Appendix A

Details in Support of the Risk Exemplar in Chapter 6

In this appendix, the committee details the data and assumptions used in the risk exemplar, described in Chapter 6.

PATHOGENS

The exemplar includes four enteric pathogens: adenovirus, norovirus, Salmonella, and Cryptosporidium. In the following discussion, each organism is briefly described and an estimated density in secondary effluent for use in the exemplar is provided. Modifications in those densities are then estimated that correspond to each of the scenarios in the exemplar. Finally, the densities are adjusted so that they are in the same form as those used in dose-response testing, and a risk of illness is estimated using quantitative microbial risk estimation methodology (Haas et al., 1999).

Pathogen Occurrence in Secondary Effluents

The information and assumptions used to estimate pathogen occurrence in undisinfected secondary wastewater effluent as a starting point for the risk exemplar is discussed in this section and summarized in Table A-1. Pathogen reduction from subsequent disinfection and treatment steps is discussed in the next section.

Adenovirus

Adenovirus is a waterborne pathogen that has been associated with recreation-related outbreaks in the United States. It causes a large spectrum of human diseases from diarrhea to eye and throat infections (Jiang, 2006; Mena and Gerba, 2008). Quantitative data on adenovirus occurrence in water and wastewater are available in the current literature, because their occurrence is often used as a marker for human viral contamination in waters. The dose-response model for this virus has also been developed previously based on epidemiological studies (Haas et al., 1999); thus, it is an organism for which quantitative risk assessment is possible.

TABLE A-1 Estimated Pathogen Densities in Secondary Effluent

Organism Concentration
Adenovirus 5,000 gc/L
Norovirus 10,000 gc/L
Salmonella 500 cfu/L
Cryptosporidium 17 oocysts/L

Human adenovirus occurrence data in the exemplar were collected from peer-reviewed literature, which used molecular biology–based genome quantification methods (He and Jiang, 2005; Albinana-Gimenez et al., 2006; Bofill-Mas et al., 2006; Haramoto et al., 2007; Katayama et al., 2008; Fong et al., 2010; Schlindwein et al., 2010). Reported densities vary over a wide range, between 1 and 105 genome copies/liter (gc/L). A density of 5 × 103 gc/L, which falls in the most frequently reported range, was chosen by the committee as a typical concentration in secondary effluent.

Although the genome-based method is sensitive at detecting viral presence, it does not provide information on viral infectivity; thus the presence of a genome



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Appendix A Details in Support of the Risk Exemplar in Chapter 6 TABLE A-1 Estimated Pathogen Densities in In this appendix, the committee details the data Secondary Effluent and assumptions used in the risk exemplar, described in Chapter 6. Organism Concentration Adenovirus 5,000 gc/L Norovirus 10,000 gc/L PATHOGENS 500 cfu/L Salmonella 17 oocysts/L Cryptosporidium The exemplar includes four enteric pathogens: adenovirus, norovirus, Salmonella, and Cryptosporidium. In the following discussion, each organism is briefly diseases from diarrhea to eye and throat infections described and an estimated density in secondary efflu- ( Jiang, 2006; Mena and Gerba, 2008). Quantitative ent for use in the exemplar is provided. Modifications data on adenovirus occurrence in water and wastewa- in those densities are then estimated that correspond ter are available in the current literature, because their to each of the scenarios in the exemplar. Finally, the occurrence is often used as a marker for human viral densities are adjusted so that they are in the same form contamination in waters. The dose-response model for as those used in dose-response testing, and a risk of this virus has also been developed previously based on illness is estimated using quantitative microbial risk epidemiological studies (Haas et al., 1999); thus, it is estimation methodology (Haas et al., 1999). an organism for which quantitative risk assessment is possible. Human adenovirus occurrence data in the exemplar Pathogen Occurrence in Secondary Effluents were collected from peer-reviewed literature, which The information and assumptions used to estimate used molecular biology–based genome quantification pathogen occurrence in undisinfected secondary waste- methods (He and Jiang, 2005; Albinana-Gimenez et water effluent as a starting point for the risk exemplar is al., 2006; Bofill-Mas et al., 2006; Haramoto et al., 2007; discussed in this section and summarized in Table A-1. Katayama et al., 2008; Fong et al., 2010; Schlindwein Pathogen reduction from subsequent disinfection and et al., 2010). Reported densities vary over a wide range, treatment steps is discussed in the next section. between 1 and 105 genome copies/liter (gc/L). A den- sity of 5 × 103 gc/L, which falls in the most frequently reported range, was chosen by the committee as a typi- Adenovirus cal concentration in secondary effluent. Adenovirus is a waterborne pathogen that has Although the genome-based method is sensitive at been associated with recreation-related outbreaks in detecting viral presence, it does not provide informa- the United States. It causes a large spectrum of human tion on viral infectivity; thus the presence of a genome 233

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234 APPENDIX A Salmonella is not synonymous with the presence of an infectious unit (IU). Dose-response studies were conducted using Salmonella has long been a well-studied waterborne tissue culture assays for quantification of IU. There is enteric pathogen. The concentration of this micro- limited quantitative information on the side-by-side organism in raw sewage ranges between 102 and 104 data for IUs and genome copies although it is generally cfu/100 mL (Asano et al., 2007). Taking the average known that infectivity decays more rapidly than does of these two and assuming the same 2-log reduction the density of genome copies (R.A. Rodriguez et al., during primary and secondary treatment that normally 2009). Based on a single report (He and Jiang, 2005), occurs for Escherichia coli produces an estimate of 5 × where three side-by-side polymerase chain reaction 102 cfu/L in secondary effluent for the exemplar. Again, (PCR) and tissue culture assays were performed on ade- the dose-response model for this organism has been novirus isolated from secondary effluent, it is estimated developed previously based on epidemiological studies that the ratio between genome copies and infectious (Haas et al., 1999). units is approximately 1,000:1. Thus, genome count densities estimated for adenovirus for each scenario Cryptosporidium were reduced by three orders of magnitude to convert to IUs during the risk estimation process. Cryptosporidium is associated with both drinking water and recreational water outbreaks in the United Norovirus States. The health significance of this organism has motivated a number of studies to understand its oc- Norovirus is one of the most important enteric currence and persistence in the water environment viruses for both waterborne and foodborne outbreaks in (Rose et al., 1996; Gennaccaro et al., 2003; Robertson the United States. Several recent studies have focused et al., 2006; Lim et al., 2007; Castro-Hermida et al., on occurrence of this virus in water and wastewater 2008; Chalmers et al., 2010; Fu et al., 2010). The peer (Pusch et al., 2005; Haramoto et al., 2006; Katayama et reviewed literature reports a range of Cryptosporidium al., 2008; Nordgren et al., 2009; Victoria et al., 2010). densities in secondary treated effluents varying with In these studies, the density of the norovirus genome season and geographical location. Studying this litera- varies over a wide range with densities as high as 107 ture, a density of 50 oocysts/L is estimated as typical gc/L reported in raw sewage. Based on the published for secondary effluents. However, most of the data on literature, a density of 104 gc/L is estimated to be the oocyst concentration were determined using the indi- median occurrence in secondary effluent. Once again, rect fluorescent-antibody assay (IFA), which also does although the genome-based method is sensitive at not directly measure IUs. A study comparing oocyst detecting the presence of copies of the genome of the densities as determined by IFA with IU densities as de- virus, it does not provide information on viral infectiv- termined by a focus-detection-method most-probable- ity. Norovirus has not been successfully cultivated using number technique in cell culture (Slifko et al., 1999) conventional tissue culture methods, and so no work is found a ratio of approximately 3:1 in 18 samples of available to establish the ratio between genome density secondary effluent (Gennaccaro et al., 2003). Using this and IU density. ratio, a density of 50 oocysts/L produces an estimate of A dose-response model for norovirus was used 17 IUs/L in secondary effluent for the exemplar. More based on the study by Teunis et al. (2008), using the es- than one dose-response model has been developed for timate for single unaggregated virus. Because norovirus this organism (Haas et al., 1999). has not been successfully cultivated in vitro, these stud- ies were conducted using fresh virus and the genome Assumptions Concerning Fate, Transport, and count quantified by PCR. Published work has shown Removal that the fraction of genome copies that are infectious drops rapidly in the environment (R.A. Rodriguez et The following is a brief discussion of assumptions al., 2009). Thus, for the purposes of this exemplar, the made regarding fate, transport, and removal for the same 1,000:1 was applied before risk estimation. pathogens in the exemplar.

