Search Results (219)

Carbon Capture and Storage (CCS) is a vital climate mitigation strategy aimed at reducing CO₂ emissions from industrial and energy sectors. This review presents a comprehensive analysis of CCS technologies, focusing on capture methods, transport systems, geological storage, geomechanical and geochemical aspects, modeling, risk assessment, monitoring, and economic feasibility. Among capture technologies, pre-combustion capture is identified as the most efficient (90–95%) due to its high purity and integration potential. Notably, most operational CCS projects in 2025 utilize pre-combustion capture, particularly in hydrogen production and natural gas processing. For geological storage, saline aquifers and depleted oil and gas reservoirs are highlighted as the most promising due to their vast capacity and proven containment. In the transport phase, pipeline systems are considered the most effective and scalable method, offering high efficiency and cost-effectiveness for large-scale CO₂ movement, especially in the supercritical phase. The study also emphasizes the importance of hybrid integrated risk assessment models, such as NRAP-Open-IAM, which combine deterministic simulations with probabilistic frameworks for robust site evaluation. In terms of monitoring, Seismic monitoring methods are regarded as the most reliable subsurface technique for tracking CO₂ plume migration and ensuring storage integrity. Economically, depleted reservoirs offer the most feasible option when integrated with existing infrastructure and supported by incentives like 45Q tax credits. The review concludes that successful CCS deployment requires interdisciplinary innovation, standardized risk protocols, and strong policy support. This work serves as a strategic reference for researchers, policymakers, and industry professionals aiming to scale CCS technologies for global decarbonization. Full article

The recently developed localized particle filter (LPF) is extended to a fully coupled general circulation model (CGCM), specifically the Community Earth System Model (CESM), to assess its efficacy in assimilating multisource ocean observations, including satellite sea surface temperature (SST) and in situ temperature and salinity (TS) profiles. The LPF introduces localization in the weighting and resampling steps to avoid the filter degeneracy problem, thereby enhancing its performance in assimilating nonlinear systems. Data assimilation experiments using real ocean observations reveal that the LPF has notable advantages in improving the quality of subsurface and deep ocean temperature and salinity, particularly below 200 m. The results are evaluated against objective analysis data, confirming the potential applicability of the LPF in operational settings. Furthermore, a comparative analysis with the ensemble adjustment Kalman filter (EAKF) elucidates the merits and limitations of the LPF, and further underscores the pronounced advantage of LPF in the deep ocean. However, when TS profiles are already assimilated, supplementing the LPF with additional SST data produces adverse effects, a behavior markedly different from that of the EAKF. This discrepancy signals the need for refined data pre-processing strategies within the LPF in real operational applications. Full article

Salinity extremes (SEs) play a crucial role in marine ecosystems, ocean circulation, and climate variability. Understanding their distribution and drivers is essential for predicting changes in ocean salinity under climate change, particularly in dynamic regions such as the Hawaiian Islands, where mesoscale eddies significantly modulate water mass properties. This study investigates the three-dimensional characteristics of SEs and their responses to mesoscale eddies using mooring observations and sea surface salinity data. We find that high salinity extremes (HSEs) generally occur more frequently than low salinity extremes (LSEs) in the study region, though LSEs exhibit greater duration and intensity. Mesoscale eddies modulate SEs significantly—anticyclonic eddies (AEs) enhance LSEs, whereas cyclonic eddies (CEs) promote HSEs in the upper layer. This relationship reverses in the deeper layer, with AEs favoring HSEs and CEs enhancing LSEs. These opposing effects are driven by a vertical displacement of the subsurface salinity maximum layer, where CEs lift high-salinity subsurface water to the upper ocean via upwelling, creating HSEs in the upper layer and LSEs in the deeper layer, while AEs subduct high-salinity water downward, reducing upper-layer salinity (LSEs) but increasing deeper-layer salinity (HSEs) via downwelling. Spatially, CEs exhibit a single-core high-salinity anomaly, displaced westward by 0.3 times of the eddy radius from the eddy center, with HSEs peaking in frequency and intensity near the core. In contrast, AEs display a dipole salinity anomaly (low northwest/high southeast), aligning with LSE frequency distribution, while HSEs show an inverse pattern. Mooring data further reveal that AE-LSE co-occurrence is highest within 1.2 times of the eddy radius, whereas CE-HSE probability declines with eddy intensity. Notably, AE-HSE and CE-LSE probabilities, though initially weaker, surpass AE-LSE and CE-HSE at certain depths, underlining the complexity of depth-dependent eddy modulation. These findings may advance understanding of ocean salinity dynamics and provide insights into how mesoscale processes modulate extreme events, with implications for marine biogeochemistry and climate modeling. Full article

