Via Electronic and Certified Mail 

August 3, 2012 

Mr. Ward Penberthy 

USEPA Headquarters 

Ariel Rios Building 

1200 Pennsylvania Avenue, N.W. 

Mail Code: 7405M 

Washington, DC 20460 

Re: Follow Up to July 24, 2012 Siloxane Technical Working Group Teleconference 

Dear Ward: 

On behalf of the member companies of the Silicones Environmental, Health and Safety Council of 

North America (SEHSC), this letter with supporting documents follows up on the discussions during the 

July 24, 2012 Siloxane Technical Working Group teleconference concerning the development of an 

environmental monitoring program for D4 and D5. During the call SEHSC agreed to provide further 

information on the scientific basis for the number of publicly owned treatment works (POTW) monitoring 

sites included in its environmental monitoring proposal. You also asked us to provide feedback on the 

Major Factors Relevant to the Environmental Presence of Siloxanes document the U.S. Environmental 

Protection Agency (EPA or Agency) shared during the teleconference and the Results from EPA’s 

Proposed D-Optimal Design of Experiment Analysis document EPA provided after the call (together 

referred to as EPA’s “Proposal”). Those items as well as some comments on the enforceable consent 

agreement (ECA) development process are provided below for your consideration. 

Scientific Basis for Number of POTW Monitoring Sites 

The intent of SEHSC’s March 1, 2012 environmental monitoring proposal is to lay out a monitoring 

program that would generate sufficient data to validate the conceptual site models that were developed 

for D4/D5 manufacturing, processing and formulating sites and publicly owned treatment works 

(POTWs) and provide for a better understanding of the presence and concentration of D4 and D5 in the 

environment and sources of and pathways to the environmental concentrations of D4 and D5. Such 

information could then be used by the Agency to assess the risk, if any, D4 and D5 may pose to the 

environment. 

With respect to the POTW monitoring component of our proposal, attached is a report entitled 

Recommendation of Number of Sites to Sample for Validation of the D4 and D5 Publicly-Owned 

Treatment Works Conceptual Site Model which was prepared for SEHSC by ERM. This report, 

together with information included in Attachments 2 to 6 to this letter, provide support for the number of 
August 3, 2012 

Mr. Ward Penberthy 

Page 2 of 3 

 

POTW monitoring sites included in the March 1, 2012 environmental monitoring proposal submitted by 

SEHSC. 

Importantly, this report should also be considered in conjunction with SEHSC’s January 31, 2012 

submission of the D4 and D5 Conceptual Site Models and Mass Balance Report which provided 

detailed information on the development of conceptual site models for D4 and D5 manufacturing, 

processing and formulating (MPF) facilities and for publicly owned treatment works (POTWs) that 

receive wastewater containing D4 and/or D5. The referenced report included detailed emission 

estimates and mass balances for MPF facilities based on an aggregation of facility-specific data 

supplied by SEHSC member companies. In the January 31 submission, SEHSC also provided 

information regarding existing D4/D5 monitoring programs and available data, including industry’s 

Voluntary Product Stewardship Initiative (VPSI) and significant monitoring work conducted by 

government authorities in Canada and Oregon. All of this information contributed to the development of 

the March 1, 2012 environmental monitoring proposal. 

Feedback on EPA “Proposal” 

During the July 24, 2012 Siloxane Technical Working Group teleconference, SEHSC agreed to provide 

feedback on EPA’s “Proposal” regarding site selection for the POTW monitoring component of an 

environmental monitoring program. Our comments on the Agency’s proposed approach are provided in 

Attachment 2, which incorporates Attachments 3 to 6 by reference. 

Comments on ECA Development Process 

Based on the most recent discussions with EPA, SEHSC has some concerns about the ECA 

development process. As you know, SEHSC submitted an initial D4/D5 environmental monitoring 

proposal to EPA on April 29, 2011. That proposal was crafted based on industry’s discussions with 

EPA regarding the Agency’s interest in, among other things, “a better understanding of the sources of 

and pathways to the environmental concentrations of D4/D5 in environmental media and biota.” EPA 

provided its feedback on the proposal via September 19, 2011 letter with attachment from Maria Doa to 

Karluss Thomas (Doa Letter). SEHSC used this feedback and subsequent discussions with the 

Agency to help guide its preparation of the technical documentation submitted to EPA on January 31, 

2012 and the revised environmental monitoring proposal submitted on March 1, 2012. 

On March 7, 2012, SEHSC met with representatives of the Agency to provide a presentation on the 

revised environmental monitoring proposal and to address any questions regarding the scope/contents 

of the proposal. Following this meeting, based on feedback from the Agency, it was our understanding 

that EPA believed that the revised proposal represented a reasonable basis to proceed with the 

development of an ECA. Indeed, the May 24, 2012 Federal Register notice (FR Notice) announcing a 

public meeting to kick off the ECA negotiation process states that EPA has evaluated the environmental 

monitoring proposal submitted by SEHSC on behalf of its members and the Agency believes that 

“proceeding with the negotiation of a consent agreement is an efficient means of developing the data.” 

In light of the above, SEHSC’s members were extremely surprised and concerned to learn during the 

July 24, 2012 Siloxane Technical Working Group teleconference that EPA’s “Proposal” is that 42 sites 

be included in POTW portion of the environmental monitoring program rather than the 5 sites described 

in our proposal. There are, of course, significant technical, practical, and cost ramifications to such an 

extensive expansion of the scope of an environmental monitoring program. Given that on just this one 

aspect of the environmental program EPA is expressing a desire for a program that is over 8 times 

more expansive than what was proposed, we are confused as to the basis for the prior determination 

that SEHSC’s proposal constituted a reasonable basis for moving forward with the negotiation of an 

ECA. Equally importantly, such a drastic expansion of the monitoring program is not necessary to 
August 3, 2012 

Mr. Ward Penberthy 

Page 3 of 3 

 

achieve the goal of assessing potential for risk to the environment from D4 and D5 discharges from 

manufacturing, processing, formulation sites and from high volume industrial and commercial end uses. 

When considered in the context of the tremendous amount of information that already exists on the 

environmental discharges, fate and effects of D4/ D5, SEHSC’s proposal would clearly provide 

sufficient data to assess whether there is such a potential risk. 

SEHSC has already expended significant time and resources in compiling technical documentation and 

preparing environmental monitoring proposals to address the Agency’s “concerns regarding the 

environmental effects of D4 and D5” and determination that “[e]nvironmental monitoring could help 

develop a better understanding of the potential effects of these chemicals in the environment.”1

 

Throughout the proposal development process, SEHSC has been very transparent with EPA. We have 

provided extensive data and information regarding the behavior of D4/D5 in the environment and we 

have consistently sought out opportunities to meet with the Agency to explain the state of the science 

regarding D4/D5, as well as the scope, purpose, and basis for our proposed monitoring program. 

SEHSC prepared the March 1, 2012 proposal in good faith based on the feedback received to date 

from the Agency taking into account best available science regarding the substances. We believe that 

our proposal represents an unprecedented commitment by industry to conduct extensive environmental 

monitoring under an ECA on substances which we believe, and other regulatory authorities have 

concluded, do not pose any appreciable risk to the environment. We believe that our proposal would 

provide the Agency with sufficient information for it to better understand the potential environmental 

effects of the substances and assess the risk, if any, the substances may pose to the environment. 

Accordingly, we are very concerned about the Agency responding at this point in the ECA negotiation 

process with a proposal that differs so substantially on such a fundamental point as number of 

monitoring sites from the March 1, 2012 proposal by SEHSC which was to serve as the basis for the 

negotiation. The intent of our monitoring proposal was never to conduct an extensive research 

program at POTW sites which we believe would be more appropriately addressed in a different venue 

under other regulatory authority. Rather, it was to develop data to enable the Agency to assess the 

risk, if any, D4/D5 pose to the environment. In that regard, we stand ready to continue to work with 

EPA and other interested parties in developing a realistic environmental monitoring program that takes 

into account all of the available scientific information on the behavior of these chemicals in the 

environment. We trust that the upcoming teleconference on August 7th will be productive to that end. 

In the meantime, if you have any questions regarding this submission, please do not hesitate to contact 

me at (703) 788-6570. 

