Methane Mole Fraction Research Articles

COCCON Measurements of XCO2, XCH4 and XCO over Coal Mine Aggregation Areas in Shanxi, China, and Comparison to TROPOMI and CAMS Datasets

This study presents the first column-averaged dry-air mole fractions of carbon dioxide (XCO2), methane (XCH4) and carbon monoxide (XCO) in the coal mine aggregation area in Shanxi, China, using two portable Fourier transform infrared spectrometers (EM27/SUNs), in the framework of the Collaborative Carbon Column Observing Network (COCCON). The measurements, collected over two months, were analyzed. Significant daily variations were observed, particularly in XCH4, which highlight the impact of coal mining emissions as a major CH4 source in the region. This study also compares COCCON XCO with measurements from the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5P satellite, revealing good agreement, with a mean bias of 7.15 ± 9.49 ppb. Additionally, comparisons were made between COCCON XCO2 and XCH4 data and analytical data from the Copernicus Atmosphere Monitoring Service (CAMS). The mean biases between COCCON and CAMS were −6.43 ± 1.75 ppm for XCO2 and 15.40 ± 31.60 ppb for XCH4. The findings affirm the stability and accuracy of the COCCON instruments for validating satellite observations and detecting local greenhouse gas sources. Operating COCCON spectrometers in coal mining areas offers valuable insights into emissions from these high-impact sources.

CH4 and CO emission estimates for megacities: deriving enhancement ratios of CO2, CH4, and CO from GOSAT-2 observations

Abstract Enhancement ratios among trace gases co-emitted by combustion of fossil fuels vary with emission sources and their combustion efficiency. We used column-averaged dry-air mole fractions of carbon dioxide (XCO2), methane (XCH4), and carbon monoxide (XCO) from the Greenhouse gases Observing SATellite-2 (GOSAT-2), a unique satellite that observes them simultaneously with the same field of view, to derive the enhancement ratios (ΔXCO/ΔXCO2, ΔXCO/ΔXCH4, and ΔXCH4/ΔXCO2) for the 40 most populous cities in the world. These enhancement ratios were used to evaluate the Emissions Database for Global Atmospheric Research (EDGAR). For cities where the difference in the 2015 EDGAR CO emissions between the latest versions (v6.1 and v5.0) was 30% or less, the GOSAT-2 ΔXCO/ΔXCO2 ratios and EDGAR (v6.1/v7.0) CO/CO2 emission ratios were in good agreement (correlation coefficient of 0.65). For ~70% of the cities where the difference of CO emissions exceeded 30%, the EDGAR CO/CO2 emission ratios using v6.1 CO emissions were in better agreement with the GOSAT-2 ΔXCO/ΔXCO2 ratios than those using v5.0 CO emissions, indicating that v6.1 CO emissions were improved over v5.0 emissions. However, for the remaining cities, the version upgrade may have reduced the CO emissions too much. The CH4 and CO emissions for each city were then estimated from the ΔXCH4/ΔXCO2 and ΔXCO/ΔXCO2 ratios, respectively, by reference to the CO2 emissions from the Open-data Inventory for Anthropogenic CO2 (ODIAC) or EDGAR. Compared to our estimates using the ODIAC (EDGAR) CO2 emissions, the EDGAR v7.0 CH4 and v6.1 CO emissions were underestimated for 74% (57%) and 76% (53%), respectively, of all cities where results were available. For several cities where emissions were estimated using in situ observations and ground-based remote sensing observations, our results were in reasonable agreement with these results. The implication is that satellite-derived enhancement ratios can provide informative constraints on anthropogenic emissions in megacities.

