Search Results (177)

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

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

Under the dual-carbon policy framework, geological CO₂ storage, particularly in saline aquifers, is pivotal to achieving national emission reduction targets. However, selecting geologically favorable storage sites demands quantitative assessment of complex geological factors—a task hindered by subjective traditional methods. To address this, the study employs an integrated approach combining multi-criteria decision analysis (Analytic Hierarchy Process and Fuzzy Comprehensive Evaluation) with multiphase flow simulations to investigate the Dezhou Subdepression in Shandong Province. The results indicate that the Dezhou Subdepression is moderately favorable for CO₂ geological storage, characterized by geologically optimal burial depth and favorable reservoir conditions. When the injection pressure increases from 1.1 times the original Group pressure (1.1P) to 1.5 times the original Group pressure (1.5P), the lateral migration distance of CO₂ expands by 240%, and the total storage capacity increases by approximately 275%. However, under 1.5P conditions, the CO₂ plume reaches the model boundary within 6.3 years, underscoring the increased risk of CO₂ leakage under high-pressure injection scenarios. This study provides strategic insights for policymakers and supports strategic planning for a CO₂ storage pilot project in the Dezhou Subdepression. It also serves as a reference framework for future assessments of CO₂ geological storage potential. Full article

To determine the long-term effect of Australian bushfires on the upper tropospheric composition in the South Pacific, we investigated the variation in CO and hydrocarbon species in the South Pacific according to the extent of Australian bushfires (2004–2020). We conducted analyses using satellite data on hydrocarbon and CO from the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS), and on fire (fire count, burned area, and fire radiative power) from the Moderate Resolution Imaging Spectroradiometer (MODIS). Additionally, we compared the effects of bushfires between Northern and Southeastern Australia (N_Aus and SE_Aus, respectively). Our analyses show that Australian bushfires in austral spring (September to November) result in the largest increase in CO and hydrocarbon species in the South Pacific and even in the west of South America, indicating the trans-Pacific transport of smoke plumes. In addition to HCN (a well-known wildfire indicator), CO and other hydrocarbon species (C₂H₂, C₂H₆, CH₃OH, HCOOH) are also considerably increased by Australian bushfires. A unique finding in this study is that the hydrocarbon increase in the South Pacific mostly relates to the bushfires in N_Aus, implying that we need to be more vigilant of bushfires in N_Aus, although the severe Australian bushfire in 2019–2020 occurred in SE_Aus. Due to the surface conditions in springtime, bushfires on grassland in N_Aus during this time account for most Australian bushfires. All results show that satellite data enables us to assess the long-term effect of bushfires on the air composition over remote areas not having surface monitoring platforms. Full article

Carbon Capture and Storage (CCS) is a critical strategy for reducing CO₂ emissions from hard-to-abate sectors. Reliable and efficient reservoir simulation tools are essential for supporting the safe and effective deployment of CCS projects. This study presents a twofold contribution to CCS modeling in saline aquifers: (1) the validation of the Black Oil Model (BoM) as a computationally efficient alternative to compositional simulators, and (2) a systematic assessment of the impact of grid resolution on plume prediction accuracy. The BoM was benchmarked against three commercial compositional simulators—Eclipse E300, CMG-GEM, and TNavigator. The comparison focused on key aspects of CO₂ storage operations, including plume evolution to assess containment and storage security, as well as injection safety and efficiency through pressure and saturation profile analysis, evaluated across both the injection and the post-closure monitoring phases. The BoM successfully reproduced plume extent and CO₂ saturation distributions, with mean deviations of 3% during injection, 5% during post-closure, and an overall average of 4% across the entire project duration. Additionally, simulation times were reduced by a factor of four compared to compositional models. These results confirm the BoM’s practical utility as a robust and efficient tool for CO₂ storage simulation. In parallel, the study investigated the influence of vertical and lateral grid resolutions/coarsening on the accuracy of CO₂ modeling. Seven models were developed and evaluated using a hybrid qualitative–quantitative framework, consistent with the BoM validation methodology. Vertical resolution was found to be particularly critical during the monitoring phase. While a 5 m resolution proved adequate during injection, deviations in plume shape and magnitude during post-injection increased to an average of 15% compared to a fine 2 m vertical resolution model, highlighting the necessity of fine vertical discretization (≤2 m) to capture gravity-driven plume dynamics during the monitoring phase. Conversely, lateral grid resolution had a stronger effect during the injection phase. A lateral cell size of 150 m was required for accurate plume prediction, with 200 m remaining moderately acceptable for early-phase assessment and prospect ranking, whereas coarser lateral grids led to significant underestimation of plume spread and dissolution extent. These findings demonstrate that the BoM, when combined with informed grid resolution strategies, enables accurate and computationally efficient simulation of CO₂ storage in saline aquifers. The study provides practical guidelines for fluid model selection and spatial discretization, offering critical input to subsurface experts involved in CCS project development, monitoring design, and regulatory compliance. Full article