Sincerely, 

Karluss Thomas 

Executive Director, SEHSC 

Enclosures 

 

1 77 Fed. Reg. 31009 (May 24, 2012).
Delivering sustainable solutions in a more competitive world

Recommendation of Number of Sites 

to Sample for Validation of the D4

and D5 Publicly-Owned Treatment 

Works Conceptual Site Model 

Silicones Environmental, Health and Safety Council 

Herndon, VA 20171 

July 2012 

www.erm.com 

Final Report 
Silicones Environmental, Health and Safety Council 

Recommendation of Number 

of Sites to Sample for 

Validation of the D4 and D5

Publicly-Owned Treatment 

Works Conceptual Site Model 

July 2012 

ERM Project No. 0151161 

Salvatore T. Giolando, Ph.D. Partner-in-Charge 

Donna D. Morrall, Ph.D., Project Manager 

Elsie F. Millano, Ph.D., P.E., Project Manager

Environmental Resources Management 

1701 Golf Road, Suite 1-1000 

Rolling Meadows, IL 60008 

www.erm.com 
DRAFT 

TABLE OF CONTENTS 

EXECUTIVE SUMMARY................................................................................................V

1.0 INTRODUCTION.................................................................................................1

1.1 BACKGROUND........................................................................................1

1.2 POTW CONCEPTUAL SITE MODEL ..................................................1

1.3 PRIMARY EXPOSURE ROUTES..........................................................2

2.0 CONCEPTUAL SITE MODEL VALIDATION.................................................4

2.1 OBJECTIVES .............................................................................................4

2.2 DETERMINATION OF NUMBER OF POTW SITES TO SAMPLE.4

3.0 CONCLUSIONS:...................................................................................................8

LIST OF FIGURES 

Figure 1 Generic Block Flow Diagram for POTWs Receiving 

Wastewater Containing D4 or D5

Figure 2 Generic Conceptual Site Model for Human and Ecological 

Receptors for POTWs Receiving Wastewater Containing D4

or D5
LIST OF ACRONYMS 

CSM Conceptual Site Model 

cVMS Cyclic volatile methyl siloxanes 

D4 Octamethylcyclotetrasiloxane 

D5 Decamethylcyclopentasiloxane 

DERR Department of Environmental Response and 

Revitalization 

EPA Environmental Protection Agency 

ERM Environmental Resources Management, Inc. 

MPF Manufacturer, Processor, and Formulator 

NIST National Institute of Standards and Technology 

POTW Publicly Owned Treatment Works 

WWTP Waste Water Treatment Plant 

SEHSC Silicones Environmental, Health and Safety Council 
EXECUTIVE SUMMARY 

Environmental Resources Management (ERM) was retained by the 

Silicones Environmental Health and Safety Council (SEHSC) to 

recommend the number of Publicly-Owned Treatment Works (POTWs) to 

sample for verification of the D4 and D5 generic Conceptual Site Model 

(CSM) for POTWs (the “POTW CSM”). The POTW CSM was developed 

by ERM and included in ERM’s D4 and D5 Conceptual Site Models and Mass 

Balance Report, dated January 2012. The January 2012 report included a 

generic block diagram for a typical POTW, with the assumption that it 

had only (1) primary and secondary treatment (activated sludge) and 

effluent chlorination for the liquid waste before discharge to a surface 

water body; and (2) blending and storage, anaerobic digestion, and 

storage for the sludge produced during primary and secondary treatment 

(“biosolids”), followed by beneficial use of the biosolids as a soil 

amendment. Advanced treatment POTWs were not modeled because 

advanced technologies are more likely to remove D4 and D5 more 

completely than conventional technologies. This selection is reasonable 

because (1) according to USEPA, approximately 50% of the POTWs 

utilized only secondary treatment technologies and served 41% of the 

population in the U.S. (USEPA (2008). Clean Watershed Needs Survey 2008, 

Report to Congress, EPA 832-R-10-002.); and (2) the absence of advanced 

treatment increases the likelihood that there could be some remaining D4

and D5 in the effluent and/or the sludge. 

To validate the exposure pathways depicted in the POTW CSM and 

provide additional information on the presence and concentration of D4

and D5 in the environment, environmental monitoring is being proposed 

by SEHSC member companies at select locations. In order to support the 

development of a detailed sampling plan, ERM has prepared this 

Recommendation of Number of Sites to Sample for Verification of the D4 and D5

Publicly-Owned Treatment Works Conceptual Site Model (the “Selection of 

Number of POTWs to Sample report”), which documents ERM’s 

procedures and recommendations. 

Conceptual site models are commonly developed to describe a specific 

site, but the POTW CSM represents a generic POTW. Therefore, ERM 

recommends that several types of POTWs be selected for sampling 

(including activated sludge [AS], oxidation ditch [OD], lagoon [LA], and 

trickling filter [TF] sites). As there is no standard statistical guidance on 

the number of sites that should be used to determine whether the CSM 

adequately represents POTWs in general, ERM used standard statistical 

analysis procedures developed for determination of a mean and standard 
deviation. Based on a standard statistical approach, we recommend 

sampling a total of five sites (including two AS, one OD, one LA, and one 

TF sites) to verify the key sources, receptors, and exposure/distribution 

pathways for D4 and D5 at POTWs and to augment the existing 

information on the presence of D4 and D5 in the environment. 

Data from these five sites will augment the large volume of data already 

available on the physical/chemical properties, fate and distribution of D4

and D5 in several countries, as well as the data to be obtained for the four 

industry sites which include manufacturer, processer, and formulator 

(MPF) plants with on-site wastewater treatment. The POTWs chosen for 

this study will serve a variety of population areas and have low effluent 

dilution factors. Other factors such as minimization of volatilization 

during treatment plant operation, will be considered during development 

of specific sampling plans. The intent is to select sites and develop 

sampling plans for these sites that maximize the occurrence and 

concentration of D4 and D5 in wastewater effluents and receiving waters 

and will therefore, represent worst- case scenarios. 
ERM 1 July 2012

that 

1.0 INTRODUCTION 

1.1 BACKGROUND 

Octamethylcyclotetrasiloxane (D4) and decamethylcyclopentasiloxane 

(D5) are chemical products from the broader family of cyclic siloxanes 

have a wide range of industrial and consumer applications in the United 

States and internationally. Both of these substances are manufactured, 

formulated and/or processed at a number of sites in the United States. 

The Silicones Environmental, Health and Safety Council (SEHSC) retained 

Environmental Resources Management, Inc. (ERM) to prepare the 

following work products: 

 A block flow diagram and conceptual site model (CSM) for 

publicly owned treatment works (POTWs) for use in the 

evaluation of emissions from POTWs receiving D4 and/or D5. 

 A strategy for validation of the exposure pathways described 

for D4 and D5 by the POTW CSM. 

A detailed description of the development of the POTW CSM is provided 

in the D4 and D5 Conceptual Site Models and Mass Balance Report (the “ERM 

CSM report”). As part of the strategy for validation of the POTW CSM, 

ERM prepared this Selection of Number of POTWs to Sample Report to 

describe the procedure used to determine the recommended number of 

POTWs that should be sampled in order to validate the 

exposure/distribution pathways described for D4 and D5 in the POTW 

CSM and provide additional information on the presence and 

concentration of D4 and D5 in the environment. 

1.2 POTW CONCEPTUAL SITE MODEL 

The POTW CSM, illustrated in Figure 1, provides a working hypothesis of 

the sources, receptors, and pathways of relevance for D4 and D5. This 

model represents processes typical of secondary treatment plants in the 

United States. As shown in the table below, activated sludge (AS) plants 

serve 79% of the US population and treat approximately 81% of the 

discharges to POTWs. Oxidation ditch (OD), lagoon (LA), and trickling 

filter (TF) plants combined serve approximately 19% of the US population 

and treat 17% of the wastewater discharges to POTWs. 
ERM 2 July 2012

Treatment Type* AS OD TF RBC LA P

Total flow in the US (%) 81 5 6 2 6 0

Total facilities in the US (%) 47 10 8 3 32 0

Population Served in the US (%) 79 6 7 2 6 0

*2004 US EPA Needs Data from ISTREEM

AS = activated sludge, OD = oxidation ditch, TF = trickling filter, RBC = rotating biological contactor, 

LA = lagoon, P = primary

In addition to AS plants, which were used to develop the POTW CSM, 

OD, TF, and LA plants will also be sampled to verify that the same 

fundamental concepts and pathways are relevant for these treatment 

types. Rotating Biological Contactors (RBC) and Primary (P) treatment 

plants are not recommended for sampling to verify the POTW CSM 

because they serve only approximately 2% of the population. 

1.3 PRIMARY EXPOSURE ROUTES 

The generic POTW CSM diagram for human and ecological receptors is 

shown in Figure 2. Exposure pathways for POTW workers were not 

included because in the U.S., these exposures are subject to regulation by 

the Occupational Safety and Health Administration. The processes and 

resulting pathways identified in the diagram may not occur at each of the 

POTWs that receive wastewater containing D4 and/or D5; the application 

of this diagram to any specific POTW is subject to verification as to the 

processes used. 

Based on the fate data and emissions mass balance of the CSM for D4 and 

D5 industrial uses, the pathways expected to be complete at POTWs are: 

 Inhalation exposure resulting from dispersion in air (this 

pathway applies only to human receptors, because ecological 

receptors are not typically evaluated for inhalation exposure 

risk); and 

 Exposures via sediment, including direct exposure for bottomdwelling biota and indirect exposure via the food chain to 

ecological receptors. 

