Variation Of Gas Concentration Research Articles

Frequency-dependent Amplitude Versus Offset analysis of a Cenozoic mass-transport deposit on the Namibian slope

Abstract A partially tuned, ‘soft’ seismic reflection, overlying a regional limestone marker on the west African slope, is shown to represent a sequence, up to 30 m thick, within which various individual stratigraphic units are identified, some of which display characteristics of a mass-transport deposit (MTD). The seismic reflection is described in terms of its two-way time structure, reflection amplitude pattern, complex seismic attributes and AVO response. Frequency-dependent aspects of the AVO response, resulting from velocity attenuation and dispersion of seismic signals, are shown to indicate variations in pore-fluid gas concentration. These are exploited to assess lithological, petrophysical and pore-fluid characteristics of the various sub-units within the sequence. A relative acoustic impedance inversion of the seismic data is combined with a low-frequency model, constructed from acoustic velocity data, to approximate absolute acoustic impedance characteristics of the sequence and to model behaviour of the various sub-units across the area. These pseudo-absolute impedance data are combined with evidence from AVO analysis, to construct a 2D model of the MTD unit and to generate a synthetic seismic record, which confirms the interpretation of stratigraphic, petrophysical and lithological properties of the MTD complex.

Propagation characteristics of turbulent deflagration in horizontal tunnel with lateral liquefied petroleum gas concentration variations

The deflagration of premixed gas with a non-uniform spatial distribution is one of the critical characteristics observed in deflagration accidents in tunnels. The concentration gradient of premixed gas in the propagation direction of the deflagration flame in the tunnel is an important factor influencing the propagation of deflagration. In this study, the numerical simulation of the deflagration process in two adjacent areas with different initial concentrations of premixed liquefied petroleum gas (LPG) was implemented in a tunnel with a unidirectional opening. The dynamic coupling characteristics of the lateral concentration difference of the premixed gas in the tunnel, the deflagration propagation process, and the concentration gradient mechanism that promotes or inhibits the initial deflagration propagation were analysed. Staged violent deflagration can be induced by a sharp transition from weak initial deflagration under an appropriate concentration gradient to unforeseen severe deflagration overpressure destruction and flame propagation. In a tunnel with a large cross-sectional area, the difference in the concentration of premixed gas along the propagation path of the deflagration flame can also cause the local protrusion of this front, thereby increasing the spreading ability of deflagration flame at the local location. However, an excessively high concentration gradient may hinder the initial propagation of deflagration to a certain extent, limiting the expansion space of combustion heat and reducing the propagation speed of a flattened deflagration flame front. To characterise the propagation velocity of deflagration flame in the tunnel formed by two zones with different initial premixed LPG concentrations, a dual-zone model that combines power and exponential functions was proposed. The validity of the model was also verified.

A highly sensitive sensor of methane and hydrogen in tellurite photonic crystal fiber based on four-wave mixing

A tellurite photonic crystal fiber (PCF) sensor structure is proposed for simultaneous measurements of methane and hydrogen. The structure is a simple hexagonal three-cladding structure, and six air holes in the inner cladding are coated with methane sensitive film and hydrogen sensitive film respectively. Based on the degenerate four-wave mixing (DFWM) theory, the direct relationship between the wavelength shifts of the Stokes spectrum or anti-Stokes spectrum and the variations in gas concentration can be established to realize the accurate detection of gas concentration. The influences of the pump wavelength and gas-sensitive film thickness on the gas sensitivity are investigated, and the maximum sensitivities of methane and hydrogen after parameter optimization are − 2.052 nm/% and − 0.236 nm/%, respectively. The linearity of the fitting can reach up to 99.95%, and the low detection limit of methane is 450 ppm and hydrogen is 2500 ppm. The sensing method based on four-wave mixing in non-silica photonic crystal fiber can also be extended to other detections of gas mixtures in the mid-infrared field.

Artificial intelligence for hurricane storm surge hazard assessment

Risk-informed coastal management requires assessment of extreme flood hazards from a large number of storm scenarios. To account for impact of climate change based on potential variations in greenhouse gas concentration and climate models, the number of storm scenarios would be even larger. Although physics-based hydrodynamic numerical models could predict flood levels and their impact from storm scenarios, the high computational cost of the solutions hinders the ability to perform the required number of simulations. Towards alleviating that cost, we show that physics-based simulations can be combined with Artificial Neural Network models to support more faster and effective prediction of low-probability events that account for uncertainties associated with climate change. We show this capability by predicting 10, 100, and 1,000 years return periods for peak storm surge height at a specific location on an idealized coastline. A large data set of synthetic tropical cyclones is generated from physics-based simulations and used for training, validating and testing the constructed neural network model. The ANN predicted values are validated against values from the physics-based simulations. The advantage of the combined approach is that, once the training was complete, it was performed in a fraction of the time required for the physics-based simulations.

