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Drinking water microbiology in a water-efficient

Cite this: Environ. Sci.: Water Res. building: stagnation, seasonality, and Technol., 2020, 6,2902 physicochemical effects on opportunistic pathogen and total bacteria proliferation†

Christian J. Ley, a Caitlin R. Proctor,abcd Gulshan Singh,e Kyungyeon Ra,b Yoorae Noh,b Tolulope Odimayomi,a Maryam Salehi,f Ryan Julien,g Jade Mitchell,g A. Pouyan Nejadhashemi,g Andrew J. Whelton ab and Tiong Gim Aw *e

The rising trend in water conservation awareness has given rise to the use of water-efficient appliances and fixtures for residential potable water systems. This study characterized the microbial dynamics at a water-efficient residential building over the course of one year (58 sampling events) and examined the effects of water stagnation, season, and changes in physicochemical properties on the occurrence of opportunistic pathogen markers. Mean heterotrophic plate counts (HPC) were typically lowest upon entering the building at the service line, but increased by several orders of magnitude at the furthest location in the building plumbing. Legionella spp. and Mycobacterium spp. were detected in the plumbing, with the highest detection occurring in the summer months. Log-transformed HPC were significantly

correlated with total cell counts (TCC) (rs = 0.714, p < 0.01), Legionella spp. (rs =0.534,p < 0.01), and

Mycobacterium spp. occurrence (rs =0.458,p < 0.01). Reduced water usage induced longer stagnation

times and longer stagnation times were weakly correlated with an increase in Legionella spp. (rs =0.356,p

Received 9th April 2020, < 0.001), Mycobacterium spp. (rs =0.287,p < 0.001), TCC (rs = 0.216, p < 0.001) and HPC (rs = 0.395, p Accepted 31st July 2020 < 0.001). Interrelationships between seasonal shifts in water chemistry and genus-level genetic markers for opportunistic pathogens were revealed. This study highlights how drinking water microbiology varies DOI: 10.1039/d0ew00334d seasonally and spatially throughout a low-flow plumbing building and highlights the possible unintended rsc.li/es-water consequences associated with reduced water usage and increases in stagnation.

Published on 17 August 2020. Downloaded by US Environmental Protection Agency 3/18/2021 4:22:14 PM. Water impact As trends in water conservation increase, it will become especially important to understand the potential risks of increased microbial and pathogen growth within building plumbing. Insight gained from this study will help building operators to better understand how drinking water in the building can varyby season, fixture location, and sampling time of day.

a Environmental and Ecological Engineering, Purdue University, West Lafayette, IN 47907, USA 1. Introduction b Lyles School of Civil Engineering, Purdue University, West Lafayette, IN 47907, USA As public awareness of water conservation issues is rising, c Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN homeowners and consumers are increasingly using water- 47906, USA efficient appliances and fixtures to reduce municipal water d School of Materials Engineering, Purdue University, West Lafayette, IN 47907, usage. Water use in single-family three-person residences USA e declined from 708 L per day (LPD) in 1999 to 500 LPD in Department of Environmental Health Sciences, School of Public Health and 1 Tropical Medicine, Tulane University, 1440 Canal Street, Suite 2100, New Orleans, 2011. Recent studies have highlighted the economic and 2 LA 70112, USA. E-mail: [email protected]; Tel: +1 504 988 9926 environmental benefits of utilizing low-flow water fixtures. f Department of Civil Engineering, University of Memphis, Memphis, TN 38152, Utilization of new water-saving technologies will further USA catalyze the trend towards lower flows and reduced water g Department of Biosystems Engineering, Michigan State University, East Lansing, usage within buildings. Retrofitted three-person residential MI 48824, USA † Electronic supplementary information (ESI) available. See DOI: 10.1039/ buildings that have been designed to reduce water usage, on 1 d0ew00334d average, use 405–443 LPD of water.

2902 | Environ. Sci.: Water Res. Technol., 2020, 6,2902–2913 This journal is © The Royal Society of Chemistry 2020 View Article Online Environmental Science: Water Research & Technology Paper

