Quantitative Risk Assessment Tools Research Articles

Scenario-based assessment of fecal pathogen sources affecting bathing water quality: novel treatment options to reduce norovirus and Campylobacter infection risks.

Wastewater discharge and runoff waters are significant sources of human and animal fecal microbes in surface waters. Human-derived fecal contamination of water is generally estimated to pose a greater risk to human health than animal fecal contamination, but animals may serve as reservoirs of zoonotic pathogens. In this study, quantitative microbial risk assessment (QMRA) tools were used to evaluate the hygienic impact of sewage effluents and runoff water from municipalities and animal farms on surface and bathing waters. The human-specific microbial source tracking (MST) marker HF183 was used to evaluate the dilution of fecal pathogens originating from the sewage effluent discharge to the downstream watershed. As novel risk management options, the efficiency of UV-LED disinfection and wetland treatment as well as biochar filtration was tested on-site for the contamination sources. According to the dilution pattern of the MST marker HF183, microbes from wastewater were diluted (2.3-3.7 log10) in the receiving waters. The scenario-based QMRA revealed, that the health risks posed by exposure to human-specific norovirus GII and zoonotic Campylobacter jejuni during the bathing events were evaluated. The risk for gastroenteritis was found to be elevated during wastewater contamination events, where especially norovirus GII infection risk increased (1-15 cases per day among 50 bathers) compared with the business as usual (BAU) situation (1 case per day). The noted C. jejuni infection risk was associated with animal farm contamination (1 case per day, versus 0.2-0.6 cases during BAU). Tertiary treatment of wastewater with wetland treatment and UV-LED disinfection effectively reduced the waterborne gastroenteritis risks associated with bathing. Based on the experiences from this study, a QMRA-based approach for health risk evaluations at bathing sites can be useful and is recommended for bathing site risk assessments in the future. In case of low pathogen numbers at the exposure sites, the MST marker HF183 could be used as a pathogen dilution coefficient for the watershed under evaluation. The full-scale implementation of novel tertiary treatment options at wastewater treatment plants (WWTPs) as well as on-site runoff water treatment options should be considered for infection risk management at locations where scenario-based QMRA implies elevated infection risks.

Establishing pathogen log reduction value targets for direct potable reuse in the United States

AbstractCommunities are now turning to potable reuse to augment their water supply portfolios in response to increasing demand and climate uncertainty. One barrier to broader implementation is a lack of regulations for direct potable reuse (DPR) in some locations. An incomplete understanding of the foundation of existing DPR frameworks may be contributing to this barrier. The objective of this study was to use a publicly available quantitative microbial risk assessment (QMRA) tool—DPRisk—to explain the basis behind California's existing indirect potable reuse regulations, California's draft DPR regulations, and an Expert Panel's response to those draft regulations. Then, leveraging a robust raw wastewater pathogen dataset from the literature, DPRisk was used to justify two alternatives: one based on maximum simulated pathogen concentrations and the other based on 97.4th percentile concentrations. The latter represents an effort to seek equivalency between “raw wastewater” (i.e., California) and “treated effluent” (i.e., Texas) approaches. Using justified QMRA assumptions, the baseline log reduction value (LRV) targets were determined to be 15/11/11 (maximum) or 13/10/10 (97.4th percentile) for viruses, Giardia, and Cryptosporidium. Additionally, instead of augmenting the baseline LRVs to account for undetected treatment process failures, tolerances for off‐specification conditions (e.g., up to 3 logs for 3–12 days per year) were characterized. With this foundational knowledge, stakeholders can better understand and adopt these frameworks or use DPRisk to establish a new framework that better addresses their unique constraints, including considerations for preferred treatment paradigms and capital and operational costs.

Using life expectancy as a risk assessment metric: The case of respirable crystalline silica

