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Comparative Human Health Risk Analysis of Coastal Community Water and Waste Service Options Mary E. Schoen,*,† Xiaobo Xue,‡ Troy R. Hawkins,§ and Nicholas J. Ashbolt∥ †

Soller Environmental, Inc., 3022 King Street, Berkeley, California 94703, United States Oak Ridge Institute for Science and Education, U.S. Environmental Protection Agency, 26 W. Martin Luther King Drive, Cincinnati, Ohio 45268, United States § U.S. Environmental Protection Agency, 26 W. Martin Luther King Drive, Cincinnati, Ohio 45268, United States ∥ University of Alberta, Room 3-57D South Academic Building, Edmonton, Alberta T6G 2G7, Canada ‡

S Supporting Information *

ABSTRACT: As a pilot approach to describe adverse human health effects from alternative decentralized community water systems compared to conventional centralized services (business-as-usual [BAU]), selected chemical and microbial hazards were assessed using disability adjusted life years (DALYs) as the common metric. The alternatives included: (1) composting toilets with septic system, (2) urine-diverting toilets with septic system, (3) low flush toilets with blackwater pressure sewer and on-site greywater collection and treatment for nonpotable reuse, and (4) alternative 3 with on-site rainwater treatment and use. Various pathogens (viral, bacterial, and protozoan) and chemicals (disinfection byproducts [DBPs]) were used as reference hazards. The exposure pathways for BAU included accidental ingestion of contaminated recreational water, ingestion of cross-connected sewage to drinking water, and shower exposures to DBPs. The alternative systems included ingestion of treated greywater from garden irrigation, toilet flushing, and crop consumption; and ingestion of treated rainwater while showering. The pathways with the highest health impact included the ingestion of cross-connected drinking water and ingestion of recreational water contaminated by septic seepage. These were also among the most uncertain when characterizing input parameters, particularly the scale of the cross-connection event, and the removal of pathogens during groundwater transport of septic seepage. A comparison of the health burdens indicated potential health benefits by switching from BAU to decentralized water and wastewater systems.

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INTRODUCTION

In a series of work, we propose to evaluate innovative water and wastewater technology from a system sustainability perspective−including human health, environment, and economic aspects. Water systems applicable to rural-developing communities that largely rely on septic systems were investigated using data relevant for Falmouth, Massachusetts. Falmouth faces expanding urbanization and increased tourism, with the predominating septic systems resulting in excessive nutrient exports and coastal eutrophication. To assist in identifying community water systems to mitigate eutrophication and provide for sustainable activities, initial work has focused on life-cycle assessment22 and reported here, human health risk assessment. Xue et al.23 present an explanation of the key metrics (including the DALY) and tools considered to facilitate sustainably assessments of community water services. Here we present a comparison of DALYs for annual exposure to reference hazards for five alternative water systems. The

The human health risk associated with water and wastewater system use has been assessed separately for conventionally treated drinking water,1−7 contact with wastewater,3,8,9 rainwater use,10−13 and greywater uses.14 However, there is limited analysis that considers the entire community water and wastewater system15 and alternative, decentralized system options.16 For exposures relating to drinking, nonpotable, and wastewater systems, various pathogens (viral, bacterial, and parasitic protozoan)7,17 and chemicals (disinfection byproducts [DBPs])1 are relevant. Both enteric and environmental pathogens along with DBPs may result in health outcomes when ingested or inhaled,18,19 ranging from acute illness to chronic disease and mortality. Therefore, to assess the disease burden from decentralized community water systems we conducted a human health risk assessment using the Disability Adjusted Life Years (DALYs) metric as advocated by WHO20 to incorporate various health outcomes. DALYs are the sum of years of life lost by premature mortality and years lived with disability.21 Using DALYs, both nonfatal and fatal health outcomes can be considered and compared. © 2014 American Chemical Society