Automated detection of regions with persistently enhanced methane concentrations using Sentinel-5 Precursor satellite data

Abstract. Methane (CH4) is an important anthropogenic greenhouse gas, and its rising concentration in the atmosphere contributes significantly to global warming. A comparatively small number of highly emitting persistent methane sources are responsible for a large share of global methane emissions. The identification and quantification of these sources, which often show large uncertainties regarding their emissions or locations, are important to support mitigating climate change. Daily global column-averaged dry air mole fractions of atmospheric methane (XCH4) are retrieved from radiance measurements of the TROPOspheric Monitoring Instrument (TROPOMI) on board on the Sentinel-5 Precursor (S5P) satellite with a moderately high spatial resolution, enabling the detection and quantification of localized methane sources. We developed a fully automated algorithm to detect regions with persistent methane enhancement and to quantify their emissions using a monthly TROPOMI XCH4 dataset from the years 2018–2021. We detect 217 potential persistent source regions (PPSRs), which account for approximately 20 % of the total bottom-up emissions. By comparing the PPSRs in a spatial analysis with anthropogenic and natural emission databases, we conclude that 7.8 % of the detected source regions are dominated by coal, 7.8 % by oil and gas, 30.4 % by other anthropogenic sources like landfills or agriculture, 7.3 % by wetlands, and 46.5 % by unknown sources. Many of the identified PPSRs are in well-known source regions, like the Permian Basin in the USA, which is a large production area for oil and gas; the Bowen Basin coal mining area in Australia; or the Pantanal Wetlands in Brazil. We perform a detailed analysis of the PPSRs with the 10 highest emission estimates, including the Sudd Wetland in South Sudan, an oil- and gas-dominated area on the west coast in Turkmenistan, and one of the largest coal production areas in the world, the Kuznetsk Basin in Russia. The calculated emission estimates of these source regions are in agreement within the uncertainties in results from other studies but are in most of the cases higher than the emissions reported by emission databases. We demonstrate that our algorithm is able to automatically detect and quantify persistent localized methane sources of different source type and shape, including larger-scale enhancements such as wetlands or extensive oil- and gas-production basins.

Evaluation of Sentinel-5P TROPOMI Methane Observations at Northern High Latitudes

The Arctic and boreal regions are experiencing a rapid increase in temperature, resulting in a changing cryosphere, increasing human activity, and potentially increasing high-latitude methane emissions. Satellite observations from Sentinel-5P TROPOMI provide an unprecedented coverage of a column-averaged dry-air mole fraction of methane (XCH4) in the Arctic, compared to previous missions or in situ measurements. The purpose of this study is to support and enhance the data used for high-latitude research through presenting a systematic evaluation of TROPOMI methane products derived from two different processing algorithms: the operational product (OPER) and the scientific product (WFMD), including the comparison of recent version changes of the products (OPER, OPER rpro, WFMD v1.2, and WFMD v1.8). One finding is that OPER rpro yields lower XCH4 than WFMD v1.8, the difference increasing towards the highest latitudes. TROPOMI product differences were evaluated with respect to ground-based high-latitude references, including four Fourier Transform Spectrometer in the Total Carbon Column Observing Network (TCCON) and five EM27/SUN instruments in the Collaborative Carbon Column Observing Network (COCCON). The mean TROPOMI–TCCON GGG2020 daily median XCH4 difference was site-dependent and varied for OPER rpro from −0.47 ppb to 22.4 ppb, and for WFMD v1.8 from 1.2 ppb to 19.4 ppb with standard deviations between 13.0 and 20.4 ppb and 12.5–15.0 ppb, respectively. The TROPOMI–COCCON daily median XCH4 difference varied from −26.5 ppb to 5.6 ppb for OPER rpro, with a standard deviation of 14.0–28.7 ppb, and from −5.0 ppb to 17.2 ppb for WFMD v1.8, with a standard deviation of 11.5–13.0 ppb. Although the accuracy and precision of both TROPOMI products are, on average, good compared to the TCCON and COCCON, a persistent seasonal bias in TROPOMI XCH4 (high values in spring; low values in autumn) is found for OPER rpro and is reflected in the higher standard deviation values. A systematic decrease of about 7 ppb was found between TCCON GGG2014 and GGG2020 product update highlighting the importance of also ensuring the reliability of ground-based retrievals. Comparisons to atmospheric profile measurements with AirCore carried out in Sodankylä, Northern Finland, resulted in XCH4 differences comparable to or smaller than those from ground-based remote sensing.

