Safe use of treated greywater requires effective control of enteric viruses, yet there is limited full-scale evidence on virus removal in membrane-based greywater treatment systems. We performed monthly challenge tests with MS2 bacteriophage, a commonly used conservative surrogate for enteric viruses, over one year in a full-scale membrane bioreactor (MBR) treating light greywater and equipped with ultrafiltration modules (nominal pore size 0.04 μm). Observed log10 removal values (LRVs) ranged from 1.0 to 3.4, substantially lower than ∼4.0 LRVs previously reported for a comparable MBR treating municipal wastewater. LRVs were lowest (∼1.0–1.5) in the weeks following chemical cleaning and increased only modestly during operation, consistent with limited fouling development under low flux conditions (2–8 L m−2 h−1). Scanning electron microscopy (SEM)-based pore size analysis of the pristine ultrafiltration membrane indicated a broad distribution with an upper tail extending to ∼85 nm. Using this measured pore size distribution as input, a mechanistic sieving model predicted a size-exclusion-only LRV of ∼0.5 for MS2-sized particles, providing a mechanistic baseline consistent with measured LRVs observed at full-scale post-cleaning. Overall, these results underscore the need for full-scale validation of greywater MBRs and show that membrane specifications on pore size distribution are needed to support more accurate predictions of virus LRVs in membrane-based greywater treatment applications. ... Read more

On-site water reuse can provide water for nonpotable applications, but ensuring long-term performance and managing treatment failures is challenging without dedicated monitoring personnel. This study proposes a risk-based framework to determine enteric pathogen log-removal targets (LRTs) as a function of operational monitoring frequency. The framework integrates (i) quantitative microbial risk assessment, (ii) modeled pathogen concentrations at three collection scales, and (iii) failure models for three treatment configurations. As an example, LRTs were calculated considering different monitoring frequencies for greywater reuse. Results show that smaller systems require less frequent monitoring due to lower pathogen occurrence compared to larger systems, e.g., >1 day at a 5-people scale vs <500 s for a 1000-people system to meet norovirus risk with a bimodal treatment barrier failing up to four times per year. Incorporating a residual disinfectant or multiple barriers extends the required monitoring intervals. While LRTs are comparable across collection scales, this study highlights a key advantage of small systems─reduced monitoring requirements─contrasting prior work that found no benefits of downsizing in terms of treatment train design. This framework can support technology developers in quantifying trade-offs between treatment and monitoring and aid regulators in establishing monitoring requirements for on-site water reuse. ... Read more

In light of increasingly diverse greywater reuse applications, this study proposes risk-based log-removal targets (LRTs) to aid the selection of treatment trains for greywater recycling at different collection scales, including appliance-scale reuse of individual greywater streams. An epidemiology-based model was used to simulate the concentrations of prevalent and treatment-resistant reference pathogens (protozoa: Giardia and Cryptosporidium spp., bacteria: Salmonella and Campylobacter spp., viruses: rotavirus, norovirus, adenovirus, and Coxsackievirus B5) in the greywater streams for collection scales of 5-, 100-, and a 1000-people. Using quantitative microbial risk assessment (QMRA), we calculated LRTs to meet a health benchmark of 10^–4 infections per person per year over 10′000 Monte Carlo iterations. LRTs were highest for norovirus at the 5-people scale and for adenovirus at the 100- and 1000-people scales. Example treatment trains were designed to meet the 95 % quantiles of LRTs. Treatment trains consisted of an aerated membrane bioreactor, chlorination, and, if required, UV disinfection. In most cases, rotavirus, norovirus, adenovirus and Cryptosporidium spp. determined the overall treatment train requirements. Norovirus was most often critical to dimension the chlorination (concentration × time values) and adenovirus determined the required UV dose. Smaller collection scales did not generally allow for simpler treatment trains due to the high LRTs associated with viruses, with the exception of recirculating washing machines and handwashing stations. Similarly, treating greywater sources individually resulted in lower LRTs, but the lower required LRTs nevertheless did not generally allow for simpler treatment trains. For instance, LRTs for a recirculating washing machine were around 3-log units lower compared to LRTs for indoor reuse of combined greywater (1000-people scale), but both scenarios necessitated treatment with a membrane bioreactor, chlorination and UV disinfection. However, simpler treatment trains may be feasible for small-scale and application-scale reuse if: (i) less conservative health benchmarks are used for household-based systems, considering the reduced relative importance of treated greywater in pathogen transmission in households, and (ii) higher log-removal values (LRVs) can be validated for unit processes, enabling simpler treatment trains for a larger number of appliance-scale reuse systems. ... Read more

Greywater reuse is a strategy to address water scarcity, necessitating the selection of treatment processes that balance cost-efficiency and human health risks. A key aspect in evaluating these risks is understanding pathogen contamination levels in greywater, a complex task due to intermittent pathogen occurrences. To address this, faecal indicator organisms like E. coli are often monitored as proxies to evaluate faecal contamination levels and infer pathogen concentrations. However, the wide variability in faecal indicator concentrations poses challenges in their modelling for quantitative microbial risk assessment (QMRA). Our study critically assesses the adequacy of parametric models in predicting the variability in E. coli concentrations in greywater. We found that models that build on summary statistics, like medians and standard deviations, can substantially underestimate the variability in E. coli concentrations. More appropriate models may provide more accurate estimations of, and uncertainty around, peak E. coli concentrations. To demonstrate this, a Poisson lognormal distribution model is fit to a data set of E. coli concentrations measured in shower and laundry greywater sources. This model estimated arithmetic mean E. coli concentrations in laundry waters at approximately 1.0E + 06 MPN 100 mL−1. These results are around 2.0 log10 units higher than estimations from a previously used hierarchical lognormal model based on aggregated summary data from multiple studies. Such differences are considerable when assessing human health risks and setting pathogen reduction targets for greywater reuse. This research highlights the importance of making raw monitoring data available for more accurate statistical evaluations than those based on summary statistics. It also emphasizes the crucial role of model comparison, selection, and validation to inform policy-relevant outcomes. ... Read more