Environmental Protection Agency's National Research Articles

A Broad-Scale Look at Nutrient Limitation and a Shift toward Co-limitation in United States Lakes.

There is a longstanding debate about the role of nitrogen (N) vs phosphorus (P) in limiting primary production in lakes and whether co-nutrient limitation should be considered for managing eutrophication. We evaluated nutrient limitation and eutrophication at a subcontinental scale. Using U.S. Environmental Protection Agency National Lakes Assessment data, we assessed broad-scale patterns in nutrient limitation and compared samples of all surveyed lakes and lakes resurveyed in multiple surveys. We found that N correlated more strongly with productivity in the western U.S., while P correlated more strongly in the eastern U.S. The aggregated subcontinental effect suggests the importance of factors like N-deposition, terrestrial vegetation, underlying geology, and land use for understanding drivers of nutrient dynamics in lakes. Our study showed how patterns can aggregate across subcontinental scales yet still demonstrate considerable variation when more deeply examined on an individual lake level. Overall, we found that nutrient limitation is dynamic over space and time, with most lakes being co-limited. The prevalence of co-limitation also increased from 2007 to 2017. Trophic states within each limitation category varied substantially. Our findings underscore the need for combined N and P reductions to mitigate accelerated eutrophication.

Neighborhood Walkability Is Associated With Global Positioning System-Derived Community Mobility of Older Adults.

Neighborhood walkability may encourage greater out-of-home travel (ie, community mobility) to support independent functioning in later life. We examined associations between a novel walkability audit index and Global Positioning System (GPS)-derived community mobility in community-dwelling older adults. We compared associations with the validated Environmental Protection Agency (EPA) National Walkability Index and further examined moderation by clinical walking speed. Participants were 146 older adults (Mean = 77.0 ± 6.5 years, 68% women) at baseline of a randomized trial to improve walking speed. A walkability index (range: 0-5; eg, land-use mix, crosswalks, and so on) was created using Google Street View audits within 1/8-mile of the home. Participants carried a GPS device for 5-7 days to derive objective measures of community mobility (eg, time spent out of home, accumulated distance from home). Each 1 SD (~1.3-point) greater walkability audit score was associated with a median 2.16% more time spent out of home (95% confidence interval [95% CI]: 0.30-4.03, p = .023), adjusting for individual demographics/health and neighborhood socioeconomic status. For slower walkers (4-m walking speed <1 m/s), each 1 SD greater audit score was also associated with a median 4.54 km greater accumulated distance from home (95% CI: 0.01-9.07, p (interaction) = .034). No significant associations were found for the EPA walkability index. Walkability immediately outside the home was related to greater community mobility, especially for older adults with slower walking speeds. Results emphasize the need to consider the joint influence of local environment and individual functioning when addressing community mobility in older populations.

Optimization of benzene exposure risk assessment: An integrated approach utilizing internal and external concentrations with a focus on biomarkers S-PMA & t, t-MA

In the majority of occupational settings within China, the concentrations of benzene are observed to fall markedly below the demarcated detection thresholds. Employing traditional risk assessment models, the presence of exceptionally low airborne benzene exposure concentrations may infuse heightened degrees of uncertainty. Consequently, the necessity arises to investigate risk assessment methodologies more apt for the prevalent exposure environment among employees. In the present study, a pharmacokinetic model premised on urinary benzene metabolites (S-PMA and t, t-MA) was employed to ascertain a more precise daily airborne benzene exposure concentration per individual. This value was integrated into the linear multistage model as the ‘internal exposure concentration’. In conjunction with the U.S National Environmental Protection Agency's (EPA) inhalation risk assessment model predicated on the external exposure concentration, the Singapore Ministry of Manpower's (MOM) model, and the linear multistage (LMS) model, the carcinogenic and non-carcinogenic effects of benzene were evaluated for 1781 benzene-exposed employees across 76 enterprises in Jiangsu Province. Findings suggest that in the linear multilevel model assessment, the cancer risk levels based on t, t-MA and S-PMA were higher in the printing and recording media reproduction industry, automobile manufacturing industry, general equipment manufacturing industry and the furniture manufacturing industry (median 2.842 × 10−4, 2.819 × 10−4, 2.809 × 10−4, and 2.678 × 10−4), which align more consistently with the actual benzene exposure circumstances of each industry's study participants, with overall risk levels calculated by the linear multistage model exceeding those of the EPA inhalation risk assessment model and the MOM model. This implies that the linear multistage model of internal exposure, based on the reciprocal of benzene biomarkers S-PMA and t, t-MA for airborne benzene exposure, presents enhanced sensitivity and suitability for the current occupational health risk assessment of workers. Without doubt, biomarker-based benzene exposure risk assessment emerges as the optimal choice.