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235 APPENDIX A Scenario 1—de Facto Reuse water treatment plant uses free chlorine for primary disinfection and that it has been modified to obtain 1 As discussed in Chapter 6, Scenario 1 represents log of additional inactivation of Cryptosporidium us- a conventional water supply drawn from a surface wa- ing UV light (required dose, 2.5 mJ/cm2). Under the ter source with a 5 percent contribution from treated LT2ESWTR, the inactivation credit for UV at a dose wastewater. For this scenario a nonnitrified secondary of 2.5 mJ/cm2 is 1 log Cryptosporidium and negligible effluent is assumed to be disinfected with chlorine prior for viruses. Thus the 2-log virus inactivation require- to discharge to bring fecal coliforms from 105/100 mL ment must be met by free chlorine. At a low tempera- to 200/100 mL, a 2.7-log reduction (99.8 percent). ture of 5 °C (a conservative surface water temperature), The exemplar assumes combined chlorine is the ac- this corresponds to a C∙t of 8 mg-min/L. So the process tive disinfectant. According to Butterfield and Wattie train is conventional water treatment (coagulation, (1946), E. coli, the principal target of the fecal coliform flocculation, filtration) followed by UV (3 mJ/cm2) and measurement, are generally as or more resistant to chlorination (8 mg-min/L) and this train will get the combined chlorine than Salmonella spp. (S. dysenteriae). full 4-log removal/inactivation credit for both Crypto- Accordingly, the same 2.7-log reduction was assumed sporidium and viruses, required by the LT2ESWTR. for Salmonella spp. For adenovirus and norovirus, re- In the exemplar, excluding dilution, the overall moval was assumed to follow the removal credit for reduction in Cryptosporidium is assumed to correspond viruses in the surface water treatment rule, which was to the 4-log removal required by EPA, and the reduc- judged to be negligible. It is also assumed that this tions in adenovirus and norovirus are also assumed to limited disinfection has no impact in the viability of correspond to EPA’s assumptions for 2 logs of physical Cryptosporidium. removal in conventional treatment and an additional The water treatment plant has been modified 2 logs of inactivation via chlorination (totaling 4-log to be compliant with the requirements of the Long- removal). EPA’s LT2ESWTR does not provide direct Term-2 Enhanced Surface Water Treatment Rule guidance on Salmonella spp., and so an independent (LT2ESWTR; EPA, 2006a). Assuming no diminish- analysis is required. Salmonella spp. are understood to ment during transport in the river, the Cryptosporidium be more sensitive to free chorine than are E. coli (But- contribution from upstream wastewater plants in the terfield et al., 1943). According to Figure 13-5 in Crit- exemplar puts the density of oocysts in the water plant’s tenden et al. (2005), a C∙t of approximately 1 mg-min/L source water at approximately 0.85 oocyst/L. This clas- is required for 2-log removal of E. coli at 25 ºC; thus, sifies the supply in “Bin 2” according to LT2ESWTR, a C∙t of 8 mg-min/L will achieve a 16-log reduction which corresponds to a requirement of 1 log of removal of E. coli. For the effect of chlorine on Salmonella spp., for Cryptosporidium beyond the performance of con- the exemplar discounts this to an inactivation credit ventional treatment. Hence, additional treatment to of 4 logs to account for temperature. Exposure to low achieve 1- and 2-log removal is required for Crypto- levels of UV light also affects Salmonella spp. and to sporidium and viruses, respectively.1 some degree adenovirus and norovirus. According to For the exemplar it is assumed that the drinking data in a recent Dutch review (Hijnen et al., 2005a), a low-pressure UV dose of 2.5 mJ/cm2 should result in a 1 Actually, the LT2ESWTR gives conventional drinking water 1.5-log inactivation of Salmonella spp., a 0.1-log reduc- treatment (without disinfection) credit for the physical removal of tion in adenovirus, and a 0.3-log reduction in norovirus. 2 logs of Cryptosporidium and viruses, respectively. Where Crypto- sporidium is concerned, this is a bit confusing because the regula- In the exemplar, the effect of UV on the Salmonella tion requires 4-log removal of Cryptosporidium for any alternative spp. is included, and the impact of UV on these viruses process in Bin 2, but requires only one additional log removal for is neglected. Thus, the overall water treatment plant conventional treatment. It appears that the 2-log credit is actually a holdover from the earlier interim enhanced surface water treatment removal is 4 logs for Cryptosporidium, 5.5 logs for Sal- rule, which established the 2-log credit and that EPA expects 3-log monella spp., and 4 logs for adenovirus and norovirus. removal of Cryptosporidium. For the exemplar it is assumed that A summary of removal for microorganisms and their the drinking water treatment plant achieves 3-log Cryptosporidium resulting densities is given in Table A-2. removal and requires UV disinfection to achieve one additional log. An actual plant might make other choices from the microbial treatment toolbox to accomplish similar results.

