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At least 361 records · Page 20

Sabatier Reactor System Integration with Microwave Plasma Methane Pyrolysis Post-Processor for Closed-Loop Hydrogen Recovery

The Carbon Dioxide Reduction Assembly (CRA) designed and developed for the International Space Station (ISS) represents the state-of-the-art in carbon dioxide reduction (CDRe) technology. The CRA produces water and methane by reducing carbon dioxide with hydrogen via the Sabatier reaction. The water is recycled to the Oxygen Generation Assembly (OGA) and the methane is vented overboard resulting in a net loss of hydrogen. The proximity to earth and the relative ease of logistics resupply from earth allow for a semi-closed system on ISS. However, long-term manned space flight beyond low earth orbit (LEO) dictates a more thoroughly closed-loop system involving significantly higher recovery of hydrogen, and subsequent recovery of oxygen, to minimize costs associated with logistics resupply beyond LEO. The open-loop ISS system for CDRe can be made closed-loop for follow-on missions by further processing methane to recover hydrogen. For this purpose, a process technology has been developed that employs a microwave-generated plasma to reduce methane to hydrogen and acetylene resulting in 75% theoretical recovery of hydrogen. In 2009, a 1-man equivalent Plasma Pyrolysis Assembly (PPA) was delivered to the National Aeronautics and Space Administration (NASA) for technical evaluation. The PPA has been integrated with a Sabatier Development Unit (SDU). The integrated process configuration incorporates a sorbent bed to eliminate residual carbon dioxide and water vapor in the Sabatier methane product stream before it enters the PPA. This paper provides detailed information on the stand-alone and integrated performance of both the PPA and SDU. Additionally, the integrated test stand design and anticipated future work are discussed.

Abney, Morgan B.↗

Methane Sensitivity to Perturbations in Tropospheric Oxidizing Capacity

Methane is an important greenhouse gas and has a 25 times greater global warming potential than CO2 on a century timescale. Yet there are considerable uncertainties in the magnitude and variability of its sources and sinks. The response of the coupled non-linear methane-carbon monoxide-hydroxyl radical (OH) system is important in determining the tropospheric oxidizing capacity. Using the NASA Goddard Earth Observing System, Version 5 (GEOS-5) chemistry climate model, we study the response of methane to perturbations of OH and wetland emissions. We use a computationally-efficient option of the GEOS-5 CCM that includes an OH parameterization that accurately represents OH predicted by a full chemical mechanism. The OH parameterization allows for studying non-linear CH4-CO-OH feedbacks in computationally fast sensitivity experiments. We compare our results with surface observations (GMD) and discuss the range of uncertainty in OH and wetland emissions required to bring modeling results in better agreement with surface observations. Our results can be used to improve projections of methane emissions and methane growth.

Yegorova, Elena↗

Testing of a Methane Cryogenic Heat Pipe with a Liquid Trap Turn-Off Feature for use on Space Interferometer Mission (SIM)

Camera cooling for SIM presents three thermal control challenges; stable operation at 163K (110 C), decontamination heating to +20 C, and a long span from the cameras to the radiator. A novel cryogenic cooling system based on a methane heat pipe meets these challenges. The SIM thermal team, with the help of heat pipe vendor ATK, designed and tested a complete, low temperature, cooling system. The system accommodates the two SIM cameras with a double-ended conduction bar, a single methane heat pipe, independent turn-off devices, and a flight-like radiator. The turn ]off devices consist of a liquid trap, for removing the methane from the pipe, and an electrical heater to raise the methane temperature above the critical point thus preventing two-phase operation. This is the first time a cryogenic heat pipe has been tested at JPL and is also the first heat pipe to incorporate the turn-off features. Operation at 163K with a methane heat pipe is an important new thermal control capability for the lab. In addition, the two turn-off technologies enhance the "bag of tricks" available to the JPL thermal community. The successful test program brings this heat pipe to a high level of technology readiness.

