Greenhouse gas production from an intermittently dosed cold-climate wastewater treatment wetland.

This study explores the greenhouse gas (GHG) fluxes of nitrous oxide (N2O), methane (CH4) and carbon dioxide (CO2) from a two-stage, cold-climate vertical-flow treatment wetland (TW) treating ski area wastewater at 3 °C average water temperature. The system is designed like a modified Ludzack-Ettinger process with the first stage a partially saturated, denitrifying TW followed by an unsaturated nitrifying TW and recycle of nitrified effluent. An intermittent wastewater dosing scheme was established for both stages, with alternating carbon-rich wastewater and nitrate-rich recycle to the first stage. The system has demonstrated effective chemical oxygen demand (COD) and total inorganic nitrogen (TIN) removal in high-strength wastewater over seven years of winter operation. Following two closed-loop, intensive GHG winter sampling campaigns at the TW, the magnitude of N2O flux was 2.2 times higher for denitrification than nitrification. CH4 and N2O emissions were strongly correlated with hydraulic loading, whereas CO2 was correlated with surface temperature. GHG fluxes from each stage were related to both microbial activity and off-gassing of dissolved species during wastewater dosing, thus the time of sampling relative to dosing strongly influenced observed fluxes. These results suggest that estimates of GHG fluxes from TWs may be biased if mass transfer and mechanisms of wastewater application are not considered. Emission factors for N2O and CH4 were 0.27 % as kg-N2O-N/kg-TINremoved and 0.04 % kg-CH4-C/kg-CODremoved, respectively. The system had observed seasonal emissions of 600.5 kg CO2 equivalent of GHGs estimated over 130-days of operation. These results indicate a need for wastewater treatment processes to mitigate GHGs.

Whole cell kinetics of ureolysis by Sporosarcina pasteurii.

AIMS: Ureolysis drives microbially induced calcium carbonate precipitation (MICP). MICP models typically employ simplified urea hydrolysis kinetics that do not account for cell density, pH effect or product inhibition. Here, ureolysis rate studies with whole cells of Sporosarcina pasteurii aimed to determine the relationship between ureolysis rate and concentrations of (i) urea, (ii) cells, (iii) NH4+ and (iv) pH (H(+) activity). METHODS AND RESULTS: Batch ureolysis rate experiments were performed with suspended cells of S. pasteurii and one parameter was varied in each set of experiments. A Michaelis-Menten model for urea dependence was fitted to the rate data (R(2)  = 0·95) using a nonlinear mixed effects statistical model. The resulting half-saturation coefficient, Km , was 305 mmol l(-1) and maximum rate constant, Vmax , was 200 mmol l(-1)  h(-1) . However, a first-order model with k1  = 0·35 h(-1) fit the data better (R(2)  = 0·99) for urea concentrations up to 330 mmol l(-1) . Cell concentrations in the range tested (1 × 10(7) -2 × 10(8)  CFU ml(-1) ) were linearly correlated with ureolysis rate (cell dependent Vmax' = 6·4 × 10(-9)  mmol CFU(-1)  h(-1) ). CONCLUSIONS: Neither pH (6-9) nor ammonium concentrations up to 0·19 mol l(-1)  had significant effects on the ureolysis rate and are not necessary in kinetic modelling of ureolysis. Thus, we conclude that first-order kinetics with respect to urea and cell concentrations are likely sufficient to describe urea hydrolysis rates at most relevant concentrations. SIGNIFICANCE AND IMPACT OF THE STUDY: These results can be used in simulations of ureolysis driven processes such as microbially induced mineral precipitation and they verify that under the stated conditions, a simplified first-order rate for ureolysis can be employed. The study shows that the kinetic models developed for enzyme kinetics of urease do not apply to whole cells of S. pasteurii.