Non-targeted analysis and toxicity prediction for evaluation of photocatalytic membrane distillation removing organic contaminants from hypersaline oil and gas field-produced water.

Membrane distillation (MD) has received ample recognition for treating complex wastewater, including hypersaline oil and gas (O&G) produced water (PW). Rigorous water quality assessment is critical in evaluating PW treatment because PW consists of numerous contaminants beyond the targets listed in general discharge and reuse standards. This study evaluated a novel photocatalytic membrane distillation (PMD) process, with and without a UV light source, against a standard vacuum membrane distillation (VMD) process for treating PW, utilizing targeted analyses and a non-targeted chemical identification workflow coupled with toxicity predictions. PMD with UV light resulted in better removals of dissolved organic carbon, ammoniacal nitrogen, and conductivity. Targeted organic analyses identified only trace amounts of acetone and 2-butanone in distillates. According to non-targeted analysis, the number of suspects reduced from 65 in feed to 25-30 across all distillate samples. Certain physicochemical properties of compounds influenced contaminant rejection in different MD configurations. According to preliminary toxicity predictions, VMD, PMD with and without UV distillate samples, respectively contained 21, 22, and 23 suspects associated with critical toxicity concerns. Overall, non-targeted analysis together with toxicity prediction provides a competent supportive tool to assess treatment efficiency and potential impacts on public health and the environment during PW reuse.

Enteric pathogen reduction targets for onsite non-potable water systems: A critical evaluation.

Onsite non-potable water systems (ONWS) collect and treat local source waters for non-potable end uses such as toilet flushing and irrigation. Quantitative microbial risk assessment (QMRA) has been used to set pathogen log10-reduction targets (LRTs) for ONWS to achieve the risk benchmark of 10-4 infections per person per year (ppy) in a series of two efforts completed in 2017 and 2021. In this work, we compare and synthesize the ONWS LRT efforts to inform the selection of pathogen LRTs. For onsite wastewater, greywater, and stormwater, LRTs for human enteric viruses and parasitic protozoa were within 1.5-log10 units between 2017 and 2021 efforts, despite differences in approaches used to characterize pathogens in these waters. For onsite wastewater and greywater, the 2017 effort used an epidemiology-based model to simulate pathogen concentrations contributed exclusively from onsite waste and selected Norovirus as the viral reference pathogen; the 2021 effort used municipal wastewater pathogen data and cultivable adenoviruses as the reference viral pathogen. Across source waters, the greatest differences occurred for viruses in stormwater, given the newly available municipal wastewater characterizations used for modeling sewage contributions in 2021 and the different selection of reference pathogens (Norovirus vs. adenoviruses). The roof runoff LRTs support the need for protozoa treatment, but these remain difficult to characterize due to the pathogen variability in roof runoff across space and time. The comparison highlights adaptability of the risk-based approach, allowing for updated LRTs as site specific or improved information becomes available. Future research efforts should focus on data collection of onsite water sources.

Droplet digital PCR quantification of norovirus and adenovirus in decentralized wastewater and graywater collections: Implications for onsite reuse.

Risk-based treatment of onsite wastewaters for decentralized reuse requires information on the occurrence and density of pathogens in source waters, which differ from municipal wastewater due to scaling and dilution effects in addition to variable source contributions. In this first quantitative report of viral enteric pathogens in onsite-collected graywater and wastewater, untreated graywater (n = 50 samples) and combined wastewater (i.e., including blackwater; n = 28) from three decentralized collection systems were analyzed for two norovirus genogroups (GI/GII) and human adenoviruses using droplet digital polymerase chain reaction (ddPCR). Compared to traditional quantitative PCR (qPCR), which had insufficient sensitivity to quantify viruses in graywater, ddPCR allowed quantification of norovirus GII and adenovirus in 4% and 14% of graywater samples, respectively (none quantifiable for norovirus GI). Norovirus GII was routinely quantifiable in combined wastewater by either PCR method (96% of samples), with well-correlated results between the analyses (R2 = 0.96) indicating a density range of 5.2-7.9 log10 genome copies/L. These concentrations are greater than typically reported in centralized municipal wastewater, yet agree well with an epidemiology-based model previously used to develop pathogen log-reduction targets (LRTs) for decentralized non-potable water systems. Results emphasize the unique quality of onsite wastewaters, supporting the previous LRTs and further quantitative microbial risk assessment (QMRA) of decentralized water reuse.