Assessing the Groundwater Quality and Hydrogeochemical Characteristics of Karst Aquifers in Kinta Valley, Perak

The rich karstic limestone aquifer in Kinta Valley, Perak is a potential resource of clean water in the future when the surface water resources will deplete and insufficient to support the growing population. A proper preliminary evaluation of groundwater hydrogeochemistry is essential for knowing the proper application and maintaining the available groundwater as a sustainable resource. Four production wells in Kinta Valley are sampled and analyzed for physicochemical parameters from 2018 to 2020. In this study, major chemical compounds, pH, total hardness (TH), and total dissolved solids (TDS) are interpreted to construct Piper’s trilinear diagram and Gibbs plot which describe the hydrochemistry of the samples. Drinking Water Quality Standard from the Ministry of Health Malaysia (MOH) and the United States Environmental Protection Agency (US EPA) National Primary Drinking Water Regulation is used as guideline standards for water quality evaluation. Based on the results from this study, the quality of groundwater in Kinta Valley is healthy and has the potential to be used as drinking water besides using as irrigation water. The predominant hydrochemical reaction of the groundwater is found to be a bicarbonate-calcium-magnesium reaction, which shows the aquifers are in contact with the subsurface karst system as the main ions originated from the dissolution of carbonate bedrocks.

Determining the connectivity of tribal communities to wastewater treatment facilities for use in environmental contamination and exposure assessments by wastewater-based surveillance.

Limited information is available on the connectivity of Tribal communities to wastewater treatment facilities (WWTFs). This is important for understanding current sanitation infrastructure which drives public health and community construction, knowledge of potential routes of exposure through lack of infrastructure and/or discharging facilities, and opportunities to assess community health through wastewater-based surveillance (WBS). The objective of this work was to assess current wastewater infrastructure for 574 Federally Recognized Indian Tribes (FRITs) in the United States (US) to determine the number and location of facilities on or adjacent to Tribal reservations and Off-Reservation Trust Lands, with the goal of determining the feasibility of employing wastewater-based surveillance within these communities and to identify areas with inadequate sanitation infrastructure. Here, we identified available National Pollutant Discharge Elimination System (NPDES) wastewater discharge permits in the Environmental Protection Agency's Environmental Compliance History Online database to assess proximity to and within spatial boundaries of Tribal lands. These data were coupled to race data and tribal spatial boundary information from the US Census Bureau. 94 FRITs have registered NPDES permits within Tribal boundaries including a total of 522 facilities. 210 of these are American Indian (AI)-serving (>50% AI) with the ability to reach 135,000 AI-people through the wastewater network to provide community health assessments via WBS. Of the remaining facilities, 153 predominantly serve non-Tribal populations raising concerns about infrastructure placement and indigenous sovereignty. 523 FRITs were identified as without permitted discharging WWTFs, which may suggest inadequate or alternative infrastructure. Here, multiple data sources including permit information from the Environmental Protection Agency's National Pollution Discharge Elimination System and US Census Bureau data were used to determine the number of wastewater treatment facilities on or adjacent to Tribal lands and how many community members were connected to those municipal systems. This information was used to assess which Tribal communities may be a viable option for wastewater public health surveillance techniques and were used to answer supplemental questions related to basic sanitation and environmental justice concerns.

Spatiotemporally resolved emissions and concentrations of styrene, benzene, toluene, ethylbenzene, and xylenes (SBTEX) in the US Gulf region