The change in age-related mortality patterns is an important characteristic of the population that can be used as a metric of risk by comparing exposed and non-exposed populations.In this paper, the mortality parameters were predicted for populations exposed to crystalline silica, a proven lung carcinogen.Seven hazard functions were tested for a dose–response relationship between lung cancer and characteristics of exposure. Life tables were calculated, along with parameters of the Gompertz-Makeham model for the force of mortality.It was demonstrated, in particular, that exposure to crystalline silica in the range from 0.03 to 0.3 mg/m3 for 40 years starting at age 20 causes a predicted drop in average life expectancy in the range of from 0.15 to 1.38 years.It was demonstrated that the lost life expectancy linearly correlates with relative risk (R = 0.995, R2 = 0.989, p< 0.00001). The probability of the life expectancy increasing while relative risk decreases was as low as 0.01.It was found that exponential parameter α of the Gompertz-Makeham equation increases with crystalline silica exposure, while the two linear parameters A and R (which are negatively correlated between each other) increase or decrease with exposure depending on the duration and onset age. Modal age of death in the cohort decreases with cumulative exposure with R = -0.977, R2 = 0.954, p < 0.0001.Based on several different approaches, it was suggested that the threshold of cumulative crystalline silica exposure concentration causing statistically significant change in the cohort life tables can be found in the range from 1.81 to 2.50 mg/m3-years. The change of average age of death in exposed male population does not exceed 1% below cumulative exposure of 3.5 mg/m3-years, and does not exceed 5% at cumulative exposure less than 9.8 mg/m3-years. It shows that no significant acceleration of death rate with age is happening even at the high levels of exposure to crystalline silica.The study demonstrated the value and advantages of the use of life expectancy and other lifetable characteristics as a tool for quantitative risk assessment.

Assessing Oral Epithelial Dysplasia Risk for Transformation to Cancer: Comparison Between Histologic Grading Systems Versus S100A7 Immunohistochemical Signature-based Grading.

While a 3-tier oral epithelial dysplasia grading system has been utilized for decades, it is widely recognized as a suboptimal risk indicator for transformation to cancer. A 2-tier grading system has been proposed, although not yet validated. In this study, the 3-tier and 2-tier dysplasia grading systems, and an S100A7 immunohistochemical signature-based grading system were compared to assess prediction of risk of transformation to oral cancer. Formalin-fixed, paraffin-embedded biopsy specimens with known clinical outcomes were obtained retrospectively from a cohort of 48 patients. Hematoxylin and eosin-stained slides were used for the 2- and 3-tier dysplasia grading, while S100A7 for biomarker signature-based assessment was based on immunohistochemistry. Inter-observer variability was determined using Cohen's kappa ( K ) statistic with Cox regression disease free survival analysis used to determine if any of the methods were a predictor of transformation to oral squamous cell carcinoma. Both the 2- and 3-tier dysplasia grading systems ranged from slight to substantial inter-observer agreement ( Kw between 0.093 to 0.624), with neither system a good predictor of transformation to cancer (at least P =0.231; ( P >>>0.05). In contrast, the S100A7 immunohistochemical signature-based grading system showed almost perfect inter-observer agreement ( Kw =0.892) and was a good indicator of transformation to cancer ( P =0.047 and 0.030). The inherent grading challenges with oral epithelial dysplasia grading systems and the lack of meaningful prediction of transformation to carcinoma highlights the significant need for a more objective, quantitative, and reproducible risk assessment tool such as the S100A7 immunohistochemical signature-based system.

Correction: Haddad, R.K.; Harun, Z. Development of a Novel Quantitative Risk Assessment Tool for UK Road Tunnels. Fire 2023, 6, 65

In the original publication [...]

Development of a Novel Quantitative Risk Assessment Tool for UK Road Tunnels

Some of the most critical transportation infrastructures are road tunnels. Underground passageways for motorists are provided through this cost-effective engineering solution, which allows for high traffic volumes. A crucial aspect of the operation of road tunnels is fire safety. Risk assessments have been established to ensure the level of safety in tunnels. As the existing quantitative risk analysis (QRA) models are inapplicable to assess the fire risk in UK road tunnels, this paper presents a novel QRA model, named LBAQRAMo, for UK road tunnels. This model consists of two main sections: quantitative frequency analysis, to estimate the frequency of fire incidents via an event tree; and quantitative consequences analysis, to model the consequences of fire incidents. LBAQRAMo covers the risk to tunnel users. The result of the risk analysis is the expected value of the societal risk of the investigated tunnel, presented via F/N curve. Another major result of this model is the estimation of the number of fatalities for each scenario based on the comparison between required safe egress time (RSET) and available safe egress time (ASET). Risk evaluation was carried out by comparison of the tunnel under study with the UK ALARP limit. The operation of the model is demonstrated by its application to the Gibraltar Airport Tunnel as a case study. Simulation of 34 different possible scenarios show that the tunnel is safe for use. The sensitivity of the model to HGV fire incident frequency and basic pre-movement times was studied as well.

Training in tools to develop quantitative microbial risk assessment along the food chain of Spanish products.