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236 APPENDIX A TABLE A-2 Summary of Log (and %) Removals of Schijven et al. (1998, 1999, 2000) are considered a Pathogens in Various Steps of Scenario 1 benchmark for removal under relatively homogeneous and steady-state conditions in a saturated sand aquifer. Process Adenovirus Norovirus Salmonella Cryptosporidium D uring dune recharge using water that was spiked Disinfection 0 0 2.7 0 with bacteriophages (MS2 and PRD1), Schijven et al. at wastewater (0%) (0%) (99.8%) (0%) treatment plant (1999) reported a virus reduction of 3 logs within the Dilution in 1.3 1.3 1.3 1.3 first 2.4 m and another linear 5-log removal within stream (95%) (95%) (95%) (95%) the following 27 m of transport in the subsurface. Removal in 4.0 4.0 4.0 3.0 Spiking tests with bacteriophages conducted by Fox water treatment (99.99%) (99.99%) (99.99%) (99.9%) et al. (2001) under field conditions suggested a 7-log Removal by 0 0 1.5 1.0 removal over a distance of 100 m. During a deep-well UV (0%) (0%) (96.8%) (90%) (~300 m below surface) injection study, Schijven et al. (2000) spiked pretreated surface water with bac- teriophages (MS2 and PRD1) and observed a 6-log removal within the first 8 m of travel followed by an Scenario 2—Soil Aquifer Treatment and Groundwater additional 2-log removal during the subsequent 30 Recharge m of travel. These values are well within the range of virus inactivation values reported by others (Dizer As described in Chapter 7, in Scenario 2, a nitrified et al., 1984; Yates et al., 1985; Powelson et al., 1990). and partially denitrified secondary effluent, which has Findings from these field studies demonstrated that been subjected to granular media filtration, is applied infiltration into a relatively homogeneous sandy aquifer to surface spreading basins with subsequent soil aquifer can achieve up to 8-log virus removal over a distance of treatment (SAT). The effluent is not disinfected. It is 30 m in about 25 days. Loveland et al. (1996) revealed assumed that the water will remain in the subsurface some of the conditions that favor removal of viruses for 6 months with no dilution from native groundwater. in the subsurface and concluded that precipitated fer- W hile the assumption of no dilution is in contrast to ric, manganese, and aluminum oxyhydroxides form hydrogeological characteristics of subsurface systems, positively charged patches on the soil grains. These this condition was selected to assign removal credits patches provide favorable attachment sites for nega- only to physicochemical and biological attenuation tively charged viruses. Powelson and Gerba (1994) also processes occurring during SAT. Subsequently, the reported that virus inactivation is more efficient under water is abstracted from a deep well, disinfected at the unsaturated than saturated infiltration conditions. In wellhead, and chlorinated prior to consumption, as- addition, some studies reported that virus inactivation suming no blending occurs with other source waters in may be enhanced by microbial activity (Quanrud et al., the distribution system. These assumptions describe a 2003; Gupta et al., 2009) resulting in the expression of scenario where drinking water is consumed that origi- enzymes that are detrimental to other microorganisms nates 100 percent from reclaimed water after additional ( Yates et al., 1987). Considering that these conditions treatment using SAT. (i.e., biological activity, sequence of unsaturated to Effect of SAT on Virus Removal. D uring percolation saturated conditions, presence of metal oxyhydroxides) are commonly observed in SAT systems and the reten- through porous media or groundwater recharge, the tion time in the potable reuse case study of the exem- removal of pathogens from infiltrating reclaimed water plar using groundwater recharge via SAT is 6 months, depends primarily on three attenuation mechanisms: a conservative removal of 6-log was assumed during s training, inactivation, and attachment to aquifer SAT for both adenovirus and norovirus. grains (McDowell-Boyer et al., 1986). Subsurface systems, such as riverbank filtration and SAT have Effect of SAT on Bacteria Removal. For subsurface been reported as efficient treatment systems for the treatment, such as SAT and riverbank filtration, several removal of microbial contaminants. With respect to studies have reported efficient inactivation of coliform virus removal, the field experiments conducted by

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237 APPENDIX A bacteria. Havelaar et al. (1995) reported removal in fate of bacterial spores in gravel aquifers suggest a high excess of 5 logs for total coliform during transport of mobility and similar removal of Cryptosporidium, mak- impaired river water over a 30-m distance from the ing bacterial spores adequate surrogate measures. Rhine River and over a 25-m distance from the Meuse Findings from various field studies suggest that River to a well. During a deep-well (~300 m below large removal of anaerobic and aerobic spores occurs surface) injection study, Schijven et al. (2000) spiked during passage across the surface water–groundwater pretreated surface water with E. coli and observed a interface, and lesser removal is observed during ground- 7.5-log removal within the first 8 m of travel in the water transport away from this interface. Havelaar subsurface. During SAT in the Dan Region Project, et al. (1995) reported 3.1-log removal of anaerobic Israel, Icekson-Tal et al. (2003) measured 5.3-log spores during transport over a 30-m distance from removal of total coliform and 4.5-log removal of fecal the Rhine River to a well and 3.6-log removal over a coliform bacteria. Total coliforms were rarely detected 25-m distance from the Meuse River to a well. Schi- in riverbank-filtered waters, with 5.5- and 6.1-log re- jven et al. (1998) measured 1.9-log removal over a 2-m ductions in average concentrations in wells relative to distance from a canal. This finding is consistent with river water (Weiss et al., 2005). The efficient removal field monitoring results from a riverbank filtration site of fecal and total coliform bacteria during subsurface in Wyoming, where Gollnitz et al. (2005) observed treatment and essentially their absence in groundwater a 2-log removal of Cryptosporidium in groundwater abstraction wells after SAT or riverbank filtration was wells characterized by flow paths between 6 and 300 confirmed by various other studies (Fox et al., 2001; m. At a riverbank filtration site at the Great Miami Hijnen et al., 2005b; Levantesi et al., 2010). Consider- River, Gollnitz et al. (2003) reported a 5-log removal ing these field and controlled laboratory studies as well of aerobic spores in a production well located 30 m off as a retention time of 6 months in the subsurface for the river. Wang et al. (2002) reported 1.7-log removal the surface spreading groundwater recharge case of the of aerobic spores over the first 0.6-m distance and 3.8- exemplar, 6 logs of removal was assumed for bacteria log removal over a distance of 15.2 m at a riverbank (Salmonella) through SAT treatment in the exemplar. filtration facility at the Ohio River. Less efficient re- moval of approximately 0.6 logs over a distance of 12 Effect of SAT on C r yptosoridium . U nder the m was reported for transport solely within groundwater LT2ESWTR (EPA, 2006a), immobilization of (Medema et al., 2000). For an injection experiment in Cryptosporidium within granular media, often accom- a sandy aquifer at distances relatively far from an in- plished by sand or riverbank filtration can result in jection well, Schijven et al. (1998) observed negligible cost-effective removal of protozoa and other patho- removal of anaerobic spores over a 30-m distance. gens (Ray et al., 2002a,b; Tufenkji et al., 2002). By Besides straining, inactivation might be important for meeting certain design standards (i.e., unconsolidated, the attenuation of Cryptosporidium during subsurface predominantly sandy aquifer with 25- or 50-ft setback treatment. For two Cryptosporidium strains examined, from the river), EPA assigns 0.5-log or 1.0-log removal NRC (2000) assumed a 1-log inactivation over 100 credits for Cryptosporidium, respectively. Log removal days and 180 days (corresponding to an inactivation calculations require counts per volume of the same rate coefficient of 0.023/d and 0.013/d, respectively). organism in the initial water source (e.g., reclaimed Considering these field and controlled laboratory stud- water) and groundwater wells. Given the usually low ies as well as a retention time of 6 months in the surface counts of Cryptosporidium in impaired source waters, spreading groundwater recharge case of the exemplar log removal studies under ambient conditions are not (much longer than is the case for any of the preceding practical. Bacterial spores, anaerobic clostridia spores, citations), a removal credit of 6 log for Cryptosporidium and aerobic endospores are resistant to inactivation in was assumed for SAT treatment. the subsurface, similar in shape to Cryptosporidium but Effect of Wellhead Chlorination. The exemplar as- smaller and sufficiently ubiquitous in both impaired surface water and groundwater that log removal can sumes that chlorination is provided at the wellhead in be calculated. Findings from studies investigating the order to achieve a 4-log virus removal credit, and so this

