Greenhouse gas emissions from an arid-zone reservoir and their environmental policy significance: Results from existing global models and an exploratory dataset.

Reservoirs in arid regions often provide critical water storage but little is known about their greenhouse gas (GHG) footprint. While there is growing appreciation of the role reservoirs play as GHG sources, there is a lack of understanding of GHG emission dynamics from reservoirs in arid regions and implications for environmental policy. Here we present initial GHG emission measurements from Lake Powell, a large water storage reservoir in the desert southwest United States. We report CO2-eq emissions from the shallow (< 15 m) littoral regions of the reservoir that are higher than the global average areal emissions from reservoirs (9.4 vs. 5.8 g CO2-eq m-2 d-1) whereas fluxes from the main reservoir were two orders of magnitude lower (0.09 g CO2-eq m-2 d-1). We then compared our measurements to modeled CO2 + CH4 emissions from the reservoir using four global scale models. Factoring these emissions into hydropower production at Lake Powell yielded low GHG emissions per MWh-1 as compared to fossil-fuel based energy sources. With the exception of one model, the estimated hydropower emissions for Lake Powell ranged from 10-32 kg CO2-eq MWh-1, compared to ∼400-1000 kg CO2-eq MWh-1 for natural gas, oil, and coal. We also estimate that reduced littoral habitat under low water levels leads to ∼50% reduction in the CO2 equivalent emissions per MWh. The sensitivity of GHG emissions to reservoir water levels suggests that the interaction will be an important policy consideration in the design and operation of arid region systems.

Spatial variability of sediment methane production and methanogen communities within a eutrophic reservoir: Importance of organic matter source and quantity.

Freshwater reservoirs are an important source of the greenhouse gas methane (CH4) to the atmosphere, but global emission estimates are poorly constrained (13.3-52.5 Tg C yr-1), partially due to extreme spatial variability in emission rates within and among reservoirs. Spatial heterogeneity in the availability of organic matter (OM) for biological CH4 production by methanogenic archaea may be an important contributor to this variation. To investigate this, we measured sediment CH4 potential production rates, OM source and quantity, and methanogen community composition at 15 sites within a eutrophic reservoir in Ohio, USA. CH4 production rates were highest in the shallow riverine inlet zone of the reservoir, even when rates were normalized to OM quantity, indicating that OM was more readily utilized by methanogens in the riverine zone than in the transitional or lacustrine zones. Sediment stable isotopes and C:N indicated a greater proportion of terrestrial OM in the particulate sediment of this zone. Methanogens were present at all sites, but the riverine zone contained a higher relative abundance of methanogens capable of acetoclastic and methylotrophic methanogenesis, likely reflecting differences in decomposition processes or OM quality. While we found that methane potential production rates were negatively correlated with autochthonous carbon in particulate sediment OM, rates were positively correlated with indicators of autochthonous carbon in the porewater dissolved OM. It is likely that both dissolved and particulate sediment OM affect CH4 production rates, and that both terrestrial and aquatic OM sources are important in the riverine methane production hot spot.

Retrospective Analysis of Wastewater-Based Epidemiology of SARS-CoV-2 in Residences on a Large College Campus: Relationships between Wastewater Outcomes and COVID-19 Cases across Two Semesters with Different COVID-19 Mitigation Policies.

Wastewater-based epidemiology (WBE) has been utilized for outbreak monitoring and response efforts in university settings during the coronavirus disease 2019 (COVID-19) pandemic. However, few studies examined the impact of university policies on the effectiveness of WBE to identify cases and mitigate transmission. The objective of this study was to retrospectively assess relationships between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) wastewater outcomes and COVID-19 cases in residential buildings of a large university campus across two academic semesters (August 2020-May 2021) under different COVID-19 mitigation policies. Clinical case surveillance data of student residents were obtained from the university COVID-19 response program. We collected and processed building-level wastewater for detection and quantification of SARS-CoV-2 RNA by RT-qPCR. The odds of obtaining a positive wastewater sample increased with COVID-19 clinical cases in the fall semester (OR = 1.50, P value = 0.02), with higher odds in the spring semester (OR = 2.63, P value < 0.0001). We observed linear associations between SARS-CoV-2 wastewater concentrations and COVID-19 clinical cases (parameter estimate = 1.2, P value = 0.006). Our study demonstrated the effectiveness of WBE in the university setting, though it may be limited under different COVID-19 mitigation policies. As a complementary surveillance tool, WBE should be accompanied by robust administrative and clinical testing efforts for the COVID-19 pandemic response.

