2024 EHE Research Retreat

Functional Assessment of hiPSC Derived Brain Organoids to Study the Effects of Chemical Exposure and Electrical Stimuli on Synaptic Plasticity

Cognitive endpoints are used in human and animal studies to determine if a chemical will cause neurodevelopmental toxicity in drug screening. Currently, there are no in vitro assays that can be used to assess cognition, therefore, to determine the effect a chemical has on learning and memory, animal models are used. Recent advances in cell culture including Microphysiological Systems (MPS) allow more physiologically relevant modeling of the cellular processes in vitro and bring the in vitro models closer to in vivo. Our lab established a highly standardized and reproducible hiPSC derived brain organoid MPS consisting of all neural cell types found in the central nervous system, myelinated axons, and spontaneous local field potentials. Using this MPS we aim to assess the extent of learning and memory in a dish to determine the effect a chemical has on synaptic plasticity so this platform can be used for high throughput drug screening. To research this, we have been differentiating brain organoids for up to 12 weeks and characterizing spontaneous and modulated electrical activity using live calcium imaging and HD MEAs. In addition, we characterized the molecular components of early synaptogenesis, including immediate early genes (IEGs) and miRNAs over time in conjunction with chemical exposure by immunohistochemistry and RT-PCR. Organoids showed spontaneous electrical activity using both HD MEAs and calcium imaging and overtime showed evidence of highly interconnected network formation within and between organoids. Additionally, we saw time-point specific expression of IEGs over development, which are known to be involved in synaptic plasticity. Additionally, our results show that receptor agonists and antagonists impact IEG expression and electrical activity. In the future, we plan to build upon this model to study how long-term potentiation is affected by chemical and electrical exposures to develop a model to perform high throughput chemical screening to assess functional changes in synaptic plasticity. An in vitro cognition assay developed for hiPSC brain organoid MPS can fill the gap between human and animal data while increasing throughput for drug screening to test for the effect of chemicals on neurodevelopment and neurodegeneration.  

Single Particle Inductively Coupled Plasma Mass Spectrometry for the Investigation of Metal Nanoparticle Content of Electronic Cigarette Devices

Background and Purpose:   Current use of electronic cigarette’s (e-cigs) among youth is of concern due to our lack of knowledge of the potential health effects and lack of a comprehensive understanding of the aerosol components.  Currently heavy metals such as chromium (Cr), nickel (Ni) and lead (Pb) among others have been identified in electronic cigarette aerosols but we do not know if these metals are a particle or free in solution as ions.   Because the bioavailability of metals depends on their solubility, studies are needed to characterize metals in aerosols to assess potential harm from using e-cig.  The goal of this research is to characterize metals in aerosols generated from  FDA devices and popular e-cig devices.  To accomplish this goal, a novel technique was developed using single cell ICP-MS  

Method:   Condensates were collected from aerosols generated from three different brands of devices and two flavors for each type of device each in triplicate for a total of eighteen devices evaluated.  The devices used were: Bar Blue Raspberry, Elf Bar Gumi, Orion Bar Blueberry Raspberry, Orion Bar Cool Mint, Vuse Alto Menthol, Vuse Alto Golden Tobacco.  Condensate was collected using our published method of collecting aerosol with the following puff protocol. 200 three second puffs were collected into a metal free 15mL tube and stored at 4 C until metal analysis.  Prior to analysis, samples were thoroughly mixed by inverting the tubes and vortexing and diluted 1:100 in MQ water or in 2% optima HNO3.  Levels of metal particles were measured using the ESI MicroFast autosampler tandem to an Agilent 8900 ICP-MS operated in single particle mode with a dwell time of 0.1s.  Single particle data analysis was performed using SPCal.  Bulk metal analysis was preformed using an Agilent 8900 in conventional analysis mode and MassHunter 5.1 for data analysis.   

Results:  Particles with different metals were detected in condensate collected from different devices:  Specially the FDA approved Vuse devices had increased number of particles containing Zn, Ni, and Cu. Geometric means for particles size of detected differed based on device brand and metal detected.  Both nanoparticles (<100 nm) were detected as well as particles larger than 100 nm.  Bulk analysis indicated the presence of several metals Cr, Co, Cd, and As that were not present in the nanoparticles detected.   

Conclusions:  This work demonstrates that metal-containing nanoparticles are present in varying concentrations and sizes in popular e-cig devices.  Understanding that e-cig users are exposed to nanoparticles containing metals increases our understanding of the potential taxological effects of e-cig use, helps us to design better experiments, provides evidence for risk assessment and informs policy.  Lastly, this is the first research to use SP-ICP-MS to characterize metals in e-cig aerosols. 

Use of Multi-pollutant Air Sensor Network to Identify Coal Dust and Other Sources of Air Pollution in Curtis Bay, South Baltimore 

Background: For decades, South Baltimore community organizations and residents have expressed concerns about the environmental and health impacts of local industrial air pollution, including pollution from a longstanding coal terminal. A December 2021 explosion at the terminal intensified these concerns, and we established the South Baltimore Air Monitoring Network in May 2022 to characterize air quality in Curtis Bay. Considering the many sources of air pollution in Curtis Bay, non-negative matrix factorization (NMF) is a statistical approach for source attribution that can be used to identify these sources. 

Objective: To use NMF to identify sources of air pollution and the duration/frequency of putative coal dust (PCD) threshold exceedances in Curtis Bay, South Baltimore. 

Methods: We applied NMF to four locations in the monitoring network, where we co-located QuantAQ MODULAIRs and Distributed Sensing Technologies (DSTech) ObservAir monitors. We input the following pollutants into NMF: PM1, PM2.5, PM10, total suspended particles (TSP ~ PM40), black carbon, carbon monoxide (CO), nitric oxide (NO), and nitrogen dioxide (NO2). 

Results: Clear PCD factors emerged at 2 of the 4 locations, and we found PCD exceedances of the highest thresholds, on average, nearly once every hour and a half. Closest to the terminal, the average duration of the highest threshold exceedance was >6 consecutive minutes, with decreasing mean durations as distances from the terminal increased. PCD factor peaks also corresponded with team-identified coal dust events and helped to identify additional events around the network. 

Conclusion: We applied NMF to data from four locations in the South Baltimore Air Monitoring Network, and PCD factors emerged at locations closest to the terminal. Further, closer to the terminal, we noted that the mean duration of PCD events was higher relative to locations farther from the terminal. Further analyses are required to address issues of PM autocorrelation and the NMF normalization scheme. 

Exposures to Pesticides in an Occupational Chilean Cohort

Introduction: The intensification of agriculture in Chile has increased potential exposure to agrochemicals, including pesticides linked to a wide array of adverse health effects. The Maule region is one of Chile’s leading agricultural regions with the 2nd largest sales of pesticides in the country. However, biomonitoring efforts in Latin America, including Chile, are scant, limiting the evaluation of the role that pesticides may have in the etiology of chronic diseases.  

Methods: We conducted a cross-sectional study to assess exposure to pesticides commonly and historically used in Maule. Spot urine samples were collected from a subset of adults participating in the ongoing prospective Maule Cohort study (n=470) in Chile. Seventeen pesticide biomarkers, including organophosphates, pyrethroids, and phenoxyacetic acids were quantified in urine samples using LC-MS/MS.  

Results: Detection frequencies for pesticide biomarkers in urine samples were between 32-100%. Specific gravity corrected biomarkers of chlorpyrifos (P50=1.80 g/L), profenofos (P50=0.08 g/L), 3-phenoxybenzoic acid (p50=0.78 g/L), 2,4-dichlorophenoxyacetic acid (P50=0.01 g/L), 2,4-Dichlorophenol (P50=2.4 g/L), 4-hydroxy-pyrimethanil (P50=0.6 g/L), and hydroxy tebuconazole (P50=0.30 g/L) were detected in >70% of the study population. For the most frequently detected biomarkers, concentrations were generally higher in female versus male participants.  

Conclusion: Analyses are ongoing and will include further interrogation of patterns of exposure to pesticides among participants and evaluation of exposure determinants to identify modifiable risk factors in this vulnerable population. 

Formaldehyde dehydrogenase-derived formate contributes to cardioprotection in the female heart 

Ischemic heart disease is a leading cause of death in the US, manifesting as ischemia/reperfusion injury, yet the risk is lower in premenopausal women vs. age-matched men and postmenopausal women. Previously, we found female hearts to contain two-fold more formaldehyde vs. males. Interestingly, females also have higher activity of formaldehyde dehydrogenase (FDH), which detoxifies formaldehyde to formate. Importantly, we found that FDH knockout exacerbates I/R injury in female hearts. The objective of this study is to investigate a potential role for estrogen in the regulation of formaldehyde metabolism. We hypothesize that estrogen enhances formaldehyde metabolism in females to increase formate. Langendorff-perfused hearts were subjected to I/R injury, and function and infarct size were assessed. Whole hearts were also perfused and used for molecular analysis. We found a significant decrease in FDH activity in ovariectomized (OVX) female hearts suggesting a role for estrogen in formaldehyde metabolism. Interestingly, several formaldehyde-producing enzymes were more highly expressed in females as compared to male and OVX hearts. Further, formate treatment reduced infarct size in male hearts when subjected to I/R injury. We also found more formate in plasma from females vs. males, potentially explaining the blunted protection observed with formate in females. More importantly, we found that formate served as an effective rescue for FDH knockout female hearts, significantly reducing infarct size following I/R injury. Taken together, our findings demonstrate that formate protects against I/R injury and further suggest that FDH-derived formate is a critical component of female-specific cardioprotection.  

"We were on our own": Animal slaughtering and processing industry workers’ perspectives on workplace health and safety during COVID-19 in North Carolina 

Background: Animal slaughtering and processing industry workers have been disproportionately affected by the COVID-19 pandemic, with high numbers of cases and deaths. Animal slaughtering and processing work has long been recognized as difficult and dangerous, and many workers are members of marginalized communities.  