However, in order to fully validate the model and provide additional 

information on the presence and concentration of D4 and D5 in the 

environment, we recommend to include air sampling at one site and 
ERM 3 July 2012

influent/effluent, biosolids, surface water, sediment, benthic organism, 

and marker fish at each site/associated receiving water. Since the 

composition of benthic communities and fish species in any receiving 

water is somewhat unique to each location, the specifics of their sampling 

would be developed during the preparation of sampling plans. 
ERM 4 July 2012

2.0 CONCEPTUAL SITE MODEL VALIDATION 

2.1 OBJECTIVES 

The CSM provides a hypothesis and description of applicable POTW 

exposure pathways and the transport and disposition of D4 and D5 along 

those pathways. Validation involves evaluation of data from a POTW 

which can be used to verify that the model compartments and pathways 

are appropriate representations of the system (in this case, sampling 

results from environmental media). The CSM can then be adjusted and 

refined accordingly. 

To verify that the POTW CSM is generally representative, ERM 

recommends that several additional POTWs be selected for sampling. 

There is no standard statistical guidance on the number of sites that 

should be used to determine whether the CSM is of general applicability. 

Therefore, ERM relied on a statistical procedure used to determine the 

appropriate number of samples to collect for calculation of mean values 

and standard deviations of the mean for pathways in the CMS. 

2.2 DETERMINATION OF NUMBER OF POTW SITES TO SAMPLE 

According to Rykiel (Rykiel, Jr., Edward J. Testing ecological models: the 

meaning of validation. Ecological Modelling. 1996. 90: 229-244) “a valid 

model is one whose scientific or conceptual content is acceptable for its 

purpose.” He notes that validation requires that the modeler specify the 

purpose of the model, the criteria the model must meet to be considered 

acceptable, and the context in which the model is intended to operate. As 

discussed earlier, the purpose and context of the model are to represent 

the flows and pathways of D4 and D5 in POTWs with secondary 

treatment. The model will be considered acceptable if monitoring data 

indicate that the primary pathways are represented in the model and that 

the model correctly indentifies the relative importance of the exposure 

pathways for D4 and D5. The sampling program developed to 

qualitatively validate the conceptual site model will concurrently provide 

quantitative values for the removal pathways and resultant environmental 

concentrations. 
ERM 5 July 2012

Validation of the CSM requires that mean concentrations be calculated for 

individual sources and pathways included in the CSM. The sample size 

required to estimate the mean concentrations will be influenced by the 

value selected for α (the risk of rejecting a true hypothesis, or Type I error) 

and the population standard deviation (σ). The following explanation of 

the required sample size for calculation of the mean was obtained from 

the National Institute of Standards and Technology (NIST)/SEMATECH eHandbook of Statistical Methods, 

http://www.itl.nist.gov/div898/handbook/index.htm, updated in April 

2012.

The basic equation to calculate the error associated with the mean is: 

  = zα/2 * (σ * √n) 

Where: 

  = difference between observed and true mean 

 zα/2 = critical value of the standard distribution curve 

 σ = standard deviation of the population 

 n = sample size 

The equation above can be rearranged as follows to obtain n: 

 n = [(zα/2 * σ)/ ]2

A restriction is that the standard deviation must be known. Lacking an 

exact value for the standard deviation requires some adjustment, such as 

using the best estimate from a previous experiment. 

It is usual to state the shift, , in units of the standard deviation, thereby 

simplifying the calculation. For a shift or error equal to one standard 

deviation the equation reduces to 

 n = [zα/2]2 ≈ 4 

for a 95% confidence interval (α = 0.05) and z = 1.96, which is the critical 

value from the normal distribution (z) for 1-α/2 = 0.975. 

Designation of the alpha levels can vary. Ecologists, by convention, use a 

probability level of 0.05 to test for statistical significance. However, there 

is no objective basis for this standard (Rykiel, 1996). According to the 

Ohio Environmental Protection Agency (EPA) Division of Environmental 
ERM 6 July 2012

Response and Revitalization (DERR) alpha levels 0.05-0.2 are 

recommended for ecological risk assessment. 

Following standard statistical and EPA convention, we used an alpha of 

0.05 for determination of the mean within one standard deviation. This 

results in a recommended sample size of 4. ERM recommends sampling 

two AS, one OD, one TF, and one LA. This would result in a total of five 

POTWs with at least one representative from each treatment type that 

serves ≥6% of the US population. The additional AS plant would be 

sampled because they occur most frequently and to provide a better set of 

data. The POTWs will be selected based on factors that maximize the 

occurrence and concentration of D4 and D5 in wastewater effluents and receiving 

waters. 

The data from the five POTWs sampled as part of this study will add to 

the already available global database of D4 and D5 environmental 

concentrations. As a result of previous efforts, there is a large amount of 

information available on the physical/chemical properties, fate, and 

removal of D4 and D5 including studies in the US, Canada, and Norway. 

In Oregon, 52 effluent sites were sampled and all sites were non-detect for 

D4 and D5 (Oregon DEQ SB737 Fact Sheet, 2011). Eleven waste water 

treatment plants (WWTP)were sampled in Canada in 2010. The WWTPs 

included different treatment types including lagoon, secondary activated 

sludge, and chemically assisted primary treatment. The detailed results 

of this study are reported in Wang et al. Concentrations of cyclic volatile 

methyl siloxanes (cVMS) in various environmental media from Southern 

Ontario and Southern Quebec were measured. Approximate removal 

efficiency of cVMS for all WWTPs was greater than 92% from wastewater, 

and mean removal efficiencies of D4 and D5 were 98%. Resultant D4 and 

D5 concentration ranges in effluent were <0.006–0.045 μg/L and <0.004–

1.56 μg/L, respectively. The different treatment types of WWTPs had little 

influence on the removal efficiency of cVMS between 10 and 25oC. 

Removal rates from lagoons were highly variable at temperatures ≤5°C, 

ranging from 25% to 99% at the 11 sites tested. [Wang, D., H. Steer, T. 

Young, T. Tait, Z. Williams, G. Pacepavicius, T. Ng, S. Smyth, L. Kinsman, 

E. Sverko, L. Svobda, S. Fazal and M. Alaee, 2010. Concentrations of cyclic 

volatile methyl siloxanes (cVMS) in various environmental media from Southern 

Ontario and Southern Quebec. Burlington, ON, Canada: Environment 

Canada, Water Science and Technology Directorate. December 16, 2010]. 

POTWs chosen for the monitoring program will represent those treatment 

types that are most prevalent in the US and serve the greatest percentage 

of the US population. However, based on these findings, little difference 
ERM 7 July 2012

is expected in removal efficiencies for the POTWs that will be sampled as 

part of this proposed study. 
ERM 8 July 2012

3.0 CONCLUSIONS: 

The goal of the POTW monitoring study is to validate the exposure pathways 

depicted in the POTW CSM and provide additional information on the presence 

and concentration of D4 and D5 in the environment. To accomplish this, 

ERM proposes collecting samples from a total of five POTWs. The five 

POTWs would include two AS, one OD, one TF, and one LA. The sites 

will be selected based on factors that maximize the occurrence and 

concentration of D4 and D5 in wastewater effluents and receiving waters 

and will therefore represent worst case scenarios. 

It is anticipated that a rigorous sampling protocol including sampling 

locations, parameters to analyze, analytical methods, sample type 

(composite or grab), etc., will be designed for each POTW before samples 

are collected. The intent is to select sites and develop sampling plans for 

these sites that allow for the validation of the CSM through assessment of 

the occurrence and concentrations of D4 and D5 in the proposed 

environmental media. 

The results from the POTW validation study will complement the data 

gathered for the four industry sites (including manufacturer, processer, 

and formulator plants) with on-site wastewater treatment in the US and 

will complement the data available from existing and on-going 

monitoring programs in the US and elsewhere.
 

Figure 1 
 
 

Figure 2 
 
ATTACHMENT 2 

 
 Page 1 of 4

Attachment 2 

Comments on EPA’s Proposed Approach for POTW Site Selection 

EPA Comment: “Charge: Build on the SEHSC proposal to develop a science-based, rational proposal 

for monitoring of Publicly Owned Treatment Works (POTW) sites which provides sufficient information 

and data on the presence and concentrations of D4 and D5 in the environment near POTWs, to support 

a national risk assessment.” 

Industry Comment: Extensive data already exists that characterizes the presence and concentrations 

of D4 and D5 in the environment near POTWs. Real world global monitoring data (Lake Pepin, MN, 

USA, Norway, Sweden, Canada and Japan) of D4 and D5 in sediment is available and most (exception 

is Japan) has been provided to EPA. In addition, recent monitoring results for D4 and D5 in surface 

sediments of Tokyo Bay, Japan are now becoming available (summary provided in Attachment 4). 