Food safety is a widespread challenge. Every year it is estimated that almost 1 in 10 people in the world fall ill after eating contaminated food resulting in over 400,000 deaths. The risk of outbreaks is higher when consuming ready-to-eat (RTE) products because they are eaten without a further cooking process that could inactivate pathogenic microorganisms. Hence, food processing is essential to increase the safety of RTE products. Microbiological risk assessment (MRA) integrates food science, microbiology and data science to provide a comprehensive understanding of the safety of the food system. MRA provides qualitative and/or quantitative information to decision makers, which might promote the adoption of better food practices. In this contest, this project aims to study and implement tools for quantitative microbial risk assessment (QMRA) of food products along the food chain. A common RTE product (cured ham) from Spain was used as a case study. Following, the exposure assessment model was implemented using mathematical models and statistical software to describe the microbial behaviour along the food chain. The study presents the possibility to identify the risk exposure in different scenarios (e.g. growth during different storage conditions, inactivation induced by traditional or innovative decontamination techniques), showing the flexibility of the predictive tools developed.

ALARP demonstration in management of change using quantitative Bowtie analysis risk assessment tool for an offshore gas platform

AbstractIn this study, a framework for a quantitative Bowtie analysis based on the layer of protection analysis (LOPA) approach in the management of change (MOC) process flow was developed. The proposed tool can be used as a quantitative risk analysis method in supporting decisions when layers of protection or safeguards are unavailable. The proposed tool can quantify the frequency of the causes of a particular hazard via Fault Tree Analysis and identify the multiple consequences of the impact of the hazards with quantitative end events for risk analysis. The practicality of the proposed tool was demonstrated in a selected case study from the MOC database from Company A's offshore gas platform, where the consequences and impacts of the hazards to the people, environment, assets, and reputation were assessed. The LOPA quantification was introduced into the Bowtie diagram using a reliability database to determine the failure rates and probability of failure of the affected equipment. The risk tolerance level was subsequently determined. The outputs of risk analysis from the proposed quantitative Bowtie were then compared with the previous qualitative risk evaluation of the selected case study. Potential opportunities for further use of the proposed quantitative Bowtie tool were recommended.

Predicting Recidivism Risk Meets AI Act

Quantitative recidivism risk assessment can be used at the pretrial detention, trial, sentencing, and / or parole stage in the justice system. It has been criticized for what is measured, whether the predictions are more accurate than those made by humans, whether it creates or increases inequality and discrimination, and whether it compromises or violates other aspects of fairness. This criticism becomes even more topical with the arrival of the Artificial Intelligence (AI) Act. This article identifies and applies the relevant rules of the proposed AI Act in relation to quantitative recidivism risk assessment. It does so by focusing on the proposed rules for the quality of the data and the models used, on biases, and on the human oversight. It is concluded that legislation may consider requiring providers of high-risk AI systems to demonstrate that their solution performs significantly better than risk assessments based on simple models, and better than human assessment. Furthermore, there is no single answer to evaluate the performance of quantitative recidivism risk assessment tools that are or may be deployed in practice. Finally, three approaches of human oversight are discussed to correct for the negative effects of quantitative risk assessment: the optional, benchmark, and feedback approach.

MO450: A New Hematuria Score, Semi-Quantitative Analysis of Hematuria Normalized for Urine Concentration Predicts the Progression of Chronic Kidney Disease: From the KNOW-CKD Study

Abstract BACKGROUND AND AIMS It is unclear whether hematuria is a risk factor for chronic kidney disease (CKD) progression. In addition, quantitative evaluation considering urine concentration as in proteinuria has not been established in hematuria. The aim of this study is to verify the relationship between semi-quantitative analysis of hematuria normalized for urine concentration and the progression in CKD. METHOD We analyzed 1909 patients with pre-dialysis CKD from KNOW-CKD cohort who assessed baseline urine microscopy. Patients were scored according to the number of red blood cells (RBC) in high power field (1 point for &amp;lt; 1, 2 points for 1–4, 3 points for 5̵119 and 4 points for ≥ 20). To obtain the hematuria score, these points were divided by the random urine creatinine level and multiplied by 100. The study endpoint was CKD progression, defined as a composite of a ≥ 50% decrease in estimated glomerular filtration rate (eGFR) from baseline values or end-stage kidney disease. RESULTS The hematuria score ranged from 1.86 to 20.3 (2.2 ± 1.86). During a median follow-up of 4.6 years (9657 person-years), 729 patients reached study endpoint. There was a graded association between hematuria score and the risk of progression of CKD. The hazard ratios (95% confidence intervals) for second, third and fourth quartile of hematuria score were 1.32 (1.04–1.67), 1.43 (1.12–1.82) and 1.50 (1.17–1.91), respectively, compared to the first quartile. For each 1 point increase in hematuria score, the risk of progression increased by 5%. CONCLUSION This study showed that there was a graded relationship between a new hematuria score and the risk of the progression of CKD. Microscopic hematuria is a risk factor for CKD progression and might be used as a quantitative risk assessment tool.