cyrogenic heat pipe↗

Ground and Airborne Methane Measurements using Optical Parametric Amplifiers

We report on an initial airborne demonstration of atmospheric methane column measurements at 1.65 micrometers using a widely tunable, seeded optical parametric amplifier (OPA) lidar and a photon counting detector. Methane is an important greenhouse gas and accurate knowledge of its sources and sinks is needed for climate modeling. Our lidar system uses 20 pulses at increasing wavelengths and integrated path differential absorption (IPDA) to map a methane line at 1650.9 nanometers. The wavelengths are generated by using a Nd:YAG pump laser at 1064.5 nanometers and distributed feedback diode laser at 1650.9 nanometers and a periodically-poled lithium niobate (PPLN) crystal. The pulse width was 3 nanoseconds and the pulse repetition rate was 6.28 KHz. The outgoing energy was approximately 13 microJoules/pulse. A commercial 20 nanometer diameter fiber-coupled telescope with a photon counting detector operated in analog mode with a 0.8 nanometer bandpass filter was used as the lidar receiver. The lidar system was integrated on NASA's DC-8 flying laboratory, based at Dryden Airborne operations Facility (DAOF) in Palmdale CA. Three flights were performed in the central valley of California. Each flight lasted about 2.5 hours and it consisted of several flight segments at constant altitudes at approximately 3, 4.5, 6, 7.6, 9.1, 10.6 km (l0, 15, 20, 25, 30, 35 kft). An in-situ cavity ring down spectrometer made by Picarro Inc. was flown along with the lidar instrument provided us with the "truth" i.e. the local CH4, CO2 and H2O concentrations at the constant flight altitude segments. Using the aircraft's altitude, GPS, and meteorological data we calculated the theoretical differential optical depth of the methane absorption at increasing altitudes. Our results showed good agreement between the experimentally derived optical depth measurements from the lidar instrument and theoretical calculations as the flight altitude was increased from 3 to 10.6 kilometers, assuming a constant methane mixing ratio of 1.8 parts per million. The in-situ spectrometer did not show any significant deviations from the ambient concentrations. Further analysis using meteorological data from the Global Modeling and Assimilation Office (http://gmao.gsfc.nasa.gov/) to derive the theoretical optical depth also showed good agreement with the experimentally derived values. The OPA lidar system with slight modifications has also been used to measure CO2, water vapor, and CO in the near and mid-infrared spectral regions on the ground.

Riris, Haris↗

Determining the Local Abundance of Martian Methane and its 13-C/l2-C and D/H Isotopic Ratios for Comparison with Related Gas and Soil Analysis on the 2011 Mars Science Laboratory (MSL) Mission

Understanding the origin of Martian methane will require numerous complementary measurements from both in situ and remote sensing investigations and laboratory work to correlate planetary surface geophysics with atmospheric dynamics and chemistry. Three instruments (Quadrupole Mass Spectrometer (QMS), Gas Chromatograph (GC) and Tunable Laser Spectrometer (TLS)) with sophisticated sample handling and processing capability make up the Sample Analysis at Mars (SAM) analytical chemistry suite on NASA s 2011 Mars Science Laboratory (MSL) Mission. Leveraging off the SAM sample and gas processing capability that includes methane enrichment, TLS has unprecedented sensitivity for measuring absolute methane (parts-per-trillion), water, and carbon dioxide abundances in both the Martian atmosphere and evolved from heated soil samples. In concert with a wide variety of associated trace gases (e.g. SO2, H2S, NH3, higher hydrocarbons, organics, etc.) and other isotope ratios measured by SAM, TLS will focus on determining the absolute abundances of methane, water and carbon dioxide, and their isotope ratios: 13C/12C and D/H in methane; 13C/12C and 18O/17O/16O in carbon dioxide; and 18O/17O/16O and D/H in water. Measurements near the MSL landing site will be correlated with satellite (Mars Express, Mars 2016) and ground-based observations.