Objective: The objective of this study was to describe animal slaughtering and processing industry workers’ perspectives on workplace safety and health practices during COVID-19, including the extent to which these practices met voluntary federal guidance and affected workers’ well-being.  

Methods : We conducted a survey of 69 animal slaughtering and processing industry workers in North Carolina during April 2021 to July 2022 and in-depth interviews with 9 workers during July 2022 to April 2023. We summarized survey results with descriptive statistics. We used a combination of inductive and deductive coding to identify themes and patterns in the qualitative data and integrated quantitative and qualitative findings narratively.    

Results: Nearly all survey participants reported their employer provided (94%) and required (90%) face masks, while engineering controls like physical barriers (35%) and administrative controls like changes in workplace sick leave (19%) were less frequently reported. Interview participants also described reductions in control measures over time. While most survey participants (92%) reported feeling able to isolate or quarantine for COVID-19, interviews revealed many obstacles to taking off work when ill. Interview participants across job and operation types described production as management’s primary priority, with consequences for safety and health.  

Conclusion: Surveys and interviews suggest that voluntary guidance during the COVID-19 pandemic was inadequate to ensure the animal slaughtering and processing industry implemented comprehensive infection prevention and control measures, especially adequate paid sick leave and provisions for physical distancing. An enforceable workplace infectious disease standard could improve animal slaughtering workplace safety, health, and well-being.  

Estimating and validating the time-varying generation rate of peracetic acid (PAA) for use in exposure modeling 

Presenter: Ryan Hines, MS, CIH 

Background:  Peracetic acid (PAA) is a commonly used disinfectant in the healthcare industry as it can be used as a ‘no-rinse’ product with relatively short contact time and environmentally benign breakdown products. A study conducted in 2017 indicated that 58% of hospital cleaning staff using a cleaning product containing PAA reported work-shift upper airway irritation, although concentrations of PAA were measured below the occupational exposure limits. Despite these potential concerns, very few occupational exposure assessments have been conducted on the use of PAA.  

Objective: Our research study aimed to determine the generation rate of PAA from surfaces using controlled chamber experiments across varying environmental conditions. 

Methods: The generation rate of PAA was determined experimentally in a 25 m3 exposure chamber, by applying a known-mass of chemical to a surface and using the ‘Small-Spill’ model to assess the evaporation rate for use in determining the time-varying generation of PAA. This empirically derived generation rate was determined across a range of environmental conditions by varying the ventilation rate, surface substrate, and local windspeed. The expected concentrations of PAA were then modeled and compared to observed concentrations from simulated cleaning tasks. 

Results/Conclusion: Our results indicate that the evaporation rate (mean(SD) = 1.18 min-1 (0.32)) of PAA remained consistent under differing test conditions, suggesting that it can be reliably used in a range of settings.  The model results showed good correlation (r = 0.91 – 0.98) between the empirically-derived generation rates in the controlled experiment with the simulated real-world conditions.  The evaporation rate parameter derived from this work will allow occupational health professionals to model potential exposures to aid in improving worker safety and health. 

Heavy metal mixture elicits less than additive neuronal impairment in human cortical microphysiological system 

Background: Heavy metal exposure can impair neurodevelopment through disrupted cellular proliferation, differentiation, and network formation. While contaminants are regulated individually, exposures don’t occur in isolation. 

Objective: Our objective is to characterize metal mixture toxicity during an early and late window of neurodevelopment in a human cortical microphysiological system (MPS). 

Methods: MPS were treated with low doses of Pb, Cr, As, and Cd alone and in combination during early (0-4 week) and late (8-12 week) stages of differentiation. Viability was confirmed with resazurin reduction. Fluorescence microscopy was used to quantify the density of synapses with excitatory neurons (SYN1+/PSD-95+), as well as neurite outgrowth (BTUBIII). Synaptic density was analyzed with SynapseJ while neurite length and density was quantified with Sholl Analysis.  

Results: Following late developmental exposure to Cr, pre- and postsynaptic puncta analysis with SynapseJ revealed a slight reduction in the density of synapses with excitatory neurons, attributed to a reduction in presynaptic puncta fluorescence intensity density. No other condition, including mixture, elicited significant effects. Subsequent neurite outgrowth assay revealed no significant effect for Cr during this same timepoint, indicating that impaired synaptogenesis is likely not due to impaired microtubule growth in extending axons or dendrites. However, neurite outgrowth was impaired in Pb exposed 8 to 12 week BrainSpheres, with the same magnitude of impairment observed in mixture-exposed BrainSpheres. 

Conclusion: Co-exposure to a mixture of all metals does not impair neurite outgrowth or synapse formation to a greater degree than metals or metalloids alone. Many diverse explanations may account for this effect, including the possibility of metals in mixture scenarios complexing outside the BrainSphere, saturating transporters, or eliciting a more pronounced compensatory response to overcome functional deficits resulting from contaminant challenge. Further investigation into the mechanism of competition will be pursued. 

Mapping epigenetic markers in autism spectrum disorders from the overlap of GWAS and EWAS genesets

Background: The increasing prevalence of neurodevelopmental disorders, such as ASD, ADHD, and schizophrenia, is of major public health relevance. A prevailing theory is that this increase may be in part mediated by the interaction between environmental exposures and transcriptional-level changes. However, previous analyses of GWAS and EWAS studies have relied on pre-existing annotations of single-nucleotide polymorphisms (SNPs) and methylation patterns to identify genes and pathways of interest, which cuts many un-annotated sites, especially those in non-coding regions, out of their analyses.  

Objective: Expanding the identification SNPs and methylation patterns of interest in coding and non-coding regions could illuminate relevant pathways and differentially expressed genes involved in the underlying etiology of these conditions. Therefore, we seek to identify which genes and gene-sets overlap in GWAS and EWAS datasets to identify new pathways of interest disturbed in autism diagnoses. 

Methods: First, we will identify GWAS and EWAS datasets with previously identified but unannotated SNPs and methylation sites of interest in coding and non-coding regions expressed in autism spectrum disorders. Then, incorporating functional weighting into our analysis will allow for the identification of critical genes and genesets associated with autism diagnoses and biological processes.

Results and Conclusion: Preliminary screens of GWAS and EWAS datasets have provided initial directions for trial runs. Further optimization of inclusion/exclusion criteria, a more expansive dataset search, use of different functional weighting methods, and preliminary analysis of genelists will provide a more robust set of genes and genesets involved in the etiology of autism spectrum disorders. 

Assessment of ambient fenceline gas concentrations related to industrial livestock operation (ILO) compared to non-ILO waste processing infrastructure  

Background  

Hydrogen sulfide (H2S), methane (CH4), and ammonia (NH3) are health- and climate relevant pollutants emitted from industrial livestock operation (ILO) facilities, as well as non-ILO-related infrastructure. In this study, we compare background concentrations and spatio-temporal variability of H2S, CH4 and NH3 at ILO and non-ILO facilities in North Carolina (NC), Delaware (DE), and Maryland (MD). 

Methods  

Between August and November 2022, we performed 27 trips in MD (2 drives), DE (8 drives) and NC (17 drives). Driving routes were designed to target swine concentrated animal feeding operations (CAFOs) and related waste infrastructure, such as waste lagoons (capped and uncapped) and biogas storage facilities associated with anaerobic digestion (AD) pipelines. Concentrations of CH4, NH3 and H2S were assessed using a car equipped with gas concentration analyzers (G2204 and G2103, Picarro Inc, Santa Clara, CA). To link gas concentrations with geographical locations and time, the Strava running application was used to record geospatial coordinates of the car during the mobile monitoring runs.  

Results  

Preliminary results indicate that average gas concentrations near uncapped swine CAFO lagoons were higher than average background concentrations for CH4 and H2S. We recorded the highest value of H2S (238 ppb) close to a biogas storage facility in North Carolina, although the highest mean value corresponded to the wastewater treatment plant AD facility (9.6 ppb) during a 30-minute interval. In contrast, the highest CH4 value (32.3 ppb) we observed was near uncapped swing CAFO lagoons. 

Conclusion  

Mobile monitoring approaches to ILO facility emissions have shown elevated gas concentrations near waste storage facilities and anerobic digestion facilities. The concentrations of these gases are similar and sometimes greater to those emitted by non-ILO waste infrastructure, which is more highly regulated compared to ILO emissions.  

Nephelometric and Gravimetric Analysis of Ambient PM2.5 in South Central Uganda

Background: This study addresses the critical gap in PM2.5 research in Sub-Saharan Africa, particularly focusing on South Central Uganda. While previous research primarily pertains to high-income western nations, this study explores PM2.5's impact in low- and middle-income countries, with an emphasis on the rural Rakai District.

Objective: To quantify the differences in PM2.5 levels between urban (Masaka and Kampala) and rural (Rakai District) areas of South Central Uganda and to uncover temporal trends influencing these concentrations.

Methods: Utilizing 27 PurpleAir sensors and the E-Sampler device, the study conducted comprehensive ambient air quality monitoring. The analysis employed advanced calibration methods, including machine learning techniques, to ensure accurate PM2.5  measurement and prediction.

Results: The study revealed stark disparities in PM2.5 concentrations, with urban areas like Kampala averaging 55.7 ± 20.3 μg/m3, significantly exceeding WHO guidelines. In contrast, rural areas exhibited lower concentrations. The XGBoost model emerged as the most accurate predictive tool, demonstrating a high correlation (R=0.96) with actual measurements, and outperforming other models in varied environmental conditions.

Conclusion: The findings illuminate the pronounced variance in air quality between urban and rural regions of Uganda, emphasizing the necessity for targeted air quality management strategies in LMICs. The successful application of low-cost sensors and advanced analytical models in this study sets a precedent for similar research in other developing regions, advocating for localized air quality monitoring and policy formulation. 