These data have been used to calibrate and validate environmental models that allow for prediction of 

environmental concentrations as well as conduct of a probabilistic risk assessment (Attachment 3; 

Woodburn, 2012). 

Industry Comment: This extensive data set already collected has also been used to conduct a 

probabilistic risk assessment to compare field exposure levels of D4 and D5 in sediment to toxicity 

trigger levels for these compounds as determined in laboratory chronic toxicity tests with benthic 

organisms (Woodburn 2012). This risk analysis indicates that existing D4 and D5 sediment residues 

pose virtually no quantifiable risk to benthic invertebrate species, as concentrations do not exceed 

interpolated, 5th centile chronic NOEC values. 

Industry Comment: Monitoring results from Tokyo Bay, Japan (summary provided in Attachment 4) 

demonstrate that concentrations of D4 and D5 in surface sediments of the receiving waters are greatest 

near the source of discharge and decrease to levels less than or equal to the detection limit with 

increasing distance from the source of discharge. Hence, probability based sampling at a single well 

selected worst-case study area would itself be sufficient to identify the range and distribution of 

concentrations that could potentially exist in surface sediments impacted by wastewater discharges. 

Probability based sampling provides precise estimates of mean concentration such that coefficients of 

variation (CV) are typically less than 10%. Consequently, probability based sampling at a few study 

areas may be used to derive precise estimates and confidence intervals for concentrations that could 

potentially exist in surface sediments impacted by wastewater discharges from different types of 

POTWs. Margin of Error (MoE) power calculations (Attachment 6) for n=5 locations having an 

estimated CV=10% indicate that the 95% confidence interval for the mean concentration would be 

±12% for the population of POTWs from which the 5 locations were selected. 

EPA Comment: “Monitoring Objective: A sampling strategy should collect monitoring data that scans 

a variety of POTWs that have attributes that could be used to characterize the “likely range” of siloxane 

environmental concentrations around POTWs. With these data, an understanding of how population 

size, receiving water body flow and other factors contribute to the environmental loading of siloxanes 

near POTWs would be developed.” 

Industry Comment: Extensive data already exists that characterizes the “likely range” of siloxane 

concentrations that would be expected around POTWs. Real world monitoring data (Lake Pepin, MN, 

USA, Norway, Sweden, Canada, and Japan) of D4 and D5 in sediment is available and has been 

provided to EPA that demonstrates this. In addition, recent work conducted in Tokyo Bay (Attachment 

4, Powell, 2012) supports that concentrations of D4 and D5 in surface sediments will be log-normally 
 Page 2 of 4

distributed over the study area, with concentrations decreasing with increasing distance from pointsource discharges at the head of the bay. Results from the systematic stratified design resulted in very 

precise estimates of mean concentrations of the cVMS materials in surface sediment of the study area 

in Tokyo Bay. Probability based sampling at a single well selected worst-case study area would itself 

be sufficient to identify the likely range and distribution of concentrations that could potentially exist in 

surface sediments impacted by wastewater discharges. Moreover, probability based sampling at a few 

study areas that includes a variety of POTWs may be used to derive precise estimates and confidence 

intervals for concentrations that could potentially exist for surface sediments impacted by wastewater 

discharges from different types of POTWs. 

 

Industry Comment: The behavior of volatile siloxanes during wastewater treatment can be 

reasonably predicted due to their characteristic physicochemical properties. A robust model such as 

SimpleTreat can be used for further in-depth analysis such as uncertainty analysis. This currently is in 

progress by the Industry in support of the POTW monitoring to be conducted under the Voluntary 

Product Stewardship Initiative (see March 1, 2012 submission). 

EPA Comment: “Approach: The major factors in site selection likely to affect the measured levels of 

siloxanes in the sediment at outfalls from POTWs outside of SEHSC control would be established. 

These factors would then be used as input to an optimization process to develop a monitoring program 

design. This optimization method, D-Optimal design, coupled with the relevant major factors 

established, would provide a scientific basis for a monitoring program design to understand how the 

various factors contribute to siloxane measured results without testing the entire set of possible 

permutations. Additional sampling considerations such as air monitoring and seasonal 

variability would be considered in the future, but do not impact site selection and are not 

included here.” 

 

Industry Comment: Industry agrees that additional sampling consideration such as air monitoring and 

seasonal variability do not impact site selection and need not be included for consideration at this time. 

EPA Comment: Above and Background on Proposed D-Optimal Design of Experiment 

“Background: The “Design of Experiment” (DOE) theory was developed during the early 

portion of the 20th century as a method of applying statistics before an experiment is conducted 

to maximize the benefit of the experiment while minimizing the number of samples. A 

particularly powerful approach applied the “D-Optimal” criterion and was coded into a 

FORTRAN computer algorithm by Mitchell (1974). This approach is available today through 

commercial software packages such as Design Expert (Stat-Ease, 2012). D-Optimal DOE has 

been widely used in agriculture, manufacturing, and the biomedical industry. D-Optimal DOE 

has been used in a few studies to design sampling experiments for environmental contaminants 

(e.g., Gribik et al., 1976). This is indeed an effective optimization technique with a demonstrated 

ability to minimize the number of required samples while generating a representative dataset.” 

Industry Comment: Industry acknowledges that a design of experiment (DOE) approach is an 

effective optimization technique and utilized this approach in the first submission to EPA (April, 2011). 

Further refinement of this approach taking into consideration the robust data available on the 

physicochemical properties of D4 and D5 is attached (Attachment 5; Kim, 2012). In order to employ a 

D-Optimal Design approach, a set of input parameters (or factors) is required which influence the 

output (i.e., environmental concentration of D4 and D5). Major factors are selected by the following 

three criteria (CR). 

 CR 1: Major factors should be selected based on proper understanding or evidence of the inputoutput relationship. 
 Page 3 of 4

 CR 2: The selected factors should be independent of each other. 

 CR 3: The quantity of the factors should be known prior to the monitoring program. 

To apply the criteria, it is critical to assess the physicochemical properties of D4 and D5 (i.e. highly 

volatile, practically insoluble in water, preferential partitioning to organic phases, and nonbiodegradable). If this understanding did not exist already then it may be appropriate to utilize a 

broader range of factors such as what was done in the EPA’s proposal that are “likely to affect the 

measured levels of siloxanes in the sediment at outfalls from POTWs”. Given the knowledge 

publically available, and provided to EPA, a more systematic evaluation of factors is warranted. 

EPA Comment: “Major Factors Relevant to the Environmental Presence of Siloxanes 

Below is a list of major factors related to site selection that EPA believes most strongly impact the 

siloxane levels in the sediment and water at POTW outfalls. 

Influent sources 

1. Population size served by the POTW (High/Medium/Low) 

This factor could provide information on how consumer or household use of siloxanes contributes to 

POTW siloxane loadings. 

POTW characteristics 

2. Treatment types (activated sludge, other secondary treatment types). Other secondary treatment 

types could include trickling filter, oxidation ditch or lagoons. 

A focus would be placed on POTWs that use secondary treatment because this would represent the 

vast majority of POTWs across the nation 

Tertiary treatment is not included because it is assumed there would be very low siloxane 

concentrations in effluent. 

3. High Total Suspended Solids (TSS) in effluent. 

Indications of high TSS in effluent from the POTW could be important as we know that siloxanes 

partition to solids. 

Receiving body characteristics 

4. Geography (North, South) 

Geography could be important as colder temperatures likely decrease the amount of siloxanes that 

partitions to the air and will increase the amount that remains in the water and that reaches the 

sediment. 

5. Receiving body flow (lake/ low flow stream/high flow river) 

Receiving body flow directly impacts the degree of dilution and probably the turbulence in the water. 

Both could impact the partitioning behavior of siloxanes. 

6. Organic content of receiving body (high/low) 

High organic content in the receiving body could increase the amount of siloxanes that partition 

to the sediment.” 
 Page 4 of 4

Industry Comment: 

We have applied three criteria to evaluate six major factors proposed by the USEPA. All the factors of 

the USPEA are incomplete to be used as inputs for a D-Optimal procedure. Instead, we proposed a 

new set of input factors as listed below. 

 Input variables 

1) Treatment type (3 levels: low/medium/high for TSS concentration and solid phase D4/D5 

concentration): for example, 

a. Low: activated sludge with bubble aeration (i.e., low TSS concentration and solid 

phase D4/D5 concentration) 

b. Medium: a trickling filter 

c. High: a lagoon without aeration (i.e., high TSS concentration and solid phase D4/D5 

concentration) 

2) Dilution factor (2 levels: low/high) 

 Input constant 

3) Predicted influent total concentration of D4/D5: only high concentration is needed. 

We can estimate effluent concentration from the same treatment type assuming the removal 

efficiency is same for the same type. 