Webster, Christopher R.↗

Efficient 1.6 Micron Laser Source for Methane DIAL

Methane is a potent greenhouse gas and on a per molecule basis has a warming influence 72 times that of carbon dioxide over a 20 year horizon. Therefore, it is important to look at near term radiative effects due to methane to develop mitigation strategies to counteract global warming trends via ground and airborne based measurements systems. These systems require the development of a time-resolved DIAL capability using a narrow-line laser source allowing observation of atmospheric methane on local, regional and global scales. In this work, a demonstrated and efficient nonlinear conversion scheme meeting the performance requirements of a deployable methane DIAL system is presented. By combining a single frequency 1064 nm pump source and a seeded KTP OPO more than 5 mJ of 1.6 μm pulse energy is generated with conversion efficiencies in excess of 20%. Even without active cavity control instrument limited linewidths (50 pm) were achieved with an estimated spectral purity of ~95%. Tunable operation over 400 pm (limited by the tuning range of the seed laser) was also demonstrated. This source demonstrated the critical needs for a methane DIAL system motivating additional development of the technology.

Shuman, Timothy↗

Combustion Stability Characteristics of the Project Morpheus Liquid Oxygen/Liquid Methane Main Engine

The Project Morpheus liquid oxygen (LOX) / liquid methane rocket engines demonstrated acousticcoupled combustion instabilities during sea‐level ground‐based testing at the NASA Johnson Space Center (JSC) and Stennis Space Center (SSC). High‐amplitude, 1T, 1R, 1T1R (and higher order) modes appear to be triggered by injector conditions. The instability occurred during the Morpheus‐specific engine ignition/start sequence, and did demonstrate the capability to propagate into mainstage. However, the instability was never observed to initiate during mainstage, even at low power levels. The Morpheus main engine is a JSC‐designed ~5,000 lbf‐thrust, 4:1 throttling, pressure‐fed cryogenic engine using an impinging element injector design. Two different engine designs, named HD4 and HD5, and two different builds of the HD4 engine all demonstrated similar instability characteristics. Through the analysis of more than 200 hot fire tests on the Morpheus vehicle and SSC test stand, a relationship between ignition stability and injector/chamber pressure was developed. The instability has the distinct characteristic of initiating at high relative injection pressure drop (dP) at low chamber pressure (Pc); i.e., instabilities initiated at high dP/Pc at low Pc during the start sequence. The high dP/Pc during start results during the injector /chamber chill‐in, and is enhanced by hydraulic flip in the injector orifice elements. Because of the fixed mixture ratio of the existing engine design (the main valves share a common actuator), it is not currently possible to determine if LOX or methane injector dP/Pc were individual contributors (i.e., LOX and methane dP/Pc typically trend in the same direction within a given test). The instability demonstrated initiation characteristic of starting at or shortly after methane injector chillin. Colder methane (e.g., sub‐cooled) at the injector inlet prior to engine start was much more likely to result in an instability. A secondary effect of LOX sub‐cooling was also possibly observed; greater LOX sub‐ cooling improved stability. Some tests demonstrated a low‐amplitude 1L‐1T instability prior to LOX injector chill‐in. The Morpheus main engine also demonstrated chug instabilities during some engine shutdown sequences on the flight vehicle and SSC test stand. The chug instability was also infrequently observed during the startup sequence. The chug instabilities predictably initiated at low dP/Pc at low Pc. The chug instabilities were always self‐limiting; startup chug instabilities terminated during throttle‐up and shutdown chug instabilities decayed by shutdown termination.

Melcher, J. C.↗

Using Unmanned Air Systems to Monitor Methane in the Atmosphere

Methane is likely to be an important contributor to global warming, and our current knowledge of its sources, distributions, and transport is insufficient. It is estimated that there could be from 7.5 to 400 billion tons carbon-equivalent of methane in the arctic region, a broad range that is indicative of the uncertainty within the Earth Science community. Unmanned Air Systems (UASs) are often used for combat or surveillance by the military, but they also have been used for Earth Science field missions. In this study, we will analyze the utility of the NASA Global Hawk and the Aurora Flight Sciences Orion UASs compared to the manned DC-8 aircraft for conducting a methane monitoring mission. The mission will focus on the measurement of methane along the boundaries of Arctic permafrost thaw and melting glaciers. The use of Long Endurance UAS brings a new range of possibilities including the ability to obtain long- term and persistent observations and to significantly augment methane measurements/retrievals collected by satellite. Furthermore, we discuss the future of long endurance UAS and their potential for science applications in the next twenty to twenty-five years.