Hydroxymethylation is involved in the DNA Damage Response in Glioblastoma Stem Cells

Background: Glioblastoma (GBM) is an aggressive and lethal type of brain tumor, with a five-year patient survival rate of less than seven percent. Epigenetic reprogramming is now appreciated as playing a substantial role in cancer initiation and progression. Previous studies have shown that loss of the Ten-eleven translocation (TET) enzymes, which catalyze the conversion of DNA Methylation (5mC) to Hydroxymethylation (5hmC), impairs the DNA Damage Response (DDR) in glioma cells. Additionally, loss of hydroxymethylation has been associated with worse GBM patient prognosis. However, the mechanisms behind these associations are not yet fully understood. 

Objective: The objective of this research is to understand the involvement of hydroxymethylation in the DDR in GBM stem-like cells (GSCs).  

Methods: Dot blots and Trypan Blue assay were used to analyze changes in global DNA methylation and cell viability. respectively. The involvement of 5hmC in the DNA Damage Response was assessed by quantifying changes in 5hmC levels after treatment with DNA damaging agents and a chemical inhibitor of 5hmC production. Co-localization of 5hmC with DNA Damage Response proteins was determined using immunocytochemistry and proximity ligation assays. Endpoints were assessed in GSCs. 

Results: Here we show that 5hmC increases after treatment with DNA Damaging Agents (Temozolomide and Ionizing Radiation) in GSCs. We further show that 5hmC co-localizes with proteins involved in multiple DDR pathways, including Non-Homologous End Joining (NHEJ) and Homologous Recombination (HR). 

Conclusion: We propose that 5hmC plays an important role in the DNA Damage Response pathway in GSCs by interacting with DDR proteins. We further propose that the involvement of 5hmC in the DDR is independent of the canonical role of regulating gene expression. These findings highlight the importance of understanding epigenetic dysregulation in GSCs and provide some insight into potential mechanisms behind the association between hypo-hydroxymethylation and worse prognosis observed in GBM patients. 

Equity Considerations for Climate and Health Research: A Review of the Literature on Disparate Health Impacts due to Hurricanes and Structural Determinants of Vulnerability

Background: Understanding vulnerability to climate related disasters, such as hurricanes, is crucial for targeting and identifying mitigation and adaptation measures. However, vulnerability assessments often focus on proximal factors and may obscure underlying drivers of health inequities.

Objective/aim: We sought to describe the existing literature on defining vulnerability to hurricanes and develop a framework to incorporate structural determinants of vulnerability.  

Methods: We conducted a literature search in the National Library of Medicine’s MEDLINE/PubMed database. We identified peer-reviewed, population-based research articles assessing equity or vulnerability within the context of hurricane-related health impacts in the U.S., from January 2000 through October 2022. For each study, we determined whether the approach pre-specified vulnerable populations or characterized vulnerability empirically. We also abstracted data on the types of factors used to assess vulnerability to hurricanes (e.g., demographic, structural, etc.). Finally, we developed a framework to guide research on structural determinants of vulnerability to hurricanes.

Results: The initial search resulted in 631 articles. After completion of the title screening, abstracts and full texts of the remaining articles (n=213) were screened and an additional set (n=9 excluded. For the included studies (n=121), 2) were the majority (n=69) pre-specified vulnerable populations of interest, while the remaining 43% (n=52) empirically derived vulnerability. Among all studies, there were common categories of vulnerability, with some overlap: demographic (e.g., race/ethnicity, age, etc.; n=81), spatial (e.g., census tracts, neighborhoods, etc.; n=26), and health status (n=17). Less common categories were outcomes (e.g., displaced; n=6), structural (n=5), and occupational (n=1). Studies on structural vulnerabilities revealed systemic issues of racism, governance, institutions, and infrastructure deficiencies, forming the basis of our conceptual framework.

Conclusion: Most studies on hurricane vulnerability do not consider systemic, upstream factors that contribute to health inequities. Research to drive systemic interventions requires a shift in focus to structural determinants of vulnerability to climate-related disasters .

Cross-sectional associations of urinary phthalate and serum PFAS biomarkers with serum total 25-hydroxyvitamin D levels in childhood: The HOME Study

Background: Exposure to endocrine disrupting chemicals, such as phthalates and per-/poly-fluoroalkyl substance (PFAS), may disrupt vitamin D metabolism and adversely affect health. These relations have been assessed in adults but not children. 

Objective: We aimed to investigate associations of urinary phthalate and serum PFAS biomarker concentrations with serum total 25-hydroxyvitamin D [25(OH)D] levels at ages 8 and 12 years in the HOME Study. 

Methods: We performed a cross-sectional analysis of data on 233 children of women enrolled during pregnancy in a prospective cohort study in Cincinnati, OH (2003-2006). We measured 9 phthalate metabolites in spot urine samples and 4 PFAS and total 25(OH)D in serum samples collected at ages 8 (n=186) and 12 (n=186). We categorized children as vitamin D deficient if total 25(OH)D was <20ng/mL (age 8: 15.6%, age 12: 32.3%). Using generalized estimating equations to account for repeated measures within-child, we estimated differences in 25(OH)D (linear regression) and odds of vitamin D deficiency (logistic regression) per interquartile range (IQR) increase in concurrent log2 biomarker concentrations. We also used quantile-based g-computation to estimate associations of a simultaneous IQR increase for all phthalate and PFAS biomarkers with vitamin D outcomes. We adjusted for covariates such as race, sociodemographics, BMI z-score, diet, and season.

Results: Urinary phthalate metabolite and serum PFAS concentrations were weakly associated with higher total 25(OH)D and lower odds of vitamin D deficiency though most confidence intervals crossed the null. In mixtures analyses, an IQR increase in all phthalate and PFAS biomarkers was associated with 6.3 ng/mL (95% CI: 2.9, 9.8) higher total 25(OH)D and 0.3 (95% CI: 0.2, 0.8) times the odds of vitamin D deficiency.

Conclusions: Combined phthalate and PFAS exposure was associated with higher total 25(OH)D levels and lower odds of vitamin D deficiency in HOME Study children.  

From Lines of the Past to Present Divides: Exploring the Impact of Historical Redlining and Modern Segregation on Housing Quality

Introduction: During the 1930s, the US government created the Home Owner's Loan Corporation (HOLC), which denied financial services based on the racial composition of neighborhoods. HOLC graded neighborhoods from A to D, with D areas marked in red (redlined) and considered places where property values were most likely to decline. Atlanta, like many other US cities, faced severe historical redlining, leading to a lack of investment in communities of color. Environmental health research has shown that redlining is a significant issue, but few studies have examined the link between redlining and modern housing quality. 

Methods: This study adopts an ecological approach, utilizing spatial analysis and Bayesian statistical methods, to investigate how historical redlining, modern-day segregation, and housing code violation complaints relate to each other. Between 2015 and 2019, residents reported hazardous and non-hazardous code violations to the City of Atlanta, which are used here to provide context towards housing quality. 

Results: Point pattern and spatial clustering analyses revealed that both total and hazardous complaints were concentrated in west and southern Atlanta, especially in areas graded C and D. Hazardous complaints were exclusively reported in D areas. A Bayesian multilevel Poisson regression showed that HOLC grades C and D, moderate and high non-white areas, high modern-day segregation, number of renters, vacancies, and home age were significant predictors of total complaints. However, HOLC grade C and modern-day segregation were insignificant for hazardous complaints. 

Conclusion: This study highlights that historical redlining is linked to modern-day housing quality. Housing complaints provide a powerful tool to investigate housing quality. Further investigation can provide critical information for evaluating associations with health outcomes and drive targeted policies and interventions to address housing disparities.  

Estimating Institutional Greenhouse Gas Emissions:  A Life Cycle Assessment of New York City High Schools

Background: Food systems are a major contributor of anthropogenic greenhouse gas (GHG) emissions. Recognizing this, local governments and public institutions have committed to reducing their food system' GHG emissions. While shifting menus towards more plant-based options is a key strategy that's been established in the literature, other supply chain opportunities to reduce GHG emissions at the institutional level are less well understood. 

Objective: To estimate the sources and breakdown of food system GHG emissions for the New York City (NYC) Department of Education High Schools in 2019. 

Methods: We developed a cradle-to-grave life cycle assessment for a standard NYC high school lunch menu from January 2019. We estimated the GHG emissions (kg CO2-eq) for the entrée items from food production, processing, packaging, transportation, storage & preparation, serving & consumption, disposal transportation, and disposal. We explored the potential change in GHG emissions of three policy interventions currently enacted in NYC.

Results: On average, the GHG emissions per serving were relatively low (1.48 kg CO2-eq) but impactful when scaled to all high schools. There was substantial variability in the percent that post-farmgate GHG emissions (i.e., GHG emissions that result after a food item has left the farm or processing facility) contributed to total GHG emissions. The post-farmgate emissions for the vegetarian item were 67% of total GHG emissions, around 30% for the poultry and dairy items, and 5% for the cheeseburger. When implemented together, we observed that two interventions – no food waste to landfills and sourcing foods within 200 miles - could reduce total GHG emissions by an average of 2 percent.

Conclusion: As institutions shift towards more plant-based menus, it will be important to prioritize post-farmgate interventions to reduce greenhouse gas emissions further, but careful consideration is needed on what interventions will be most successful. 

Brain MPS: Towards Human Brain Complexity​ 

Recent advancements in brain microphysiological systems (bMPS) have significantly enhanced our understanding of neurological functions and disorders. These systems, including 3D spheroids, organoids, and organ-on-chip models, closely mimic human brain cellular architecture and functionality. However, they often lack the complexity of neuronal circuitry and regional organization found in the human brain, crucial for higher-order brain functions.  

In this study, we present two significant innovations to overcome these limitations. Firstly, we introduce a chemically defined glial-enriched medium (GEM) that effectively expands the population of astrocytes and oligodendrocytes in bMPS without affecting neuronal differentiation.  