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238 APPENDIX A is the removal assigned to adenovirus and norovirus. At cannot be ensured unless monitoring demonstrates that the membranes continue to perform. 15 °C (an approximate groundwater temperature), this would require a C∙t of 4 mg-min/L. Salmonella removal Effect of Reverse Osmosis. In principle, reverse osmo- is estimated using the equation in Table 13-3 in Crit- sis, which is designed to remove individual ions from tenden et al. (2005), and adjusting the log inactivation water, should completely reject all microorganisms. On by a factor of 2 for every 10 °C, results in a removal the other hand, testing has demonstrated that these of 6 logs. No removal is assumed in the exemplar for organisms can pass through these installations unless Cryptosporidium via chlorine. The removals are sum- special quality control practices, beyond those normally marized in Table A-3. exercised in the desalination community, are under- taken (Trussell et al., 2000). This is particularly true Scenario 3—Reverse Osmosis, Advanced Oxidation, and where viruses are concerned because these organisms Deep-Well Injection. have been shown to pass through flaws in the mem- branes themselves (Adham et al, 1998). More limited Scenario 3, as discussed in Chapter 6, represents a quality control on the installation of the membranes water supply drawn from a deep well in an aquifer fed and O-rings has been shown adequate to manage the by injection of reclaimed water that received secondary rejection of bacteria and protozoa. As a result, a removal treatment by chloramination, microfiltration, reverse credit of 99.99 percent is assumed for both bacteria and osmosis, and high-output low-pressure ultraviolet Cryptosporidium but a credit of only 97 percent is as- (UV) light supplemented with hydrogen peroxide (also sumed for viruses because this roughly corresponds to called advanced oxidation). the removal of conductivity through reverse osmosis.2 Effect of Microfiltration. Olivieri et al. (1999) showed Effect of UV/H2O2. UV/H2O2 installations in exist- median coliphage removals of 2 logs for microfiltration ing projects are designed using low-pressure UV to and 3 logs for ultrafiltration, but for microfiltration, re- provide 1.2-log removal of NDMA. It has been dem- movals as low as 0.1 log were observed on one occasion onstrated that this corresponds to a delivered UV dose and removals below 1 log were observed 30 percent of of approximately 1,200 mJ/cm2 (Sharpless and Linden, the time. Consequently no virus removal was assumed 2003). Low doses of peroxide and chloramines (both 3 in the exemplar for microfiltration. There is a great deal to 5 mg/L) are also present and these absorb some of of literature on the removal of bacteria and protozoa the UV; nevertheless, the remaining effective UV dose via membrane filtration. This literature shows virtually complete rejection so long as the membranes remain in- is nearly 10-fold above the dose specified by EPA for tact ( Jacangelo et al., 1997). Methods used were able to 4-log removal of adenovirus or Cryptosporidium in the demonstrate between 4 and 5 logs for Cryptosporidium LT2ESWTR. Evidence is that Salmonella and norovi- and 7 and 8 logs for bacteria. For the purposes of the rus are more easily removed than adenovirus (Hijnen et exemplar, 99.99 percent removal is assumed for both al., 2005a). Consequently a removal of 6 logs (99.9999 Salmonella and Cryptosporidium. It should be cautioned percent) is assumed for all these organisms, and this is that, for specific projects, these removals must be dem- thought to be very conservative. onstrated for each membrane type and, even then, they Effect of Deep-Well Injection on Pathogen Re- moval. The lack of microbial activity and the potential absence of metal oxyhydroxides in deep aquifers re- TABLE A-3 Summary of Logs (and %) Pathogen Removal Assumed for Processes in Scenario 2 charged with reverse osmosis–treated reclaimed water will provide less favorable conditions for virus removal Process Adenovirus Norovirus Salmonella Cryptosporidium SAT + 6 mo 6 6 6 6 (99.9999%) (99.9999%) (99.9999%) (99.9999%) 2 Based on data from the first 2 years of operation of the Orange Chlorination 4 4 6 0 County Water District’s Advanced Water Purification Facility (B. at wellhead (99.99%) (99.99%) (99.9999%) (0%) D univan, OCWD, personal communication, 2011).

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239 APPENDIX A and/or inactivation. Thus, in the exemplar, no removal 5. Table A-6 summarizes the coefficients derived from credit for viruses was considered for the reuse scenario the literature in order to facilitate those calculations, as using direct injection into a potable aquifer. Likewise, well as the pertinent dose-response model equations. given the lack of a surface water–groundwater interface Table A-7 summarizes the quantitative microbial in direct injection projects and a rather low inactivation risk assessment in three parts for the three scenarios. rate in aquifers, no removal credits for Salmonella or Table A-7A details the pathogen densities at the point Cryptosporidium were assigned for the direct injection of exposure (i.e., the tap). The virus densities in Table process and groundwater travel time. It is noteworthy A-7A were used to compute the daily risk (based on a that these are conservative assumptions, because patho- daily consumption of 1 L) using equations (1) or (2) as gen inactivation could occur in deep aquifers receiving appropriate for the organism being considered. Table reverse osmosis permeate. A-7B shows the estimated levels of excess illness that result from the drinking water from a single exposure Effect of Wellhead Chlorination. As described under (1-L consumption). A consumption of 1 L/d is used Scenario 2, wellhead chlorination was assigned a 4-log for consumption of unboiled water as contrasted with virus removal credit, and a 6-log removal for Salmonella. the consumption of 2 L/d used for total consumption No removal is assumed in the exemplar for Cryptospo- (Roseberry and Burmaster, 1992). ridium via chlorine. The removals are summarized in Table A-4. TRACE ORGANIC CHEMICALS For potable reuse projects, there is growing concern Summary of Results on Pathogen Densities among stakeholders and the public about potential ad- Using the assumptions and results summarized verse health effects associated with the presence of trace earlier, calculations were conducted to produce an organic chemicals in reclaimed water. Reclaimed water estimate of the densities of each of the four pathogens can contain thousands of chemicals originating from studied in the drinking water produced in each of the consumer products (e.g., household chemicals, personal three scenarios. The results of these calculations are care products, pharmaceutical residues), human waste summarized in Table A-5. (e.g., natural hormones), industrial and commercial dis- charges (e.g., solvents, heavy metals), or chemicals that are generated during water treatment (e.g., disinfection Quantitative Microbial Risk Assessment byproducts) (see Chapter 3). For the risk exemplar, 24 The pathogen densities shown in Table A-5 can be chemicals were selected that represent different classes translated into risk of illness using the methodologies of contaminants (i.e., nitrosamines, disinfection by- for quantitative risk assessment summarized in Chapter products, hormones, pharmaceuticals, antimicrobials, flame retardants, and perfluorochemicals). TABLE A-4 Summary of Logs (and %) Pathogen Chemical Occurrence in Secondary Effluents Removal Assumed for Processes in Scenario 3 Process Adenovirus Norovirus Salmonella Cryptosporidium For disinfection byproducts in secondary effluents, data were obtained from Krasner et al. (2008), which Microfiltration 0 0 4 4 (MF) (0%) (0%) (99.99%) (99.99%) reported occurrence of unregulated and regulated disin- Reverse osmosis 1.5 1.5 4 4 fection byproducts for secondary wastewater treatment (RO) (97%) (97%) (99.99%) (99.99%) processes with various disinfection practices for a range UV/H2O2 6 6 6 6 of different geographical regions of the United States. (99.9999%) (99.9999%) (99.9999%) (99.9999%) These datasets were validated and augmented with re- Deep-well 0 0 0 0 sults from field monitoring efforts reported by Snyder Injection + 6 mo (0%) (0%) (0%) (0%) et al. (2010a) and Dickenson et al. (2011). Hormones Chlorination at 4 4 6 0 wellhead (99.99%) (99.99%) (99.9999%) (0%) and pharmaceutical occurrence data were adopted

