Seasonal extreme temperatures and short-term fine particulate matter increases pediatric respiratory healthcare encounters in a sparsely populated region of the intermountain western United States.

BACKGROUND: Western Montana, USA, experiences complex air pollution patterns with predominant exposure sources from summer wildfire smoke and winter wood smoke. In addition, climate change related temperatures events are becoming more extreme and expected to contribute to increases in hospital admissions for a range of health outcomes. Evaluating while accounting for these exposures (air pollution and temperature) that often occur simultaneously and may act synergistically on health is becoming more important. METHODS: We explored short-term exposure to air pollution on children's respiratory health outcomes and how extreme temperature or seasonal period modify the risk of air pollution-associated healthcare events. The main outcome measure included individual-based address located respiratory-related healthcare visits for three categories: asthma, lower respiratory tract infections (LRTI), and upper respiratory tract infections (URTI) across western Montana for ages 0-17 from 2017-2020. We used a time-stratified, case-crossover analysis with distributed lag models to identify sensitive exposure windows of fine particulate matter (PM2.5) lagged from 0 (same-day) to 14 prior-days modified by temperature or season. RESULTS: For asthma, increases of 1 µg/m3 in PM2.5 exposure 7-13 days prior a healthcare visit date was associated with increased odds that were magnified during median to colder temperatures and winter periods. For LRTIs, 1 µg/m3 increases during 12 days of cumulative PM2.5 with peak exposure periods between 6-12 days before healthcare visit date was associated with elevated LRTI events, also heightened in median to colder temperatures but no seasonal effect was observed. For URTIs, 1 unit increases during 13 days of cumulative PM2.5 with peak exposure periods between 4-10 days prior event date was associated with greater risk for URTIs visits that were intensified during median to hotter temperatures and spring to summer periods. CONCLUSIONS: Delayed, short-term exposure increases of PM2.5 were associated with elevated odds of all three pediatric respiratory healthcare visit categories in a sparsely population area of the inter-Rocky Mountains, USA. PM2.5 in colder temperatures tended to increase instances of asthma and LRTIs, while PM2.5 during hotter periods increased URTIs.

Public health assessment of Kenyan ASGM communities using multi-element biomonitoring, dietary and environmental evaluation.

The Kakamega gold belt's natural geological enrichment and artisanal and small-scale gold mining (ASGM) have resulted in food and environmental pollution, human exposure, and subsequent risks to health. This study aimed to characterise exposure pathways and risks among ASGM communities. Human hair, nails, urine, water, and staple food crops were collected and analysed from 144 ASGM miners and 25 people from the ASGM associated communities. Exposure to PHEs was predominantly via drinking water from mine shafts, springs and shallow-wells (for As>Pb>Cr>Al), with up to 366 µg L-1 arsenic measured in shaft waters consumed by miners. Additional exposure was via consumption of locally grown crops (for As>Ni>Pb>Cr>Cd>Hg>Al) besides inhalation of Hg vapour and dust, and direct dermal contact with Hg. Urinary elemental concentrations for both ASGM workers and wider ASGM communities were in nearly all cases above bioequivalents and reference upper thresholds for As, Cr, Hg, Ni, Pb and Sb, with median concentrations of 12.3, 0.4, 1.6, 5.1, 0.7 and 0.15 µg L-1, respectively. Urinary As concentrations showed a strong positive correlation (0.958) with As in drinking water. This study highlighted the importance of a multidisciplinary approach in integrating environmental, dietary, and public health investigations to better characterise the hazards and risks associated with ASGM and better understand the trade-offs associated with ASGM activities relating to public health and environmental sustainability. Further research is crucial, and study results have been shared with Public Health and Environmental authorities to inform mitigation efforts.

Estimating the daily pollen concentration in the atmosphere using machine learning and NEXRAD weather radar data.