Received: Revised: Accepted: Published: 9728

March July 1, July 2, July 2,

17, 2014 2014 2014 2014

dx.doi.org/10.1021/es501262p | Environ. Sci. Technol. 2014, 48, 9728−9736

Environmental Science & Technology

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associated with treated rainwater include a suite of pathogens reported in rainwater, Campylobacter jejuni, Salmonella enterica, Cryptosporidium spp., Giardia spp., E. coli O157:H7, Norovirus, and Legionella pneumophila.11 Chloroform was selected as a reference chemical for exposure to DBPs from a centralized drinking water system treated with free chlorine based on a screening risk analysis.6 Step 1: Estimated DALY per Illness Case. The DALYs per case of illness for each reference pathogen were adapted from previous work that estimated the disease burden in The Netherlands from microbial hazards.31−34 The DALYs per illness case used in the current study were 4.6 × 10−3 DALYs for C. jejuni,34 1.7 × 10−3 for Cryptosporidium,33 5.5 × 10−2 for E. coli O157:H7,31 9.5 × 10−4 for Norovirus,32 and 1.4 for Chloroform.2 The health outcomes, duration, and probability of recovery in the United States for the population at large were assumed to be comparable to those used for The Netherlands. The DALYs per illness case from exposure to DBPs was calculated using bladder cancer as the health outcome. Bladder cancer has been linked to exposure to other DBPs for males35 but not to chloroform, the selected reference DBP. The DALYs per case of illness was calculated based on a quantitative risk assessment of chlorinated drinking water2 with a rate of bladder cancer recovery specific to the United States.36 Step 2: Simulated Risks by Water Service. The primary aims of the risk assessment were to capture the natural variability in pathogen dose and to identify the uncertain parameters for which additional data can be collected. The exposure assessment was conducted using Monte Carlo simulation with 10 000 iterations in software package R. Each Monte Carlo iteration represents a possible year of system use. Within each iteration, multiple hazard doses were estimated one for each exposure event during the year, each with an independently sampled set of input parameters. The probability of illness for each event (Pilln) was estimated using the dose− response relationships and probabilities of illness given infection in Table S1, SI. The annual probability of illness (Pilla) was estimated assuming n events per year:

business-as-usual (BAU) system consisted of a conventional, centralized drinking water system and a centralized wastewater treatment system. The centralized wastewater treatment system was replaced with composting toilets and on-site greywater treatment by septic tank in CT-SS. The centralized wastewater treatment was replaced with urine-diverting toilets and on-site fecal solids treatment by septic tank in UD-SS. For systems CTSS and UD-SS, all potable and nonpotable water uses were supplied by a centralized drinking water system. A low flush toilet and blackwater pressure sewer was utilized in BE-GR with a community energy recovery system and on-site greywater treatment and reuse for toilet flushing, outside hosing, and potentially to water homegrown salad crops. BE-GRR was identical to BE-GR with the addition of onsite rainwater collection, treatment and use for showering. The energy recovery system in BE-GR was not relevant to the calculation of the human health metric, but was important for other metrics such as greenhouse gas emissions and energy use. See Figure S1, Supporting Information (SI), for system diagrams of each option. Technical details about each system are described below when relevant to the calculation of the DALY.

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APPROACH

The morbidity and mortality associated with a particular community water system is generally not known, even when a major epidemiology study is undertaken.24−26 Therefore, the DALY was calculated for each system using simulated estimates of risk, following the quantitative risk assessment paradigm.27 The DALY was estimated for annual exposure to the exposure pathways and reference hazards for each system for a population of 10 000, assuming that a fraction of the total population are exposed to each exposure pathway. The pathways selected were considered the most likely exposures or exposures with the greatest infection risk given the systems considered. Certain exposure pathways that were shared by all systemssuch as consumption of municipal potable water were not included. The steps followed to estimate the annual DALY for each system include: 1. Estimation of the DALY per case of illness for each reference hazard from the literature; 2. Estimation of the annual probability of illness for each reference hazard and exposure pathway through quantitative risk assessment; and 3. Combination of the results of steps 1 and 2 to estimate the total annual DALY for each system. The final step (Step 4) was the calculation of the relative health burden, when the total annual DALY of each system was compared to BAU.

Pill a = 1 − [(1 − Pill1)∗ (1 − Pill 2) ∗...∗ (1 − Pill n)]

(1)

Recurring exposures were considered independent, and immunity from prior exposure was not considered. Probability distributions were used for input parameters with natural variability when data was available. Point estimates were used when information on variability was not reported in the literature. For highly uncertain inputs, best estimates were assumed (see Table S2, SI). Parametric sensitivity analysis was performed to determine the possible changes in the median predicted DALY when select input parameters were changed from the best estimate. The peer-reviewed dose−response relationships were used as reported and additional analysis (such as second order Monte Carlo analysis) was not conducted to account for the dose−response uncertainty given the limited possibility for additional data collection. The risk assessment computations are described below for each water system. Accidental Ingestion of Recreational Water Contaminated with Wastewater. The annual probability of illness from accidental ingestion of recreational water contaminated with WWTP effluent containing Norovirus was estimated for a secondary-treated, UV-disinfected WWTP under BAU. In Falmouth, the WWTP effluent is discharged to large sand beds from which the treated wastewater infiltrates into the soil,