Despite the benefits associated with reduced water usage, 2. Materials and methods there is a growing concern that the reduction in flow caused 2.1 Description of the testing site by low-flow plumbing fixtures increases the hydraulic retention time (HRT) of the plumbing, exacerbating concerns A highly water efficient single-family residential building was regarding water quality. Increases in HRT have previously chosen as the primary test site for this study. In the United been linked to water quality degradation, including potential States, average water usage in a single-family residential – 1,18 for increased microbial growth,3 loss of disinfectant,4 metal building is 344 500 L/person/day. After renovating the leaching,5 as well as taste and odor issues.6 Compared to 1920's building with water-saving fixtures, per capita water centralized distribution systems, building plumbing may face usage of the building in this study, was reduced to 79 L/ 18 more severe water quality degradation due to higher person/day. Water entered the three-year old building ″ temperatures, regular intermittent periods of non-use,7,8 and plumbing from a 3/4 (1.90 cm) copper utility line, which ″ higher surface area to volume ratios9 in building plumbing. feeds into a 3/4 (1.90 cm) PEX service line (4.30 m in length). Legionella pneumophila and Mycobacterium avium are two Building plumbing consists of trunk-and-branch PEX of the most common causative agents of drinking water- plumbing and brass valves and fittings. Fixture information † associated disease outbreaks.10,11 They commonly survive and their respective efficiencies are included in ESI (Fig. S1, and persist in drinking water due to shared properties of Table S1). The municipal water source is groundwater. The disinfectant resistance, biofilm growth, and ability to thrive groundwater is oxidized, aerated, filtered, chlorinated for in low-nutrient environments.3 While these opportunistic secondary disinfection with free chlorine, and a corrosion plumbing pathogens (OPPs) may originate from the drinking inhibitor is added before distribution. To monitor water water distribution system, they tend to grow more readily in usage, flow meters were installed on all in-building fixtures building plumbing due to a lack of disinfectant residual. It is and a data acquisition system recorded data at each flow expected that low-flow plumbing may pose a heightened risk meter every second, 24 h per day, 365 days per year. Water for opportunistic pathogen exposure compared to usage events consisted of periods of flow greater than 3 conventional plumbing due to lower flow rates and increased seconds. Additional information regarding the flow data 19 stagnation. While previous studies have evaluated the analysis was conducted as previously reported. The volume presence of OPPs in conventional building plumbing8,12,13 used per event and mean stagnation time, (mean defined as – and simulated plumbing systems,14 17 to the best of our the mean time elapsed between water use events) at the same knowledge no studies have holistically evaluated the roles of fixture, were determined to help uncover any relationships temporal and spatial physicochemical water quality variation between increased HRT and water quality. on the occurrence of OPPs in low-flow plumbing over a long period (an entire year). 2.2 Sampling regime and water chemistry analysis Since multiple physical, chemical, and microbial water Water sampling events were evenly distributed to examine quality parameters change concurrently in building plumbing spatial and temporal variations of water quality throughout and during stagnation, it is difficult to determine cause and the building. Beginning in October 2017 and ending in effect relationships between physicochemical and microbial October 2018, a minimum of 12 sampling events occurred parameters. By analyzing multiple parameters, one can better per season. These sampling events were conducted at three Published on 17 August 2020. Downloaded by US Environmental Protection Agency 3/18/2021 4:22:14 PM. determine methods to control these water quality changes time points during the day (7:30 a.m., 12:00 p.m., and 3:00 p. that occur as a result of increased stagnation. m.) with three to four sampling events for each time point in In this study, a municipal water supplied a retrofitted each season 58 total sampling dates in fall (n = 13), winter (n water and energy-efficient building which was used to = 17), spring (n = 12), summer (n = 16). Potable cold water examine drinking water quality changes associated with fixtures were sampled sequentially at three locations, starting increased water efficiency. A total of 58 sampling events were with the service line, kitchen sink cold water line, and the completed throughout the 12-month study. The objectives of distal-end bathroom sink cold water line. Hot water lines this study were to (i) determine the impact of stagnation on were then sampled at four locations: water heater tank, microbial water quality in a water-efficient building; (ii) kitchen sink hot water line, bathroom sink hot water line examine the seasonality of water physicochemical parameters (distal-end), and the shower (distal-end). At each fixture, and its effect on water microbiology over a one year sampling approximately one-liter first-flush samples were collected for period; (iii) assess long-term spatial microbiological physicochemical analysis. Water samples for heterotrophic variations at proximal and distal fixtures in the building; and plate counts (HPC) and molecular microbial analysis were (iv) to examine the relationship between culturable and total collected in two autoclaved 1 L HDPE bottles with sodium microbial counts with the occurrence of OPPs (Legionella and thiosulfate added to inactivate any chlorine in the water. Mycobacterium spp.) within a water-efficient building. If Temperature, pH, and total chlorine were measured onsite increased stagnation in plumbing systems is associated with immediately after sample collection. The pH was analyzed increased microbial and potential OPPs growth, then control with an Oakton 450™ pH probe. Total chlorine was strategies could be needed to prevent waterborne infectious quantified using N,N-diethyl-phenylenediamine (DPD) disease. reagent and Hach Pocket Colorimeter™ chlorine test kits.

