Measurements Of Methane Emissions Research Articles

A satellite constellation dedicated to frequently monitor methane emissions from oil and gas facilities around the world

This paper discusses GHGSat’s pioneering operating satellites dedicated to high-resolution measurements of methane emissions. We demonstrate their role as an integral part of an emissions intensity improvement strategy. The instrument on board each satellite uses spectroscopy principles to detect and quantify methane emissions, exhibiting a spatial resolution of less than 30 m. A discussion on how this constellation can be used as a key system in the mitigation of emissions is presented. Results reflect observations taken with GHGSat’s satellites. Recent examples of oil and gas emitting facilities around the world are shown followed by how this constellation can serve three objectives: (1) emissions mitigation; (2) regulatory compliance; and (3) a system to achieve voluntary efforts such as OGMP 2.0. The intention is to show that there isn’t a one-size-fits-all solution, but that the use of a satellite constellation is a complimentary and efficient way of monitoring for large leaks with increased frequency. This paper also reviews GHGSat’s top-down approach through its aircraft sensor technology as another solution for monitoring smaller leaks. Mitigation success stories are discussed providing opportunities for achievement of regulatory certifications in regions like the United States, Australia and Iraq. The resulting datasets are integrated into GHGSat’s ESRI ArcGIS-based portal, SPECTRA, to facilitate the interpretation of its high-resolution measurements, giving further insights through the available analytics layers. This platform provides situational awareness of methane emissions to operators, creating opportunities for mitigation.

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.

9 Use of new technology to measure methane emissions

Abstract Over recent decades, the impact of human-induced climate change and the role of ruminant agriculture has been of growing concern for both the public and the scientific community. This has led to rapid advancements in technology needed to measure methane emissions accurately and precisely. Primarily, these advancements have been focused on measurements of enteric methane, with the proliferation of GreenFeed emission measurement systems (GEM; C-Lock, Inc; Rapid City, SD) being utilized by animal scientists across the world. The GEM relies on spot measurements collected in a portable head-box, either in a freestall or on a trailer. The GEM uses bait feed to entice animals to place their head into the head-box to collect measurements. Use of respiration chambers or head-boxes are still considered the “gold standard”, but the GEM allows for quantification in production environments and with greater number of animals. While enteric emissions are the primary source of methane from ruminant agriculture, manure methane emissions account for 15.8% of direct emissions from cattle in the U.S. This emission source is a significant contributor to confined feeding operations’ greenhouse gas emissions (GHG), where consolidation and changes in manure handling practices have occurred over the last several decades. From 2010 to 2020, manure methane emissions were a larger contributor to climate warming than enteric methane (90.8 MMT CO2-we vs. 89.2 MMT CO2-we, respectively) when calculated using the new GWP* metric. However, few advancements have been made in quantifying emissions from manure, with the cost-effective static chamber methodology still widely used. This technique allows for the determination of temporal gas concentration change in a known volume of air with a PVC cylinder, inserted 5-10 cm in the soil and posteriorly closed with a PVC lid to generate “known volume” headspace. However, this method does have known limitations on spatial and temporal flux calculations. These limitations include: the PVC chamber may alter the soil microenvironment thereby altering soil GHG flux estimates; they have potential for technician bias; and are short term monitoring, limiting interpretations to that snapshot in time and making comparisons across experiments difficult. Differing measuring techniques, such as eddy covariance and dual-comb, that more accurately and precisely monitor the soil-atmosphere interface may help better understand gas fluxes from livestock systems. Key Word: cattle, enteric, manure, methane

Подземные источники балки Пещерная озера Баскунчак: гидрохимические особенности и эмиссия парниковых газов