Risk-based enteric pathogen reduction targets for non-potable and direct potable use of roof runoff, stormwater, and greywater.

This paper presents risk-based enteric pathogen log reduction targets for non-potable and potable uses of a variety of alternative source waters (i.e., locally-collected greywater, roof runoff, and stormwater). A probabilistic Quantitative Microbial Risk Assessment (QMRA) was used to derive the pathogen log10 reduction targets (LRTs) that corresponded with an infection risk of either 10-4 per person per year (ppy) or 10-2 ppy. The QMRA accounted for variation in pathogen concentration and sporadic pathogen occurrence (when data were available) in source waters for reference pathogens in the genera Rotavirus, Mastadenovirus(human adenoviruses), Norovirus, Campylobacter, Salmonella, Giardia and Cryptosporidium. Non-potable uses included indoor use (for toilet flushing and clothes washing) with occasional accidental ingestion of treated non-potable water (or cross-connection with potable water), and unrestricted irrigation for outdoor use. Various exposure scenarios captured the uncertainty from key inputs, i.e., the pathogen concentration in source water; the volume of water ingested; and for the indoor use, the frequency of and the fraction of the population exposed to accidental ingestion. Both potable and non-potable uses required pathogen treatment for the selected waters and the LRT was generally greater for potable use than non-potable indoor use and unrestricted irrigation. The difference in treatment requirements among source waters was driven by the microbial quality of the water - both the density and occurrence of reference pathogens. Greywater from collection systems with 1000 people had the highest LRTs; however, those for greywater collected from a smaller population (~ 5 people), which have less frequent pathogen occurrences, were lower. Stormwater had highly variable microbial quality, which resulted in a range of possible treatment requirements. The microbial quality of roof runoff, and thus the resulting LRTs, remains uncertain due to lack of relevant pathogen data.

Simulation of enteric pathogen concentrations in locally-collected greywater and wastewater for microbial risk assessments.

As decentralized water reuse continues to gain popularity, risk-based treatment guidance is increasingly sought for the protection of public health. However, effort s to evaluate pathogen risks and log-reduction requirements have been hindered by an incomplete understanding of pathogen occurrence and densities in locally-collected wastewaters (i.e., from decentralized collection systems). Of particular interest is the potentially high enteric pathogen concentration in small systems with an active infected excreter, but generally lower frequency of pathogen occurrences in smaller systems compared to those with several hundred contributors. Such variability, coupled with low concentrations in many source streams (e.g., sink, shower/bath, and laundry waters), has limited direct measurement of pathogens. This study presents an approach to modeling pathogen concentrations in variously sized greywater and combined wastewater collection systems based on epidemiological pathogen incidence rates, user population size, and fecal loadings to various residential wastewater sources. Pathogen infections were modeled within various population sizes (5-, 100-, and 1,000-person) for seven reference pathogens (viruses: adenoviruses, Norovirus, and Rotavirus; bacteria: Campylobacter and Salmonella spp.; and protozoa: Cryptosporidium and Giardia spp.) on each day of 10,000 possible years, accounting for intermittent infection and overlap of infection periods within the population. Fecal contamination of fresh greywaters from bathroom sinks, showers/baths, and laundry, as well as combined greywater and local combined wastewater (i.e., including toilets), was modeled based on reported fecal indicators in the various sources. Simulated daily infections and models of fecal contamination were coupled with pathogen shedding characteristics to generate distributions of pathogen densities in the various waters. The predicted frequency of pathogen occurrences in local wastewaters was generally low due to low infection incidence within small cohort groups, but increased with collection scale (population size) and infection incidence rate (e.g., Norovirus). When pathogens did occur, a decrease in concentrations from 5- to 100- and from 100- to 1,000-person systems was observed; nonetheless, overall mean concentrations (i.e., including non-occurrences) remained the same due to the increased number of occurrences. This highlights value of the model for characterizing scaling effects over averaging methods, which overestimate the frequency of pathogen occurrence in small systems while underestimating concentration peaks that likely drive risk periods. Results of this work will inform development of risk-based pathogen reduction requirements for decentralized water reuse.