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The limit of detection for the Hach Pocket Colorimeter™ is Legionella spp. (targeting 23S rRNA), Legionella −1 0.02 mg L as Cl2. However, the minimum state-suggested pneumophila (mip gene), Mycobacterium spp. (the internal −1 level of total chlorine is set at 0.20 mg L as Cl2 and chlorine transcribed spacer sequence) and Mycobacterium avium (16S levels should not be below this limit for more than 5% of rRNA) were enumerated by qPCR using previously published – samples per month. Metal concentrations (Al, As, Be, Cd, Co, methods.23 25 All qPCR reactions were performed using a Cr, Mn, Ni, Se, Pb, Zn, Fe, Cu) were quantified by inductively StepOne Plus™ real-time PCR sequence detector (Applied coupled plasma-optical emission spectrometry (iCAP 7400 Biosystems, Foster City, CA). For each assay, a 10-fold diluted Duo ICP-OES, Thermo Scientific) and an autosampler (ASX- standard curve of at least six points, a non-template control, 280, CETAC Teledyne). Ion concentrations were quantified by and samples were tested in triplicate. Genomic DNA of ion chromatography (Metrohm 940 Professional IC Vario) Legionella pneumophila strain Philadelphia-1 (ATCC 33152D- immediately after sample collection, as previously 5) and Mycobacterium avium (ATCC 25291), respectively, was described.19 Total organic carbon (TOC) was measured using used to generate standard curves. For Mycobacterium, a Shimadzu TOC-L CPH/CPN in accordance with USEPA amplification reaction mixtures (final total volume of 25 μl) method 415.1.20 contained five μl template DNA, 12.5 μlof2× Perfecta qPCR ToughMix (QuantaBio), 400 nM of each primer and 200 nM of probe. The thermal cycling protocol was as follows: 15 min 2.3 Microbiological analysis at 95 °C for initial denaturation, followed by 45 cycles of HPC and flow cytometry (FCM) methods were used to analyze three steps consisting of 30 s at 95 °C, 40 s at 55 °C, and 30 s the culturable cell population and the total cell count (TCC), at 72 °C. A duplex qPCR assay was used for Legionella respectively. Depending on the concentration of colony detection. Amplification reaction mixtures (final total volume forming units (CFU) in each HPC sample, dilutions were of 25 μl) contained five μl template DNA, five μlof5× prepared such that each plate yielded 20–200 colonies. Perfecta Multiplex qPCR ToughMix (QuantaBio), 500 nM of Dilutions were filtered through a sterile 0.45 μm membrane each primer and 200 nM of probe. The thermal cycling filter (Millipore), and the membrane filter was plated and protocol was as follows: 15 min at 95 °C for initial incubated on m-HPC agar (Difco™)at35°C for 48 hours. denaturation, followed by 45 cycles of two steps consisting of Following the 48-hour incubation period, CFU were counted. 15 s at 95 °C and 60 s at 60 °C. qPCR amplification FCM analysis was conducted to quantify the total efficiencies for the quantification of the Legionella 23S rRNA, number of microbial cells in each water sample using SYBR Legionella pneumophila mip gene, Mycobacterium spp. and Green I dye, which binds specifically to nucleic acids (Swiss Mycobacterium avium 16S rRNA assays were 98.6 ± 1.7%, Research method 366.1).21 Each water sample was stained 100.9 ± 3.2%, 97.5 ± 2.5% and 86.5 ± 5.3%, respectively, and 1 : 100 with SYBR-Green I nucleic acid gel stain diluted in the correlation coefficients of the standard curves were 0.998 filtered dimethylsulfoxide (DMSO). The samples were ± 0.003, 0.996 ± 0.003, 0.999 ± 0.002 and 0.993 ± 0.003, incubated in a 96-well plate in the dark at 37 °C for 13 respectively. Standard precautions were applied when minutes. Triplicate samples from each fixture were analyzed conducting the qPCR, such as UV sterilization of PCR using FCM (CytoFLEX, Beckman-Coulter Inc., Brea, CA, equipment and the working environment, using aerosol- USA). A constant and uniform gating strategy was applied resistant tips, separate locations for sample preparation and Published on 17 August 2020. Downloaded by US Environmental Protection Agency 3/18/2021 4:22:14 PM. to all samples. amplification. Negative controls using PCR-grade water were included in each reaction set.

2.4 Quantitative PCR (qPCR) OPPs analysis 2.5 Statistical analysis For molecular detection, approximately one liter of water sample was filtered through 47 mm diameter, 0.4 μm pore Ranges and mean values for physicochemical and microbial size polycarbonate filters (Millipore #HTTP04700). DNA data were determined. The data were tested for normality extractions were performed as described in EPA Methods using the Kolmogorov–Smirnov test.26,27 Nonparametric 1611.22 Briefly, the filter was transferred to a two mL semi- Spearman rank correlation analysis was used to determine conical screw cap microcentrifuge tube containing 0.3 g of correlations between non-normal distributed chemical acid-washed, 212–300 mm glass beads (Sigma-Aldrich, #G- properties and microbial metrics (TCC, HPC, Legionella spp., 1277) and 600 mL AE buffer (Qiagen, Valencia, CA, USA) and Mycobacterium spp.). Correlation analysis was applied added. The tubes were sealed, bead milled at 5000 using IBM® SPSS® version 26 statistical software to explore reciprocations per min for 60 s and centrifuged at 12 000 × g the relationship between stagnation, physicochemical factors for one min to pellet silica beads and debris. The (pH, temperature, total chlorine), and log-transformed supernatants were transferred to clean, low retention micro- microbial metrics (HPC and FCM), where the type I error at a centrifuge tubes and centrifuged for an additional five min. significance level of 0.05 was considered significant. Holm's The resulting clarified supernatants were transferred to correction method was tried to check for error rates for another clean, low retention micro-centrifuge tubes and multiple hypothesis tests. This method reduces type I errors stored at −80 °C until qPCR analysis. when multiple tests are performed.