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REFERENCE HAZARDS Referenced hazards represent classes of pathogens or chemicals with potential negative health impacts. Norovirus was selected as the reference hazard representing infectious viral pathogens associated with poorly treated sewage or wastewater treatment plant (WWTP) effluent based on previous work that identified viruses as representative of the dominant risk.9,28 In addition, Cryptosporidium spp. was included in the analysis of a crossconnection event because it is resistant to chlorination. Campylobacter jejuni and Norovirus were selected for the exposure pathways associated with greywater based on the high incidence of Norovirus in the population19 and a screening risk analysis of greywater reuse.29 The limitations of using Norovirus as a reference hazard have been described elsewhere.18,28,30 The reference pathogens for exposure pathways 9729



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wastewater.42 The resulting dilution range was used to characterize a uniform distribution with lower limit of 0.01 and upper limit of 0.1. During runoff conditions, the recreational water was assumed to be contaminated by a plume of runoff contaminated from failing septic systems. The probability of a waterbody receiving Norovirus was modeled such that the probability increases with the number of tanks in the vicinity and the probability of Norovirus occurrence in a household. The dose of Norovirus during runoff conditions from accidental ingestion of recreational water was estimated as follows:

to the groundwater table, and then to West Falmouth Harbor. Each swimming event may be one of three conditions: no WWTP pathogen treatment failure (with probability, P = 0.968), rainfall induced leaking or overflow (P = 0.016), and treatment failure (P = 0.016). The leaking pipe condition was considered to result in raw wastewater contamination, and the treatment failure condition was considered to result in no treatment removal. The dose of Norovirus (Dn) by accidental ingestion of recreational water was calculated as follows: Dn = Vr∗0.001∗Dil ww,c∗ 10(C ww,n − R ww,n − R s,n)

(2)

Dn = Vr∗0.001∗[10C s,n ∗ (1 − (1 − Pn)(F s * N s))]

where, Vr is the volume of water ingested (mL); Dilww,c is the dilution factor in recreational water for condition c, Cww,n is the raw wastewater concentration for Norovirus (log10 genome· L−1); Rww,n is the secondary-treated, UV-disinfected wastewater log removal/inactivation for Norovirus; and Rs,n is the log removal/inactivation from groundwater transport for Norovirus. The characterization of the pathogen densities in the WWTP effluent and volume of water ingested were from previous U.S. EPA studies.9,37 The dilution factors and treatment failure rates were best estimates (Table S2, SI). The probability of a leakage event was based on the daily probability of a runoff event when the soil was saturated with runoff data for the Cape Cod area.38,39 Norovirus removal through the sandy soil for travel time between two and 20 days was characterized as uniform assuming a lower limit of removal estimated from bench-scale experiments8 and an upper limit estimated from field studies using the enteric virus model, PRD-1 phage.40 The number of swim events per year was based on the reported number of beach visits to a comparable beach in Rhode Island, with a mean of eight visits.41 In reality, only a fraction of the recreational sites are affected by the wastewater effluent and leakage; however, the first pass assumed that all swimmers swim at affected sites. Although many of the input variables were uncertain, additional sensitivity analysis was not conducted due to the relatively low resulting predicted risks. Ingestion of Recreational Water Contaminated with Septic Tank Seepage Containing Fecal Solids. The annual probability of illness from accidental ingestion of recreational water contaminated with septic tank effluent containing Norovirus from fecal solids under UD-SS was estimated accounting for both nominal septic seepage through the groundwater and by septic tank-leachfield failure. Each swimming event may be one of two conditions: rainfall producing runoff (P = 0.016) and nominal (P = 0.984). During nominal conditions, the recreational water was assumed to be contaminated with septic seepage from normally operating septic fields that travels through the saturated soil. During rainfall producing runoff conditions, the recreational water was assumed to be contaminated with a plume of septic effluent from the failing systems. The daily probability of a runoff event was based on the approach proposed by Teng et al.39 with runoff data for the Cape Cod area.38 The dose during nominal conditions was calculated using eq 2 with the same inputs as the previous recreational water exposure pathway (without treatment); this assumes that there is sufficient effluent from multiple septic systems such that the Norovirus density was equivalent to raw wastewater. One exception was the septic seepage dilution, Dils. The dilution was estimated by dividing the observed nitrogen levels in Falmouth ponds by the best estimate nitrogen concentration in

