Nanosystems Engineering Research Center for Nanotechnology-Enabled Water Treatment, School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ 85287-3005, USA.
Nanosystems Engineering Research Center for Nanotechnology-Enabled Water Treatment, School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ 85287-3005, USA; Laboratoire Interfaces et Systèmes Electrochimiques (LISE), Sorbonne Université, CNRS, 4 Place Jussieu, Paris 75005, France.
Water Res. 2022 Oct 15;225:119118. doi: 10.1016/j.watres.2022.119118. Epub 2022 Sep 14.
Water matrix composition impacts water treatment performance. However, matrix composition impacts have rarely been studied for electrochemical water treatment processes, and the correlation between the composition and the treatment efficiency is lacking. This work evaluated the electrochemical reduction of nitrate (ERN) using different complex water matrices: groundwater, brackish water, and reverse osmosis (RO) concentrate/brine. The ERN was conducted using a tin (Sn) cathode because of the high selectivity towards nitrogen evolution reported for Sn electrocatalysts. The co-existence of calcium (Ca), magnesium (Mg), and carbonate (CO) ions in water caused a 4-fold decrease in the nitrate conversion into innocuous nitrogen gas due to inorganic scaling formation on the cathode surface. XRF and XRD analysis of fouled catalyst surfaces detected brucite (Mg(OH)), calcite (CaCO), and dolomite (CaMg(CO)) mineral scales formed on the cathode surface. Surface scaling created a physical barrier on the electrode that decreased the ERN efficiency. Identifying these main sources of ERN inhibition was key to devising potential fouling mitigation strategies. For this reason, the chemical softening pre-treatment of a real brackish water was conducted and this significantly increased nitrate conversion and faradaic efficiency during subsequent ERN treatment, leading to a lower electric energy consumption per order. Understanding the ionic foulant composition responsible for influencing electrochemically-driven technologies are the first steps that must be taken to move towards niche applications such as decentralized ERN. Thus, we propose either direct ERN implementation in regions facing high nitrate levels in soft waters, or a hybrid softening/nitrate removal system for those regions where high nitrate and high-water hardness appear simultaneously.
水基质组成会影响水处理性能。然而，电化学水处理过程中很少研究基质组成的影响，而且缺乏组成与处理效率之间的相关性。本工作评估了不同复杂水基质对硝酸盐电化学还原（ERN）的影响：地下水、咸水和反渗透（RO）浓缩物/盐水。由于报道锡（Sn）电催化剂对氮析出具有高选择性，因此使用 Sn 阴极进行 ERN。水中存在钙（Ca）、镁（Mg）和碳酸根（CO）离子会导致硝酸盐向无害氮气的转化率降低 4 倍，这是由于阴极表面形成无机结垢。污染催化剂表面的 XRF 和 XRD 分析检测到在阴极表面形成的水镁石（Mg(OH)）、方解石（CaCO）和白云石（CaMg(CO)）矿物结垢。表面结垢在电极上形成物理障碍，降低了 ERN 效率。确定这些 ERN 抑制的主要来源是设计潜在防污缓解策略的关键。出于这个原因，对实际咸水进行了化学软化预处理，这显著提高了随后 ERN 处理过程中的硝酸盐转化率和法拉第效率，从而降低了每阶的电能消耗。了解导致影响电化学驱动技术的离子污染物组成是迈向分散式 ERN 等特定应用的第一步。因此，我们建议在软水中硝酸盐水平较高的地区直接实施 ERN，或者在同时存在高硝酸盐和高水硬度的地区采用软化/硝酸盐去除混合系统。