For the first time, full-scale measurements of methane and carbon dioxide emissions by the chamber method were carried out in summer for groundwater sources discharged in the valley of the Peshernaya Gulch creek, located in the north-west of Lake Baskunchak. pH values, concentrations of CH4, basic ions, gross Fe and Mn were determined in the water of the sources; concentrations of CH4, H2S, organic matter, Eh and pH values, density and humidity were determined in various layers of bottom sediments (up to 27 cm). A detailed description of the identified groundwater sources was carried out, their primary morphometric and morphological characteristics were measured, as well as the flow rate. It was found that more than 10 ascending karst sources of groundwater are discharged in the Peshchernaya beam, 5 of which were active during the research period and mainly confined to the left screw of the beam. The active sources of the left screw of the beam are characterized by a small flow rate and are sodium chloride brines with a mineralization of 93.9–107.1 g/l. The bottom sediments accumulating in the sinkholes of underground sources are characterized by a neutral acid-base environment and restorative conditions. The concentrations of CH4 and ∑H2S in the sediments of the sources varied, respectively, in the range of 0.08–0.77 µg/g vl.o. and 0.023–2.63 mg/g vl.o. with minimal values for both gases in the lower less reduced layer with a low content of Sorg. The concentration of methane in the water of active sources varied from 26.3 up to 38.4 µl/l and was on average 2 times higher than in the waters of a stream fed by them and an inactive source. The specific methane flux from the water surface of active sources varied in the range of 0.6–1.5 mg/(m2∙h), which is 2 orders of magnitude lower than the specific CO2 flux of 46.4–106.1 mg/(m2∙h). The isotopic composition of carbon (δ13C) CH4 and CO2 measured in gas bubbles rising from the bottom of one of the ascending sources indicates the modern biochemical genesis of these greenhouse gases.

Analyses of plasma metabolites using a high performance four-channel CIL LC-MS method and identification of metabolites associated with enteric methane emissions in beef cattle.

Reducing enteric methane (one greenhouse gas) emissions from beef cattle not only can be beneficial in reducing global warming, but also improve efficiency of nutrient utilization in the production system. However, direct measurement of enteric methane emissions on individual cattle is difficult and expensive. The objective of this study was to detect plasma metabolites that are associated with enteric methane emissions in beef cattle. Average enteric methane emissions (CH4) per day (AVG_DAILYCH4) for each individual cattle were measured using the GreenFeed emission monitoring (GEM) unit system, and beef cattle with divergent AVG_DAILYCH4 from Angus (n = 10 for the low CH4 group and 9 for the high CH4 group), Charolais (n = 10 for low and 10 for = high), and Kinsella Composite (n = 10 for low and 10 for high) populations were used for plasma metabolite quantification and metabolite-CH4 association analyses. Blood samples of these cattle were collected near the end of the GEM system tests and a high performance four-channel chemical isotope labeling (CIL) liquid chromatography (LC) mass spectrometer (MS) method was applied to identify and quantify concentrations of metabolites. The four-channel CIL LC-MS method detected 4235 metabolites, of which 1105 were found to be significantly associated with AVG_DAILYCH4 by a t-test, while 1305 were significantly associated with AVG_DAILYCH4 by a regression analysis at p<0.05. Both the results of the t-test and regression analysis revealed that metabolites that were associated with enteric methane emissions in beef cattle were largely breed-specific whereas 4.29% to 6.39% CH4 associated metabolites were common across the three breed populations and 11.07% to 19.08% were common between two breed populations. Pathway analyses of the CH4 associated metabolites identified top enriched molecular processes for each breed population, including arginine and proline metabolism, arginine biosynthesis, butanoate metabolism, and glutathione metabolism for Angus; beta-alanine metabolism, pyruvate metabolism, glycolysis / gluconeogenesis, and citrate cycle (TCA cycle) for Charolais; phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism, arginine biosynthesis, and arginine and proline metabolism for Kinsella Composite. The detected CH4 associated metabolites and enriched molecular processes will help understand biological mechanisms of enteric methane emissions in beef cattle. The detected CH4 associated plasma metabolites will also provide valuable resources to further characterize the metabolites and verify their utility as biomarkers for selection of cattle with reduced methane emissions.

