Search Results (274)

Accurate methane emission estimates are essential for climate policy, yet current field methods often struggle with spatial constraints and source complexity. Ground-based mobile approaches frequently miss key plume features, introducing bias and uncertainty in emission rate estimates. This study addresses these limitations by using small unmanned aerial systems equipped with precision gas sensors to measure methane alongside co-released tracers. We tested whether arc-shaped flight paths and alternative ratio estimation methods could improve the accuracy of tracer-based emission quantification under real-world constraints. Controlled releases using ethane and nitrous oxide tracers showed that (1) arc flights provided stronger plume capture and higher correlation between methane and tracer concentrations than traditional flight paths; (2) the cumulative sum method yielded the lowest relative error (as low as 3.3%) under ideal mixing conditions; and (3) the arc flight pattern yielded the lowest relative error and uncertainty across all experimental configurations, demonstrating its robustness for quantifying methane emissions from downwind plume measurements. These findings demonstrate a practical and scalable approach to reducing uncertainty in methane quantification. The method is well-suited for challenging environments and lays the groundwork for future applications at the facility scale. Full article

This work uses the MATLAB Reservoir Simulation Toolbox (MRST) to reduce the 3D reservoir model into a 2D version in order to investigate CO₂ storage in the Aurora model using the vertical equilibrium (VE) model. For this purpose, we used an open-source reservoir simulator, MATLAB Reservoir Simulation Toolbox (MRST). MRST is an open-source reservoir simulator, with supplementary modules added to enhance its versatility in addition to a core set of procedures. A fully implicit discretization is used in the numerical formulation of MRST-co2lab enabling the integration of simulators with vertical equilibrium (VE) models to create hybrid models. This model is then compared with the Eclipse model in terms of properties and simulation results. The relative permeability of water and gas can be compared to verify that the model fits the original Eclipse model. Comparing the fluid viscosities used in MRST and Eclipse also reveals comparable tendencies. However, reservoir heterogeneity is the reason for variations in CO₂ plume morphologies. The upper layers of the Eclipse model have lower permeability than the averaged MRST model, which has a substantial impact on CO₂ transport. According to the study, after 530 years, about 17 MT of CO₂ might be stored, whereas 28 MT might escape the reservoir, since after 530 years CO₂ plume reaches completely the open northern boundary. Additionally, a sensitivity analysis study has been conducted on permeability, porosity, residual gas saturation, rock compressibility, and relative permeability curves which are the five uncertain factors in this model. Although plume migration is highly sensitive to permeability, porosity, and rock compressibility variation, it shows a slight change with residual gas saturation and relative permeability curve in this study. Full article

Source inversion optimization using sensor observations is a key method for rapidly and accurately identifying unknown source parameters (source strength and location) in abrupt hazardous gas leaks. Sensor number and location distribution both play important roles in source inversion; however, their combined impacts on source inversion optimization remain poorly understood. In our study, the optimization inversion method is established based on the Gaussian plume model and the generation algorithm. A research strategy combining random sampling and coefficient of variation methods was proposed to simultaneously quantify their combined impacts in the case of a single emission source. The sensor layout impact difference was analyzed under varying atmospheric conditions (unstable, neutral, and stable) and source location information (known or unknown) using the Prairie Grass experiments. The results indicated that adding sensors improved the source strength estimation accuracy more when the source location was known than when it was unknown. The impacts of sensor location distribution were strongly negatively correlated (r ≤ −0.985) with the number of sensors across scenarios. For source strength estimation, the impacts of the sensor location distribution difference decreased non-linearly with more sensors for known locations but linearly for unknown ones. The impacts of sensor number and location distribution on source strength estimation were amplified under stable atmospheric conditions compared to unstable and neutral conditions. The minimum number of randomly scattered sensors required for stable source strength inversion accuracy was 11, 12, and 17 for known locations under unstable, neutral, and stable atmospheric conditions, respectively, and 24, 9, and 21 for unknown locations. The multi-layer arc distribution outperformed rectangular, single-layer arc, and downwind-axis distributions in source strength estimation. This study enhances the understanding of factors influencing source inversion optimization and provides valuable insights for optimizing sensor layouts. Full article