(3)

where Cs,n is the concentration of Norovirus in the failing septic tank seepage (log10 genomes·L−1); Pn is probability of Norovirus being present in one septic tank over 30 days preceding rain; Fs is the septic system failure rate; and Ns is the number of septic systems affecting the recreational waterbody The concentration of Norovirus in the failing septic seepage was characterized by a uniform distribution with limits determined from previous septic tank risk assessment work.8 No pathogen removal or dilution was applied for overland flow. The probability of Norovirus illness in a household of two people for at least one of 30 days was calculated using the binomial distribution with the daily probability of Norovirus occurrence pn (described in the nonpotable greywater exposure pathway section) as ∑i 30!/(i!*(30-i)!)*(pni)*(1-pn)(30‑i). Accidental Ingestion of Recreational Water Contaminated with Septic Seepage Containing Only Greywater. The annual probability of illness for accidental ingestion of recreational water contaminated with septic seepage originating from greywater (no toilet blackwater contribution) was identical to that of conventional septic seepage, except for the characterization of the Norovirus density in the effluent. First, the Norovirus density in greywater (Cg,n) was estimated from the pathogen density (Cf,n) in the feces of infected persons as follows: Cg,n = (10C g,fi /Cf,fi) ∗Cf,n

(4)

where Cg,fi is the density of fecal indicator in the greywater (log10 cfu·L−1); Cf,fi is the density of fecal indicator in the feces (cfu·g−1); and Cf,p is the density of Norovirus in the feces of infected persons (genomes·L−1). Deere and colleagues provide a compilation of pathogen densities and indicators which we use here.29 The Norovirus density in septic tank effluent was characterized as uniform with an upper limit as the fresh Norovirus density in greywater (Cg,n) from eq 4 and a lower limit calculated as Cg,n − 5.3 based on the Norovirus attenuation from septic tank passage.8 Ingestion of Household Potable Water Contaminated with a Long-Duration, High-Dilution Cross-Connection to Sewage. The annual probability of illness from ingestion of potable water contaminated with raw wastewater effluent containing Norovirus and Cryptosporidium was estimated considering a range of event characteristics. Each independent, simulated event (N = 10 000) was assumed to have a duration of 30 to 130 days. The dose of each pathogen was calculated for each day over the duration of the event: Dp = Vp∗Dilcc∗ (10C ww,p) ∗10(−kp * C d,c * t)

(5)

where Vp is the volume of potable water ingested per day (L); Dilcc is the cross-connection dilution factor; kp Chick−Watson 9730



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inactivation constant for pathogen p (mg min·L−1)−1; Cd,c is the concentration of chlorine in the distribution system (mg·L−1); and t is the contact time (min). The characterization of the pathogen densities in the raw wastewater and volume of water ingested were as previously reported in U.S. EPA studies.9,43 The inactivation constant was derived by Teunis et al.3 in a QMRA of small duration negative pressure events. The estimated dilution factors for the small duration pressure events informed the selection of a conservative dilution factor of 0.001 for the long duration event simulated here. This parameter was further examined by sensitivity analysis. The contact time and concentration of chlorine in the system were best estimates. Ingestion of Potable Water Derived from Treated Rainwater while Showering. The annual probability of illness from daily ingestion of treated, collected rainwater from showering under BE-GRR was estimated assuming the use of a sand filtration and UV-disinfection treatment system combined with the heat reduction of pathogens in the hot water tank (as rainwater was only assumed to be used for hot water production). The daily hazard dose was assumed to vary due to the natural variation in pathogen density in collected rainwater and with treatment performance. Contamination by zoonotic pathogens is likely episodic and driven by a combination of animal access to the collection surface, event magnitude and frequency, as well as other factors.44 Nonenteric pathogens, like Legionella, that can proliferate while in storage will have densities in stored rainwater that depend on the characteristics of the storage, like presence of particulate matter and warm temperature.44 In two recent large-scale studies in Australia and The Netherlands,11,44 pathogens were reported in a low number of the samples across time and space. The same low number was reported in a review of literature on collected rainwater by Ahmed et al.45 and Abbasi and Abbasi46 with the exception of qPCR methods for some pathogens.47 Nonetheless, the density of pathogens in the rainwater may vary over orders of magnitude.11,44 The dose of each reference pathogen was estimated for each daily shower. The probability of a detection event (Pe,p) for each pathogen was characterized by a uniform distribution using the reported fraction of positive samples from multiple studies.10−12,45 The probability of a detection event of virulent E. coli O157:H7 was characterized as a point estimate set at the fraction of 30 rainwater samples that had E. coli present with possible virulence genes.45 During nonevents the dose was assumed to be zero for pathogens. During events conditions, when treatment was not in failure, the dose was calculated: Dp = 10(Log(C r,p * h p) −∑(R t,p))∗Vi