Millions of people have an allergic reaction to pollen. The impact of pollen allergies is on the rise due to increased pollen levels caused by global warming and the spread of highly invasive weeds. The production, release, and dispersal of pollen depend on the ambient weather conditions. The temperature, rainfall, humidity, cloud cover, and wind are known to affect the amount of pollen in the atmosphere. In the past, various regression techniques have been applied to estimate and forecast the daily pollen concentration in the atmosphere based on the weather conditions. In this research, machine learning methods were applied to the Next Generation Weather Radar (NEXRAD) data to estimate the daily Ambrosia pollen over a 300 km × 300 km region centered on a NEXRAD weather radar. The Neural Network and Random Forest machine learning methods have been employed to develop separate models to estimate Ambrosia pollen over the region. A feasible way of estimating the daily pollen concentration using only the NEXRAD radar data and machine learning methods would lay the foundation to forecast daily pollen at a fine spatial resolution nationally.

Electronic health record case studies to advance environmental public health tracking.

Data from traditional public health surveillance systems can have some limitations, e.g., timeliness, geographic level, and amount of data accessible. Electronic health records (EHRs) could present an opportunity to supplement current sources of routinely collected surveillance data. The National Environmental Public Health Tracking Program (Tracking Program) sought to explore the use of EHRs for advancing environmental public health surveillance practices. The Tracking Program funded four state/local health departments to obtain and pilot the use of EHR data to address several issues including the challenges and technical requirements for accessing EHR data, and the core data elements required to integrate EHR data within their departments' Tracking Programs. The results of these pilot projects highlighted the potential of EHR data for public health surveillance of rare diseases that may lack comprehensive registries, and surveillance of prevalent health conditions or risk factors for health outcomes at a finer geographic level. EHRs therefore, may have potential to supplement traditional sources of public health surveillance data.

Systemic inflammatory markers associated with cardiovascular disease and acute and chronic exposure to fine particulate matter air pollution (PM2.5) among US NHANES adults with metabolic syndrome.

BACKGROUND: There has been no investigation to date of adults with metabolic syndrome examining the association of short and long-term exposure to fine particulate matter (PM2.5) air pollution with cardiovascular-disease related inflammatory marker (WBC and CRP) levels in a nationally representative sample. The goal of this study is to assess the susceptibility of adults with metabolic syndrome to PM2.5 exposure as suggested by increased cardiovascular-disease related inflammatory marker levels. METHODS: A cross sectional analysis of adult National Health and Nutrition Examination Survey (NHANES) participants (2000-2008) was carried out with linkage of CDC WONDER meteorological data and downscaler modeled USEPA air pollution data for census tracts in the continental United States. Participants were non-pregnant NHANES adults (2000-2008) with complete data for evaluating presence of metabolic syndrome and laboratory data on WBC and CRP. Exposures studied included short (lags 0-3 days and their averages), long-term (30 and 60 day moving and annual averages) PM2.5 exposure levels at the census tract level in the continental United States. The main outcomes included CRP and WBC levels the day of NHANES study visit analyzed using multiple linear regression, adjusting for age, gender, race, education, smoking status, history of any cardiovascular disease, maximum apparent temperature and ozone level, for participants with and without metabolic syndrome. RESULTS: A total of 7134 NHANES participants (35% with metabolic syndrome) met the inclusion criteria. After adjusting for confounders, we observed a significant effect of PM2.5 acutely at lag day 0 on CRP level; a 10µg/m3 rise in lag day 0 PM2.5 level was associated with a 10.1% increase (95% CI: 2.2-18.6%) in CRP levels for participants with metabolic syndrome. For those without metabolic syndrome, the change in CRP was -1.3% (95% CI -8.8%, 6.8%). There were no significant associations for WBC count. In this first national study of the effect of PM2.5 air pollution on levels of cardiovascular-disease related inflammatory markers in adults with metabolic syndrome, CRP levels were found to be significantly increased in those with this condition with increased fine particulate matter levels at lag day 0. With one third of US adults with metabolic syndrome, the health impact of PM2.5 in this sensitive population may be significant.

Engaging academia to advance the science and practice of environmental public health tracking.