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240 TABLE A-5 Summary of Exemplar Calculations to Establish Pathogen Levels in Drinking Water for the Three Scenarios Scenario 1 De facto Reuse: Secondary effluent, disinfected with chlorine, diluted 95%, conventional water treatment Removal Removal in 2° Effluent through Discharge 95% Concentration in Die-off & WTP Influent Conventional Removal Drinking Water Concentration Disinfection Concentration dilution River Predation Concentration WTP by UV Concentration Norovirus 10,000 gc/L 0% 10,000 gc/l 95% 500 gc/L 0% 500 gc/L 99.99% 0.0% 0.050 gc/L Adenovirus 5,000 gc/L 0% 5,000 gc/L 95% 250 gc/L 0% 250 gc/L 99.99% 0.0% 0.025 gc/L Salmonella 500 CFU/L 99.80% 1.0 CFU/L 95% 0.1 CFU/L 0% 0.1 CFU/L 99.99% 96.8% 1.6E-07 CFU/L Cryptosporidium 17 oocyst/L 0% 17 oocyst/L 95% 0.85 oocyst/L 0% 0.85 oocyst/L 99.9% 90% 8.5E-05 oocysts/L Scenario 2 Secondary effluent, no disinfection, followed by SAT, 6 mo retention, no dilution, free chlorine disinfection 2° Effluent Concentration SAT Removal Concentration at Wellhead Removal by Chlorination Drinking Water Concentration Norovirus 10,000gc/L 99.9999% 1.0E-02 gc/L 99.99% 1.0E-06 gc/L Adenovirus 5,000 gc/L 99.9999% 5.0E-03 gc/L 99.99% 5.0E-07 gc/L Salmonella 500 CFU/L 99.9999% 5.0E-04 CFU/L 99.9999% 5.0E-10 CFU/L Cryptospoidium 17 oocyst/L 99.9999% 1.7E-05 oocysts/L 0.00% 1.7E-05 oocysts/L Scenario 3 Secondary effluent, MF, RO, UV/H202, groundwater injection, free chlorine disinfection Removal Removal through 2° Effluent Removal Removal through AWT Effluent Groundwater Wellhead Removal by Drinking Water Concentration through MF through RO UV/H2O2 Concentration Injection Concentration Free Chlorine Concentration Norovirus 10,000 gc/L 0% 97% 99.9999% 3.0E-04 gc/L 0% 3.0E-04 gc/L 99.99% 3.0E-08 gc/L Adenovirus 5,000 gc/L 0% 97% 99.9999% 1.5E-04 gc/L 0% 1.5E-04 gc/L 99.99% 1.5E-08 gc/L Salmonella 500 CFU/L 99.99% 99.99% 99.9999% 5.0E-12 CFU/L 0% 5.0E-12 CFU/L 99.9999% 5.0E-18 CFU/L Cryptosporidium 17 oocyst/L 99.99% 99.99% 99.9999% 1.7E-13 oocysts/L 0% 1.7E-13 oocysts/L 0% 1.70E-13 CFU/L

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241 APPENDIX A TABLE A-6 Dose-Response Parameters for Quantitative Microbial Risk Assessment Beta Poisson α Beta Poisson β Exponential k Beta Poisson N50 Dose-Response Modelsa Norovirusb 0.04 0.055 −a  d p = 1 − 1 +   β Adenovirusc 0.4172 p = 1 – exp(–kd) 0.3126 23600 Salmonellad −a  1    2 − 1 d  a   p = 1 − 1 +  N 50      0.0042 p = 1 – exp(–kd) Cryptosporidiume aIn these equations, p and d are the single exposure risk and dose, respectively. As discussed previously, when the drinking water concentration is measured in genome count densities, the concentration is divided by 1000 to convert to infectious units. bTeunis et al. (2008, Table III—pooled response for infection). cFrom Haas et al. (1999, Table 9-15). dFrom Haas et al. (1999, Table 9-3, Pooled Salmonella strains) eOriginal Iowa strain data for Cryptosporidium (Haas et al., 1996). from studies comparing the chemical composition of (2010a), Laws et al. (2011), and Drewes et al. (2003). It reclaimed and conventional waters at seven field sites has been demonstrated that disinfection processes used in the United States (Snyder et al., 2010a; Dickenson in the treatment of wastewater and drinking water are et al. 2011), with some additional data from select effective in removing a significant number of hormones pharmaceuticals adopted from Krasner et al. (2008). and pharmaceutical compounds (Snyder et al., 2007), Other chemicals of interest, such as antimicrobials, but disinfection processes also introduce disinfectant chlorinated flame retardants, and perfluorochemicals, byproducts, and for these reasons, previously cited were adopted from field monitoring efforts using measurements are used in the exemplar as opposed secondary treated effluents reported by Snyder et al. to the model-based estimates used for microbials. Table A-8 lists the concentrations of the 24 chemicals in disinfected secondary effluent, and Table A-9 shows TABLE A-7 Summary of Quantitative Microbial Risk the concentrations for undisinfected secondary effluent. Assessment of Risk Exemplar Scenario 1 Scenario 2 Scenario 3 Assumptions Concerning Fate, Transport, and Organism De Facto Reuse SAT MF/RO/UV Removal A. Pathogen Densities Norovirus 0.050 gc/L 1.0E-06 gc/L 3.0E-08 gc/L Scenario 1—De Facto Reuse Adenovirus 0.025 gc/L 5.0E-07 gc/L 1.5E-08 gc/L 1.6E-07 CFU/L 5.0E-10 5.0E-18 Salmonella For the scenario describing de facto reuse (Scenario CFU/L CFU/L 1), it was assumed that the surface water providing 8.5E-05 oocysts/L 1.7E-05 1.7E-13 Cryptosporidium dilution of treated wastewater discharge to a drinking oocysts/L oocysts/L water source represents a pristine water quality with B. Risk of Illness (illness/(capita*d)) respect to trace organic chemical concentrations, as Norovirus 3.6E-05 7.3E-10 2.2E-11 reported by Krasner et al. (2008). The concentration of Adenovirus 1.0E-05 2.1E-10 6.3E-12 unregulated and regulated disinfection byproducts after 1.7E-11 5.4E-14 0 Salmonella conventional treatment (including coagulation/floccu- 3.6E-07 7.1E-08 0 Cryptosporidium lation, filtration, free chlorine as primary disinfectant, C. Relative Risk and residual chloramines) is adopted from Krasner et al. Norovirus 1 2.0E-05 6.0E-07 (2008). The effectiveness of conventional water treat- Adenovirus 1 2.0E-05 6.0E-07 1 3.2E-03 0 Salmonella ment for hormones, pharmaceuticals, and other trace 1 0.2 0 Cryptosporidium organic chemicals was adopted from an investigation of