This method not only increases the number of glial cells but also enhances their morphology, more closely resembling primary culture astrocytes. Our results demonstrate that GEM bMPS maintain electro-chemical activity, showing varied patterns of Ca+2 staining and flux, and the presence of synaptic vesicles and terminals observed by electron microscopy. Notably, GEM improves neurite outgrowth, cell migration, and differentially modulates neuronal maturation in diverse iPSC lines, advancing the in vivo-like functionality of bMPS for studying neurological diseases and drug discovery.  

Secondly, we propose a novel microfluidic system that functions as a surrogate vasculature to support the growth of brain organoids up to 10 mm. This system addresses the limitation of passive diffusion in traditional 3D organoids, often leading to necrosis at the core. 

By supporting larger organoids, we can significantly increase the biological complexity and inter-regional connections, mimicking the human brain's regional organization more effectively.  

Our approach combines these advancements to create a brain organoid model with substantially higher complexity. We plan to exploit this model for studying learning and memory, and cognitive decline in neurodegenerative models like Alzheimer’s Disease.  We aim to replicate disease hallmarks, explore neurodegenerative agents, and profile drugs affecting learning and memory.   

The effect of perinatal and early-life exposure to metal mixtures on neurodevelopment

Background and Objective: Accumulating evidence suggests that exposure to certain heavy metals contributes to neurobehavioral and cognitive deficits and may play a role in the pathogenesis of several neurodevelopmental disorders such as autism spectrum disorder (ASD). Metal toxicity increases the formation of reactive oxygen species (ROS) and can elevate oxidative stress in the nervous system. In the present study, we tested the hypothesis that perinatal and early-life exposure to PACC metal mixture (Pb, As, Cd, and CrVI) induces developmental neurotoxicity.  

Methods: To test this hypothesis female C57BL/6J mice were exposed to PACC mixture 2 weeks preconception until weaning of the F1 generation at 3 weeks of age. The F1 offspring (4 weeks of age) underwent behavioral studies, including a Novel object recognition test [NOR] (learning and memory deficits) and an elevated plus maze [EPM] (Anxiety). At 5-6 weeks these mice were euthanized, and their brain slices were used for electrophysiology and brain and serum samples were used for molecular analysis. 

Results: Our preliminary data reveals that PACC exposure at respective maximum contaminant levels (MCL) for Pb, As, Cd, or maximum action level (ACL) for Pb, has adverse effects on cognition and anxiety levels, as measured by NOR and EPM. Patch clamp recording from mPFC and hippocampus CA1 neurons in acute brain slices shows PACC metal exposure results in increased input resistance and intrinsic excitability. These physiological changes made PACC-exposed neurons enter into a hyperexcitable state. 

Conclusions: Our study indicates that perinatal and early-life exposure to PACC metal mixture at supposedly “safe” drinking water levels leads to developmental neurotoxicity and potentially neurological disorders. Future studies will focus on transcriptomic analysis of brain tissues and pharmacological experiments to determine the mechanism underlying the PACC exposure effect. 

An immune competent brain MPS for Gene and Environment studies in ASD 

Autism Spectrum Disorders (ASD) are behaviorally defined neurodevelopmental disorders that are increasingly prevalent in society—affecting up to 1 in 36 children in the US, a 316% increase since 2000. Despite the increasing prevalence of ASD, the pathogenesis is still unknown; however, brain hyperconnectivity, neuroinflammation and neurotransmitter imbalances are established molecular features of autism. This project aims to establish an immune competent brain microphysiologic system (MPS) that can be used to identify potential convergences across ASD risk alleles and disease severity while investigating Gene and Environment interactions (GxE) that may impact ASD development and progression. Human iPSC derived brain microphysiologic systems recapitulate key features of human neural development and activity, can be generated from patient derived cell lines, and provide a reproducible assay for neurotoxicity determination. Microglia are brain resident immune cells that derive from the yolk sac in early brain development and are thus absent in traditional neuroectoderm derived MPS. Here, we separately derive microglial progenitors and neural progenitors which can then be incorporated into aggregates for subsequent maturation and development. We have demonstrated that microglia survive for the full timeline of maturation, express several key markers and are capable of interacting with and responding to their environments. In future work we aim to characterize their role in ASD pathogenesis and environmental risk factors. Through collaborations with the Kennedy Krieger Autism Center for Excellence we are working to establish brain MPS for genetic risk factors with varying ASD penetrance to investigate the individual and overlapping impacts of known autism risk alleles on neuronal growth and development. Subsequently we will determine whether individual ASD risk alleles contribute to increased susceptibility to ASD-associated environmental exposures, and potential GxE interactions 

The Influence of Weather Patterns on Water Collection Labor in Senegal, 1992-2019.

Background: Increased rates of evaporation and decreased rainfall could impact water availability and increase the burden of collecting water. This study uses DHS surveys from Senegal to assess associations between precipitation and evaporation on water collection labor.  

Methods: Nine surveys from Senegal between 1992 and 2019 were included. All surveys included GPS coordinates for each cluster of households. Weather data were included from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) from NASA. Each household cluster was assigned a specific Köppen-Geiger climate classification zone. Data from MERRA-2 were downloaded from the nasapower package, climate zones were assigned using the kgc package, and associations were estimated in R 4.2.3.  

Results: The source population included 53,649 households within 380 clusters (primary sampling units) between 1992 and 2019.  

The average water collection time across all households was 32.2 minutes. The person responsible for collecting water included 7805 adult women (88.6%), 588 adult men (6.7%), 286 female children (3.2%), and 128 male children (1.5%).  

The average walk time was 22.2 minutes in the tropical climate zone and 38.0 minutes in the dry climate zone (p < 0.001). There were weak correlations between walk time and 30-day total precipitation for the tropical climate zone (r = 0.01) and the dry climate zone (r = 0.02). Additionally, there were weak correlations between walk time and 30-day total evaporation for the tropical climate zone (r = -0.03) and the dry climate zone (r = -0.04). 

Discussion: This study shows that climate zone, but not precipitation and evaporation in the prior 30 days, are associated with the amount of time needed to collect water in Senegal. Additionally, men and male children walk further to collect water; however, women and female children are more likely to collect water. 

Russian and U.S. News Media Coverage of Ukrainian Biological Laboratories, February – March 2022

Background: Soon after the Russian invasion of Ukraine, false narratives about U.S.-funded biological weapons laboratories in Ukraine began circulating in both Russian and U.S. news. Such narratives could weaken international health and security by undermining peaceful cooperative biological research activities and eroding trust in the U.S. government and its allies. 

Objective: We sought to characterize Russian and U.S. news media coverage of Ukrainian biological laboratories and to understand potential differences in coverage between different news sources.

Methods: 401 news media items from Russian and U.S. news sources covering Ukrainian biological laboratories between February 24 and March 24, 2022 were analyzed for content and framing tactics based on theories of risk perception, persuasion, and misinformation/disinformation. Pearson’s chi-square test and Fisher’s exact test were used to assess differences in content and framing between different news sources.   

Results: Results showed strong differences between U.S. mainstream news coverage and Russian news coverage and similarities between U.S. hyper-partisan right (HPR) news coverage and Russian news coverage of Ukrainian biological laboratories. Some differences between U.S. HPR and Russian coverage of the topic were also found.

Conclusion: Findings indicate that the U.S. HPR media ecosystem serves as an important amplifier of Russian strategic narratives about U.S. cooperative biological research. Moreover, findings suggest that U.S. HPR news sources have become sophisticated purveyors of false information, capable of applying the Russian “firehose of falsehood” model more forcefully than Russians themselves. 

Indoor Air Pollution in Multigenerational Households and COVID-19 Infection in the Cheyenne River Sioux Tribe, South Dakota

Introduction: The Cheyenne River Sioux Tribe (CRST), as other Indigenous communities in the US, have been disproportionately impacted by chronic environmental exposures. In addition to this, the CRST has high tobacco use compared to other demographic groups and a reliance on propane gas for heating/cooking fuel. Of concern is exposure to environmental tobacco smoke (ETS) and NO2 from propane in indoor environments and their potential impact on risk of infection from COVID-19. The purpose of our study was to assess indoor air pollution and COVID-19 infection in multi-generation households within the CRST, an environmental justice community of concern.  

Methods: The CRST COVID-19–Wayakta He study (“Are you on guard against COVID-19?”) recruited multigenerational households with 2 adults at least 9 years apart. All participants provided responses to a questionnaire on COVID-19 infection, risk factors, housing conditions, and environmental health factors. Participants deployed passive ETS and a sub-group of 100 households deployed NO2 air monitors for one week. ETS was measured using GC-MS, NO2 measured using colorimetric assay. Poisson regression was used to assess the relationship between indoor air and COVID-19 cases per household. 

Results: In this community-based study, 281 households (562 participants) were recruited. The median ETS concentration was 0.017 µg/m3 (range: 0.017-12.7). Of the 39.7% samples with results above LOD (0.034), 14.8% of households had exposures qualified as high. The median NO2 concentration was 9.87 µg/m3 (range: 0.65-138) and 25.9% of households had levels above the WHO Indoor Air Standard of 25 µg/m3. Sixty eight percent of participants have been infected with COVID-19 at least once based on self-report. We found that ETS, but not NO2, was significantly positively associated with the number of COVID-19 cases per household. 

Discussion: ETS and NO2 exposure are known to be associated with more severe upper respiratory infections. The combination of health disparities and systemic racism causes Indigenous communities to be at higher risk of COVID-19 infection. High exposures to household ETS, NO2, and COVID-19 in the CRST highlight the importance of exposure assessment to design targeted interventions in Tribal communities. 

Pediatric Psychosocial Problems and Exposure to Consumer Product Chemicals among Children in an Urban Environment

Background: Phenols and parabens commonly found in consumer products may interfere with biological pathways involved in behavioral development. While some epidemiologic studies suggest that prenatal exposure to some of these chemicals impacts behavior, studies on postnatal exposures are scarce.  