ENTERIC METHANE PRODUCTION IN RUMINANTS: ITS EFFECT ON GLOBAL WARMING AND MITIGATION STRATEGIES-A REVIEW

Anthropic activities produce around 2/3 share of the total methane emission in the world, with the livestock sector being the primary contributor. Methane is a potent greenhouse gas, exhibiting a warming effect more than 21 times that of carbon dioxide, and is produced by microbes called methanogens during anaerobic fermentation. The release of methane from ruminants indicating a loss of feed energy that has the potential to elevate production. Economic and population growth will increase milk and meat demand, increasing CH4 production from the livestock sector. Various approaches including feed manipulation, supplementation of feed additives, management practices, genetic selection and vaccinations all were aimed at mitigating CH4 from the livestock sector. These measures change the composition of rumen and alter the working of methane-producing microbes. The addition of feed additives reduces the CH4 emission but human well-being limits their usage. Methane inhibitors, like those with a hydrogen sink property that has no adverse effects on rumen microbe populations, are considered ideal for reducing emissions. Research also shows that methane emission is a heritable and repeatable trait and that genomic and genetic traits present a considerable opportunity to minimize methane emissions from ruminants the accuracy of methane measurements is crucial and attention to background information in publications regarding measurement context and methods is necessary for comprehensive interpretation of results. Each method for measuring methane emissions from livestock has limitations tied to its original intent of use. Standardization within and between techniques, especially in respiration chambers, SF6 and Greenfeed Emission Monitoring System, can enhance result reliability. However, using these technologies beyond their intended purpose is risky, and extrapolating estimations may lead to unintended consequences. Combining different methods may offer the most comprehensive approach, but further research is needed to validate and compare individual methods, especially in wide-ranging production systems and to develop standardization protocols.

Onshore methane emissions measurements from the oil and gas industry: a scoping review

Abstract Research on methane (CH4) emissions from the oil and gas (O&amp;G) industry informs policies, regulations, and international initiatives that target reductions. However, there has been little integration and synthesis of the literature to document the state of knowledge, identify gaps, and determine key insights that can guide research priorities and mitigation. To address this, we performed a scoping review of 237 English-language peer-reviewed articles on CH4 emissions from onshore O&amp;G sources, charting data on five research themes: publication trends, geography, measurement levels and methods, emissions sources, and emissions rates. Almost all articles (98%) were published between 2012 and 2022 with an increasing publication rate, indicating a nascent and evolving understanding of the science. Most articles (72%) focused on CH4 emissions from the U.S. O&amp;G industry and were written by U.S.-based authors (69%), while other major O&amp;G-producing countries like Saudi Arabia, Russia, and China were under-represented. Upstream was the most frequently studied supply chain segment, where U.S.-focused articles accounted for 75% of the research. Nearly half the articles (43%) included in the review reported site-level measurements, limiting the identification of equipment- and component-level emissions sources and root cause. Articles that measured or identified equipment-level sources (18%) noted high emissions from tanks, unlit flares, and compressors. The most common stand-off measurement platforms were vehicles and aircraft, while the use of satellites increased in articles published since 2019. Reported emissions profiles were consistently heavy-tailed and indicate method-based and geographic differences in magnitude and skew. All articles (n = 26) that compared inventory- to measurement-based estimates of emissions found large discrepancies in that inventories under-estimated the latter by a factor of 1.2–10 times. We recommend future research focus on: (i) field-based emissions studies for under-represented regions and source categories, (ii) identifying root causes and linking measurements to mitigation, and (iii) multi-level measurement integration.

A low-methane rice with high-yield potential realized via optimized carbon partitioning

Global rice cultivation significantly contributes to anthropogenic methane emissions. The methane emissions are caused by methane-producing microorganisms (methanogenic archaea) that are favoured by the anoxic conditions of paddy soils and small carbon molecules released from rice roots. However, different rice cultivars are associated with differences in methane emission rates suggesting that there is a considerable natural variation in this trait. Starting from the hypothesis that sugar allocation within a plant is an important factor influencing both yields and methane emissions, the aim of this study was to produce high-yielding rice lines associated with low methane emissions. In this study, the offspring (here termed progeny lines) of crosses between a newly characterized low-methane rice variety, Heijing 5, and three high-yielding elite varieties, Xiushui, Huayu and Jiahua, were selected for combined low-methane and high-yield properties. Analyses of total organic carbon and carbohydrates showed that the progeny lines stored more carbon in above-ground tissues than the maternal elite varieties. Also, metabolomic analysis of rhizospheric soil surrounding the progeny lines showed reduced levels of glucose and other carbohydrates. The carbon allocation, from roots to shoots, was further supported by a transcriptome analysis using massively parallel sequencing of mRNAs that demonstrated elevated expression of the sugar transporters SUT-C and SWEET in the progeny lines as compared to the parental varieties. Furthermore, measurement of methane emissions from plants, grown in greenhouse as well as outdoor rice paddies, showed a reduction in methane emissions by approximately 70 % in the progeny lines compared to the maternal elite varieties. Taken together, we report here on three independent low-methane-emission rice lines with high yield potential. We also provide a first molecular characterisation of the progeny lines that can serve as a foundation for further studies of candidate genes involved in sugar allocation and reduced methane emissions from rice cultivation.