Although the transition to electric vehicles (EVs) is well underway and expected to continue in global car markets, most vehicles on the world’s roads will be powered by internal combustion engine vehicles (ICEVs) and fossil fuels for the foreseeable future, possibly well past 2050. Thus, good environmental performance and effective emission control of ICE vehicles will continue to be of paramount importance if the world is to achieve the stated air and climate pollution reduction goals. In this study, we review 228 publications and identify four main issues confronting these objectives: (1) cheating by vehicle manufacturers, (2) tampering by vehicle owners, (3) malfunctioning emission control systems, and (4) inadequate in-service emission programs. With progressively more stringent vehicle emission and fuel quality standards being implemented in all major markets, engine designs and emission control systems have become increasingly complex and sophisticated, creating opportunities for cheating and tampering. This is not a new phenomenon, with the first cases reported in the 1970s and continuing to happen today. Cheating appears not to be restricted to specific manufacturers or vehicle types. Suspicious real-world emissions behavior suggests that the use of defeat devices may be widespread. Defeat devices are primarily a concern with diesel vehicles, where emission control deactivation in real-world driving can lower manufacturing costs, improve fuel economy, reduce engine noise, improve vehicle performance, and extend refill intervals for diesel exhaust fluid, if present. Despite the financial penalties, undesired global attention, damage to brand reputation, a temporary drop in sales and stock value, and forced recalls, cheating may continue. Private vehicle owners resort to tampering to (1) improve performance and fuel efficiency; (2) avoid operating costs, including repairs; (3) increase the resale value of the vehicle (i.e., odometer tampering); or (4) simply to rebel against established norms. Tampering and cheating in the commercial freight sector also mean undercutting law-abiding operators, gaining unfair economic advantage, and posing excess harm to the environment and public health. At the individual vehicle level, the impacts of cheating, tampering, or malfunctioning emission control systems can be substantial. The removal or deactivation of emission control systems increases emissions—for instance, typically 70% (NO_x and EGR), a factor of 3 or more (NO_x and SCR), and a factor of 25–100 (PM and DPF). Our analysis shows significant uncertainty and (geographic) variability regarding the occurrence of cheating and tampering by vehicle owners. The available evidence suggests that fleet-wide impacts of cheating and tampering on emissions are undeniable, substantial, and cannot be ignored. The presence of a relatively small fraction of high-emitters, due to either cheating, tampering, or malfunctioning, causes excess pollution that must be tackled by environmental authorities around the world, in particular in emerging economies, where millions of used ICE vehicles from the US and EU end up. Modernized in-service emission programs designed to efficiently identify and fix large faults are needed to ensure that the benefits of modern vehicle technologies are not lost. Effective programs should address malfunctions, engine problems, incorrect repairs, a lack of servicing and maintenance, poorly retrofitted fuel and emission control systems, the use of improper or low-quality fuels and tampering. Periodic Test and Repair (PTR) is a common in-service program. We estimate that PTR generally reduces emissions by 11% (8–14%), 11% (7–15%), and 4% (−1–10%) for carbon monoxide (CO), hydrocarbons (HC), and oxides of nitrogen (NO_x), respectively. This is based on the grand mean effect and the associated 95% confidence interval. PTR effectiveness could be significantly higher, but we find that it critically depends on various design factors, including (1) comprehensive fleet coverage, (2) a suitable test procedure, (3) compliance and enforcement, (4) proper technician training, (5) quality control and quality assurance, (6) periodic program evaluation, and (7) minimization of waivers and exemptions. Now that both particulate matter (PM, i.e., DPF) and NO_x (i.e., SCR) emission controls are common in all modern new diesel vehicles, and commonly the focus of cheating and tampering, robust measurement approaches for assessing in-use emissions performance are urgently needed to modernize PTR programs. To increase (cost) effectiveness, a modern approach could include screening methods, such as remote sensing and plume chasing. We conclude this study with recommendations and suggestions for future improvements and research, listing a range of potential solutions for the issues identified in new and in-service vehicles. Full article