A gas migration law study of a large-scale 3D physical similarity simulation with an adaptive Kalman filter algorithm

PurposeIn this study, a physical similarity simulation plays a significant role in the study of crack evolution and the gas migration mechanism. A sensor is deployed inside a comparable artificial rock formation to assure the accuracy of the experiment results. During the building of the simulated rock formation, a huge volume of acidic gas is released, causing numerous sensor measurement mistakes. Additionally, the gas concentration estimation approach is subject to uncertainty because of the complex rock formation environment. As a result, the purpose of this study is to introduce an adaptive Kalman filter approach to reduce observation noise, increase the accuracy of the gas concentration estimation model and, finally, determine the gas migration law.Design/methodology/approachFirst, based on the process of gas floatation-diffusion and seepage, the gas migration model is established according to Fick’s second law, and a simplified modeling method using diffusion flux instead of gas concentration is presented. Second, an adaptive Kalman filter algorithm is introduced to establish a gas concentration estimation model, taking into account the model uncertainty and the unknown measurement noise. Finally, according to a large-scale physical similarity simulation platform, a thorough experiment about gas migration is carried out to extract gas concentration variation data with certain ventilation techniques and to create a gas chart of the time-changing trend.FindingsThis approach is used to determine the changing process of gas distribution for a certain ventilation mode. The results match the rock fissure distribution condition derived from the microseismic monitoring data, proving the effectiveness of the approach.Originality/valueFor the first time in large-scale three-dimensional physical similarity simulations, the adaptive Kalman filter data processing method based on the inverse Wishart probability density function is used to solve the problem of an inaccurate process and measurement noise, laying the groundwork for studying the gas migration law and determining the gas migration mechanism.

Detection and attribution of climate change: A deep learning and variational approach

Abstract Twelve climate models and observations are used to attribute the global mean surface temperature (GMST) changes from 1900 to 2014 to external climate forcings. The external forcings are decomposed into the effects of the well-mixed greenhouse gas concentration variation, the effects of anthropogenic aerosol concentration changes, and the effects of natural forcings. First, a convolutional neural network (CNN) is trained to estimate the simulated historical GMST from single-forcing experiments using outputs from the multi-model ensemble. We then use this CNN to solve the attribution problem using an original variational inversion approach. The variational inversion is first validated using historical climate simulations as pseudo-observations. Then we perform an inversion from observations. This provides a distribution of the GMST resulting from the three forcings. For 2014, inversions estimate that the greenhouse gases changes are responsible for a GMST anomaly within [0.8 $ {}^{\circ } $ C,1.9 $ {}^{\circ } $ C], while anthropogenic aerosols and natural forcings anomalies are within [−0.7 $ {}^{\circ } $ C,−0.1 $ {}^{\circ } $ C] and [−0.1 $ {}^{\circ } $ C,0.3 $ {}^{\circ } $ C], respectively. The method designed here can be adapted and extended to attribute the changes of other variables or to focus on the regional scale.

Thermo-gas dynamics affect the leaf canopy shape and moisture content of aquaponic lettuce in a modified partially diffused microclimatic chamber

Precise and timely monitoring of leaf water content and growth is necessary for precision agriculture. In this study, the impact of temperature and gas concentration variations was synthesized with leaf canopy shape and moisture content of aquaponic lettuce in a customized partially diffused microclimatic chamber equipped with an RGB camera. Using the acquired thermo-gas sensor data during the light-dependent photosynthetic reaction and dark-period aerobic respiration, it was analyzed with the extracted spectro-morphological leaf canopy signatures. Applying spectro-morphological leaf canopy data as input to the recurrent neural network it was possible to sensitively predict full moisture content (FMT) and equivalent water thickness (EWT) with 92.34% and 85.96% accuracy, respectively. A decrease in red green blue vegetation index (RGBVI) and an increase in excess of green (ExG) optical vegetation stress index corresponds to an increase in FMT. According to our data, it was possible to observe that the water content balance during the third week after sowing, follows the same trend observed for the oxygen production increase during the light period. Additionally, it was also possible to observe that uneven leaf broadening (canopy shape index > 1), low EWT, high photosynthetic quotient (PQ), and photothermal unit (PTU), and minimal temperature and humidity stretch resulted in higher oxygen production rates. A growing degree day of 23.46 ± 0.30 °C day is ideal for aquaponic lettuce. Plants with six (6) weeks exhibited the highest thermal sensitivity (Q1) of 0.205. Overall, the developed model and observations allow concluding that the combined temperature-O2CO2 dynamics monitoring must be considered to achieve maximum production rates. Moreover, in the framework of the new approaches developed within precision agriculture schemes, the collected optical data allied to the recurrent neural network are suitable tools for this continuous monitoring in an automated way.

