Methane Measurements Research Articles

Active near‐infrared laser heterodyne system based on supercontinuum laser source for gas measurement

AbstractThe performance of an active near‐infrared laser heterodyne system using a supercontinuum light source as the light signal for trace species detection is experimentally demonstrated. The characteristics of the supercontinuum light source and the data processing methods used in heterodyne detection are described. The measurement of methane (CH₄) and carbon dioxide (CO₂) absorption spectra was carried out in the laboratory to evaluate the active laser heterodyne system, and high‐resolution absorption spectra of CO₂ and CH₄ were recorded simultaneously. The stability of the active laser heterodyne system is analyzed using Allan variance analysis of long‐term observation data. The active near‐infrared laser heterodyne detection system demonstrated in this paper has great potential for the development of industrial parks' gas monitoring.

Programming rumen microbiome development in calves with the anti-methanogenic compound 3-NOP

The aim of this study was to establish a distinctive rumen microbial and fermentation profile using the anti-methanogenic compound 3-NOP to assess dam effect, and nutritional intervention of the juvenile offspring on microbial structure and function of rumen up to 12 months of age, once the treatment was withdrawn. Forty-eight pregnant heifers (H) and their future offspring (C) were allocated to either Control (-) or 3-NOP (+) treatment resulting in four experimental groups: H+/C+, H+/C-, H-/C + and H-/C-. Animals were treated from 6 weeks prior to calving until weaning, with the offspring monitored until 12 months of age. Rumen fluid samples and methane measurements using the Greenfeed system were collected during the trial. Results supported the mode of action of the compound, with a shift in fermentation from acetate to propionate, increases in branched chain fatty acids and formic acid in the 3-NOP treated animals. Similar shifts in microbial populations occurred in 3-NOP treated animals with lower abundances of rumen methanogen populations, increases of bacterial groups Succiniclasticum spp, Candidatus Saccharimonas. Fibrobacter and the families Prevotellaceae and Succinivibrioacea. and the protozoa Entodinium. Early life intervention had an enduring impact on the rumen microbial structure of young animals up to 28 weeks post weaning, however the effect was diminished once 3-NOP was withdrawn. Interestingly, a group of young animals emitted significantly less methane (15%) than the animals that did not receive the treatment during their juvenile stage. Our results suggest a higher resemblance of the young calf microbiome to a low methane adult and that early life colonisation of the rumen persists through to later life with the pre-weaning microbiome comprising ~ 65% of the yearling animal. Further research needs to be performed to determine the timing and dose of 3-NOP for new-born calves that can sustain a reduction in methane emissions after the treatment is withdrawn, under extensive grazing or controlled conditions.

An SPR-Based In Situ Methane Sensor for the Aqueous and Gas Phase.

This paper presents a fast, low-cost, precise methane sensor based on refractive index changes in a cryptophane A (CryptA)-doped polystyrene membrane. For the realization of this sensor, we built a surface plasmon resonance sensor with a refractive index resolution of 4.31 × 10-6 and investigated the optimal membrane thickness, i.e., a polymer layer of sufficient sensitivity with the lowest response time. For a membrane thickness of 760 nm, a limit of detection of 135 ppm and a response time constant of 45 s were found. Despite a comparable refractive index resolution and a higher CryptA content, the limit of detection is 3 orders of magnitude larger than that of a reported prototype. The sensor is capable of quantifying methane in the gas or aqueous phase. However, temperature, humidity, and ethanol vapor highly influence the signal. Although the principle of CryptA-based methane measurement is a promising, fast, and low-cost method, it will not be able to compete with state-of-the-art sensing in its current state.