Abstract. Styrene, benzene, toluene, ethylbenzene, and xylenes (SBTEX) are established neurotoxicants. SBTEX contains hazardous air pollutants (HAPs) that are released from the petrochemical industry, combustion process, transport emission, and solvent usage sources. Although several SBTEX toxic assessment studies have been conducted, they have mainly relied on ambient measurements to estimate exposure and limit their scope to specific locations and observational periods. To overcome these spatiotemporal limitations, an air quality modeling system over the US Gulf region was created, predicting the spatially and temporally enhanced SBTEX modeling concentrations from May to September 2012. Due to the incompleteness of SBTEX in the official US Environmental Protection Agency (EPA) National Emission Inventory (NEI), the Hazardous Air Pollutions Imputation (HAPI) program was used to identify and estimate the missing HAP emissions. The improved emission data were processed to generate the chemically speciated hourly gridded emission inputs for the Comprehensive Air Quality Model with Extensions (CAMx) chemical transport model to simulate the SBTEX concentrations over the Gulf modeling region. SBTEX pollutants were modeled using the Reactive Tracer feature in CAMx that accounts for their chemical and physical processes in the atmosphere. The data show that the major SBTEX emissions in this region are contributed by mobile emissions (45 %), wildfire (30 %), and industry (26 %). Most SBTEX emissions are emitted during daytime hours (local time 14:00–17:00), and the emission rate in the model domain is about 20–40 t h−1, which is about 4 times higher than that in the nighttime (local time 24:00–04:00, about 4–10 t h−1). High concentrations of SBTEX (above 1 ppb) occurred near the cities close to the I-10 interstate highway (Houston, Beaumont, Lake Charles, Lafayette, Baton Rouge, New Orleans, and Mobile) and other metropolitan cities (Shreveport and Dallas). High styrene concentrations were co-located with industrial sources, which contribute the most to the styrene emissions. The HAPI program successfully estimated missing emissions of styrene from the chemical industry. The change increased total styrene emissions by 22 %, resulting in maximum ambient concentrations increasing from 0.035 to 1.75 ppb across the model domain. The predicted SBTEX concentrations with imputed emissions present good agreement with observational data, with a correlation coefficient (R) of 0.75 (0.46 to 0.77 for individual SBTEX species) and a normalized mean bias (NMB) of −5.6 % (−24.9 % to 32.1 % for the individual SBTEX species), suggesting their value for supporting any SBTEX-related human health studies in the Gulf region. The SBTEX data were published at Zenodo (https://doi.org/10.5281/zenodo.7967541) (Wang et al., 2023), and the HAPI tool was also published at Zenodo (https://doi.org/10.5281/zenodo.7987106) (Wang and Baek, 2023).

Behaviourally-informed household communications increase uptake of radon tests in a randomised controlled trial

Exposure to radon gas is a leading cause of lung cancer. Testing homes for the gas is straightforward, yet most people do not undertake tests even when offered freely. We report a pre-registered randomised controlled trial of communications to encourage test uptake. Households (N = 3500) in areas at high risk of radon exposure were randomly assigned to receive (i) a the control letter from the national Environmental Protection Agency; (ii) a behaviourally-informed version of the control letter that incorporated multiple nudges, including reciprocity messages and numeric frequencies of risk; (iii) this same behaviourally-informed letter in a re-designed envelope; (iv) the behaviourally-informed letter in the re-designed enveloped with a radon risk map of the household’s county. The behaviourally-informed letter led to a large increase in test uptake, from 22% in the control condition to 33% (a 50% increase). There was no additional benefit of the re-designed envelope, which generated uptake of 30%. Including the map led some households to respond faster, but the overall uptake (26%) was weaker. The results have implications for public health communications with households and show the potential for techniques from behavioural science to help mitigate environmental risks.

Simulations of winter ozone in the Upper Green River basin, Wyoming, using WRF-Chem

Abstract. In the Upper Green River basin (UGRB) of Wyoming and the Uintah Basin of Utah, strong wintertime ozone (O3) formation episodes leading to O3 mixing ratios occasionally exceeding 70 parts per billion (ppb) have been observed over the last 2 decades. Wintertime O3 events in the UGRB were first observed in 2005 and since then have continued to be observed intermittently when meteorological conditions are favorable, despite significant efforts to reduce emissions from oil and natural gas extraction and production. While O3 formation has been successfully simulated using observed volatile organic compound (VOC) and nitrogen oxide (NOx) mixing ratios, successful simulation of these wintertime episodes using emission inventories in a 3-D photochemical model has remained elusive. An accurate 3-D photochemical model driven by an emission inventory is critical to understanding the spatial extent of high-O3 events and which emission sources have the most impact on O3 formation. In the winter of 2016/17 (December 2016–March 2017) several high-O3 events were observed with 1 h mixing ratios exceeding 70 ppb. This study uses the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to simulate one of the high-O3 events observed in the UGRB during March 2017. The WRF-Chem simulations were carried out using the 2014 edition of the Environmental Protection Agency National Emissions Inventory (EPA NEI2014v2), which, unlike previous versions, includes estimates of emissions from non-point oil and gas production sources. Simulations were carried out with two different chemical mechanisms: the Model for Ozone and Related Chemical Tracers (MOZART) and the Regional Atmospheric Chemistry Mechanism (RACM), and the results were compared with data from seven weather and air quality monitoring stations in the UGRB operated by the Wyoming Department of Environmental Quality (WYDEQ). The simulated meteorology compared favorably to observations with regard to temperature inversions, surface temperature, and wind speeds. Notably, because of snow cover present in the basin, the photolysis surface albedo had to be modified to predict O3 in excess of 70 ppb, although the models were relatively insensitive to the exact photolysis albedo if it was over 0.65. O3 precursors, i.e., NOx and VOCs, are predicted similarly in simulations with both chemical mechanisms, but simulated VOC mixing ratios are a factor of 6 or more lower than the observations, while NOx is also underpredicted but to a lesser degree. Sensitivity simulations revealed that increasing NOx and VOC emissions to match observations produced slightly more O3 compared to baseline simulations, but an additional sensitivity simulation with doubled NOx emissions resulted in a considerable increase in O3 formation. These results suggest that O3 formation in the basin is most sensitive to NOx emissions.

