Liu Tongtong, Li Da, Tian Yan, Zhou Jiajie, Qiu Ye, Li Dongyi, Liu Guohong, Feng Yujie
State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, No. 73 Huanghe Road, Nangang District, Harbin 150090, China.
Institute of Chemical Engineering in Heilongjiang Province, 3# Nanhu load, High Tech R & D Zone of Harbin City, Harbin 150028, China.
Environ Sci Ecotechnol. 2024 Mar 20;21:100411. doi: 10.1016/j.ese.2024.100411. eCollection 2024 Sep.
Recent advancements in constructed wetlands (CWs) have highlighted the imperative of enhancing nitrogen (N) removal efficiency. However, the variability in influent substrate concentrations presents a challenge in optimizing N removal strategies due to its impact on removal efficiency and mechanisms. Here we show the interplay between influent substrate concentration and N removal processes within integrated vertical-flow constructed wetlands (IVFCWs), using wastewaters enriched with NO-N and NH-N at varying carbon to nitrogen (C/N) ratios (1, 3, and 6). In the NO-N enriched systems, a positive correlation was observed between the C/N ratio and total nitrogen (TN) removal efficiency, which markedly increased from 13.46 ± 2.23% to 87.00 ± 2.37% as the C/N ratio escalated from 1 to 6. Conversely, in NH-N enriched systems, TN removal efficiencies in the A-6 setup (33.69 ± 4.83%) were marginally 1.25 to 1.29 times higher than those in A-3 and A-1 systems, attributed to constraints in dissolved oxygen (DO) levels and alkalinity. Microbial community analysis and metabolic pathway assessment revealed that anaerobic denitrification, microbial N assimilation, and dissimilatory nitrate reduction to ammonium (DNRA) predominated in NO-N systems with higher C/N ratios (C/N ≥ 3). In contrast, aerobic denitrification and microbial N assimilation were the primary pathways in NH-N systems and low C/N NO-N systems. A mass balance approach indicated denitrification and microbial N assimilation contributed 4.12-47.12% and 8.51-38.96% in NO-N systems, respectively, and 0.55-17.35% and 7.83-33.55% in NH-N systems to TN removal. To enhance N removal, strategies for NO-N dominated systems should address carbon source limitations and electron competition between denitrification and DNRA processes, while NH-N dominated systems require optimization of carbon utilization pathways, and ensuring adequate DO and alkalinity supply.
人工湿地（CWs）的最新进展凸显了提高氮（N）去除效率的紧迫性。然而，进水底物浓度的变化对优化氮去除策略构成了挑战，因为它会影响去除效率和机制。在此，我们利用富含不同碳氮比（1、3和6）的NO-N和NH-N的废水，展示了综合垂直流人工湿地（IVFCWs）中进水底物浓度与氮去除过程之间的相互作用。在富含NO-N的系统中，观察到碳氮比与总氮（TN）去除效率之间呈正相关，随着碳氮比从1增加到6，总氮去除效率显著从13.46±2.23%提高到87.00±2.37%。相反，在富含NH-N的系统中，A-6装置中的总氮去除效率（33.69±4.83%）仅比A-3和A-1系统中的高1.25至1.29倍，这归因于溶解氧（DO）水平和碱度的限制。微生物群落分析和代谢途径评估表明，在碳氮比更高（C/N≥3）的NO-N系统中，厌氧反硝化、微生物氮同化和异化硝酸盐还原为铵（DNRA）占主导地位。相比之下，好氧反硝化和微生物氮同化是NH-N系统和低C/N的NO-N系统中的主要途径。质量平衡方法表明，在NO-N系统中，反硝化和微生物氮同化分别对总氮去除贡献了4.12 - 47.12%和8.51 - 38.96%，在NH-N系统中分别贡献了0.55 - 17.35%和7.83 - 33.55%。为了提高氮去除率，以NO-N为主的系统的策略应解决碳源限制以及反硝化和DNRA过程之间的电子竞争问题，而以NH-N为主的系统则需要优化碳利用途径，并确保充足的溶解氧和碱度供应。
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