Carbon capture and storage (CCS) plays a role in mitigating climate change, but effective implementation requires accurate prediction of CO₂ behavior in geological formations. This study introduces a novel machine learning framework for quantifying uncertainty across 2D and 3D carbon storage models. We develop a dimension-adaptive Bayesian neural network architecture that enables efficient knowledge transfer between dimensional representations while maintaining physical consistency. The framework incorporates aleatoric uncertainty from inherent geological variability and epistemic uncertainty from model limitations. Trained on over 5000 high-fidelity simulations across multiple geological scenarios, our approach demonstrates superior computational efficiency, reducing analysis time for 3D models by 87% while maintaining prediction accuracy within 5% of full simulations. The framework effectively captures complex uncertainty patterns in spatiotemporal CO₂ plume evolution. It identifies previously unrecognized parameter interdependencies, particularly between vertical permeability anisotropy and capillary entry pressure, which significantly impact plume migration in 3D models but are often overlooked in 2D representations. Compared with traditional Monte Carlo methods, our approach provides more accurate uncertainty bounds and enhanced identification of high-risk scenarios. This multidimensional framework enables rapid assessment of storage capacity and leakage risk under uncertainty, providing a practical tool for CCS site selection and operational decision-making across dimensional scales. Full article

To achieve the precise quantification and real-time monitoring of CO₂ emissions from stationary sources, this study developed a Gaussian plume model-based dispersion framework incorporating emission characteristics. Critical factors affecting CO₂ dispersion were systematically analyzed, with model optimization conducted through plume rise height adjustments and reflection coefficient calibrations. MATLAB-based simulations on an industrial park case study demonstrated that wind speed, atmospheric stability, and effective release height constituted pivotal determinants for enhancing CO₂ dispersion modeling accuracy. Furthermore, the inverse estimation of source strength at emission terminals was implemented via particle swarm optimization, establishing both theoretical foundations and methodological frameworks for the precision monitoring and predictive dispersion analysis of stationary-source CO₂ emissions. Full article