2904 | Environ. Sci.: Water Res. Technol., 2020, 6,2902–2913 This journal is © The Royal Society of Chemistry 2020 View Article Online Environmental Science: Water Research & Technology Paper

3. Results & discussion than in stagnant conventionally plumbed buildings (0.71 mg −1 4 3.1 Physicochemical water quality variation by season L ), and chlorine was not detected in the green building until after thirty minutes of flushing. Without flushing, low- While seasonal variations in pH, temperature, and total flow buildings are likely to have lower chlorine chlorine concentration were observed at the service line, concentrations than conventionally plumbed buildings.4 much greater variations were found inside the building Seasonal temperature shifts were significantly correlated with − < (Table 1). The service line water pH was similar across changes in total chlorine concentrations (rs = 0.41, p seasons, with the mean pH of 7.74 and 7.51 in the winter 0.001). Overall, water temperature and total chlorine varied and summer months, respectively. However, the pH at other seasonally and spatially, even after entering the building fixtures often increased throughout the building (range: 7.2– plumbing. This phenomenon of lower chlorine residual 9.4). The pH levels were likely higher in the building detection in warmer months has been previously reported compared to the service line, due to increased stagnation and and is due to the relationship between total chlorine contact with calcium deposits in the pipe scale. Increased concentration and temperature.29 stagnation time and temperature were correlated with Copper, lead, and zinc levels were higher in the building

increased pH (rs = 0.229–0.303, p < 0.001). It is plumbing than at the entry point of the building (Table S2†). recommended to keep water pH between 6.5–8.5 in Metal and ion concentrations for each fixture are provided in accordance with the EPA secondary maximum contaminant Tables S2 and S3.† Mean copper concentrations at the − level (SMCL) to avoid pipe corrosion, deposit release, and building entry were lowest in the summer (mean: 32.2 μgL1) drinking water taste issues.28 and increased substantially after exiting the water heater − Water temperature at the service line varied from 21.6– (mean: 92.5 μgL1). The mean copper concentrations were 23.6 °C in the summer months and ranged from 11.5–19.0 °C well below the acceptable EPA lead and copper rule copper − in the winter months. The total chlorine in the service line limit of 1300 μgL1.30 Our concurrent study indicated that − varied by season (spring mean: 0.6 mg L 1; range: non- copper and zinc concentrations were higher in the morning −1 detectable (ND) to 2.1 mg L as Cl2). Service line mean total sampling events compared to the afternoon sampling chlorine levels were the greatest in the winter (mean: 0.9 mg events.27 Magnesium and calcium concentrations decreased −1 −1 L , range: ND-1.6 mg L as Cl2) and lowest in the summer significantly after treatment through the water softener, while −1 −1 (mean: 0.4 mg L , range: ND-0.8 mg L as Cl2) and fall sodium concentrations increased after water softening (Table −1 – −1 † (mean: 0.4 mg L , range: 0.2 0.8 mg L as Cl2). At the S3 ). Increases in copper and zinc concentrations are likely service line in the summer months, chlorine was only due to contact with brass valves and fittings. detected for 75% of the samples (n = 12 of 16), whereas in the winter, chlorine was detected at the building entry for 94% of the samples (n = 16 of 17). After entering the 3.2 Microbial metrics varied by fixture: HPC and TCC plumbing system in the summer months, chlorine was only Microbial growth increased in the distal fixtures in relation − detectable (state law ND is <0.2 mg L 1) at 3% of fixture to the entry point of the building, underscoring that the samples (n = 3 of 96) during the summer (June–September) indoor building environment is more favorable for microbial months. Whereas, in the winter months, chlorine was growth than the service line. Significant differences in HPC Published on 17 August 2020. Downloaded by US Environmental Protection Agency 3/18/2021 4:22:14 PM. − present at detectable levels (>0.2 mg L 1) for 32.4% of and TCC levels were observed across fixtures (Tables S5 and building fixture samples collected in winter (n = 33 of 102). S6†), but service line water consistently had lower mean Chlorine concentrations in drinking water of conventional values of HPC compared to the other fixtures in the building plumbing systems and green buildings have been compared for the spring (mean: 2.74 log CFU/100 mL), summer (mean: previously for one to two discrete sampling events.4 In a 2.88 log CFU/100 mL) and fall months (mean: 3.16 log CFU/ − previous study, lower chlorine concentrations (0.04 mg L 1) 100 mL), but not winter. Surprisingly, mean winter HPC were consistently detected in stagnant green building fixtures levels at the service line (mean: 2.08 log CFU/100 mL) were

Table 1 Service line water temperature, pH, and total chlorine concentration by season

Season (number of sampling events) Parameter Fall (n = 13) Winter (n = 17) Spring (n = 12) Summer (n = 16) Water volume (m3) 25.5 23.6 19.7 23.8 Water pH 7.66–7.72 7.65–7.81 7.66–7.78 7.24–7.67 Mean: 7.76 Mean: 7.74 Mean: 7.72 Mean: 7.51 Temperature (°C) 20.0–22.6 11.5–19.0 19.5–22.5 21.6–23.6 Mean: 21.6 Mean: 14.6 Mean: 21.1 Mean: 22.9 −1 Total chlorine (mg L as Cl2) 0.2–0.8 ND – 1.6 ND – 2.1 ND – 0.8 Mean: 0.40 Mean: 0.88 Mean: 0.58 Mean: 0.41

− nd = level was not found above 0.1 mg L 1 concentrations.

