts of various land uses such as commercial forestry, agriculture, flood control, and transportation infrastructure. Of the nine salmon species, three have been listed as threatened under the federal Endangered Species Act (ESA) and are of high priority to restoration efforts in the South Fork—spring Chinook salmon, summer steelhead trout, and bull trout. Growing evidence shows that climate change will exacerbate legacy impacts.
This qualitative assessment is a comprehensive analysis of climate change impacts on freshwater habitat and Pacific salmon in the South Fork. It also evaluates the effectiveness of restoration tools that address Pacific salmon recovery. Restoration actions evaluated are those that address legacy, ongoing, and future climate change impacts within each reach and sub-basin.
According to the findings, actions with the greatest potential to address the impacts of climate change in the South Fork watershed are: restoring of habitats adjacent to water, reconnecting water bodies to their floodplains, restoring of wetlands, and placement of log jams. Most of these actions are already being implemented to varying degrees, but the pace and scale of implementation will need to be increased by explicitly addressing barriers to implementation. This will require substantial planning including a watershed conservation plan, project feasibility assessments, agency consultation, landowner cooperation, stakeholder involvement, and funding.
The qualitative assessment’s findings will inform development of the CWA South Fork temperature TMDL Implementation Plan, updates to the ESA Water Resource Inventory Area 1 (WRIA1) Salmonid Recovery Plan, and other land use and restoration planning efforts.