Mountain watersheds are highly vulnerable to climate change, as rising temperatures and shifting precipitation patterns can alter streamflow sources and subsurface flow pathways. Such changes are often reflected in river geochemistry. This study examines changes in geogenic solutes and their relationship to climate change over the past few decades in the Sheep River, an Eastern Slope River of the Canadian Rockies. We integrated principal component analysis, concentration-discharge (C-Q) relationships, conductivity-based mass balance, mixing diagrams, trend analysis, and convergent cross mapping to characterize hydrogeochemical behavior, quantify groundwater and aquifer contributions, and evaluate hydrogeochemical changes and their potential climatic controls. Groundwater contributes similar to 43-58% of mean annual discharge at Okotoks and similar to 50-67% at Diamond Valley and sustains nearly all streamflow during the low-flow period. River chemistry is dominated by signals from carbonate aquifers (similar to 60-75%), with secondary contributions from siliciclastic aquifers. Over the past five decades, most geogenic solutes have increased significantly, and C-Q relationships indicate a shift toward more chemostatic behavior, despite no significant trend in streamflow. Causality analysis reveals both immediate and lagged effects of climatic variables on river chemistry, highlighting their roles in controlling groundwater recharge, subsurface storage, and consequently water-rock interactions. Together, these findings demonstrate a hydrogeochemical transition toward more persistent groundwater contributions to streamflow, and intensified water-rock interactions under a changing climate. This study underlines climate-driven hydrological changes mediated through groundwater, providing insight for adaptive water management in alpine and subalpine regions.

Mountainous regions play a pivotal role in global freshwater supply. Changes in river flow dynamics in upstream reaches can have significant consequences for water availability and management. This paper examines changes in flow seasonality and hydrological extremes in the upstream reach of the Bow River, located in the eastern slopes of the Canadian Rocky Mountains-a region that substantially contributes to downstream river flow. Using a century-long hydroclimatological dataset (1923-2022), we applied trend analysis, correlation analysis, apportionment entropy, circular statistics and wavelet coherence to explore temporal variations in flow seasonality, the magnitude and timing of high and low flows, and their associations with climate variables. We defined the low-flow period using the change points detected on the rising and falling limbs of the annual hydrograph. Results show a weakening of flow seasonality (at the monthly scale), characterized by increased flow during the overwinter season and decreased flow during the open-water season. Despite these seasonal shifts, no significant trend was detected in mean annual flow at the headwater stations. These seasonal changes coincide with rising temperatures, decreasing snowfall, increasing rainfall during the overwinter season and declining snow water equivalent (SWE), accompanied by earlier melt termination and reduced melt duration at the upper stations. The increase in overwinter flow is also consistent with enhanced groundwater contributions, which sustain the river flow during the season. Hydrological extremes also exhibit non-stationary behaviour: low flows increased consistently across the watershed, while high flows (>= 90th percentile) declined at lower elevations. High flows, particularly at the upper stations, show a stronger association with snow-related metrics (i.e., annual maximum SWE and melt intensity) than with antecedent precipitation inputs. The timing of both high and low flows also shifted earlier in parts of the headwater watershed. Wavelet analysis confirms strong coherence between flow and climate variables, especially at an approximate annual cycle, with temperature showing more consistent and pronounced associations with flow than precipitation and large-scale climate indices. Overall, the findings demonstrate climate-driven hydrological changes in the headwater watershed of the Bow River over the past century, underscoring the need for adaptive water management strategies under future climate scenarios.