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higher than the HPC levels at the kitchen sink cold water line in the building, including low chlorine concentrations and (mean: 1.89 log CFU/100 mL) and the 2nd floor bathroom longer stagnation times. sink cold water line (mean: 1.74 log CFU/100 mL) in the In this study, HPC and TCC also varied by season due to winter (Fig. 1). The higher HPC levels detected at the service shifting water temperatures and total chlorine line compared to the kitchen sink cold water line may be due concentrations. Both the HPC and TCC were lower in the to the low level of use for the service line sampling tap. winter and higher in the summer. Thus, this seasonal trend The highest mean HPC levels were found in water samples in microbial growth may, in part, be due to variation in collected from the water exiting the water heater during the outdoor temperatures, which vary considerably by season. fall, spring, and summer months (range: 6.37–7.37 log CFU/ Log-transformed HPC concentrations were significantly < 100 mL). Fixture HPC levels exceeded a recommended correlated with temperature of water samples (rs = 0.460, p maximum level of 4.69 log CFU/100 mL (5.0 × 104 CFU/100 0.01) (Table 2). Given the significant negative correlation 31 mL). In this study, HPC and TCC were significantly between HPC and total chlorine (rs = −0.294**, p < 0.01) < correlated (rs = 0.714, p 0.01), in other studies the (Table 2), it is likely that the lower disinfectant correlation between HPC and TCC was strong (Pearson ρ = concentrations in water exiting the water heater contributed 0.57).32 A strong correlation between HPC and TCC may have to the higher degree of microbial growth in the hot water been observed due to generally favorable growing conditions fixtures. Indoor air temperature is also a driving factor for Published on 17 August 2020. Downloaded by US Environmental Protection Agency 3/18/2021 4:22:14 PM.

Fig. 1 (a) Heterotrophic plate counts (HPC) (CFU/100 mL) and (b) total cell counts (TCC) (log cells/mL) vary by water fixture and season. Fixture abbreviations: service line (SL), water heater (WH), kitchen sink cold (KC), kitchen sink hot (KH), bathroom sink cold (BC), bathroom sink hot (BH), and shower (SH).

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Table 2 Spearman correlation analysis for physicochemical and microbial properties

Temp: temperature, Chlorine: total chlorine, TOC: total organic carbon, DO: dissolved oxygen. TCC: total cell counts, and HPC: heterotrophic plate counts. a Correlation is significant at the 0.01 level. NS means not significant. Published on 17 August 2020. Downloaded by US Environmental Protection Agency 3/18/2021 4:22:14 PM. increased microbial growth in building plumbing.33 All of relatively large volume of in-building water storage is the samples collected from the water heater during the required to support the solar thermal–photovoltaic spring, summer, and fall exceeded the suggested HPC system.19 Due to the energy-efficient design of the building, guideline, and many of the other hot water fixtures the water heating storage volume (1360 L) is not typical for exceeded the guideline in the spring and summer months. a single-family home (typically 150–420 L per home). The seasonality of HPC growth is consistent with findings Conventional residential water heaters have a hydraulic of other studies evaluating seasonal water quality variation retention time (HRT) of 1 day.4 In this study, HRT in the in premise plumbing.15,34 Although the HPC growth in water heating system (Table S7-b†) varied by season as drinking water often exceeds the recommended maximum determined by dividing the volume of the water heating level of 4.69 log CFU/100 mL (5.0 × 104 CFU/100 mL), HPC system (1378 L) by the mean total volumetric flow rate for bacteria do not explicitly impose a health threat. This each season (Table S7-b†). The lowest mean HRT in the suggests that the HPC guideline may not be a suitable or water heater occurred in the fall (14.4 days) and the informative metric of the water quality. highest HRT occurred in the summer (29.2 days). These The maximum first-flush temperature observed at the high HRT values indicate that it took two to four weeks for sampling outlet of the energy-efficient water heating system a complete water turnover to occur in the water heater, as was 26 °C. Thus the water heater may have acted as an compared to conventional water heaters that have an incubator facilitating microbial growth in the warm water average HRT of one day. To counteract these long hydraulic fixtures throughout the building, as the HPC concentrations residence times, the importance of properly controlling the were always greater after exiting the water heater. A temperature in water heaters should be considered,35 so as

