Performance Of Sludge Degradation, Mineralization And Electro-Energy Harvesting In A Sludge Treatment Electro-Wetland: Insight Into The Sludge Loading Rate

JOURNAL OF WATER PROCESS ENGINEERING(2021)

引用 6|浏览19
暂无评分
摘要
In order to enhance the performance of sludge treatment wetland (STW), microbial electrochemical system (MES) was introduced into a conventional sludge treatment wetland. A sludge treatment electro-wetland (STEW) was specially developed and investigated for its performance in sludge treatment and bioenergy production. The study investigated the performance of the STEW in terms of sludge organic degradability, sludge stabilization and the capability of bioelectricity generation at different sludge loading rates (SLR) of 50, 95, 125 kg TS/year.m(2). The quality of the final residual sludge product for agricultural reuse was also characterized. Results revealed that the highest power output (0.790 V of voltage and 0.229 W/m(3) of power density) of STEW was achieved with the highest SLR (125 kg TS/year.m(2)). The best sludge treatment efficiency (7.07 % of dewatering rate, 40.43 % of volatile solid (VS) removal and 80.95 % of total chemical oxygen demand (TCOD) removal) of STEW were achieved with proper SLR of 95 kg TS/year.m(2). After resting period, the nutrient concentrations in the residual sludge were quite low (total nitrogen of 2.86 % total solid (TS) and total phosphorous of 0.93 %TS), and heavy metals and faecal bacteria (Salmonella spp. and Escherichia coli) concentrations remained within the current legal limits for land application of the sludge. Experiments showed that the STEW system demonstrated a satisfactory efficiency for sludge dewatering and mineralization in spite of the high sludge loading rate and recycled the bioenergy simultaneously. The results also illustrated that the STEW was a promising technology for simultaneous sludge treatment and energy recovery.
更多
查看译文
关键词
Sludge treatment electro-wetland, Sludge loading rate, Electricity generation, Organic degradation, Sludge mineralization
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要