This study develops an integrated framework combining emergy analysis, carbon footprint accounting, and long short-term memory neural network modeling to investigate the effects of nature-based solutions on coastal ecosystem services and blue carbon functions from the perspective of river–coast connectivity. Three transects along a connectivity gradient were established in the Yellow River Delta, a typical large river delta in temperate China, covering riparian zones, estuarine transition areas, intertidal wetlands, and seagrass beds, with multi-source data collected over three consecutive hydrological years. Emergy–carbon coupling analysis based on this case study indicates that the high-connectivity transect shows a higher emergy yield ratio and net carbon sink compared to the low-connectivity transect, with salt marshes being most sensitive to connectivity change. Threshold analysis, specific to this delta, identifies a three-phase response pattern of carbon burial rate with increasing sediment connectivity, and reveals that wave attenuation efficiency declines notably when hydrological connectivity falls below approximately 0.5, although this value may vary across different coastal settings. A higher sea level rise rate raises the critical connectivity level required to maintain carbon sink function. The long short-term memory neural network trained on observational data achieves better prediction accuracy for blue carbon accumulation rates than traditional statistical methods, and SHAP value analysis suggests the possible existence of synergistic effects among connectivity dimensions. Based on these findings, three optimization strategies including tiered restoration, a dynamic pathway, and spatial configuration are proposed as case-specific recommendations for the Yellow River Delta. Framework-based simulations indicate the potential for connectivity-informed strategy adjustments to improve restoration efficiency under local conditions. This study concludes that river–coast connectivity represents an important lever regulating the ecological benefits of nature-based solutions, but emphasizes that all quantitative thresholds and benefit magnitudes reported here are case-specific estimates that require recalibration when applied to other coastal systems.

As a new type of unconventional natural gas resource, shale gas plays a vital role in energy supply. In order to deeply understand the shale fracture seepage characteristics, filled and unfilled fracture seepage tests were carried out on shale samples with different fracture surface topography with the use of self-developed shale fracture seepage testing equipment. The fitting formula that the seepage discharge decreased as a negative exponential function with the increase in normal stress was obtained in the unfilled fracture seepage test; the fitting coefficient had a good logarithmic and exponential function relationship with joint roughness coefficient JRC and surface development interface area ratio S_dr. Meanwhile, the modified cubic law was obtained by adding the correction coefficient. The correction coefficient had an exponential relationship with the anisotropy value K_a. Compared with the unfilled one, the fracture surface topography had little effect on the seepage discharge when it was filled. The experimental results show the effects of water head difference, fracture surface topography, particle size, and thickness of filling sand on shale fracture seepage characteristics under different normal stress conditions, which have a certain significance for improving the efficiency of shale gas production.

A comprehensive emergy-based evaluation framework was developed for coastal engineering–wetland coupled systems to quantitatively assess the carbon efficiency and sustainability of three representative engineering models: traditional hard engineering (Scenario A), ecological restoration engineering (Scenario B), and Nature-based Solutions (NbS) engineering (Scenario C). Through field investigations, engineering records, and remote sensing interpretation, key indicators including emergy-based carbon efficiency, Emergy Sustainability Index (ESI), spatial coupling degree, and path dependence coefficients were calculated, combined with system dynamics modeling. The results showed that the NbS model achieved the highest emergy-based carbon efficiency (0.547), which was 2.0 times that of Scenario B (0.271) and 260 times that of Scenario A (0.0021), with ESI values of 2.79, 0.814, and 0.084, respectively. A phased nonlinear relationship was identified between intervention intensity and system benefits, with a synergy–trade-off transition threshold of γ₁ = 0.58 and a high-input dependency trap threshold of γ₂ = 0.78. Spatial coupling degree was identified as the most critical mediating variable, with optimal configuration parameters of spatial coupling degree 0.68–0.75, engineering–wetland distance 12–18 m, and hydrological connectivity 0.65–0.75. Path dependence analysis revealed that the initial renewable emergy proportion significantly influenced later-stage ESI (α₁ = 1.86, p = 0.004), with trap-type sample points showing 5–18% declines. System dynamics modeling demonstrated that the moderate-input scenario achieved optimal long-term performance, surpassing the high-input scenario in carbon sequestration after year 20, and under the RCP8.5 climate scenario, the ecology-priority restoration strategy maintained a carbon pool retention rate of 85%. Based on these findings, a three-level hierarchical retrofitting strategy for traditional embankments and a full lifecycle emergy management system were proposed, providing a quantitative scientific basis for engineering model selection, intervention intensity control, spatial configuration optimization, and long-term planning in coastal blue carbon restoration projects.