triangular distribution with parameters set according to the minimum, maximum, and median reported results from Chapman et al.11 The best data for the density of L. pneumophila in collected rainwater was enumerated using qPCR10,47 and was used to characterize their density. The exposure model is not specified here, but was based on previous work.18 Potentially virulent E. coli density in rainwater was characterized by a uniform distribution from the log-transformed reported densities of total E. coli enumerated by membrane filtration method.45 The fraction of E. coli that is human infectious was set at 0.005 based on the lack of detection of toxin genes associated with E. coli O157:H7 in isolates from collected rainwater45 and was further explored using sensitivity analysis with a higher limit of 0.48 based on the fraction of E. coli isolates harboring toxin genes.45 Little data were available on the density of parasitic protozoa in rainwater; hence the densities of Cryptosporidium and Giardia spp. were characterized as uniform, using the minimum and maximum reported values in wildlife-impacted waters.48 The fraction of Campylobacter, Salmonella, Cryptosporidium, and Giardia spp. assumed human infectious was 0.1.9 Ingestion of Nonpotable Water Derived from Treated Greywater. The pathogen dose from ingestion of nonpotable water (toilet flushing and garden irrigation) derived from treated greywater for BE-GR was calculated: Dp = 10(Log(C r,p * h p) −∑(R t,p))∗Vt

(8)

where Cg,p is the pathogen p density in greywater (cfu, genomes·L−1); hp is the human infectious fraction for enteric pathogens; Rt,p is the pathogen specific log removal by treatment; and Vt or h is the volume of water ingested during toilet or hose use (L). Treatment included both sand filtration and UV-disinfection (Table S2, SI). The volumes of water ingested (Vt and Vh) were conservative best estimates and assume three flushing events and one hosing event each day. The pathogen density in greywater (Cg,p) was estimated from the pathogen density in the feces of infected persons as in eq 4. The human infectious fraction for enteric pathogens was assumed to be 1.0. The Monte Carlo analysis sampled the inputs to eq 8 according to the daily probability of each outcome: no pathogen source present, pathogen source present and no treatment failure, pathogen source present and UV treatment failure, pathogen source present and filter treatment failure, and pathogen source present and total treatment failure. The filter failure rate was set at the UV failure rate. The daily probability of pathogen presence in greywater (pp) was calculated: pp = (CI p *DI p)/(A ∗365)

(7)

where Cr,p is the pathogen p density in rainwater (cfu, cells, oocysts, cysts·L−1); hp is the human infectious fraction for enteric pathogens; Rt,p is the pathogen specific log removal by treatment; and Vi is the volume of water ingested during showering (L). Treatment included both reduction of pathogens due to high temperatures in the hot water tank and UV-disinfection (Table S2, SI). The UV- failure rate (Fuv) was estimated as once every two months, for which only the (hot water) heat inactivation was applied. The treatment failure rate remains uncertain and likely technology specific.11 The density of Campylobacter spp. and Salmonella enterica in collected rainwater during events was characterized by a

(9)

where CIp is the reported number of cases of illness; A is the population; and DIp is the duration of illness (days). The reported number of cases of illness (CIp) was characterized using a triangular distribution.19 Using eq 9, the daily probability of pathogen presence (pp) was variable, but small. An annual probability of illness was estimated over the duration of 365 days using eq 1. Salad Crop Consumption Contaminated with Nonpotable Water Derived from Treated Greywater. The annual illness risk associated with ingestion of treated greywater from consumption of contaminated salad crop from watering under BE-GRR was estimated similar to the previous greywater nonpotable exposure scenario. The volume of water ingested 9731



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Table 1. Median Annual DALY for Dominant Hazardsa annual DALY per 10 000 people alternative BAU BAU BAU, CT-SS, UD-SS, BEGR CT-SS UD-SS BE-GR, BEGRR BE-GR, BEGRR BE-GRR

risk description

Campylobacter

Accidental ingestion of recreational water contaminated with wastewater Ingestion of drinking water contaminated with a cross-connection to conventional wastewater Dermal exposure to disinfection byproducts in conventionally treated potable water