Isotopic fractionation of methane on Mars via diffusive separation in the subsurface

Many processes have been identified in the Martian subsurface which may produce or release methane that eventually can be emitted into the atmosphere. Given the wide range of isotopic values for source carbon reported on Mars and the importance of atmospheric methane isotopologues as a tracer for subsurface processes, it is critical to quantify the level of isotopic fractionation that can occur during subsurface transport. On Earth, isotopic fractionation occurs when methane transport is dominated by Knudsen diffusion through small pores. However, unlike the Earth, on Mars the low atmospheric pressure and commensurate longer mean free path suggest that most subsurface transport of methane occurs in the Knudsen regime, amplifying this effect. Here, we report on simulations of diffusion through the martian subsurface and report on the level of fractionation that would be expected under two end-member scenarios. For Interplanetary Dust Particles (IDPs) incorporated in near-surface sediments in which methane is released quickly upon generation, atmospheric emissions of methane are expected to be representative of the reservoir isotopic ratio. However, for deeper sources in which methane accumulates as trapped gas, subsurface transport will result in depletions of 13CH4 compared to reservoir concentrations by approximately −31‰. Over time, both the reservoir and the emitted gas will evolve to become isotopically enriched in 13CH4 compared to a standard of constant isotopic ratio. This necessitates temporal measurements of emitted methane to understand the δ13C of the reservoir and depth of the release, preferably with hourly or better frequency. Finally, a seasonal cycle in δ13C with an amplitude of 5.3‰ is expected with adsorption acting to create small temporary reservoirs that are filled and emptied over the year by the subsurface thermal wave. This effect may provide a way to probe near-surface thermophysical properties.

63 Impacts of protein supplementation frequency on animal performance, rumen fermentation and methane emission from growing beef cattle

Abstract Nutrient supplementation is one of largest expenditure in forage-based beef production systems, especially when forage quality is poor or limited. Decreasing supplementation frequency may have a role in improving sustainability by increasing animal performance and minimizing cost of labor and fuel. This study evaluated the impacts of protein supplementation frequency (canola meal pellet; CMP) on animal performance, rumen fermentation, and enteric methane production from beef cattle fed forage-based diet. A total of 60 crossbred backgrounding steers [body weight (BW) = 278 ± 10 kg) was randomly assigned to one of the three treatments (n = 20/treatment): i) control (no CMP supplementation), ii) control + everyday CMP supplementation (0.83 kg/d per steer), and iii) control + every other day supplementation of CMP. The study was comprised of 21 d of adaptation followed by three 21-d periods, with enteric methane measured for 7 d per period. Animals were fed grass hay-based diets once a day at 0800 h and remained on their respective diets throughout the 63-d study. Diets were formulated considering animal BW, feed nutrient density and environmental condition in accordance with the National Academies of Sciences, Engineering and Medicine. Each treatment group was assigned to a pen, with the cattle and diets rotated among pens weekly to allow the animals to access the GreenFeed system stationed in one of the pens for enteric methane measurement. For measurement of rumen fermentation products, three ruminally canulated steers (BW = 350 ± 20 kg) were allocated to the three treatments using a 3 x 3 Latin Square Design with 21-d periods so that one animal received all the treatments over the three experimental periods. Animals were adapted to the treatments for 17 d and rumen samples were collected between d 19 and 21 at 0700 h, 1000h, 1300 h, 1600 h and 1900 h. Data were analyzed using the Mixed procedure of SAS. Relative to the control treatment (9.9 kg/d), DM intake was 4 to 5% greater (P < 0.001) following CMP supplementation regardless of supplementation frequency. Similarly, average daily gain was greater (7 to 11%, P = 0.01) for CPM supplemented treatments as compared with control (1.04 kg/d) irrespective of supplantation frequency. Rumen fermentation was affected by treatments. Total VFA concentration was greater (P = 0.01) for the every other day supplementation of CMP as compared with control and daily supplementation treatments. Conversely, rumen ammonia concentration was not affected by treatments. The control group had greater acetate and reduced propionate molar proportions that resulted in a 5 to 6% greater acetate:propionate ratio (P < 0.01) as compared with the CMP supplemented groups. Enteric methane production (g/d) was greater for the daily CMP supplementation (P = 0.02) while yield (g/kg daily weight gain) was not affected by treatment. Our results indicated that reduction of protein supplementation frequency improved animal performance without negatively impacting rumen fermentation.

