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At least 451 records · Page 25

Subsurface Redox Interactions Regulate Ebullitive Methane Flux in Heterogeneous Mississippi River Deltaic Wetland

Abstract As interfaces connecting terrestrial and ocean ecosystems, coastal wetlands develop temporally and spatially complex redox conditions, which drive uncertainties in greenhouse gas emission as well as the total carbon budget of the coastal ecosystem. To evaluate the role of complex redox reactions in methane emission from coastal wetlands, a coupled reactive‐transport model was configured to represent subsurface biogeochemical cycles of carbon, nitrogen, and sulfur, along with production and transport of multiple gas species through diffusion and ebullition. This model study was conducted at multiple sites along a salinity gradient in the Barataria Basin at the Mississippi River Deltaic Plain. Over a freshwater to saline gradient, simulated total flux of methane was primarily controlled by its subsurface production and consumption, which were determined by redox reactions directly (e.g., methanogenesis, methanotrophy) and indirectly (e.g., competition with sulfate reduction) under aerobic and/or anaerobic conditions. At fine spatiotemporal scales, surface methane fluxes were also strongly dependent on transport processes, with episodic ebullitive fluxes leading to higher spatial and temporal variability compared to the gradient‐driven diffusion flux. Ebullitive methane fluxes were determined by methane fraction in total ebullitive gas and the frequency of ebullitive events, both of which varied with subsurface methane concentrations and other gas species. Although ebullition thresholds are constrained by local physical factors, this study indicates that redox interactions not only determine gas composition in ebullitive fluxes but can also regulate ebullition frequency through gas production.

03 NATURAL GAS↗

BAWLD-CH 4 : a comprehensive dataset of methane fluxes from boreal and arctic ecosystems

Methane (CH 4 ) emissions from the boreal and arctic region are globally significant and highly sensitive to climate change. There is currently a wide range in estimates of high-latitude annual CH 4 fluxes, where estimates based on land cover inventories and empirical CH 4 flux data or process models (bottom-up approaches) generally are greater than atmospheric inversions (top-down approaches). A limitation of bottom-up approaches has been the lack of harmonization between inventories of site-level CH 4 flux data and the land cover classes present in high-latitude spatial datasets. Here we present a comprehensive dataset of small-scale, surface CH 4 flux data from 540 terrestrial sites (wetland and non-wetland) and 1247 aquatic sites (lakes and ponds), compiled from 189 studies. The Boreal–Arctic Wetland and Lake Methane Dataset (BAWLD-CH 4 ) was constructed in parallel with a compatible land cover dataset, sharing the same land cover classes to enable refined bottom-up assessments. BAWLD-CH 4 includes information on site-level CH 4 fluxes but also on study design (measurement method, timing, and frequency) and site characteristics (vegetation, climate, hydrology, soil, and sediment types, permafrost conditions, lake size and depth, and our determination of land cover class). The different land cover classes had distinct CH 4 fluxes, resulting from definitions that were either based on or co-varied with key environmental controls. Fluxes of CH 4 from terrestrial ecosystems were primarily influenced by water table position, soil temperature, and vegetation composition, while CH 4 fluxes from aquatic ecosystems were primarily influenced by water temperature, lake size, and lake genesis. Models could explain more of the between-site variability in CH 4 fluxes for terrestrial than aquatic ecosystems, likely due to both less precise assessments of lake CH 4 fluxes and fewer consistently reported lake site characteristics. Analysis of BAWLD-CH 4 identified both land cover classes and regions within the boreal and arctic domain, where future studies should be focused, alongside methodological approaches. Overall, BAWLD-CH 4 provides a comprehensive dataset of CH 4 emissions from high-latitude ecosystems that are useful for identifying research opportunities, for comparison against new field data, and model parameterization or validation.

