Distribution and risk of mercury in the sediments of mangroves along South China Coast.

The importance of mangrove was widely reported. However, the potential risks of pollutants (e.g., Hg) accumulated in the mangroves are often ignored. Thus, the present study aimed to explore the distribution and risk of mercury (Hg) in the sediments of mangroves along South China Coast. Results showed that concentrations of total Hg ranged from 0.0815 to 0.6377 mg/kg, with an arithmetic mean value of 0.2503 mg/kg. The contamination index (Pi) showed mild pollution toxicity risks in NS, slight toxicity risks in DZG, QZ, SY, ND, GQ, TLG, and free pollutions in BMW, SJ, ZJK and BLHK. NS, DZG and SY scored the highest values of Igeo among the eleven mangrove regions studied, indicating moderate to heavy pollution inputs in these regions. As for the distribution of Hg in the sediments along tidal gradient, concentrations of Hg in the sediments sharply increased from seaward mudflat to landward mangrove, corresponding with the increases of TOC. In summary, the present data indicated that mangrove ecosystem is efficient in Hg reservoir. However, the potential ecological risks of Hg, especially in some mangrove regions easily affected by human activities, should be noted.

Pathway decisions for reuse and recycling of retired lithium-ion batteries considering economic and environmental functions.

Reuse and recycling of retired electric vehicle (EV) batteries offer a sustainable waste management approach but face decision-making challenges. Based on the process-based life cycle assessment method, we present a strategy to optimize pathways of retired battery treatments economically and environmentally. The strategy is applied to various reuse scenarios with capacity configurations, including energy storage systems, communication base stations, and low-speed vehicles. Hydrometallurgical, pyrometallurgical, and direct recycling considering battery residual values are evaluated at the end-of-life stage. For the optimized pathway, lithium iron phosphate (LFP) batteries improve profits by 58% and reduce emissions by 18% compared to hydrometallurgical recycling without reuse. Lithium nickel manganese cobalt oxide (NMC) batteries boost profit by 19% and reduce emissions by 18%. Despite NMC batteries exhibiting higher immediate recycling returns, LFP batteries provide superior long-term benefits through reuse before recycling. Our strategy features an accessible evaluation framework for pinpointing optimal pathways of retired EV batteries.

Collaborative and privacy-preserving retired battery sorting for profitable direct recycling via federated machine learning.

Unsorted retired batteries with varied cathode materials hinder the adoption of direct recycling due to their cathode-specific nature. The surge in retired batteries necessitates precise sorting for effective direct recycling, but challenges arise from varying operational histories, diverse manufacturers, and data privacy concerns of recycling collaborators (data owners). Here we show, from a unique dataset of 130 lithium-ion batteries spanning 5 cathode materials and 7 manufacturers, a federated machine learning approach can classify these retired batteries without relying on past operational data, safeguarding the data privacy of recycling collaborators. By utilizing the features extracted from the end-of-life charge-discharge cycle, our model exhibits 1% and 3% cathode sorting errors under homogeneous and heterogeneous battery recycling settings respectively, attributed to our innovative Wasserstein-distance voting strategy. Economically, the proposed method underscores the value of precise battery sorting for a prosperous and sustainable recycling industry. This study heralds a new paradigm of using privacy-sensitive data from diverse sources, facilitating collaborative and privacy-respecting decision-making for distributed systems.