Abundances of trace constituents in Jupiter’s atmosphere inferred from Herschel/PACS observations

Context. On October 31, 2009, the Photodetector Array Camera and Spectrometer (PACS) on board the Herschel Space Observatory observed far-infrared spectra of Jupiter in the wavelength range between 50 and 220 µm as part of the program “Water and Related Chemistry in the Solar System”. The spectra have an effective spectral resolution between 900 and 3500, depending on the wavelength and grating order. Aims. We investigate the disk-averaged chemical composition of Jupiter’s atmosphere as a function of height using these observations. Methods. We used the Planetary Spectrum Generator and the least-squares fitting technique to infer the abundances of trace constituents. Results. The PACS data include numerous spectral lines attributable to ammonia (NH3), methane (CH4), phosphine (PH3), water (H2O), and deuterated hydrogen (HD) in the Jovian atmosphere and probe the chemical composition from p ~ 275 mbar to p ~ 900 mbar. From the observations, we infer an ammonia abundance profile that decreases from a mole fraction of (1.7 ± 0.8) × 10−4 at p ~ 900 mbar to (1.7 ± 0.9) × 10−8 at p ~ 275 mbar, following a fractional scale height of about 0.114. For phosphine, we find a mole fraction of (7.2 ± 1.2) × 10−7 at pressures higher than (550 ± 100) mbar and a decrease of its abundance at lower pressures following a fractional scale height of (0.09 ± 0.02). Our analysis delivers a methane mole fraction of (1.49 ± 0.09) × 10−3. Analyzing the HD R(0) line at 112.1 µm yields a new measurement of Jupiter’s D/H ratio, D/H = (1.5 ± 0.6) × 10−5. Finally, the PACS data allow us to put the most stringent 3σ upper limits yet on the mole fractions of hydrogen halides in the Jovian troposphere. These new upper limits are <1.1 × 10−11 for hydrogen fluoride (HF), <6.0 × 10−11 for hydrogen chloride (HCl), <2.3 × 10−10 for hydrogen bromide (HBr) and <1.2 × 10−9 for hydrogen iodide (HI) and support the proposed condensation of hydrogen halides into ammonium halide salts in the Jovian troposphere.

Toward on-demand measurements of greenhouse gas emissions using an uncrewed aircraft AirCore system

Abstract. This paper evaluates the performance of a multirotor uncrewed aircraft and AirCore system (UAAS) for measuring vertical profiles of wind velocity (speed and direction) and the mole fractions of methane (CH4) and carbon dioxide (CO2), and it presents a use case that combines UAAS measurements and dispersion modeling to quantify CH4 emissions from a dairy farm. To evaluate the atmospheric sensing performance of the UAAS, four field deployments were performed at three locations in the San Joaquin Valley of California where CH4 hotspots were observed downwind of dairy farms. A comparison of the observations collected on board the UAAS and an 11 m meteorological tower show that the UAAS can measure wind velocity trends with a root mean squared error varying between 0.4 and 1.1 m s−1 when the wind magnitude is less than 3.5 m s−1. Findings from UAAS flight deployments and a calibration experiment also show that the UAAS can reliably resolve temporal variations in the mole fractions of CH4 and CO2 occurring over periods of 10 s or longer. Results from the UAAS and dispersion modeling use case further demonstrate that UAASs have great potential as low-cost tools for detecting and quantifying CH4 emissions in near real time.

Cryogenic Process Optimization for Natural Gas Purification: Predictive Modeling of Methane-CO2 Solid-Vapor Phase Equilibrium Using Response Surface Methodology.

This research combines industrial engineering principles with chemical process modeling to explore the capture of CO2 from natural gas under cryogenic conditions. The study specifically investigates the Solid-Vapor (S-V) phase equilibrium in a methane-carbon dioxide (CH4-CO2) system. The study employs Response Surface Methodology (RSM) to develop a robust model for predicting phase behavior in industrial gas separation processes. The model is validated using experimental data, offering enhanced operational insights into cryogenic CO2 capture in industrial applications. The developed RSM model is particularly valuable as it can predict the mole fractions of methane and CO2 at various temperatures and pressures in the solid-vapor region of phase equilibrium, where limited experimental data make it difficult to estimate these components accurately. The key contribution of this study is to validate the RSM model's available experimental data, and the model can further be used to predict the process conditions at which high methane composition (yCH4) can be achieved. The developed model showed good agreement when the results were compared with previous experimental studies. The utilization of chemical engineering data to forecast previously unknown conditions in gas separation processes broadens the scope of industrial process optimization in this work.