Objective: We examined associations between exposure to phenols and parabens and behavior among 110 Baltimore City children (8-17 years) with asthma in an indoor air pollution study.  

Methods: We measured urinary concentrations of 12 consumer product chemicals (2,4-dichlorophenol, 24DCP; 2,5-dichlorophenol, 25DCP; bisphenol A, BPA; bisphenol S, BPS; bisphenol F, BPF; methylparaben, MPB; ethylparaben, EPB; butylparaben, BPB; propylparaben, PBP; benzophenone-3, BP3; triclocarban, TCC; and triclosan, TCS). Internalizing, externalizing, and total behavioral problems were reported by the primary caregiver using the child behavioral checklist (CBCL/6-18). We conducted covariate-adjusted linear and logistic regression to examine associations between urinary biomarker concentrations and behavioral problems (continuous scores and normal vs. borderline/clinical range). 

Results: Participants were an average age of 11 years (± 2), African American (86%), male (57%), and receiving public health insurance (83%). 24DCP, 25DCP, BP3, BPA, BPS, MPB, and PPB were detected in >90% of children. Geometric mean urinary concentrations of BPS, EPB, MPB and PPB were higher than levels observed among in general U.S. children. Approximately 25% of the study sample were categorized as having either borderline or clinical behavioral problems. Exposure to select parabens (MPB, PPB) was associated with better CBCL externalizing t-scores and CBCL scores in the normal range (externalizing and total scores) while exposure to select phenols (BP-3 and BPF) was positively associated with total CBCL scores in the borderline/clinical range. 

Conclusion: While limited by sample size, this is the first study to show adverse associations between child behavior and exposure to BP-3 and BPF among a sample of predominantly Black children. Future analyses will examine individual behavioral syndromes and potential differences by child sex. 

Associations of individual, environmental, and community features with active sinus inflammation in Pennsylvania. 

Background  

Chronic rhinosinusitis (CRS) is a disease of the nasal and sinus mucosa with direct and indirect costs for individuals and society. Climate change-driven variation in weather and land use may contribute to changes in aeroallergen growing seasons. Few studies have explored how these changes influence active sinus inflammation (ASI), an objective finding of CRS.  

Objective  

Evaluate associations of individual, environmental, and community features with ASI using electronic health records from Geisinger in 37-counties of Pennsylvania.  

Methods  

In a nested case-control study we included individuals aged 18 - 80 years from 2008 – 2018. Cases (n = 2382) with ASI were identified using free text from sinus CT scan reports. Controls (n = 11,910) were frequency matched. Land cover, greenness, and weather were assigned in a 1250-meter residential buffer and evaluated in a 3-month latency and 3-month duration window. Logistic regression with robust standard errors was used to estimate associations (odds ratios and 95% confidence intervals) while adjusting for confounding variables and co-occurring conditions.  

Results  

Among 14,289 individuals, the mean (SD) age was 49.5 (15.3) years. The mean (SD) contact time with Geisinger was 5.88 (3.29) years. Increasing urbanization was associated with increased odds (vs. rural) of ASI; suburban - small town (odds ratio, 95% confidence interval: 1.25, 1.12 - 1.38), lower density urban (1.33, 1.17 - 1.53), higher density urban (1.47, 1.23 - 1.76). There was a significant trend of larger odds ratios across quartiles of precipitation (p < 0.004), percent agriculture (p < 0.004), and percent forested (p = 0.01). No trend was found for greenness, vapor pressure deficit, or cumulative growing degree day. 

Conclusions 

Increasing urbanization, lower precipitation, and lower percent agriculture and percent forested were associated with increased odds of ASI.  

Characterization of metals in communities at the fenceline of an industrial corridor in Louisiana using size-resolved filter measurements and mobile monitoring 

Amira Yassine, Mina Tehrani, Shivang Agarwal, Edward Fortner, Ellis Robinson, Benjamin Werden, Megan Claflin, Andrea Chiger, Carolyn Gigot, Sara Lupolt, Thomas Burke, Keeve Nachman, Kirsten Koehler, Ana Rule, Peter DeCarlo. 

Background: Exposure to metals in aerosol particles emitted from industrial activities can pose serious adverse effects to humans. The St. James, St. John the Baptist, and Ascension Parishes areas in Louisiana are located 40 miles south of Baton Rouge and are one of the most densely populated industrial corridors in the US. These areas have faced increasing scrutiny due to environmental justice concerns. Reported fenceline communities’ exposures in these areas are based on EPA models which feature the facilities' self-reported release data.  

Methods: During a 4-week sampling campaign in February 2023, metal concentrations in particulate matter were determined in St. James, St. John the Baptist, and Ascension Parishes areas in Louisiana. Two complementary approaches for the determination of 19 metals were used: (1) online measurements of total PM2.5 metal concentrations around these areas using a real-time Cooper x-ray fluorescence (XRF) instrument, and (2) stationary size-resolved measurements of metals in PM using a micro-orifice uniform deposit impactor (MOUDI) followed by offline filter analysis by inductively coupled plasma mass spectrometry (ICP-MS). 

Results: ICP-MS measurements of size resolved toxic trace elements showed that arsenic, lead, antimony, and vanadium were at the highest concentrations in fine PM, with mean concentrations of 0.18, 0.51, 0.26, and 0.44 ng/m3 respectively. Furthermore, the comparison of total concentration of trace elements between the XRF measurements and the MOUDI-ICP-MS measurements suggested strong agreement between the two approaches for vanadium, arsenic, and lead: linear regression slopes were 0.8, 1.3, 0.7, and spearman R values were 0.88, 0.72, 0.41 for vanadium, arsenic, and lead respectively. 

Conclusion: These results suggest that stationary metals measurements may be used to aid in the interpretation of mobile fenceline measurements in communities disproportionately affected by environmental health hazards.  

Subject Matter Expert Consensus of Future Capabilities of Biological Design Tools – A Delphi Study 

Artificial intelligence tools seek to provide benefit to biological engineers by reducing the time and cost required to engineer biological systems. Biological design tools are artificial intelligence tools that are trained on biological data. There is concern that the same benefits of these tools will have a significant, negative impact on the deliberate biological threat landscape. Ongoing discussions in the biosecurity, national security, and associated policy communities endeavor to identify potential options to mitigate risks arising from the development of biological design tools. However, to develop forward-looking and effective governance that adequately balances the costs and benefits, a better understanding of the predicted future capabilities of artificial intelligence-based biological design tools is needed. We propose to conduct a modified Delphi study to reach subject matter expert consensus on the predicted future capabilities of biological design tools. A Delphi study is a way to solicit expert opinion while avoiding “group think”. This study will enroll roughly 30 subject matter experts with technical backgrounds in developing biological design tools or applying biological design tools to engineering biology. The study will focus on achieving consensus the future capabilities of biological design tools in seven areas related to dual-use biological engineering applications. If consensus is not reached, round-to-round stability will serve as a sufficient end point and results will be analyzed by subgroup of experts. Results and conclusions are expected to be available late 2024. 

Precision Cut Lung Slices (PCLS) to model cigarette smoke induced lung damage and COPD 

Background: Chronic obstructive pulmonary disease (COPD) accounts for up to 50% of prevalent cases of chronic respiratory disease and there are no pharmaceutical interventions that reverse disease progression. In patients, COPD is characterized by irreversible airflow obstruction due to airways inflammation (chronic bronchitis) and alveolar destruction (emphysema). Mouse models of COPD reproduce similar phenotypes, but are time consuming, and require large numbers of animals. Additionally, current in vitro models are limited in cellular diversity and 3D structure reducing their translatability. We have developed a cigarette smoke induced model of COPD using three-dimensional precision-cut lung slices (PCLS) from mouse lungs to address these concerns. Using increasing doses of cigarette smoke, we can investigate how and why airway remodeling and alveolar destruction occurs in COPD. 

Methods: PCLS from wildtype C57BL/6J mice were generated and exposed to air and cigarette smoke using an adaptation of our in vitro cigarette smoke protocol. PCLS were exposed to 2, 6, or 10 cigarettes over the course 5 days. Results from the exposed PCLS were then compared to banked samples from wildtype C57BL/6J mice that were exposed in vivo for 6 months to air and cigarette smoke. 

Results: Repeated cigarette smoke exposure resulted in alveolar remodeling in both ex vivo (PCLS) and in vivo models. In both models, cigarette smoke increased mean linear intercept (MLI) scores, indicating emphysema-like alveolar destruction. Alveolar destruction in both models was also accompanied by increased apoptosis and altered cytoskeletal structure highlighting mechanistic similarities between the two models. 

Conclusions: Our results highlight the utility of cigarette smoke exposed lung slices as a platform to model cigarette smoke induced lung injury and COPD pathogenesis with increased throughput and a shorter time frame than traditional in vivo smoke exposure models. 

Fungal biodegradation of biosolid-associated organic compounds  

Background. Biosolids are a waste byproduct of wastewater treatment facilities and have been utilized for decades as land filler and agriculture fertilizer. However, during the treatment process, many organic contaminants sorb onto the surfaces of biosolids and become recalcitrant to degradation. Little is known regarding the fate of these biosolid-associated organic compound (BOCs) when they are spread on the environment.  

Objective. The main objective of this project is to determine if white-rot fungi can facilitate the biodegradation of BOCs en situ.  

Methods. Pleurotus ostreatus fungi was exposed to a biosolid slurry and sacrificially tested in triplicate over a five-day experiment. At each timepoint the mycelia, biosolids, and liquid were separated and extracted using QuECHERS (biosolids and liquid) or SLE (mycelia). Extracted samples were analyzed with LC-HRMS and the data were collected for nontarget analysis to look for degradation and transformation products.  