Ebullition dominates methane fluxes from the water surface across different ecohydrological patches in a temperate freshwater marsh at the end of the growing season.

Measurements of the spatial heterogeneity of methane fluxes in wetlands are critical to better understand and predict methane emissions at the ecosystem scale. However, the within-wetland spatial heterogeneity of fluxes is rarely assessed. Here, we use a spatially balanced rapid chamber-based survey of methane at different ecohydrological patches within a temperate freshwater marsh. We measured fluxes exclusively from the water surface without including vegetation. We further used the data from chamber measurements to partition diffusive and ebullitive fluxes. Three ecohydrological patches were distinguishable in the marsh, defined by the type and presence/absence of vegetation. These patches were emergent vegetation, floating-leaved, and open water. Net methane fluxes from the water surface (diffusion plus ebullition) in emergent vegetation patches were larger than in the floating-leaved vegetation and open water patches (p < 0.05). Diffusive fluxes, representing a sizable smaller fraction of net fluxes, were larger in vegetated than in unvegetated patches (p < 0.05), while ebullitive fluxes mirrored the magnitude and differences observed in the net fluxes. Moreover, pooled net and ebullitive fluxes across patches (but not diffusive fluxes) were negatively correlated with water levels, the primary variable affecting patch distribution. Altogether, our results indicate that the differences among ecohydrological patches are driven by ebullition, ultimately highlighting challenges faced by scientists and practitioners in the field and modelers seeking to improve the predictability and resolution of wetland biogeochemical models.

Temporal trends in methane emissions from a small eutrophic reservoir: the key role of a spring burst.

Waters impounded behind dams (i.e., reservoirs) are important sources of greenhouses gases (GHGs), especially methane (CH4), but emission estimates are not well constrained due to high spatial and temporal variability, limitations in monitoring methods to characterize hot spot and hot moment emissions, and the limited number of studies that investigate diurnal, seasonal, and interannual patterns in emissions. In this study, we investigate the temporal patterns and biophysical drivers of CH4 emissions from Acton Lake, a small eutrophic reservoir, using a combination of methods: eddy covariance monitoring, continuous warm-season ebullition measurements, spatial emission surveys, and measurements of key drivers of CH4 production and emission. We used an artificial neural network to gap fill the eddy covariance time series and to explore the relative importance of biophysical drivers on the interannual timescale. We combined spatial and temporal monitoring information to estimate annual whole-reservoir emissions. Acton Lake had cumulative areal emission rates of 45.6 ± 8.3 and 51.4 ± 4.3 g CH4 m-2 in 2017 and 2018, respectively, or 109 ± 14 and 123 ± 10 Mg CH4 in 2017 and 2018 across the whole 2.4 km2 area of the lake. The main difference between years was a period of elevated emissions lasting less than 2 weeks in the spring of 2018, which contributed 17 % of the annual emissions in the shallow region of the reservoir. The spring burst coincided with a phytoplankton bloom, which was likely driven by favorable precipitation and temperature conditions in 2018 compared to 2017. Combining spatially extensive measurements with temporally continuous monitoring enabled us to quantify aspects of the spatial and temporal variability in CH4 emission. We found that the relationships between CH4 emissions and sediment temperature depended on location within the reservoir, and we observed a clear spatiotemporal offset in maximum CH4 emissions as a function of reservoir depth. These findings suggest a strong spatial pattern in CH4 biogeochemistry within this relatively small (2.4 km2) reservoir. In addressing the need for a better understanding of GHG emissions from reservoirs, there is a trade-off in intensive measurements of one water body vs. short-term and/or spatially limited measurements in many water bodies. The insights from multi-year, continuous, spatially extensive studies like this one can be used to inform both the study design and emission upscaling from spatially or temporally limited results, specifically the importance of trophic status and intra-reservoir variability in assumptions about upscaling CH4 emissions.

Methane and Carbon Dioxide Emissions From Reservoirs: Controls and Upscaling.

