Certain limitations and assumptions that affect

The gap

Evidence profile

Sourced from the limitations and abstract and limitations section of the source papers, classified as general, spanning 3 journals.

Supporting evidence — 3 representative gaps

• Deployment-scale CO2 storage capacity and suitability assessment in the Subei Basin, China using a stratified and grid-based framework (2026) · Environmental Earth Sciences · doi

  Although the sensitivity analysis enhances interpretabil- ity, some limitations remain. First, the current framework applies static AHP-derived weights, which may not fully capture spatial variability or site-specific uncertainties. Sensitivity analysis indicates that certain medium-weight indicators, such as reservoir permeability and unit capac- ity, exert disproportionate influence in specific layers, sug- gesting that layer-specific weighting strategies may improve model realism. Second, the analysis is constrained by the availability and spatial resolution of input datasets. Fault and seismic data are commonly mapped at the basin scale and may therefore overlook local-scale heterogeneity. Similarly, lithology and sedimentary facies are represented using formation-scale characteristics due to limited lateral coverage, restricting Fig. 14 Sensitivity analysis of CO2 storage suitability across five stratified reservoir layers 1 3Environmental Earth Sciences (2026) 85:287 explicit quantification of fine-scale facies-controlled capac- ity variations. Recent studies have further highlighted the importance of incorporating geological heterogeneity into regional CCS assessments (Li et al. 2025). In addition to data-related constraints, uncertainty also arises from methodological assumptions. Storage capacity estimates are based on a deterministic volumetric approach that does not explicitly quantify probabilistic uncertainty. Major uncertainty sources include unresolved basin-scale heterogeneity, simplified lithological assumptions within formations, and the use of representative parameter values where data density is limited. Given current data resolution and coverage, probabilistic or Monte Carlo-based analy- ses were not applied to avoid over-interpretation. Instead, uncertainty is addressed through sensitivity analysis, focus- ing on identifying influential indicators rather than defining absolute uncertainty bounds. Recent studies have emphasized interactions between CO₂ storage and underground coal resource development in coal-bearing basins (Lin et al. 2025b). However, economi- cally exploitable coal seams are absent in the Subei Basin, and coal-related constraints therefore do not constitute a con- trolling factor in the present assessment. In addition, long- term storage security and potential environmental impacts associated with leakage pathways remain important consid- erations for CCS deployment (Plampin and Merrill 2025). Future research should incorporate higher-resolution geological surveys, probabilistic weighting methods, and scenario-based perturbation schemes to further refine uncertainty characterization. Emerging approaches inte- grating machine learning with geological modeling may improve prediction efficiency and uncertainty awareness in large-scale CO₂ storage assessments (Lin et al. 2025a). In addition, future deployment-oriented studies may benefit from integrating refined regional storage characterization, dynamic injection strategies, pressure management, and long-term containment behavior into regional assessment frameworks (Gasanzade and Bauer 2025; Dutta et al. 2025). Implications for CCS deployment in China The sensitivity results have direct implications for CO2 storage deployment strategies in China. The dominance of geological stability indicators underscores the neces- sity of rigorous site screening and exclusion of seismically active zones, regardless of depth. The strong sensitivity of source–sink indicators, particularly in shallow layers, highlights the potential for near-source storage hubs to minimize transportation costs and accelerate early deploy- ment. By contrast, deep formations such as DN1 and DN2 Page 15 of 18 287 exhibit relatively stable suitability with respect to reservoir property indicators, suggesting their role as long-term, large-capacity sinks that are less dependent on marginal variations in reservoir quality. Overall, the combination of stratified evaluation and sen- sitivity analysis demonstrates that a differentiated, multi- layered deployment strategy is essential. Rather than a one-size-fits-all approach, shallow layers should prioritize economic proximity and rapid deployment, middle layers require balancing storage capacity with safety, and deep layers should be reserved for large-scale, secure, long-term sequestration (Lin et al. 2025c). These findings provide both methodological and policy-level insights, strengthening the scientific basis for China’s carbon neutrality roadmap.

  generallimitationsevidence 5/5
  Keywords: storage scale uncertainty sensitivity layers deployment indicators reservoir geological coal long term specific strategies resolution
• Struktura zmienności parametrów polskich złóż węgla kamiennego – spojrzenie na cztery dekady badań geostatystycznych (2026) · Przegląd Geologiczny · doi

  The main factors limiting both the generalization and the geological interpretation of the variability structure include: frequently insufficient data sets (particularly in categories C 1 and C 2 ), the unknown magnitude of sampling errors and their impact on semivariogram shape, evolving criteria for deposit classification, uncertainty in seam correlation, and the use of different semivariogram estimators.

  generalabstractevidence 5/5
  Keywords: semivariogram main factors limiting generalization geological interpretation variability structure include frequently insufficient sets particularly categories
• GEOGRAPHIC INFORMATION SYSTEM APPLICATION FOR PROSPECTING THE SANDSTONE-TYPE URANIUM DEPOSIT IN THE MELAWI REGION, WEST KALIMANTAN, INDONESIA (2026) · Rudarsko-geološko-naftni zbornik · doi

  The study reveals certain limitations and assumptions that affect the precision and reliability of the analysis. The model may benefit from refinement, particularly in regions with limited data resolution, complex structural histories, or ambiguous geochemical signatures.

  generallimitations sectionevidence 5/5
  Keywords: study reveals certain limitations assumptions affect precision reliability

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