372 What we have learned and are still learning about enteric methane emission measurements in extensive grazing environments

Abstract Across the Western U.S., beef cattle spend considerable time grazing extensive rangelands. Enteric methane (CH4) production in grazing systems represents more than 80% of the total enteric CH4 emissions. However, more measured CH4 data from cattle grazing extensive rangelands is needed to inform measurement, reporting, modeled emissions, and to identify mitigation opportunities. The availability of pasture-ready automatic head-chamber systems (AHCS; C-Lock Inc, Rapid City, South Dakota) has allowed the determination of emissions in rangelands. In this regard, different methods to ensure an accurate determination of enteric CH4 using this measurement technique have been evaluated in recent years. An initial step to obtaining accurate enteric emissions data is ensuring efforts secure adequate AHCS visitation. Investigations in small (< 99 ac) pastures have shown that ≥ 15 visits to ≥ 55 visits in feedlot pens are adequate for robust enteric CH4 production data. Here, our goal is to examine AHCS visitation outcomes to inform the use of this technique in extensive rangeland. For two grazing seasons at the USDA ARS Central Plains Experimental Range (CPER), we have studied enteric CH4 emissions from yearling steer herds ranging in size from 26 to 60 animals in continuously stocked rangeland (Table 1). After 30 d of acclimation in 2022, 46% of individuals continued using an AHCS until the end of the drought-shortened grazing season, totaling 60 d of constant AHCS exposure. In 2023, individuals were measured first at post-weaning, and those with ≥ 15 visits to an AHCS were stocked at CPER. These steers were previously exposed to an AHCS on average 69 d earlier (range: 28 to 118). Of these 60 individuals, 68% used the two available AHCS ≥ 15 times when grazing rangeland for 76 d, totaling 137 d of discontinuous AHCS exposure. While grazing, individual visits per season were reduced in 2022 and substantially greater in 2023. At this point in our enteric CH4 emission investigation, we learned that either exposing an individual multiple times to an AHCS after weaning or doubling the days of exposure in the acclimation phase increases visitation during the measurement phase by about 20% at the herd level and 450% on an individual basis. Insights learned on rangeland have uncovered several considerations for measuring enteric CH4 emissions in extensive environments: lengthy past exposure to AHCS is ideal for adequate visitation during the measurement phase and visitation of unacclimated individuals is unlikely during the measurement phase. Further work should determine the true number of individual visits required for accurate methane measurement in extensive rangelands and evaluate 1) efficacy of different acclimation practices, 2) continued use of previously exposed animals and temporal visitation decay, and 3) alternative placement of AHCS, and use of palatable attractants to increase AHCS visitation may improve measurement of enteric CH4 emissions.

Sward type alters enteric methane emissions, nitrogen output and the relative abundance of the rumen microbial ecosystem in sheep.

Observed improvements in animal and sward performance, coupled with a desire for more sustainable pasture-based feeding systems, has triggered a surge in the implementation of more botanically diverse pastures. However, thus far, there has been limited research investigating the effects of botanically diverse sward types on enteric methane (CH4) or nitrogen (N) excretion, alongside the ruminal microbiota and fermentation profile, in sheep. Hence, this study investigates the effect of sward type on CH4 production and N excretion, in addition to assessing the rumen microbiome, volatile fatty acid proportions, and ammonia nitrogen (NH3-N) concentration in sheep. A 5 × 5 Latin square design experiment was implemented to investigate 5 dietary treatments; perennial ryegrass (Lolium perenne L.; PRG) only or PRG plus white clover (Trifolium repens L.; PRG + WC), red clover (Trifolium pratense L.; PRG + RC), chicory (Chicorium intybus L.; PRG + Chic) or plantain (Plantago lanceolata L.; PRG + Plan). Diets were mixed at a ratio of 75% PRG and 25% of the respective companion forage and 100% PRG for the PRG treatment, on a dry matter basis. Twenty castrated male sheep were housed in metabolism crates across 5 feeding periods. Methane measurements were acquired utilizing portable accumulation chambers. Rumen fluid was harvested using a transoesophageal sampling device. Microbial rumen DNA was extracted and subjected to 16S rRNA amplicon sequencing and fermentation analysis. Data were analyzed using PROC MIXED in SAS. Results show that animals consuming PRG + WC ranked lower for CH4 production (g/d) than sheep offered PRG, PRG + Chic or PRG + Plan (P < 0.01) while the addition of any companion forage ranked CH4 yield (g/kg dry matter intake (DMI)) lower (P < 0.001) than PRG. There was a moderate positive correlation between DMI and CH4 (g/d; r = 0.51). Ruminal NH3-N was lowest in animals consuming the PRG diet (P < 0.01). There was a greater abundance of Methanobrevibacter and reduced abundance of Methanosphaera (P < 0.001) in sheep offered PRG, compared with any binary sward. On average, herb diets (PRG + Chic or PRG + Plan) reduced the urinary nitrogenconcentration of sheep by 34% in comparison to legume diets (PRG + WC or PRG + RC) and 13% relative to the PRG diet (P < 0.001). Sheep offered PRG + Chic had a greater dietary nitrogen use efficiency than PRG + RC (P < 0.05). This study demonstrates the potential for sward type to influence rumen function and the microbial community, along with CH4 and N output from sheep.

