Mingdong Chang , Xiubo Chen , Jian Shen , Tong Zhu , Tangfu Xiao , Jianqiao Wang , Chao Wang , Youzhao Wang
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引用次数: 0
Abstract
In the view of the serious prejudice of nitrates, sulfur-based autotrophic denitrification filter (SADF) has been widely used for deep nitrate removal from electron-donor-deficient water. However, it faces many challenges like slow start-up, reliance on backwashing, and poor low-temperature tolerance. For these challenges, a novel sulfur-based fiber carrier fixed bed reactor (SFFR) was developed in this study. It was found that SFFR had great film-forming ability and flow field characteristics, which promoted it to obtain superior denitrification performance, and the maximum nitrogen removal rate of 0.53 kg-N/m3/d. Meanwhile, SFFR shows significant cold tolerance, and alleviating the acidification problem of effluent to a certain extent. To sum up, the SFFR possesses the potential to be widely used in real-world wastewater treatment applications, especially as a promising solution for nitrate removal in cold regions. This study can provide an important reference for the improvement of the elemental sulfur autotrophic denitrification process.
期刊介绍:
The Journal of Environmental Chemical Engineering (JECE) serves as a platform for the dissemination of original and innovative research focusing on the advancement of environmentally-friendly, sustainable technologies. JECE emphasizes the transition towards a carbon-neutral circular economy and a self-sufficient bio-based economy. Topics covered include soil, water, wastewater, and air decontamination; pollution monitoring, prevention, and control; advanced analytics, sensors, impact and risk assessment methodologies in environmental chemical engineering; resource recovery (water, nutrients, materials, energy); industrial ecology; valorization of waste streams; waste management (including e-waste); climate-water-energy-food nexus; novel materials for environmental, chemical, and energy applications; sustainability and environmental safety; water digitalization, water data science, and machine learning; process integration and intensification; recent developments in green chemistry for synthesis, catalysis, and energy; and original research on contaminants of emerging concern, persistent chemicals, and priority substances, including microplastics, nanoplastics, nanomaterials, micropollutants, antimicrobial resistance genes, and emerging pathogens (viruses, bacteria, parasites) of environmental significance.