Clow, Jacqueline↗

Gulf of Mexico Health & Air Quality: Mapping Methane Emission Plumes Using Sunglint-configured Imagery for Monitoring Offshore Oil and Gas Activity

We had three project objectives that we set out to accomplish. The first objective is to demonstrate how remote sensing can complement the current bottom-up methane emission assessments. Currently, quantities of disposed gas vented and flared are self-reported by operators to BOEM and BSEE. Meanwhile, inspections are uncommon, and ground sensors are non-existent. Therefore, remote sensing may be the agencies' best bet in verifying these operator accounts. The second objective is to identify methane plumes in the Gulf of Mexico, Asia, and elsewhere using Sentinel-2, LandSat, and PRISMA images, and then present an estimate of their emission rate. While methane retrievals from oil and gas infrastructure on-shore has been relatively well-documented, doing so on the offshore oil and gas platforms is more difficult, less prevalent, and contingent on the presence of specific conditions. The final objective is to give our partners, BOEM and BSEE, a more robust understanding of methane emissions from oil and gas production in the Gulf of Mexico. This increased knowledge, paired with a demonstration of methane monitoring, is intended to help our partners think about how they can incorporate remote sensing into their monitoring, regulatory and enforcement framework.

Ben Dahan↗

Smart Methane Emission Detection System Development (Final Report)

Working with the Department of Energy’s National Energy Technology Laboratory, Southwest Research Institute® (SwRI®) developed a system to identify methane leaks reliably, accurately, and autonomously at critical midstream sections of the natural gas distribution network in real- time for the purpose of mitigating methane emissions using Optical Gas Imaging (OGI) cameras. SwRI’s Smart Leak Detection – Methane (SLED/M) adds a high degree of automation to the process of methane leak detection to minimize sources of human error, minimize response time to a leak event, and maximize midstream visibility. Furthermore, SwRI has been working towards integrating Quantitative OGI (QOGI) capabilities into this existing technology. By leveraging Deep Learning, SwRI now has the capability to estimate fugitive emission leak rates quickly and reliably, which allows operators to detect emissions, quantify leak rate, prioritize repairs, and validate the repairs in a single instrument. The next generation QOGI technology leverages the same cameras used in Leak Detection and Repair (LDAR) programs, with improvements in safety and speed for traditional quantification-based repairs, ultimately leading to less overhead cost for the operators. The goals for this research were to develop two types of models with the following goals: 1. Run in real-time on the edge (≥ 12 Hz) 2. Classification: Achieve less than 5% false positive detection 3. Classification: Achieve ≥ 95% methane plume detection rate 4. Regression: achieve ≤ 10 standard cubic feet per hour (scfh) prediction > 70% of the time In order to achieve these results, multiple infrared (IR) and other sensors were investigated in tandem with the midwave IR (MWIR) OGI to provide additional information to train the underlying models. Information on atmospheric conditions including humidity, temperature, pressure, and solar radiation was provided by a weather station. Several machine learning and deep learning architectures and methods, including looking at quantized classification networks and regressions networks, were explored. As further data was collected, curated, and labeled, it allowed for more refined regressive networks to be adequately trained, leading to better insight into the true flow rates being observed. An important valuable deliverable of this research effort was the development of an advanced network which underwent multiple iterations capable of giving a continuous output. The current network has a predicted mean average percentage error (MAPE) of 12.3% just outside our target goal of 10.00%, but an accuracy of 97.78% at ±50 scfh, well within the overall goal for the Department of Energy (DOE) program. Upon closer inspection, it was observed that more than 10% of datapoints contributing to the MAPE predictions were the result of low flow rate predictions and are beyond the sensitivity of instrument measurement as a result of normal operational variation and noise.