Health burden associated with tillage-related PM2.5 pollution in the United States, and mitigation strategies

Exposure to airborne particulate matter of diameter less than 2.5 μm (PM2.5) is associated with cardiovascular diseases (CVD) and chronic obstructive pulmonary disease (COPD). In agriculture, the practice of tilling generates PM2.5 emissions that can jeopardize human health. This paper estimates the annual deaths and disability-adjusted life years (DALYs) from CVD and COPD attributable to PM2.5 emissions from corn, soybean, cotton, and wheat tillage in the contiguous United States. Primary PM2.5 from crop-tillage combination was calculated using values obtained from the Environmental Protection Agency's National Emissions Inventory, 2017, while deaths and DALYs estimates were calculated using data from the Institute of Health Metrics and Evaluation's global burden of risk factors study, the US decennial census, and the US Centers for Disease Control. We also propose and implement a conceptual framework for identifying the optimal subsidy upon accounting for health benefits arising from reducing conventional tillage, and we discuss strategies to achieve conservation tillage. Annual PM2.5 emissions from crop tillage is about 0.25 million tons. We estimate that approximately 1000 annual deaths and 22,000 DALYs from CVD, as well as 300 annual deaths and 7400 DALYs from COPD, were attributable to tillage-related PM2.5 emissions. Tillage related primary PM2.5 emissions contribute about 0.002 % of total CVD and COPD deaths in the United States, and its related health economic value loss is about 12.9 billion USD annually. About 350 annual deaths may be averted upon a shift from conventional to conservation tillage. Conservation tillage is generally adopted when the pecuniary and soil health benefits exceed those from adopting intensive tillage. Agricultural policies and on-farm measures that may help reduce intensive tillage, and the related PM2.5 emissions, include subsidies for adopting conservation tillage and carbon capture credits, use of herbicides and herbicide-tolerant crops, protecting herbicide-tolerance traits, planting cover crops, and use of windbreaks.

Ecosystem services profiles for communities benefitting from estuarine habitats along the Massachusetts coast, USA

The Massachusetts Bays National Estuary Partnership is one of 28 programs in the United States Environmental Protection Agency's National Estuary Program (NEP) charged with developing and implementing comprehensive plans for protecting and restoring the biological integrity and beneficial uses of their estuarine systems. The Partnership has recently updated their comprehensive management plan to include restoration targets for coastal habitats, and as part of this effort, the program explored how to better demonstrate that recovery of ecological integrity of degraded ecosystems also provides ecosystem services that humans want and need. An essential step was to identify key stakeholders and understand the benefits important to them. The primary objective of the study presented here was to evaluate variability in beneficial uses of estuarine habitats across coastal communities in Massachusetts Bays. We applied a text mining approach to extract ecosystem services concepts from over 1400 community planning documents. We leveraged a Final Ecosystem Goods and Services (FEGS) classification framework and related scoping tool to identify and prioritize the suite of natural resource users and ecosystem services those users care about, based on the relative frequency of mentions in documents. Top beneficiaries included residents, experiencers and viewers, property owners, educators and students, and commercial or recreational fishers. Beneficiaries had a surprising degree of shared interests, with top ecosystem services of broad relevance including for naturalness, fish and shellfish, water movement and navigability, water quality and quantity, aesthetic viewscapes, availability of land for development, flood mitigation, and birds. Community-level priorities that emerged were primarily related to regional differences, the local job industry, and local demographics. Identifying priority ecosystem services from community planning documents provides a starting point for setting locally-relevant restoration goals, designing projects that reflect what stakeholders care about, and supporting post-restoration monitoring in terms of accruing relevant benefits to local communities.

