Dataset Information

Quantitative microbial risk assessment of Greywater on-site reuse.

ABSTRACT: Recycle domestic greywater for on-site non-potable uses can lessen the demand on potable water and the burden on wastewater treatment plants. However, lack of studies to assess health risk associated with such practices has hindered their popularity. A Quantitative Microbial Risk Assessment was conducted to estimate the public health risks for two greywater reuse scenarios: toilet flushing and food-crop irrigation. Household greywater quality from three sources (bathroom, laundry and kitchen) was analyzed. Mathematical exposure rates of different scenarios were established based on human behavior using Monte-Carlo simulation. The results showed that, greywater from all three household sources could be safely used for toilet flushing after a simple treatment of microfiltration. The median range of annual infection risk was 8.8?×?10^-15-8.3?×?10^-11 per-person-per-year (pppy); and the median range of disease burden was 7.6?×?10^-19-7.3?×?10^-15 disability-adjusted life years (DALYs) pppy. In food-crop irrigation scenario, the annual infection risks and disease burdens of treated greywater from bathroom and laundry (2.8?×?10^-8, 4.9?×?10^-8 pppy; 2.3?×?10^-12-4.2?×?10^-12 DALYs pppy) were within the acceptable levels of U.S. EPA annual infection risk (?10^-4 pppy) and WHO disease burden (?10^-6 DALYs pppy) benchmarks, while kitchen greywater was not suitable for food-crop irrigation (4.9?×?10^-6 pppy; 4.3?×?10^-10 DALYs pppy) based on these benchmarks. The model uncertainties were discussed, which suggests that a more accurate risk estimation requires improvements on data collection and model refinement.

SUBMITTER: Shi KW

PROVIDER: S-EPMC6024565 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Quantitative microbial risk assessment of Greywater on-site reuse.

Shi Kuang-Wei KW Wang Cheng-Wen CW Jiang Sunny C SC

The Science of the total environment 20180425

Recycle domestic greywater for on-site non-potable uses can lessen the demand on potable water and the burden on wastewater treatment plants. However, lack of studies to assess health risk associated with such practices has hindered their popularity. A Quantitative Microbial Risk Assessment was conducted to estimate the public health risks for two greywater reuse scenarios: toilet flushing and food-crop irrigation. Household greywater quality from three sources (bathroom, laundry and kitchen) wa ...[more]

PMID: 29710672

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Project description:Data below detection limits, left-censored data, are common in environmental microbiology, and decisions in handling censored data may have implications for quantitative microbial risk assessment (QMRA). In this paper, we utilize simulated data sets informed by real-world enterovirus water data to evaluate methods for handling left-censored data. Data sets were simulated with four censoring degrees (low [10%], medium [35%], high [65%], and severe [90%]) and one real-life censoring example (97%) and were informed by enterovirus data assuming a lognormal distribution with a limit of detection (LOD) of 2.3 genome copies/liter. For each data set, five methods for handling left-censored data were applied: (i) substitution with LOD/[Formula: see text], (ii) lognormal maximum likelihood estimation (MLE) to estimate mean and standard deviation, (iii) Kaplan-Meier estimation (KM), (iv) imputation method using MLE to estimate distribution parameters (MI method 1), and (v) imputation from a uniform distribution (MI method 2). Each data set mean was used to estimate enterovirus dose and infection risk. Root mean square error (RMSE) and bias were used to compare estimated and known doses and infection risks. MI method 1 resulted in the lowest dose and infection risk RMSE and bias ranges for most censoring degrees, predicting infection risks at most 1.17 × 10-2 from known values under 97% censoring. MI method 2 was the next overall best method. For medium to severe censoring, MI method 1 may result in the least error. If unsure of the distribution, MI method 2 may be a preferred method to avoid distribution misspecification.IMPORTANCE This study evaluates methods for handling data with low (10%) to severe (90%) left-censoring within an environmental microbiology context and demonstrates that some of these methods may be appropriate when using data containing concentrations below a limit of detection to estimate infection risks. Additionally, this study uses a skewed data set, which is an issue typically faced by environmental microbiologists.

Project description: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.