Public health agencies at the federal, state, and local level are responsible for implementing actions and policies that address health problems related to environmental hazards. These actions and policies can be informed by integrating or linking data on health, exposure, hazards, and population. The mission of the Centers for Disease Control and Prevention׳s National Environmental Public Health Tracking Program (Tracking Program) is to provide information from a nationwide network of integrated health, environmental hazard, and exposure data that drives actions to improve the health of communities. The Tracking Program and federal, state, and local partners collect, integrate, analyze, and disseminate data and information to inform environmental public health actions. However, many challenges exist regarding the availability and quality of data, the application of appropriate methods and tools to link data, and the state of the science needed to link and analyze health and environmental data. The Tracking Program has collaborated with academia to address key challenges in these areas. The collaboration has improved our understanding of the uses and limitations of available data and methods, expanded the use of existing data and methods, and increased our knowledge about the connections between health and environment. Valuable working relationships have been forged in this process, and together we have identified opportunities and improvements for future collaborations to further advance the science and practice of environmental public health tracking.

A case-crossover analysis of the impact of PM(2.5) on cardiovascular disease hospitalizations for selected CDC tracking states.

BACKGROUND: Information is currently being collected by the CDC Environmental Public Health Tracking (EPHT) network on hospitalizations due to Acute Myocardial Infarction (AMI) and there is interest by CDC in exploring the relationship between fine particulate matter (PM2.5) and other cardiovascular (CVD) outcomes in the context of the EPHT program. The goal of this study was to assess the short term effects of daily PM(2.5) air pollution levels on hospitalizations for CVD for seven states within the CDC EPHT network (Florida, Massachusetts, New Hampshire, New Jersey, New Mexico, New York, and Washington). METHODS: Hospitalization data was obtained for 2001-2008 admissions for circulatory disease (primary discharge diagnosis of ICD-9 codes 390-459) from data stewards in those states and included admission date, age, gender, and zip code of residence. We used CMAQ-derived predicted daily PM2.5 data as estimated by EPA at the centroid of each Census Bureau Zip Code Tabulation Area (ZCTA) and linked to zip code of patient residence. A time-stratified case-crossover study design with conditional logistic regression was used to evaluate the short-term association of PM2.5 on risk of non-elective hospitalizations for CVD. Specifically, we considered all circulatory disease, ischemic heart disease, acute myocardial infarction, heart failure, cardiac arrhythmia, cerebrovascular disease and peripheral vascular disease endpoints. RESULTS: Data were obtained on over 7,500,000 hospitalizations for this time period. Mean annual PM2.5 exposure levels were lowest for New Mexico and Washington (6.5 µg/m3 PM2.5 and 8.4 µg/m3 PM2.5). New Jersey, New York and Massachusetts exhibited the highest annual averages for PM2.5, (12.8 µg/m3, 11.1 µg/m3 and 10.8 µg/m3), respectively. The Northeast states (Massachusetts, New Jersey, New Hampshire and New York) exhibited significant effects of PM2.5 during the cooler months across most disease categories after adjustment for ozone and maximum apparent temperature. Ischemic heart disease risk per 10 µg/m3 increase in PM2.5 varied from 1.02 to 1.05 for the cooler months. The largest lag effect was noted on lag days 0 and 1. New Mexico and Washington exhibited no cool or warm month significant effects. Although Florida showed no cooler month effects, significant increases were noted in odds ratios for the warm weather months for all outcomes except peripheral vascular disease. This study is one of the first large scale applications of linkage of hospitalization data by state with national US EPA statistically modeled air pollution data. The results demonstrate that state-wide, there are multiple cardiovascular outcomes in addition to AMI which may be impacted by particulate air pollution.

Promotion of environmental public health and environmental justice in communities affected by large and long lasting industrial contamination: methods applied and lessons learned from the case study of Porto Torres (Italy).

Introduction: Communities affected by large scale and long lasting industrial contamination are often keen to understand whether their health has been impaired by such contamination. This requires answers that integrate environmental public health and environmental justice perspectives. At these sites, exposure scenarios from environmental contamination over time by multiple chemicals, often involving different environmental matrices, are complex and challenging to reconstruct. Methods: An approach for describing the health of such communities in association with environmental contamination is presented, with the methods applied across the three domains of environmental contamination, population exposure and toxicology, environmental and social epidemiology, and environmental public health communication. The approach is described with examples from its application to the case study of Porto Torres, a town with a substantial industrially conditioned evolution. Results: Activities in the field of environmental contamination, population exposure and toxicology focus on the collection and systematization of available contamination data, the identification of priority pollutants based on their toxicological profiles, the qualitative assessment of the likelihood of exposure for the population to priority pollutants and their known health effects. Environmental and social epidemiology methods are applied to describe the health profiles and socioeconomic conditions of the local population, taking into account multiple health outcomes from local information systems and considering specific diseases based on exposure and toxicological assessments. The environmental public health communication methods are directed to produce a communication plan and for its implementation through interaction with local institutional and social actors. The interpretation of health profiles benefits from a transdisciplinary analysis of the results. Discussion: The proposed approach combines the needs of environmental public health and environmental justice allowing the integration of multidisciplinary knowledge to define recommendations for reducing and/or preventing hazardous environmental exposures and adverse health effects, stimulating the interactions between stakeholders, and making the study results more accessible to citizens.