A Molecular Simulation Study of Silica/Polysulfone Mixed Matrix Membrane for Mixed Gas Separation.

Polysulfone-based mixed matrix membranes (MMMs) incorporated with silica nanoparticles are a new generation material under ongoing research and development for gas separation. However, the attributes of a better-performing MMM cannot be precisely studied under experimental conditions. Thus, it requires an atomistic scale study to elucidate the separation performance of silica/polysulfone MMMs. As most of the research work and empirical models for gas transport properties have been limited to pure gas, a computational framework for molecular simulation is required to study the mixed gas transport properties in silica/polysulfone MMMs to reflect real membrane separation. In this work, Monte Carlo (MC) and molecular dynamics (MD) simulations were employed to study the solubility and diffusivity of CO2/CH4 with varying gas concentrations (i.e., 30% CO2/CH4, 50% CO2/CH4, and 70% CO2/CH4) and silica content (i.e., 15–30 wt.%). The accuracy of the simulated structures was validated with published literature, followed by the study of the gas transport properties at 308.15 K and 1 atm. Simulation results concluded an increase in the free volume with an increasing weight percentage of silica. It was also found that pure gas consistently exhibited higher gas transport properties when compared to mixed gas conditions. The results also showed a competitive gas transport performance for mixed gases, which is more apparent when CO2 increases. In this context, an increment in the permeation was observed for mixed gas with increasing gas concentrations (i.e., 70% CO2/CH4 > 50% CO2/CH4 > 30% CO2/CH4). The diffusivity, solubility, and permeability of the mixed gases were consistently increasing until 25 wt.%, followed by a decrease for 30 wt.% of silica. An empirical model based on a parallel resistance approach was developed by incorporating mathematical formulations for solubility and permeability. The model results were compared with simulation results to quantify the effect of mixed gas transport, which showed an 18% and 15% percentage error for the permeability and solubility, respectively, in comparison to the simulation data. This study provides a basis for future understanding of MMMs using molecular simulations and modeling techniques for mixed gas conditions that demonstrate real membrane separation.

Assessment of variations of air pollutant concentrations during the COVID-19 lockdown and impact on urban air quality in South Asia

Quantifying the variations of atmospheric aerosols and trace gas concentrations with the impact of lockdown due to the Coronavirus disease of 2019 (COVID-19) pandemic is crucial in understanding urban air quality. For this purpose, we utilized the multi-instrumental approach of satellite remote sensing and reanalysis model data to examine the spatial and temporal patterns of major air pollutants during December 2019–June 2020 in South Asia. The lockdown has to lead to a considerable decrease in aerosol optical thickness (AOT) over South China (−18.92%) and Indo-Gangetic Plain (IGP; −24.29%) compared to its ordinary level for a couple of weeks. Noticeable reductions in tropospheric NO2 are observed over the Pearl River Delta (PRD; −0.3/cm2) followed by Central China (CC) with −0.21/cm2and IGP (−0.085/cm2), and the lowest (−0.0008/cm2) in the Tibetan Plateau (TP) region. The changes observed in PM2.5 and SO2 levels (from −58.56% to - 63.64%) are attributed to the decrease in anthropogenic emissions, vehicular exhaust, and industrial activities. However, the BC concentrations are reduced by approximately halved of its ordinary levels in the IGP (−2.28 μg/m3) followed by YRD (−1.56 μg/m3), CC (−1.5 μg/m3), NCP (−1.29 μg/m3), and PRD (−0.78 μg/m3) regions. The total column O3 predominantly increased from 262.68 to 285.53DU, 323.00 to 343.00DU, and 245.00 to 265.00DU in the YRD, NCP, and IGP areas. This is mainly associated with solar radiation, meteorological factors, and an unprecedented reduction in NOx during the lockdown period.

