The sewer system, despite being a significant source of methane emissions, has often been overlooked in current greenhouse gas inventories due to the limited availability of quantitative data. Direct monitoring in sewers can be expensive or biased due to access limitations and internal heterogeneity of sewer networks. Fortunately, since methane is almost exclusively biogenic in sewers, we demonstrate in this study that the methanogenic potential can be estimated using known sewer microbiome data. By combining data mining techniques and bioinformatics databases, we developed the first data-driven method to analyze methanogenic potentials using a data set containing 633 observations of 53 variables obtained from literature mining. The methanogenic potential in the sewer sediment was around 250–870% higher than that in the wet biofilm on the pipe and sewage water. Additionally, k-means clustering and principal component analysis linked higher methane emission rates (9.72 ± 51.3 kg_CO2 eq m^–3 d^–1) with smaller pipe size, higher water level, and higher potentials of sulfate reduction in the wetted pipe biofilm. These findings exhibit the possibility of connecting microbiome data with biogenic greenhouse gases, further offering insights into new approaches for understanding greenhouse gas emissions from understudied sources.

中文翻译：

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下水道微生物组的产甲烷潜力及其对甲烷排放的影响


下水道系统尽管是甲烷排放的重要来源，但由于定量数据的有限，在当前的温室气体清单中经常被忽视。由于访问限制和下水道网络的内部异质性，下水道中的直接监测可能成本高昂或有偏差。幸运的是，由于下水道中的甲烷几乎完全是生物来源，我们在这项研究中证明，可以使用已知的下水道微生物组数据来估计产甲烷的潜力。通过结合数据挖掘技术和生物信息学数据库，我们开发了第一个数据驱动的方法来分析产甲烷潜力，该方法使用包含从文献挖掘中获得的 53 个变量的 633 个观察值的数据集。下水道沉积物中的产甲烷潜力比管道和污水上的湿生物膜高约 250-870%。此外，k-means 聚类和主成分分析将较高的甲烷排放率（9.72 ± 51.3 kg_CO2 eq m^–3 d^–1）与更小的管道尺寸、更高的水位和更高的硫酸盐还原潜力联系起来接液管道生物膜。这些发现展示了将微生物组数据与生物温室气体联系起来的可能性，进一步为了解研究不足来源的温室气体排放的新方法提供了见解。