The blast furnace (BF) and basic oxygen route account for approximately 70% of the global steel production and create 1.8 tons of CO₂ per ton of steel, produced primarily due to the use of coke and pulverized coal (PC) at the BF. With global pressure to reduce CO₂ emissions, optimization of BF operation is crucial, which is possible through optimizing fuel consumption, and improving process stability. Understanding the complex combustion and flow dynamics in the raceway region is essential for enhancing reducing agent utilization. Modeling plays a key role in predicting these behaviors and providing insights into the process; however, validation of these models is crucial for their reliability but difficult in the complex and hostile BF raceway region. In this study, a validated raceway model developed at Swerim was used to evaluate four different cases, namely R1 (Reference), R2 (Low oxygen to blast), R3 (High blast moisture), and R4 (High PC) using an injection coal from SSAB Oxelösund. During actual experiments, the temperature distribution in the raceway was measured using a thermovision camera (TVC) to validate the CFD simulation results. The combined use aims to cross-validate the results simultaneously to establish a reliable framework for future parametric studies of raceway behavior under varying operational conditions using CFD simulations The results indicated that it is possible to measure the temperature within the raceway region using TVC at depths indicated to be 0.5–0.7 m, when not obscured by the coal plume, or <0.5 m, when obscured. TVC measurements are clearly quantitatively affected when obscured, indicated by considerably lower temperatures in the order of 200 °C between similar process conditions. A decrease of O₂ injection results in an extended raceway region as the conditions become less chemically favorable for combustion due to a lower reactant content offsetting the ignition point and reducing the reaction rate in the raceway. An increased moisture content in the blast results in a reduced size of the race-way region as energy is consumed as latent energy and cracks water. An increase in PC rate results in a larger/wider raceway region, as more PC is devolatilized and combusted early on, resulting in larger gas volumes expanding the raceway region outwards, perpendicular to the injection. Full article

Ammonium nitrate (NH₄NO₃) is a major constituent of fine particulate matter (PM_2.5), playing a critical role in air quality and atmospheric chemistry. However, the dual regulatory role of ammonia (NH₃) in both the formation and volatilization of NH₄NO₃ under ambient atmospheric conditions remains inadequately understood. To address this gap, we conducted high-resolution field measurements at a clean tropical coastal site in China using an integrated system of Aerosol Ion Monitor-Ion Chromatography, a Scanning Mobility Particle Sizer, and online OC/EC analyzers. These observations were complemented by thermodynamic modeling (E-AIM) and source apportionment via a Positive Matrix Factorization (PMF) model. The E-AIM simulations revealed persistent thermodynamic disequilibrium, with particulate NO₃⁻ tending to volatilize even under NH_3gas-rich conditions during the northeast monsoon. This suggests that NH₄NO₃ in PM_2.5 forms rapidly within fresh combustion plumes and/or those modified by non-precipitation clouds and then undergoes substantial evaporation as it disperses through the atmosphere. Under the southeast monsoon conditions, reactions constrained by sea salt aerosols became dominant, promoting the formation of particulate NO₃⁻ while suppressing NH₄NO₃ formation despite ongoing plume influence. In scenarios of regional accumulation, elevated NH₃ concentrations suppressed NH₄NO₃ volatilization, thereby enhancing the stability of particulate NO₃⁻ in PM_2.5. PMF analysis identified five source factors, with NO₃⁻ in PM_2.5 primarily associated with emissions from local power plants and the large-scale regional background, showing marked seasonal variability. These findings highlight the complex and dynamic interplay between the formation and evaporation of NH₄NO₃ in NH_3gas-rich coastal atmospheres. Full article