In this paper, we develop a deep learning neural network characterized by feature fusion and physical guidance (denoted as FFPG-net) for reconstructing subsurface sea temperature (T) and salinity (S) from sea surface data. Designed with the idea of feature fusion, FFPG-net combines the deep learning algorithms of residual and channel attention with the physical constraints of vertical modes of T/S profiles decomposed by empirical orthogonal functions (EOFs). The results from a series of single point experiments show that FFPG-net outperforms the CNN or CNN-PG (without physical guidance or feature fusion) in the reconstruction of subsurface T/S in a region of the South China Sea (SCS), with monthly mean RMSEs of 0.31 °C (0.35 °C) and 0.06 psu (0.07 psu) for the reconstructed T/S profiles in winter (summer), averaged over the water depth of 1200 m and the study area. In addition, the performance of the FFPG-net can be improved significantly by incorporating full surface currents or geostrophic currents derived from SSH into the input variables for training the neural network. The preliminary application of FFPG-net in the SCS using satellite-derived sea surface observations indicates that FFPG-net is reliable and feasible for reconstructing subsurface ocean thermal fields in real situations. Our study highlights the advantages and necessity of combining deep learning algorithms with physical constraints in reconstructing subsurface T/S profiles. It provides an effective tool for reconstructing the subsurface global ocean from remote-sensing sea surface observations in the future. Full article

Numerical simulations are essential for optimizing CO₂ geological storage in deep saline aquifers; however, their substantial computational demands pose a significant challenge. This study introduces an automated machine learning (ML)-driven grid block classification framework applied to a realistic deep saline aquifer model to accelerate numerical simulations while maintaining accuracy. The methodology employs an ML and interquartile range-based classifier to distinguish grid blocks as either fast- or slow-varying. ML-based proxy models are applied exclusively to slow-varying regions, while traditional iterative methods handle dynamic, fast-varying regions. Results confirm a considerable reduction in computational costs without compromising predictive accuracy. Validated under realistic reservoir conditions, the approach demonstrates scalability and robustness, supporting efficient, accurate large-scale CO₂ storage simulations and advancing sustainable subsurface sequestration strategies. Full article

The impact of long-term organic (ECO) versus conventional (CON) agricultural management on subsurface soil microbiota diversity and soil physicochemical properties remains unclear in Mediterranean vineyards. This study evaluated long-term ECO and CON effects in the Alt Penedès terroir (Spain), focusing on subsurface soil microbial diversity and soil characteristics. ECO increased the fungal-to-bacterial ratio and ammonium-oxidizing bacteria but reduced total subsurface soil bacterial populations and soil organic carbon. While ECO did not enhance annual yield production in the vineyard, fungal abundance, and ammonium-oxidizing archaea, it slightly increased the overall alpha diversity (Shannon and Inverse Simpson indexes) and significantly altered taxa composition in subsurface soil with a more robust and modular community. Crop management, soil texture, training system, and rootstock, but not vine variety, significantly influenced beta diversity in subsurface soil. The Mantel test revealed subsurface soil texture, Ca²⁺/Mg²⁺ ratio, and salinity as the main key soil drivers shifting the microbial community (beta diversity), while C/N and topsoil organic matter significantly correlated with bacterial abundance; NH₄⁺ correlated with fungal abundance; and N-Kjeldahl, pH, and Mg²⁺/K⁺ correlated with alpha diversity. Integrating soil microbiota and physicochemical monitoring allowed us to confirm the positive effect of long-term agroecological practices on subsurface soil health and to identify the critical factors shaping their microbial communities in Mediterranean vineyards. Full article

Maximizing hydrocarbon recovery from mature and complex reservoirs is constrained by heterogeneity, sand production, and harsh operational conditions. While polyacrylamide (PAM)-based systems are pivotal in addressing these challenges, a comprehensive synthesis of their transformative evolution and multifunctional capabilities remains overdue. This review critically analyzes advancements in PAM-based materials for enhanced oil recovery (EOR), conformance control, and sand management. We show that nanomaterial integration (e.g., magnetic NPs, nanoclays) significantly augments PAM’s rheological control, thermal and salinity stability, interfacial properties, and wettability alteration. Furthermore, the emergence of supramolecular chemistry has endowed PAM systems with unprecedented resilience, enabling self-healing and adaptive performance under extreme subsurface conditions. The review highlights a crucial paradigm shift towards integrated reservoir management, synergizing these advanced chemical designs with mechanical strategies and leveraging sophisticated monitoring and predictive analytics. Critically, innovations in sustainable and bio-inspired PAM materials offer environmentally responsible solutions with enhanced biodegradability. This synthesis provides a holistic understanding of the state of the art. Despite persistent challenges in scalability and predictability, continually re-engineered PAM systems are positioned as an indispensable and increasingly sustainable cornerstone for future hydrocarbon recovery in the complex energy landscape. Full article