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to prevent the growth of OPPs. More specifically, a were not measured in the spring). Interestingly, mean temperature-based risk assessment tool indicates that Legionella concentrations in the shower were the highest in temperatures exiting water heaters should be maintained the winter months (mean: 4.71 log gene copy/100 mL), above 55–60 °C to prevent the growth of OPPs such as followed by summer (mean: 3.81 log gene copy/100 mL) and Legionella pneumophila.36 fall (2.78 log gene copy/100 mL). These levels are low compared to a previous study of Legionella spp. growth in green buildings, where mean Legionella spp. concentrations 3.3 Occurrence of potential OPPs were reported as 6.949 log gene copy/100 mL.4 Legionella Mycobacterium spp. and Legionella spp. gene copy numbers spp. concentrations may have been higher in the shower were lowest at the building entry and increased in water during the winter months due to higher ambient after entering building plumbing (Tables 3 and S5†). temperatures in the building and higher water use in the Legionella pneumophila was not detected in any samples, but shower (Table S6-a†). Alternatively, the higher water use in Mycobacterium avium was detected in two fall samples out the shower in the winter months may have allowed for a of 259 total water samples measured throughout the study. more continuous supply of nutrients, which may have led Both Mycobacterium spp. and Legionella spp. concentrations to an increase in Legionella spp. concentrations during were low at the service line, but increased substantially in winter. building plumbing. Mycobacterium spp. concentrations were In the winter, 37.5% (n = 8) of the samples collected from also lowest at the service line, but the concentrations the service line tested positive for Mycobacterium spp.,whereas increased by 1–3 logs in the building plumbing. This in the summer, 87.5% (n = 16) of the samples collected from indicates that the building plumbing was more favorable for the service line tested positive for Mycobacterium spp. On OPP growth as compared to the centralized distribution average, Mycobacterium spp. at the service line were detected at system. similar concentrations each season ranging from 3.9–4.13 log Seasonal variation in Legionella and Mycobacterium spp. gene copy/100 mL, these numbers are somewhat lower than the detection. In the summer, all water samples collected from Mycobacterium spp. levels that have been detected in water the building's water fixtures tested positive for both systems from a similar climate (6.15 log gene copy/100 mL).37 Legionella spp. and Mycobacterium spp. (Table 3), except the Mycobacterium gene copy numbers increased throughout the service line where municipal water entered the building. building and fixture levels were higher in the summer and fall, Across the seasons, Legionella spp. concentrations at the as compared to the winter. Similar seasonal trends in Legionella building entry were similar (range: 1.43–1.77 log gene copy/ spp. detection have been observed at the centralized 100 mL). However, the seasonal trends in Legionella spp. distribution system level, where L. pneumophila is more likely to concentrations were more evident at all fixture locations, be detected in summer months and when temperatures are − where Legionella levels followed the trend: summer > fall > >18 °C and chlorine residuals are <0.1 mg L 1.38 However, in winter, except at the shower (Legionella spp. concentrations this study, Legionella spp. concentrations were similar across

Table 3 Occurrence of Legionella spp. and Mycobacterium spp. in different water fixtures in a water-efficient building as determined by qPCR Published on 17 August 2020. Downloaded by US Environmental Protection Agency 3/18/2021 4:22:14 PM. Legionella spp.a (log gene copy/100 mL) Mycobacterium spp.a (log gene copy/100 mL) Summer Fall Winter Summer Fall Winter % Positive % Positive % Positive % Positive % Positive % Positive Min (x¯) max Min (x¯) max Min (x¯) max Min (x¯) max Min (x¯) max Min (x¯) max Service line 12.5% 30.8% 14.3% 87.5% 38.5% 37.5% 1.39 (1.65) 2.9 1.12 (1.77) 3.6 1.37 (1.43) 1.81 1.87 (4.13) 5.00 1.60 (3.9) 4.96 1.85 (3.97) 4.87 Water heater 100.0% 100.0% 50.0% 100.0% 92.3% 87.5% 4.16 (4.63) 4.86 1.36 (3.56) 4.6 1.29 (1.67) 2.85 6.54 (7.14) 7.61 1.57 (7.1) 7.94 1.85 (5.5) 6.19 Kitchen cold 100.0% 61.5% 62.5% 100.0% 69.2% 87.5% 1.69 (3.06) 4.19 1.03 (1.89) 3.4 1.37 (1.49) 1.64 4.14 (5.78) 6.21 1.48 (5.36) 6.41 1.85 (3.66) 4.05 Kitchen hot 100.0% 84.6% 75.0% 85.7% 76.9% 75.0% 4.29 (4.57) 5.08 1.12 (3.19) 4.2 1.29 (1.62) 2.10 1.85 (6.71) 7.20 1.60 (6.87) 7.37 1.85 (4.75) 5.58 Bathroom cold 100.0% 69.2% 50.0% 100.0% 69.2% 75.0% 2.51 (3.19) 4.29 1.12 (2.14) 2.9 1.37 (1.63) 2.11 4.96 (6.48) 7.35 1.60 (5.78) 6.52 1.85 (3.54) 4.28 Bathroom hot 100.0% 92.3% 87.5% 100.0% 69.2% 87.5% 3.15 (4.78) 5.26 1.12 (3.38) 4.6 1.37 (2.12) 2.62 1.60 (6.71) 8.43 1.60 (6.87) 7.90 1.60 (4.81) 5.29 Shower 100.0% 92.3% 100.0% 100.0% 76.9% 100.0% 2.33 (3.81) 5.3 1.12 (2.78) 4.8 2.52 (4.71) 5.72 5.29 (6.77) 7.42 1.60 (6.86) 7.62 4.79 (5.91) 6.38

a Legionella and Mycobacterium spp. detection limits are 13 and 70 gene copies/100 mL, respectively. Number of samples collected by season varied (winter: n = 8; summer: n = 16; fall, n = 13). % positive is the number of positive detection events divided by total sampling events per season at each fixture.