Extraction, purification, and clumped isotope analysis of methane (Δ13CDH3 and Δ12CD2H2) from sources and the atmosphere

Abstract. Measurements of the clumped isotope anomalies (Δ13CDH3 and Δ12CD2H2) of methane have shown potential for constraining methane sources and sinks. At Utrecht University, we use the Thermo Scientific Ultra high-resolution isotope-ratio mass spectrometer to measure the clumped isotopic composition of methane emitted from various sources and directly from the atmosphere. We have developed an extraction system with three sections for extracting and purifying methane from high (> 1 %), medium (0.1 % to 1 %), and low-concentration (< 0.1 %) samples, including atmospheric air (∼ 2 ppm = 0.0002 %). Depending on the methane concentration, a quantity of sample gas is processed that delivers 3 ± 1 mL of pure methane, which is the quantity typically needed for one clumped isotope measurement. For atmospheric air with a methane mole fraction of 2 ppm, we currently process up to 1100 L of air. The analysis is performed on pure methane, using a dual-inlet setup. The complete measurement time for all isotope signatures is about 20 h for one sample. The mean internal precision values of sample measurements are 0.3 ± 0.1 ‰ for Δ13CDH3 and 2.4 ± 0.8 ‰ for Δ12CD2H2. The long-term reproducibility, obtained from repeated measurements of a constant target gas, over almost 3 years, is around 0.15 ‰ for Δ13CDH3 and 1.2 ‰ for Δ12CD2H2. The measured clumping anomalies are calibrated via the Δ13CDH3 and Δ12CD2H2 values of the reference CH4 used for the dual-inlet measurements. These were determined through isotope equilibration experiments at temperatures between 50 and 450 °C. We describe in detail the optimized sampling, extraction, purification, and measurement technique followed in our laboratory to measure the clumping anomalies of methane precisely and accurately. This paper highlights the extraction and one of the first global measurements of the clumping anomalies of atmospheric methane.

Greenhouse gas retrievals for the CO2M mission using the FOCAL method: first performance estimates

Abstract. The Anthropogenic Carbon Dioxide Monitoring (CO2M) mission is a constellation of satellites currently planned to be launched in 2026. CO2M is planned to be a core component of a Monitoring and Verification Support (MVS) service capacity under development as part of the Copernicus Atmosphere Monitoring Service (CAMS). The CO2M radiance measurements will be used to retrieve column-averaged dry-air mole fractions of atmospheric carbon dioxide (XCO2), methane (XCH4) and total columns of nitrogen dioxide (NO2). Using appropriate inverse modelling, the atmospheric greenhouse gas (GHG) observations will be used to derive United Nations Framework Convention on Climate Change (UNFCCC) COP 21 Paris Agreement relevant information on GHG sources and sinks. This challenging application requires highly accurate XCO2 and XCH4 retrievals. Three different retrieval algorithms to derive XCO2 and XCH4 are currently under development for the operational processing system at EUMETSAT. One of these algorithms uses the heritage of the FOCAL (Fast atmOspheric traCe gAs retrievaL) method, which has already successfully been applied to measurements from other satellites. Here, we show recent results generated using the CO2M version of FOCAL, called FOCAL-CO2M. To assess the quality of the FOCAL-CO2M retrievals, a large set of representative simulated radiance spectra has been generated using the radiative transfer model SCIATRAN. These simulations consider the planned viewing geometry of the CO2 instrument and corresponding geophysical scene data (including different types of aerosols and varying surface properties), which were taken from model data for the year 2015. We consider instrument noise and systematic errors caused by the retrieval method but have not considered additional error sources due to, for example, instrumental issues, spectroscopy or meteorology. On the other hand, we have also not taken advantage in this study of CO2M's MAP (multi-angle polarimeter) instrument, which will provide additional information on aerosols and cirrus clouds. By application of the FOCAL retrieval to these simulated data, confidence is gained that the FOCAL method is able to fulfil the challenging requirements for systematic errors for the CO2M mission (spatio-temporal bias ≤ 0.5 ppm for XCO2 and ≤ 5 ppb for XCH4).