Using information provision and interactive risk maps to motivate testing for radon

Radon exposure in homes is a leading cause of lung cancer, but the rate at which householders test for this environmental risk is low. In a pre-registered experiment with a nationally representative sample of adults (N = 1700), we used psychological theory to design information interventions to influence perceptions of risk from radon and motivate testing. Results show that information about radon increased belief that exposure would lead to negative consequences, but not perceived likelihood of exposure. Interactive maps depicting the geographical distribution of radon risk increased perceived likelihood of exposure, general worry and willingness to test for radon, but the effects depended on the map's attributes. Maps communicating risk using numeric frequencies of the number of homes in an area likely to be affected by radon (e.g., 1 in 5 homes) were more effective than ones that used simple statements (e.g., your home is at high risk). Adding an intermediate “moderate” risk category increased perceived risk compared to a binary high/low classification system among those in the moderate risk area, without altering perceptions of those at high risk. Other map features (colour and search functionality) had little impact. The best performing map led to 72% more people being willing to test for radon, compared to the map in use by the national Environmental Protection Agency at the time of the study. The results have implications for theories of risk perception and show the potential for techniques from psychological science to help mitigate a real-world environmental risk.

Estimating biotic integrity to capture existence value of freshwater ecosystems

The US Environmental Protection Agency (EPA) uses a water quality index (WQI) to estimate benefits of proposed Clean Water Act regulations. The WQI is relevant to human use value, such as recreation, but may not fully capture aspects of nonuse value, such as existence value. Here, we identify an index of biological integrity to supplement the WQI in a forthcoming national stated preference survey that seeks to capture existence value of streams and lakes more accurately within the conterminous United States (CONUS). We used literature and focus group research to evaluate aquatic indices regularly reported by the EPA's National Aquatic Resource Surveys. We chose an index that quantifies loss in biodiversity as the observed-to-expected (O/E) ratio of taxonomic composition because focus group participants easily understood its meaning and the environmental changes that would result in incremental improvements. However, available datasets of this index do not provide the spatial coverage to account for how conditions near survey respondents affect their willingness to pay for its improvement. Therefore, we modeled and interpolated the values of this index from sampled sites to 1.1 million stream segments and 297,071 lakes across the CONUS to provide the required coverage. The models explained 13 to 36% of the variation in O/E scores and demonstrate how modeling can provide data at the required density for benefits estimation. We close by discussing future work to improve performance of the models and to link biological condition with water quality and habitat models that will allow us to forecast changes resulting from regulatory options.

Shifts in the composition of nitrogen deposition in the conterminous United States are discernable in stream chemistry

Across the conterminous United States (U.S.), the composition of atmospheric nitrogen (N) deposition is changing spatially and temporally. Previously, deposition was dominated by oxidized N, but now reduced N (ammonia [NH3] + ammonium [NH4+]) is equivalent to oxidized N when deposition is averaged across the entire nation and, in some areas, reduced N dominates deposition. To evaluate if there are effects of this change on stream chemistry at the national scale, estimates of N deposition form (oxidized or reduced) from the National Atmospheric Deposition Program Total Deposition data were coupled with stream measurements from the U.S. Environmental Protection Agency (EPA) National Rivers and Streams Assessments (three stream surveys between 2000 and 2014). A recent fine-scaled N input inventory was used to identify watersheds (<1000 km2) where atmospheric deposition is the largest N source (n = 1906). Within these more atmospherically-influenced watersheds there was a clear temporal shift from a greater proportion of sites dominated by oxidized N deposition to a greater proportion of sites dominated by reduced forms of N deposition. We found a significant positive correlation between oxidized N deposition and stream NO3− concentrations, whereas the correlation between reduced N deposition and stream NO3− concentrations were significant but weaker. Sites dominated by atmospheric inputs of reduced N forms had higher stream total organic N and total N despite lower total N deposition on average. This higher stream concentration of total N is mainly driven by the higher concentration of total organic N, suggesting an interaction between elevated reduced N in deposition and living components of the ecosystem or soil organic matter dynamics. Regardless of the proportion of reduced to oxidized N forms in deposition, stream NH4+ concentrations were generally low, suggesting that N deposited in a reduced form is rapidly immobilized, nitrified and/or assimilated by watershed processes.

