Probabilistic assessment of environmental exposure ...

Science of the Total Environment 493 (2014) 1079–1087

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Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv

Probabilistic assessment of environmental exposure to the polycyclic musk, HHCB and associated risks in wastewater treatment plant mixing zones and sludge amended soils in the United States Thomas Federle a, Ping Sun a,⁎, Scott Dyer a, Brian Kiel b a b

Global Product Stewardship, The Procter & Gamble Company, Cincinnati, OH, USA International Flavors & Fragrances Inc., Union Beach, NJ, USA

H I G H L I G H T S • Probabilistic exposure analyses were performed for the polycyclic musk, HHCB, in aquatic mixing zones downstream from wastewater treatment plants (WWTPs) and in sludge amended soils across the United States. • Distributions of measured concentrations of HHCB in effluent and sludge from 40 WWTPs, reported in a companion paper (Sun et al.) were combined with distributions of surface water dilution factors at low and mean flow, sludge application rates to soil, sludge application practices, and soil degradation rates using Monte Carlo analyses. • Comparison of pelagic, sediment and terrestrial PNECs (Predicted No Effect Concentrations) with modeled concentrations in WWTP mixing zones and soils amended with sludge for 10 years revealed that the probability of exposure exceeding effect levels are very low.

a r t i c l e

i n f o

Article history: Received 7 January 2014 Received in revised form 11 March 2014 Accepted 14 March 2014 Available online 5 May 2014 Editor: Kevin V. Thomas Keywords: Musk fragrance HHCB Probabilistic environmental risk assessment

a b s t r a c t The objective of this work was to conduct an environmental risk assessment for the consumer use of the polycyclic musk, HHCB (CAS No. 1222-05-5) in the U.S. focusing on mixing zones downstream from municipal wastewater treatment plants (WWTPs) and sludge amended soils. A probabilistic exposure approach was utilized combining statistical distributions of effluent and sludge concentrations for the U.S. WWTPs with distributions of mixing zone dilution factors and sludge loading rates to soil to estimate HHCB concentrations in surface waters and sediments below WWTPs and sludge amended soils. These concentrations were then compared to various toxicity values. Measured concentrations of HHCB in effluent and sludge from a monitoring program of 40 WWTPs across the U.S. formed the basis for estimating environmental loadings. Based upon a Monte Carlo analysis, the probability of HHCB concentrations being below the PNEC (predicted no effect concentration) for pelagic freshwater organisms was greater than or equal to 99.87% under both mean and low flow regimes. Similarly, the probability of HHCB concentrations being less than the PNEC for freshwater sediment organisms was greater than or equal to 99.98%. Concentrations of HHCB in sludge amended soils were estimated for single and repeated annual sludge applications with tilling of the sludge into the soil, surface application without tilling and a combination reflecting current practice. The probability of soil HHCB concentrations being below the PNEC for soil organisms after repeated sludge applications was 94.35% with current sludge practice. Probabilistic estimates of HHCB exposures in surface waters, sediments and sludge amended soils are consistent with the published values for the U.S. In addition, the results of these analyses indicate that HHCB entering the environment in WWTP effluent and sludge poses negligible risk to aquatic and terrestrial organisms in nearly all exposure scenarios. © 2014 Elsevier B.V. All rights reserved.

1. Introduction Synthetic polycyclic musks (PCMs) are fragrance materials used in many consumer products such as shampoos, perfumes, cosmetics and

⁎ Corresponding author. E-mail address: [email protected] (P. Sun).

http://dx.doi.org/10.1016/j.scitotenv.2014.03.058 0048-9697/© 2014 Elsevier B.V. All rights reserved.

cleaning products and have frequently been reported in the environment (Roosens et al., 2007; Reiner and Kannan, 2011). In 2004, AHTN (6-acetyl-1,1,2,4,4,7-hexamethyltetraline, trade name Tonalide) and HHCB (1,3,4,6,7,8-hexahydro-4,6,6,7,8,8-hexamethylcyclopenta-γ-2benzopyran, trade name Galaxolide) comprised 90% of the U.S. market for musk fragrances (HERA, 2004). The major environmental pathway for these materials involves consumer release down the drain after which they become a constituent of domestic wastewater that is treated

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T. Federle et al. / Science of the Total Environment 493 (2014) 1079–1087