Analysis on temperature uniformity in methane-rich internal reforming solid oxide fuel cells (SOFCs)

Temperature uniformity is a critical parameter in solid oxide fuel cells (SOFCs) since it directly impacts thermal stress, material degradation and output performance. Effective thermal management typically aims to achieve a minimal temperature gradient, especially within a SOFC stack assembled by numerous single cells. In this study, numerical simulations of various boundary conditions and cell designs are performed to investigate thermal uniformity in methane-rich internal reforming SOFCs, which can be utilized as a guidance for design and operation in practical application. The results indicate that the fuel gas with a 5 % mole fraction of methane is more effective in enhancing thermal uniformity through reforming cooling effect at the electrolyte compared to only a 1 % mole fraction. It is strongly recommended in cell design to maintain the ratio of the cell's length to its width (Rcell) greater than or equal to 1.0 considering its better thermal uniformity. However, both increasing the ratio of channel width to rib width (Rc-r) and decreasing the ratio of channel height to channel width (RH-W) have been demonstrated to deteriorate temperature uniformity. Within this study, increasing the backpressure to 1.5 bar is found to result in a 16.7 % reduction in the maximum temperature difference across the electrolyte when compared to that at atmospheric pressure. It is also advisable to operate at the inlet temperature ranging from 973 K to 1023 K for a more uniform temperature distribution within the SOFC.

Determining methane mole fraction at a landfill site using the Figaro Taguchi gas sensor 2611-C00 and wind direction measurements

The Figaro Taguchi gas sensor 2611-C00 was used to derive methane mole fraction at a landfill site from the ratio between measured resistance and a modelled reference resistance corresponding to background sampling, identified from wind direction.

Methane Source Attribution in the UK Using Multi‐Year Records of CH4 and δ13C

AbstractIsotopic measurements of atmospheric methane are valuable for the verification of bottom‐up atmospheric emissions inventories. The balance of sources in emissions inventories must be consistent with the δ13C‐CH4 isotopic record in the air. Long‐term records of both methane mole fraction and δ13C from five sites across the UK are presented, showing post‐2007 growth in CH4 and negative trend in δ13C, consistent with global background sites. Miller‐Tans analyses of atmospheric measurements identified that the δ13C signature of the methane source mix varied between −50.1 and −56.1‰, with less depleted δ13C signatures at sites receiving air from urban areas, consistent with an increased proportion of thermogenic sources. Isotopic signatures calculated for all sites are more enriched than those expected from the bottom‐up emissions inventory, suggesting that inventories for the UK either underestimate contributions of thermogenic/pyrogenic emissions or overestimate biogenic sources.

Thermodynamic design and experimental study of a condensation recovery system for VOCs

During the storage and transportation process of crude oil on tankers, the light hydrocarbon components in liquid form have the tendency to evaporate and vaporize easily, resulting in wasted resources and environmental pollution. The current petroleum volatile organic compounds (VOCs) recovery system such as absorption and membrane separation applied to crude oil tankers is unable to fulfil the requirements of existing VOCs emission standards. In contrast, the condensation method of VOCs recovery technology has the benefit of a straightforward process principle, and the recovered liquid hydrocarbons can be utilized directly. It is thus vital to develop a condensation recovery system for petroleum VOCs that is compatible with crude oil tankers. To attain the condensation and recovery of the non-azeotropic gases, such as CH4, C2H6, C3H8, and N2 in the feed gas, this paper proposes a low-temperature VOCs condensation recovery system with graded cooling and liquefaction separation for crude oil tankers. The proposed system initially utilizes a R404A/R23 double-stage cascade refrigeration cycle to cool the VOCs below −75 ℃ to liquefy most heavy hydrocarbons. Then, a low-temperature nitrogen expansion cooling cycle is utilized to cool the VOCs to approximately −160 °C to recover the remaining light hydrocarbons. The condensation process is simulated by Aspen HYSYS to study the variable operating conditions. The recovery of total hydrocarbons in the outlet tail gas in the simulation results is analyzed and found to be up to 95.50 %. Under identical refrigeration capacity circumstances, decreasing the inlet pressure, increasing the inlet flow rate, and increasing the methane mole fraction in VOCs component, all lead to declining trends of total hydrocarbon recovery and methane recovery rate. Specifically, the effects of four different hydrocarbon component ratios on total hydrocarbon recovery and total cooling load are investigated at a constant nitrogen content and refrigeration capacity. Furthermore, the optimal design and analysis process for the flow path section of the turbine expander under the cryogenic conditions is discussed. The results demonstrate that the outlet temperature through the turbine expander is at least −172.1 °C, and the cooling capacity can be up to 4.5 kW with a margin of 80 %. Finally, through the comprehensive VOCs condensation recovery experiments, the proposed system successfully achieves the liquefied separation and recovery of CH4, C2H6, and other hydrocarbons. The recovery rate of the total hydrocarbons in the outlet tail gas reaches 96.21 %, conforming to the VOCs emission standards and regulations. The findings of this study provide a viable technical resolution in the field of petroleum VOCs recovery from crude oil tankers.