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242 APPENDIX A TABLE A-8 Estimation of Margin of Safety for Scenario 1—Drinking Water from Surface Water Source with 5% Contribution from Wastewater Discharges 2° Effluent with Surface Blend 95% SW Drinking Risk Based Margin of Safety Name of Chemical Unit Disinfect. Watera 5% 2° Effluent Waterb Action Level (unitless) Nitrosaminesc,d,e 0.35 N-Nitrosodimethylamine (NDMA) ng/L 10 0.7 Disinfection Byproductsf,g,h Bromate µg/L N/A N/A N/A N/A 10 N/A <0.5 <1.1i Bromoform µg/L 18 3 80 27 <1 <1.7i Chloroform µg/L 25 5 80 16 60 Dibromoacetic acid µg/L 10 60 54 Dibromoacetonitrile µg/L 16 70 80 Dibromochloromethane µg/L 80 <1 <2i Dichloroacetic acid µg/L 31 5 60 12 20 Dichloroacetonitrile µg/L 0.3 20 <1 <4i Haloacetic acid (HAA5) µg/L 70 10 60 6 <0.5 <3.1i Trihalomethanes THMs) µg/L 57 30 80 3 Pharmaceuticalsf,g,h 350,000,000 Acetaminophen ng/L 1 350,000,000 120,000,000 Ibuprofen ng/L 38 280,000,000 Carbamazepine ng/L 180 10 19 19 186,900,000 10,000,000 Gemfibrozil ng/L 305 1 16 16 140,000,000 8,600,000 80,000,000 Sulfamethoxazole ng/L 30 160,000,000 Meprobamate ng/L 240 5 17 17 280,000,000 17,000,000 Primidone ng/L 98 1 6 6 58,100,000 10,000,000 Othersc,f,g,h Caffeine ng/L 210 10 20 20 70,000,000 3,500,000 17-β Estradiol 35,000,000 ng/L 0.15 3,500,000 3,500,000 Triclosan ng/L 2.5 2,100,000 84,000 TCEP (tris(2-chloroethyl)phosphate) ng/L 400 2,100,000 PFOS ng/L 54 10 12 12 200 17 NOTES: N/A = data not available. aTaken from median conc. from Krasner national occurrence survey (Krasner et al., 2008) bRemaining after conventional surface water treatment (including coagulation/flocculation; filtration, free chlorine; residual chloramines); no transformation occurred in surface water. cKrasner et al. (2008). dSnyder et al. (2010a). eDickenson et al. (2011) fBellona et al. (2008). gM. Wehner, OCWD, personal communication, 2009. hBellona and Drewes (2007). iWhen surface water concentrations were below the detection limit, one-half the detection limit was used in the dilution calculations. (In contrast, for Scenarios 2 and 3, the detection limit is used for concentrations below the detection limit to be a more conservative assumption in the relative comparison and because secondary effluent is likely to contain higher levels of contaminants than pristine surface waters.) If the final calculated concentration was below the detection limit, less than the detection limit was reported. five conventional drinking water plants in the United charge, an effluent quality is assumed that mirrors the States by Snyder et al. (2010a). The removal efficien- secondary effluent qualities assumed in Scenario 1, ex- cies assumed were within the same range as reported by cept that Scenario 2 represents a undisinfected, filtered, Snyder et al. (2008a) for conventional drinking water secondary wastewater effluent. The water quality after processes. 6 months of SAT, assuming no dilution with ambient groundwater, and a final disinfection with free chlorine Scenario 2—Soil Aquifer Treatment and Groundwater at the wellhead, is based on findings from field moni- Recharge toring efforts at SAT and riverbank filtration installa- tions (Drewes et al., 2003; Hoppe-Jones et al., 2010; For Scenario 2 describing a potable reuse system Snyder et al., 2010a; Laws et al., 2011). The data are using surface spreading leading to groundwater re- augmented by field monitoring results for disinfection

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243 APPENDIX A TABLE A-9 Estimation of Margin of Safety for Scenario 2—Drinking Water from Deep-Well Supplied by Spreading of Undisinfected, Filtered, Effluent 2° Effluent, Drinking Risk-Based Margin of Safety Name of Chemical Unit No Disinfection Water Conc. Action Level (unitless) Nitrosaminesa,b 0.35 N-Nitrosodimethylamine (NDMA) ng/L 2.7 0.7 Disinfection Byproductsa,b,c Bromate µg/L N/A N/A 10 N/A Bromoform µg/L 2 0.5 80 160 Chloroform µg/L 10 1 80 80 60 Dibromoacetic acid µg/L 0.5 60 140 Dibromoacetonitrile µg/L 70 Dibromochloromethane µg/L N/A N/A 80 N/A 60 Dichloroacetic acid µg/L 1 60 20 Dichloroacetonitrile µg/L 20 Haloacetic acid (HAA5) µg/L 2 5 60 12 Trihalomethanes (THMs) µg/L 1 5 80 16 Pharmaceuticalsa,b,c 350,000,000 Acetaminophen ng/L 10 350,000,000 Ibuprofen ng/L 50 5 280,000,000 56,000,000 Carbamazepine ng/L 200 150 186,900,000 1,200,000 Gemfibrozil ng/L 610 61 140,000,000 2,300,000 Sulfamethoxazole ng/L 295 221 160,000,000 720,000 Meprobamate ng/L 320 32 280,000,000 8,800,000 Primidone ng/L 130 130 58,100,000 450,000 Others 70,000,000 Caffeine ng/L 280 70,000,000 17-β Estradiol 35,000,000 ng/L 1.5 3,500,000 Triclosana,b,c ng/L 25 2.5 2,100,000 840,000 TCEP (Tris(2-Chloroethyl)-phosphate)2 a,b,c ng/L 400 360 2,100,000 5,800 PFOSa,b,c,d ng/L 54 54 200 3.7 PFOAa,b,c,d ng/L 21 21 400 19 NOTES: N/A = data not available. aBellona et al. (2008). bM. Wehner, OCWD, personal communication, 2009. cBellona and Drewes (2007). dSnyder et al. (2010a). byproducts after SAT reported by Krasner et al. (2008) after 6 months of retention in a potable aquifer, assum- and Dickenson et al. (2011). ing no dilution with ambient groundwater, followed by chlorination at the point of abstraction is based on field monitoring data reported by Wehner (2009) and Scenario 3—Reverse Osmosis, Advanced Oxidation, and Snyder et al. (2010a). Deep-Well Injection The concentration levels of each of the 24 chemi- For the potable reuse scenario via direct injection cals discussed above are presented in Tables A-8, A-9, (Scenario 3), a reclaimed water quality after microfil- and A-10 for the three scenarios for the source waters tration, reverse osmosis, and advanced oxidation (UV/ or the reclaimed water applied to the spreading or direct H2O2) is assumed. The concentration of disinfection injection projects. Additionally, the “drinking water” byproducts in this reclaimed water after advanced column represents the final water quality delivered to treatment is adopted from monitoring at full-scale customers at the end of the final treatment processes installations as reported by Wehner (2009), Bellona et from the drinking water treatment plant (Scenario 1) al. (2008), and Bellona and Drewes (2007). Hormones, or after wellhead disinfection after withdrawal from the pharmaceuticals, and other trace organic chemicals in environmental buffer (Scenarios 2 and 3). Table A-11 this highly treated reclaimed water are adopted from summarizes the concentrations of contaminants at the Wehner (2009), Bellona and Drewes (2007), Bellona et point of exposure for all three scenarios. al. (2008), and Snyder et al. (2010a). The water quality