in a wastewater treatment plant (WWTP). Their primary entry routes into the environment are as components of effluent discharged into surface waters and sludge amended to soils. A recent monitoring effort measured the concentrations of AHTN and HHCB in effluent and sludge from 40 WWTPs across the United States (Sun et al., 2014). In this study, effluent levels of HHCB were on average 10 times greater than those for AHTN, while sludge levels of HHCB were on average 9.4 times greater than those for AHTN indicating that current uses and environmental releases of HHCB far exceed those for AHTN. During wastewater treatment, HHCB is removed by a combination of sorption, volatilization and biotransformation. Average removal for HHCB in different types of treatment systems are 30% for primary treatment, 88–90% for combined primary and activated sludge treatment (including oxidation ditches), 78% for combined primary and trickling filter systems and N 99% for lagoons (Simonich et al., 2002). Several environmental risk assessments have been conducted on polycyclic musks in Europe (HERA, 2004; Balk and Ford, 1999a, 1999b; Schwartz et al., 2000) with the most recent and comprehensive assessments conducted by the European Union in 2008 (European Union, 2008a, 2008b). In addition to these EU assessments, a screening level environmental risk assessment was recently published on PCMs in Lake Taihu, China (Guo et al., 2012). To our knowledge, there is no comparable assessment publically available for these materials in the U.S. at present. A variety of factors can account for differences in environmental risk in different regions. These variables relate primarily to exposure and include per capita chemical use, per capita water use, wastewater treatment infrastructure, dilution of wastewater treatment effluents and sludge disposal practices. Consequently, one needs to explicitly account for these factors when conducting a risk assessment in a specific region. The objective of this work was to conduct an environmental risk assessment for the consumer use and release of HHCB in the U.S. focusing on mixing zones immediately downstream from WWTPs and sludge amended soils. Given how HHCB enters the environment, mixing zones below WWTPs are the aquatic environments with the highest exposure. A probabilistic exposure approach was utilized combining statistical distributions of effluent and sludge concentrations for the U.S. WWTPs with distributions of mixing zone dilution factors and sludge loading rates to soil to estimate HHCB concentrations in surface waters and sediments below WWTPs and sludge amended soils. These predicted environmental concentrations (PECs) were then compared to various toxicity values including predicted no effect concentrations (PNECs). The statistical nature of the PEC estimates made it possible to estimate the probability of PEC values being less the various effect concentrations. The majority of the environmental effects data used for these comparisons were contained in the 2008 EU HHCB risk assessment (European Union, 2008b). Measured concentrations of HHCB in effluent and sludge from a recent monitoring program of 40 WWTPs (Sun et al., 2014) formed the basis for estimating environmental loadings. The aquatic risk assessment centered on mixing zones below WWTPs, receiving almost exclusively (N 90%) domestic wastewater, under low flow (7Q10) conditions and included inputs from other upstream WWTPs. 7Q10 is the lowest stream flow for seven consecutive days that would be expected to occur in a ten-year period. In this way, consumer inputs of HHCB were maximized and dilution was minimized to provide a relatively high level conservatism to the assessment. The terrestrial assessment likewise focused on fields receiving sludge from WWTPs receiving almost exclusively (N 90%) domestic wastewater to maximize HHCB inputs.

uc.edu/iSTREEM/login.aspx and is an update of GIS-ROUT (Wang et al., 2000, 2005). Dilution factors were determined for river segments below 8863 WWTPs nationwide. The model integrates the U.S. EPA's Enhanced Reach File Version 1.0 for the Conterminous United States (Alexander et al., 1999), the 2004 Clean Water Needs Survey dataset (U.S. EPA, 2008), and the Permit Compliance System database supporting the NPDES discharge permitting program (U.S. EPA, 2001). Dilution factors were extracted from the program by setting the level of chemical released from every WWTP in the database at a single uniform concentration and then allowing the program to estimate the concentration of the chemical in stream segments immediately below every WWTP. The effluent concentration released from each WWTP divided by the concentration estimated in the reach immediately below a given WWTP equals the dilution factor for that WWTP and includes hydrologic dilution of that effluent and contributions from other upstream WWTPs in the dilution water. Consequently, the dilution factors were based on hydraulic flows of WWTPs and surface waters. Dilution factors were estimated for mean and low (7Q10) stream flows and included all upstream inputs from other WWTPs. It did not include in-stream losses as a result of biotransformation or other processes (e.g. volatilization, sorption, and settling). An excel spreadsheet (Table S1 in Supporting Information) provides a list of the dilution factors used in this analysis. 2.2. Probabilistic exposure assessment for the pelagic aquatic environment A probabilistic model was constructed to estimate HHCB concentrations in WWTP mixing zones across the United States resulting from up-stream discharges to surface waters from municipal WWTPs receiving predominately domestic wastewater. The model was written with Excel 2007 and Crystal Ball, Fusion Edition and validated with point estimate inputs. It was based upon the distribution of HHCB concentrations measured in effluents (Sun et al., 2014) and the distribution of in-stream dilution factors derived from the iSTREEM. Each estimate of HHCB in mixing zone surface water was determined by dividing a HHCB effluent concentration with a dilution factor. Distributions describing effluent concentrations and dilution factors were modeled using the fit function in Crystal Ball to estimate surface water concentrations in mixing zones below WWTPs. Table 1 provides the detailed parameters and the distributions used in this probabilistic exposure analysis. 2.3. Probabilistic exposure assessment for sediment environment Sediment concentrations were estimated from mixing zone water concentrations based upon an equilibrium partitioning using the following equations:

C sedsolid ¼ Koc Foc C water

ð1Þ

where Csedsolid Concentration of HHCB on sediment solids (mg/kg dry wt.) Koc Partitioning coefficient for HHCB between organic carbon and water (L/kgC) Foc Organic carbon content of sediment solids (kgC/kg dry wt.) Concentration of HHCB in water (mg/L). Cwater

2.1. Determination of dilution factors in WWTP mixing zones

Dry bulk density (D) in kg/L for sediment was estimated based upon the Foc using the relationship described in Eq. (2) by Avnimelech et al. (2001):

iSTREEM, a U.S.-wide exposure model suitable for evaluating chemicals at the scale of river reaches, was used to estimate dilution in wastewater discharges below WWTPs. It is available at http://gis2.