54 ENVIRONMENTAL SCIENCES↗

Regional trends and drivers of the global methane budget

Abstract The ongoing development of the Global Carbon Project (GCP) global methane (CH 4 ) budget shows a continuation of increasing CH 4 emissions and CH 4 accumulation in the atmosphere during 2000–2017. Here, we decompose the global budget into 19 regions (18 land and 1 oceanic) and five key source sectors to spatially attribute the observed global trends. A comparison of top‐down (TD) (atmospheric and transport model‐based) and bottom‐up (BU) (inventory‐ and process model‐based) CH 4 emission estimates demonstrates robust temporal trends with CH 4 emissions increasing in 16 of the 19 regions. Five regions—China, Southeast Asia, USA, South Asia, and Brazil—account for >40% of the global total emissions (their anthropogenic and natural sources together totaling >270 Tg CH 4 yr −1 in 2008–2017). Two of these regions, China and South Asia, emit predominantly anthropogenic emissions (>75%) and together emit more than 25% of global anthropogenic emissions. China and the Middle East show the largest increases in total emission rates over the 2000 to 2017 period with regional emissions increasing by >20%. In contrast, Europe and Korea and Japan show a steady decline in CH 4 emission rates, with total emissions decreasing by ~10% between 2000 and 2017. Coal mining, waste (predominantly solid waste disposal) and livestock (especially enteric fermentation) are dominant drivers of observed emissions increases while declines appear driven by a combination of waste and fossil emission reductions. As such, together these sectors present the greatest risks of further increasing the atmospheric CH 4 burden and the greatest opportunities for greenhouse gas abatement.

59 BASIC BIOLOGICAL SCIENCES↗

MISTRAL: Concept and Analysis of Persistent Airborne Localization of GHG Emissions

In this study, we propose a concept for localizing and mitigating greenhouse gases and other emissions from areas of various sizes, using a multiscale, airborne localization fleet, supported by information from satellites. Our objective is a rapidly implementable capability for the reduction of atmospheric methane by empowering the communities in proximity to emissions to actively contribute to methane mitigation via fleet operations by local governments, first responders, and individuals . Fully autonomous operations are economically desirable and technically feasible now. However, the development of regulations for autonomous operations is in early stages. Since rapid impact is critical to reducing emissions, the concept starts with remotely controlled vehicles. As regulations for autonomous operations reach maturity, the concept can be easily transitioned from the remotely piloted to autonomous mode. We report on a preliminary system analysis of the concept. Localization of methane emissions from the Permian Basin oil and gas production site serves as the design reference mission; however, the airborne concept is applicable to a broad range of use cases, and we describe several in this analysis. We consider leveraging satellite and ground-based resources within the airborne concept of operations. The study analyses uninhabited aerial system localization operations under the most conservative assumptions on resources and available information. Even under these assumptions, the concept is shown to be viable for local community operations.

airborne methane localization↗

CFD modeling of non-catalytic, partial-oxidation engine reformer for flare mitigation

Flaring associated natural gas is commonly employed in the oil and gas industry to reduce methane (CH 4 ) emissions but generates carbon dioxide (CO 2 ) and harmful pollutants, significantly contributing to air pollution and posing risks to public health. To mitigate this impact, M2X Energy Inc. has developed a small-scale, modular gas-to-methanol system. This system features an engine reformer that performs fuel-rich partial oxidation of wellhead gas to produce syngas—a mixture of carbon monoxide (CO) and hydrogen (H 2 )—followed by a downstream reactor for methanol synthesis. This study focused on computational fluid dynamics (CFD) modeling of the engine reformer to simulate partial oxidation chemistry, predict the rich-burn operating limit, and assess syngas quality, ultimately aiding in design and operational optimization. The CFD model, developed within a Reynolds-Averaged Navier-Stokes (RANS) turbulence framework, incorporated sub-models for turbulent combustion, a chemical mechanism with polycyclic aromatic hydrocarbon (PAH) pathways, and soot emissions to accurately capture the fuel-rich, turbulent jet ignition and combustion processes. Model validation against experimental data showed good agreement across pre- and main-chamber pressures, apparent heat release rates, and exhaust gas concentrations of key species (H 2 , CO, CO 2 , CH 4 ) for varying intake equivalence ratios. Here, the model identified a rich-burn operating limit near a fuel-air equivalence ratio of 2.35, consistent with experimental observations. Furthermore, syngas quality analysis revealed that extending the rich-burn limit through engine reformer optimization could enhance syngas production, contributing to higher methanol synthesis efficiency.