Hydrogen sensing properties of Pd loaded TiO2 nanorods

The hydrogen sensing performance of palladium (Pd) catalyst loaded TiO$_2$ nanorods based sensors were investigated. TiO$_2$ nanorods were grown on Al$_2$O$_3$ substrate by a facile hydrothermal process. TiO$_2$ nanorods (NRs) were functionalized with Pd metal by RF magnetron sputtering. Samples were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM) techniques for structural and morphological analysis. Sensor measurements toward H$_2$ and some volatile organic compounds (VOCs) such as acetone, ethanol, xylene and toluene were performed by varying gas concentrations at different temperatures. The sensors were found to exhibit excellent sensitivities towards different hydrogen concentrations ranging from 25 to 1000 ppm in air. The effects of different operating temperatures on the sensing performance of the devices were studied in the range of 100-200$^{\circ}$C. It was observed that the 2 nm Pd?loaded and 4 nm Pd-loaded sensors were approximately 12 and 44 times more sensitive than the pristine TiO$_2$ nanorods sensor, respectively. The effect of temperature dependence on sensor response and the influence of the metal loading for hydrogen sensing are presented and discussed.

ZONES OF RECENT ACTIVATION AND SCHEME OF THE EARTH CRUST PERMEABILITY OF UKRAINE

An attempt is considered to supplement the criteria for identifying zones of recent activation in the territory of Ukraine with another one — data on the results of studies of helium concentration in ground-water. The previous analysis of information showed that as regional criteria, information can be applied on anomalies in heat flow, increased electrical conductivity of Earth’s crustal and the upper mantle rocks, distribution of mantle gravitational anomalies, and surface uplifts over the past millions of years. They were chosen among others precisely because of the dissemination of relevant information throughout the country. This requirement is also met by the permeability Scheme of the earth’s crust of Ukraine, which is a fragment of the permeability Scheme of the earth’s crust of the European part of the USSR based on the results of helium studies. The principal applicability of such information for solving the problem is shown. Areas of maximum helium concentrations in near-surface waters are indicated, primarily those associated with disjunctive dislocation. Theу are concentrated in the south-west of Ukraine and in Moldova. The disadvantages of the Scheme are noted, due to poor study and significant variations in background gas concentrations, directly caused not by recent activation, but by the peculiarities of helium generation by rocks of the upper part of the earth’s crust. There are inconsistencies between the previously obtained ideas about the activated zones and the data of the Scheme. They are especially large in the Carpathian, Crimean and Donetsk regions, and are noticeable in others. Therefore, it seems necessary, first, to continue research, thicken the network of observations and develop a methodology for analyzing their results.

Utilization of Mendong Plant Activated Charcoal as SO2 Gas Adsorbent: Preliminary Study

This study aims to find alternative low-cost, easy and environmental-friendly adsorbent materials to eliminate SO2 gas, by utilizing Mendong plants as activated charcoal. Therefore, need to know the ability of this low-cost adsorbent in term of optimum concentration, adsorption efficiency, and the adsorption capacity of the charcoal to eliminate SO2. Mendong plants were prepared with a modified tool and macerated with ZnCl2 2.5% (w/v) for 24 hours. Then, the adsorption process with artificial SO2 waste was conducted for 1 hour. UV-Vis Spectrophotometer was used to determine the gas concentration. The results showed that the highest concentration of absorbed SO2 gas (Ct) is at the initial gas concentration 4.4006 µg/mL (mass Na2S2O3 0.015 g), with 3.008 µg/mL of gas is absorbed. The gas adsorption efficiency is 70.53% at the variation of initial gas concentration of 4.1400 µg/mL. While, the adsorption capacity of activated ZnCl2-Mendong stem charcoal is 92.1123 (µg/g). The results of the characterization by FTIR showed that the Mendong plant ZnCl2- activated charcoal is polar and aromatic, verified by the absorbance of hydroxyl group and aromatic skleleton of cellulose, hemicellulose and lignin.