Thus, all six combinations (3×2, the full factorial) are suggested according to the new proposal. The 

total number could be reduced by a D-Optimal procedure (possible to three). The monitoring 

program will measure actual D4/D5 concentration in water and TSS of effluent and receiving water, 

TSS concentration in effluent, and organic content in sediment of receiving water body. 
ATTACHMENT 3 

 
Page 1 of 24 

Attachment 3 

Woodburn, 2012 

Benthic Invertebrate Exposure and Chronic Toxicity Analysis for cVMS Materials – A 

Probabilistic Risk Assessment Approach 

Kent B. Woodburn and David E. Powell 

Dow Corning Corporation 

Midland, MI 48686 

Abstract 

The objective of this study was to use probabilistic risk assessment techniques to 

compare field exposure levels of cyclic volatile methylsiloxanes materials 

octamethylcyclotetrasiloxane (D4) and decamethylcyclopentasiloxane (D5) in sediment 

to toxicity trigger levels for these compounds determined in laboratory chronic toxicity 

tests with benthic organisms. The lipophilic nature of these cVMS materials (i.e., log 

Kow >6) suggests that sorption to sediment organic carbon is a likely removal 

mechanism of these compounds from water. The exposure data for D4 and D5 in 

sediment were sorted and the 95th centile exposure levels in sediment, both on a dry 

weight (dw) and organic carbon (OC) basis, were calculated. These concentrations 

were then compared to interpolated, highly sensitive 5th centile benthic sediment NOEC 

trigger concentrations, calculated from sorted distributions of chronic assays using a 

variety of benthic species. Neither material showed any overlap of sediment 95th centile 

levels to 5th centile NOEC values and safety factors separated the unlikely (i.e., 0.25%) 

events. Body burden NOEC values were calculated for D4 and D5 using field worstcase BSAF values of 20 and 5, respectively, to calculate chronic NOEC 5th centile levels 

on the basis of mass of chemical per lipid mass of organism. 

Again, no overlap between measured exposure 95th centile concentrations and 

interpolated, highly sensitive chronic NOEC values were observed for either compound. 

This risk analysis indicates that existing D4 and D5 sediment residues pose virtually no 

quantifiable risk to benthic invertebrate species, as concentrations do not exceed 

interpolated, 5th centile chronic NOEC values. Further research could explore the 

applicability of this relationship to other benthic species and also exposure the absence 

of apparent toxicological impact of D4 and D5 on benthic invertebrate organisms even at 

concentration levels exceeding their respective OC solubility values in sediment. 

Introduction 

Benchmarking concentrations versus toxicity threshold levels 

Natural and anthropogenic materials enter the environment on a regular basis, and it is 

frequently of interest to estimate the probability or likelihood of adverse effects of a 

chemical to wildlife organisms. The simplest approach to assessing the potential for 

environmental effects of a chemical is to compare a measure of exposure with some 

threshold for detrimental effects. On a screening basis, this can be done using the 

calculation of a simple hazard quotient (HQ), where a point estimate of the measured or 

predicted exposure concentration is divided by a toxicity reference value; generally the 

threshold or safe level is determined from a dose-response relationship in a chronic 

exposure: 
Page 2 of 24 

HQ = Exposure concentration/Effect concentration or chronic NOEC (1) 

The HQ method represents the initial tier of an assessment, meant only to rebut the 

presumption of potential adverse effects. If the HQ>1, the potential of risk cannot be 

rebutted nor quantified in terms of probability or likelihood. Since conservative 

assumptions apply to both exposure and toxicity endpoints in the HQ assessment, the 

method is inherently protective in nature, but not predictive as to the level of potential 

risk. The term “risk” implies an element of likelihood or probability, which cannot be 

calculated from such point estimates. A tiered risk assessment process has been 

proposed and endorsed by the US EPA (ECOFRAM, 1999), in which increasingly 

complex and resource-intensive levels of assessment are conducted. The lower tier 

assessments utilize conservative assumptions and estimates of parameters, along with 

possible safety factors. By design, these estimates are highly conservative and produce 

very protective HQ values. Higher tier, probabilistic risk assessment (PRA) methods 

allow the risk assessor to include stochastic properties of both exposure and response. 

The use of PRA expresses a continuum of potential exposure and effect and a range of 

certainty can be calculated for overlap, or lack thereof. The probabilistic method has 

been applied in numerous environmental risk assessments for North American systems 

(Giesy et al., 1999; Klaine et al. 1996; Solomon et al., 2000), as well as Europe (Hart, 

2001). This type of assessment has been used for several years to derive federal water 

quality criteria (Stephan et al., 1985), generally utilizing a 5th centile no-observed effect 

concentration (NOEC) from chronic toxicity studies as the target effect level. 

Body burden concentrations of chemicals are not a commonly-used endpoint in risk 

assessments for aquatic contaminants, as nearly all toxicity data for fish are expressed 

in terms of aquatic concentrations. However, organism body burdens potentially provide 

an exposure metric that may be more strongly correlated with effects (McCarty and 

Mackay, 1993). The correlation is most prevalent for chemicals that demonstrate 

bioaccumulation in fish and other biota to levels in greater than water concentrations. 

Research indicates that at naturally-occurring food/water concentration ratios, uptake of 

highly lipophilic chemicals (i.e., log KOW >6) from water into biota may be low compared 

to uptake via consumption of contaminated foodstuffs, with the importance of dietary 

uptake increasing with increasing Kow values (Thomann, 1989; Qiao et al., 2000). 

Modeling of field data from TMF studies in Lake Pepin, MN (Powell et al., 2008) on cyclic 

volatile methylsiloxanes (cVMS), such as decamethylcyclopentasiloxane (D5), revealed 

that food uptake accounted for greater than 90% of accumulated D5 residues in fish 

(HydroQual, 2009). 

Objective 

The objective of this study was to compare the field exposure levels of 

octamethylcyclotetrasiloxane (D4) and decamethylcyclopentasiloxane (D5) in sediment 

to toxicity trigger levels for these compounds determined in laboratory chronic toxicity 

tests with benthic organisms. The lipophilic nature of these cVMS materials suggests 

that sediment adsorption is a likely removal mechanism of these compounds from water 

and empirical evidence supports this concept (Norden, 2005; NILU 2007). Screening 

risk assessments on D4 (Environment Canada, 2008a) and D5 (Environment Canada, 

2008b) have been completed by Environment Canada, but risk quotients for sediment 

were not explicitly examined. Therefore, probabilistic comparisons of measured D4 and 

D5 sediment residues to sediment chronic toxicity NOEC values for benthic species may 

still prove useful for risk evaluation of each material. 
Page 3 of 24 

Materials and Methods 

Sediment Field Residues - D4:

For D4, data on sediment concentrations were taken from Norden (2005), NILU (2007), 

Boehmer and Gerhards (2003), Powell and Kozerski (2007), Powell (2012), and Wang et 

al. (2010); these data represent urban waterways, sediment downstream from municipal 

wastewater treatment plants (WWTPs), landfills, marine systems, and sediment from 

industrial WWTPs. The data come from sites in the United States, Canada, Norway, 

Iceland, Sweden, Germany, the UK, Denmark, Finland, and Japan. Table 1 presents 

the D4 sediment field data, both in terms of mass of D4 per g-dry weight (dw) sediment 

and mass of chemical per g-organic carbon (OC). The highest concentrations of D4 

appear to be associated with urban settings and industrial WWTPs, likely due to 

wastewater discharge of D4 present in personal care products and other applications. 

Some sediment samples contained no detectable residue of D4; in these cases, the limit 

of detection (LOD) is presented in parentheses. For samples in Table 1, such as the 

sediments taken from Lake Pepin, the measured concentrations of D4 in sediment were 

less than the method detection limit (MDL) but greater than the LOD; these low level D4 

sediment concentrations were estimated and the data presented in Table 1. A 

cumulative frequency distribution of all measured D4 sediment concentrations (ng/g-dw) 

is presented in Figure 1, using a log-normal distribution described by the presented 

linear regression model; if no detectable D4 was noted in a sediment sample, the data 

were not included in the sediment frequency distribution. The 95th centile exposure 

concentration (i.e., the concentration that encompasses 95% of the measured D4 

sediment dw residues) may be calculated form a linear regression analysis of the lognormal distribution; for D4 in sediment, the 95th centile field residue is approximately 117 

ng/g-dw. When the sediment residue samples have measured organic carbon levels, it 

is possible to produce a similar cumulative probability function for D4 sediment residues 

normalized to organic carbon content (ng/g-OC); these data are shown on Figure 2. For 

several of the sediment samples with measurable D4 residues (ng/g-dw), it was 

necessary to assume a sediment %OC level (i.e., 2.0%) to include these pertinent data 

in the D4 sediment residue OC distribution. As shown in Figure 2, the 95th centile 

sediment exposure concentration calculated for D4 from the log-normal linear regression 

model was 3850 ng/g-OC. The highest D4 sediment concentration (ng/g-dw) was 

observed by Powell and Kozeraki (2007) in Toronto harbor (Canada), with a single 

measured residue of 287 ng/g-dw or 13,667 ng/g-OC when normalized by the measured 

OC content of 2.1%. 