D ¼ 1:766−0:363 ln ðFoc 1000Þ:

2. Methodology

ð2Þ


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Table 1 Model input parameters for Monte Carlo analysis to estimate HHCB exposure in WWTP mixing zone waters and sediments. Parameters

Distribution

HHCB concentration in effluent

Gamma Location Scale Shape Minimum Lognormal Location Mean Std. deviation Minimum Gamma Location Scale Shape Minimum Gamma Location Scale Shape Minimum sMaximum Point

Dilution factor at mean flow conditions

Dilution factor at low (7Q10) flow conditions

Organic carbon content of sediments

Organic carbon partitioning coefficient for HHCB in sediment (Koc)

Sediment porosity (P) in l/l was estimated based upon the bulk density and Foc with the following equations from Avnimelech et al. (2001): P ¼ 1−

D Dsolid

ð3Þ

where Dsolid

Values

References

ug/L

Sun et al. (2014)

0 1.05 1.3495 0.05 Current study −0.33 575.95 2611 1 Current study 1.00 251.74 0.19448 1 kgC/kg dw 0 0.04 1.07 0.0005 0.30 7079

Lyndall et al. (2010)analysis of NOAA (2004) data

Fooken (2004)

model was modified to include repetitive amendment with sludge on an annual basis so that the output included not only freshly added chemical but also residual chemical remaining from prior applications. The model was written using Excel 2007 and Crystal Ball, Fusion Edition and validated with point estimate inputs. The HHCB concentration in soil following the first application was determined using the following equations: Csoilðn¼1Þ ¼

weighted average sediment solid density

Units

Cadd SoilMass þ SludgeApp

ð7Þ

where Dsolid ¼ 1:25 Fom þ 2:65 ð1−FomÞ

ð4Þ

where Fom

Fraction of organic matter (kg organic matter/kg dry wt.)

Fom ¼ 1:7 Foc: ð5Þ Total sediment concentration (Csedtot) in mg/kg dry weight (dw) was then estimated with Eq. (6):

C sedtot ¼ Csedsolid þ

Cwater P : D

ð6Þ

Concentration of HHCB in Soil immediately after 1st Application(mg/kg dw) Mass of HHCB (mg/ha) added to soil during an application Cadd Soil Mass Mass of Soil into which Sludge is Mixed (kg dw/ha) SludgeApp Sludge Application Rate to Soil (kg dry sludge/hectare). Cadd and SoilMass were calculated using Eqs. (8) and (9).

Csoil(n

C add ¼ C sludge SludgeApp

ð8Þ

where Csludge

The probabilistic model was run using Monte Carlo simulations with random sampling and 500,000 iterations. During the simulation, estimated HHCB effluent concentrations that were less than the LOQ (limit of quantitation, i.e. b 0.05 μg/L) for the analytical method were set to a default value of 0.05 μg/L. In the same approach, estimated dilution factors less than 1 were set to a default value of 1.

= 1)

Concentration of HHCB in Sludge (mg/kg dw)

SoilMass ¼ Depth Area SoilBulkDensity

ð9Þ

where Depth Mixing Depth of Sludge into the Soil (m) Area 10,000 m2 (ha) Soil Bulk Density 1200 kg/m3.

2.4. Probabilistic exposure assessment for sludge amended soils A probabilistic model was constructed to estimate HHCB concentrations in the sludge amended soil. It was a modification of the direct exposure model described previously by Fuchsman et al. (2010). The original model incorporated distributions describing concentrations of a chemical in sludge, sludge application rates to soil, mixing depths of sludge into the soil, and the prevalence of till or no till application to estimate chemical concentration in the soil immediately after a sludge application. This

The residual HHCB and sludge mass remaining in the soil after a year and immediately prior to the next sludge application were determined using the following two equations (Eqs. (10) and (11)): −kct

C remðn¼1Þ ¼ Cadd e where

ð10Þ

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Table 2 Model input parameters for Monte Carlo analysis to estimate HHCB exposure in sludge amended soils. Parameters

Distribution

HHCB concentration in sludge

Lognormal Location Geo Mean Geo Std. deviation Lognormal Location Geo Mean Geo Std. deviation Minimum Point Triangular Minimum Best Maximum Point Point Point

Sludge application rate

Soil mixing depth (no till) Soil mixing depth (till)

Probability of no till Soil loss rate for HHCB Sludge decay rate in soil

Crem(n

Values

Units

References

mg/kg dw

Sun et al. (2014)

kg/ha

Fuchsman et al. (2010)

m m

Fuchsman et al. (2010) analysis of U.S. Environmental Protection Agency (2003b) data Fuchsman et al. (2010) analysis of Schowanek et al. (2007) data

Proportion Days−1 Days−1

Fuchsman et al. (2010) analysis of CTIC (2007) data European Union (2008b) Gilmour and Gilmour (1980)