The 2020 wildfire season in the Western U.S. was historic in its intensity and impact on the land and atmosphere. This study aims to characterize satellite retrievals of carbon monoxide (CO), a tracer of combustion and signature of those fires, from two key satellite instruments: the Cross-track Infrared Sounder (CrIS) and the Tropospheric Monitoring Instrument (TROPOMI). We evaluate them during this event and assess their synergies. These two retrievals are matched temporally, as the host satellites are in tandem orbit and spatially by aggregating TROPOMI to the CrIS resolution. Both instruments show that the Western U.S. displayed significantly higher daily average CO columns compared to the Central and Eastern U.S. during the wildfires. TROPOMI showed up to a factor of two larger daily averages than CrIS during the most intense fire period, likely due to differences in the vertical sensitivity of the two instruments and representative of near-surface CO abundance near the fires. On the other hand, there was excellent agreement between the instruments in downwind free tropospheric plumes (scatter plot slopes of 0.96–0.99), consistent with their vertical sensitivities and indicative of mostly lofted smoke. Temporally, TROPOMI CO column peaks were delayed relative to the Fire Radiative Power (FRP), and CrIS peaks were delayed with respect to TROPOMI, particularly during the intense initial weeks of September, suggesting boundary layer buildup and ventilation. Satellite retrievals were evaluated using ground-based CO column estimates from the Network for the Detection of Atmospheric Composition Change (NDACC) and the Total Carbon Column Observing Network (TCCON), showing Normalized Mean Errors (NMEs) for CrIS and TROPOMI below 32% and 24%, respectively, when compared to all stations studied. While Normalized Mean Bias (NMB) was typically low (absolute value below 15%), there were larger negative biases at Pasadena, likely associated with sharp spatial gradients due to topography and proximity to a large city, which is consistent with previous research. In situ CO profiles from AirCore showed an elevated smoke plume for 15 September 2020, highlighted consistency between TROPOMI and CrIS CO columns for lofted plumes. This study demonstrates that both CrIS and TROPOMI provide complementary information on CO distribution. CrIS’s sensitivity in the middle and lower free troposphere, coupled with TROPOMI’s effectiveness at capturing total columns, offers a more comprehensive view of CO distribution during the wildfires than either retrieval alone. By combining data from both satellites as a ratio, more detailed information about the vertical location of the plumes can potentially be extracted. This approach can enhance air quality models, improve vertical estimation accuracy, and establish a new method for assessing lower tropospheric CO concentrations during significant wildfire events. Full article

The technical objective of a monitoring system is to provide the means to detect potential irregularities related to the project plan, to provide assurance that the migration of the CO₂ plume stays within the storage unit, and to show that CO₂ behaves in conformance with the model predictions. From an operational point of view, monitoring will also provide data that can be used to optimize the injection schedule relative to the storage capacity and availability of CO₂ to minimize risks and long-term costs. Finally, monitoring is a crucial factor for the public perception of risks related to CO₂ storage, as surveys indicate that adequately designed monitoring can mitigate concerns. The Analytical Hierarchy Process (AHP) is a holistic, transdisciplinary, multi-criteria decision-making framework. The objective of this work is to apply the AHP framework to monitoring-solutions for a synthetic geological storage site of CO₂ to secure the technical, operational, and societal embeddedness of the solutions and gain experience in how this can be applied to a real project. Through this first application of AHP within the field of geological carbon storage, the AHP was found to be a structured and transparent framework for holistic, multi-criteria decision-making (MCDM), where the wisdom and expertise of different domain experts were considered. A further novelty in this study is introducing a measure of spread in assessing the various solution alternatives’ capacity to meet monitoring criteria. This approach was utilized to underscore disparities among respondents’ experiences and to identify potential informational deficiencies in evaluating alternatives and devising the optimal monitoring solution. Full article

Worldwide, a growing list of critical (Bi, Co, Cu, F, Fe, Mo, Ni, P, PGE, REE, W, U, and Zn) and precious metal (Ag and Au) resources have been identified in mineral systems forming Fe-oxide-copper-gold (IOCG) deposits; Fe-oxide-apatite (IOA); Fe-sulfide Cu-Au (ISCG); and affiliated W skarn; Fe-rich Au-Co-Bi or Ni; albitite-hosted U or Au ± Co; and five-element (Ag, As, Co, Ni, and U) vein deposits. This paper frames the genesis of this metallogenic diversity by defining the Metasomatic Iron and Alkali-Calcic (MIAC) mineral system and classifying its spectrum of Fe-rich-to-Fe-poor and alkali-calcic deposits. The metasomatic footprint of MIAC systems consists of six main alteration facies, each recording a distinct stage of mineralization as systems have evolved. The fluid flow pathways and the thermal and chemical gradients inferred from the space–time distribution of the alteration facies within a system are best explained by the ascent and lateral propagation of a voluminous hypersaline fluid plume. The primary fluid plume evolves, chemically and physically, as metasomatism progresses and through periodic ingresses of secondary fluids into the plume. Exploration strategies can take advantage of the predictability and the expanded range of exploration targets that the MIAC system framework offers, the building blocks of which are the alteration facies as mappable prospectivity criteria for the facies-specific critical and precious metal deposits the systems generate. Global case studies demonstrate that these criteria are applicable to MIAC systems worldwide. Full article