Computational Fluid Dynamics↗

Microtopography Matters: Belowground CH 4 Cycling Regulated by Differing Microbial Processes in Peatland Hummocks and Lawns

Water table depth and vegetation are key controls of methane (CH 4 ) emissions from peatlands. Microtopography integrates these factors into features called microforms. Microforms often differ in CH 4 emissions, but microform-dependent patterns of belowground CH 4 cycling remain less clearly resolved. Here, to investigate the impact of microtopography on belowground CH 4 cycling, we characterized depth profiles of the community composition and activity of CH 4 -cycling microbes using 16S rRNA amplicon sequencing, incubations, and measurements of porewater CH 4 concentration and isotopic composition from hummocks and lawns at Sallie's Fen in NH, USA. Geochemical proxies of methanogenesis and methanotrophy indicated that microforms differ in dominant microbial CH 4 cycling processes. Hummocks, where water table depth is lower, had higher porewater redox potential (Eh) and higher porewater δ 13 C-CH 4 values in the upper 30 cm than lawns, where water table depth is closer to the peat surface. Porewater δ 13 C-CH 4 and δD-CH 3 D values were highest at the surface of hummocks where the ratio of methanotrophs to methanogens was also greatest. These results suggest that belowground CH 4 cycling in hummocks is more strongly regulated by methanotrophy, while in lawns methanogenesis is more dominant. We also investigated controls of porewater CH 4 chemistry. The ratio of the relative abundance of methanotrophs to methanogens was the strongest predictor of porewater CH 4 concentration and δ 13 C-CH 4 , while vegetation composition had minimal influence. As microbial community composition was strongly influenced by redox conditions but not vegetation, we conclude that water table depth is a stronger control of belowground CH 4 cycling across microforms than vegetation.

59 BASIC BIOLOGICAL SCIENCES↗

An Integrative Model for Soil Biogeochemistry and Methane Processes. II: Warming and Elevated CO 2 Effects on Peatland CH 4 Emissions

Peatlands are one of the largest natural sources for atmospheric methane (CH 4 ), a potent greenhouse gas. Climate warming and elevated atmospheric carbon dioxide (CO 2 ) are two important environmental factors that have been confirmed to stimulate peatland CH 4 emissions; however, the mechanisms underlying enhanced emissions remain elusive. A data-model integration approach was applied to understand the CH 4 processes in a northern temperate peatland under a gradient of warming and doubled atmospheric CO 2 concentration. We found that warming and elevated CO 2 stimulated CH 4 emissions through different mechanisms. Warming initially stimulated but then suppressed vegetative productivity while stimulating soil organic matter (SOM) mineralization and dissolved organic carbon (DOC) fermentation, which led to higher acetate production and enhanced acetoclastic and hydrogenotrophic methanogenesis. Warming also enhanced surface CH 4 emissions, which combined with warming-caused decreases in CH 4 solubility led to slightly lower dissolved CH 4 concentrations through the soil profiles. Elevated CO 2 enhanced ecosystem productivity and SOM mineralization, resulting in higher DOC and acetate concentrations. Higher DOC and acetate concentrations increased acetoclastic and hydrogenotrophic methanogenesis and led to higher dissolved CH 4 concentrations and CH 4 emissions. Both warming and elevated CO 2 had minor impacts on CH 4 oxidation. A meta-analysis of warming and elevated CO 2 impacts on carbon cycling in wetlands agreed well with a majority of the modeled mechanisms. Finally, this mechanistic understanding of the stimulating impacts of warming and elevated CO 2 on peatland CH 4 emissions enhances our predictability on the climate-ecosystem feedback.