"I think they should give primary health care a little more priority". The primary health care in Caribbean SIDS: what can be said about adaptation to the changing climate? The case of Dominica- a qualitative study.

BACKGROUND: Adaptation to climate change (CC) is a priority for Small Island Developing States (SIDS) in the Caribbean, as these countries and territories are particularly vulnerable to climate-related events. Primary health care (PHC) is an important contributor to CC adaptation. However, knowledge on how PHC is prepared for CC in Caribbean SIDS is very limited. The aim of this paper is to discuss health system adaptation to climate change, with a focus on PHC. METHODS: We explored the perspectives of PHC professionals in Dominica on PHC adaptation to climate change. Focus group discussions (FGDs) were conducted in each of the seven health districts in Dominica, a Caribbean SIDS, between November 2021 and January 2022. The semi-structured interview guide was based on the Essential Public Health Functions: assessment, access to health care services, policy development and resource allocation. Data coding was organized accordingly. RESULTS: Findings suggest that health care providers perceive climate change as contributing to an increase in NCDs and mental health problems. Climate-related events create barriers to care and exacerbate the chronic deficiencies within the health system, especially in the absence of high-level policy support. Healthcare providers need to take a holistic view of health and act accordingly in terms of disease prevention and health promotion, epidemiological surveillance, and ensuring the widest possible access to healthcare, with a particular focus on the environmental and social determinants of vulnerability. CONCLUSION: The primary health care system is a key stakeholder in the design and operationalization of adaptation and transformative resilience. The Essential Public Health Functions should integrate social and climate and other environmental determinants of health to guide primary care activities to protect the health of communities. This study highlights the need for improved research on the linkages between climate events and health outcomes, surveillance, and development of plans informed by contextual knowledge in the SIDS.

Open science, the replication crisis, and environmental public health.

Concerns about a crisis of mass irreplicability across scientific fields ("the replication crisis") have stimulated a movement for open science, encouraging or even requiring researchers to publish their raw data and analysis code. Recently, a rule at the US Environmental Protection Agency (US EPA) would have imposed a strong open data requirement. The rule prompted significant public discussion about whether open science practices are appropriate for fields of environmental public health. The aims of this paper are to assess (1) whether the replication crisis extends to fields of environmental public health; and (2) in general whether open science requirements can address the replication crisis. There is little empirical evidence for or against mass irreplicability in environmental public health specifically. Without such evidence, strong claims about whether the replication crisis extends to environmental public health - or not - seem premature. By distinguishing three concepts - reproducibility, replicability, and robustness - it is clear that open data initiatives can promote reproducibility and robustness but do little to promote replicability. I conclude by reviewing some of the other benefits of open science, and offer some suggestions for funding streams to mitigate the costs of adoption of open science practices in environmental public health.

Exploring the influence of local alcohol availability on drinking norms and practices: A qualitative scoping review.

INTRODUCTION: High alcohol availability is related to increased alcohol consumption and harms. Existing quantitative research provides potential explanations for this relationship but there is little understanding of how people experience local alcohol availability. This is the first review to synthesise qualitative research exploring the relationship between alcohol availability and other factors in local alcohol environments. METHODS: The scoping review includes qualitative studies exploring community-level alcohol availability and other factors, facilitating the purchase and consumption of alcohol. We included studies focusing on children and adolescents as well as adults. Study findings were brought together using thematic analysis and the socio-environmental context model, which explains how certain environments may facilitate drinking. RESULTS: The review includes 34 articles. The majority of studies were conducted since 2012. Most studies were conducted in the United Kingdom, Australia and South Africa. The physical availability of alcohol and proximity to local amenities and temporal aspects, like late night opening hours, may be linked to social factors, such as normalisation of drinking and permissive drinking environments. The review highlights the importance of social and cultural factors in shaping interactions with local alcohol environments. DISCUSSION AND CONCLUSION: This qualitative scoping review advances understanding of the pathways linking alcohol availability and alcohol harms by showing that availability, accessibility and visibility of alcohol may contribute towards permissive drinking environments. Further research is needed to better understand how people experience alcohol availability in their local environment and how this can inform alcohol control policies.