Taxonomy and Stakeholder Risk Management in Integrated Projects of the European Green Deal

The article analyzed the state of the global problem of ecological safety of the EU and argued the need to create a methodology for planning technologically integrated projects of the “European Green Deal” (TIP “EGD”) that accounts for the risks to the stakeholders, i.e., the state, project executors, resource suppliers, project managers, and clients. Each of these has an individual set of values that determines the project risk for them. Herein is proposed a taxonomy of three ranks of TIP “EGD” involving agricultural waste, determined by their characteristics, products, and requirements for the stakeholders. The authors point out the need to create tools for quantitative risk assessment for the stakeholders of TIP “EGD” involving agricultural waste and distinguish four groups of risk components with regard to the value of such projects. A model of value risk formation is presented that addresses the risk management of each of these stakeholder values. The need to develop tools (models, methods, and algorithms) for quantitative risk assessment of the values of each type of project is discussed. Regularities in the formation of stakeholder values, which were a foundation of the model of formation, are established.

A scientometric study on quantitative microbial risk assessment in water quality analysis across 6 years (2016-2021).

Water contamination by microbes is a growing environmental challenge that has exacerbated the apparent scarcity of safe drinking water. To alleviate this challenge, it is important to screen water for pathogens to reduce the risk of contracting waterborne diseases among consumers. The use of the quantitative microbial risk assessment (QMRA) tool to approximate illness possibility from exposure to microorganisms using dose-response models between pathogens and their associated health impacts is, therefore, recommended. The aim of this study was to explore the use of QMRA in water quality assessment using a scientometric approach and data sourced from the Web of Science (WoS) database for the period between 2016 and 2021. Articles were searched in the WoS databases before downloading the content for a bibliometric analysis using the VOSviewer software. Additionally, Microsoft Excel was used to analyze the inter-relationships of the searched results. Journal articles had the highest results from the searched query at 90.6% compared to other forms of output. High-impact journals such as the Science of the Total Environment and Water Research had the highest number of publications at 11.056 and 7.5%, respectively. Keyword analysis showed the multidisciplinary nature of the search query based on the clustered themes. The USA and China showed greater publication output with a total of 51.7% of total publications compared to developing countries due to their high research potential and extensive collaborative networks. A similar trend was evident in the institutional analysis with the University of California, USA, and the Chinese Academy of Sciences being the highest research contributors with 8% of the searched output. The study highlighted the need to extend research inputs to developing countries of Africa and Asia to improve their research and development capacity, productivity and share knowledge on QMRA in water quality assessment.

Environmental and ecotoxicological risk assessment of pollution with light crude oil for an oil exploatation field

Global development of transportation dependent on internal combustion engines, involves major increases in the consumption of fossil fuels obtained by extracting crude oil from depths by means of wells and refining it. In this context, protection of environment and groundwater quality is an increasingly difficult objective to maintain, requiring modern methods to address possible negative effects on the environment. The current research assesses the degree of eco-toxicological and environmental risk for an oil exploitation area in case of an accidental pollution scenario with crude oil. The entire risk spectrum was analysed through a set of qualitative and quantitative risk assessment tools to highlight and quantify the most important effects caused by petroleum products on biotope and biocenoses. The primary aim of the research is to identify vulnerable environmental reservoirs for accidental oil pollution and to establish the best tools to quantify the environmental and ecotoxicological risk of groundwater contamination. The results obtained from the area showed a low to medium risk of contamination of the saturated and unsaturated area with crude oil expressed as TPH (total petroleum hydrocarbons) and a low risk of contamination with volatile organic compounds type BTEX associated contamination of biocenoses that can directly or indirectly interact with potentially polluted areas.