03 NATURAL GAS↗

Impacts of The Wetland Sedge Carex aquatilis on Microbial Community and Methane Metabolisms

Microbial activity in the soil of wetlands is responsible for the emission of more methane to the atmosphere than all other natural sources combined. This microbial activity is heavily impacted by plant roots, which influence the microbial community by exuding organic compounds and by leaking oxygen into an otherwise anoxic environment. This study compared the microbial communities of planted and unplanted wetland soil from an Alaskan bog to elucidate how plant growth influences populations and metabolisms of methanogens and methanotrophs. A common boreal wetland sedge, Carex aquatilis, was grown in the laboratory and DNA samples were sequenced from the rhizosphere, unplanted bulk soil, and a simulated rhizosphere with oxygen input but no organic carbon. The abundance of both methanogens and methanotrophs were positively correlated with methane emissions. Among the methanotrophs, both aerobic and anaerobic methane oxidizing microbes were more common in the rhizosphere of mature plants than in unplanted soil, while facultative methanotrophs capable of utilizing either methane or other molecules became relatively less common. Furthermore, these trends indicate that the roots in this experiment created an environment which favored highly specialized microbial metabolisms over generalist approaches. One aspect of this specialized microbiome is the presence of both aerobic and anaerobic metabolisms, which indicates that oxygen is present but is a limiting resource controlling competition.

54 ENVIRONMENTAL SCIENCES↗

A multiscale packed-bed reactor model for sustainable ethylene production via chemical looping oxidative coupling of methane

The rising global warming concerns and shale gas discovery have prompted research in the direction of greenhouse gas (GHG), such as methane, reduction and conversion. Oxidative coupling of methane (OCM) offers a pathway to low carbon-intense valorization of methane while producing ethylene, a chemical regarded as central to the petrochemical industry. Even after decades of OCM discovery, researchers keep understanding the process and underlying chemical reactions in a pursuit to achieve industrial viability for OCM. Here, in general, OCM suffers from low C 2 selectivity, yield and reactor temperature runaways due to highly exothermic nature of its reactions. Computational Fluid Dynamics (CFD) tools help analyze spatial gradients within the reactor to deeply understand the diffusion of species, mass and heat transfer phenomena. Furthermore, challenges associated with scaling up such as hot spot formation and parametric sensitivity can be addressed without having to expend on costly experiments. The current paper presents a multiscale packed-bed reactor CFD model coupled with a chemical kinetic model for the chemical looping OCM. The CFD model includes two scales i.e., macroscale for catalyst bed and microscale for individual pellets. Moreover, a chemical kinetic model based on 10 gas-phase reactions is integrated with the CFD model. An additional surface reaction for the formation of gas-phase oxygen from catalyst surface is added to account for the absence of feed oxygen. The model is calibrated against experimental results. The calibrated model captures trends in CH 4 conversion, C 2 selectivity and C 2 yield within a ± 4.35 % range across a temperature range of 700-900 °C. Moreover, model fidelity is evaluated by varying key computational parameters such as mesh resolution and time step size. The model is also verified by varying the inlet methane concentration and the gas hourly space velocity (GHSV) and comparing the results with literature. A sensitivity analysis and scale-up of the current model is undergoing.

Chemical looping↗

Revolutionizing Methane Transformation with the Dual Production of Aromatics and Electricity in a Protonic Ceramic Electrocatalytic Membrane Reactor