MOFs-based Fe@YAU-101/GCE electrochemical sensor platform for highly selective detecting trace multiplex heavy metal ions

The construction of sensors with specific recognition functions can easily, sensitively and efficiently detect heavy metal ions, which is a demand in the field of electrochemical sensing and an important topic in the detection of environmental pollutants. An electrochemical sensor based on MOFs composites was developed for sensing of multiplex metal ions. The large surface area, adjustable porosities and channels in MOFs facilitate successful loading of sufficient quantities highly active units. The active units and pore structures of MOFs are regulated and synergetic with each other to enhance the electrochemical activity of MOFs composites. Thus, the selectivity, sensitivity and reproducibility of MOFs composites have been improved. Fortunately, after characterization, Fe@YAU-101/GCE sensor with strong signal was successfully constructed. In the presence of target metal ions in solution, the Fe@YAU-101/GCE can efficiently and synchronously identify Hg2+, Pb2+, and Cd2+. The detection limits (LOD) are 6.67 × 10−10 M(Cd2+), 3.33 × 10−10 M(Pb2+) and 1.33 × 10−8 M (Hg2+), and are superior to the permissible limits set by the National Environmental Protection Agency. The electrochemical sensor is simple without sophisticated instrumentation and testing processes, hence promising for practical applications.

Simulation of Neighborhood‐Scale Air Quality With Two‐Way Coupled WRF‐CMAQ Over Southern Lake Michigan‐Chicago Region

AbstractThe southern Lake Michigan region of the United States, home to Chicago, Milwaukee, and other densely populated Midwestern cities, frequently experiences high pollutant episodes with unevenly distributed exposure and health burdens. Using the two‐way coupled Weather Research Forecast and Community Multiscale Air Quality Model (WRF‐CMAQ), we investigate criteria pollutants over a southern Lake Michigan domain using 1.3 and 4 km resolution hindcast simulations. We assess WRF‐CMAQ's performance using data from the National Climatic Data Center and Environmental Protection Agency Air Quality System. Our 1.3 km simulation slightly improves on the 4 km simulation's meteorological and chemical performance while also resolving key details in areas of high exposure and impact, that is, urban environments. At 1.3 km, we find that most air quality‐relevant meteorological components of WRF‐CMAQ perform at or above community benchmarks. WRF‐CMAQ's chemical performance also largely meets community standards, with substantial nuance depending on the performance metric and component assessed. For example, hourly simulated NO2 and O3 are highly correlated with observations (r &gt; 0.6) while PM2.5 is less so (r = 0.4). Similarly, hourly simulated NO2 and PM2.5 have low biases (&lt;10%), whereas O3 biases are larger (&gt;30%). Simulated spatial pollutant patterns show distinct urban‐rural footprints, with urban NO2 and PM2.5 20%–60% higher than rural, and urban O3 6% lower. We use our 1.3 km simulations to resolve high‐pollution areas within individual urban neighborhoods and characterize seasonal changes in O3 regimes across tight spatial gradients. Our findings demonstrate both the benefits and limitations of high‐resolution simulations, particularly over urban settings.

Association of community walkability and glycemic control among pregnant individuals with pregestational diabetes mellitus