Measurements of Methane Emissions from a Biofertilizer Storage Tank Using Ground-Based Hyperspectral Imaging and Flux Chambers.

Open storages of organic material represent potentially large sources of the greenhouse gas methane (CH4), an emissions source that will likely become more common as a part of societal efforts toward sustainability. Hence, monitoring and minimizing CH4 emissions from such facilities are key, but effective assessment of emissions without disturbing the flux is challenging. We demonstrate the capacity of using a novel high-resolution hyperspectral camera to perform sensitive CH4 flux assessments at such facilities, using as a test case a biofertilizer storage tank for residual material from a biogas plant. The camera and simultaneous conventional flux chamber measurements showed emissions of 6.0 ± 1.3 and 13 ± 5.7 kg of CH4 h-1, respectively. The camera measurements covered the whole tank surface of 1104 m2, and the chamber results were extrapolated from measurements over 5 m2. This corresponds to 0.7-1.4% of the total CH4 production at the biogas plant (1330 N m3 h-1 corresponding to 950 kg h-1). The camera could assess the entire tank emission in minutes without disturbing normal operations at the plant and revealed additional unknown emissions from the inlet to the tank (17 g of CH4 h-1) and during the loading of the biofertilizer into trucks (3.1 kg of CH4 h-1 during loading events). This study illustrates the importance of adequate measurement capacity to map methane fluxes and to verify that methane emission mitigation efforts are effective. Given the high methane emissions observed, it is important to reduce methane emissions from open storage of organic material, for example by improved digestion in the biogas reactor, precooling of sludge before storage, or building gastight storage tanks with sealed covers. We conclude that hyperspectral, ground-based remote sensing is a promising approach for greenhouse gas monitoring and mitigation.

Landfill gas collection efficiency: Categorization of data from existing in-situ measurements

Landfill methane emissions are commonly estimated using cover-type dependent default collection efficiency values, with a first-order decay model or measured gas collection. Current default collection efficiencies used in the United States were predominately derived from 4 studies conducted during or prior to 2007 that relied on flux chambers. Flux chambers are limited by small sample sizes, placement restrictions, and the inability to measure emissions from gas or leachate collection systems. Since 2007, over 14 new studies have been completed using more advanced technologies that allow for direct measurement of methane plumes from most or all of a landfill’s surface. On average, these measurements are 2–3 times greater than emissions predicted by current models and collection efficiency defaults. In lieu of measuring emissions from all landfills, updating collection efficiency defaults can bring modeled emissions into better alignment with measurements. To this end, collection efficiency estimates derived from measured data were categorized into cover types and then adjusted to account for cases where whole plume measurement was an amalgamation of multiple cover types. The resultant adjusted default values were 41% for daily cover, 69% for intermediate cover, and 71% for final cover. Direct measurement of landfill methane emissions is preferrable to account for the full range of variables driving landfill emissions, including collection system design and operation. However, applying these updated defaults back into the landfill emission models eliminates underprediction of landfill emissions for the dataset reviewed, and would provide a more accurate estimate of landfill gas emissions where measurements are unavailable.

The first data on the concentration and emission of methane and carbon dioxide in the underground sources of the Peshernaya beam of Lake Baskunchak

For the first time, full-scale measurements of methane and carbon dioxide emissions by the chamber method were carried out in summer for groundwater sources discharged in the valley of the creek of the Peshernaya beam, located in the north-west of Lake Baskunchak. The values of pH, temperature, concentration of basic ions and methane were determined in the water of the sources. A detailed description of the identified groundwater sources was carried out, their primary morphometric and morphological characteristics were measured, as well as the flow rate. It has been established that more than ten ascending karst groundwater sources are discharged in the Peshernaya gully, five of which were active during the research period and were mainly confined to the left branch of the gully. The active sources of the left side of the beam are characterized by a small flow rate and are sodium chloride brines with a mineralization of 93.9–107.1 g/l. The concentration of methane in the water of active sources varied between 26.3–38.4 µl/l and was on average more than 2 times higher than in the waters of the stream fed by them and an inactive source. The specific flow of methane from the water surface of active sources varied in the range of 0.6–1.5 mg/(m2·hour), which is 2 orders of magnitude lower than the specific flow of CO2, which is 46.4–106.1 mg/(m2·hour).