A novel vulnerability model considering synergistic effect of fire and overpressure in chemical processing facilities

Processing facilities are faced with spatial-temporal dependent multiple-hazards. These hazards could cause catastrophic consequences. A novel vulnerability model called the “fire and explosion synergistic effect model” (FESEM) is proposed in the present study to model equipment vulnerability under the spatial-temporal synergistic of heat radiation and overpressure. On the basis of the fire synergistic effect model, the FESEM firstly model the temperature elevation and the yield strength reduction of the storage tank wall under fire heat radiation. Then, based on the von Mises yield criterion, the FESEM models the equivalent stress under overpressure. Combining the lowered yield strength induced by fire heat radiation and equivalent stress induced by overpressure under the synergistic effect, the logistic function is used to estimate time to failure and escalation probability. The application of the model is demonstrated in the case study, which confirms that the synergistic effect is significant and closer to reality. The parameters that have considerable effects on time to failure and escalation probability are discussed. The proposed method will serve as a rapid quantitative risk assessment tool of multi-hazard coupling, including the domino effect. The model will serve as an essential guide for preventing and controlling domino effects.

A quantitative risk assessment of a domestic property connected to a hydrogen distribution network

The increased reliance on natural gas for heating worldwide makes the search for carbon-free alternatives imperative, especially if international decarbonisation targets are to be met. Hydrogen does not release carbon dioxide (CO2) at the point of use which makes it an appealing candidate to decarbonise domestic heating. Hydrogen can be produced from either 1) the electrolysis of water with no associated carbon emissions, or 2) from methane reformation (using steam) which produces CO2, but which is easily captured and storable during production. Hydrogen could be transported to the end-user via gas distribution networks similar to, and adapted from, those in use today. This would reduce both installation costs and end-user disruption. However, before hydrogen can provide domestic heat, it is necessary to assess the ‘risk’ associated with its distribution in direct comparison to natural gas. Here we develop a comprehensive and multi-faceted quantitative risk assessment tool to assess the difference in ‘risk’ between current natural gas distribution networks, and the potential conversion to a hydrogen based system. The approach uses novel experimental and modelling work, scientific literature, and findings from historic large scale testing programmes. As a case study, the risk assessment tool is applied to the newly proposed H100 demonstration (100% hydrogen network) project. The assessment includes the comparative risk of gas releases both upstream and downstream of the domestic gas meter. This research finds that the risk associated with the proposed H100 network (based on its current design) is lower than that of the existing natural gas network by a factor 0.88.

Vulnerability of bridges to individual and multiple hazards- floods and earthquakes

Building resilient bridges, that are able to withstand multiple natural stressors with minimal damage and quickly restore their functionality is paramount to delivering climate-resilient transport infrastructure. Nevertheless, bridges are proven to be vulnerable to natural hazards, with floods and earthquakes being the main causes of failure. The available research and practice for assessing the vulnerability of river-crossing bridges is predominantly qualitative and therefore relies heavily on visual inspections, while ignoring important characteristics of the complex water-soil-bridge interaction. This is a knowledge gap that this paper aims to fill. This work provides novel fragility models for hydraulically induced stressors and/or combinations of hydraulic and seismic hazards. To achieve this, unique detailed two- and three- dimensional numerical models are employed, for a typical three-span prestressed box-girder river-crossing bridge. This paper is a primer on the vulnerability of flood-critical bridges as it models the entire water-soil-bridge system, taking into account critical hydraulic stressors (scour, debris accumulation, hydraulic forces), the uncertainty in scour hole formation, and all components of integral and isolated bridges: deck, bearings, piers and abutments, backfill, and the foundation soil. A detailed description of the damage modes for each component is given and sets of fragility curves for floods and combinations of hydraulic stressors and earthquakes are developed. The study concludes that integral bridges are in most cases more vulnerable to local scour than bridges with bearings, since the latter are more flexible and can therefore adapt to changes in their geometry. The opposite is true for global scour and/or seismic earthquake excitations. The generated fragility models are useful tools for quantitative risk assessment of transport systems and provide practical means in resilience-based asset management by owners and operators of transport infrastructure.

Safety assessment of industrial locations under the effects generated by controlled explosions

The identification and consideration of various potential hazards significantly reduce the accidents in the industrial locations where specific operations with explosive materials take place. The purpose of this study was to assess the effects generated by external explosions produced near an experimental steel frame building model. The novelty of the paper is the combination of experimental results on site with data from specialised databases of accidental explosions. These data were integrated using computer modelling to evaluate the risk associated with different hazardous situations (shockwave propagation, spreading of debris), and the effects on the location. The numerical simulations were performed using IMESAFR software, which is a quantitative risk assessment tool and can be used to calculate risk to personnel from commercial explosives facilities and operations. The results of the simulations were used to design the perimeter security within the site and the placement of the experimental model, considering the maximum expected blast charge. Considering the limited space available on site, the results of the simulations were very valuable and confirmed the tests that were already planned can be performed without any risk for personnel, nearby buildings and facilities.

