Environmental Technology

Dang, Longtu; Du, Yanlong; Li, Shuang; Zhu, Yangmo; Qiu, Fuguo

doi: 10.1080/09593330.2026.2683308pmid: N/A

This study investigates the comprehensive effects of iron-carbon micro-electrolysis on the anaerobic digestion (AD) performance of food waste (FW). The addition of nano-zero-valent iron (nZVI) or activated carbon (AC) can enhance AD performance individually, while their combined application shows a synergistic effect that significantly improves process efficiency. Compared to individual nZVI, the co-addition of nZVI and AC reduced the methane production lag phase by 30.72–36.86%. On the other hand, the cumulative methane yield increased by 13.57–25.01% in comparison with AC. These enhancements are attributed to the iron-carbon co-dosing strategy induced by the interaction between nZVI and AC. Microbial community analysis revealed that the AC/nZVI system not only enriched hydrogenotrophic methanogens but also increased the abundance of microorganisms associated with electron transfer. Furthermore, the optimal enhancement of coenzyme F420 activity and the electron transport system (ETS) -related electron transfer potential was observed at an iron-to-carbon mass ratio of 1:1 (P1), indicating the most significant synergistic effects. Therefore, the iron–carbon co-dosing strategy appears promising for enhancing electron transfer efficiency and promoting methane production in anaerobic digestion systems. Highlights The AD performance can be improved by adding nZVI or AC alone, and the AD performance can be further improved by adding both additives. At the same time, adding nZVI and AC can significantly shorten the methane production lag period and increase the cumulative methane production. Iron-carbon co-dosing strategy effect is the main reason for improving AD performance. It can promote the abundance of hydrogen-nutrient-producing methanogens and the abundance of electron transport-related microorganisms. When the mass ratio of iron and carbon is 1:1, the enhancement effect of coenzyme F420 and ETS is the best.

Ai, Shengshu; Gao, YongTai; Wang, YiMin; Hao, Rui; Zeng, Shangjing; Qu, Hong; Bian, Dejun

doi: 10.1080/09593330.2026.2683306pmid: 42251752

Membrane bioreactor (MBR) has attracted widespread attention owing to its unique membrane separation technology and high treatment efficiency. However, conventional MBRs struggle to remove pollutants with different oxygen requirements (e.g. nitrogen removal) in a single bioreactor, and the cost of membrane fouling control remains high. To address these challenges, this study devised an integrated gas-lift cross-flow Membrane Bioreactor (GL-CF-MBR), that possesses unique oxygen supply conditions and a cross-flow circulation pattern. Chemical analysis, 16S rRNA sequencing and transmembrane pressure (TMP) monitoring were employed to systematically evaluate the performance in terms of pollutant removal efficiency, microbial community composition and metabolic pathways, and membrane fouling behaviour. Results showed that the effluent concentrations of COD, NH₄⁺-N, and TN reached 25.58, 0.50, and 14.31 mg/L, respectively, meeting the Class 1A discharge standards of China's “Discharge standard of pollutants for municipal wastewater treatment plants’ (GB 18918-2002). Molecular biological analysis confirmed that, compared with the inoculated sludge, the Chao1 index and Observed species index increased by 37.32% and 30.94%, respectively. Moreover, denitrifying genera such as Rhodobacter and SC-I-84 were enriched in the system, and key functional genes involved in carbon and nitrogen metabolism were predicted. Owing to the unique flow field of the reactor, the time to reach a critical TMP surge for membrane modules installed in the scouring zone was delayed by 65.4% compared with those installed in the turbulent zone. The reactor promotes simultaneous pollutant removal and fouling mitigation, and its promising low operating cost provides a theoretical reference for practical engineering applications.

Li, Shuaishuai; Liu, Yuling; Wang, Zhixiao; Shu, Hao; Zhao, Wangben; Sun, Li; Dou, Chuanchuan

doi: 10.1080/09593330.2026.2685900pmid: 42285377

Floc image analysis shows promise for monitoring coagulation in water treatment, yet a systematic understanding of the relationship between image features and coagulation efficiency remains lacking. In this study, floc images were captured using a non-invasive image acquisition system, and multiple morphological and textural features were extracted via Python-OpenCV. The associations among floc images, settling behaviour, and effluent turbidity were systematically investigated using partial least squares regression. The results demonstrated that image features can effectively characterise floc population behaviour. Floc number removal was jointly influenced by the three-dimensional fractal dimension (D3), the proportion of 100–150 μm particles, and textural correlation. The fractal dimension and textural correlation reflect floc compactness and internal uniformity, while the small-particle proportion indicates flocculation completeness. Effluent turbidity was primarily governed by the initial floc number, D3 and small-particle proportion, and showed a strong positive correlation with the residual floc count. This study provides a theoretical basis for optimising the operational management of drinking water treatment processes, thereby supporting SDG 6 (Clean Water and Sanitation) through improved coagulation monitoring and process control.