Natural Gas Leakage Ratio Determined from Flux Measurements of Methane in Urban Beijing

Natural Gas Leakage Ratio Determined from Flux Measurements of Methane in Urban Beijing

A Comprehensive Integration and Synthesis of Methane Emissions from Canada's Oil and Gas Value Chain.

Methane emissions from the global oil and gas value chain are a major contributor to climate change, and their mitigation could avoid 0.1 °C of warming by 2050. Here, we synthesize nearly a decade of research encompassing thousands of multiscale methane measurements along the oil and gas value chain (production to end use) to better constrain estimates of methane emissions from Canada's energy sector and to identify research gaps contributing to uncertainty in current estimates. We find that total value chain methane emissions are 2,600 (2,100-3,700) kt, which broadly agrees with Canada's latest official inventory that now includes atmospheric measurement data in some of their oil and gas methane estimates. Accurate understanding of emission magnitudes is critical because Canada committed to a 75% reduction of oil and gas methane emissions by 2030. We also identify and discuss information gaps in both emissions and activity data, namely, from the midstream, downstream, and end-use sectors. While they make up a smaller portion of the total inventory, accurate quantification of these emissions is still important and could point to more cost-effective mitigation solutions. This work emphasizes the need for frequent, comprehensive measurements to better constrain the climate impacts of the oil and gas sector and to validate reductions and commitments pledged by industry and governments.

Urban sources of methane characterised by long-term eddy covariance observations in central Europe

Multiyear eddy covariance measurements of methane and carbon dioxide were performed in Innsbruck, Austria, a mid-sized European city in the Alps. Annual mean methane and carbon dioxide fluxes were on the order of 21.6 nmol/m2/s and 11.7 μmol/m2/s respectively. Methane fluxes increased significantly with decreasing temperature and showed a negligible weekend to weekday effect. Accompanying non-methane volatile organic compound (NMVOC) measurements provided additional constraints on urban methane sources during an intensive 6-week campaign in 2021. Positive matrix factorization analysis identified a unique and dominant methane source. Contributions from biomass burning and vehicle emissions were found to be small. No evidence was found for a large unknown biogenic source. A second intensive campaign in 2023 revealed that the measured ethane to methane enhancement in turbulent plumes showed a typical ratio of 5.2 ± 0.6%, close to the unburned ratio of natural gas (5%) in Austria. The analysis suggests that urban methane fluxes are likely to be dominated by end-user releases rather than natural gas leaks in the pipeline system. Long-term eddy flux observations also allowed identifying the existence of urban super-emitters, which brought area weighted methane fluxes up to 39 nmol/m2/s in 2022. On average, the 100 y global warming potential of methane emitted by natural gas combustion activities is 6% relative to the total urban CO2 flux, and ∼12% relative to CO2 emissions from the residential, commercial and public sectors in Innsbruck.