Study region: The Sheep River basin on the Canadian Rockies' Eastern Slopes of the Rocky Mountains, whose upper basins are unregulated and undeveloped. Study focus: We investigated streamflow generation, hydroclimatic changes, and flood-generating mechanisms using parsimonious statistical methods and over 50 years of hydroclimate data at multiple spatial (sub-basin and entire basin) and temporal (annual, seasonal, monthly, and daily) scales. New hydrological insights for the region: The upper mountainous basin generated similar to 95 % of open-water streamflow, with similar to 66 % from the upper-south basin, where rain, snowmelt, and the streamflow coefficient were higher. Annual and open-water precipitation declined in the lower basin, but overwinter precipitation slightly increased basin-wide. Overwinter snowpack loss increased in the lower basin, and snowpack loss seasonality weakened. Air temperature increased across all basins. Despite these climatic changes, streamflow remained unchanged, likely due to groundwater's buffering effect. Open-water streamflow was primarily driven by rainfall, with additional rapid and slow snowmelt contributions. Overwinter streamflow was predominantly sustained by groundwater, but early snowmelt also contributed. Finally, extreme floods were triggered by heavy precipitation, although high antecedent basin wetness conditions influenced all floods. These findings highlight (i) the importance of mountainous basins in streamflow generation, (ii) the key role of groundwater on streamflow, and (iii) the need to consider complex and diverse hydrologic processes for water supply and flood management in the Sheep River basin under climate change.

Wastewater-based surveillance (WBS) for SARS-CoV-2 was a key strategy for epidemiological modelling and informing COVID-19 health policy during the pandemic. We assessed the capacity and performance of SARS-CoV-2 WBS in public schools. Of seventeen schools screened for participation, only four had plumbing systems that were amenable to comprehensive monitoring. From December 2020 to March 2021 composite wastewater collected twice-weekly from these four schools was compared with three municipal wastewater treatment plants (WWTPs) for SARS-CoV-2 RNA by RTqPCR and fecal biomarkers. Schools had lower rates of successful sample collection relative to WWTPs (64/79 vs. 66/66, p < 0.001). In a time of low COVID-19 activity, 13/64 of school samples were positive for SARS-CoV-2, versus 66/66 for WWTP (p < 0.0001). SARS-CoV-2 RNA in school wastewater was associated with, and often preceded, clinically confirmed COVID-19 cases among students, but showed no correlation with overall rates of student absenteeism. Levels of both SARS-CoV-2 RNA and fecal biomarkers were markedly lower in school wastewater relative to WWTPs. This work demonstrated that WBS for SARS-CoV-2 in schools can be a leading indicator of clinical disease but is technically challenging. The lower fecal biomarker levels from schools suggests children may avoid defecation at school which may further adversely impact school-based WBS for fecal-shed targets.

Wastewater-based surveillance has become an important tool for research groups and public health agencies investigating and monitoring the COVID-19 pandemic and other public health emergencies including other pathogens and drug abuse. While there is an emerging body of evidence exploring the possibility of predicting COVID-19 infections from wastewater signals, there remain significant challenges for statistical modeling. Longitudinal observations of viral copies in municipal wastewater can be influenced by noisy datasets and missing values with irregular and sparse samplings. We propose an integrative Bayesian framework to predict daily positive cases from weekly wastewater observations with missing values via functional data analysis techniques. In a unified procedure, the proposed analysis models severe acute respiratory syndrome coronavirus-2 RNA wastewater signals as a realization of a smooth process with error and combines the smooth process with COVID-19 cases to evaluate the prediction of positive cases. We demonstrate that the proposed framework can achieve these objectives with high predictive accuracies through simulated and observed real data.

Repetitive, long-term inhalation of radioactive radon gas is one of the leading causes of lung cancer, with exposure differences being a function of geographic location, built environment, personal demographics, activity patterns, and decision-making. Here, we examine radon exposure disparities across the urban-to-rural landscape, based on 42,051 Canadian residential properties in 2034 distinct communities. People living in rural, lower population density communities experience as much as 31.2% greater average residential radon levels relative to urban equivalents, equating to an additional 26.7 Bq/m3 excess in geometric mean indoor air radon, and an additional 1 mSv/year in excess alpha radiation exposure dose rate to the lungs for occupants. Pairwise and multivariate analyses indicate that community-based radon exposure disparities are, in part, explained by increased prevalence of larger floorplan bungalows in rural areas, but that a majority of the effect is attributed to proximity to, but not water use from, drilled groundwater wells. We propose that unintended radon gas migration in the annulus of drilled groundwater wells provides radon migration pathways from the deeper subsurface into near-surface materials. Our findings highlight a previously under-appreciated determinant of radon-induced lung cancer risk, and support a need for targeted radon testing and reduction in rural communities.