Sediment Field Residues – D5: 

For D5, the sediment residues examined in a probabilistic approach were taken from 

Norden (2005), NILU (2007), Powell et al. (2009), Powell (2010), Boehmer and Gerhards 

(2003), Powell and Kozerski (2007), Powell (2012) and Wang et al. (2010); these data 

represent urban waterways, sediment downstream from municipal wastewater treatment 

plants (WWTPs), landfills, marine systems, and sediment from industrial WWTPs. The 

data come from sites in the United States, Canada, Norway, Iceland, Sweden, Germany, 

the UK, Denmark, Finland, and Japan. Table 2 presents the D5 sediment field data, 

both in terms of mass of D5 per g-dw sediment and mass of chemical per g-OC; the 

highest D5 sediment residue was collected in a sediment sample taken from an 

industrial WWTP. Some sediment samples contained no detectable residue of D5; in 

these cases, the limit of detection (LOD) is presented in parentheses. A cumulative 

frequency distribution of the measured D5 sediment concentrations (ng/g-dw) is 

presented in Figure 3, using a log-normal distribution described by the presented linear 
Page 4 of 24 

regression model. The 95th centile exposure concentration is approximately 1330 ng/gdw. Many of the sediment samples with measurable D5 residues have measured %OC 

levels and for other samples it was necessary to assume a sediment %OC level (i.e., 

2.0%) to include these data in the D5 sediment residue OC distribution. As shown in 

Figure 4, the 95th centile sediment exposure concentration calculated for D5 from the 

log-normal linear regression model was 61,500 ng/g-OC, with the highest, outlying D5 

sediment residue taken in a sediment sample from an industrial WWTP. 

Chronic Toxicity Data with benthic organisms: D4 and D5 

In a best case scenario, probabilistic risk assessment involves a diverse range of 

species, in an attempt to simulate the taxanomic and functional diversity of aquatic 

ecosystems. The wide array of standardized pelagic test species (e.g., trout, bluegill, 

daphnia, etc.) is not replicated in the current freshwater sediment toxicity assays 

commonly used by OECD (Guidelines 218 and 225) and the US EPA (OPPTS 

850.1735). The arthropods Chironomus tentans and Chironomus riparius are commonly 

used in chronic sediment exposures (OECD guideline 218); the amphipod Hyalella 

azteca (EPA OPPTS 850.1735), and the oligochaete Lumbriculus variegatus (OECD 

guideline 225) may also be used for chronic sediment toxicity assays. 

The sediment toxicity of D4 has been evaluated in chronic, 28-day assays with 

Chironomus riparius (Krueger et al., 2008a) and Lumbriculus variegatus (Picard, 2009a), 

and in a 14-day subchronic exposure with Chironomus tentans (McNamara, 1995; Kent 

et al., 1994); the pertinent no-observed effect concentration (NOEC) results, both in 

terms of g/g-dw and g/g-OC, are presented in Table 3. The Chironomus tentans

study (McNamara, 1995; Kent et al., 1994) produced three NOEC values based on low, 

medium, and high organic carbon sediments and mean NOEC and standard deviation 

values were calculated from these data. Two separate Lumbriculus variegates studies 

were conducted with D4 and work by Krueger et al. (2009a) with artificial sediment and 

non-synchronized worms did not produce a NOEC value. A subsequent study by Picard 

(2009a) on natural sediment and synchronized worms (as per OECD guideline 225) 

resulted in a NOEC of 13 g/g-dw or 591 g/g-OC; these data were used in the D4 

benthic invertebrate toxicity distribution. The results of a BSAF bioaccumulation study 

with D4 and Lumbriculus variegates (Krueger et al., 2009b) are also noted in Table 3 as 

additional evidence pertaining to the chronic NOEC value observed with this species and 

sediment-spiked D4. The BSAF values observed for D4 in Lake Pepin invertebrates (7 

and 19; Powell et al., 2009) were also used to estimate a range of D4 benthic 

invertebrate NOEC body burden levels in terms of g/g-lipid; these data are also shown 

in Table 3, using an assumed worst-case BSAF for D4 of 20. In summary, the NOEC 

values for Chironomus tentans (mean value), Chironomus riparius, and Lumbriculus 

variegatus were used to develop chronic sediment toxicity distributions for D4. From 

these distributions, 5th centile NOECs (i.e., the estimated chronic NOEC values for the 

lowest theoretical 5th centile sensitive species) were extrapolated, consistent with 

Stephan et al. (1985), for comparison with D4 exposure data. 

The sediment toxicity of D5 has been evaluated in chronic, 28-day assays with Hyalella 

azteca (Picard, 2009b; Norwood et al., 2010) Chironomus riparius (Ransom and Putt, 

2009b; Krueger et al., 2008b), and Lumbriculus variegatus (Krueger et al., 2007); the 

pertinent no-observed effect concentration (NOEC) results, both in terms of g/g-dw and 

g/g-OC, are presented in Table 3. The Hyalella azteca testing produced three chronic 

NOEC values (Picard, 2009b; Norwood et al., 2010), Chironomus riparius studies 
Page 5 of 24 

(Ransom and Putt, 2009b; Krueger et al., 2008b) produced two NOEC values; mean 

NOEC and standard deviation values were calculated from these data. The results of a 

BSAF bioaccumulation study with D5 and Lumbriculus variegates (Krueger et al., 2009c) 

are also noted in Table 3 as additional evidence pertaining to the chronic NOEC value 

observed with this species and sediment-spiked D5. The BSAF values observed for D5 

in Lake Pepin invertebrates (range of 1 to 5; Powell et al., 2009) were also used to 

estimate a range of D5 benthic invertebrate NOEC body burden levels in terms of g/glipid; these data are also shown in Table 3, using an assumed worst-case BSAF value 

for D5 of 5. In summary, the NOEC values for Hyalella azteca, Chironomus riparius

(mean value), and Lumbriculus variegatus were used to develop chronic sediment 

toxicity distributions for D5. From these distributions, 5th centile NOECs were 

extrapolated, consistent with Stephan et al. (1985), for comparison with D5 exposure 

data. 

D4 and D5 biota residues – benthic invertebrate species

Benthic invertebrate biota concentrations of D4 and D5 on a lipid basis were taken from 

field data on Lake Pepin (Powell et al., 2009) and Inner and Outer Oslofjord (Powell, 

2010); the data are presented in Table 4. The data have been analyzed and sorted into 

separate cumulative probability distributions, which appear for D4 and D5 in Figures 5 

and 6, respectively. 

Powell et al. (2009) measured biota-sediment accumulation factors (BSAF) for D4 and 

D5 in Lake Pepin sediments and biota. The average BSAF values for benthic 

invertebrate species exposed to D4 ranged from 7 (mayfly nymphs) to 19 (midge larvae), 

while the average BSAF values for D5 ranged from 1 (mayfly nymphs) to 5 (midge 

larvae). These BSAF values were used in this analysis to estimate biota residues in 

benthic invertebrate species corresponding to D4 and D5 NOEC levels from sediment 

toxicology studies featuring measured sediment residues. The calculated D4 benthic 

invertebrate biota NOEC distribution is presented in Figure 5, where the D4 Lake Pepin 

BSAF value of ~20 was used to calculate the corresponding biota chronic NOEC levels. 

Similarly, the calculated D5 benthic invertebrate biota NOEC distribution is presented in 

Figure 6, where the D5 Lake Pepin BSAF value of ~5 was used to calculate the 

corresponding biota chronic NOEC levels. 

Results and Discussion 

Risk Assessment - D4:

Figure 1 presents the D4 sediment field data in a cumulative probability distribution, 

along with a comparison to a cumulative probability distribution of the D4 NOEC values 

from the chronic sediment toxicity assays. The respective distributions indicate that 

there is no overlap between the 95th centile concentration for D4 in sediment (70 ng/gdw) and the calculated 5th centile D4 chronic NOEC of 4100 ng/g-dw. In probability 

theory, if two events, A and B, are independent, the probability (P) that they both occur is 

equal to the product of the probabilities of the two individual events: 

 (2) 

Hence, the probability that a 95th centile exposure event will occur simultaneously with 

the presence of a sensitive 5th centile benthic invertebrate organism, is 0.25%; the 

likelihood this event will not occur is 99.75%. Even at this low probability event, a safety 
Page 6 of 24 

factor of ~60-fold exists separating the 95th centile D4 sediment exposure level and the 

5th centile D4 chronic NOEC value in sediment. 