Assessment of methane emissions from pressure regulation stations in China

Pressure regulation stations are responsible for transporting natural gas downstream and are an indispensable part of the gas supply chain. In recent years, countries and enterprises have attached increasing importance to methane emission accounting. However, methane emissions from pressure regulation stations are still not comprehensively understood and accounted for. In this study, methane emissions from 21 pressure regulation stations under normal conditions were quantified using the Environmental Protection Agency's (EPA's) “Other Test Method 33 A” (OTM 33 A) in three regions of China: the eastern, northern, and central regions of China. The results showed that the emission rate from pressure regulation stations generally lied in the order of 10−1-10−3 kg/h, whereas the measured methane emission rate (MMER) with 95% confidence interval (95%CI) was 0.671 (0.066, 3.040) (kg/h), which was determined from the bootstrapping measurements from all pressure regulation stations. The MMER (95%CI) values were 0.051 (0.026, 0.102) for East China, 2.263 (0.095, 8.317) for North China, and 0.004 (0.003, 0.005) (kg/h) for Central China, showing a relatively obvious skewed distribution. Overall, MMER had a diminutive correlation with gas throughput and pipeline pressure. In contrast, the degree of correlation of pipeline pressure was higher than that of gas throughput.

Direct measurements of methane emissions from key facilities in Alberta's oil and gas supply chain

The Canadian government aims to achieve a 40–45 % reduction of oil and gas (O&G) methane (CH4) emissions by 2025, and 75 % by 2030, although recent studies consistently show that Canada's federal inventory underestimates emissions by a factor of 1.4 to 2.0. We conducted aerial mass balance measurements at sixteen upstream O&G facilities in Alberta between September 29 and November 6, 2021, and our measurements revealed that emissions were, on average, 1.7 (standard deviation (SD): 0.6) times higher than the reported emissions for the same year. On a subsequent campaign from August 12 to September 27, 2022, we focused on understudied O&G sectors covering 24 midstream and end-use facilities. These sites were found to be emitting, on average, 3.4 (SD: 1.1) times more CH4 than reported. By extrapolating our measurements to Alberta, we found that underground gas storage contributed to 1.6 % of provincial O&G emissions, followed by natural gas power stations/refineries less than 1.0 %. The widespread underreporting of CH4 emissions highlights the necessity for more empirical measurements of midstream and end-use facilities.

A simple method to measure methane emissions from indoor gas leaks.

From wellhead to burner tip, each component of the natural gas process chain has come under increased scrutiny for the presence and magnitude of methane leaks, because of the large global warming potential of methane. Top-down measures of methane emissions in urban areas are significantly greater than bottom-up estimates. Recent research suggests this disparity might in part be explained by gas leaks from one of the least understood parts of the process chain: behind the gas meter in homes and buildings. However, little research has been performed in this area and few methods and data sets exist to measure or estimate them. We develop and test a simple and widely deployable closed chamber method that can be used for quantifying indoor methane emissions with an order-of-magnitude precision which allows for screening of indoor large volume ("super-emitting") leaks. We also perform test applications of the method finding indoor leaks in 90% of the 20 Greater Boston buildings studied and indoor methane emissions between 0.02-0.51 ft3 CH4 day-1 (0.4-10.3 g CH4 day-1) with a mean of 0.14 ft3 CH4 day-1 (2.8 g CH4 day-1). Our method provides a relatively simple way to scale up indoor methane emissions data collection. Increased data may reduce uncertainty in bottom-up inventories, and can be used to find super-emitting indoor emissions which may better explain the disparity between top-down and bottom-up post-meter emissions estimates.

Methane Emissions from Abandoned Oil and Gas Wells in Alberta and Saskatchewan, Canada: The Role of Surface Casing Vent Flows.