Evidence for multi-decadal fuel buildup in a large California wildfire from smoke radiocarbon measurements

In recent decades, there has been a significant increase in annual area burned in California’s Sierra Nevada mountains. This rise in fire activity has prompted the need to understand how historical forest management practices affect fuel composition and emissions. Here we examined the total carbon (TC) concentration and radiocarbon abundance (Δ14C) of particulate matter (PM) emitted by the KNP Complex Fire, which occurred during California’s 2021 wildfire season and affected several groves of giant sequoia trees in the southern Sierra Nevada. During a 26 h sampling period, we measured concentrations of fine airborne PM (PM2.5), as well as dry air mole fractions of carbon monoxide (CO) and methane (CH4), using a ground-based mobile laboratory. We also collected filter samples of PM2.5 for analysis of TC concentration and Δ14C. High correlation among PM2.5, CO, and CH4 time series confirmed that our PM2.5 measurements captured variability in wildfire emissions. Using a Keeling plot approach, we determined that the mean Δ14C of PM2.5 was 111.6 ± 7.7‰ (n = 12), which was considerably enriched relative to atmospheric carbon dioxide in the northern hemisphere in 2021 (−3.2 ± 1.4‰). Combining these Δ14C data with a steady-state one-box ecosystem model, we estimated that the mean age of fuels combusted in the KNP Complex Fire was 40 years, with a range of 29–57 years. These results provide evidence for emissions originating from woody biomass, larger-diameter fine fuels, and coarse woody debris that have accumulated over multiple decades. This is consistent with independent field observations that indicate high fire intensity contributed to widespread giant sequoia mortality. With the expanded use of prescribed fires planned over the next decade in California to mitigate wildfire impacts, our measurement approach has the potential to provide regionally-integrated estimates of the effectiveness of fuel treatment programs.

GAS LEAK DETECTION USING GAS QUALITY IN NATURAL GAS PROCESSING PLANT

The two major parameters used in determining the quality of a processed natural gas are the water content and water dew point. For every natural gas contract, the minimum amount of water the processed gas contained and the water dew point must be specified. Natural gas treatment processes include the removal of unwanted components or the reduction of these unwanted components, such as acid gases (carbon dioxide-CO2, hydrogen sulphide-H2S), nitrogen-N2 and water vapour. Their presence in natural gas can be detrimental to natural gas process facility and gas pipeline efficiency, hence the need to remove or reduce their concentration to the barest minimum or acceptable standard in natural gas transportation and utilization. Natural gas treatment allows the gas to pass through different stages with specific functions, such as: pressure control; separation of gas and condensate; sweetening; dehydration; regeneration of sweetening and dehydration solvents; dew point control. This report focuses on simulating natural gas plant which integrate the different stage, focusing on two scenarios; the first scenario is without gas leak in the plant and the second scenario is with leak in the gas plant. The results were compared to determine the impact of the leak in the quality of the processed natural gas (dry gas). It was found out that as the volume of gas leak increases, the quality of the gas increases (i.e low water content; water dew point; increase mole fraction of methane). This is a very good finding, since it is the target of gas processors.