Results. The fungi P. ostreatus was able to grow with only the biosolids as its carbon and nitrogen sources. Data analysis from LC-HRMS is still ongoing; however, over 50 BOCs have been found to be degrading over time when exposed to the white-rot fungi. We have also identified potential transformation products from the fungal metabolism of BOCs.  

Conclusion. P. ostreatus fungi does biodegrade some BOCs during a five-day exposure period. The fungal ability to use carbon and nitrogen from biosolids indicates it could be a feasible large-scale remediation strategy to degrade some BOCs prior to use in the environment.  

Inter-Annual Variability in Atmospheric Transport Complicates Estimation of US Methane Emissions Trends

Background: 

US natural gas production increased from 18 to 27.1 trillion cubic feet per year between 2005 and 2015 as a result of the shale gas boom and the associated technological breakthrough of combining horizontal drilling and hydraulic fracturing. This increase in natural gas activity has caused concern about methane emissions, since methane is the primary constituent of natural gas and an important greenhouse gas. However, existing studies of US methane emissions trends have reached conflicting conclusions. Furthermore, atmospheric methane levels at many US observation locations have increased faster than the global mean, raising questions about whether increasing US natural gas production has led to increased emissions.

Objective: 

In this study, we explore the roles of changing emissions versus meteorology in explaining recent increases in atmospheric methane enhancements across the US and we evaluate the likely contributions of atmospheric transport to an upward trend in atmospheric methane enhancements (AME) during 2007–2015.  

Methods: 

We model AME between years 2007 and 2015 at 8 tower measurement sites in the continental US using a atmospheric transport model (WRF-STILT) with designed 2 transport scenarios and 2 emissions scenarios to better assess the impact of interannual variability (IAV) and changing emissions on AME. 

Results: 

We find that IAV in transport yields an apparent upward trend in enhancements across the US during this time and can explain disagreements among existing studies over emissions trends. We further find that enhancements at satellite and in situ monitoring sites are 19% higher during El Niño than La Niña, possibly because air masses spend more time over North America on average during some years.

Conclusion: 

The results show that accurate modeling of IAV in transport is a key prerequisite to quantifying emissions trends. Overall, the results lend support for the conclusion that there was little upward trend in US methane emissions during this time. 

Geostatistical inverse modeling of methyl bromide and sulfuryl fluoride emissions in the U.S.

The Montreal Protocol on Substances that Deplete the Ozone Layer initiated a global phase-out of the production and consumption of methyl bromide (CH3Br) in order to protect the stratospheric ozone layer. CH3Br is an ozone-depleting substance (ODS) that has been largely phased out of use as a fumigant in favor of the non-ODS, but potent greenhouse gas, sulfuryl fluoride (SO2F2). We seek to understand how emissions of these two fumigants in the U.S. have changed since the 2005 phase-out of CH3Br using long-term atmospheric measurements of CH3Br and SO2F2 from trace gas monitoring sites run by the National Oceanic and Atmospheric Administration (NOAA) Global Monitoring Laboratory (GML). We analyze these atmospheric measurements using a geostatistical inverse model (GIM) to estimate the magnitude, spatial distribution, and seasonality of CH3Br and SO2F2 emissions in the U.S. The GIM requires an atmospheric transport model to link atmospheric measurements to emissions, and we use the Stochastic Time Inverted Lagrangian Transport (STILT) model to simulate back-trajectories and footprints corresponding to each atmospheric measurement. To model the spatial pattern of emissions, we utilize CH3Br and SO2F2 usage data from the California Department of Pesticide Regulation (CDPR) and land cover classification data from the U.S. Geological Survey’s (USGS) National Land Cover Database (NLCD) to define the deterministic component of the GIM, and we use a stochastic variable to describe deviations from the deterministic component in the estimated emissions. We find that although anthropogenic emissions of CH3Br have generally decreased since 2005, they have not quite declined to zero, and exhibit significant interannual variability, despite the heavy restrictions on its use. On the other hand, we find that emissions of SO2F2 have remained relatively constant since 2015, with California alone emitting 60-85% of U.S. emissions and up to 12% of global SO2F2 emissions.  

Development of a Novel Analytical Platform for Detection & Identification of Organic Electrophiles in Environmental Matrices 

Background:  Water disinfection processes, including chlorination, have prevented countless cases of waterborne illnesses. An unintended consequence of these disinfectants, however, have resulted in the formation of toxic disinfection byproducts (DBPs). A certain class of DBPs known as “organic electrophiles” exhibit a wide range of toxicity due to their interactions with biological nucleophiles, e.g., DNA base pairs and proteins. Despite their toxicity, organic electrophile DBPs are poorly characterized due to their incompatibility with traditional extraction and detection methods.  

Objective/aim: A novel reactivity-directed analysis approach was developed to simultaneously capture, detect, and identify organic electrophiles formed during water disinfection processes.

Methods:  Nucleophile probes, including biologically relevant thiols and amines, were synthesized onto photocleavable microbeads. The effectiveness of these nucleophile microbeads to enable electrophile capture and detection was evaluated by spiking in standards of organic electrophiles with varying reactivities. The resulting nucleophile-electrophile adducts were subsequently cleaved from the microbeads to analyze via liquid-chromatography-high-resolution mass spectrometry.  

Results:  Thiol microbeads enabled detection of all twelve halogenated organic electrophiles tested in the spiked standard mixture, thus highlighting the suitability of this derivatization method for detecting organic electrophiles formed during chlorination disinfection. No halogenated electrophile adducts were detected using the amine microbeads, thus classifying them as a poor derivatization reagent for electrophiles of this reactivity class. Separately, an organic electrophile mixture containing carbonyls—compounds commonly formed during ozonation— was tested against the amine microbeads. The addition of a reducing agent in solution, or the introduction of an oxygen atom adjacent to the amine nucleophile probe (i.e., an aminooxy group) offered superior stability of the carbonyl-nucleophile bond and offered more sensitive detection of electrophiles of this reactivity class.

Conclusion:  The effective detection of organic electrophiles achieved by the developed microbead assay shows promise in upcoming applications regarding the detection of electrophiles in more complex environmental matrices.  

Decarbonization Strategy for Aging Coal Power Fleets and Associated Repurposing Opportunities in China

There are five options to decarbonize the energy sector regarding coal power assets: demolishing completely, mothballing for backup generation, retrofitting with carbon capture and storage devices, repurposing with renewable energy for cleaner generation, and repurposing into other economic activity use. Each decarbonization option has different levels of costs and benefits in economics and environment. In addition, coal retirement may come along with the loss of economic gains and loss of coal employment in the existing coal power town. This study aims to co-optimize goals in reducing GHG emissions and achieving societal benefits in terms of the role of coal power in energy sector.  It identifies the optimal decarbonization strategy for existing coal assets at both plant-by-plant level and power system level using an agent-based model, which simulates the interaction between coal agent and power system environment. The coal agent is likely to maximize its utility among five decarbonization strategies by comparing multiple attributes in cost, profit, and environmental impacts. As individual plant decisions can affect the system operation through system pricing, reserves, and frequency, a long-term capacity expansion model, serving as the environment, will consider the impacts from agent’s decisions and will aim for system cost minimization in investment and operation. Thus, such an analysis framework can incorporate the societal impacts from decarbonization strategies of coal power with long-term power system expansion, which can potentially provide valuable implications for our policy makers. The research scope is currently focused on China region, where coal power is a dominant energy type in the electricity generation system.  

Combining Capillary Electrophoresis and Iron Colorimetry: A New Analytical Approach Applied to the Monitoring and Management of Growth Media for Mammalian Cells

Background:  Mammalian cell growth media supports essential processes in modern biomanufacturing. The trend in biomanufacturing is towards chemically defined media (CDM, i.e., medium free of added proteins or other cell-derived ingredients that pose risks of bacterial or viral contamination). Components often found in other biofluids supporting certain essential biological processes are lacking in CDM. Without proteins dedicated to Fe transfer and storage (e.g., transferrin and ferritin), Fe is free to interact with all the other components in CDM, thus it needs more attention and better management. Currently available analytical methods can’t discern Fe^II from Fe^III well enough in CDM.

Objective/aim:  Development of an analytical method to determine Fe^II and Fe^III concentrations in CDM aliquots.  

Methods:  Following the evaluation pathway of traditional colorimetric methods (e.g., ferrozine method), we propose to add a pair of Fe selective chelating agents (BPDC and HBED) simultaneously to CDM aliquots so that Fe oxidation state can be stabilized. All the FeII species should be converted to Fe^II-BPDC complex and all the FeIII species should be converted to Fe^III-HBED complex at equilibrium. A separation technique, capillary electrophoresis (CE), will be employed to assist the quantification of Fe^II-BPDC and Fe^III-HBED complexes, so that interference from constitute CDM components can be minimized.  

Results:  Details of the proposed method regarding dilution rate and pH adjustment of CDM aliquot as pretreatment, concentrations of BPDC and HBED to add, and CE method quantification of Fe^II-BPDC and Fe^III-HBED complexes have been decided based on results from preliminary results. Our method reported correct concentration of FeII and approximately 20% lower concentration of FeIII when it’s applied to CDM samples with known amount of Fe^II and Fe^III prepared in our laboratory.

Conclusion:  Our method can report accurate concentrations of Fe^II in CDM aliquots. It needs further optimization to report accurate concentrations of Fe^III. 