Reducing the energy and carbon intensity of the conventional chemical processing industry can be achieved by electrochemically transforming natural gases into higher-value chemicals with higher efficiency and near-zero emissions. In this work, the direct conversion of methane to aromatics and electricity has been achieved in a protonic ceramic electrocatalytic membrane reactor through the integration of a proton-conducting membrane assembly and a trimetallic Pt–Cu/Mo/ZSM-5 catalyst for the nonoxidative methane dehydro-aromatization reaction. In this integrated system, a remarkable 15.6% single-pass methane conversion with an 11.4% benzene yield has been demonstrated, while a peak power density of 276 mW cm –2 is obtained at 700 °C. The enhanced 15.7% increase in conversion and 16.0% improvement in the yield are observed when compared with the thermochemical process, which is attributed to the shift of reaction equilibrium by the removal of hydrogen through the protonic membrane. Concurrently, the faster H2 removal at a higher electrical current gave rise to a higher methane conversion and benzene yield. Furthermore, the catalyst can be efficiently regenerated by eliminating carbon deposition. A stable cell potential is maintained for 45 h under a constant current load of 0.13 A cm –2 . Lastly, the dual production of aromatics and electricity in the electrocatalytic membrane reactor has been demonstrated to be an attractive approach for decarbonizing chemical processing.

aromatic compounds↗

Microbially induced precipitation of silica by anaerobic methane-oxidizing consortia and implications for microbial fossil preservation

Authigenic carbonate minerals can preserve biosignatures of microbial anaerobic oxidation of methane (AOM) in the rock record. It is not currently known whether the microorganisms that mediate sulfate-coupled AOM—often occurring as multicelled consortia of anaerobic methanotrophic archaea (ANME) and sulfate-reducing bacteria (SRB)—are preserved as microfossils. Electron microscopy of ANME-SRB consortia in methane seep sediments has shown that these microorganisms can be associated with silicate minerals such as clays [Chen et al., Sci. Rep. 4, 1–9 (2014)], but the biogenicity of these phases, their geochemical composition, and their potential preservation in the rock record is poorly constrained. Long-term laboratory AOM enrichment cultures in sediment-free artificial seawater [Yu et al., Appl. Environ. Microbiol. 88, e02109-21 (2022)] resulted in precipitation of amorphous silicate particles (~200 nm) within clusters of exopolymer-rich AOM consortia from media undersaturated with respect to silica, suggestive of a microbially mediated process. The use of techniques like correlative fluorescence in situ hybridization (FISH), scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDS), and nanoscale secondary ion mass spectrometry (nanoSIMS) on AOM consortia from methane seep authigenic carbonates and sediments further revealed that they are enveloped in a silica-rich phase similar to the mineral phase on ANME-SRB consortia in enrichment cultures. Like in cyanobacteria [Moore et al., Geology 48, 862–866 (2020)], the Si-rich phases on ANME-SRB consortia identified here may enhance their preservation as microfossils. Finally, the morphology of these silica-rich precipitates, consistent with amorphous-type clay-like spheroids formed within organic assemblages, provides an additional mineralogical signature that may assist in the search for structural remnants of microbial consortia in rocks which formed in methane-rich environments from Earth and other planetary bodies.

54 ENVIRONMENTAL SCIENCES↗

Hydrothermal but Not Mechanical Pretreatment of Wastewater Algae Enhanced Anaerobic Digestion Energy Balance due to Improved Biomass Disintegration and Methane Production Kinetics

This study used pilot-scale high-rate algae ponds to assess algal–bacteria biomass productivity and wastewater nutrient removal as well as the impact of mechanical and hydrothermal pretreatments on biomass disintegration, methane production kinetics, and anaerobic digestion (AD) energy balance. Mechanical pretreatment had a minor effect on biomass disintegration and methane production. By contrast, hydrothermal pretreatment significantly reduced particle size and increased the solubilized organic matter content by 3.5 times. The methane yield and production rate increased by 20–55% and 20–85%, respectively, with the highest values achieved after pretreatment at 121 °C for 60 min. While the 1st-order and pseudo-1st-order reaction equation models fitted methane production from untreated biomass best (R2 > 0.993), the modified Gompertz sigmoidal-type model provided a superior fit for hydrothermally pretreated algae (R2 ≥ 0.99). The AD energy balance revealed that hydrothermal pretreatment improved the total energy output by 25–40%, with the highest values for volume-specific and mass-specific total energy outputs reaching 0.23 kW per digester m3 and 2.3 MW per ton of biomass volatile solids. Additionally, net energy recovery (energy output per biomass HHV) increased from 20% for untreated algae to 32–34% for hydrothermally pretreated algae, resulting in net energy ratio and net energy efficiency of 2.14 and 68%, respectively.