If the D4 concentrations are expressed on an OC basis, as shown in Figure 2, the D4 

residues for both exposure and chronic sediment toxicity similarly indicates an absence 

of overlap of unlikely events. The 95th centile concentration for D4 in sediment (3850 

ng/g-OC) does not overlap with the calculated 5th centile D4 chronic NOEC of 85,700 

ng/g-OC; a safety factor of 20-fold exists between the two metrics. It is noteworthy that 

all measured laboratory NOEC values for D4 are either roughly approximate to or in 

excess of the calculated OC solubility concentration for D4 (i.e., water solubility * Koc), 

9.3 x 105 ng/g-OC. This suggests that physical deposition of D4 in sediment OC may 

not chronically affect benthic invertebrate organisms. These findings are also consistent 

with the recent work of Redman et al. (2012), who found the data on D4 consistent with 

a narcotic mode of action. 

Finally, the D4 chronic sediment NOEC values may be expressed on a body burden 

basis (ng/g-lipid) using the worst-case field BSAF value of ~20 (Powell et al., 2009) and 

compared to field biota concentrations of D4 in benthic organisms (Powell et al., 2009; 

Powell, 2010); the two cumulative probability distributions are presented in Figure 5. 

The graph demonstrates the lack of overlap between exposure and chronic NOEC 

values, and even a low probability co-occurrence event (0.25%) retains a safety factor of 

approximately 300-fold. 

In conclusion, the available sediment and biota field data on D4 indicate that the 

likelihood of concentrations of this material approaching the 5th centile chronic sediment 

NOEC for D4 with benthic invertebrate species is less than 0.25%, i.e., the probability of 

an absence of this event is >99.75%. This risk analysis indicates that current D4 

sediment residues pose little to no risk to benthic species. Further research would be 

useful to explore the applicability of this relationship to other benthic species and other 

likely sites for cVMS in sediment. 

Risk Assessment – D5:

Figure 3 presents the D5 sediment field data in a cumulative probability distribution, 

along with a comparison to a cumulative probability distribution of the D5 NOEC values 

from the chronic sediment toxicity assays. The respective distributions indicate that 

there is no overlap between the 95th centile concentration for D5 in sediment (1330 ng/gdw) and the calculated 5th centile D5 chronic NOEC of 8360 ng/g-dw. The probability 

that a 95th centile exposure event will occur simultaneously with the presence of a 5th

centile sensitive benthic invertebrate organism is low (0.25%), and a safety factor of ~6 

exists separating these low probability events. 

If the D5 concentrations are expressed on an OC basis, as shown in Figure 4, the D5 

residues for both exposure and chronic sediment toxicity similarly indicates an absence 

of overlap of unlikely events. The 95th centile concentration for D5 in sediment (61,500 

ng/g-OC) does not overlap with the calculated 5th centile D5 chronic NOEC of 380,000 

ng/g-OC; a safety factor of 6-fold separates these two unlikely co-events. It is 

noteworthy that all measured laboratory NOEC values for D5 are either roughly 

approximate to or in excess of the calculated OC solubility concentration for D5 (i.e., 

water solubility * Koc), 2.5 x 106 ng/g-OC. This suggests that physical deposition of D5 

in sediment OC may not affect benthic invertebrate organisms. These findings are also 
Page 7 of 24 

consistent with the recent work of Redman et al. (2012), who found the data on D5 

consistent with a narcotic mode of action. 

A final comparison of the D5 chronic sediment NOEC values may be expressed on a 

body burden basis (ng/g-lipid) using the worst-case field BSAF value of ~5 (Powell et al., 

2009) and compared to field biota concentrations of D5 in benthic organisms (Powell et 

al., 2009; Powell, 2010); the two cumulative probability distributions are presented in 

Figure 6. The graph demonstrates the lack of overlap between exposure and chronic 

NOEC values, and even a low probability co-occurrence event (0.25%) retains a safety 

factor of approximately 3-fold. 

Conclusions 

In conclusion, the cVMS materials D4 and D5 are highly lipophilic (i.e., log Kow >6) and 

are therefore will predominantly reside in sediment when exposed to natural aquatic 

systems. The likelihood of sediment environmental exposure levels of D4 and D5 to 

reach chronic NOEC values with benthic invertebrate species may be assessed using 

probabilistic risk assessment techniques. For both compounds, there is an absence of 

overlap of sediment exposure concentrations (i.e., 95th centile exposure levels) with an 

interpolated, highly sensitive 5th centile benthic sediment NOEC trigger level, both with 

dry weight and organic carbon adjusted sediment levels. Field worst-case BSAF values 

of 20 and 5 were used for D4 and D5, respectively, for comparison of field collected 

benthic invertebrate body burden concentrations with calculated benthic chronic NOEC 

body burden concentrations, again using an interpolated, highly sensitive 5th centile 

NOEC trigger level for comparison; no overlap was calculated for either D4 or D5. This 

risk analysis indicates that existing D4 and D5 sediment residues pose virtually no 

quantifiable risk to benthic invertebrate species. Further research could explore the 

applicability of this relationship to other benthic species and also exposure the absence 

of apparent toxicological impact of D4 and D5 on benthic invertebrate organisms even at 

concentration levels exceeding their respective OC solubility values in sediment. 
Page 8 of 24 

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R. Solomon. 1996. An ecological risk assessment for the use of the biocide, 
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dibromonitrilopropionamide (DBNPA) in industrial cooling systems. Environ. Toxicol. 

Chem. 15:21-30. 

Krueger HO; Thomas ST; Kendall TZ, and DrottarK. 2007. D5: A prolonged sediment 

toxicity test with Lumbriculus variegates using spiked sediment. . Unpublished report of 

Dow Corning #2007-I0000-57181, performed for CES. 

Krueger HO; Thomas ST; Kendall TZ. 2008a. D4: A prolonged sediment toxicity test 

with Chironomus riparius using spiked sediment. Unpublished report of Dow Corning 

#2008-I0000-59031, performed for SEHSC. 

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with Chironomus riparius using spiked sediment. Unpublished report of Dow Corning 

#2008-I0000-59030, performed for SEHSC. 

Krueger HO; Thomas ST; Kendall TZ. 2009a. Octamethylcyclotetrasiloxane (D4): A 

prolonged sediment toxicity test with Lumbriculus variegatus Using spiked artificial 

sediment. Unpublished report of Dow Corning #2009-I0000-60927, performed for CES. 

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bioaccumulation test with Lumbriculus variegatus using spiked sediment. Unpublished 

report of Dow Corning #2009-I0000-60372, performed for CES. 

Krueger HO; Thomas ST; Kendall TZ. 2009c. Octamethylcyclotetrasiloxane (D5): A 

bioaccumulation test with Lumbriculus variegatus using spiked sediment. Unpublished 

report of Dow Corning #2009-I0000-60373, performed for CES. 

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assessment. Environ. Sci. Technol. 27: 1719-1728. 

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Oslofjord. Rapport No. 986/2007. 

Norden. 2005. Siloxanes in the Nordic Environment (PDF Format, 1.6MB). TemaNord 

2005:593. Nordic Council of Ministers, Copenhagen. 

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Bioaccumulation and toxicity to the benthic invertebrate. Environment Canada. 

Available at: http://www.sehsc.com/presentations.asp 

Pickard C. 2009a. D4-sediment-water Lumbriculus toxicity test using spiked natural 

sediment, following OECD Guideline 225. Unpublished report of Dow Corning #2009-

I0000-61113, performed for CES. 

Pickard C. 2009b. 28-day toxicity test exposing freshwater amphipods (Hyalella azteca) 

to D5 applied to sediment under static-renewal conditions following OPPTS Draft 
Page 10 of 24 

Guideline 850.1735. Unpublished report of Dow Corning #2009-I0000-60662, performed 

for CES. 

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#2009-I0000-60886. 

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(cVMS) Materials in a Temperate Freshwater Lake. Dow Corning Corporation, HES 

Study No. 10771-108. 

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(cVMS) materials in aquatic marine food webs of the Inner and Outer Oslofjord, Norway. 

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dietary uptake of hydrophobic chemicals to the body burden in juvenile rainbow trout. 

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report of Dow Corning #2005-I0000-54997, performed for SEHSC. 

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Page 12 of 24 

Table 1. Collected field residue data on D4 in sediment. 

