The increasing concern for decarbonization and sustainability in construction materials is calling for green binders to partially replace cement since its production is responsible for approximately 8% of global anthropogenic greenhouse gas emissions. Supplementary cementitious materials (SCMs), including fly ash, slag, silica fume, etc., can be used as a partial replacement for ordinary Portland cement (OPC) owing to reduced carbon dioxide emissions associated with OPC production. This study aims to investigate the sustainable use of waste oyster shell powder (OSP)-lithium slag (LS)-ground granulated blast furnace slag (GGBFS) ternary SCM system in green concrete. The effect of ternary SCMs to OPC ratio (0%, 10%, 20%, and 30%) on compressive strength and permeability of the green concrete were studied. The reaction products of the concrete containing OSP-LS-GGBFS SCM system were characterized by SEM and thermogravimetric analyses. The results obtained from this study revealed that the compressive strength of concrete mixed with ternary SCMs are improved compared with the reference specimens. The OSP-LS-GGBFS ternary SCMs-based mortars exhibited a lower porosity and permeability compared to the control specimens. However, when the substitution rate was 30%, the two parameters showed a decline. In addition, the samples incorporating ternary SCMs had a more refined pore structure and lower permeability than that of specimens adding OSP alone. This work expands the possibility of valorization of OSP for sustainable construction materials.

As cement manufacturing accounts for 8% of global CO₂ emissions, there is an urgent need to tackle the environmental impacts of cement production and address the decarbonization of construction materials. Adopting supplementary cementitious materials (SCMs), including fly ash, slag, silica fume, etc., can be used as a partial replacement for ordinary Portland cement (OPC) to reduce CO₂ emissions related to the OPC industry, while providing benefits for waste valorization. This study aims to explore the sustainable utilization of a waste oyster shell powder (OSP)–lithium slag (LS)–ground granulated blast furnace slag (GGBFS) ternary SCM system in green concrete. The effect of OSP fineness on compressive strength, hydration products, pore structure, and transport properties in ternary SCM-based mortars was studied using a wide array of experimental techniques, including thermogravimetric analysis (TGA), scanning electron microscopy (SEM) analysis, Mercury intrusion porosimetry (MIP), the water absorption test and the rapid chloride penetration test (RCPT). The results revealed that the concrete with the ternary SCMs showed equivalent compressive strength compared to reference specimens. The water absorption and chloride ion charge of the RCPT in the concrete containing the ternary SCMs decreased by up to 30% and 81.4%, respectively. It was observed that the specimens incorporating the OSP with a mesh size of 3000 exhibited the highest compressive strength and the most refined microstructure.

Formulating a scientifically sound and efficient approach to allocating carbon quota aligned with the carbon peaking goal is a fundamental theoretical and practical challenge within the context of climate-oriented trading in the power sector. Given the highly irrational allocation of carbon allowances in China’s power sector, as well as the expanding role of renewable energy, it is essential to rationalize the use of green energy in the development of carbon reduction in the power sector. This study addresses the risk of “carbon transfer” within the power industry and develops a predictive model for CO₂ emission based on multiple influential factors, thereby proposing a carbon quota distribution scheme adapted to green energy growth. The proposed model employs a hybrid of the gray forecasting model-particle swarm optimization-enhanced back-propagation neural network (GM-PSO-BPNN) for forecasting and allocating the total carbon quota. Assuming consistent total volume control through 2030, carbon quota is distributed to regional power grids in proportion to actual production allocation. Results indicate that the PSO algorithm mitigates local optimization constraints of the standard BP algorithm; the prediction error of carbon emissions by the combined model is significantly smaller than that of the single model, while its identification accuracy reaches 99.46%. With the total national carbon emissions remaining unchanged in 2030, in the end, the regional grids received the following quota values: 873.29 million tons in North China, 522.69 million tons in Northwest China, 194.15 million tons in Northeast China, 1283.16 million tons in East China, 1556.40 million tons in Central China, and 1085.37 million tons in the Southern Power Grid. The power sector can refer to this carbon allowance allocation standard to control carbon emissions in order to meet the industry’s emission reduction standards.