54 ENVIRONMENTAL SCIENCES↗

Characterizing Performance of Freshwater Wetland Methane Models Across Time Scales at FLUXNET-CH 4 Sites Using Wavelet Analyses

Process-based land surface models are important tools for estimating global wetland methane (CH 4 ) emissions and projecting their behavior across space and time. So far there are no performance assessments of model responses to drivers at multiple time scales. In this study, we apply wavelet analysis to identify the dominant time scales contributing to model uncertainty in the frequency domain. We evaluate seven wetland models at 23 eddy covariance tower sites. Our study first characterizes site-level patterns of freshwater wetland CH 4 fluxes (FCH 4 ) at different time scales. A Monte Carlo approach was developed to incorporate flux observation error to avoid misidentification of the time scales that dominate model error. Our results suggest that (a) significant model-observation disagreements are mainly at multi-day time scales (<15 days); (b) most of the models can capture the CH 4 variability at monthly and seasonal time scales (>32 days) for the boreal and Arctic tundra wetland sites but have significant bias in variability at seasonal time scales for temperate and tropical/subtropical sites; (c) model errors exhibit increasing power spectrum as time scale increases, indicating that biases at time scales <5 days could contribute to persistent systematic biases on longer time scales; and (d) differences in error pattern are related to model structure (e.g., proxy of CH 4 production). Our evaluation suggests the need to accurately replicate FCH 4 variability, especially at short time scales, in future wetland CH 4 model developments.

58 GEOSCIENCES↗

Massive peatland carbon banks vulnerable to rising temperatures

Peatlands contain one-third of the world’s soil carbon (C). If destabilized, decomposition of this vast C bank could accelerate climate warming; however, the likelihood of this outcome remains unknown. Here, we examine peatland C stability through five years of whole-ecosystem warming and two years of elevated atmospheric carbon dioxide concentrations (eCO 2 ). Warming exponentially increased methane (CH 4 ) emissions and enhanced CH 4 production rates throughout the entire soil profile; although surface CH 4 production rates remain much greater than those at depth. Additionally, older deeper C sources played a larger role in decomposition following prolonged warming. Most troubling, decreases in CO 2 :CH 4 ratios in gas production, porewater concentrations, and emissions, indicate that the peatland is becoming more methanogenic with warming. We observed limited evidence of eCO 2 effects. Our results suggest that ecosystem responses are largely driven by surface peat, but that the vast C bank at depth in peatlands is responsive to prolonged warming.

54 ENVIRONMENTAL SCIENCES↗

Depth-resolved carbon dioxide and methane concentrations in 522 lakes, ponds, and reservoirs worldwide

Lakes, ponds, and reservoirs (hereafter: “lakes”) are important sources of the greenhouse gases carbon dioxide (CO 2 ) and methane (CH 4 ). Emissions of CO 2 and CH 4 from lakes are regulated in part by in-lake processes, including the production and storage of gases in the lower parts of the water column (bottom waters). However, while substantial efforts have been made to improve estimates of greenhouse gas emissions from lakes, limited data on gas concentrations along depth profiles have prevented the incorporation of bottom-water processes in global emission estimates. Here, we present GHG-depths: the largest existing dataset of depth-profile CO 2 and CH 4 measurements worldwide, including 522 lakes across 38 countries and all seven continents. These data include contributions from 45 research teams and 56 published studies, totaling 2558 discrete sampling events. As global change continues to alter biogeochemical cycling in lakes, these data can help improve mechanistic models to better predict greenhouse gas production and emission from lakes worldwide.

Rabaey, Joseph S. [University of Minnesota, Duluth↗

Development and Evaluation of Ensemble Learning-based Environmental Methane Detection and Intensity Prediction Models

The environmental impacts of global warming driven by methane (CH 4 ) emissions have catalyzed significant research initiatives in developing novel technologies that enable proactive and rapid detection of CH 4 . Several data-driven machine learning (ML) models were tested to determine how well they identified fugitive CH 4 and its related intensity in the affected areas. Various meteorological characteristics, including wind speed, temperature, pressure, relative humidity, water vapor, and heat flux, were included in the simulation. We used the ensemble learning method to determine the best-performing weighted ensemble ML models built upon several weaker lower-layer ML models to (i) detect the presence of CH 4 as a classification problem and (ii) predict the intensity of CH 4 as a regression problem. The classification model performance for CH 4 detection was evaluated using accuracy, F1 score, Matthew’s Correlation Coefficient (MCC), and the area under the receiver operating characteristic curve (AUC ROC), with the top-performing model being 97.2%, 0.972, 0.945 and 0.995, respectively. The R 2 score was used to evaluate the regression model performance for CH 4 intensity prediction, with the R 2 score of the best-performing model being 0.858. The ML models developed in this study for fugitive CH 4 detection and intensity prediction can be used with fixed environmental sensors deployed on the ground or with sensors mounted on unmanned aerial vehicles (UAVs) for mobile detection.

