A multiple regression assessment of the biomineral urease activity from urine drainpipes of California public restrooms

Abstract

AbstractClogging and odor is strongly associated with ureolytic biomineralization in waterless and low-flow urinal drainage systems in high usage settings. These blockages continue to hinder widespread waterless and low-flow urinal adoption due to subsequent high maintenance requirements and hygiene concerns. Through field observations, hypothesis testing, and multiple regression analysis, this study attempts to characterize, for the first time, the ureolytic activity of the biomineralization found in alternative technologies located at 9 State-owned restrooms. Multiple regression analysis (n = 55, df = 4, R2 = 0.665) suggests that intrasystem sampling location ($$ \hat{\upbeta} $$ β ̂ = 1.23, p < 0.001), annual users per rest area ($$ \hat{\upbeta} $$ β ̂ = 0.5, p = 0.004), and the volatile solids to total solids mass fraction ($$ \hat{\upbeta} $$ β ̂ = 0.59, p = 0.003), are statistically significant influencers of the ureolytic activity of biomineral samples (p < 0.05). Conversely, ureC gene abundance (p = 0.551), urinal type (p = 0.521) and sampling season (p = 0.956) are not significant predictors of biomineral ureolytic activity. We conclude that high concentrations of the urease alpha subunit, ureC, which can be interpreted as proxy measure of a strong, potentially ureolytic community, does not necessarily mean that the gene is being expressed. Future studies should assess ureC transcriptional activity to measure gene expression rather than gene abundance to assess the relationship between environmental conditions, their role in transcription, and urease activities. In sum, this study presents a method to characterize biomineral ureolysis. This study establishes baseline values for future ureolytic inhibition treatment studies that seek to improve the usability of urine collection and related source separation technologies.