‘Fugitive’ or ‘stray’ gas migration from deeper formations due to well bore integrity failure has prompted concern regarding environmental impacts. Unintended methane (CH4) migration can increase greenhouse gas emissions and affect groundwater quality in the critical zone. Although the CH4 transport in shallow aquifers has been investigated at experimental injection sites, no intensive groundwater studies have been published around an oil and gas well that has been leaking for a significant period of time. In this field study, groundwater samples were collected from sixteen groundwater monitoring wells (1.25 m below ground surface) installed around a suspended oil and gas well with decadal scale gas migration (estimated ~0.2 m3/day). Stray CH4 distribution and preferential pathways in the shallow groundwater zone were evaluated though high-resolution profiling of equivalent concentrations of hydrocarbon gases (C1-C6; >85 % CH4 at the study site) and bulk formation electrical conductivity to 6.0 m below ground surface. The highest dissolved CH4 concentration (0.074 mmol/L or 1.18 mg/L) in groundwater (1.25 m bgs) was observed immediately downgradient (1.25 m) of the oil and gas well head. Similarly, high-resolution profiling data also revealed the occurrence of relatively high CH4 concentrations in shallow groundwater along the groundwater flow direction and below fine-grained layers up to 10 m distance from the well head. Microbial DNA analysis from groundwater showed significant community shifts, with the highest relative abundance and diversity of methanotrophs observed in the vicinity of the oil and gas well. This study supports findings from experimental injection and laboratory studies, which also found that significant CH4 transport i) dominantly occurs in the groundwater flow direction, and ii) laterally as free phase below fine-grained layers. The occurrence of CH4 concentrations below saturation after more than two decades of gas migration suggests limited impacts have occurred in the shallow subsurface investigated.

Total dissolved gas pressure (P-TDG) measurements are useful to measure accurate in situ dissolved gas concentrations in groundwater, but challenged by in-well degassing. Although in-well degassing has been widely observed, its cause(s) are not clear. We investigated the mechanism(s) by which gas-charged groundwater in a recently pumped well becomes degassed. Vertical P-TDG and dissolved gas concentration profiles were monitored in the standing water column (SWC) of a groundwater well screened in a gas-charged aquifer for 7 days before and 15 days after pumping. Prior to pumping, P-TDG values remained relatively constant and below calculated bubbling pressure (P-BUB) at all depths. In contrast, significant increases in P-TDG were observed at all depths after pumping was initiated, as fresh groundwater with elevated in situ P-TDG values was pumped through the well screen. After pumping ceased, P-TDG values decreased to below P-BUB at all depths over the 15-day post-pumping period, indicating well degassing was active over this time frame. Vertical profiles of estimated dissolved gas concentrations before and after pumping provided insight into the mechanism(s) by which in-well degassing occurred in the SWC. During both monitoring periods, downward mixing of dominant atmospheric and/or tracer gases, and upwards mixing of dominant groundwater gases were observed in the SWC. The key mechanisms responsible for in-well degassing were (i) bubble exsolution when P-TDG exceeded P-BUB as gas-charged well water moves upwards in the SWC during recovery (i.e., hydraulic gradient driven convection), (ii) microadvection caused by the upward migration of bubbles under buoyancy, and (iii) long-term, thermally driven vertical convection.

We evaluated sampling design in wastewater-based epidemiology to monitor SARS-CoV-2 RNA signal, with a focus on sampling site selection. Sampling in wastewater collection systems ranged from locations that were highly granular (i.e., individual buildings) to large wastewater treatment plants with city-scale catchments. Potential data uses and major considerations for each sampling method are discussed. Our study demonstrates sampling at varying degrees of granularity to be viable tools for pandemic response, with both sampling location and data applicability varying significantly based on location type sampled. Wastewater treatment plant data allows for population level trending that provides an early warning sign of increased disease burden community wide. Sampling at individual buildings can facilitate a direct public health response through follow-up patient testing and/or providing early warning to allow an employer to respond to an outbreak at a warehouse or work camp. Sampling within the wastewater collection system presents a novel epidemiologic tool that could allow for early warning of neighbourhood outbreaks to inform local pandemic response(s) and enable case-finding.