−5.69 33.29 1.86 −2241.45 19,012.6 2.36 500 0.02 0.15 0.20 0.25 0.25 0.0046 0.00051

Mass of HHCB (mg) Remaining in Soil 1 year after Sludge Application 1st order Decay Rate of HHCB in Soil (days−1) Base of the natural log (0.693) Days since last application (365)

= 1)

kc e t

SludgeMassremðn¼1Þ ¼ SludgeApp e

−kst

ð11Þ

run using the Monte Carlo simulations with random sampling and 500,000 iterations. During the simulation, sludge application rates estimated to be less than 500 kg/ha were set to this value as a default. Table 2 contains the parameters and describes the distributions used in this analysis. 3. Results and discussion 3.1. HHCB concentration in WWTP effluent and sludge

where SludgeMassrem(n = 1) Mass of Sludge (kg/ha) Remaining in Soil 1 year after Application 1st order Decay Rate of Sludge in Soil (days−1). ks The concentrations of HHCB in soil at the time of subsequent sludge applications were calculated in an iterative manner using Eq. (12): C soilðnÞ ¼

C add þ C remðn−1Þ MassSoil þ SludgeApp þ SludgeMassremðn−1Þ

ð12Þ

where Csoil(n)

Concentration HHCB immediately following the nth application (mg/kg dw)

Crem(n − 1) Mass of HHCB remaining in the Soil from prior applications (mg/kg dw) SludgeMassrem(n − 1) Mass of Sludge remaining in the Soil from prior applications (kg dw/ha).

The distribution describing sludge concentrations was modeled using the fit function in Crystal Ball. The probabilistic model was

Measured concentrations of HHCB in effluent and sludge from a monitoring program of 40 WWTPs across the U.S. formed the basis of estimating environmental loadings. Detailed information on sampling and analytical results can be found elsewhere (Sun et al., 2014). The summary statistics describing HHCB concentrations in effluent and sludge are listed in Table 3. Briefly, the measured HHCB levels in effluent averaged at 1.85 ± 1.09 μg/L and ranged from 0.45 to 4.79 μg/L with a median of 1.55 μg/L and 90th percentile of 3.39 μg/L. This distribution of effluent concentrations was fit to various distribution models and was best described by a gamma distribution. HHCB concentrations in sludge ranged from 4.1 to 91 mg/kg dw with a mean of 34.0 ± 23.1 mg/kg dw (mean ± standard deviation). The median was 25.8 and the 90th percentile was 68.0 mg/kg dw. The distribution comprised of HHCB levels in sludge was best described by a lognormal model. 3.2. Dilution factors in WWTP mixing zones The summary statistics describing in-stream dilution factors predicted by the iSTREEM under mean flow and low (7Q10) flow conditions also can be found in Table 3. Distributions of mean and low flow dilution factors were likewise fit to various models, with mean flow dilution factors best described by a lognormal distribution and low flow best described by a gamma distribution. At mean flow, the median in-stream

Table 3 Summary statistics for measured HHCB concentrations in 40 WWTP effluents, sludge and estimated in-stream dilution factors in the mixing zones below 8863 WWTPs under mean and low (7Q10) flow conditions. Summary statistics

HHCB concentration in WWTP effluent (μg/L)a

HHCB concentration in WWTP sludge (mg/kg dw)a

Mixing zone dilution factors at mean flow

Mixing zone dilution factors at low (7Q10) flow

Mean ± S.D. Minimum Maximum 10th percentile Median 90th percentile

1.85 ± 1.09 0.45 4.79 0.71 1.55 3.39

34.0 ± 23.1 4.1 91 8.53 25.8 68

584 ± 2979 1 161,511 13 131 1037

50 ± 300 1 14,238 1 5 78

a

Data from Sun et al. (2014).

T. Federle et al. / Science of the Total Environment 493 (2014) 1079–1087 Table 4 Summary statistics for estimated HHCB concentrations in surface water in mixing zones below WWTPs under mean and low (7Q10) flow conditions derived from a Monte Carlo analysis. Summary statistics

HHCB concentration in WWTP mixing zones at mean flow (μg/L)

HHCB concentration in WWTP mixing zones at low flow (μg/L)