Majumder, Reek↗

Understanding and modeling current and future coastal wetland methane dynamics (Final Report)

The coastal terrestrial-aquatic interface (TAI) is a highly dynamic component of the Earth system that plays a critical role in biogeochemical cycling. Due to its dynamic nature, the processes that regulate decomposition and methane (CH 4 ) emissions are of greater significance at the TAI than in upland systems. Despite this, we have limited mechanistic understanding of how climate stressors interact to regulate the electron acceptors and donors that determine decomposition pathways within TAIs, including the generation of hot spots and hot moments. Accurately modeling these processes is critical for incorporating the coastal TAI into Earth systems models, such as DOE’s E3SM. With previous DOE support, we adapted an aerobic terrestrial representation of decomposition using PFLOTRAN, a reactive flow and transport model, and added anerobic decomposition pathways, salinity, and oxygen (O 2 ) that fluctuates independently of water table level. However, because this model (PFLOTRAN TAI ) is based on decomposition rates and organic matter carbon to nitrogen ratios from terrestrial systems, its performance in TAI systems is currently limited by the lack of empirical data to properly parameterize variables. In addition, while PFLOTRAN TAI can simulate movement of O 2 into sediments, it is not currently capable of tracking the movement of CH 4 gas through plant tissues due to both current model structure and lack of available data. Our overall objective of the project was the increase our mechanistic understanding of CH 4 dynamics in response to environmental change, such that we can improve the representation of these dynamics in PFLOTRAN. We installed automated flux chambers in a new field-scale active soil warming experiment and set up marsh organs (mesocosms) to test effects of warming, flooding, and salinity. This resulted in a new dataset consisting of chamber-level CH 4 flux measurements across multiple sites, ecological conditions, and timeframes, as well as corresponding measurements on porewater chemistry, soil carbon quality, plant biomass, and redox reaction rates. Using these data, we improved PFLOTRAN TAI to more accurately model CH 4 dynamics and successfully tested our hypotheses. This grant contributed to the professional development of 3 postdocs, 4 undergraduate interns, 4 teacher interns, 17 technicians, and 15 participatory scientists. The automated chamber technology designed for this grant has also been shared with multiple new projects.

54 ENVIRONMENTAL SCIENCES↗

Hysteretic temperature sensitivity of wetland CH 4 fluxes explained by substrate availability and microbial activity

Methane (CH 4 ) emissions from wetlands are likely increasing and important in global climate change assessments. However, contemporary terrestrial biogeochemical model predictions of CH 4 emissions are very uncertain, at least in part due to prescribed temperature sensitivity of CH 4 production and emission. While statistically consistent apparent CH 4 emission temperature dependencies have been inferred from meta-analyses across microbial to ecosystem scales, year-round ecosystem-scale observations have contradicted that finding. Here, we show that apparent CH 4 emission temperature dependencies inferred from year-round chamber measurements exhibit substantial intra-seasonal variability, suggesting that using static temperature relations to predict CH 4 emissions is mechanistically flawed. Our model results indicate that such intra-seasonal variability is driven by substrate-mediated microbial and abiotic interactions: seasonal cycles in substrate availability favors CH 4 production later in the season, leading to hysteretic temperature sensitivity of CH 4 production and emission. Our findings demonstrate the uncertainty of inferring CH 4 emission or production rates from temperature alone and highlight the need to represent microbial and abiotic interactions in wetland biogeochemical models.