In this article, we consider the roles of transcrustal magma- and fluid-conducting faults (TCMFCFs) in the formation of mineral deposits, showing the importance of deep sources of heat and hydrothermal solutions in the genesis and history of deposit formation. As a result of the impact on the lithosphere of mantle plumes rising along TCMFCFs, intense block deformations and tectonic movements are generated; rift systems, and volcanic–plutonic belts spatially combined with them, are formed; and intrusive bodies are introduced. These processes cause epithermal ore formation as a consequence of the impact of mantle plumes rising along TCMFCF to the lithosphere. At hydrocarbon fields, they play extremely important roles in conductive and convective heat, as well as in mass transfer to the area of hydrocarbon generation, determining the relationship between the processes of lithogenesis and tectogenesis, and activating the generation of hydrocarbons from oil and gas source rock. Detection of TCMFCFs was carried out using MMSS (the method of microseismic sounding) and MTSM (the magnetotelluric sounding method), in combination with other geological and geophysical data. Practical examples are provided for mineral deposits where subvertical transcrustal columns of increased permeability, traced to considerable depths, have been found; the nature of these unique structures is related to faults of pre-Paleozoic emplacement, which determined the fragmentation of the sub-crystalline structure of the Earth and later, while developing, inherited the conditions of volumetric fluid dynamics, where the residual forms of functioning of fluid-conducting thermohydrocolumns are granitoid batholiths and other magmatic bodies. Experimental modeling of deep processes allowed us to identify the quantum character of crystal structure interactions of minerals with “inert” gases under elevated thermobaric conditions. The roles of helium, nitrogen, and hydrogen in changing the physical properties of rocks, in accordance with their intrastructural diffusion, has been clarified; as a result of low-energy impact, stress fields are formed in the solid rock skeleton, the structures and textures of rocks are rearranged, and general porosity develops. As the pressure increases, energetic interactions intensify, leading to deformations, phase transitions, and the formation of chemical bonds under the conditions of an unstable geological environment, instability which grows with increasing gas saturation, pressure, and temperature. The processes of heat and mass transfer through TCMFCFs to the Earth’s surface occur in stages, accompanied by a release of energy that can manifest as explosions on the surface, in coal and ore mines, and during earthquakes and volcanic eruptions. Full article

The identification of leakage sources in underwater natural gas pipelines (UNGPs) remains a critical challenge due to complex environmental conditions. In this study, we propose a novel simulation–optimization method, integrating numerical bubble plume dynamics models with surrogate models to enable accurate leakage parameter inversion. First, a bubble plume underwater motion simulation model was developed based on the actual conditions of the study area to predict the future spatial and temporal variation characteristics of the bubble plumes in certain wave fields. Then, the simulation–optimization method was applied to determine the leakage velocity and offset distance of the underwater gas pipeline leakage source via inversion. To reduce the computational load of the optimization model by repeatedly invoking the simulation model, the Kriging method and a backpropagation (BP) neural network were used to build surrogate models for the numerical model. Finally, the optimized surrogate model was solved using the simulated annealing method, and the inverse identification results were obtained. The experimental results show that both methods can achieve a high inversion accuracy. The relative error of the Kriging model is no more than 12%, and the running time is 13 min. Meanwhile, based on the BP neural network surrogate model, the relative error of the BP neural network model is about 14%, and the running time is 2.5 min. Full article