Estimating carbon dioxide (CO2) and methane (CH4) emission rates from reservoirs is important for regional and national greenhouse gas inventories. A lack of methodologically consistent data sets for many parts of the world, including agriculturally intensive areas of the United States, poses a major challenge to the development of models for predicting emission rates. In this study, we used a systematic approach to measure CO2 and CH4 diffusive and ebullitive emission rates from 32 reservoirs distributed across an agricultural to forested land use gradient in the United States. We found that all reservoirs were a source of CH4 to the atmosphere, with ebullition being the dominant emission pathway in 75% of the systems. Ebullition was a negligible emission pathway for CO2, and 65% of sampled reservoirs were a net CO2 sink. Boosted regression trees (BRTs), a type of machine learning algorithm, identified reservoir morphology and watershed agricultural land use as important predictors of emission rates. We used the BRT to predict CH4 emission rates for reservoirs in the U.S. state of Ohio and estimate they are the fourth largest anthropogenic CH4 source in the state. Our work demonstrates that CH4 emission rates for reservoirs in our study region can be predicted from information in readily available national geodatabases. Expanded sampling campaigns could generate the data needed to train models for upscaling in other U.S. regions or nationally.

N2O Emissions From Two Agroecosystems: High Spatial Variability and Long Pulses Observed Using Static Chambers and the Flux-Gradient Technique.

With the addition of nitrogen (N), agricultural soils are the main anthropogenic source of N2O, but high spatial and temporal variabilities make N2O emissions difficult to characterize at the field scale. This study used flux-gradient measurements to continuously monitor N2O emissions at two agricultural fields under different management regimes in the inland Pacific Northwest of Washington State, USA. Automated 16-chamber arrays were also deployed at each site; chamber monitoring results aided the interpretation of the flux gradient results. The cumulative emissions over the six-month (1 April-30 September) monitoring period were 2.4 ± 0.7 and 2.1 ± 2 kg N2O-N/ha at the no-till and conventional till sites, respectively. At both sites, maximum N2O emissions occurred following the first rainfall event after N fertilization, and both sites had monthlong emission pulses. The no-till site had a larger N2O emission factor than the Intergovernmental Panel on Climate Change Tier 1 emission factor of 1% of the N input, while the conventional-till site's emission factor was close to 1% of the N input. However, these emission factors are likely conservative. We estimate that the global warming potential of the N2O emissions at these sites is larger than that of the no-till conversion carbon uptake. We recommend the use of chambers to investigate spatiotemporal controls as a complementary method to micrometeorological monitoring, especially in systems with high variability. Continued monitoring coupled with the use of models is necessary to investigate how changing management and environmental conditions will affect N2O emissions.

Inconsistencies undermine the conclusion that agriculture is a dominant source of NO x in California.

Almaraz et al. reported that agricultural soils are a dominant source of NO x pollution in California (20 to 32% of total statewide NO x emissions). However, this conclusion may be undermined by the lack of agreement between their modeled estimates and previously reported empirical measurements, the extrapolation of NO x fluxes during hot moments to derive annual estimates, and the overestimation of nitrogen fertilizer consumption in California.

Effects of an Experimental Water-level Drawdown on Methane Emissions from a Eutrophic Reservoir.

Reservoirs are a globally significant source of methane (CH4) to the atmosphere. However, emission rate estimates may be biased low due to inadequate monitoring during brief periods of elevated emission rates (that is, hot moments). Here we investigate CH4 bubbling (that is, ebullition) during periods of falling water levels in a eutrophic reservoir in the Midwestern USA. We hypothesized that periods of water-level decline trigger the release of CH4-rich bubbles from the sediments and that these emissions constitute a substantial fraction of the annual CH4 flux. We explored this hypothesis by monitoring CH4 ebullition in a eutrophic reservoir over a 7-month period, which included an experimental water-level drawdown. We found that the ebullitive CH4 flux rate was among the highest ever reported for a reservoir (mean = 32.3 mg CH4 m-2 h-1). The already high ebullitive flux rates increased by factors of 1.4-77 across the nine monitoring sites during the 24-h experimental water-level drawdown, but these emissions constituted only 3% of the CH4 flux during the 7-month monitoring period due to the naturally high ebullitive CH4 flux rates that persist throughout the warm weather season. Although drawdown emissions were found to be a minor component of annual CH4 emissions in this reservoir, our findings demonstrate a link between water-level change and CH4 ebullition, suggesting that CH4 emissions may be mitigated through water-level management in some reservoirs.