Evolution of Atmospheric Carbon Dioxide and Methane Mole Fractions in the Yangtze River Delta, China

As the most economically developed region in China, the Yangtze River Delta (YRD) region contributed to ~17% of the total anthropogenic CO2 emissions from China. However, the studies of atmospheric CO2 and CH4 in this area are relatively sparse and unsystematic. Here, we analyze the changing characters of those gases in different development periods of China, based on the 11-year atmospheric CO2 and CH4 records (from 2010 to 2020) at one of the four Chinese sites participating in the World Meteorological Organization/Global Atmospheric Watch (WMO/GAW) program (Lin’an regional background station), located in the center of YRD region, China. The annual average atmospheric CO2 and CH4 mole fractions at LAN have been increasing continuously, with growth rates of 2.57 ± 0.14 ppm yr−1 and 10.3 ± 1.3 ppb yr−1, respectively. Due to the complex influence of regional sources and sinks, the characteristics of atmospheric CO2 and CH4 varied in different periods: (i) The diurnal and seasonal variations of both CO2 and CH4 in different periods were overall similar, but the amplitudes were different. (ii) The elevated mole fractions in all wind sectors tended to be uniform. (iii) The potential source regions of both gases expanded over time. (iv) The growth rate in recent years (2016–2020) changed significantly less than that in the earlier period (2010–2015). Our results indicated that the CO2 and CH4 mole fractions were mainly correlated to the regional economic development, despite the influence of special events such as the G20 Summit and COVID-19 lockdown.

Characterising the methane gas and environmental response of the Figaro Taguchi Gas Sensor (TGS) 2611-E00

Abstract. In efforts to improve methane source characterisation, networks of cheap high-frequency in situ sensors are required, with parts-per-million-level methane mole fraction ([CH4]) precision. Low-cost semiconductor-based metal oxide sensors, such as the Figaro Taguchi Gas Sensor (TGS) 2611-E00, may satisfy this requirement. The resistance of these sensors decreases in response to the exposure of reducing gases, such as methane. In this study, we set out to characterise the Figaro TGS 2611-E00 in an effort to eventually yield [CH4] when deployed in the field. We found that different gas sources containing the same ambient 2 ppm [CH4] level yielded different resistance responses. For example, synthetically generated air containing 2 ppm [CH4] produced a lower sensor resistance than 2 ppm [CH4] found in natural ambient air due to possible interference from supplementary reducing gas species in ambient air, though the specific cause of this phenomenon is not clear. TGS 2611-E00 carbon monoxide response is small and incapable of causing this effect. For this reason, ambient laboratory air was selected as a testing gas standard to naturally incorporate such background effects into a reference resistance. Figaro TGS 2611-E00 resistance is sensitive to temperature and water vapour mole fraction ([H2O]). Therefore, a reference resistance using this ambient air gas standard was characterised for five sensors (each inside its own field logging enclosure) using a large environmental chamber, where logger enclosure temperature ranged between 8 and 38 ∘C and [H2O] ranged between 0.4 % and 1.9 %. [H2O] dominated resistance variability in the standard gas. A linear [H2O] and temperature model fit was derived, resulting in a root mean squared error (RMSE) between measured and modelled resistance in standard gas of between ±0.4 and ±1.0 kΩ for the five sensors, corresponding to a fractional resistance uncertainty of less than ±3 % at 25 ∘C and 1 % [H2O]. The TGS 2611-E00 loggers were deployed at a landfill site for 242 d before and 96 d after sensor testing. Yet the standard (i.e. ambient air) reference resistance model fit based on temperature and [H2O] could not replicate resistance measurements made in the field, where [CH4] was mostly expected to be close to the ambient background, with minor enhancements. This field disparity may have been due to variability in sensor cooling dynamics, a difference in ambient air composition during environmental chamber testing compared to the field or variability in natural sensor response, either spontaneously or environmentally driven. Despite difficulties in replicating a standard reference resistance in the field, we devised an excellent methane characterisation model up to 1000 ppm [CH4] by using the ratio between measured resistance with [CH4] enhancement and its corresponding reference resistance in standard gas. A bespoke power-type fit between resistance ratio and [CH4] resulted in an RMSE between the modelled and measured resistance ratio of no more than ±1 % Ω Ω−1 for the five sensors. This fit and its corresponding fit parameters were then inverted and the original resistance ratio values were used to derive [CH4], yielding an inverted model [CH4] RMSE of less than ±1 ppm, where [CH4] was limited to 28 ppm. Our methane response model allows other reducing gases to be included if necessary by characterising additional model coefficients. Our model shows that a 1 ppm [CH4] enhancement above the ambient background results in a resistance drop of between 1.4 % and 2.0 % for the five tested sensors. With future improvements in deriving a standard reference resistance, the TGS 2611-E00 offers great potential in measuring [CH4] with parts-per-million-level precision.