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244 APPENDIX A TABLE A-10 Estimation of Margin of Safety for Scenario 3—Reuse with MF/RO/UV-H2O2 and Groundwater Injection 2° Effluent, no Drinking Risk Based Margin of Safety Name of Chemical Unit disinfection Water Conc. Action Level (unitless) Nitrosaminesa,b 0.35 N-Nitrosodimethylamine (NDMA) ng/L 0.7 Disinfection Byproductsa,b,c 2 Bromate µg/L 10 160 Bromoform µg/L 80 Chloroform µg/L 20 5 80 16 60 Dibromoacetic acid µg/L 60 Dibromoacetonitrile µg/L N/A N/A 70 N/A 160 Dibromochloromethane µg/L 80 60 Dichloroacetic acid µg/L 60 Dichloroacetonitrile µg/L N/A N/A 20 N/A Haloacetic acid (HAA5) µg/L 13 5 60 12 Trihalomethanes (THMs) µg/L 30 10 80 8 Pharmaceuticalsa,b,c 350,000,000 Acetaminophen ng/L 350,000,000 280,000,000 Ibuprofen ng/L 280,000,000 190,000,000 Carbamazepine ng/L 186,900,000 <1 Gemfibrozil ng/L 3 140,000,000 140,000,000 <1 Sulfamethoxazole ng/L 2 160,000,000 160,000,000 930,000,000 Meprobamate ng/L 0.4 280,000,000 58,000,000 Primidone ng/L 58,100,000 Others 223,000,000 Caffeine ng/L 70,000,000 17-β Estradiol 35,000,000 ng/L 3,500,000 2,100,000 Triclosana,b,c ng/L 3 2,100,000 210,000 TCEP (Tris(2-chloroethyl)-phosphate)a,b,c,d ng/L 2,100,000 200 PFOSa,b,c,d ng/L 200 80 PFOAa,d,c,d ng/L 400 NOTES: N/A = data not available. aBellona et al. (2008). bM. Wehner, OCWD, personal communication, 2009. cBellona and Drewes (2007). dSnyder et al. (2010a). Quantitative Chemical Risk Assessment maximum recommended therapeutic doses (MRTDs), and National Library of Medicine/National Institute of For each of the 24 chemicals identified in the Health maximum tolerated doses (MTDs) from which three water treatment scenarios, potential lifetime a drinking water action level can be derived (see also health risks were assessed by calculating margins of Chapter 5). Table A-12 shows the source of the values safety (MOSs), or the risk-based action level (RBAL) used for each of the 24 chemicals. divided by the concentration of contaminant in water These risk-based values have undergone extensive (see Tables A-8 to A-10). RBALs represent bench- regulatory and/or peer review and incorporate uncer- mark values for risk or existing chemical-specific tainty factors to account for variability and uncertainty action levels, such as EPA maximum contaminant in the hazard database, and for nonpharmaceuticals, the levels (MCLs), EPA health advisories, World Health values consider effects on sensitive subpopulations (e.g., Organization (WHO) drinking water guidelines, or children, pregnant women, the elderly). Conversion of chemical-specific EPA reference doses (RfDs), Agency an oral reference toxicity dose to a drinking water ac- for Toxic Substances and Disease Registry (ASTDR) tion level uses assumptions about daily drinking water minimal risk levels (MRLs), WHO acceptable daily intake, consumer body weight, and the relative source intakes (ADIs), Food and Drug Administration (FDA) contribution of water to total human exposure. The

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245 APPENDIX A TABLE A-11 Summary of the Levels of the 24 Chemicals in the Drinking Water for Each Scenario Name of Chemical Unit Scenario 1 Scenario 2 Scenario 3 Nitrosamines <2 <2 <2 N-Nitrosodimethylamine (NDMA) ng/L Disinfection Byproducts <5 Bromate ng/L N/A N/A <0.5 Bromoform µg/L 3 0.5 Chloroform µg/L 5 1 5 <1 <1 <1 Dibromoacetic acid µg/L <1.3 <0.5 Dibromoacetonitrile µg/L N/A <1 <0.5 Dibromochloromethane µg/L N/A <1 <1 Dichloroacetic acid µg/L 5 <1 <1 Dichloroacetonitrile µg/L N/A Haloacetic acid (HAA5) µg/L 10 5 5 Trihalomethanes THMs) µg/L 30 5 10 Pharmaceuticals <1 <1 <10 Acetominophen (paracetamol) ng/L <2.4 <1 Ibuprofen ng/L 5 <1 Carbamazepine ng/L 19 150 <1 Gemfibrozil ng/L 16 61 <2 <1 Sulfamethoxazole ng/L 221 <0.3 Meprobamate ng/L 17 32 <1 Primidone ng/L 6 130 Others <1 <3 Caffeine ng/L 20 17-β Estradiol <0.1 <0.1 <0.1 ng/L <0.6 <1 Triclosan ng/L 2.5 <25 <10 TCEP ng/L 360 (Tris(2-chloroethyl)phosphate) <1 PFOS ng/L 12 54 <5 PFOA ng/L 11 21 dose metric is expressed as concentrations in drinking Risk Based Action Level (mg/L) = water. Although numerous contaminants present in [ X ] mg/kg/day × 70 kg × 0.20 the three scenarios have existing drinking water action 2 L/day levels (such as an EPA MCL), a significant number of where chemicals have only oral RfDs, ADIs, or are pharma- = Oral RfD, ADI, or other reference point such ceuticals with MRTDs, all expressed as milligrams per X as MRTD; kilogram of body weight per day. Risk values such as RfDs and ADIs are generally based upon experimental 70 kg = Default adult body weight;3 doses from repeat-dose animal studies that have been 0.2 = Default relative source contribution from adjusted with appropriate uncertainty factors to ac- drinking water of 20%; count for animal to human extrapolation and interhu- 2 L/d = Default daily drinking water intake for a 70- man sensitivity, while MRTDs are generally derived kg adult. from doses employed in human clinical trials. To derive = Acceptable level in drinking water (i.e., esti- Y RBALs for chemicals without existing drinking water mated action level) action levels, the following formula was used: 3 WHO drinking water guidelines are based upon a default adult body weight of 60 kg, while a default adult body weight of 70 kg is used by EPA and was used by this NRC committee to estimate RBALs using FDA MRTDs.