Public Health Data Applications Using the CDC Tracking Network: Augmenting Environmental Hazard Information With Lower-Latency NASA Data.

Exposure to environmental hazards is an important determinant of health, and the frequency and severity of exposures is expected to be impacted by climate change. Through a partnership with the U.S. National Aeronautics and Space Administration, the U.S. Centers for Disease Control and Prevention's National Environmental Public Health Tracking Network is integrating timely observations and model data of priority environmental hazards into its publicly accessible Data Explorer (https://ephtracking.cdc.gov/DataExplorer/). Newly integrated data sets over the contiguous U.S. (CONUS) include: daily 5-day forecasts of air quality based on the Goddard Earth Observing System Composition Forecast, daily historical (1980-present) concentrations of speciated PM2.5 based on the modern era retrospective analysis for research and applications, version 2, and Moderate Resolution Imaging Spectroradiometer (MODIS) daily near real-time maps of flooding (MCDWD). Data integrated into the CDC Tracking Network are broadly intended to improve community health through action by informing both research and early warning activities, including (a) describing temporal and spatial trends in disease and potential environmental exposures, (b) identifying populations most affected, (c) generating hypotheses about associations between health and environmental exposures, and (d) developing, guiding, and assessing environmental public health policies and interventions aimed at reducing or eliminating health outcomes associated with environmental factors.

A Current Review of Water Pollutants in American Continent: Trends and Perspectives in Detection, Health Risks, and Treatment Technologies.

Currently, water pollution represents a serious environmental threat, causing an impact not only to fauna and flora but also to human health. Among these pollutants, inorganic and organic pollutants are predominantly important representing high toxicity and persistence and being difficult to treat using current methodologies. For this reason, several research groups are searching for strategies to detect and remedy contaminated water bodies and effluents. Due to the above, a current review of the state of the situation has been carried out. The results obtained show that in the American continent a high diversity of contaminants is present in the water bodies affecting several aspects, in which in some cases, there exists alternatives to realize the remediation of contaminated water. It is concluded that the actual challenge is to establish sanitation measures at the local level based on the specific needs of the geographical area of interest. Therefore, water treatment plants must be designed according to the contaminants present in the water of the region and tailored to the needs of the population of interest.

Exploring the Joint Association of Road Traffic Noise and Air Quality with Hypertension Using QGIS.

There is growing evidence linking exposure to air pollution and traffic noise with hypertension. The aim of this study was to examine the associations of registered hypertension cases and hypertension rate with exposure to air pollution and road noise. In this cross-sectional study, we linked the information from the NHS Scotland database of 776,579 hypertension patients' registrations and rates per 13.80 people at the Scottish NHS Board, HSCP, Cluster, and GP practice levels. Based on the geospatial attributes, the data on residential areas were added by modelling annual average air pollutant concentrations, including particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2), and road-traffic noise at different frequency components (Lden). The relationships between exposure to road noise, air pollution, and hypertension were examined using multiple regression and multivariate analysis. Traffic noise and air pollution at various frequency components positively and negatively predicted registered hypertension cases and hypertension rate. Based on the canonical loading technique, the variance explained by the canonical independent variable at a canonical correlation of 0.342 is 89%. There is a significant correlation between joint air pollution and noise at different frequency components and combined registered hypertension cases and hypertension rate. Exploring the combined effects of the two environmental exposures and the joint modelling of noise and air pollutants with hypertension in geospatial views provides an opportunity to integrate environmental and health data to support spatial assessment strategies in public and environmental health.

Mycotoxin exposure biomonitoring in breastfed and non-exclusively breastfed Nigerian children.