DupuitLEM and the Search for Fundamental Insights into the Coevolution of Landscape Hydrology and Geomorphology

Authors: David G. Litwin (1), Gregory E. Tucker (2,3), Katherine R. Barnhart (4), Ciaran J. Harman (1,5) 1. Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA 2. Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado, Boulder, CO, USA 3. Department of Geological Sciences, University of Colorado, Boulder, CO, USA 4. U.S. Geological Survey, Geologic Hazards Science Center, Golden, CO, USA 5. Department of Earth and Planetary Science, Johns Hopkins University, Baltimore, MD, USA

Most long-term landscape evolution models still operate under the assumption that discharge scales with upslope accumulated area. While this can be appropriate for answering certain kinds of questions, it overlooks a wealth of hydrological knowledge and prevents us from asking hydrological questions of landscape evolution models. For instance, how do subsurface properties and climate impact drainage density? Where and why do variable source areas develop? The hydrological model needed to answer these questions must be sophisticated enough to capture evapotranspiration, subsurface lateral flow, and the development of saturated areas, while being efficient enough to evolve the landscape over thousand-to-million-year timescales. However, this does not necessarily mean a new model should be built from scratch, which would be time consuming and duplicate many existing high-quality tools. To answer these questions, we took a community modeling approach, building a groundwater component for Landlab, and integrating other process components to develop a coupled modelling platform called DupuitLEM. While model process components like those in Landlab can be simply coupled in a script, this is often just the beginning of what is needed to manage the full workflow of model testing, handling parameter sets, sequencing component execution, managing outputs, and post processing. Here we will present highlights of the research that has been accomplished with this model, along with thoughts on model development that may be useful to others interested in using community software to jumpstart investigations of processes across broad ranges of timescales.  

Martial Atmospheric Pressure Fluctuations Can Vent Underground from Habitable Depths

Background: The existence of methane on Mars is a topic of significant interest because of its potential association with subsurface microbial life. Measurements of methane in the atmosphere of Mars indicate that its abundance fluctuates over time. Although the source of methane is unknown, it most likely comes from below the surface of Mars. If methane is currently being produced by living microbes, it would have to be at depths of at least 200 m in order to support life. This begs the question of how to produce short-term atmospheric methane variations if the source is relatively deep underground.

Objective/aim: I am to demonstrate that atmospheric pressure fluctuations (i.e., “barometric pumping”) on Mars are capable of delivering methane to the surface from habitable depths rapidly, and could be a way to explain the observed short-term atmospheric concentration variations.

Methods: I performed numerical flow and transport simulations in fractured rock using Mars atmospheric pressures as surface forcing.  

Results: My flow and transport simulations in fractured rock demonstrate that barometric pumping is capable of producing significant surface fluxes of underground methane. The simulations confirm the clear connection between atmospheric pressures and surface methane flux hypothesized in previous works. Driven by atmospheric pressure fluctuations acquired by the Curiosity barometric record, the overall simulated surface seepage pattern at Gale crater is highly seasonal. It is noteworthy that the seasonality of fluxes generated in our model is reasonably consistent with that of atmospheric methane abundance variations found in previous research.  

Conclusion: Because barometric-pressure pumping is able to vent subsurface methane from potentially habitable depths, this work reinvigorates the hypothesis that methane on Mars could be generated by microbial life. 

Edible crop plant metabolism of wastewater-derived psychoactive pharmaceuticals

The use of reclaimed wastewater for agricultural irrigation exposes fields to hundreds of anthropogenic organic pollutants. Crop plants can uptake many of these pollutants and subsequently metabolize them, resulting in human exposures to both the parent compounds and their transformation products when the plants are consumed. Most plant-derived transformation products of xenobiotics remain unknown, and this results in incomplete risk assessments for these contaminants. Additionally, interspecies metabolic differences make extrapolation of contaminant fate among crop types unreliable. These differences in the production of transformation products were explored by exposing lettuce, tomatoes and carrots to four psychoactive pharmaceuticals found in wastewater that are known to be taken up by and accumulated in crop plants: carbamazepine, lamotrigine, amitriptyline and fluoxetine. Crops were grown in semi-hydroponic conditions and exposed to the selected chemicals individually at an initial concentration of 500 µg/L for 4-6 weeks. The leaves and edible tissues of each plant were collected separately, lyophilized, powdered and extracted with methanol and water before analysis via LC-HRMS. Initial non-target analysis indicated the presence of the major transformation products of carbamazepine, amitriptyline and fluoxetine: carbamazepine-10,11-epoxide, 10-hydroxyamitriptyline and norfluoxetine. Additionally, the data showed that the leaves of tomato and carrot plants had higher dry-weight concentrations of the pharmaceuticals than their edible portions. 

Attribution of the Greenland Ice Sheet's Subseasonal Surface Elevation Change

Background:  

This study evaluates the potential for monitoring subseasonal-to-seasonal (S2S) (1-90 day) variations in Greenland Ice Sheet (GrIS) basal processes alongside mass change, based on dynamic surface elevation changes (DSEC) derived independently from both altimetry from NASA's Ice, Cloud and land Elevation Satellite-2 (ICESat-2) and vertical strain rates from ice velocity dataset ITS_LIVE.

Methods: 

The research aims to develop high resolution datasets of subseasonal DSEC over marginal regions across the GrIS, and attribute them to underlying ice dynamic and basal processes. Estimation of DSEC at subseasonal time scales from ICESat-2 (DSEC-IS2) is facilitated by using data from track crossovers, which reduce the time interval between successive measurements to well below the 91-day repeat interval of ICESat-2 tracks. A robust methodology was implemented for estimating horizontal strain rates and associated uncertainties around crossover locations, leading to estimates of DSEC due to vertical strain (DSEC-VS).

Results: 

Together, the datasets we are developing provide additional insights into subseasonal/seasonal dynamics to supplement GRACE/GRACE-FO gravimetry. We implemented automated workflows for estimating DSEC-IS2 and DSEC-VS for any crossover point and associated time interval. We present illustrative results from Petermann glacier across both winter and summer seasons showcasing examples of basal signals across multiple locations.

Conclusion:   

Results reveal S2S patterns and potential basal signals. The study acknowledges differing uncertainties during both winter and summer seasons and explores the potential for future work in other regions of the GrIS. 

sigROCKET: A scalable long time series classification algorithm using signature and ROCKET 

Hydrologic systems are renowned for their intricate non-linear and long-latency behaviors, posing significant challenges in data assimilation and model construction. Hydrologic time series data encounters several specific hurdles, including 1) noise and upscaling as a subsample of the true non-linear dynamic system, 2) diverse processes measured across different temporal scales, and 3) the complexities of handling long multivariate time series that strain model computational capacity. Addressing these challenges requires robust time series feature extraction techniques that preserve essential information, allowing for effective discrimination among time series generated by distinct dynamic systems. 

In this research, we present a novel scalable algorithm tailored explicitly for long multivariate time series data. Our approach capitalizes on the power of non-linear signature transformation, skillfully combined with the ROCKET framework. Through rigorous benchmarking on diverse datasets, our proposed method achieves state-of-the-art classification Area Under the Curve (AUC) performance. 

This research introduces an innovative framework for efficiently classifying long non-linear multivariate time series data, with wide-ranging applicability across various hydrologic system applications. By empowering researchers and practitioners to address the intricacies of hydrologic processes more effectively, this work enables enhanced predictions and improved water resource management strategies. 

Investigating the Impacts of Building HVAC Systems on Aerosol Composition and Concentration

This work investigates how aerosols change in concentration and composition as they move through heating, ventilating, and air-conditioning (HVAC) systems. Without strong indoor emissions, outdoor-originated aerosols are the main contributor to indoor aerosols. Upon transport to the indoor environment through building HVAC systems, outdoor aerosol concentrations and chemical compositions are modified due to filtration and air conditioning (heating or cooling), especially when the indoor-outdoor temperature gradient is significant. Measurements were conducted in a modern HVAC system on the Johns Hopkins University Campus in Baltimore, MD. During the measurement period, the instrumentation sampled air from a valve switching system pulling from four different zones inside of the HVAC system: 1) return air, 2) mixed air where outdoor air is mixed with returned indoor air, 3) post filter and heating coil, and 4) supply - post cooling coil. We used a variety of instruments to measure the concentration and chemical composition of particulate matter and gases and T/RH.  Instrumentation included 1) Soot Particle Aerosol Mass Spectrometer (SP-AMS), 2) scanning mobility particle sizer (SMPS), 3) proton transfer reaction – mass spectrometry (PTR-MS), 4) Three PICARRO gas concentration analyzers measuring CH4, CO, CH2O, CO2, NH3, and 5) Quant-AQ MODULAIR-PM. Results from this study demonstrate that the primary source of PM in the building originates outdoors. Positive Matrix Factorization on the organic component of the aerosol indicated 4 different sources.  The identified factors changed in relative concentration as they passed through the HVAC system. The results also suggest that the filtration efficiency of the MERV filters in the HVAC varied for different species, and the installed filters did not achieve the expected filtration levels. 

Analyzing Long-Term Electricity and Natural Gas Investments at the City-Level: A Case Study on New York City  

Background: Much of NYC’s energy infrastructure requires either replacement as equipment reaches the end of service life or expansion due to network constraints. Although designed for 25-50 years, NYC’s natural gas (NG) pipelines are on average 65 years old leading to increased fugitive emissions, or unintended methane leakage [1]–[3].  As a result, local distribution companies are required to replace leak-prone distribution mains, approximately half of the existing mains [3]–[6]. At the same time, NYC’s electricity distribution network faces shrinking distribution headroom, the difference between peak demand and line capacity, due to demand growth [7]. The interdependency of electricity and NG networks necessitates that investment decisions are made simultaneously to reduce barriers to future technologies and to decrease the risk of stranded assets. 

Objective: How should New York City (NYC) invest in power system & NG infrastructure from 2020 to 2055 given the price and availability of new technologies and NG substitutes? 

Methods: The City-based Optimization Model for Energy Technologies-X (COMET-X), an extension of COMET, models city-level electricity and NG system planning from 2010 to 2055 in 5-year increments [10]. COMET-X adds new commercial and residential demand (e.g., cooking), technologies (e.g., heat pumps), fuels (e.g., hydrogen) and physical attributes (e.g., pipeline leakage rates). COMET-X determines the minimum-cost operation and construction of energy generation technologies, electricity and NG transmission and distribution, and end-use demand devices. COMET-X then was applied to NYC represented as the five boroughs, New York State, and the greater-U.S. 