Nitrate pollution is a major threat to groundwater quality in agricultural areas. Natural attenuation of nitrate in contaminated aquifers is mediated by denitrifying microbial populations in anoxic environments. Vertical distribution of denitrifying microbial communities in aquifers is greatly influenced by groundwater redox conditions, local hydrogeological parameters, and seasonal variability in groundwater flow and recharge. In this study, we investigated groundwater geochemistry and the composition of bacterial and archaeal communities with increasing depth in a shallow nitrate-contaminated aquifer in British Columbia, Canada. High-resolution passive diffusion sampling was conducted to collect groundwater at 10-cm intervals from 4 to 20 m below ground surface (mbgs) in the aquifer. Geochemical analyses of major ions indicated a general shift in the groundwater chemistry below 16 mbgs including decreasing chloride concentrations that suggest two-end member mixing of shallow and deep groundwater with different chemistries. A redoxcline was further observed within a 2 m transition zone at 18-20 mbgs characterized by sharp declines in nitrate concentrations and increases in sulfate and total inorganic carbon. Excursions in δ15N-NO3- and δ18O-NO3- in the same depth interval are consistent with denitrification, and a concomitant decrease in δ34S-SO42- suggested that denitrification was coupled to sulfide or sulfur oxidation. Microbial communities within this depth interval were significantly dissimilar to those above and below, featuring putative lithotrophic denitrifying bacteria belonging to the genera Sulfurifustis, Sulfuritalea and Sulfuricella. These lineages were detected in greatest abundance at 19 mbgs while the abundances of putative heterotrophic sulfate-reducing bacteria belonging to the genus Desulfosporosinus were greatest at 20 mbgs. In addition to help distinguish denitrification from mixing-induced changes in groundwater chemistry, the above observed vertical stratification of the microbial key players connects nitrate removal to the locations of the aquifer sampled.

Abstract Background WW surveillance enables real time monitoring of SARS-CoV-2 burden in defined sewer catchment areas. Here, we assessed the occurrence of total, Delta and Omicron SARS-CoV-2 RNA in sewage from three tertiary-care hospitals in Calgary, Canada. Methods Nucleic acid was extracted from hospital (H) WW using the 4S-silica column method. H-1 and H-2 were assessed via a single autosampler whereas H-3 required three separate monitoring devices (a-c). SARS-CoV-2 RNA was quantified using two RT-qPCR approaches targeting the nucleocapsid gene; N1 and N200 assays, and the R203K/G204R and R203M mutations. Assays were positive if Cq< 40. Cross-correlation function analyses (CCF) was performed to determine the time-lagged relationships between WW signal and clinical cases. SARS-CoV-2 RNA abundance was compared to total hospitalized cases, nosocomial-acquired cases, and outbreaks. Statistical analyses were conducted using R. Results Ninety-six percent (188/196) of WW samples collected between Aug/21-Jan/22 were positive for SARS-CoV-2. Omicron rapidly supplanted Delta by mid-December and this correlated with lack of Delta-associated H-transmissions during a period of frequent outbreaks. The CCF analysis showed a positive autocorrelation between the RNA concentration and total cases, where the most dominant cross correlations occurred between -3 and 0 lags (weeks) (Cross-correlation values: 0.75, 0.579, 0.608, 0.528 and 0.746 for H-1, H-2, H-3a, H-3b and H-3c; respectively). VOC-specific assessments showed this positive association only to hold true for Omicron across all hospitals (cross-correlation occurred at lags -2 and 0, CFF value range between 0.648 -0.984). We observed a significant difference in median copies/ml SARS-CoV-2 N-1 between outbreak-free periods vs outbreaks for H-1 (46 [IQR: 11-150] vs 742 [IQR: 162-1176], P< 0.0001), H-2 (24 [IQR: 6-167] vs 214 [IQR: 57-560], P=0.009) and H-3c (2.32 [IQR: 0-19] vs 129 [IQR: 14-274], P=0.001). Conclusion WW surveillance is a powerful tool for early detection and monitoring of circulating SARS-CoV-2 VOCs. Total SARS-CoV-2 and VOC-specific WW signal correlated with hospitalized prevalent cases of COVID-19 and outbreak occurrence. Disclosures All Authors: No reported disclosures.