NA

Accidental ingestion of recreational water contaminated with greywater septic tank leakage Accidental ingestion of recreational water contaminated with fecal solids septic tank leakage Ingestion of nonpotable water derived from onsite treated greywater Salad crop consumption contaminated with nonpotable water derived from on-site treated greywater Ingestion of potable water derived from on-site treated rainwater while showering

Salmonella NA

Cryptosporidum NA

Giardia NA

NA

NA

5.7 × 10

NA

NA

NA

−1

E. coli O157:H7 NA

Norovirus 2.6 × 10

−5 −1

Chloroform NA

NA

NA

3.2 × 10

NA

NA

NA

NA

5.8 × 10−4

NA

NA

NA

NA

2.2 × 10−3

NA

NA

NA

NA

NA

NA

2.7 × 10−1

NA

0.0

NA

NA

NA

NA

0.0

NA

0.0

NA

NA

NA

NA

0.0

NA

NA

NA

2.3 × 10−2

NA

7.7 × 10−2

NA

NA

NA

a

BAU with a centralized, conventional water and wastewater system; CT-SS with greywater treatment via septic tank and composting toilet; UD-SS with fecal solids treatment via septic tank and urine diversion toilet; BE-GR with a low flush toilet and blackwater pressure transport system and onsite greywater treatment and reuse; BE-GRR with a low flush toilet and blackwater pressure transport system and on-site greywater and rainwater treatment and reuse; NA- not applicable or very low risk.

22% based on Australian participation, but likely community specific.14 The total annual DALY per system alternative was the sum of the annual DALYs for each exposure pathway for each Monte Carlo iteration. Step 4: Relative DALY Difference for Each Alternative System. The relative DALY difference was calculated for each Monte Carlo iteration as the total annual DALY for BAU minus the total annual DALY for the alternative system. Hence, a positive relative DALY indicates a potential health benefit posed by switching to an alternative system.

(Vs) was estimated in a previous risk assessment by Petterson et al.49 It was assumed that there were 10 consumption events14 and that the contaminated salad crops were freshly contaminated and not washed when consumed, thereby representing a high end estimate of risk. As this pathway appears to be insignificant when compared with others considered, we did not revisit this conservative estimate. The other inputs were characterized as described in the previous section. Annual Dermal Exposure to DBPs from Showering. The risk of cancer from lifetime exposure to DBPs through showering was estimated assuming disinfection with free chlorine for all systems except BE-GRR. A screening analysis performed by Wang et al.6 showed that the dermal risk dominates the inhalation risk for the shower scenario. Therefore, only the dermal risk was estimated. The lifetime risk of cancer was conservatively estimated for the reference DBP using the chemical specific dermal/oral slope factor (SF) [mg/kg-d]−1 and the dermally absorbed dose (Dd) [mg/kgday]: risk = SF∗Dd

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RESULTS Annual Probability of Illness and DALY for Each Reference Pathogen by Alternative. The median annual probability of illness or lifetime cancer risk associated with each reference pathogen by exposure pathway is presented in Table S3, SI. The exposure pathway with the highest estimated annual probability of illness was ingestion of Cryptosporidium and Norovirus via drinking water contaminated by cross-connection to conventional wastewater under BAU. This was also the exposure pathway with the greatest annual DALY. The median annual DALY per 10 000 people for each exposure pathway is summarized in Table 1. The annual DALYs for reference hazards with negligible illness risks were omitted from Table 1. Accidental ingestion of recreational water contaminated with septic seepage under UD-SS had the second highest annual DALY. The ingestion of E. coli O157:H7 while showering and Cryptosporidium derived from on-site treated rainwater under BE-GRR was also relatively high compared to the other exposure pathways examined. The pathways with the smallest predicted DALY per 10 000 people were those associated with ingestion of nonpotable water derived from treated greywater and salad crop watering. Total Annual DALY for Each System. The total annual DALY per 10 000 people for each alternative water system was calculated as the sum of the Monte Carlo iterations of the annual DALYs for each relevant exposure pathway. Considering only the median values, the annual DALY of each alternative

(10)