Abandoned oil and gas wells can act as leakage pathways for methane, a potent greenhouse gas, and other fluids to migrate through the subsurface and to the atmosphere. National estimates of methane emissions remain highly uncertain, and available measurements do not provide details on whether the emissions are associated with well integrity failure (indicating subsurface leaks) or aboveground well infrastructure leaks. Therefore, we directly measured methane emission rates from 238 unplugged and plugged abandoned wells across Alberta and Saskatchewan, Canada, separately quantified emissions from surface casing vents and other emissions from the wellhead (non-surface casing vent), and developed emission factors to estimate Canada-wide emissions from abandoned wells. Our highest measured emission rate (5.2 × 106 mg CH4/hr) from an unplugged gas well was two to three times higher than the largest previously published emission rate from an abandoned well. We estimated methane emissions from abandoned wells in Canada to be 85-93 kilotonnes of methane per year, of which surface casing vent emissions represented 75-82% (70 kilotonnes of methane per year). We found that subsurface leaks, as evidenced by surface casing vent flows, occurred at 32% of abandoned wells in Alberta, substantially higher than previously estimated using provincial data alone (6 and 11%). Therefore, well integrity failures and groundwater contamination are likely to be more common than previous studies suggest.

Uncertainty Quantification of Methods Used to Measure Methane Emissions of 1 g CH4 h-1.

The recent interest in measuring methane (CH4) emissions from abandoned oil and gas wells has resulted in five methods being typically used. In line with the US Federal Orphaned Wells Program's (FOWP) guidelines and the American Carbon Registry's (ACR) protocols, quantification methods must be able to measure minimum emissions of 1 g of CH4 h-1 to within ±20%. To investigate if the methods meet the required standard, dynamic chambers, a Hi-Flow (HF) sampler, and a Gaussian plume (GP)-based approach were all used to quantify a controlled emission (Qav; g h-1) of 1 g of CH4 h-1. After triplicate experiments, the average accuracy (Ar; %) and the upper (Uu; %) and lower (Ul; %) uncertainty bounds of all methods were calculated. Two dynamic chambers were used, one following the ACR guidelines, and a second "mobile" chamber made from lightweight materials that could be constructed around a source of emission on a well head. The average emission calculated from the measurements made using the dynamic chamber (Qav = 1.01 g CH4 h-1, Ar = +0.9%), the mobile chamber (Qav = 0.99 g CH4 h-1, Ar = -1.4%), the GP approach (Qav = 0.97 g CH4 h-1, Ar = -2.6%), and the HF sampler (Qav = 1.02 g CH4 h-1, Ar = +2.2%) were all within ±3% of 1 g of CH4 h-1 and met the requirements of the FOWP and ACR protocols. The results also suggest that the individual measurements made using the dynamic chamber can quantify emissions of 1 g of CH4 h-1 to within ±6% irrespective of the design (material, number of parts, geometrical shape, and hose length), and changes to the construction or material specifications as defined via ACR make no discernible difference to the quantification uncertainty. Our tests show that a collapsible chamber can be easily constructed around the emission source on an abandoned well and be used to quantify emissions from abandoned wells in remote areas. To our knowledge, this is the first time that methods for measuring the CH4 emissions of 1 g of CH4 h-1 have been quantitively assessed against a known reference source and against each other.

A note on dairy cow behavior when measuring enteric methane emissions with the GreenFeed emission monitoring system in tie-stalls

Changes in the environment or novel procedures can result in altered cow behavior during data collection; training is often recommended to ensure accurate data is being recorded. Currently, there is little knowledge regarding the habituation of dairy cows during methane emission testing with the GreenFeed emission monitoring system (C-Lock Inc., Rapid City, SD, USA), or how behavior relates to enteric methane emission measurements. Methane emissions were estimated from a total of 202 Holstein dairy cows (120–150 d in milk) housed in tie-stalls as part of a larger project. Cows were tested on Day 0 (training day) and Day 1–5 (test day) for approximately 10 min, during which behavior was recorded by a trained observer. While cows spent more time with their head outside of the machine on the training day (Day 0) than during the test days (Day 1–5), the opposite pattern was observed for the number of leg movements. No differences in estimated methane production were found over the different days, though it was negatively correlated to both behaviors. These results highlight the importance of habituation of dairy cows to the GreenFeed system for methane measurements to minimize changes to cow behavior under tie-stall conditions, while the methane emissions themselves are less affected. However, further research is needed to determine the impact of cow behavior on the reliability and repeatability of methane emission measurements as it may introduce bias in genetic evaluations for methane efficiency.

