Low-carbon energy transition multi-agent network evolutionary under carbon trading scheme.

Transitioning to low-carbon energy is key for reaching carbon neutrality and modernizing our energy systems, but it presents significant cost-related challenges for energy businesses. To foster optimal outcomes, this paper develops a game model including power generators, high-energy businesses, and consumers in the carbon trading framework. The model explores how different entities evolve their low-carbon strategies under social learning influence to optimize utility. Stability analysis of strategy and simulation experiments reveal the following findings: (1) Greater carbon quotas reduce power generators' low-carbon transition willingness while high-energy-consuming enterprises and consumers remain unchanged. (2) Higher prices for low-carbon products offered by high-energy-consuming enterprises boost low-carbon transition motivation across all parties. (3) Increased green premiums enhance revenue for all parties but are constrained by policy and carbon pricing. (4) Both direct and indirect increases in carbon emissions negatively impact the revenue and utility for all stakeholders. (5) Increasing social learning effect fosters a shift towards low-carbon strategies, accelerating the attainment of game equilibrium, and enhancing market stability and sustainability. This research provides decision support for carbon trading policy design and low-carbon transition of energy enterprises.

Promising Low-Cost Adsorbent from Waste Green Tea Leaves for Phenol Removal in Aqueous Solution.

Phenol is the most common organic pollutant in many industrial wastewaters that may pose a health risk to humans due to its widespread application as industrial ingredients and additives. In this study, waste green tea leaves (WGTLs) were modified through chemical activation/carbonization and used as an adsorbent in the presence of ultrasound (cavitation) to eliminate phenol in the aqueous solution. Different treatments, such as cavitation, adsorption, and sono-adsorption were investigated to remove the phenol. The scanning electron microscope (SEM) morphology of the adsorbent revealed that the structure of WGTLs was porous before phenol was adsorbed. A Fourier Transform Infrared (FTIR) analysis showed an open chain of carboxylic acids after the sono-adsorption process. The results revealed that the sono-adsorption process is more efficient with enhanced removal percentages than individual processes. A maximum phenol removal of 92% was obtained using the sono-adsorption process under an optimal set of operating parameters, such as pH 3.5, 25 mg L-1 phenol concentration, 800 mg L-1 adsorbent dosage, 60 min time interval, 30 ± 2 °C temperature, and 80 W cavitation power. Removal of chemical oxygen demand (COD) and total organic carbon (TOC) reached 85% and 53%. The Freundlich isotherm model with a larger correlation coefficient (R2, 0.972) was better fitted for nonlinear regression than the Langmuir model, and the sono-adsorption process confirmed the pseudo-second-order reaction kinetics. The findings indicated that WGTLs in the presence of a cavitation effect prove to be a promising candidate for reducing phenol from the aqueous environment.