Mixing time, as a key parameter for evaluating ladle refining efficiency, has long attracted extensive attention from researchers. In typical experimental studies, salt solution tracers are introduced into ladle water models to assess the degree of mixing within the ladle. Previous studies have demonstrated that the volume of tracer can significantly influence the measured mixing time. However, the gas flow rates employed in these studies are generally relatively high, whereas, in industrial operations, especially during final composition adjustments, lower gas flow rates are often applied. To systematically investigate the effect of the salt solution tracer volume on the mixing efficiency in a ladle water model under asymmetrical gas stirring with a low gas flow rate, a 1:3-scaled water model was developed based on a 130-ton industrial ladle. The mixing behaviors corresponding to different tracer volumes were comprehensively analyzed. The results indicate that the relationship between tracer volume and mixing time is non-monotonic. As the tracer volume increases, the mixing time first decreases and then increases, reaching a minimum at 185 mL. When the tracer volume was small, the dimensionless concentration curves at Monitoring Point 4 exhibited two distinct patterns: A parabolic profile, which was when the tracer initially moved through the left and central regions and then slowly crossed the gas plume to reach the monitoring point. A sinusoidal profile, which was when the tracer predominantly circulated along the right side of the ladle. When the tracer volume exceeded 277 mL, the concentration curves at Monitoring Point 4 consistently exhibited a sinusoidal pattern. Compared with moderate gas flow conditions (8.3 L/min), the peak concentration at Monitoring Point 3 was significantly lower under a low gas flow (2.3 L/min), and the overall mixing time was longer, indicating reduced mixing efficiency. Based on the findings, a recommended tracer volume range of 185–277 mL is proposed for low gas flow conditions (2.3 L/min) to achieve accurate and efficient mixing time measurements with minimal disturbance to the flow field. It was also observed that when the tracer concentration was relatively low, the mixing behavior throughout the ladle became more uniform. Full article

Since pre-industrial times, anthropogenic methane emissions have increased and are partly responsible for a changing global climate. Natural gas and oil extraction activities are one significant source of anthropogenic methane. While methods have been developed and refined to quantify onshore methane emissions, the ability of methods to directly quantify emissions from offshore production facilities remains largely unknown. Here, we review recent studies that have directly measured emissions from offshore production facilities and critically evaluate the suitability of these measurement strategies for emission quantification in a marine environment. The average methane emissions from production platforms measured using downwind dispersion methods were 32 kg h⁻¹ from 188 platforms; 118 kg h⁻¹ from 104 platforms using mass balance methods; 284 kg h⁻¹ from 151 platforms using aircraft remote sensing; and 19,088 kg h⁻¹ from 10 platforms using satellite remote sensing. Upon review of the methods, we suggest the unusually large emissions, or zero emissions observed could be caused by the effects of a decoupling of the marine boundary layer (MBL). Decoupling can happen when the MBL becomes too deep or when there is cloud cover and results in a stratified MBL with air layers of different depths moving at different speeds. Decoupling could cause: some aircraft remote sensing observations to be biased high (lower wind speed at the height of the plume); the mass balance measurements to be biased high (narrow plume being extrapolated too far vertically) or low (transects miss the plume); and the downwind dispersion measurements much lower than the other methods or zero (plume lofting in a decoupled section of the boundary layer). To date, there has been little research on the marine boundary layer, and guidance on when decoupling happens is not currently available. We suggest an offshore controlled release program could provide a better understanding of these results by explaining how and when stratification happens in the MBL and how this affects quantification methodologies. Full article

Nowadays, industries and society are very concerned about pollution, well-being, health, air quality, and the possible negative effects of industrial emissions on a property’s surroundings. This gas dispersion is typically estimated with Gaussian Plume/Puff Models or software that uses these models with slight adjustments. The issue regarding these models is that they do not consider the surroundings’ particularities, for instance, when obstacles are present, and they require experimental data to adapt to specific scenarios. Therefore, the aim of this work is to validate the use of ANSYS Fluent^® 2022 R1 for modelling atmospheric gas dispersion. This validation is performed by comparing the ANSYS Fluent^® 2022 R1 findings to published experimental data, Gaussian Plume Models (GPM in this case corresponds to the application of the Gaussian Equation or Gaussian Fit, and does not correspond to a specific dispersion model), and ALOHA 5.4.7 software. A comparison between these three alternatives was not available in the literature. In terms of downwind dispersion, the findings of the three models are extremely comparable. However, ANSYS Fluent^® has a propensity to overestimate the concentration at higher heights. Validation using ANSYS Fluent^® in atmospheric gas dispersion applications enables confident results to be obtained in other scenarios. Differences in pollutant estimation between models are clear when studying more complex cases containing turbulence-inducing geometries. In these cases, CFD exhibits a more realistic description of the transport phenomena than the other models considered. The Prairie Grass Project is used as a tool to validate the CFD model, and to demonstrate its potential for more complex cases. Full article