Mean ± S.D. Median 90th percentile 95th percentile 99th percentile

0.07 ± 0.23 0.01 0.14 0.28 1.02

0.72 ± 1.02 0.27 2.06 2.81 4.51

dilution factor was 131, and values ranged from 1 to 161,511 across the entire U.S. At low flow, the median in-stream dilution factor was 5, and values ranged from 1 to 14,238. This wide range of dilution factors is not unexpected given the diversity of hydrology, climates and precipitation patterns in the U.S. 3.3. Pelagic mixing zone risk assessment Table 4 and Figure S1 summarize the results of the Monte Carlo analysis to estimate surface water concentrations in mixing zones below WWTPs at mean and low flow. The predicted median, 90th percentile and 99th percentile concentrations of HHCB in mixing zones at mean stream flow were 0.01, 0.14 and 1.02 μg/L, respectively, while these same percentiles at low flow were 0.27, 2.06 and 4.51 μg/L. Sensitivity analysis indicated that approximately 90% of the variance in mixing zone concentrations was attributable to dilution with the balance associated with effluent concentration. These estimated concentrations are consistent with the measured U.S. surface water concentrations reported in the literature. In 2004, Kolpin et al (2004) reported maximum observed concentrations of HHCB of 0.056 μg/L under high flow conditions and 0.26 μg/L under low flow conditions in 23 stream locations upstream and downstream of ten cities in the State of Iowa. In 2005, Alvarez et al. (2005) measured HHCB concentrations ranging from 0.12 to 0.32 μg/L approximately 100 m downstream from a WWTP discharge to Assunpink Creek near Trenton NJ and lower levels (0.04–0.12 μg/L) two miles further downstream. In 2011, Reiner and Kannan (2011) measured HHCB levels varying from 0.004 to 0.025 μg/L in the upper Hudson River in New York, and in the same time frame, Chase et al. (2012) reported levels ranging from 0.08 to 0.79 μg/L in the North Fork of the Brazos River in Texas. Estimated surface water mixing zone concentrations were compared to toxicity values to determine the probability of HHCB exposure exceeding a safe concentration for pelagic organisms. While a variety of toxicity values have been reported for HHCB, the EU HHCB Risk Assessment (European Union, 2008b) reviewed these data and focused on four high quality freshwater chronic toxicity tests. The PNEC was calculated by dividing the lowest NOEC (no effect concentration) from these test studies by a factor of 10, which is customary to adjust for uncertainty with this level of effects data (Nabholz, 1991). Table 5 contains the NOECs and PNEC, based on

1083

Table 6 Summary statistics for estimated HHCB concentrations in sediments in mixing zones below WWTPs under mean and low (7Q10) flow conditions derived from a Monte Carlo analysis. Summary statistics

HHCB concentration in WWTP mixing zone sediments at mean flow (μg/kg dw)

HHCB concentration in WWTP mixing zone sediments at low flow (μg/kg dw)


21.4 ± 239 2.34 37.1 80.5 350

222 ± 1161 41.5 623 1030 2340

fathead minnow toxicity, as well as the probabilities of HHCB levels being lower than these values in mixing zones downstream from WWTPs under both mean and low flow conditions. In all but one situation the probability of exposure being less than a chronic NOEC or a PNEC was N 99.99%. The only exception was at low flow, when the probability of exposure being less than the PNEC was slightly lower at 99.87%. 3.4. Mixing zone sediment risk assessment HHCB concentrations in sediment were based on the distribution of HHCB surface water concentrations in mixing zones, estimated above, and the distribution of organic carbon content (Foc) of the U.S. sediments. Foc was used not only to estimate the partitioning of HHCB to sludge solids but also to estimate the porosity and bulk density of the sediments. Table 6 and Figure S2 summarize the results of this Monte Carlo analysis to estimate sediment concentrations in mixing zones below WWTPs at mean and low flow. The predicted median, 90th percentile and 99th percentile HHCB concentrations in mixing zone sediments at mean stream flow were 2.34, 37.1 and 350 μg/kg dw, respectively, while these same values at low flow were 41.5, 623 and 2340 μg/kg dw. Sensitivity analysis revealed that approximately 66–71% of the variances in estimated sediment concentrations was associated with effluent dilution, 23– 26% with organic carbon content of the sediments and 7–8% with HHCB concentration in the effluent. These values are consistent with the limited data available in the literature for HHCB levels in the U.S. sediments. Peck et al. (2006) reported HHCB levels in sediment cores obtained from Lakes Erie and Ontario. Surficial sediment concentrations were 3.2 and 16 μg/kg dw in Lake Erie and Lake Ontario, respectively. Within the Lake Erie core, levels ranged from 0.3 to 3.3 μg/kg dw, while within the Lake Ontario core, they varied from b5.1 to 38 μg/kg dw. In addition to reporting HHCB water concentrations, Reiner and Kannan (2011) measured sediment levels in the Hudson River that ranged from 72.8 to 388 μg/kg dw, while Chase et al. (2012) reported HHCB levels ranging from 1.4 to 2.1 μg/kg dw in sediment from a lake receiving WWTP effluent. Table 7 contains toxicity data for freshwater sediment organisms contained in the EU HHCB Risk Assessment (European Union, 2008b). Once again, while all available sediment toxicity data were

Table 5 Chronic HHCB toxicity values for freshwater pelagic species and probability that WWTP mixing zone concentrations will not exceed these values based upon the Monte Carlo analysis. Pelagic test organism

Alga (Pseudokirchneriella subcapita) Daphnia magna Bluegill Sunfish (Lepomis macrochirus) Fathead Minnow (Pimephales promelas) PNEC (Lowest NOEC divided by 10) a

Data from EU HHCB Risk Assessment (European Union, 2008b).

