Methanogenic Potential of Sewer Microbiomes and Its Implications for Methane Emission

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 kgCO2 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.