Accurate quantification of metallic contaminants in rocket exhaust plumes serves as a critical diagnostic indicator for engine wear monitoring. This paper develops a hybrid method combining atomic emission spectroscopy (AES) theory with a genetic algorithm (GA) optimized backpropagation (BP) network to quantify the metallic element concentrations in liquid-propellant rocket exhaust plumes. The proposed method establishes linearized intensity–concentration mapping through the introduction of a photon transmission factor, which is derived from radiative transfer theory and experimentally calibrated via AES measurement. This critical innovation decouples the inherent nonlinearities arising from self-absorption artifacts. Through the use of the transmission factor, the training dataset for the BP network is systematically constructed by performing spectral simulations of atomic emissions. Finally, the trained network is employed to predict the concentration of metallic elements from the measured atomic emission spectra. These spectra are generated by introducing a solution containing metallic elements into a CH₄-air premixed jet flame. The predictive accuracy of the method is rigorously evaluated through 32 independent experimental trials. Results show that the quantification error of metallic elements remains within 6%, and the method exhibits robust performance under conditions of spectral self-absorption, demonstrating its reliability for rocket engine health monitoring applications. Full article

In marine seismic surveys, weak signals can be overlaid by stronger signals or even random noise. Detecting these signals can be challenging, especially when they are close to each other or partially overlapping. Several normalization methods have already been proposed, but they often lead to distortion. In this paper, we show that the unwrapped instantaneous phase of the associated analytical signal is an effective detection tool and validate it using synthetic and real data examples. This approach does not require user-defined parameters and therefore does not introduce personal bias in the results. We show that weak signals from submarine fluid plumes can be successfully detected by seismic surveys. These plumes can reveal anomalies in shallow sediments such as near-surface gas pockets and soft formations, which can severely affect offshore structures such as platforms and wind farms. Full article

As global atmospheric methane concentrations surge at an unprecedented rate, the identification of methane super-emitters with significant mitigation potential has become imperative. In this study, we utilize remote sensing satellite data with varying spatiotemporal coverage and resolutions to detect and quantify methane emissions. We exploit the synergistic potential of Sentinel-2, EnMAP, and GF5-02-AHSI for methane plume detection. Employing a matched filtering algorithm based on EnMAP and AHSI, we detect and extract methane plumes within emission hotspots in China and the United States, and estimate the emission flux rates of individual methane point sources using the IME model. We present methane plumes from industries such as oil and gas (O&G) and coal mining, with emission rates ranging from 1 to 40 tons per h, as observed by EnMAP and GF5-02-AHSI. For selected methane emission hotspots in China and the United States, we conduct long-term monitoring and analysis using Sentinel-2. Our findings reveal that the synergy between Sentinel-2, EnMAP, and GF5-02-AHSI enables the precise identification of methane plumes, as well as the quantification and monitoring of their corresponding sources. This methodology is readily applicable to other satellite instruments with coarse SWIR spectral bands, such as Landsat-7 and Landsat-8. The high-frequency satellite-based detection of anomalous methane point sources can facilitate timely corrective actions, contributing to the reduction in global methane emissions. This study underscores the potential of spaceborne multispectral imaging instruments, combining fine pixel resolution with rapid revisit rates, to advance the global high-frequency monitoring of large methane point sources. Full article

