Quantitative Microbial Risk Analysis for Various Bacterial Exposure Scenarios Involving Greywater Reuse for Irrigation

Abstract

Greywater reuse can significantly reduce domestic water consumption. While the benefits are promising, risks are still under debate. Using a quantitative microbial risk-assessment model, we assessed the health risks associated with greywater reuse. The pathogens Salmonella enterica, Shigella spp., and Staphylococcus aureus were evaluated due to their possible prevalence in greywater and limited information regarding their potential risk with relation to greywater reuse for irrigation. Various exposure scenarios were investigated. Monte Carlo simulation was used and results were compared to the maximum "acceptable" limit of 10 −6 disability-adjusted life years (DALY) set by the World Health Organization. Safe reuse was met for all worst-case exposure scenarios for Staphylococcus aureus, Salmonella enterica and Shigella spp. If their concentrations were kept below 10,000, 50 and 5 cfu/100 mL, respectively. For the best-practice (more realistic) scenarios, safe reuse was met for Staphylococcus aureus if its concentration was kept below 10 6 cfu/100 mL. Salmonella enterica met the safe reuse requirements if a maximum concentration of 500 cfu/100 mL was maintained and Shigella spp. if a maximum concentration was lower than 5 cfu/100 mL. Based on reported concentrations of these bacteria in greywater, proper treatment and disinfection are recommended.

Applying Quantitative Microbial Risk Assessment Model in Developing Appropriate Standards for Irrigation Water

“…The concentrations needed to attain this limit ranged between 34 and 119 MPN/100 mL, respectively, for spinach and lettuce plants. Some calculated levels in previous studies were in harmony with the current results and ranged between 91 to 150 cfu/100 mL (Stine et al ; Busgang et al ).…”

Quantitative microbial risk assessment and sensitivity analysis for workers exposed to pathogenic bacterial bioaerosols under various aeration modes in two wastewater treatment plants

“…For S . aureus bioaerosol QMRA, the metrics used for P ( a )inf and DB were directly related to each other, and the DB was calculated via P ( a )inf and DALYs ( Havelaar et al, 2012 ; Busgang et al, 2018 ). By contrast, uncorrelation of the dose–response models for E .…”

“… Aerosol ingestion rate (ag) Unitless Supplementary Materials Table 2 – Removal fraction by employing PPE (F PPE ) Unitless Uniform distribution (Min = 0.95; Max = 0.99) Haas et al, 2017 Annual exposure frequency (n) Number of times 183 According to the field survey in this research. Staphylococcus aureus bioaerosol Exponential dose–response model (dose–infection model) k Unitless Uniform (Min = 6.46E−8; Max = 1.00E−7) Esfahanian et al, 2019 Prevalence P ill/inf Unitless 1 Busgang et al, 2018 Health burden (HB) DALYs/case 2.60E-3 Havelaar et al, 2012 Escherichia coli bioaerosol Beta-Poisson dose–response model (dose–infection model) α Unitless 1.55E-01 Shi et al, 2018 N 50 Unitless 2.11E+06 Shi et al, 2018 Exponential dose–response model (dose–illness model) k Unitless 1.22E-08 Shi et al, 2018 Health burden (HB) DALYs/case 4.55E-2 Shi et al, 2018

Fig. 1 Flow chart of quantitative microbial risk assessment.

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“…The probability of illness, as a conditional of infection, was calculated in Eq. (5) ( Busgang et al, 2018 ; Carducci et al, 2018 ): where P ( a ) ill is the annual probability of illness, and P ill/inf is the specific conditional probability of illness given an infection (i.e., prevalence) ( Table 1 ).…”

Microbiological Health Risk Assessment of Water Conservation Strategies: A Case Study in Amsterdam

“…Previous studies have discussed the health risk of using greywater or rainwater for various usages. However, most of them only focused on one or two particular pathogens in one study, most notably Legionella pneumophila [ 19 , 20 , 21 , 22 ]. In addition, most of them also did not indicate the level of pathogens removal that is needed to get the risk at a safe level and what measures can be applied to mitigate the risks.…”