Methodology and Uncertainty Analysis of Methane Flux Measurement for Small Sources Based on Unmanned Aerial Vehicles

The top–down emission rate retrieval algorithm (TERRA) method for calculating the net flux out of a box has been employed by other researchers to assess large sources of methane release. This usually requires a manned aircraft drone with powerful performance to fly over the boundary layer. Few studies have focused on low-altitude box sampling mass balance methods for small sources of methane release, such as at maximum flight altitudes of less than 100 m. The accuracy and sources of uncertainty in such a method still need to be determined as they differ from the conditions of large sources. Nineteen flights were conducted to detect methane emissions from Chinese oil field well sites using a measurement system consisting of a quadcopter and methane, wind speed, wind direction, air pressure, and temperature sensors. The accuracy and uncertainty of the method are discussed. The average absolute relative error of the measurement is 18.5%, with an average uncertainty of 55.75%. The uncertainty is mainly caused by the wind speed and direction, and the background CH4 concentration. The main paths to reduce uncertainty and improve accuracy for low-altitude box sampling include subtracting the background concentration during flux retrieval, enhancing the accuracy of methane measurements, selecting a period of downwind dominant or wind direction change of less than 30 degrees, and ensuring a maximum flight height greater than 50 m with a horizontal distance from the pollution source center of less than 75 m. The results show that TERRA-based low-altitude box sampling is suitable for quantifying methane release rates from small sources.

Simultaneous measurement of methane, propane and isobutane using a compact mid-infrared photoacoustic spectrophone

Hydrocarbon gas sensing is a challenging task using laser absorption spectroscopy due to the complex and broad structure of absorption lines. This application requires quick, accurate and highly sensitive detection of hydrocarbon gases concentrations. In this paper, a compact photoacoustic spectrophone was developed to simultaneously measure methane, propane and isobutane. This spectrophone uses wavelength modulation spectroscopy (WMS) with a single acoustic resonator and a single DFB laser emitting at 3368 nm, which greatly reduces the system complexity without using time-division multiplexing technology for multi-gas sensing. Due to the complex and broadband absorption of hydrocarbon gases, a novel signal processing method based on multilinear regression with Ridge regression (MLR-RG) is proposed to reduce the measurement error caused by the nonlinearity of spectra signal. For single gas measurement, the detection limits of methane, propane, and isobutane are determined to be 828 ppb, 419 ppb, and 619 ppb (SNR = 1, integration time = 20 s), respectively. For simultaneous multi-gas sensing in a gaseous mixture, the detection limits of propane and isobutane are determined to be 7 ppb, 68 ppb with an integration time of 860 s, 460 s, respectively. The measurement accuracy of propane and isobutane using MLR-RG is higher than that of ordinary least squares regression and partial least squares regression by 75% and 60%, respectively. The proposed algorithm based on MLR-RG provides a promising approach to process the broad overlapping absorption spectra for accurately retrieving hydrocarbon gases concentrations.

Mid-infrared methane standoff sensor using a frequency channel attention based convolutional neural network filter

Highly sensitive standoff methane detection is vital for atmospheric science, environmental protection, and production safety. We develop a mid-infrared methane standoff sensor using a cooperative target based on tunable diode laser absorption spectroscopy (TDLAS). To enhance sensor sensitivity, we propose a one-dimensional frequency channel attention-based convolutional neural network (1D-FCACNN) filter, which can effectively denoise the methane absorbance signals and its second harmonic signals. The filter model is adequately trained on a simulated spectrum dataset, which we constructed based on data augmentation. In comparison with reported filtering algorithms, the proposed filter shows the best performance in both measuring modes and evaluation metrics. Real-time measurements show that the measuring accuracy and limit of detection (LOD) of the proposed sensor reach a minimum of 30.40 ppb and 5.04 ppb over a 10-meter optical range, a significant improvement compared to previous reports of methane standoff sensors. The proposed methane standoff sensor proves the feasibility of enhancing the performance of TDLAS gas sensors with the attention mechanism, bringing a new option for high-sensitivity measurements of methane and other atmospheric trace gases.