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seasons at the building entry but varied seasonally at the growth in domestic drinking water systems fluctuates building taps. seasonally15 with higher HPC concentrations in the summer In this study, Legionella spp. and Mycobacterium spp. were compared to the winter. Factors that contribute to higher also found with high frequency in warm water fixtures and distal microbial growth in the summer may be lower chlorine ends. Legionella spp. gene copy numbers increased with water concentrations, seasonal source water variations in total temperature, where all of the hot water fixtures had a higher organic carbon (TOC),41 and variations in temperature.42 Legionella spp. detection rate (Table 3). Of all the fixtures, the Impacts of water chemistry on total cell counts as shower and the distal end bathroom hot water line typically had determined by FCM. When comparing the physicochemical the highest frequency of Legionella spp. detection with mean parameter correlations with TCC data, the log-transformed detection frequencies ranging from 87.5–100%. A previous study TCC concentrations were significantly correlated with < < by Ling et al. (2018) indicated that Legionella spp. may proliferate temperature (rs = 0.463, p 0.01) and TOC (rs = 0.512, p in the distal ends in plumbing that experiences long stagnation 0.01), while TCC were negatively and weakly correlated with 12 − < times. A similar spatial trend occurred in this study, as a total chlorine (rs = 0.225, p 0.01) (Table 2). The correlation higher frequency of detection of Legionella spp. occurred in both between TCC and ion concentrations were determined (Table the 2nd floor bathroom shower and 2nd floor bathroom sink S8†). Significant correlations were found between log- hot water line, due to their similar distal locations in the transformed TCC and several aqueous ions (Br, Cl, Cl, Na, plumbing and long stagnation times. This finding highlights Mg, and Zn) (p < 0.01). Significant negative correlations were

that building water sampling and testing for potential shown between log-transformed TCC and Fe, K, and NO3 (p opportunistic pathogens should not occur only at the building < 0.01). Since HPC and TCC were significantly correlated, entry where water quality is highest. Instead, water samples many of these metal and nutrient relationships that occurred should be collected at hot and cold water taps throughout the with TCC are also likely to occur with HPC. building to gain an accurate assessment of the microbial Relationships between physicochemical water quality and populations throughout the building. OPPs. Legionella spp. log-transformed gene copy numbers

were significantly correlated with temperature (rs = 0.344, p < − < 0.01), and chlorine (rs = 0.417, p 0.01) (Table 4). Similar 3.4 Role of water chemistry changes in microbial growth and physicochemical relationships were observed for the detection potential OPPs of Mycobacterium spp. with temperature (rs = 0.380, p < 0.01) − < Seasonal water chemistry variation affected HPC and total chlorine (rs = 0.369, p 0.01), but not with pH. The concentrations. Seasonal variations in water chemistry may lack of correlation between Mycobacterium abundance and pH help explain variation in microbial growth throughout the could be due to the fact that Mycobacteria species can grow at domestic drinking water system. Log-transformed HPC a wider pH range43 (5.4–7.4) as compared to Legionella, which – 44 concentrations were negatively correlated with chlorine (rs = grows best at a pH range of 6.5 7.5. Also, pH affects the −0.294, p < 0.01). As expected, total chlorine and temperature speciation of copper, which Legionella spp. is highly sensitive − < are negatively correlated (rs = 0.413, p 0.01) with each to, thus secondary effects of copper exposure could also other (Table 2). In addition, HPC concentrations were account for Legionella's sensitivity to pH.45 positively and significantly correlated (p < 0.01) with many Aqueous ion concentrations were significantly correlated Published on 17 August 2020. Downloaded by US Environmental Protection Agency 3/18/2021 4:22:14 PM. metals and nutrients quantified in this study, including Cu, with log-transformed concentrations of Legionella spp. and Zn, Br, Cl, Na and Mg (Tables S8 and S9†). Copper and Mycobacterium spp. (p < 0.01). Ion concentrations of Br, Cl, transition metals play important biological roles as redox Na and Pb were positively significantly correlated with the cofactors.39 Iron and potassium were negatively correlated occurrence of both Legionella and Mycobacterium spp. (Tables with HPC concentrations (Tables S8 and S9†). Complete S8 and S9†). Negative correlations (p < 0.01) were observed tables for metals and ion concentrations measured in this for both bacterial species and the ion concentrations of K, † study can be found in ESI (Tables S2 and S3). Changes in Mn, NO3, and Fe. The inverse correlation between nitrite, influent water chemistry can affect biofilm stability.40 Biofilm nitrate, and the detection of Mycobacterium spp. are likely detachment during stagnation cannot be completely due to the role that Mycobacterium plays in nitrate and nitrite discounted,12 as detachment was not distinguished from reduction.46 The ability of Mycobacteria to reduce nitrate may planktonic growth in this study. enable the species to rapidly assimilate to oxygen and HPC concentrations were significantly correlated with nitrogen changes, allowing for better survival in the low- shifts in water physicochemical properties (temperature, DO, nutrient water, such as drinking water.47 and pH) (p < 0.01), indicating that seasonality in water Microbial interrelationships. Legionella spp. and HPC

chemistry may contribute to seasonal shifts in microbial concentrations were significantly correlated (rs = 0.600, p < concentrations (Table 2). Mean total chlorine concentrations 0.01). Mycobacterium spp. and HPC concentrations were also

were significantly and negatively correlated (p < 0.01) with significantly correlated, but to a lesser extent (rs = 0.458, p < HPC during both fall and summer sampling periods. This 0.01) (Table 4). Interestingly, the correlation of Mycobacterium indicates that the lack of chlorine was an important spp. and Legionella spp. concentrations as determined by

contributing factor to increased microbial growth. Microbial qPCR was strong (rs = 0.758, p < 0.01). The correlation