NOECa (μg/L)

201 111 93 68 6.8

Probability of HHCB concentration in WWTP mixing zones being below toxicity value Mean flow conditions

Low flow conditions

N99.99% N99.99% N99.99% N99.99% N99.99%

N99.99% N99.99% N99.99% N99.99% 99.87%

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Table 7 Chronic HHCB toxicity values for freshwater sediment species and probability that WWTP mixing zone concentrations will not exceed these values based upon the Monte Carlo analysis. NOECa (μg/kg dw)

Sediment test organism

Chironomus riparius Hyalella azteca Lumbriculus variegatus PNEC (Lowest NOEC divided by 10) a

200,000 7100 16,200 710

Equivalent overlying water concentration (μg/L)

Probability of HHCB concentration in WWTP mixing zone sediments being below toxicity value

1670 85.7 168 8.5

Mean flow conditions

Low flow conditions

N99.99% N99.99% N99.99% N99.99%

N99.99% N99.99% N99.99% 99.98%

Data from EU HHCB Risk Assessment (European Union, 2008b).

reviewed, the PNEC was derived from a select series of high quality chronic toxicity tests contained in the table. The artificial sediment in these tests contained 1.8 to 2.6% organic carbon and 65 to 70% dry weight solids. The estimated HHCB sediment concentrations in mixing zones include sediments with much more variable and different levels of organic carbon content and fraction dry solids than those used in the toxicity tests. Consequently, rather than directly comparing the estimated sediment concentrations with these toxicity values, the toxicity values were converted to equivalent overlying water concentrations, resulting in a reported sediment toxicity value based upon the equilibrium partitioning theory. These values were then compared to the mixing zone water concentrations of HHCB. Overlying equivalent water concentration was calculated from the reported toxicity values using the following equation: C waterequiv ¼

ToxValue Fsolids Foc Koc

ð13Þ

where ToxValue Fsolid Foc Koc

NOEC (μg/kg dw) Fraction of dry solids in toxicity test (0.65–0.70) Organic carbon content (kgC/kg dw) (.018–0.026) Partitioning coefficient for HHCB between organic carbon and water (L/kgC).

Table 7 shows that the probability of HHCB surface water concentrations in WWTP mixing zones not exceeding this equivalent PNEC, based on Hyalella azteca's NOEC, was minimally 99.98% under both mean and low flow conditions. 3.5. Sludge amended soil risk assessment The distribution of measured HHCB sludge concentrations was combined with a distribution of sludge application rates to estimate HHCB concentrations in the sludge amended soil immediately following an initial sludge application using the Monte Carlo analysis. Moreover, by including soil decay rates for HHCB and sludge, maximum soil HHCB concentrations were estimated after repeated annual applications. The model simulations revealed that a maximum soil HHCB level was reached after the 3rd application. With further

additions, soil HHCB levels decline slightly due to dilution resulting from a buildup of sludge solids, which decay slower than HHCB. Table 8 and Figures S3–S5 summarize the results of the Monte Carlo analyses to estimate initial and maximum HHCB concentrations in the sludge amended soil for 3 scenarios: tilling of the applied sludge into the soil, direct application of sludge to the surface of the soils (without tilling) and a combination of tilling (75%) and no tilling (25%) representative of current practice. The estimated 99th percentile soil concentrations of HHCB immediately following an initial sludge application were 2.68 mg/kg dw with tilling, 19.8 mg/ kg dw without tilling and 11.5 mg/kg dw with both practices. The 99th percentile maximum soil concentrations after repeated sludge applications were 3.12, 20.3 and 12.0 mg/kg dw, respectively. Sensitivity analysis indicated that 56–61% of the variations in estimated HHCB concentrations in sludge amended soils was associated with sludge application rates in the tilling and no tilling scenarios with the balance (38–44%) related to sludge HHCB concentrations. In the combined till and no till scenario, 39% of the variation was associated with application rates, 35–36% with sludge concentrations and 24– 25% with frequency of the no till practice. In the tilling and combined scenarios, sludge mixing depth accounted for b1% of the variation. The sole literature report regarding the concentrations of HHCB in the sludge amended soil for North America is for a single application of sludge to a field in Ontario, Canada. Yang and Metcalfe (2006) measured 0.002–0.003 mg/kg dw of HHCB in soil samples collected 1 day and 2 weeks post-application with no HHCB being detected after 6 months. While these initial measured soil concentrations were very low compared to model predictions, presumably due to a low sludge application rate, the decrease in HHCB with time was consistent with modeled dissipation after application. Tables 9 and 10 show chronic toxicity data for earthworms and springtails contained in the EU HHCB Risk Assessment (European Union, 2008b). Since no standard toxicity data were available for terrestrial plants in the EU report, a NOEC was estimated from the results of a nonstandard seed germination and seedling growth study with wheat (Chen et al., 2010). Furthermore, additional plant toxicity values were estimated from the algal chronic toxicity data and a nonstandard hydroponic study with wheat (An et al., 2009), In the case of the latter, a NOEC was not reported and an EC20 was first estimated from the data. These toxicity values were converted to mg/ kg dw based upon equilibrium partitioning data using the following

Table 8 Summary statistics for estimated HHCB concentrations in sludge amended soils generated through a Monte Carlo analysis. Summary statistics


HHCB concentration (mg/kg dw) in sludge amended soils after initial sludge application

Maximum HHCB concentration (mg/kg dw) in sludge amended soils after repeated sludge applications