Neighborhood walkability is a community-level social determinant of health that measures whether people who live in a neighborhood walk as a mode of transportation. Whether neighborhood walkability is associated with glycemic control among pregnant individuals with pregestational diabetes remains to be defined. This study aimed to evaluate the association between community-level neighborhood walkability and glycemic control as measured by hemoglobin A1c (A1C) among pregnant individuals with pregestational diabetes. This was a retrospective analysis of pregnant individuals with pregestational diabetes enrolled in an integrated prenatal and diabetes care program from 2012 to 2016. Participant addresses were geocoded and linked at the census-tract level. The exposure was community walkability, defined by the US Environmental Protection Agency National Walkability Index (score range 1-20), which incorporates intersection density (design), proximity to transit stops (distance), and a mix of employment and household types (diversity). Individuals from neighborhoods that were the most walkable (score, 15.26-20.0) were compared with those from neighborhoods that were less walkable (score <15.26), as defined per national Environmental Protection Agency recommendations. The outcomes were glycemic control, including A1C <6.0% and <6.5%, measured both in early and late pregnancy, and mean change in A1C across pregnancy. Modified Poisson regression and linear regression were used, respectively, and adjusted for maternal age, body mass index at delivery, parity, race and ethnicity as a social determinant of health, insurance status, baseline A1C, gestational age at A1C measurement in early and late pregnancy, and diabetes type. Among 417 pregnant individuals (33% type 1, 67% type 2 diabetes mellitus), 10% were living in the most walkable communities. All 417 individuals underwent A1C assessment in early pregnancy (median gestational age, 9.7 weeks; interquartile range, 7.4-14.1), and 376 underwent another A1C assessment in late pregnancy (median gestational age, 30.4 weeks; interquartile range, 27.8-33.6). Pregnant individuals living in the most walkable communities were more likely to have an A1C <6.0% in early pregnancy (15% vs 8%; adjusted relative risk, 1.46; 95% confidence interval, 1.00-2.16), and an A1C <6.5% in late pregnancy compared with those living in less walkable communities (13% vs 9%; adjusted relative risk, 1.33; 95% confidence interval, 1.08-1.63). For individuals living in the most walkable communities, the median A1C was 7.5 (interquartile range, 6.0-9.4) in early pregnancy and 5.9 (interquartile range, 5.4-6.4) in late pregnancy. For those living in less walkable communities, the median A1C was 7.3 (interquartile range, 6.2-9.2) in early pregnancy and 6.2 (interquartile range, 5.6-7.1) in late pregnancy. Change in A1C across pregnancy was not associated with walkability. Pregnant individuals with pregestational diabetes mellitus living in more walkable communities had better glycemic control in both early and late pregnancy. Whether community-level interventions to enhance neighborhood walkability can improve glycemic control in pregnancy requires further study.

Air Quality Integrated Assessment: Environmental Impacts, Risks and Human Health Hazards

The monitoring and evaluation of air quality is a topic of great global interest as, with the decline of air quality, there are negative effects on human health and ecosystems. Thus, the purpose of this paper was to evaluate the air quality over 11 years, in the period 2011–2021, in four cities in Romania, reported as most polluted, namely, Brasov, Cluj-Napoca, Iasi, and Timisoara. Pollutants of interest included arsenic, carbon monoxide, and PM2.5. The measured concentrations of the selected pollutants were collected from the National Environmental Protection Agency public reports. The database considered the daily measurements for the selected pollutants, from three monitoring stations in each city so that the air quality and trends for the last 11 years and impact assessment could be developed. Therefore, the input data were statistically analyzed to identify the trends of air quality, and then, on this basis, the environmental impacts and risks and health hazards were quantified. High concentrations of PM2.5 were recorded for Iasi city, while for Timisoara city, significant concentrations of arsenic were reported. The results regarding the air quality aggregate index, air pollution index, and health hazard index were in the regular range, but in the case of sensitive, vulnerable targets such as children, they were triple compared to adults. The results show that the alert threshold value for PM2.5 was exceeded every year in all four cities, while in the case of Timisoara city, the arsenic air pollution proved to be at a significant level with a major risk for human health.

Pediatric Cancer in the Northeast United States-Letter.