A multi-specimen, multi-mycotoxin approach involving ultra-sensitive LC-MS/MS analysis of breast milk, complementary food and urine was applied to examine mycotoxin co-exposure in 65 infants, aged 1-18 months, in Ogun state, Nigeria. Aflatoxin M1 was detected in breast milk (4/22 (18%)), while six other classes of mycotoxins were quantified; including dihydrocitrinone (6/22 (27%); range: 14.0-59.7 ng/L) and sterigmatocystin (1/22 (5%); 1.2 ng/L) detected for the first time. Seven distinct classes of mycotoxins including aflatoxins (9/42 (21%); range: 1.0-16.2 µg/kg) and fumonisins (12/42 (29%); range: 7.9-194 µg/kg) contaminated complementary food. Mycotoxins covering seven distinct classes with diverse structures and modes of action were detected in 64/65 (99%) of the urine samples, demonstrating ubiquitous exposure. Two aflatoxin metabolites (AFM1 and AFQ1) and FB1 were detected in 6/65 (9%), 44/65 (68%) and 17/65 (26%) of urine samples, respectively. Mixtures of mycotoxin classes were common, including 22/22 (100%), 14/42 (33%) and 56/65 (86%) samples having 2-6, 2-4, or 2-6 mycotoxins present, for breast milk, complementary food and urine, respectively. Aflatoxin and/or fumonisin was detected in 4/22 (18%), 12/42 (29%) and 46/65 (71%) for breast milk, complimentary foods and urine, respectively. Furthermore, the detection frequency, median concentrations and occurrence of mixtures were typically greater in urine of non-exclusively breastfed compared to exclusively breastfed infants. The study provides novel insights into mycotoxin co-exposures in early-life. Albeit a small sample set, it highlights transition to higher levels of infant mycotoxin exposure as complementary foods are introduced, providing impetus to mitigate during this critical early-life period and encourage breastfeeding.

Fatal Unintentional Non-Fire Related Carbon Monoxide Poisoning: Data from Narrative Verdicts in England and Wales, 1998-2019.

Unintentional non-fire related (UNFR) carbon monoxide (CO) poisoning continues to cause fatalities. The narrative verdicts from coroners concerning fatal UNFR CO poisoning in England and Wales, 1998-2019, were collated by the Office for National Statistics. Search terms related to CO exposure were used to obtain information regarding the circumstances of death. Findings were grouped by the location of death, the source of CO, and the reason or behaviour underlying the exposure. There were 750 deaths (77% male). The annual number of deaths decreased over the period studied. Two thirds (68%) of the deaths occurred in the autumn or winter. From the records with information, 59% of deaths occurred within a dwelling (67% male). Males also predominated deaths within vehicles (91%) and garages or outbuildings (95%). From the deaths with information, domestic piped gas was the most common source of CO (36%) and the most frequent underlying factor was inadequate ventilation of exhaust gases (39%, 91% male). Despite the decrease in the annual number of deaths over the study period, there remains a clear need for measures that raise awareness of the dangers of CO poisoning, especially amongst men working alone in garages or outbuildings. Education campaigns and fitting and maintaining CO alarms in high-risk areas should be encouraged.

Assessment of Environmental Impacts on Health: Examples from the Pacific Basin.

Assessing environmental impacts on health in the Pacific Basin is challenged by significantly varying data types - quantities, qualities, and paucities - because of varying geographic sizes, environments, biodiversity, ecological assets, and human population densities, with highly varied and unequal socio-economic development and capacity to respond to environmental and health challenges. We discuss three case-based methodological examples from Pacific Basin environmental health impact assessments. These methods could be used to improve environmental health evidence at all country and regional levels across a spectrum of big data availability to no data. These methods are, 1) a risk assessment of airborne particulate matter in Korea based on the chemical composition of these particulates; 2) the use of system dynamics to appraise the influences of a range of environmental health determinants on child health outcomes in remote Solomon Islands; and 3) precision environmental public health methodologies based on comprehensive data collection, analyses, and modelling (including Bayesian belief networks and spatial epidemiology) increasing precision for good environmental health decision making to prevent and control a zoonotic disease in Fiji Islands. We show that while a common theme across the three examples is the value of high quality and quantity data to support stronger policy decisions and appropriate prioritizing of investment, it is also clear that for many countries in the Pacific Basin, sufficient data will remain a challenge to inform decision makers about environmental impact on health.

