Environmental metadata for: 2019/2020 biomineral sampling of drainpipes from California public rest areas

This environmental data set corresponds to a two part study. The first part details a multiple regression analysis of measured and categorical parameters that influence biomineral urease activity. Using an expanded version of the dateset used in the first part, a second and separate microbial ecology study focuses on the bacterial community structure related to both biomineral and liquid associated bacteria. The expanded data set includes liquid samples obtained from urine drainage systems. Part 1: Multiple Regression Analysis submitted to Sustainable Environment Research Clogging 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 cated at 9 State-owned restrooms. Multiple regression analysis (n = 55, df = 4, R2 = 0.665) suggests that intrasystem sampling location (β = 1.23, P < 0.001), annual users per rest area (β = 0.5, P < 0.004), and the organic/inorganic mass fraction (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 and establishes baseline values for future ureolytic inhibition treatment studies that seek to improve the usability of urine collection and related source separation technologies. Part 2: Microbial Ecology Study submitted to PLOS ONE In this study, we examined the total bacterial community associated with ureolytic biomineralization from urine dr