Methane is the second largest greenhouse gas. The detection of methane super-emitters and the quantification of their emission rates are necessary for the implementation of methane emission reduction policies to mitigate global warming. High-spectral-resolution satellites such as Gaofen-5 (GF-5), EMIT, GHGSat, and MethaneSAT have been successfully employed to detect and quantify methane point source leaks. In this study, a matched filter (MF) algorithm is improved using data from the EMIT instrument and applied to data from the Advanced Hyperspectral Imager (AHSI) onboard the Ziyuan-1 (ZY-1) satellite. Validation by comparison with EMIT′s L2 XCH₄ products shows the good performance of the improved MF algorithm, in spite of the lower spectral resolution of AHSI/ZY-1 in comparison with other point source imagers. The improved MF algorithm applied to AHSI/ZY-1 data was used to detect and quantify methane super-emitters in global methane hotspot regions. The results show that the improved MF algorithm effectively suppresses noise in retrieval results over both land and ocean surfaces, enhancing algorithm robustness. Sixteen methane plumes were detected in global hotspot regions, originating from coal mines, oil and gas fields, and landfills, with emission rates ranging from 0.57 to 78.85 t/h. The largest plume was located at an offshore oil and gas field in the Gulf of Mexico, with instantaneous emissions nearly equal to the combined total of the other 15 plumes. The findings demonstrate that AHSI, despite its lower spectral resolution, can detect sources with emission rates as small as 571 kg/h and achieve faster retrieval speeds, showing significant potential for global methane monitoring. Additionally, this study highlights the need to focus on methane emissions from marine sources, alongside terrestrial sources, to efficiently implement reduction strategies. Full article

The Beishan Orogenic Belt, situated along the southern margin of the Central Asian Orogenic Belt, represents a critical tectonic domain that archives the prolonged subduction–accretion processes and Paleo-Asian Ocean closure from the Early Paleozoic to the Mesozoic. Early Permian magmatism, exhibiting the most extensive spatial-temporal distribution in this belt, remains controversial in its geodynamic context: whether it formed in a persistent subduction regime or was associated with mantle plume activity or post-collisional extension within a rift setting. This study presents an integrated analysis of petrology, zircon U-Pb geochronology, in situ Hf isotopes, and whole-rock geochemistry of Early Permian granites from the Tiancang area in the southern Beishan Orogenic Belt, complemented by regional comparative studies. Tiancang granites comprise biotite monzogranite, monzogranite, and syenogranite. Zircon U-Pb dating of four samples yields crystallization ages of 279.3–274.1 Ma. These granites are classified as high-K calc-alkaline to calc-alkaline, metaluminous to weakly peraluminous I-type granites. Geochemical signatures reveal the following: (1) low total rare earth element (REE) concentrations with light REE enrichment ((La/Yb)_N = 3.26–11.39); (2) pronounced negative Eu anomalies (Eu/Eu* = 0.47–0.71) and subordinate Ce anomalies; (3) enrichment in large-ion lithophile elements (LILEs: Rb, Th, U, K) coupled with depletion in high-field-strength elements (HFSEs: Nb, Ta, P, Zr, Ti); (4) zircon ε_Hf(t) values ranging from −10.5 to −0.1, corresponding to Hf crustal model ages (T_DMC) of 1.96–1.30 Ga. These features collectively indicate that the Tiancang granites originated predominantly from partial melting of Paleoproterozoic–Mesoproterozoic crustal sources with variable mantle contributions, followed by extensive fractional crystallization. Regional correlations demonstrate near-synchronous magmatic activity across the southern/northern Beishan and eastern Tianshan Orogenic belts. The widespread Permian granitoids, combined with post-collisional magmatic suites and rift-related stratigraphic sequences, provide compelling evidence for a continental rift setting in the southern Beishan during the Early Permian. This tectonic regime transition likely began with lithospheric delamination after the Late Carboniferous–Early Permian collisional orogeny, which triggered asthenospheric upwelling and crustal thinning. These processes ultimately led to the terminal closure of the Paleo-Asian Ocean’s southern branch, followed by intracontinental evolution. Full article