Development of Risk Assessment Framework for First Time Offenders Using Ensemble Learning

Recidivism is generally considered as a deficiency disease in which offenders recommend a crime or repeat an offence. Empirically committing the first crime at a very young age leads to a much higher rebound rate and the continuation of similar offensive behavior. Accordingly, prioritization must be given for the early assessment of recidivism behavior in first-time offender by law enforcing agencies. Different prison studies suggest that recidivism can be curtailed by early behavioral risk assessment in first-time offenders. Ideally, a psychologist conducts a manual risk assessment using standard psychological assessment tools, which has long been regarded as a standard method for recidivism risk assessment. However, such behavioral examination procedures are usually sluggish and constrained by subjective perceptions. Consequently, this study aims to develop a machine learning-based quantitative risk assessment tool for the recidivism behavioral gradation of first-time offenders. Quantitative gradation and prediction of future recidivism behavior in such offenders are achieved using an ensemble learning model and an advanced machine-learning approach. For the available behavioral data collected from multiple prison locations, simulations were performed, and the experimental results were obtained. It is ascertained that, the proposed three-member and five-member ensemble classifier models lead to 85.47% and 87.72% accuracy respectively in comparison to other standard individual classifiers.

Reservoir dam operating risk dynamics modelling for safety control in the emergency response process

As revealed by the dam break accident investigation statistics, flawed organizational behavior determines the safety level of the reservoir dam. Its operating risk revolution process involves water, disaster, relief material dispatching, information interaction, and so on. The multiple information transferring mode and dynamic processes perform with the characteristics of the social-technical system, but little prior research on the risk causality can be found in such a view. The traditional risk analysis and assessment techniques based on linear accident model and the partial probability calculation cannot effectively satisfy the requirements for dam-break emergency decision-making in a dynamic and systematic way. Based on the system dynamics approach, this study proposed risk dynamics models aiming for risk interaction mechanisms involving organizational, human, and technical system factors leading to dam break. The models guided the development of a quantitative risk assessment tool to integrate relevant professional modules and data. The derived policy suggestions which guarantee the life and property of downstream residents can improve the abilities of dam operating management organization for more effective responses under emergency circumstances.

Quantitative microbial risk assessment of occupational and public risks associated with bioaerosols generated during the application of dairy cattle wastewater as biofertilizer

The reuse or recycling of wastewater provides environmental and economic benefits, representing a sustainable and circular alternative for the management of liquid waste. However, the application of effluents to agricultural crops via spraying creates a potentially dangerous situation for individuals exposed to airborne pathogens. This study used Quantitative Microbial Risk Assessment (QMRA) tools to quantitatively assess the microbial risks of occupational and public exposures to bioaerosols in fertigation scenarios by spraying untreated and treated dairy cattle wastewater. Analyses of Escherichia coli (EC) and spores of Clostridium perfringens (CpSP) in raw and treated effluents as well as pathogen / indicator ratios from the literature were used to estimate the concentrations of Escherichia coli O157:H7 (EC O157:H7) and Cryptospodirium spp. (Crypto) in the air, and the results were applied to an atmospheric microbiological dispersion model. From the concentrations of pathogens in the air, infectious risks for downwind receptors were calculated. The risks of infection by EC O157:H7 to workers at 10 m and 50 m away from the emission source ranged between 3.81 × 10 1 and 2.68 × 10 3 pppy (per person per year), whereas to residents at 100 m and 500 m ranged from 4.59 × 10 1 to 1.51 × 10 4 pppy. Peak values (95th percentile) of occupational and public risks associated with the exposure to Crypto were 3.41 × 10 3 and 6.84 × 10 4 pppy at 10 m and 50 m from the source, respectively, and were lower than 1.48 × 10 6 pppy regarding exposures to CpSP. Anaerobic digestion reduced risks by approximately one order of magnitude. The distance from the source was inversely proportional to the risk of exposure. It is recommended that wastewater is treated prior to its reuse and the adoption of application methods with low aerosolization potential. In addition, the need for workers to use personal protective equipment (PPE) is highlighted.