Protozoa reduction through secondary wastewater treatment in two water reclamation facilities.

The State of Nevada, USA Administrative Code requires a 12-log enteric virus reduction/inactivation, 10-log Giardia cyst reduction, and 10-log Cryptosporidium oocyst reduction for Category A+ reclaimed water suitable for indirect potable reuse (IPR) based on raw wastewater to potable reuse water. Accurately demonstrating log10 reduction values (LRVs) through secondary biological treatment prior to an advanced water treatment train enables redundancy and resiliency for IPR projects while maintaining a high level of public confidence. LRVs for Cryptosporidium and Giardia resulting from secondary biological treatment are not fully established due to a wide range of performance variabilities resulting from different types of secondary biological treatment processes employed in water reclamation. A one-year investigation of two full-scale northern Nevada (e.g. ≤4 mgd; 1.5 × 107 L/day) water reclamation facilities (WRFs) was conducted to monitor Cryptosporidium oocysts and Giardia cysts in untreated wastewater and secondary effluent. This study aimed at establishing secondary treatment LRVs, monitor WRF performance and attempted to correlate performance to protozoan reduction. California's IPR regulations, in which Nevada IPR regulations were modeled after, were based on a maximum concentration of 5-logs (cysts/L) of Giardia and 4-logs (oocysts/L) of Cryptosporidium. The recovery-corrected Giardia and Cryptosporidium concentrations measured in untreated influent (20 samples each at each WRF) were below 5-log cysts/L at the 99th percentile (maximum 4.4-log cysts/L) and 4-log oocysts/L (maximum 2.7 log oocysts/L), respectively. Both secondary treatment WRFs produced secondary effluent that is consistently better than federal and the State of Nevada requirements and perform within an operating envelop for other secondary facilities. Given the results, it appears that a minimum conservative estimate for LRVs for well-operated secondary activated sludge treatment plants (at the 5th percentile) of 0.5 LRV credit for Cryptosporidium and 2.0 LRV for Giardia is warranted. These minimum LRVs are consistent with a conservative review of the available literature.

Spatial and temporal variability and data bias in wastewater surveillance of SARS-CoV-2 in a sewer system.

The response to disease outbreaks, such as SARS-CoV-2, can be constrained by a limited ability to measure disease prevalence early at a localized level. Wastewater based epidemiology is a powerful tool identifying disease spread from pooled community sewer networks or at influent to wastewater treatment plants. However, this approach is often not applied at a granular level that permits detection of local hot spots. This study examines the spatial patterns of SARS-CoV-2 in sewage through a spatial sampling strategy across neighborhood-scale sewershed catchments. Sampling was conducted across the Reno-Sparks metropolitan area from November to mid-December of 2020. This research utilized local spatial autocorrelation tests to identify the evolution of statistically significant neighborhood hot spots in sewershed sub-catchments that were identified to lead waves of infection, with adjacent neighborhoods observed to lag with increasing viral RNA concentrations over subsequent dates. The correlations between the sub-catchments over the sampling period were also characterized using principal component analysis. Results identified distinct time series patterns, with sewersheds in the urban center, outlying suburban areas, and outlying urbanized districts generally following unique trends over the sampling period. Several demographic parameters were identified as having important gradients across these areas, namely population density, poverty levels, household income, and age. These results provide a more strategic approach to identify disease outbreaks at the neighborhood level and characterized how sampling site selection could be designed based on the spatial and demographic characteristics of neighborhoods.