Self and N[formula omitted] collisional broadening of far-infrared methane lines at low-temperature with application to Titan

We report the measurement of broadening coefficients of pure rotational lines of methane at different pressure and temperature conditions. A total of 27 far-infrared spectra were recorded at the AILES beamline of the SOLEIL synchrotron at room-temperature, 200K and 120K, in a range of 10 to 800mbar. Self and N2 broadening coefficients and temperature dependence exponents of methane pure rotational lines have been measured in the 73–136cm−1 spectral range using multi-spectrum non-linear least squares fitting of Voigt profiles. These coefficients were used to model spectra of Titan that were compared to a selection of equatorial Cassini/CIRS spectra, showing a good agreement for a stratospheric methane mole fraction of (1.17 ± 0.08)%.

Analysis of methane pyrolysis experiments at high pressure using available reactor models

Most batch reactor methane thermal decomposition (MTD) studies have focused on sub-atmospheric pressures. In this study, MTD experiments were performed between 892 K and 1292 K and 4 atm inside a quasi-isothermal quartz batch reactor at residence times ranging from 0 to 300 s. At a given temperature, elevated pressure resulted in higher methane conversion compared with the sub-atmospheric conditions. A zero-dimensional, closed, isochoric, homogeneous gas-phase model was used to compare numerical predictions from available reaction mechanisms in literature to experimental data. It was found that most models accurately predict conversion at low pressure and high temperature and at high pressure and high temperature, but did not accurately predict methane, hydrogen, and intermediate species mole fractions at 4 atm and either 892 K or 1093 K. A reaction path analysis showed the reactions responsible for the delay in hydrogen formation at elevated pressure are 2CH3(+M)⟺ C2H6, C2H6 ＋ CH3⟺ C2H5 ＋ CH4, C2H6 ＋ H ⟺ C2H5 ＋ H2 and C2H5(+M)⟺ C2H4 ＋ H, where M is the collision partner. A gas-phase model accounting for the solid carbon shows that the observed discrepancy is not due to the unavailability of the carbon formation model but to slower reaction kinetics, especially at lower temperatures. The experimental data presented can be used to obtain a methane pyrolysis reaction mechanism suitable for high pressure conditions.

Estimation of syngas yield in hydrothermal gasification process by application of artificial intelligence models

Quality syngas production with higher moles of hydrogen and methane are the primary objective of gasification process which is dependent upon the process parameters and composition of biomass. However, it is always a costly and time-consuming task to get the optimum biomass composition and process parameters for quality syngas production. In this research, artificial intelligence (AI) algorithms have been applied for high quality syngas prediction with better moles fractions of hydrogen and methane using hydrothermal gasification (HTG). Comparative analysis of Convolutional Neural Network (CNN), Artificial Neural Network (ANN), Gradient Boost Regressor (GBR), Extreme Boost Regressor (XGB), and Random Forest Regressor (RFR) based algorithms have been done to select an optimal one. Ultimate analysis of biomass and process input parameters inlcuding temperature, pressure, percentage solid content of biomass, and resident time have been used as an input parameter for prediction models. Final comparative results of these AI models conclude that XGB has a better prediction result as compared to other with coefficient of determinant (R2) and mean square errors ranges from 0.85 to 0.95 and 0.008–0.01, respectively. Furthermore, process temperature and the resident time are the most contributing factors in mole fractions of hydrogen and methane. Higher hydrogen and oxygen contents in the biomass, significantly contributes to the production of quality syngas.