Global climate changes impact the Arctic seas by decreasing the sea ice area and changing the inorganic and organic matter supply via rivers and coastal permafrost thawing. Therefore, climate change may affect biogeochemical processes in the Kara Sea (KS) and Laptev Sea (LS), which form the Arctic Transpolar Drift. This study explores the effect of the KS shelf water supply on seawater parameters in the LS in late summer and early fall 2007, 2008, 2018, 2019, and 2024 using ship-borne (temperature, salinity, dissolved oxygen, nutrients, and pH), satellite-derived (sea surface heights, geostrophic current velocities), and model (current velocities) data. The results demonstrate that an inflow of KS shelf water with salinity of 33.0–34.5, high Apparent Oxygen Utilization values (50–110 µM), and increased concentrations of the dissolved inorganic phosphorus (DIP~ 0.7–1.2 µM), dissolved inorganic nitrogen (DIN~ 4–12 µM) and silicic acid (DSi~ 10–18 µM) enriches the subsurface layer of the LS with nutrients. The distributions of Atlantic—derived water (ADW) and KS shelf water in the LS from August to October depend on water dynamics caused by wind and river discharge. High Lena River discharge and westerly (downwelling favorable) winds promoted the supply of the KS shelf water to the LS through Vilkitsky Strait. In the area of the central trough of the LS, the KS shelf water can be modified by mixing with ADW. Mixing ADW with high DIN/DIP ratios (DIN~ 10 µM at DIP of 0.80 µM) and KS shelf water with low DIN/DIP ratios (DIN~ 8 µM at DIP of 0.80 µM) leads to changes in the DIN vs. DIP ratio in the subsurface layer of the LS. Full article

This study investigates ground deformations in the southeastern Po Plain (northern Italy), focusing on the Bologna area—a densely populated region affected by natural and anthropogenic subsidence. Ground deformations in the area result from geological processes (e.g., sediment compaction and tectonic activity) and human activities (e.g., ground water production and underground gas storage—UGS). We apply a multidisciplinary approach integrating subsurface geology, ground water production, advanced differential interferometry synthetic aperture radar—DInSAR, gas storage data, and land use information to characterize and analyze the spatial and temporal variations in vertical ground deformations. Seasonal and trend decomposition using loess (STL) and cluster analysis techniques are applied to historical DInSAR vertical time series, targeting three representatives areas close to the city of Bologna. The main contribution of the study is the attempt to correlate the lateral extension of ground water bodies with seasonal ground deformations and water production data; the results are validated via knowledge of the geological characteristics of the uppermost part of the Po Plain area. Distinct seasonal patterns are identified and correlated with ground water production withdrawal and UGS operations. The results highlight the influence of superficial aquifer characteristics—particularly the geometry, lateral extent, and hydraulic properties of sedimentary bodies—on the ground movements behavior. This case study outlines an effective multidisciplinary approach for subsidence characterization providing critical insights for risk assessment and mitigation strategies, relevant for the future development of CO₂ and hydrogen storage in depleted reservoirs and saline aquifers. Full article

High-resolution mooring observations captured diverse upper-ocean responses during typhoon passage, showing strong agreement with satellite-derived sea surface temperature and salinity. Analysis indicates that significant wind-induced mixing drove pronounced near-surface cooling and salinity increases at the mooring site. This mixing enhancement was predominantly governed by rapid intensification of near-inertial shear in the surface layer, revealed by mooring observations. Unlike shear instability, near-inertial horizontal kinetic energy displays a unique vertical distribution, decreasing with depth before rising again. Interestingly, the subsurface peak in diurnal tidal energy coincides vertically with the minimum in near-inertial energy. While both barotropic tidal forcing and stratification changes negligibly influence diurnal tidal energy emergence, significant energy transfer occurs from near-inertial internal waves to the diurnal tide. This finding highlights a critical tide–wave interaction process and demonstrates energy cascading within the oceanic internal wave spectrum. Full article

Deep saline aquifers in the eastern part of Drava Basin were screened for potential storage sites. The input dataset included three seismic volumes, a rather extensive set of old seismic sections and 71 wells. Out of all identified potential storage objects, only two sites were found to be situated in the favorable geological settings, meaning that the inspected wells drilled through structural traps had a seal at least 20 m thick which was intersected by only a few faults with rather limited displacement. Many more closed structures in the area were tested by exploration wells, but in all other wells, various problems were encountered, including inadequate reservoir properties, inadequate seal or inadequate depth of the identified trap. Analysis was highly affected by the insufficient quality and spatial distribution of the seismic input data, as well as in places with insufficient quality of input well datasets. An initial characterization of identified storage sites was performed, and their attributes were compared, with potential storage object B recognized as the one that should be further developed. However, given the depth and increased geothermal gradient of the potential storage object B, it is possible that it will be developed as a geothermal reservoir, and this brings forward the problem of concurrent subsurface use. Full article