Maritime transportation plays a vital role in global economic development but is also a significant contributor to air pollution, especially through emissions of SO₂, NO_x, and CO₂. Identifying non-compliance with fuel sulfur content regulations is crucial for mitigating these environmental impacts, yet current methods face challenges, particularly in the absence of reliable CO₂ concentration data. This study proposes a novel inverse calculation framework to estimate ship fuel sulfur content without relying on CO₂ measurements. An improved Gaussian plume line source model was tailored to the dispersion characteristics of ship emissions, with influencing factors evaluated under varying wind field conditions. The emission source intensity inversion was formulated as an unconstrained multi-dimensional optimization problem, solved using genetic algorithms. By incorporating ship fuel consumption data derived from basic ship information, the sulfur content of ship fuels was effectively estimated. Experimental evaluations using 30 days of monitoring data revealed that the method successfully identified 2743 ships, with an overall detection rate of 82.72%. Among them, 131 ships were flagged as suspected of using high-sulfur fuel, and 111 were confirmed to be non-compliant via sampling and laboratory testing, achieving an accuracy of 84.73%. These results demonstrate that the proposed approach offers a reliable and efficient solution for real-time fuel sulfur content monitoring and enforcement under diverse atmospheric conditions, contributing to improved environmental management of maritime transport emissions. Full article

The “top-down” global stocktake (GST) requires the processing of vast volumes of hyperspectral data to derive emission information, placing greater demands on data processing efficiency. Deep learning, leveraging its strengths in the automated and rapid analysis of image datasets, holds significant potential to enhance the efficiency and effectiveness of data processing in the GST. This paper develops a method for detecting carbon dioxide (CO₂) emission hotspots using a convolutional neural network (CNN) with short-lived and co-emitted nitrogen dioxide (NO₂) as a proxy. To address the data gaps in model parameter training, we constructed a dataset comprising over 210,000 samples of NO₂ plumes and emissions based on atmospheric dispersion models. The trained model performed well on the test set, with most samples achieving an identification accuracy above 80% and more than half exceeding 94%. The trained model was also applied to the NO₂ column data from the TROPOspheric Monitoring Instrument (TROPOMI) for hotspot detection, and the detections were compared with the MEIC inventory. The results demonstrate that in high-emission areas, the proposed method successfully identifies emission hotspots with an average accuracy of over 80%, showing a high degree of consistency with the emission inventory. In areas with multiple observations from TROPOMI, we observed a high degree of consistency between high NO₂ emission areas and high CO₂ emission areas from the Global Open-Source Data Inventory for Anthropogenic CO₂ (ODIAC), indicating that high NO₂ emission hotspots can also indicate CO₂ emission hotspots. In the future, as hyperspectral and high spatial resolution remote sensing data for CO₂ and NO₂ continue to grow, our methods will play an increasingly important role in global data preprocessing and global emission estimation. Full article

Geothermal energy is typically produced from underground reservoirs using water as the working fluid to transfer heat energy to surface and eventually to the delivery point. CO₂ has been proposed as an alternative working fluid due to its improved mobility, density and its supercritical phase state, leading thus to so-called CPG (CO₂ Plume Geothermal) systems. As a positive side effect, the injected CO₂ mass circulation in the reservoir can be considered a CO₂ storage mechanism, which, depending on the size of the porous medium, may account for few millions of CO₂ tons. Moreover, the thermosiphon effect, owned to the significant change of fluid density between the injection (cold) and the production wells (hot) as well as to its change along the wells, significantly reduces the need for pumping, hence the operating costs. In this work, we setup a mathematical model that fully describes flow in the production/injection wells doublet as well as in the geothermal reservoir. Subsequently, the model is used to evaluate the sensitivity of the beneficial effects of circulating CO₂ rather than water. Parameters such as reservoir properties, injection temperature and thermal effects, are tweaked to demonstrate the sensitivity of each one to the system performance. The results can be utilized as a guideline to the design of such systems and to the emphasis needed to be paid by the engineers. Full article