Investigation of optoelectrical properties of indium oxide thin films with hydrogen and oxygen gas concentration variation during sputtering

We have investigated the optoelectrical properties of the In2O3 thin films deposited with hydrogen and oxygen gas concentration variation during the sputtering process. As-deposited films have shown amorphous nature and post-annealing treatment has led to polycrystalline films with better optoelectrical properties. The hydrogen and oxygen gas concentration optimization has led to the In2O3:H films' with electrical mobility of ~80 cm2/V.s at the carrier concentration of ~1 × 1020 cm−3, and the resistivity of ~5 × 10−4 Ω cm. The better carrier mobility of the In2O3:H films in comparison to the pure In2O3 films is due to minimization of carrier scattering, after replacing some of the doubly ionized oxygen vacancies (in In2O3) with the singly charged hydrogen (in In2O3:H). The spectroscopic ellipsometry (SE) analysis of the In2O3:H films' have revealed the role of oxygen in the free carrier absorption in near-infrared wavelength region; apart from quantification of optical mobility, and plasma energy of the In2O3:H films. The post-annealed In2O3:H films’ carrier mobility obtained from the Hall and SE measurements have pointed out the influential role of carrier impurity scattering rather than the grain boundary scattering.

Plasma sprayed copper oxide sensor for selective sensing of carbon monoxide

This investigation deals with a carbon monoxide (CO) sensing of copper oxide (CuO) coating obtained using plasma spraying of CuO powder. CO sensing measurements were undertaken using a dynamic flow gas sensing set up that operated in the temperature range of 100–350 °C. The coating showed a maximum sensor response at 150 °C. Therefore, effect of variation of CO gas concentration (500-5 ppm) on the sensor response was studied at 150 °C. Coating exhibited reproducible CO sensing characteristics along with good stability of baseline resistance. To understand the stability aspect, time dependent sensor response at various concentrations were analysed using a reversible sensing model following the Langmuir-Hinshelwood mechanism. To ascertain the selectivity of response towards CO, sensing measurements were performed at 150 °C in the presence of other gases like nitrogen dioxide (NO2), iso-butane (i-C4H10), and methane (CH4) in addition to CO. The plausible reasons for selective CO sensing are also discussed. To the best of authors’ knowledge, this is the first report presenting the CO sensing capability of plasma sprayed CuO coating.

Ultracompact gas sensor with metal-organic-framework-based differential fiber-optic Fabry-Perot nanocavities.

Refractive-index (RI)-based sensing is a major optical sensing modality that can be implemented in various spectral ranges. While it has been widely used for sensing of biochemical liquids, RI-based gas sensing, particularly small-molecule gases, is challenging due to the extremely small RI change induced by gas concentration variations. We propose a RI-based ultracompact fiber-optic differential gas sensor that employs metal-organic-framework (MOF)-based dual Fabry-Perot (FP) nanocavities. A MOF is used as the FP cavity material to enhance the sensitivity as well as the selectivity to particular gas molecules. The differential sensing scheme leverages the opposite change in the cavity-length-dependent reflection of the two FP cavities, which further enhances the sensitivity compared with single FP cavity based sensing. For proof-of-concept, a fiber-optic CO2 sensor with ZIF-8-based dual FP nanocavities was fabricated. The effective footprint of the sensor was as small as 157 µm2 and the sensor showed an enhanced sensitivity of 48.5 mV/CO2Vol%, a dynamic range of 0-100 CO2Vol%, and a resolution of 0.019 CO2Vol% with 1 Hz low-pass filtering. Although the current sensor was only demonstrated for CO2 sensing, the proposed sensor concept can be used for sensing of a variety of gases when different kinds of MOFs are utilized.

Deployment of Underground Wireless Sensor Network Based on Magnetic Core Antennas and Multiple Surface Acoustic Wave Sensor Modules

For the first time, a 3less (batteryless, chipless, wireless) underground sensor system was developed for real time monitoring of variations in temperature, humidity, and hydrogen gas concentrations around underground utility burials. The completed sensor system consists of several magnetic core antennas, surface acoustic wave (SAW) sensors, and a measurement system. Each SAW sensor was activated by pure magnetic energy, and showed high sensor performances in sensitivity and linearity. A long readout distance was observed between the upper and underground antennas, and wireless magnetic communication was analyzed in terms of the interdistances, the angles between antennas, and the underground constituent mediums. A circulator was employed to discern magnetic signals emitting and receiving in between the upper and underground systems. A COMSOL simulation and coupling of mode (COM) modeling were also conducted to determine optimal design parameters for the sensor modules, and to predict the experimental results in advance.