54 ENVIRONMENTAL SCIENCES↗

From the top: surface-derived carbon fuels greenhouse gas production at depth in a peatland

Tropical peatlands play an important role in global carbon (C) cycling, but little is known about factors driving carbon dioxide (CO 2 ) and methane (CH 4 ) emissions from these ecosystems, especially production in deeper soils. This study aimed to identify source material and processes regulating C emissions originating deep in three sites in a peatland on the Caribbean coast of Panama. We hypothesized that (1) surface-derived organic matter transported down the soil profile is the primary C source for respiration products at depth and that (2) high lignin content results in hydrogenotrophic methanogenesis as the dominant CH 4 production pathway throughout the profile. We used radiocarbon isotopic values to determine whether CO 2 and CH 4 at depth are produced from modern substrates or ancient deep peat, and we used stable C isotopes to identify the dominant CH 4 production pathway. Peat organic chemistry was characterized using 13 C solid-state nuclear magnetic resonance spectroscopy ( 13 C-NMR). We found that deep peat respiration products had radiocarbon signatures that were more similar to surface dissolved organic C (DOC) than deep solid peat. These results indicate that surface-derived organic matter was the dominant source for gas production at depth in this peatland, likely because of vertical transport of DOC from the surface to depth. Lignin, which was the most abundant compound (55 %–70 % of C), increased with depth across these sites, whereas other C compounds like carbohydrates did not vary with depth. These results suggest that there is no preferential decomposition of carbohydrates but instead preferential retention of lignin. Stable isotope signatures of respiration products indicated that hydrogenotrophic rather than acetoclastic methanogenesis was the dominant production pathway of CH 4 throughout the peat profile. These results show that deep C in tropical peatlands does not contribute greatly to surface fluxes of carbon dioxide, with compounds like lignin preferentially retained. This protection of deep C helps explain how peatland C is retained over thousands of years and points to the vulnerability of this C should anaerobic conditions in these wet ecosystems change.

54 ENVIRONMENTAL SCIENCES↗

FLUXNET-CH 4 : a global, multi-ecosystem dataset and analysis of methane seasonality from freshwater wetlands

Methane (CH 4 ) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH 4 emissions due to quasi-continuous and high-temporal-resolution CH 4 flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH 4 Version 1.0, the first open-source global dataset of CH 4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH 4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH 4 representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH4 Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH 4 emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH 4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20°S to 20°N) the spring onset of elevated CH 4 emissions starts 3 d earlier, and the CH 4 emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH 4 emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH 4 emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH 4 emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH 4 emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH 4 modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH 4 peak). FLUXNET-CH 4 is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH 4 cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH 4 data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.

54 ENVIRONMENTAL SCIENCES↗

SELF-HEALING PNEUMATIC ACTUATOR DIAPHRAGMS

In the oil and gas industry, damaged diaphragms in pneumatic actuators can lead to unintended methane leaks, increasing emissions. In this work, replacement self-healing diaphragms are manufactured for a commercial pneumatic actuator. To enable self-healing, hollow microvascular networks are created within the diaphragms using sacrificial 3D printed PLA w/ tin(II) oxalate. These microvascular networks are filled with healing chemistries and, upon damage, rupture. After rupturing, the healing chemistries mix and cure to “heal” the damage and reduce leaks. Separate actuator test stands using nitrogen gas and using natural gas were developed to assess the healing performance of diaphragms. A fatigue stand was also developed to evaluate the effects of the different microvascular network geometries on the fatigue life of diaphragms. Our results demonstrate self-healing in diaphragms subjected to damage and tested for leaks. In fatigue testing, our results indicate that the introduction of microvascular networks does not influence the fatigue life.

Self-healing, pneumatic actuator↗

Illuminating the pathways to carbon liberation: a systems approach to characterizing the consequential unknowns of carbon transformation and loss from thawing permafrost peatlands (Final Report)