Global atmospheric methane uptake by upland tree woody surfaces

Methane is an important greenhouse gas1, but the role of trees in the methane budget remains uncertain2. Although it has been shown that wetland and some upland trees can emit soil-derived methane at the stem base3,4, it has also been suggested that upland trees can serve as a net sink for atmospheric methane5,6. Here we examine in situ woody surface methane exchange of upland tropical, temperate and boreal forest trees. We find that methane uptake on woody surfaces, in particular at and above about 2 m above the forest floor, can dominate the net ecosystem contribution of trees, resulting in a net tree methane sink. Stable carbon isotope measurement of methane in woody surface chamber air and process-level investigations on extracted wood cores are consistent with methanotrophy, suggesting a microbially mediated drawdown of methane on and in tree woody surfaces and tissues. By applying terrestrial laser scanning-derived allometry to quantify global forest tree woody surface area, a preliminary first estimate suggests that trees may contribute 24.6–49.9 Tg of atmospheric methane uptake globally. Our findings indicate that the climate benefits of tropical and temperate forest protection and reforestation may be greater than previously assumed.

Methane measurement method based on F-P angle-dependent correlation spectroscopy

This study explores a gas measurement method based on Fabry-Perot (F-P) angle-dependent correlated spectroscopy, which achieves highly sensitive and selective gas measurements by adjusting the angle to match the F-P interference peak with the gas absorption peak. Methane (CH4) is the chosen target gas, and an F-P etalon is designed with parameters matching the CH4 absorption peak. An angle-scanning measurement system is established to enable correlated spectroscopic detection of CH4 gas. Angle-scanning measurements reveal distinct absorption signals at the angle where the F-P interference peak aligns with the CH4 absorption peak. Gas measurements of standard samples demonstrate a linear relationship between the apparent absorbance at the on/off positions and CH4 concentration, allowing for accurate CH4 concentration measurements. The study further investigates the detection limit of the experimental system, achieving a 3σ detection limit of 720 ppm under the on/off measurement mode. A conical incidence model is developed to analyze the impact of beam divergence angles on the transmittance of the F-P cavity. Simulations are conducted to assess absorption signals in the presence of extreme cross-interference, demonstrating the method's robust resistance to cross-interference. The F-P correlated spectroscopy method described in this paper, as a non-dispersive spectroscopic measurement technique, holds promise for designing high-sensitivity gas sensors and imaging applications.

Real-time breath gas analysis of methane using a multipass cell-based near-infrared gas sensor.

We demonstrated a near-infrared exhaled breath sensor for real-time methane measurements by using tunable diode laser absorption spectroscopy (TDLAS), which can enable the noninvasive diagnosis of intestinal tract problems. The core component of the near-infrared TDLAS sensor is a two-mirror-based multipass cell with nine-circle patterns. An optical path length of 23.4 m was achieved in a volume of 233.3 cm3, which effectively improved the detection sensitivity and shortened the gas exchange time. The minimum detection limit was 0.37 ppm by applying wavelength modulation spectroscopy, which was 12.4 times greater than that of direct absorption spectroscopy. In addition, combined with wavelength modulation spectroscopy, the two-mirror-based multipass cell enabled sub-second gas exchange time of 0.6 s. Methane breath experiments were conducted with six volunteers, and the real-time measurement results and concentrations at the end of exhalation were analyzed. This study demonstrates that the developed sensor has high sensitivity, high selectivity, and fast response for breath methane measurements and has promising potential for noninvasive, real-time, and point-of-care disease diagnosis in clinical applications.