With tilling

Without tilling

All conditions

With tilling

Without tilling

All conditions

0.36 ± 0.58 0.18 0.84 1.26 2.68

3.01 ± 4.15 1.69 7.08 10.3 19.8

1.02 ± 2.44 0.28 2.52 4.45 11.5

0.42 ± 0.66 0.22 1.00 1.49 3.12

3.24 ± 4.26 1.89 7.51 10.7 20.3

1.13 ± 2.52 0.33 4.50 4.95 11.9


1085

Table 9 Chronic HHCB toxicity values for terrestrial species and probability that concentrations in sludge amended soils will not exceed these values following an initial application of sludge based upon the Monte Carlo analysis. Terrestrial test organism

NOEC (mg/kg dw)

Probability of HHCB concentration in sludge amended soil being below toxicity value after initial sludge application With tilling

Without tilling

All conditions

Earthworm (Eisenia fetida) Springtail (Folsomia candida) Wheat seed germination & seedling growth (Triticum aestivum) Algae (Pseudokirchneriella subcapita) Hydroponic Wheat (Triticum aestivum)

45a 45a 77b 99a,b 4,714c,d (EC20) 68.7 4.5

N99.99% N99.99% N99.99% N99.99% N99.99%

99.94% 99.94% N99.99% N99.99% N99.99%

99.98% 99.98% N99.99% N99.99% N99.99%

N99.99% 99.74%

99.94% 80.41%

99.98% 94.93%

Toxicity reference valuee PNECf (Lowest NOEC divided by 10) a b c d e f

Data from EU HHCB Risk Assessment (European Union, 2008b). Data from Chen et al. (2010). Based upon equilibrium partitioning calculation. Data from An et al. (2009). Based upon procedures in the USEPA Guidance for Developing Ecological Soil Screening Levels (USEPA, 1995). Based upon procedures in the European Chemical's Bureau TGD (European Chemical Bureau, 2003).

equation: SoilToxValue ¼ WaterToxValue Kd

ð14Þ

where SoilToxValue Equivalent toxicity value on a dry weight basis (mg/kg dw) Kd Soil water partitioning coefficient (L/kg dw) = 495 L/kg (9) WaterToxValue Toxicity endpoint in mg/L. Unlike aquatic risk assessment, there is no single perspective among regulatory agencies on the risks and benefits of applying sewage sludge to neither agricultural soil nor a common or consensus approach for developing soil protection criteria from terrestrial toxicity data. Consequently, both sludge loading rates and the approach for determining protection criteria differ around the world. The EU Technical Guidance Document on Risk Assessment (European Chemicals Bureau, 2003) uses annual sludge application rates of 1–5 t/ha for risk assessment. In the U.S., a sludge application rate of 10 t/ha on an annual or biannual basis is considered typical for agricultural soil and reported ranges of soil application rates to agricultural soil range from 2 to 70 t/ha (US EPA, 1995). The data used by Fuchsman et al. (2010) to develop the distribution of sludge application rates, had a median of 31 t/ha and a range from 0.6 to 213 t/ha. Moreover, approaches for determining protection criteria can differ. The U.S. Environmental Protection Agency's approach for soil protection is contained within a document, EPA Guidance for Developing Ecological Soil Screening Levels (U.S. Environmental Protection Agency, 2003a). In this document, a method is described for estimating a Toxic Reference Value (TRV) from the available terrestrial data. In the presence of sufficient chronic data, the TRV is calculated by taking the geometric mean of the available chronic toxicity values. To be conservative in this study, the TRV for HHCB was based only on the invertebrate data. In addition, a soil PNEC was calculated by dividing the lowest NOEC with an uncertainty factor of 10 because chronic data for 3 species were available. This is the most stringent regulatory approach and the one prescribed within the European Union (European Chemicals Bureau, 2003). In a similar approach, the Canadian Council of Ministers of the Environment employ uncertainty factors to determine soil quality guidelines and soil quality remediation objectives, but the uncertainty factors range from only 1 to 5 based upon the chronic toxicity information available (U.S. Environmental Protection Agency, 2003b). Tables 9 and 10 show the probabilities that HHCB in sludge amended soils will not exceed the toxicity values for the various soil test organisms after single and repeated sludge applications,