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246 APPENDIX A TABLE A-12 Summary of Risk-Based Action Values and Sources Name of Chemical Unit Source of Risk Value Risk Based Action Level Nitrosamines NDMA ng/L EPA HA (EPA, 2011) 0.7 Disinfection Byproducts Bromate µg/L EPA MCL (EPA, 2011) 10 Bromoform µg/L EPA MCL (EPA, 2011) 80 Chloroform µg/L EPA MCL (EPA, 2011) 80 DBCA µg/L EPA MCL (EPA, 2011) 60 DBAN µg/L WHO Drinking Water Guideline Value (WHO, 2008) 70 DBCM µg/L EPA MCL (EPA, 2011) 80 DCAA µg/L EPA MCL (EPA, 2011) 60 DCAN µg/L WHO Drinking Water Guideline Value (WHO, 2008) 20 HAA5a µg/L EPA MCL (EPA, 2011) 60 THM µg/L EPA MCL (EPA, 2011) 80 Pharmaceuticals Acetominophen ng/L FDA MRTD (FDA, 2011) 350,000,000 Ibuprofen ng/L FDA MRTD (FDA, 2011) 280,000,000 Carbamazepine ng/L FDA MRTD (FDA, 2011) 190,000,000 Gemfibrozil ng/L FDA MRTD (FDA, 2011) 140,000,000 Sulfamethoxazole ng/L FDA MRTD (FDA, 2011) 160,000,000 Meprobamate ng/L FDA MRTD (FDA, 2011) 280,000,000 Primidone ng/L FDA MRTD (FDA, 2011) 58,000,000 Other Caffeine ng/L FDA MRTD (FDA, 2011) 70,000,000 17-β Estradiol ng/L FDA MRTD (FDA, 2011) 3,500,000 Triclosan ng/L EPA RfD (EPA, 2008) 2,100,000 TCEP ng/L ASTDR MRL (ASTDR, 2009) 2,100,000 PFOS ng/L Provisional EPA HA (EPA, 2011) 200 PFOA ng/L Provisional EPA HA (EPA, 2011) 400 aHAA5: monochloroacetic acid (MCAA) + dichloroacetic acid (DCAA) + trichloroacetic acid (TCAA) + Monobromoacetic acid (MBAA) + dibromoacetic acid (DBAA). RBAL Ideally, the EPA bases the relative source contribution MOS = Estimated Drinking Water Level (RSC) on data regarding exposures that occur from (Scenario 1, 2, or 3) food, air, and other important media such as personal care products or pharmaceutical agents (Donohue and With the exception of the chemical NDMA, the Orme-Zavaleta, 2003). When data allow exposure MOS values are all greater than 1, indicating that there pathways for other selected media to be quantified, is unlikely to be a significant health risk, even after a default RSC values of 20, 50, or 80 percent are possible. lifetime of exposure to these individual chemicals. The In the absence of any data, a default RSC of 20 percent analysis does not take into account combined health ef- is used (Donohue and Orme-Zavaleta, 2003). EPA also fects of contaminant mixtures. Simultaneous exposure assumes a daily drinking water intake of 2 L/d for an to multiple chemicals would occur in all three scenarios; adult (EPA, 2004). thus, a consideration of mixtures would not signifi- MOSs were estimated for each of the 24 contami- cantly affect the relative risk comparison for purposes nants (see summary of results in Table A-13). Where of the risk exemplar. NDMA was not detected in any compounds were not detected, the lower limit on the of the scenarios, but the MOS is less than 1 because the MOS was determined using the level of detection at detection limit (2 ng/L) is above EPA’s health advisory the concentration in drinking water. level of 0.7 ng/L. The large MOS for pharmaceuticals listed in Table A-13 indicates that potential health risks

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247 APPENDIX A TABLE A-13 Margin of Safety for 24 Chemicals for from exposure to pharmaceuticals in reclaimed water is Each Scenario small. However, RBALs for pharmaceuticals presented in Table A-12 assume that long-term exposure to phar- Chemical Scenario 1 Scenario 2 Scenario 3 maceuticals will result in toxicity similar to short-term Nitrosamines exposures, which is an admitted area of uncertainty. >0.4 >0.4 >0.4 NDMA Additional research to evaluate the effects of long-term, Disinfection Byproducts >2 Bromate N/A N/A low-level exposure to chemicals in reclaimed water >160 Bromoform 27 160 could provide additional insight on whether these areas Chloroform 16 80 16 >60 >60 >60 of uncertainty are biologically significant. DBCA >54 >140 DBAN N/A >80 >160 DBCM N/A >60 >60 DCAA 12 VERIFICATION >20 >20 DCAN N/A HAA5 6 12 12 The committee performed several levels of veri- THM 2.7 16 8 fication on this risk exemplar exercise to ensure that Pharmaceuticals the results are sound. In the compilation of the water >350,000,000 >350,000,000 >35,000,000 Acetaminophen >120,000,000 >280,000,000 Ibuprofen 56,000,000 quality data that provide a basis for the analysis, three >190,000,000 Carbamazepine 10,000,000 1,200,000 committee members worked to gather and/or review >140,000,000 Gemfibrozil 8,600,000 2,300,000 >80,000,000 >160,000,000 Sulfamethoxazole 720,000 the chemical occurrence data used and three additional >930,000,000 Meprobamate 17,000,000 8,800,000 members gathered and/or reviewed the microbial oc- >58,000,000 Primidone 10,000,000 450,000 currence data. After the risk analysis calculations were Others completed and the assumptions documented by the >70,000,000 >23,000,000 Caffeine 3,500,000 17-β Estradiol >35,000,000 >35,000,000 >35,000,000 committee members, the chair carefully reviewed the >3,500,000 >2,100,000 Triclosan 840,000 analysis. When the report was in review, Appendix A >84,000 >210,000 TCEP 5,800 >200 and the spreadsheet containing the calculations were PFOS 17 4 >80 PFOA 36 19 reviewed in detail by a non-committee member with experience in risk assessment. With no oversight, other than to explain the task, this individual reviewed the values and formulas used in each cell of the spreadsheet and compared them to the information documented in Appendix A. Following this verification, a few minor errors were detected that were discussed with the com- mittee chair and staff and subsequently corrected.

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