Wastewater monitoring of SARS-CoV-2 enables early detection and monitoring of the COVID-19 disease burden in communities and can track specific variants of concern. We determined proportions of the Omicron and Delta variants across 30 municipalities covering >75% of the province of Alberta (population 4.5 million), Canada, during November 2021-January 2022. Larger cities Calgary and Edmonton exhibited more rapid emergence of Omicron than did smaller and more remote municipalities. Notable exceptions were Banff, a small international resort town, and Fort McMurray, a medium-sized northern community that has many workers who fly in and out regularly. The integrated wastewater signal revealed that the Omicron variant represented close to 100% of SARS-CoV-2 burden by late December, before the peak in newly diagnosed clinical cases throughout Alberta in mid-January. These findings demonstrate that wastewater monitoring offers early and reliable population-level results for establishing the extent and spread of SARS-CoV-2 variants.

Importance:The association between hydraulic fracturing and human development is not well understood. Several studies have identified significant associations between unconventional natural gas development and adverse birth outcomes; however, geology and legislation vary between regions.Objective:To examine the overall association between residential proximity to hydraulic fracturing sites and adverse birth outcomes, and investigate whether well density influenced this association.Design, Setting, and Participants:This population-based retrospective cohort study of pregnant individuals in rural Alberta, Canada, took place from 2013 to 2018. Participants included reproductive-aged individuals (18-50 years) who had a pregnancy from January 1, 2013, to December 31, 2018, and lived in rural areas. Individuals were excluded if they lived in an urban setting, were outside of the age range, or were missing data on infant sex, postal code, or area-level socioeconomic status.Exposures:Oil and gas wells that underwent hydraulic fracturing between 2013 to 2018 were identified through the Alberta Energy Regulator (n = 4871). Individuals were considered exposed if their postal delivery point was located within 10 km of 1 or more wells that was hydraulically fractured during 1 year preconception or during pregnancy.Main Outcomes and Measures:Outcomes investigated were spontaneous and indicated preterm birth, small for gestational age, major congenital anomalies, and severe neonatal morbidity or mortality.Results:After exclusions, the sample included 26 193 individuals with 34 873 unique pregnancies, and a mean (SD) parental age of 28.2 (5.2) years. Small for gestational age and major congenital anomalies were significantly higher for individuals who lived within 10 km of at least 1 hydraulically fractured well after adjusting for parental age at delivery, multiple births, fetal sex, obstetric comorbidities, and area-level socioeconomic status. Risk of spontaneous preterm birth and small for gestational age were significantly increased in those with 100 or more wells within 10 km.Conclusions and Relevance:Results suggest that individuals who were exposed to hydraulic fracturing within pregnancy may be at higher risk of several adverse birth outcomes. These results may be relevant to health policy regarding legislation of unconventional oil and gas development in Canada and internationally.

El valle de Ica, ubicado en la zona central y occidental de Perú, es el principal valle con potencial agroexportador por sus altos índices de productividad y calidad, a la vez el acuífero del cual se extrae agua se enfrenta a una extracción intensiva de agua subterránea; dando lugar a un descenso considerable de los niveles piezométricos a causa de la sobreexplotación del acuífero. Hemos planteado un modelo conceptual para establecer la interconexión entre las precipitaciones ocurridas en la cuenca alta y el acuífero Ica, así como los mecanismos de recarga. Adicionalmente se ha establecido una red de monitoreo isotópico y geoquímico en puntos estratégicos desde la cuenca baja, media y alta, para la evaluación de aguas subterráneas, superficiales y de precipitaciones, esto ha permitido entender que el Acuífero Ica es recargado principalmente por agua proveniente de elevaciones medias y altas de la cuenca y es en estos puntos donde se debe hacer la recarga artificial mediante infiltración; ya que existe una interconexión directa a través de fallas geológicas entre el agua proveniente de altas elevaciones y del mismo acuífero.