The slope factor and Dd were derived from the U.S. EPA Guidance document for dermal exposures to showering5 assuming a chloroform concentration of 5.9 × 10−6 mg·cm−3. Step 3: Estimated Total Annual DALY for Each System. The annual DALY for each exposure pathway was calculated as the product of the estimated annual probability of illness (or lifetime risk), the population exposed, and the DALY per case of illness. The population exposed to each exposure pathway was assumed to be 10 000 people except for the recreational water, cross-connection, and salad crop consumption pathways. On the basis of a national survey of 75 000 households, the participation rate of persons 16 years of age or older for swimming was 25% per year.50 The percent of the population affected by a cross-connection event is uncertain and was set at 10% as a conservative estimate. The percent of the population that grows and consumes salad crops was set at 9732



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system as a percentage of the total disease burden of BAU were 23% for CT-SS, 63% for UD-SS, 1% for BE-GR, and 15% for BE-GRR. The cumulative distribution function (CDF) of the total annual DALY per 10 000 people conveys information about the median total annual DALY as well as the range of likely total annual DALY from the inherent variation in the input parameters in the exposure assessment (Figure 1). The

Figure 2. Cumulative distribution function (CDF) of the health benefit of alternative water and wastewater systems’ relative to the BAU measured by total annual DALY per 10 000 people; CT-SS with greywater treatment via septic tank and composting toilet (dash typeface); UD-SS with fecal solids treatment via septic tank and urine diversion toilet (dot typeface); BE-GR with a low flush toilet and blackwater pressure transport system and on-site greywater reuse (solid typeface); and BE-GRR with a low flush toilet and blackwater pressure transport system and on-site greywater and rainwater treatment and reuse (dashed-dot typeface).

Figure 1. Cumulative distribution function (CDF) of alternative water and wastewater systems’ total annual DALY per 10 000 people including BAU (solid typeface); CT-SS with greywater treatment via septic tank and composting toilet (dash typeface); UD-SS with fecal solids treatment via septic tank and urine diversion toilet (dot typeface); BE-GRR with a low flush toilet and blackwater pressure transport system and on-site greywater and rainwater treatment and reuse (dashed-dot typeface). BE-GR not shown as negligible.

gastrointestinal health outcomes from microbial exposures. On the basis of the exposure pathways considered here, the microbial exposures present the larger human health burden. The hazards Norovirus and Cryptosporidium were associated with the exposure routes with the highest burden of disease (Table 1). However, additional routes of exposure or hazards are possible (but outside the scope of this comparison) and there remains outstanding uncertainty in the risk estimates. The exposure routes included in this comparative risk assessment accounted for variation in the conditions over the course of a year, such as typical storm events and treatment failures. However, misuse and mishandling of the on-site systems were not considered.52 Occupational exposures related to pumping and transport of septic tank and urine diversion or composting toilet products were excluded from the community assessment of health impact.53 Exposures to pathogens resulting from increased water age in the drinking water distribution network of low water use options was not examined. Consumption of shellfish contaminated from wastewaters were also outside of the scope of this assessment. The excluded exposure routes, as well as others, may be important for specific communities. Under BAU, the exposure pathway with the greatest human health impact was the ingestion of drinking water contaminated by a long-duration, high dilution cross-connection with sewage. The cross-connection exposure pathway had an uncertain (and variable) dilution of sewage in the distribution system and an uncertain scale of impact (i.e., the fraction of the population affected each year) as many go unreported. A parametric sensitivity analysis of the illness risk determined that the risk was most sensitive to changes in the dilution factor over the ranges proposed by Teunis et al.3 compared to changes in the volume of water ingested, inactivation constant, event duration, chlorine contact time, or chlorine concentration (results not shown). The median annual DALY was also sensitive to the fraction of the population exposed annually. If the best estimate of 0.1 is too high and the fraction is smaller, say 0.01, then the median annual DALY would decrease linearly to 5.7 × 10−2. Given the uncertainties and the conservative dilution assumption, it is still likely that there would be health benefits

BE-GR option is not depicted as the risks associated with the pathways considered were estimated to be near zero. To assess if these systems present a tolerable health burden, the widely accepted annual threshold for drinking water of 1 × 10−6 DALYs per person was used, which translates in to a threshold of 0.01 DALYs per 10 000 people.48,51 For the BE-GR system, 96% of the Monte Carlo samples of the total annual DALY per 10 000 were less than or equal to 0.01 DALYs. For the BAU, 0.01% of the Monte Carlo samples were less than or equal to 0.01 DALYs. The CT-SS and UD-SS systems, i.e., composting or urine-diverting toilets and on-site greywater treatment, have annual disease burdens less than or equal to 0.01 DALYs for 58% and 25% of the Monte Carlo samples. The annual disease burden of BE-GRR was less than or equal to 0.01 DALYs for 3% of the Monte Carlo samples. Relative DALY Difference for Each Alternative System. The health benefit of switching from BAU to an alternative water and wastewater system was calculated as the difference between the Monte Carlo samples of the total annual DALY for BAU and those of an alternative. The CDF of the health benefit for each alternative is depicted in Figure 2. Generally, the health benefit was positive for BE-GR and BEGRR, indicating that switching from BAU to one of these alternative systems is likely advantageous from a human health perspective. For CT-SS and UD-SS, the health benefit was negative (indicating a potential increase in health burden over BAU) for 19% and 36% of the Monte Carlo samples, respectively. However, Figure 2 does not consider the outstanding uncertainties in the input parameters, which may shift the relative difference once resolved.