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Table 4 Spearman correlation between Legionella and Mycobacterium spp. occurrence with microbial and physicochemical metrics

TCC: total cell counts, HPC: heterotrophic plate counts.

between the two genera may indicate that the presence of either To determine the relationship between stagnation and species may serve as a better predictor of potential OPPs increased microbial growth for each sample tap, the occurrence as compared to HPC or TCC. Several drinking water correlations between mean stagnation time and the microbial microbial ecology studies have found significant relationships metrics were determined (Tables 4 and S4-a and S4-e†). between the qPCR signals of Legionella and Mycobacterium.48,49 At the service line building entry point, stagnation time was Published on 17 August 2020. Downloaded by US Environmental Protection Agency 3/18/2021 4:22:14 PM. This may be due to an overlap in niches for the two genera.49 not significantly correlated with any of the microbial metrics Neither HPC or TCC metrics constitute a strong predictor of (HPC, TCC, Legionella spp., Mycobacterium spp.). However, OPPs growth, but a variety of microbial metrics may be mean stagnation times were positively and significantly < required to accurately portray the microbial community within correlated with TCC (rs = 0.601, p 0.001), HPC (rs = 0.564, p a drinking water system. < 0.01), and Legionella spp. gene copy numbers (rs = 0.545, p < 0.01) at the distal end bathroom sink (Table S4-d†), indicating that microbial growth increased with longer 3.5 Stagnation and water usage patterns influenced microbial stagnation times. Water stagnation played an elevated role in growth microbial proliferation within this water-efficient building, Total volume and mean stagnation times were determined especially due to the variation in water age throughout the using hydraulic data captured from the flow meters (Table building. S7-a†). Total water usage varied slightly by season (range: A previous study demonstrated that water-efficient 19.7–25.5 m3), with the highest water usage occurring during buildings with elevated water age might exhibit higher levels the fall. More specifically, the stagnation times at the of microbial and OPPs growth in premise plumbing.4 building entry point were very low (90th percentile: 0–1 Molecular estimation methods such as qPCR may hours) based on the season. However, stagnation times were overestimate the actual OPPs risk, as the method does not often the highest at the distal ends in the plumbing for the differentiate between live and dead cells.50 Most molecular bathroom sink cold water line (90th percentile range: 7.3– microbial results presented in this study are for the genus 11.6 hours) and the shower (90th percentile range: 3.6–15.6 level (not species level), but it is possible that Legionella spp. hours). and Mycobacterium spp. exhibit similar growth characteristics

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to the opportunistic pathogens as these genera contain, Lower flows and reduced water usage led to increased Legionella pneumophila and Mycobacterium avium. stagnation, which was correlated with elevated Legionella and Mycobacterium spp. concentrations, microbial growth, and 3.6 Implications and moving forward in green building lower chlorine concentrations. While the use of water- design to protect water quality efficient fixtures is expanding, the unintended consequences of reduced water usage need to be better evaluated to control Although previous studies have compared water quality of and prevent OPP proliferation in green buildings. low-flow plumbing for a few sampling events,4,16 this study Additionally, flushing of taps or onsite disinfection may be consisted of 58 sampling events over a one year period, which useful to reduce the risk of waterborne OPPs disease in green included over 2.4 billion online monitoring data points buildings with low-flow plumbing. (fixture flow and temperature) to further evaluate the (i) seasonality of water physicochemical parameters and its Conflicts of interest effect on drinking water microbiology; (ii) spatial stagnation and microbiological variation at low-flow fixtures in the There are no conflicts to declare. building; and (iii) relationship between low-flow water use hydraulics with water microbiology and chemistry. Acknowledgements Elevated microbial activity, as indicated by HPC, TCC, and This research was funded primarily under the Environmental increased levels of potential OPPs genus-level genetic Protection Agency grant R836890. Funding was also provided markers were significantly correlated with seasonal from the National Science Foundation Graduate Research fluctuations in water pH, chlorine, and temperature. Levels Fellowship (NSF GRFP) Grant under Grant No. DGE-1333468. of disinfectant concentrations were generally low in all Lab assistance was provided by Purdue affiliates: Kathy samples in this study, which may account for a consistent Ragheb, Jennifer Sturgis, Selina Boer, Stephen Caskey, Sruthi proportion of cultivable cells relative to total cells. A Dasika, Kun Huang, Xiangning Huang, Xianzhen Li, John detachment of viable bacteria from biofilm may have also Maiyo, Chloe De Perre, Miriam Tariq, and Erica Wang. We contributed to this trend. Thus, if preventative measures (i.e., also thank Rebecca Ives at Michigan State University and flushing) are taken to avoid OPP proliferation in building Kathryn Jordan and Nicholas Lee at Tulane University for plumbing, the effects of seasonal changes in water chemistry laboratory assistance. on microbial growth may need to be considered. 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