Global occurrence and probabilistic environmental health hazard assessment of per- and polyfluoroalkyl substances (PFASs) in groundwater and surface waters.

Per- and polyfluoroalkyl substances (PFASs) have been used in consumer and military products since the 1950s but are increasingly scrutinized worldwide because of inherent chemical properties, environmental contamination, and risks to public health and the environment. The United States Environmental Protection Agency (USEPA) identified 24 PFASs of interest for further study and possible regulation. We examined 371 peer-reviewed studies published since 2001 to understand the occurrence and distribution of 24 priority PFASs in global surface waters and groundwater. We identified 77,541 and 16,246 data points for surface waters and groundwater, respectively, with total PFAS concentrations ranging from low pg/L to low mg/L levels. Most data were from Asia, Europe, and North America with some reports from Oceania. PFAS information from other geographic regions is lacking. PFASs levels are consistently higher in rivers and streams followed by lakes and reservoirs and then coastal and marine systems. When sufficient data were available, probabilistic environmental hazard assessments (PEHAs) were performed from environmental exposure distributions (EEDs) to identify potential exceedances of available guideline values for each compound by matrix, region, and aquatic system. Specifically, exceedances of USEPA drinking water lifetime health advisory levels were up to 74% for PFOS in groundwater from Oceania and 69% for PFOA in North American groundwater. Our findings support selection of environmentally relevant experimental treatment levels for future toxicology, ecotoxicology and bioaccumulation studies, and potable source water exposure investigations, while highlighting PFASs and major geographic locations requiring additional study and inclusion in global monitoring and surveillance campaigns.

Exploring the Combined Association between Road Traffic Noise and Air Quality Using QGIS.

There is mounting evidence that exposure to air pollution and noise from transportation are linked to the risk of hypertension. Most studies have only looked at relationships between single exposures. To examine links between combined exposure to road traffic, air pollution, and road noise. A Casella CEL-63x instrument was used to monitor traffic noise on a number of locations in residential streets in Glasgow, UK during peak traffic hours. The spatial numerical modelling capability of Quantum GIS (abbreviated QGIS) was used to analyse the combined association of noise and air pollution. Based on geospatial mapping, data on residential environmental exposure was added using annual average air pollutant concentrations from local air quality monitoring network, including particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2), and road-traffic noise measurements at different component frequencies (Lden). The combined relationships between air pollution and traffic noise at different component frequencies were examined. Based on Moran I autocorrelation, geographically close values of a variable on a map typically have comparable values when there is a positive spatial autocorrelation. This means clustering on the map was influenced significantly by NO2, PM10 and PM2.5, and Lden at the majority of monitoring locations. Studies that only consider one of these two related exposures may exaggerate the impact of the individual exposure while underestimating the combined impact of the two environmental exposures.

A Framework for Interfacing and Partnering with Environmental Justice Communities as a Prelude to Human Health and Hazard Identification in the Vulnerable Census Tracts of Columbus, Ohio.

Columbus, Ohio is one of the more prosperous, well-educated, and progressive cities in the United States. However, it ranks as the second worst life expectancy at birth, has a census tract wealth gap (27-year disparity), and one of the higher infant mortality rates in the country. These data suggest that there are likely several high-risk, vulnerable neighborhoods in Columbus with residents experiencing disparate and adverse outcomes. Illustrative of this fact are studies that have examined the social processes and mechanisms through which neighborhood contexts are at the forefront, including exposures to chemical stressors such as particulate matter (PM2.5) as well as non-chemical stressors including violence, social determinants of health, zoning, and land use policies. It is documented that disparate and adverse outcomes are magnified in the vulnerable neighborhoods on the Near East Side as compared to Columbus city proper, Franklin County and/or the state of Ohio. As such, we developed a nuanced community engagement framework to identify potential environmental hazards associated with adverse pregnancy outcomes in those census tracts. The refined framework uses a blended version of traditional community-based participatory research (CBPR) models and is referred to as E6, Enhancing Environmental Endeavors via e-Equity, Education, and Empowerment.