Reproducing natural variations in CO2 concentration in vadose zone wells with observed atmospheric pressure and groundwater data

Continuous CO2 gas monitoring was performed to understand the natural variations of the gas concentration in the vadose zone wells. The monitoring results demonstrated sudden rise and fall signals, which posed a possibility of error in interpreting the CO2 leaking signal from the sequestrating reservoir or evaluating the quantity of removed VOCs at a contaminated site. Based on the monitoring data, conceptual models were established and three cases were numerically simulated to determine whether or not reproducing the natural variations of gas concentration is possible. The simulated numerical model indicated that the atmospheric pressure and groundwater level data should be considered together, rather just only one boundary condition each (top or bottom). Reproducing the natural pattern of the target gas and understanding the gas flow and transport under real closed natural conditions would also be useful. The results demonstrated the need for numerical simulation to predict the natural pattern of the CO2 gas concentration before designing or performing actual CO2 release test or CO2 leakage monitoring in the wells of the vadose zone, as well as at the geologic carbon sequestration site.

Simulation of gas concentration during the process of air injection and extraction in a landfill

AbstractOld landfills require pre‐aeration before excavation to reduce the emissions of volatile organic compounds and methane. Variation and distribution of gas species during landfill aeration is important in designing an aeration system and evaluating aeration progress. Limited research is conducted on the variation of gas concentration in aerobic landfills considering methane oxidation and aerobic waste degradation. In this study, a numerical model is developed considering reactions to simulate the changes in methane, oxygen, and carbon dioxide concentrations in landfills during air injection and extraction. Parameter sensitivity analyses are conducted to evaluate the effects of permeability, dispersion coefficient, maximum methane oxidation rate, and oxygen consumption rate on simulation results. Results show that the model is sensitive to oxygen consumption rate. Overall, the application of this model in aerobic landfills provides a practical method to predict gas concentration variation. This model can be used in the optimal design of in situ aeration system.

Highly selective and sensitive WO[formula omitted] nanoflakes based ammonia sensor

Tungsten oxide (WO3) nanoflakes were grown directly on a seed layer-free Al2O3 substrate by a simple hydrothermal method. Process temperature and time were optimized for nanoflake formation on Al2O3 substrate. Samples were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), and X-ray photoelectron spectroscopy (XPS) techniques for structural, morphological and chemical composition analysis, respectively. Sensor measurements toward some volatile organics (VOCs) such as acetone, ethanol; and inorganic molecules such as ammonia (NH3), hydrogen cyanide (HCN) and nitrogen dioxide (NO2) were performed by varying gas concentrations at different temperatures. WO3 nanoflakes exhibited superior sensor response toward ammonia gas at a concentration as low as 1 ppm. The superior cross sensitivity and very high response to ammonia allow the developed sensor to be used as a potential platform for low level ammonia detection applications.

Origin and evolution of hydrogen-rich gas discharges from a hot spring in the eastern coastal area of China

Unlike the typical low-temperature (<150 °C) continental geothermal systems usually characterized by high N2, CH4 and CO2 concentrations but a trace H2 concentration, the sandstone-dominated Jimo hot spring on China's eastern coast exhibits: (1) abnormally high H2 concentrations (2.4–12.5 vol%) and H2/CH4 (up to 46.5); (2) depleted δD-H2 (−822 to −709‰), comparable to the Kansas hot springs near the Mid-Continent rift system with the most depleted δD-H2 (−836 to −740‰) recorded in nature; and (3) dramatic gas concentration and isotope ratio variations within an area of 0.2 km2. Gas chemistry and H-C-He-Ne isotope ratios are studied with reference to published H2 isotope data from various systems. The origin of the gas is most likely attributed to: (a) allochthonous abiotic H2 generated by the reduction of water and oxidation of FeII-rich pyroxene and olivine (serpentinization) in the basalt located 2 km away under near-surface conditions and migration to the deep sandstone reservoir; (b) primary thermogenic CH4 produced in the sandstone; (c) mixing with a considerable amount of microbial H2 from shallow fresh and marine sediments; and (d) biotic CH4 with typical abiotic signatures resulting from isotope exchanges with fluids high in H2/CH4 and CO2/CH4 ratios. Allochthonous abiotic H2 in a sandstone-dominated continental geothermal system and massive microbial fermentation-based H2 production in shallow fresh and residual marine sediments with insignificant but differential consumption activity are highlighted. The published hydrogen isotope ratios for H2 produced under various natural geological environmental and experimental conditions have been collected systematically to provide a fundamental framework and an initial tool for restricting the dominant origin of H2.