Process and Systems Engineering Center (PROSYS), Department of Chemical and Biochemical Engineering, Technical University of Denmark, 2800, Kgs. Lyngby, Denmark.
School of Resources and Environmental Engineering, East China University of Science and Technology, Shanghai, 200237, PR China.
Environ Pollut. 2019 Oct;253:974-980. doi: 10.1016/j.envpol.2019.07.104. Epub 2019 Jul 20.
Thiocyanate (SCN)-based autotrophic denitrification (AD) has recently been demonstrated as a promising technology that could be integrated with anaerobic ammonium oxidation (Anammox) to achieve simultaneous removal of nitrogen and SCN. However, there is still a lack of a complete SCN-based AD model, and the potential microbial competition/synergy between AD bacteria and Anammox bacteria under different operating conditions remains unknown, which significantly hinders the possible application of coupling SCN-based AD with Anammox. To this end, a complete SCN-based AD model was firstly developed and reliably calibrated/validated using experimental datasets. The obtained SCN-based AD model was then integrated with the well-established Anammox model and satisfactorily verified with experimental data from a system coupling AD with Anammox. The integrated model was lastly applied to investigate the impacts of influent NH-N/NO-N ratio and SCN concentration on the steady-state microbial composition as well as the removal of nitrogen and SCN. The results showed that the NH-N/NO-N ratio in the presence of a certain SCN level should be controlled at a proper value so that the maximum synergy between AD bacteria and Anammox bacteria could be achieved while their competition for NO would be minimized. For the simultaneous maximum removal (>95%) of nitrogen and SCN, there existed a negative relationship between the influent SCN concentration and the optimal NH-N/NO-N ratio needed.
硫氰酸盐 (SCN)-基自养反硝化 (AD) 最近被证明是一种很有前途的技术,它可以与厌氧氨氧化 (Anammox) 相结合,实现氮和 SCN 的同时去除。然而,目前仍然缺乏完整的基于 SCN 的 AD 模型,并且在不同运行条件下 AD 细菌和 Anammox 细菌之间的潜在微生物竞争/协同作用仍然未知,这极大地阻碍了将基于 SCN 的 AD 与 Anammox 相结合的可能应用。为此,本文首先开发了一个完整的基于 SCN 的 AD 模型,并使用实验数据集对其进行了可靠的校准/验证。然后,将获得的基于 SCN 的 AD 模型与成熟的 Anammox 模型集成,并使用耦合 AD 与 Anammox 的系统的实验数据进行了令人满意的验证。最后,该集成模型被应用于研究进水 NH-N/NO-N 比和 SCN 浓度对稳态微生物组成以及氮和 SCN 去除的影响。结果表明,在一定 SCN 水平存在的情况下,应将进水 NH-N/NO-N 比控制在适当的值,以实现 AD 细菌和 Anammox 细菌之间的最大协同作用,同时最小化它们对 NO 的竞争。对于同时最大程度地去除(>95%)氮和 SCN,进水 SCN 浓度与所需的最佳 NH-N/NO-N 比之间存在负相关关系。