To the Editor,Rees and colleagues (1) examined whether the pediatric cancer rate in the Northeast region is higher than in other regions of the United States. In June 2018, the Centers for Disease Control and Prevention (CDC) released a report indicating that New Hampshire's (NH) pediatric cancer rate is the highest in the United States (2). The NH Department of Health and Human Services determined that the pediatric incidence rate of two rare cancers was significantly higher than expected in a five-town area of NH (3). Understanding whether cancer rates are significantly higher in any particular region and/or state is an important component of identifying and modifying causal risk factors.Rees and colleagues concluded that the pediatric cancer rate in the Northeast region is statistically significantly higher than in other regions. Furthermore, they conclude that the causal risk factor(s) for NH pediatric cancers are likely regional, not localized, deemphasizing environmental contributors while noting that NH and the northeast region have more United States Environmental Protection Agency National Priorities List sites per capita than other regions of the United States.While we are grateful for the attention to the alarming CDC report, we take strong issue with the conclusions drawn by the authors. The hypothesis did not test whether the NH pediatric cancer rate is different than other states within the Northeast region or whether the regional cancer rate is driven primarily by NH. The conclusions in this article are an overextension of the analysis and are a disservice to the important task of identifying and modifying localized causal risk factors for cancer prevention.A significantly elevated regional risk of pediatric cancer in the Northeast is a valuable finding and one piece of a larger puzzle of data analysis and interpretation. The high incidence rate in the Northeast and NH demands further investigation. There are many contextual effects of pediatric cancers to explore; there are also geographic community-level exposures that potentially contribute to an increased risk of cancer [e.g., perfluoroalkyl and polyfluoroalkyl substance (PFAS)-contaminated drinking water and air]. The authors have access to individual-level data which would facilitate analysis of possible community-level contextual effects contributing to elevated cancer risk. For example, we recently found an elevated risk of several types of cancer in a community with known PFAS contamination in groundwater (4).Finally, it is worth noting that the authors used a Bonferroni correction to avoid type 1 error, in which the null hypothesis is rejected for spurious associations resulting from multiple comparisons. A conservative alpha of 0.01, rather than the standard alpha of 0.05, was used to assess statistical significance. Biostatisticians debate the necessity of conservative alphas, given large adjustments to avoid a type 1 error increase the likelihood of a type 2 error, where meaningful group differences are missed. We suggest a more prudent approach rather than one that risks an unwarranted trade-off in the likelihood of type 1 and 2 errors. In fact, the CDC used a 95% confidence interval when they determined that the pediatric cancer rate in NH is the highest in the nation.A full and transparent assessment of the environmental and public health damage is an essential step in that process since most cancer diagnoses could be prevented by minimizing environmental causes (5). The field would be well served by using resources to inspect internal surveillance, policies, and regulations to prevent environmental exposure and focus attention and resources on prevention and mitigation. We sincerely hope that Rees and colleagues, and others, direct resources to identifying and modifying localized factors contributing to cancers while focusing on prevention. We owe it to NH children who experience the highest risk of pediatric cancer in the nation.See the Response, p. 150No disclosures were reported.

Neighborhood Emission Mapping Operation (NEMO): A 1-km anthropogenic emission dataset in the United States

We present an unprecedented effort to map anthropogenic emissions of air pollutants at 1 km spatial resolution in the contiguous United States (CONUS). This new dataset, Neighborhood Emission Mapping Operation (NEMO), is produced at hourly intervals based on the United States Environmental Protection Agency (US EPA) National Emission Inventories 2017. Fine-scale spatial allocation was achieved through distributing the emission sources using 108 spatial surrogates, factors representing the portion of a source in each 1 km grid. Gaseous and particulate pollutants are speciated into model species for the Carbon Bond 6 chemical mechanism. All sources are grouped in 9 sectors and stored in NetCDF format for air quality models, and in shapefile format for GIS users and air quality managers. This dataset shows good consistency with the USEPA benchmark dataset, with a monthly difference in emissions less than 0.03% for any sector. NEMO provides the first 1 km mapping of air pollution over the CONUS, enabling new applications such as fine-scale air quality modeling, air pollution exposure assessment, and environmental justice studies.

Air Pollution and Maximum Temperature Are Associated with Neurodevelopmental Regressive Events in Autism Spectrum Disorder

Neurodevelopmental regression (NDR) is an enigmatic event associated with autism spectrum disorder (ASD) during which a child loses previously acquired skills and develops ASD symptoms. In some, a trigger which precedes the NDR event, such as a fever, can be identified, but in many cases no trigger is obvious. We hypothesize that air pollution (PM2.5) may trigger NDR, especially in those children without an identified trigger. Average daily PM2.5, ozone, precipitation and maximum temperature (Tmax) were derived from Environmental Protection Agency models and National Oceanic and Atmospheric Administration monitors based on zip-code information from 83 ASD participants during the six-weeks following the onset month of an NDR event and a reference period defined as one year before and one year after the event. Seasonally adjusted logistic regression (LR) and linear mixed models (LMM) compared cases (with a history of NDR) and matched controls (without a history of NDR). LR models found that the risk of NDR was related to higher PM2.5 during 3 to 6 weeks of the NDR event period, particularly in those without a trigger. Overall, both models converged on NDR being related to a higher PM2.5 and lower Tmax both during the NDR event period as well as the reference period, particularly in those without a known trigger. This temporal pattern suggests that environmental triggers, particularly PM2.5, could be related to NDR, especially in those without an identifiable trigger. Further studies to determine the underlying biological mechanism of this observation could help better understand NDR and provide opportunities to prevent NDR.