Abstract Background Universities are interactive communities where frequent contacts between individuals occur, increasing the risk of outbreaks of COVID-19. We embarked upon a real-time wastewater (WW) monitoring program across the University of Calgary (UofC) campus measuring WW SARS-CoV-2 burden relative to levels of disease in the broader surrounding community. Figure 1 The colour scheme shows 6 sewer sub-catchments at the University of Calgary. Autosamplers were deployed at 4 sampling nodes within sub-catchments CR and YA (both residence halls), and UCE and UCS (catchments that include several campus buildings). Figure 2 Log10-transformed abundance (i.e., copies per mL) of nucleocapsid gene (i.e., N1) for SARS-CoV-2 for each sampling location during October 2021 – April 2022. Locations denoted by the same letters (A, B, or C) show no statistical difference (p > 0.05) according to the Wilcoxon rank-sum test. The WWTP sample corresponds to a catchment area covering most of Calgary including the university campus, for which sampling locations CR, UCE, UCS, and UCW are defined in Fig. 1. Methods From October 2021 – April 2022, WW was collected thrice weekly across UofC campus through 4 individual sewer sampling nodes (Fig. 1) using autosamplers (C.E.C. Analytics, CA). Results from these 4 nodes were compared with community monitoring at Calgary’s largest WW treatment plant (WWTP), which received WW from surrounding neighborhoods, and also from UofC. Nucleic acid was extracted from WW for RTqPCR quantification of the N1 nucleocapside gene from SARS-CoV-2 genomic RNA. Qualitative (positive samples defined if cycle threshold < 40) and quantitative statistical analyses were performed using R. Results Levels of SARS-CoV-2 in WW were significantly lower at all campus monitoring sites relative to the WWTP (Wilcoxon rank-sum test p < 0.05; Fig. 2). The proportion of WW samples that were positive for SARS-CoV-2 was significantly higher for WWTP than at least two campus locations (p < 0.05 for Crowsnest Hall and UCE - University way and campus drive) according to Fischer’s exact 2-sided test. The proportion of WW samples with positive WW signals were still higher for WWTP than the other two locations, but statistically not significant (p = 0.216). Among campus locations, the buildings in UCE catchment showed much lower N1 signals than other catchments, likely owing to buildings in this catchment primarily being administration and classroom environments, with lower human-to-human contact and less defecation compared to the other 3 catchments, which include residence hall, a dining area, and/or laboratory spaces. Conclusion Our results show that SARS-CoV-2 RNA shedding in WW at the UofC is significantly lower than the city-wide signal associated with surrounding neighborhoods. Furthermore, we demonstrate that WW testing at well-defined nodes is a sampling strategy for potentially locating specific places where high transmission of infectious disease occurs. Disclosures All Authors: No reported disclosures.

Wastewater monitoring of SARS-CoV-2 allows for early detection and monitoring of COVID-19 burden in communities and can track specific variants of concern. Targeted assays enabled relative proportions of SARS-CoV-2 Omicron and Delta variants to be determined across 30 municipalities covering >75% of the province of Alberta (pop. 4.5M) in Canada, from November 2021 to January 2022. Larger cities like Calgary and Edmonton exhibited a more rapid emergence of Omicron relative to smaller and more remote municipalities. Notable exceptions were Banff, a small international resort town, and Fort McMurray, a more remote northern city with a large fly-in worker population. The integrated wastewater signal revealed that the Omicron variant represented close to 100% of SARS-CoV-2 burden prior to the observed increase in newly diagnosed clinical cases throughout Alberta, which peaked two weeks later. These findings demonstrate that wastewater monitoring offers early and reliable population-level results for establishing the extent and spread of emerging pathogens including SARS-CoV-2 variants.

Monitoring of dissolved methane concentrations in groundwater is required to identify impacts from oil and gas development and to understand temporal variability under background conditions. Currently, long-term (i.e., multiyear) monitoring is performed via periodic groundwater sampling; hence, the data are temporally limited and can suffer from degassing losses in-well and at surface for groundwater with high dissolved gas concentrations. The application of total dissolved gas pressure (PTDG) probes for long-term monitoring of methane-rich groundwater was investigated for >2 years in three monitoring wells in a low-permeability bedrock aquifer above the Utica Shale, Canada. The advantage of these probes is that they allow for continual in situ monitoring. A hydraulic packer was installed in each well, below which PTDG and water pressure were measured every 15 or 30 min. The major dissolved gas species composition, required to calculate methane concentrations from PTDG, was determined from groundwater samples collected approximately bimonthly. Methane was the dominant gas in each well (~80–97%), with relatively consistent composition over time, indicating PTDG provided a reasonable proxy for methane concentrations. All three wells had high PTDG (reaching 53.0 m H2O), with PTDG-derived methane concentrations (34–156 mg/L) much higher (3–12 times) and relatively more stable than determined by conventional groundwater analysis. PTDG monitoring also revealed substantial short-term changes during pumping and between sampling events (up to 4 m H2O), possibly associated with background variability. Limitations and technical remedies are discussed. This study demonstrates that PTDG probes can be a valuable tool for monitoring methane-rich groundwater.