Project description:We assessed the annual probability of infection resulting from non-potable exposures to distributed greywater and domestic wastewater treated by an aerobic membrane bioreactor (MBR) followed by chlorination. A probabilistic quantitative microbial risk assessment was conducted for both residential and office buildings and a residential district using Norovirus, Rotavirus, Campylobacter jejuni, and Cryptosporidium spp. as reference pathogens. A Monte Carlo approach captured variation in pathogen concentration in the collected water and pathogen (or microbial surrogate) treatment performance, when available, for various source water and collection scale combinations. Uncertain inputs such as dose-response relationships and the volume ingested were treated deterministically and explored through sensitivity analysis. The predicted 95th percentile annual risks for non-potable indoor reuse of distributed greywater and domestic wastewater at district and building scales were less than the selected health benchmark of 10-4 infections per person per year (ppy) for all pathogens except Cryptosporidium spp., given the selected exposure (which included occasional, accidental ingestion), dose-response, and treatment performance assumptions. For Cryptosporidium spp., the 95th percentile annual risks for reuse of domestic wastewater (for all selected collection scenarios) and district-collected greywater were greater than the selected health benchmark when using the limited, available MBR treatment performance data; this finding is counterintuitive given the large size of Cryptosporidium spp. relative to the MBR pores. Therefore, additional data on MBR removal of protozoa is required to evaluate the proposed MBR treatment process for non-potable reuse. Although the predicted Norovirus annual risks were small across scenarios (less than 10-7 infections ppy), the risks for Norovirus remain uncertain, in part because the treatment performance is difficult to interpret given that the ratio of total to infectious viruses in the raw and treated effluents remains unknown. Overall, the differences in pathogen characterization between collection type (i.e., office vs. residential) and scale (i.e., district vs. building) drove the differences in predicted risk; and, the accidental ingestion event (although modeled as rare) determined the annual probability of infection. The predicted risks resulting from treatment malfunction scenarios indicated that online, real-time monitoring of both the MBR and disinfection processes remains important for non-potable reuse at distributed scales. The resulting predicted health risks provide insight on the suitability of MBR treatment for distributed, non-potable reuse at different collection scales and the potential to reduce health risks for non-potable reuse.

Project description:Rapid economic development has caused industrial expansion into residential communities, leading to higher fecal pollution loads that could be discharged into aquatic environments. However, little is known regarding the potential microbial impact on human health. This study investigated microbial contamination from coastal industrial-residential community areas in nine sampling sites in waterways during three dry events. A general microbial source tracking (MST) marker, GenBac3, was detected in all samples from all three events, indicating continuing fecal pollution in the area, mostly from human sewage contamination. This was shown by the human-specific genetic marker crAssphage (88.9%) and human polyomavirus (HPyVs; 92.6%) detection. Enteric human adenovirus (HAdV40/41) showed three positive results only from residential sites in the first event. No spatial difference was observed for MST markers and traditional fecal indicators (total coliforms and Escherichia coli) in each event. Still, a significantly lower abundance of GenBac3, HPyVs, and total coliforms in the first sampling event was detected. Spearman's rho analysis indicated a strong correlation among certain pairs of microbial parameters. Multivariate analysis revealed two clusters of samples separated by land use type (industrial vs. residential). According to factor analysis of mixed data, the land use parameter was more associated with physicochemical parameters (i.e., salinity, conductivity, water temperature, and dissolved oxygen). A Quantitative Microbial Risk Assessment (QMRA) was then conducted to estimate the annual infection risks of HAdV40/41 for non-potable water reuse purposes using predicted concentrations from crAssphage and HPyVs. The highest risks (95th percentiles) were ranked by food crop irrigation, aquaculture, and toilet flushing, at 10-1, 10-2, and 10-3 per person per year (pppy). Required treatment levels to achieve a 10-4 pppy annual infection risk were estimated. QMRA-based water treatment scenarios were suggested, including chlorination for toilet flushing reuse and depth filtration prior to chlorination for aquaculture and food crop irrigation. Microbial monitoring combined with a QMRA could provide better insights into fecal pollution patterns and the associated risks, facilitating effective water quality management and appropriate prior treatments for water reuse.

Dataset Information

Quantitative microbial risk assessment of Greywater on-site reuse.

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Quantitative microbial risk assessment of Greywater on-site reuse.

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