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DISCUSSION The use of the DALY as the human health metric allowed the comparison of chronic health outcomes from DBP exposure, mainly male bladder cancer, with the more acute, largely 9733



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and a table of the median annual probability of illness or lifetime cancer risk for each exposure pathway and hazard. This material is available free of charge via the Internet at http:// pubs.acs.org/.

in switching to one of the alternative water and wastewater systems described. The UD-SS system, which had the second highest associated annual median DALY, was calculated assuming a large range of natural variation in key input parameters. Both the Norovirus removal through groundwater transport and dilution of seepage once entering recreational water were modeled as highly variable to cover the various possible conditions expected within the Cape Cod region. A parametric sensitivity analysis of the illness risk for the UD-SS system determined that the risk is most sensitive to changes in the removal of Norovirus through groundwater passage when compared to the septic failure rate, the number of septic tanks affecting the waterbody, the septic tank seepage dilution, and the daily probability of Norovirus occurrence in septic tank leakage. Although natural variability is likely large given the broad assessment definition of recreational waters, additional research may reduce uncertainty and decrease inherent variability in these parameters for specific waterbodies. The annual probability of illness from the ingestion of treated rainwater while showering was generally small (i.e., between 10−6 and 10−9) for most reference pathogens, including C. jejuni, S. enterica, Giardia spp., and L. pneumophila; even when C. jejuni density in rainwater was characterized by real-time quantitative polymerase chain reaction (qPCR) (i.e., dead and alive cells), the risk remained unchanged (results not shown). However, the predicted annual risks associated with two reference pathogens, Cryptosporidium spp. and E. coli 0157:H7, were much larger for rainwater ingestion. The pathogen density of these reference hazards in the rainwater was the most uncertain of any alternative. The Cryptosporidium spp. density in rainwater was based on estimates in “natural” surface waters due to a lack of sufficient data48 with the additional assumption that a low fraction of these oocysts maybe human infectious.54 The E. coli 0157:H7 incidence was based on an estimate of the fraction of virulence factor-containing cells using qPCR.45 Given the high rainwater incidence of E. coli, densities, and large DALY per case of E. coli O157:H7, any treatment failure may result in potentially high infection risk for shower exposures. In general, the possible risk from using treated rainwater remains highly uncertain and is certainly site-specific. From a human health perspective, the comparison of the annual DALYs for each system indicates that there may be a health benefit associated with adopting the low flush toilet and blackwater pressure transport system option with on-site greywater treatment and reuse, or possibly the option which includes rainwater treatment and reuse. In general, the options that avoided septic systems had greater health benefits. The urine-diversion toilet system appears to be similar in health burden to the BAU given the potentially high exposures of pathogens in natural waters contaminated with septic seepage. The composting-toilet option was preferable compared to the urine-diversion toilet. Ultimately, we intend that these human health metrics should be weighed with other decision factors, such as costs, environmental burdens, and resilience to fully understand the relative benefits and trade-offs associated with the selection of options.

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AUTHOR INFORMATION

Corresponding Author

*Address: 312 NE 82nd St, Seattle, WA 98115; Phone: 206523-3372; E-mail: [email protected]. Funding

This project was supported by the U.S. Environmental Protection Agency Office of Research and Development. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This project was supported by the U.S. Environmental Protection Agency Office of Research and Development. The views expressed in this article are those of the authors and do not necessarily reflect the views or policies of the U.S. Environmental Protection Agency. Any mention of specific products or processes does not represent endorsement by the U.S. EPA.

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REFERENCES

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ASSOCIATED CONTENT

S Supporting Information *

Schematic of all system options, a table that specifies the dose− response models and probability of illness for the microbial hazards, a table of model input parameter values and sources, 9734



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