Model predicted N2O production from membrane-aerated biofilm reactor is greatly affected by biofilm property settings - Chen, Xueming; Huo, Pengfei; Liu, Jinzhong; Li, Fuyi; Yang, Linyan; Li, Xianhui; Wei, Wei; Liu, Yiwen; Ni, Bing-Jie (Chemosphere (Oxford), 2021)
Even though modeling has been frequently used to understand the autotrophic deammonification-based membrane-aerated biofilm reactor (MABR), the relationships between system-specific biofilm property settings and model predicted N2O production have yet to be clarified. To this end, this study investigated the impacts of 4 key biofilm property settings (i.e., biofilm thickness/compactness, boundary layer thickness, diffusivity of soluble components in the biofilm structure, and biofilm discretization) on one-dimensional modeling of the MABR, with the focus on its N2O production. The results showed that biofilm thickness/compactness (200–1000 μm), diffusivity of soluble components in the biofilm structure (reduction factor of diffusivity: 0.2–0.9), and biofilm discretization (12–28 grid points) significantly influenced the simulated N2O production, while boundary layer thickness (0–300 μm) only played a marginal role. In the studied ranges of biofilm property settings, distinct upper and lower bounds of N2O production factor (i.e., the percentage ratio of N2O formed to NH4+ removed, 5.5% versus 2.3%) could be predicted. In addition to the microbial community structure, the N2O production pathway contribution differentiation was also subject to changes in biofilm property settings. Therefore, biofilm properties need to be quantified experimentally or set properly to model N2O production from the MABR correctly. As a good practice for one-dimensional modeling of N2O production from biofilm-based reactors, especially the MABR performing autotrophic deammonification, the essential information about those influential biofilm property settings identified in this study should be disclosed and clearly documented, thus ensuring both the reproducibility of modeling results and the reliable applications of N2O models. [Display omitted] •Impacts of 4 key biofilm properties on modeling N2O production from MABR.•Distinct upper and lower bounds of modeled N2O production factor (5.5% vs 2.3%).•Disclosure of quantified/set biofilm properties as a good modeling practice.