respectively. In the case of the soil NOECs and the TRV, this probability is at least 99.94% in all sludge application scenarios. When the lowest NOEC is divided by an uncertainty fact of 10 to estimate a PNEC, these probabilities are 99.74% with tilling, 80.41% without tilling and 94.93% when both practices are combined during the initial application. With repeated applications of sludge, these probabilities decrease to 99.62%, 78.29% and 94.35%, respectively. Hence, the only situation where risk is not negligible is when sludge is directly added to the soil surface at high application rates without tilling and highly conservative toxicity criteria are used. Nevertheless, it is important to recognize a variety of factors when interpreting these results. First, although the same distribution of sludge application rates is used for both till and no till scenarios, it is unlikely that some of the high loadings represented in the distribution would be used for surface application. In the no till scenario exposure occurs only in the top 2 cm of soil, where the potential for dissipation through volatilization and weathering is the highest. Moreover, this zone is also above the planting and root zone for most agriculturally important species and most biological activity in a soil occurs below this depth. Furthermore, at the time of sludge application, HHCB is bound to the sludge and the soil zone contains very high levels of sludge organic matter that would decrease HHCB's bioavailability. Thus, the field situation is quite different from that existing in the artificial soils used in the toxicity tests, which would yield more conservative results given in the absence of sludge and a lower level of organic matter. In addition, soil compaction associated with no till agriculture may have much more certain and adverse affects on earthworm populations than components of sludge immediately following sludge application (Capowiez et al., 2012). While this work focuses on the environmental risks associated with the HHCB parent molecule, HHCB lactone is a known oxidation and biotransformation product that has been measured in various environmental compartments. Bester (2005) reported a typical ratio of HHCB lactone to HHCB parent of 0.42 in surface water in a catchment of the Ruhr River but found that ratios of the lactone to the parent were variable ranging from 0.17 to 0.95 in the WWTP effluents entering the catchment. Reiner et al. (2007) reported average concentrations for HHCB of 3.35 and 2.7 μg/L in effluents of two New York WWTPs with corresponding average HHCB lactone concentrations of 1.74 and 1.62 μg/L. They also reported average sludge levels of 9.5 and 14 mg/kg dw for HHCB and 7.2 and 6.3 mg/kg dw for HHCB lactone. In another study, Horii et al (2007) measured these same analytes in effluent and sludge from a WWTP in Kentucky and in another from Georgia. Average concentrations in the Kentucky plant

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Table 10 Chronic HHCB toxicity values for terrestrial species and probability that concentrations in sludge amended soils will not exceed these values after repeated applications of sludge based upon the Monte Carlo analysis. Terrestrial test organism

NOEC (mg/kg dw)

Probability of maximum HHCB concentration in sludge amended soil being below toxicity value after repeated sludge applications With tilling

Without tilling

All conditions

Earthworm (Eisenia fetida) Springtail (Folsomia candida) Plants (Alga) (Pseudokirchneriella subcapita) Wheat (Triticum aestivum)

45a 45a 99a,b 4,714b,c (EC20) 45 4.5

N99.99% N99.99% N99.99% N99.99%

99.94% 99.94% N99.99% N99.99%

99.99% 99.99% N99.99% N99.99%

N99.99% 99.62%

99.94% 78.29%

99.99% 94.35%

Toxicity Reference Valued PNECe (Lowest NOEC divided by 10) a b c d e

Data from EU HHCB Risk Assessment (European Union, 2008b). Based upon equilibrium partitioning calculation. Data from An et al. (2009). Based upon procedures in the USEPA Guidance for Developing Ecological Soil Screening Levels (USEPA, 1995). Based upon procedures in the European Chemical's Bureau TGD (European Chemical Bureau, 2003).

were 0.044 and 0.229 μg/L for parent and the lactone, respectively, while these concentrations were 0.055 and 0.378 μg/L in the Georgia WWTP. Sludge levels of HHCB in these same WWTPs were 9.5 and 14 mg/kg dw, while the corresponding HHCB lactone concentrations were 7.2 and 6.3 mg/kg dw. These studies indicate that environmental exposure to the HHCB lactone are variable and can be significant depending on the concentrations. While aquatic and terrestrial toxicity data are not readily available for HHCB lactone, the USEPA ECOSAR program can be used to compare the toxicity of these two compounds. In the case of fish, the most sensitive taxa for HHCB, the lactone is predicted to be 5 to 12 times less toxic than the parent. Consequently, it is likely that parent HHCB accounts for the bulk of the toxic units in the environments associated with its consumer use. 4. Conclusion In summary, this study shows that concentrations of parent HHCB released in municipal WWTP effluents, receiving primarily household wastewater, represent a negligible risk to biological communities in surface water and sediments below WWTPs. In addition, it also demonstrates that concentrations of HHCB present in sludge typically represent negligible risk to terrestrial species when sludge is used as a soil amendment. However, there may be some higher localized risk at the time of application in situations where sludge is directly applied at high rates to the surface of soil without tilling. Nevertheless, such situations are likely less frequent than predicted by the model and mitigated by other factors. Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.scitotenv.2014.03.058. References [CTIC] Conservation Technology Information Center. Amendment to the National Crop Residue Management Survey Summary. Available from http://www. conservationinformation.org/pdf/National_Summary_2007_Amendment.pdf, 2007. [NOAA] National Oceanic and Atmospheric Administration. Sediment toxicity database (SEDTOX) freshwater. Office of Response and Restoration; 2004 [Available from: http://www.response.restoration.noaa.gov/cpr/sediment/]. Alexander RB, Brakebill JW, Brew RE, Smith RA. ERF — enhanced River Reach File 1.2. Reston (VA): U.S. Geological Survey; 1999. Alvarez DA, Stackelberg PE, Petty JD, Huckins JN, Furlong ET, Zaugg SD, et al. Comparison of a novel passive sampler to standard water-column sampling for organic contaminants associated with wastewater effluents entering a New Jersey stream. Chemosphere 2005;61:610–22.

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