Results & Conclusions: The limitations on the rate of NG distribution main replacement and growing replacement costs result in the abandonment of over half of replacement-eligible mains. Although model results indicate NG substitutes are not economical without policy intervention, inclusion of system-wide costs reduces NG consumption in both commercial and residential sectors. However, in 2055, both NG and electric devices serve end-use demands, indicating that without electrification standards or municipal ordinances, cost-optimal investments include diverse fuel options. 

Linking Energy Sector and Air Quality Models Through Downscaling: Long Run EGU Siting and Dispatch to Account for Spatial and Temporal Variability

Modeling the air pollution implications of long-term energy transitions requires a downscaling process as an intermediate step between national-scale energy models and fine-scaled air quality models. Traditional “Grow-in-Place” (GIP) downscaling methods assume that future patterns of generator siting and operation will be similar to those in the past. However, rapid technological change and shifting policy might yield very different future spatiotemporal patterns of power emissions. Here, we propose a “Site-and-Grow” (SAG) and “Temporal Dispatch Model (TDM)” downscaling framework to couple the Electricity Market Module (EMM) of the National Energy Modeling System (NEMS) with the Community Multi-scale Air Quality (CMAQ) model to simulate future changes in emissions from power sector. The SAG focus on spatial disaggregation which consists of two steps - a modified generation expansion model to downscale regional energy information and GIS-based screening and siting to specify the final county-level placement. The TDM targets on temporal allocation, which is power system dispatch model taking the SAG projected generation mix and a multi-variable linear regression model to projected future hourly load demand and renewable profiles as inputs. It operates projected future power system and outputs power emissions reflecting impacts of simulated meteorological conditions. The method is implemented in one EMM region (Carolinas and Virginia) as a case study. We compare GIP and SAG-TDM methods downscaled among four NEMS scenarios (base case, high natural gas consumption, high penetration of electric vehicles, and marine vessel electrification in ports). The results indicate the bias exists in GIP downscaled emissions in terms of difference in spatial, temporal and projections compared to SAG-TDM downscaled emissions which accounts for more realistic representation of fundamental changes in system, economics, policy and climate.  

Subject Matter Expert Consensus of Future Capabilities of Biological Design Tools – A Delphi Study 

Artificial intelligence tools seek to provide benefit to biological engineers by reducing the time and cost required to engineer biological systems. Biological design tools are artificial intelligence tools that are trained on biological data. There is concern that the same benefits of these tools will have a significant, negative impact on the deliberate biological threat landscape. Ongoing discussions in the biosecurity, national security, and associated policy communities endeavor to identify potential options to mitigate risks arising from the development of biological design tools. However, to develop forward-looking and effective governance that adequately balances the costs and benefits, a better understanding of the predicted future capabilities of artificial intelligence-based biological design tools is needed. We propose to conduct a modified Delphi study to reach subject matter expert consensus on the predicted future capabilities of biological design tools. A Delphi study is a way to solicit expert opinion while avoiding “group think”. This study will enroll roughly 30 subject matter experts with technical backgrounds in developing biological design tools or applying biological design tools to engineering biology. The study will focus on achieving consensus the future capabilities of biological design tools in seven areas related to dual-use biological engineering applications. If consensus is not reached, round-to-round stability will serve as a sufficient end point and results will be analyzed by subgroup of experts. Results and conclusions are expected to be available late 2024. 

Characterization of metals in communities at the fenceline of an industrial corridor in Louisiana using size-resolved filter measurements and mobile monitoring

Background: Exposure to metals in aerosol particles emitted from industrial activities can pose serious adverse effects to humans. The St. James, St. John the Baptist, and Ascension Parishes areas in Louisiana are located 40 miles south of Baton Rouge and are one of the most densely populated industrial corridors in the US. These areas have faced increasing scrutiny due to environmental justice concerns. Reported fenceline communities’ exposures in these areas are based on EPA models which feature the facilities' self-reported release data.  

Methods: During a 4-week sampling campaign in February 2023, metal concentrations in particulate matter were determined in St. James, St. John the Baptist, and Ascension Parishes areas in Louisiana. Two complementary approaches for the determination of 19 metals were used: (1) online measurements of total PM2.5 metal concentrations around these areas using a real-time Cooper x-ray fluorescence (XRF) instrument, and (2) stationary size-resolved measurements of metals in PM using a micro-orifice uniform deposit impactor (MOUDI) followed by offline filter analysis by inductively coupled plasma mass spectrometry (ICP-MS). 

Results: ICP-MS measurements of size resolved toxic trace elements showed that arsenic, lead, antimony, and vanadium were at the highest concentrations in fine PM, with mean concentrations of 0.18, 0.51, 0.26, and 0.44 ng/m3 respectively. Furthermore, the comparison of total concentration of trace elements between the XRF measurements and the MOUDI-ICP-MS measurements suggested strong agreement between the two approaches for vanadium, arsenic, and lead: linear regression slopes were 0.8, 1.3, 0.7, and spearman R values were 0.88, 0.72, 0.41 for vanadium, arsenic, and lead respectively. 

Conclusion: These results suggest that stationary metals measurements may be used to aid in the interpretation of mobile fenceline measurements in communities disproportionately affected by environmental health hazards.  

Modeling the Impacts of Climate Change on Weathering Reactions and Water Quality in Mountain Watersheds

Background: Climate change increasingly influences water resources in mountainous regions through earlier spring snowmelt and runoff, declining snowpack volume and reduced the duration and intensity of snowfall. Several observational studies in the Upper Colorado River Basin document changes in both hydrology and water quality due to climate change. The specific goal of this research is to advance understanding of hillslope scale pyrite weathering and predict the influence of further decreasing water tables on weathering rates, solute export, and water quality, resulting from climate change. 

Methods: Unsaturated-saturated Hydrologic models and multi-component reactive transport models are developed using PFLOTRAN, a massively parallel reactive flow and transport model for describing subsurface processes. 

Results: The modeling results establish quantitative relationships between water table decline and increase in metals and SO42- concentrations. The sensitivity of water quality trends (d[SO42-]) to water table decline (dWT) is shown to be controlled by the subsurface permeability architecture of the hillslope. Different subsurface permeability architectures produce different fractions of shallow subsurface flow. Subsurface permeability architectures with higher fractions of shallow flow result in smaller d[SO42-]/dWT. The magnitude of d[SO42-]/dWT is also influenced by the location of weathering front, which developed over the complex and poorly constrained paleoclimatic history of the region. 

Conclusion: The hillslope scale model is applied to reproduce trends in stream sulfate concentration in a well investigated watershed, Handcart Gulch.  The model is also employed to project the long-term behavior of water quality in mountain watersheds subject to decreasing hydrologic inputs. 

Trends in U.S. ethane emissions and implications for fugitive leaks from the oil and gas industries

Oil and natural gas (O&G) production activities have changed markedly across the U.S. over the past several years. However, the impacts of these changes on fugitive oil and gas emissions are not clear. For example, between 2017 and 2020, natural gas production grew at a rate 2.7 times faster than the previous decade. However, the onset of the COVID-19 pandemic dramatically impacted the world economy, including the O&G sector. The shutdown impact on the U.S. O&G sector is multifold, including disrupted production and processing and possibly delayed maintenance.

In this study, we examine US ethane (C₂H₆ ) emissions from 2015 onward as a lens to understand changes in O&G industry fugitive emissions. Ethane is a non-methane hydrocarbon that is predominantly emitted from O&G operations in the U.S., and ethane can therefore act as an important tracer for fugitive O&G emissions. We specifically use ethane observations from towers and aircraft, collected by the NOAA Global Monitoring Laboratory and partner organizations, for years 2015 through 2020. We further pair these observations with a geostatistical inverse model to quantify whether U.S. O&G ethane emissions have changed and by how much. Overall, we find that U.S. ethane emissions increased between 2015-2020 but that the increase is much less than reported changes in U.S. ethane production. We will also discuss changes during the pandemic and the sensitivity of estimated trends to possible changes in atmospheric chemistry. 

Elucidation of reaction pathways of ring cleavage products from chlorination of ¹³C labeled phenols

Background:  For more than a century, chlorine has been widely applied in water treatment as disinfectant for inactivation of pathogens in drinking water. However, its reactions with organic substances can lead to the formation of a variety of toxic DBPs. Among the known DBP precursors, phenols have been shown to be particularly important due to their widespread occurrence in both natural organic matter and anthropogenic compounds and their high reactivity with chlorine. Despite decades of research on the formation of toxic disinfection by-products (DBPs) in the reaction of free chlorine with phenols, uncertainties remain regarding the identity of ring cleavage products and the reaction pathways involved.

Objective/aim:  To systematically elucidate the reaction pathways leading to the formation of the C_4- and C_2-DBPs during chlorination of phenols.

Methods:  We synthesized a series of stable-isotope-labeled ethyl parabens (EP) containing ¹³C labels at different positions of the molecule and investigated the formation of DBPs via a novel amino acid reactivity assay and liquid chromatography-high resolution mass spectrometry (LC-HRMS), which can directly detect the ¹³C isotopic differences in the DBPs.

Results:  We found that, besides the known C_2-DBPs chloroacetic acids, α, β-unsaturated C_4-dialdehydes and C_4-dicarboxylic acids were formed as previously unidentified ring cleavage products. The formation of C_4- and C_2-DBPs inheriting ¹³C labels from corresponding EPs revealed the existence of four general ring cleavage pathways. Moreover, quantification of the different ¹³C labeled DBPs enabled further assessment of the contribution of different pathways.

Conclusion:  Ring cleavage pathways in the reactions of free chlorine with phenols are more complex than previously reported. These novel DBPs and different pathways should be considered in the reaction of free chlorine with phenols in all contexts.