Effective measurement of the presence and rate of methane gas migration (GM) outside the casing of energy wells is important for managing social and environmental impacts and financial liabilities in the upstream petroleum industry. Practitioners typically assess GM by above-background methane gas concentrations in-soil or at-grade; however, factors influencing the potential variation in these measurements are not well represented in industry-recommended best practices. Inexpensive chemoresistive sensors were used to record a 1-minute frequency methane gas concentration time series over 19 days. Time series were recorded at three soil depths (0, 5, and 30 cm) at two locations <30 mcm radially from a petroleum well with known GM, in addition to two “control” locations. Observed concentration variations ranged over several orders of magnitude at all depths, with generally lower concentrations and more variation observed at shallower depths. Varying concentrations were correlated to meteorological factors, primarily including wind speed and shallow groundwater table elevation. The gas concentration patterns were affected by a 3.5-mm rainfall event, suggesting soil moisture changes affected preferential GM pathways. Results indicate potential variability in repeated snapshot GM test results. Although, currently recommended GM detection methods would have effectively identified the presence/absence of GM, they would not have quantified the order of magnitude changes in concentration. GM detection success at this site was increased with measurement at more than one location spatially within 30 cm of the well casing, lower concentration detection limits, and greater measurement depth. These findings indicate that meteorological factors should be considered when conducting GM surveys (particularly for improving at-grade test reliability). The low-cost approach for long-term concentration measurement facilitates insight into variable gas concentrations and may be advantageous in comparison to snapshot measurements in some circumstances.

Abstract Background We sought to compare WW SARS-CoV-2 RNA detection across a range of sites and scales using RTqPCR and RTddPCR. Figure. Methods Composite-24h WW was collected from a WW treatment plant (WTP; n=18), a neighborhood (Nb1; n=12) and three hospitals; H-1, H-2, and H-3 (3-sites; A-C)(n=84). RNA was extracted using the 4S-silica column method. RTqPCR (QuantStudio5, ThermoFisher) and RTddPCR (C1000 Thermal Cycler and QX200 Droplet Reader, BioRad) quantified SARS-CoV-2 RNA nucleocapsid (N2, US CDC) and envelope (E Sarbeco, Corman et al 2020) in triplicate. Fisher’s exact test was used to compare assay sensitivity. Correlations between modalities and RNA - clinically-confirmed COVID-19 cases (defined by postal code of primary residence using 5-day rolling average) was assessed using Persons correlation. Results 114 samples were tested (02/23/2021-04/22/2021). SARS-CoV-2-N2 was identified in 90/114 (79%) by RTqPCR and 89/114 (78%) by ddPCR (p=1). SARS-CoV-2 E was found in 72/114 (63%) by RTqPCR and 90/114 (79%) by ddPCR, p=0.01. Correlations between modalities were strongest for N2 relative to E across all sites (see Table). N2 correlated with clinically diagnosed cases for both modalities greater at the level of the WTP (RTqPCR; r=0.8972, p< 0.0001and ddPCR; 0.933, p< 0.0001) relative to neighborhood (RTqPCR; r=0.6, p=0.04 and ddPCR; 0.60, p=0.04). E correlated to a lesser degree with cases at WTP (RTqPCR; r=0.65, p=0.0035 and ddPCR; 0.88, p=< 0.001) and neighborhoods (RTqPCR; r=0.40, p=0.20 and ddPCR; r=0.43, p=0.16). Conclusion SARS-CoV-2 detection of N2 was similar between RTqPCR and RTddPCR across a range of sites and scales in the sewershed, and this correlated best with clinical cases whereas E detection was superior with ddPCR. Disclosures All Authors: No reported disclosures.