Measurement-based carbon intensity of US offshore oil and gas production

The United States (US) produces oil and gas from six offshore regions: the North Slope of Alaska, Cook Inlet in Alaska, offshore California, and three Gulf of Mexico (GOM) sub-regions: state shallow, federal shallow, and deep waters. Measurement-based assessment of direct greenhouse gas emissions from this production can provide real-world information on carbon emissions to inform decisions on current and future production. In evaluating the climate impact of production, the carbon intensity (CI, the ratio of greenhouse gases emitted compared to the energy of fuels produced) is often used, though it is rarely quantified with measurements. Here, we complete an observational evaluation of the US offshore sector and present the largest current set of measurement-based CIs. We collected airborne measurements of methane, carbon dioxide, and nitrogen oxides from the North Slope, Cook Inlet, and California and combined with prior GOM results. For Alaska and California, we found emissions agree with facility-level inventories, however, the inventories miss some facilities. The US offshore CI, on a 100 year GWP basis, is 5.7 g CO2e/MJ[4.5, 6.8, 95% confidence interval]. This is greater than double the CI based on the national US inventory, with the discrepancy attributed primarily to methane emissions from GOM shallow waters, with a methane dominated CI of 16[12, 22] for GOM federal shallow waters and 43[25–65] for state shallow waters. Regional intensities vary, with carbon dioxide emissions largely responsible for CI on the North Slope 11[7.5, 15], in Cook Inlet 22[13, 34], offshore California 7.2[3.2, 13], and in GOM deep waters 1.1[1.0, 1.1]. These observations indicate offshore operations outside of the GOM in the US have modest methane emissions, but the CI can still be elevated due to direct carbon dioxide emissions. Accurate assessment of different offshore basins, with differing characteristics and practices, is important for the climate considerations of expanded production.

Integrated microcontroller mq sensors for monitoring biogas: Advancements in methane and hydrogen sulfide detection

Recent technological advances in microcontroller systems enable novel biogas monitoring capabilities. This study investigates microcontroller-based quantification of methane and hydrogen sulfide concentrations in biogas derived from anaerobic digestion. Anaerobic digesters were fed either 100% cow dung substrates or a 50:50 mixture of cow dung with municipal solid waste (MSW). Methane levels were monitored using an MQ-4 sensor, hydrogen sulfide via an MQ-136 sensor, and temperature with a K-type thermocouple, all integrated with an ATmega 2560 microcontroller system. The 100% cow dung digester produced biogas with maximum methane concentrations of 3488 ppm at 21 days, indicating improved methane production compared to the 50:50 mixture of cow dung with MSW. Hydrogen sulfide reached 195 ppm and 192 ppm for the 100% cow dung and mixed digesters. Mesophilic temperature conditions were maintained throughout the digestion process. Real-time quantification of biogas composition demonstrates the capabilities of microcontroller-based anaerobic digester monitoring to provide precise methane and hydrogen sulfide measurements.

Developing a ‘fit for purpose’ approach to measuring methane emissions

Tackling methane emissions from fossil fuel operations represents one of the best near- and medium-term opportunities for limiting the effects of climate change. Over the last few years, independent methane studies have challenged the accuracy and completeness of publicly disclosed emissions estimates. To address this, new methane accounting and reporting frameworks have been developed. Central to these frameworks are key principles linked to measurement, monitoring, reporting, verification (MMRV) and reduction. Woodside has taken specific actions to measure and reduce its methane emissions and is developing a pathway to embed ongoing and sustainable measurements technologies in its operations. Previously, Woodside discussed the management and valuation of methane reductions, this paper will describe the approach taken to develop methane measurement plans including (i) the objective of measurement plans, (ii) measurement technology attributes and (iii) the identification of measurement technology use cases. It also overviews measurement techniques such as satellite, aerial, drone, handheld and continuous monitoring which can form part of a curated multi-scale approach to MMRV across a portfolio of assets.

Automatic detection of methane emissions in multispectral satellite imagery using a vision transformer

Curbing methane emissions is among the most effective actions that can be taken to slow down global warming. However, monitoring emissions remains challenging, as detection methods have a limited quantification completeness due to trade-offs that have to be made between coverage, resolution, and detection accuracy. Here we show that deep learning can overcome the trade-off in terms of spectral resolution that comes with multi-spectral satellite data, resulting in a methane detection tool with global coverage and high temporal and spatial resolution. We compare our detections with airborne methane measurement campaigns, which suggests that our method can detect methane point sources in Sentinel-2 data down to plumes of 0.01 km2, corresponding to 200 to 300 kg CH4 h−1 sources. Our model shows an order of magnitude improvement over the state-of-the-art, providing a significant step towards the automated, high resolution detection of methane emissions at a global scale, every few days.