Subsurface drainage and biochar application are conventional measures for improving saline–alkali soils. However, their combined effects on the fate of nitrogen (N) fertilizers remain unclear. This study investigated the combined effects of subsurface drainage and biochar amendment on the fate of nitrogen (N) in coastal saline–alkali soils, where these conventional remediation measures’ combined impacts on fertilizer N dynamics remain seldom studied. Using ¹⁵N-labeled urea tracing in an alfalfa–soil system, we examined how different drainage spacings (0, 6, 12, and 18 m) and biochar application rates (5, 10, and 15 t/ha) influenced N distribution patterns. Results demonstrated decreasing in drainage spacing and increasing in biochar application; these treatments enhanced ¹⁵N use efficiency on three harvested crops. Drainage showed more sustained effects than biochar. Notably, the combination of 6 m drainage spacing with 15 t/ha biochar application achieved optimal performance of ¹⁵N use, showing N utilization efficiency of 46.0% that significantly compared with most other treatments (p < 0.05). ¹⁵N mass balance analysis revealed that the plant absorption, the soil residual and the loss of applied N accounted for 21.6–46.0%, 38.6–67.5% and 8.5–18.1%, respectively. These findings provide important insights for optimizing nitrogen management in coastal saline–alkali agriculture, demonstrating that strategic integration of subsurface drainage (6 m spacing) with biochar amendment (15 t/ha) can maximize N use efficiency, although potential N losses warrant consideration in field applications. 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

Rapid urbanization and climate change are the driving forces behind changing the urban landscape and affecting natural resources and the environment, particularly in the megacities of arid regions. Many of these cities face an acute water crisis leading to over-exploitation of groundwater resources. This over-exploitation has led to the depletion of aquifers, land infertility, saline intrusion, land subsidence, and harm to hydrological ecosystems. Globally, numerous studies have documented the potential of groundwater recharge (GWR) using GIS and remote sensing techniques. However, its practical application in a landscape context for sustainable urban and regional development is underexplored. In this study, we developed the landscape-based GWR concept by conducting a case study of Karachi city (Pakistan). We took physical landscape (surface and sub-surface) features and groundwater recharge potential as a base for design and planning to improve groundwater recharge and urban landscape. Moreover, we highlighted the added values of this approach besides recharging the depleted ground hydrological conditions and improving the urban landscape condition (i.e., social–ecological inclusiveness, sustainable future development, and interdisciplinary collaboration). The results indicated a negative impact of urbanization on groundwater recharge, especially in the alluvial zones and river valleys, underscoring the need for a spatial approach to safeguard GWR and guide development. Through this study, we propose that landscape-based GWR can be one of the potential solutions not only for the critical water crisis faced by rapidly urbanizing arid megacities but also for improving the overall quality of life and urban landscape. Furthermore, this holistic approach toward groundwater recharge can guide future urban development patterns, preservation of high groundwater recharge potential sites, and evolution toward sustainable development in arid regions where groundwater is the most significant yet vulnerable resource. Full article

CO₂-switchable surfactants, applicable for mitigating CO₂ geological storage efficiency challenges, offer promising control over foam stability under reservoir conditions, but their performance under extreme pressure, temperature, and salinity still needs thorough investigation. This study experimentally characterizes the performance of CO₂-switchable surfactants by evaluating their interfacial tension (IFT) reduction, foamability, and foam stability under reservoir-relevant conditions. Six surfactants, including cationic (cetyltrimethylammonium bromide (CTAB) and benzalkonium chloride (BZK)) and nonionic amine-based surfactants (N,N-Dimethyltetradecylamine, N,N-Dimethyldecylamine, and N,N-Dimethylhexylamine), were assessed using synthetic brine mimicking a depleted North Sea oil reservoir. A fractional factorial design was employed to minimize experimental runs while capturing key interactions between surfactant type, temperature, salinity, and divalent ion concentrations. Foam switchability was analyzed by alternating CO₂ and N₂ injections, and interfacial properties were measured to establish correlations between foam generation and IFT. Experimental findings demonstrate that cationic surfactants (BZK and CTAB) exhibit CO₂-switchability and moderate foam stability. Nonionic surfactants show tail length-dependent responsiveness, where D14 demonstrated the highest foamability due to its optimal hydrophilic–hydrophobic balance. IFT measurements revealed that BZK consistently maintained lower IFT values, facilitating stronger foam generation, while CTAB exhibited higher variability. The inverse correlation between IFT and foamability was observed. These insights contribute to the development of tailored surfactants for subsurface CO₂ storage applications, improving foam-based mobility control in CCS projects. Full article