A novel approach for anomaly detection in dairy cow gas emission records

Mitigating the considerable contribution of ruminant livestock to global methane emissions, which accounts for 17%, is of vital importance. One significant approach to this is the genetic selection of cows for reduced methane emissions, a strategy that demands large-scale, accurate methane emission measurements from individual cows in commercial farms. The existing ‘sniffer’ technique, which obtains samples of the air near the cow’s nostrils through a tube fixed in the feed bin within an automated milking system (AMS), presents challenges due to the cow’s head movements during the milking recording, creating anomalies in the gas emission data. Moreover, correcting these anomalies directly remains a pressing issue. This study presents a novel data mining approach for detecting anomalous by approximating the cow head position using CO2 time series data collected from cows. The data was collected using sniffer machines on two dairy cattle farms and analyzed using a data-decomposition approach. The performance of the proposed method was evaluated using probabilistic methods such as the Kolmogorov–Smirnov (KS) test and confusion matrix. Results showed that the proposed method was able to accurately detect anomalous peaks in the synthetic CO2 time series, with more than 95% of anomalous peaks being detected. This study demonstrates the potential of the proposed method to improve the accuracy of methane emissions estimates from cows and the understanding of cows’ behavior. To further validate the effectiveness of the proposed method, it was tested on the gas emission dataset recorded by GreenFeed (C-LockTM), which contains various CO2 time series with annotated anomalous points. The validation results demonstrated that the method successfully detected more than 90% of the anomalous points in the time series while marking the peaks containing the anomalous data points. This approach proved to be efficient and accurate, as the peaks represent regions of high anomaly concentration and are more likely to contain true anomalies.

Pig slurry organic matter transformation and methanogenesis at ambient storage temperatures.

Manure management is a significant source of global methane emissions, and there is an increased interest in understanding and predicting emissions. The hydrolysis rate of manure organic matter is critical for understanding and predicting methane emissions. We estimated hydrolysis rate constants of crude protein, fibers, and lipids and used the Arrhenius equation to describe its dependency on temperature. Simultaneously, measurements of methane emission, 13/12 C isotope ratios, and methanogen community were conducted. This was achieved by incubating fresh pig manure without inoculum at 10°C, 15°C, 20°C, and 25°C for 85 days in a lab-scale setup. Hydrolysis of hemicellulose and cellulose increased more with temperature than crude protein, but still, hydrolysis rate of crude protein was highest at all temperatures. Results suggested that crude protein consisted of multiple substrate groups displaying large differences in degradability. Lipids and lignin were not hydrolyzed during incubations. Cumulative methane emissions were 7.13±2.69, 24.6±8.00, 66.7±4.8, and 105.7±7.14 gCH4 kgVS -1 at 10°C, 15°C, 20°C, and 25°C, respectively, and methanogenic community shifted from Methanosphaera toward Methanocorpusculum over time and more quickly at higher temperatures. This study provides important parameter estimates and dependencies on temperature, which is important in mechanistic methane emission models. Further work should focus on characterizing quickly degradable substrate pools in the manure organic matter as they might be the main carbon source of methane emission from manure management.

Remote Detection and Quantification of Methane Emissions Based on Hyperspectral Data Analysis

Measurement of methane emissions from leaks occurring on the territorially extensive network of transmission gas grid is a topical issue and highly desirable from the point of view of safety and reducing methane emissions into the atmosphere. Remote detection of methane is a problem whose technical solution is based on several types of optoelectronic devices, e.g. thermal imaging cameras with sets of optical filters, spectroradiometers, laser systems of the DIAL (DIfferential Absorption Lidar) type. On the other hand, the quantification of emission magnitudes is in most cases realized by spectoradiometric systems. This paper will present a method for analyzing hyperspectral data from an imaging Fourier infrared spectroradiometer. Measurements will be made on a purpose-built bench simulating methane emissions from a transmission network. Data obtained from ground level under different atmospheric conditions will be presented, together with the results of their analysis for different methane emissions.