09 BIOMASS FUELS↗

Utilizing Earth Observations of Soil Freeze/Thaw Data and Atmospheric Concentrations to Estimate Cold Season Methane Emissions in the Northern High Latitudes

The northern wetland methane emission estimates have large uncertainties. Inversion models are a qualified method to estimate the methane fluxes and emissions in northern latitudes but when atmospheric observations are sparse, the models are only as good as their a priori estimates. Thus, improving a priori estimates is a competent way to reduce uncertainties and enhance emission estimates in the sparsely sampled regions. Here, we use a novel way to integrate remote sensing soil freeze/thaw (F/T) status from SMOS satellite to better capture the seasonality of methane emissions in the northern high latitude. The SMOS F/T data provide daily information of soil freezing state in the northern latitudes, and in this study, the data is used to define the cold season in the high latitudes and, thus, improve our knowledge of the seasonal cycle of biospheric methane fluxes. The SMOS F/T data is implemented to LPX-Bern DYPTOP model estimates and the modified fluxes are used as a biospheric a priori in the inversion model CarbonTracker Europe-CH 4 . The implementation of the SMOS F/T soil state is shown to be beneficial in improving the inversion model’s cold season biospheric flux estimates. Our results show that cold season biospheric CH4 emissions in northern high latitudes are approximately 0.60 Tg lower than previously estimated, which corresponds to 17% reduction in the cold season biospheric emissions. This reduction is partly compensated by increased anthropogenic emissions in the same area (0.23 Tg), and the results also indicates that the anthropogenic emissions could have even larger contribution in cold season than estimated here.

54 ENVIRONMENTAL SCIENCES↗

Impact of methane and black carbon mitigation on forcing and temperature: a multi-model scenario analysis

The relatively short atmospheric lifetimes of methane (CH 4 ) and black carbon (BC) have focused attention on the potential for reducing anthropogenic climate change by reducing Short-Lived Climate Forcer (SLCF) emissions. This paper examines radiative forcing and global mean temperature results from the Energy Modeling Forum (EMF)-30 multi-model suite of scenarios addressing CH 4 and BC mitigation, the two major short-lived climate forcers. Central estimates of temperature reductions in 2040 from an idealized scenario focused on reductions in methane and black carbon emissions ranged from 0.18–0.26 °C across the nine participating models. Reductions in methane emissions drive 60% or more of these temperature reductions by 2040, although the methane impact also depends on auxiliary reductions that depend on the economic structure of the model. Climate model parameter uncertainty has a large impact on results, with SLCF reductions resulting in as much as 0.3–0.7 °C by 2040. We find that the substantial overlap between a SLCF-focused policy and a stringent and comprehensive climate policy that reduces greenhouse gas emissions means that additional SLCF emission reductions result in, at most, a small additional benefit of ~ 0.1 °C in the 2030–2040 time frame.

54 ENVIRONMENTAL SCIENCES↗

Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Time series of methane fluxes measured by eddy-covariance require gap-filling to estimate annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for methane, with regards both to the best model algorithms and predictors. In this study, we address the need for standardization by synthesizing results of gap-filling methods applied at 17 wetland sites spanning boreal to tropical regions including all major wetlands classes and two rice paddies. We introduce new procedures for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with robust uncertainty estimates. We tested a conventional method (marginal distribution sampling) and four machine learning algorithms - penalized linear regression, artificial neural networks, random forests, and boosted decision trees - and four predictor sets, including temporal, meteorological, ecosystem carbon and energy flux, and soil predictors. We find that the conventional method can achieve similar median performance to the machine learning models but is worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. Finally, we gap-fill and provide summary evaluation metrics for all 81 sites in the FLUXNET-CH4 community dataset and publicly release the python code for model development, evaluation, and uncertainty estimation.

42 ENGINEERING↗