The IsoGenie3 Project delivered new systems-level insights into carbon cycling in thawing permafrost landscapes, with an emphasis on methane and carbon dioxide emissions. From >200 samples from the site collected over a decade, co-analyzed for geochemistry and microbiology, the team recovered ~1,500 assembled microbial genomes and ~1,900 viral population genomes, revealing appreciable genetic novelty - from a new highly abundant bacterial phylum, to novel methane consumers and their activities, to rampant viral novelty. IsoGenie3 linked these organisms to carbon compound transformations (which define the cycling of organic matter in soils, and the loss of the greenhouse gases carbon dioxide and methane), and saw that the microbes at each stage of permafrost thaw had different genetic potential to degrade categories of compounds, expressed that genetic potential differently, and actually transformed carbon compounds into greenhouse gases in different ways. IsoGenie 3 identified that some of the thaw-stage differences were due to plant-microbiome relationships; the plant species across the thaw gradient contributed different carbon compounds into the soil, and hosted distinct microbiota (differing among parts of plants as well as species). Lastly, microbes in the saturated post-thaw conditions appeared likely to contribute to the mobilization and toxification of mercury released during thaw. In parallel with ongoing field sampling and analysis, hypotheses arising from field observations were tested via lab incubation experiments. When communities are taken out of their native habitats, they behave differently, and the team first rigorously quantified the magnitude of this effect on microbiome composition and functional capacity, organic matter composition, and gas production; overall the main system processes were maintained in the lab incubations under the conditions tested. Further, the microbial data could inform geochemical reaction network models of those processes. Then, the team ran experiments with additions of compounds, varying temperature, and “live” vs. “dead” peat (the latter having been gamma irradiated, with a few additional variants to control for methodological artifacts). From these, we (a) determined the importance of plant-derived soluble phenolic compounds in bogs’ extraordinary recalcitrance of organic matter, and carbon gas emissions skewed to carbon dioxide; (b) proposed an abiotic ‘tanning’ mechanism, which could contribute to Sphagnum’s inhibitory effect on anaerobic decomposition through alteration of N availability. IsoGenie3 illuminated longer-term and landscape-scale interactions of permafrost thaw and carbon cycling, advancing knowledge of the drivers of methane dynamics not only across in the permafrost-associated peatland (where hydrology and plant communities dictate microbiomes) but also their interconnected lakes (where sediment carbon quality and resident microbiota are determined by position within lake, and lake features). By leveraging observations of site methane dynamics extending well before this project, the team was able to construct a 44-year portrait of the interplay of permafrost thaw, hydrology, vegetation dynamics, and carbon gas emissions, and the doubling of the fully-thawed fens over this time. From the detailed study of this focal site, IsoGenie3 also aimed to improve model representation of these kinds of sites and processes. To improve predictions of methane transformations, we incorporated acetate and isotope dynamics into the ‘DNDC’ biogeochemistry model. In addition, recovered genomes were grouped into ‘functional groups’, i.e. the genomes that perform a specific function of interest, then used to parameterize maximum growth rate and optimum growth temperature (via signatures in their sequence composition) for the BioCrunch model. The BioCrunch model was then in turn used to test the impact of increasing functional resolution of the microbes, on the carbon gas emissions. Lastly for modeling, the ecosys model was parameterized from the microbial and other data, and used to evaluate drivers of e.g. change in methane emissions. Finally, this project also led to the development of a range of new methods and tools, a new metric of organic matter decomposability, as well as a graph-database solution to multidisciplinary data storage and querying. This project’s ongoing analyses at our focal site also contributed to broader advancements in understanding elements of genetic plasticity and methane metabolism, climate change microbiology and community assembly, global peatland geochemistry and Arctic lakes’ roles in climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗

Submersed Macrophyte Density Regulates Aquatic Greenhouse Gas Emissions

Abstract Shallow freshwater ecosystems emit large amounts of greenhouse gases (GHGs), such as carbon dioxide (CO 2 ) and methane (CH 4 ), yet emissions are highly variable. The role that aquatic macrophytes play in regulating aquatic GHG emissions is uncertain despite their ability to dominate shallow waterbodies. Here, we studied the effects of submersed macrophyte (Ceratophyllum demersum) density on CO 2 and CH 4 concentrations and fluxes. We conducted a 61‐days experiment using mesocosms containing one of the followingC.demersumdensity treatments: 0, 10, 20, or 30 individual shoots (n = 3). We found that high densityC.demersumhad the highest CO 2 and CH 4 surface water concentrations and emissions while there was no significant difference in CH 4 in the low and medium densities and no plant control. The high density treatment lost biomass over the course of the experiment, indicating die‐off and additions of organic matter to the sediment. High organic matter loading and low dissolved oxygen likely stimulated GHG production in the high density treatment. Our results emphasize that submersed macrophyte density and periods of growth and dieback are important in regulating GHG emissions, which may help explain why shallow waterbodies are high yet variable sources of GHGs to the atmosphere.

Environmental Sciences & Ecology↗