In the context of ecological building and green building popularity, building sustainability assessment is becoming more and more important. In this paper, a comprehensive evaluation platform by coupled LCA method and energy method was designed, verified, and analyzed to assess the sustainability of the building system. The main results illustrated that the construction stage is the most critical stage in terms of emergy angle. From a sustainability perspective, the Emergy Sustainability Indicator was at a moderate level (1.0141), which can be considered to increase the proportion of renewable energy and reduce the proportion of non-renewable resources to improve the sustainability degree. Of the three scenarios designed, the second scenario has the best sustainability in the building system. The unit emergy value of the whole building was also shown to demonstrate the unit emergy of an individual. In order to verify the accuracy of the data, a sensitivity analysis was conducted. Finally, two types of positive measures are proposed to ameliorate the environmental sustainability in the building system, containing the increasing proportion of renewable energy and using recycled building materials.

Bioretention systems are a low-impact development (LID) measure to effectively control stormwater runoff and reduce pollutant concentrations. In this paper, three groups of bioretention cells with different filling materials (1# bioretention soil media (BSM), 2# BSM + 5% biochar, and 3# BSM +5% biochar +biological filler) were constructed to analyze the pollutant removal characteristics and microbial action under different simulated rainfall conditions. Results showed that the overall pollutant removal capacity of systems 2# and 3# was higher than that of system 1#, with system 3# having the lowest effluent concentrations of 2.71 mg/L for total nitrogen (TN) and 64.3 mg/L for chemical oxygen demand (COD). The load reduction effect for heavy metals of the three systems was ranked as 2# > 1# > 3#, and average load reduction rates were 80.3, 75.1, and 84.8% for Cu, Pb, and Zn in 2#. Microbial community analysis indicated that Proteobacteria and Firmicutes were the absolute dominant bacteria of the three bioretention systems, and the dominant genera included Bacillus, Hyphomicrobium, Micrococcaceae, and Nitrospira. In addition, the total number of denitrifying functional bacteria genera in systems 2# and 3# was increased by 1.39 and 52.1% compared to system 1#.

As one of the highest energy and resource consumption industries in China, discussion on the sustainability of the cement production system has great significance. This study conducted sustainable calculations and analyses for cement production systems based on the emergy method. This study also considers the sustainability impact of clean energy on the overall cement production system. Through a series of sustainable indicator measurements, the results prove that: (1) the two primary sections, non-renewable resource and non-renewable energy, contribute 88.6% and 11.1% of the emergy proportion, respectively; (2) the emergy sustainability indicator (ESI) was only 0.058, which is significantly less than the standard; (3) through the analysis of eight hypotheses, a very small change between the absolute values was found, which demonstrates that the sensitivity changes are within acceptable limits for the cement production system; and (4) by integrating the biological power generation subsystem, sustainability has been optimized in the cement production system. Finally, two ameliorated strategies are discussed in this paper for the better sustainability performance of the cement production system in the future.

Sustainable building systems can effectively reduce environmental pressures and mitigate the deterioration of the global climate. The sustainability of complex building systems is influenced by various factors. This article quantitatively analyzes building systems from an ecological emergy and carbon emissions perspective, and considers typical feedback structures’ impact. A neural network algorithm is employed for sustainability prediction analysis. The results demonstrate that both from an emergy and carbon emissions perspective, the operational phase of the building and the production phase of building materials are the main contributors (accounting for over 90%). Among the three types of feedback subsystems, the cross-feedback structure has a more significant impact and yields the best corrective effect. For example, the correction proportion of the building’s emergy sustainability parameter reaches 11.3%, while it is 15.8% for carbon emissions. The neural network model predicts a decreasing trend in the energy sustainability of buildings and increasing carbon emissions over time. To improve the sustainability of building systems, measures such as ecological landscape design and carbon sequestration in building materials are considered, which can enhance the sustainability of buildings to a certain extent.

Against the background of climate change intensifying extreme hail events, the photovoltaic module industry faces a critical trade-off between improving hail resistance and maintaining environmental sustainability. This study establishes an emergy–life cycle coupling assessment framework to systematically evaluate the environmental sustainability of six typical hail resistance enhancement designs across four hail risk scenarios in China. Five hierarchical hypotheses are proposed and validated through quantitative analysis. The optimal design point occurs at 30 mm hail resistance using 3.2 mm tempered glass, achieving a minimum unit environmental impact per impact resistance UEIC of 9.63 × 10¹² sej/mm. The ranking divergence index SDR between coupled emergy–LCA and conventional LCA methods is 0.267, with ecosystem service dependence ESD reaching 0.241 for composite backsheet designs, revealing natural capital overlooked by traditional methods. A complete ranking reversal occurs at a threshold hail frequency of 1.3 events per year, above which the 3.2 mm glass design outperforms standard modules with life cycle emergy input LCEA of 3.20 × 10¹⁴ sej versus 3.41 × 10¹⁴ sej under high-risk scenarios. Material type dominates environmental impact over structural parameters by a factor of 2.32, with recycled aluminum frames reducing ELCI by 12.4%. The dual-optimum design is identified as the 3.2 mm tempered glass scheme, achieving a combined sustainability score CSS of 0.782 and emergy yield ratio EYR of 3.86, outperforming the industry average of 3.61. Multi-objective optimization using NSGA-II yields a Pareto front of 12 non-dominated solutions, with the 3.2 mm glass design maintaining Pareto optimal status in 72% of Monte Carlo iterations. This research provides a quantitative decision-making framework recommending standard modules for regions below one annual hail event, the 3.2 mm glass design for regions between one and four annual events, and steel frame combinations above four annual events, demonstrating that moderate enhancement achieves the optimal balance between hail protection and environmental sustainability.

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.