Sediment D4 D4

Source Country Location Site %OC (dw) (ng/g‐dw) (ng/g‐OC)

Powell et al. 2009 USA L. Pepin, MN I.1 3.26% 1.5* 46

Powell et al. 2009 USA L. Pepin, MN I.2 3.31% 1.2 36

Powell et al. 2009 USA L. Pepin, MN I.3 3.22% 1.1 34

Powell et al. 2009 USA L. Pepin, MN I.4 3.07% 1.1 36

Powell et al. 2009 USA L. Pepin, MN I.5 2.89% 1.3 45

Powell et al. 2009 USA L. Pepin, MN II.1 3.43% 1.5 44

Powell et al. 2009 USA L. Pepin, MN II.2 3.57% 1.4 39

Powell et al. 2009 USA L. Pepin, MN II.3 3.50% 1.5 43

Powell et al. 2009 USA L. Pepin, MN II.4 3.41% 1.2 35

Powell et al. 2009 USA L. Pepin, MN II.5 2.50% 1 40

Powell et al. 2009 USA L. Pepin, MN III.1 3.73% 1.7 46

Powell et al. 2009 USA L. Pepin, MN III.2 3.67% 1.7 46

Powell et al. 2009 USA L. Pepin, MN III.3 3.61% 1.5 42

Powell et al. 2009 USA L. Pepin, MN III.4 3.73% 1.7 46

Powell et al. 2009 USA L. Pepin, MN III.5 3.74% 1.6 43

Powell et al. 2009 USA L. Pepin, MN IV.1 2.93% 1.5 51

Powell et al. 2009 USA L. Pepin, MN IV.2 3.91% 1.9 49

Powell et al. 2009 USA L. Pepin, MN IV.3 3.99% 1.8 45

Powell et al. 2009 USA L. Pepin, MN IV.4 4.17% 2.3 55

Powell et al. 2009 USA L. Pepin, MN IV.5 2.89% 1.4 48

Powell et al. 2009 USA L. Pepin, MN V.1 4.22% 2.0 47

Powell et al. 2009 USA L. Pepin, MN V.2 4.47% 2.2 49

Powell et al. 2009 USA L. Pepin, MN V.3 4.30% 2.1 49

Powell et al. 2009 USA L. Pepin, MN V.4 4.26% 2.3 54

Powell et al. 2009 USA L. Pepin, MN V.5 4.22% 2.2 52

Schlabach et al. 2007 Norway Inner Oslofjord Lysaker 2 <31

Schlabach et al. 2007 Norway Inner Oslofjord Lysaker 1 <33

Schlabach et al. 2007 Norway Inner Oslofjord Oslofj A1 <24

Schlabach et al. 2007 Norway Inner Oslofjord Oslofj A2 <23

Schlabach et al. 2007 Norway Inner Oslofjord Bekkelagsbassenget BB14 <4

Schlabach et al. 2007 Norway Inner Oslofjord Bekkelagsbassenget BB5 <38

Powell (2010) Norway Inner Oslofjord Assume 2% 86 4300

Powell (2010) Norway Inner Oslofjord Assume 2% 98 4900

Powell (2010) Norway Outer Oslofjord Assume 2% 45 2250

Powell (2010) Norway Outer Oslofjord Assume 2% 1 50

Bakke et al. (2008) Norway Barents Sea (N=1) Assume 2% 40 2000

Bakke et al. (2008) Norway Barents Sea (N=10) <MDL

Evenset et al. (2009) Norway Svalbard Liefdefjorden, N=2 <4

Evenset et al. (2009) Norway Svalbard Kongsfjorden, N=2 <3.3

Norden, 2005 Denmark Coast area Kattegat <3

Norden, 2005 Denmark Oresund, Lynetten <5

Norden, 2005 Denmark Roskiide, coast area Assume 2% 84 4200

Norden, 2005 Faroe Islands Kaldakfjordur <11

Norden, 2005 Finland Helsinki, vakai (old city bay) <20

Norden, 2005 Finland Espco coastal sea <20

Norden, 2005 Iceland Sediment <4

Norden, 2005 Iceland Sediment <3

Norden, 2005 Iceland Sediment <10

Norden, 2005 Iceland Sediment <7

Norden, 2005 Norway Bergsjoen <60

Norden, 2005 Norway Bergsjoen <65

Norden, 2005 Norway Rogden <50

Norden, 2005 Norway Rogden <50

Norden, 2005 Norway Vrengansundet <10

Norden, 2005 Norway Leangbukta <20

Norden, 2005 Norway Brodrene Sunde Verft <11

Norden, 2005 Sweden Nissan <2

Norden, 2005 Sweden Nissan <2

Norden, 2005 Sweden Nissan <3

Norden, 2005 Sweden Landsorfsdjupet 0‐2 cm <30

Norden, 2005 Sweden Goffandsdjupet 0‐2 cm <30

Norden, 2005 Sweden Riddarfjarden <9

Norden, 2005 Sweden Essingen <13
Page 13 of 24 

Table 1 (cont). Collected field residue data on D4 in sediment. 

Sediment D4 D4

Source Country Location Site %OC (dw) (ng/g‐dw) (ng/g‐OC)

Powell and Kozerski, 2007 Canada Lake Ontario Kingston Basin (surface) 2.4% <5.8

Powell and Kozerski, 2007 Canada Lake Ontario Niagara basin (surface) 4.6% <5.8

Powell and Kozerski, 2007 Canada Lake Ontario Rochester basin A (surface) 4.4% <5.8

Powell and Kozerski, 2007 Canada Lake Ontario Rochester basin G (surface) 4.4% <5.8

Powell and Kozerski, 2007 Canada Lake Ontario Missasauga basin (surface) 5.1% <5.8

Powell and Kozerski, 2007 Canada Lake Ontario Toronto Harbor July 2006 (surface) 0.02

287 (N=1),

<LOD (N=5) 13667

Powell (2012) Japan Tokyo Bay Tokyo Bay A‐4 3.21 7.17 224

Powell (2012) Japan Tokyo Bay Tokyo Bay A‐5 3.56 11.34 318

Powell (2012) Japan Tokyo Bay Tokyo Bay A‐6 3.55 7.26 205

Powell (2012) Japan Tokyo Bay Tokyo Bay A‐7 2.94 4.25 144

Powell (2012) Japan Tokyo Bay Tokyo Bay B‐4 3.83 6.39 167

Powell (2012) Japan Tokyo Bay Tokyo Bay B‐5 4.05 8.86 219

Powell (2012) Japan Tokyo Bay Tokyo Bay B‐6 3.91 17.45 446

Powell (2012) Japan Tokyo Bay Tokyo Bay B‐7 3.78 25.63 678

Powell (2012) Japan Tokyo Bay Tokyo Bay C‐4 3.46 2.2 64

Powell (2012) Japan Tokyo Bay Tokyo Bay C‐5 3.52 0.94 27

Powell (2012) Japan Tokyo Bay Tokyo Bay C‐6 3.36 1.1 33

Powell (2012) Japan Tokyo Bay Tokyo Bay D‐2 1.66 0.45 27

Powell (2012) Japan Tokyo Bay Tokyo Bay D‐3 3.32 2.2 66

Powell (2012) Japan Tokyo Bay Tokyo Bay D‐4 3.43 0.8 23

Powell (2012) Japan Tokyo Bay Tokyo Bay E‐2 0.42 0.43 102

Powell (2012) Japan Tokyo Bay Tokyo Bay E‐3 0.59 0.82 140

Powell (2012) Japan Tokyo Bay Tokyo Bay E‐4 0.56 0.23 41

Powell (2012) Japan Tokyo Bay Tokyo Bay F‐1 1.43 0.96 67

Powell (2012) Japan Tokyo Bay Tokyo Bay F‐2 0.32 0.3 93

Powell (2012) Japan Tokyo Bay Tokyo Bay F‐3 0.24 0.15 64

Wang et al. (2010) Canada Site 1 Municipal WWTP Sediment Measured 49.1 3517

Wang et al. (2010) Canada Site 2 Municipal WWTP Sediment Measured 4.7 131

Wang et al. (2010) Canada Site 3 Municipal WWTP Sediment Measured 10.9 323

Wang et al. (2010) Canada Site 4 Municipal WWTP Sediment Measured 15 381

Wang et al. (2010) Canada Site 5 Municipal WWTP Sediment Measured 15 394

Wang et al. (2010) Canada Site 7 Municipal WWTP Sediment Measured 29.2 1518

Wang et al. (2010) Canada Site 8 Industrial WWTP Sediment Measured 14.9 5456

Wang et al. (2010) Canada Site 9 Municipal WWTP Sediment Measured 45.2 3865

Wang et al. (2010) Canada Site 10 Municipal WWTP Sediment Measured 11.7 258

Wang et al. (2010) Canada Site 11 Municipal WWTP Sediment Measured 36.9 2641

* In Lake Pepin, values are less than MDL (~2.3 ng/g‐dw) but greater than LOD, so estimated measured values are reported.
Page 14 of 24 

Table 2. Collected field residue levels for D5 in sediment. 

Sediment D5 residues D5 residues

Source Country Location Site %OC (dw) (ng/g-dw)* (ng/g-OC)

Powell et al. 2009 USA L. Pepin I.1 3.26% 132 4034

Powell et al. 2009 USA L. Pepin I.2 3.31% 120 3630

Powell et al. 2009 USA L. Pepin I.3 3.22% 117 3625

Powell et al. 2009 USA L. Pepin I.4 3.07% 108 3519

Powell et al. 2009 USA L. Pepin I.5 2.89% 89 3078

Powell et al. 2009 USA L. Pepin II.1 3.43% 145 4232

Powell et al. 2009 USA L. Pepin II.2 3.57% 121 3376

Powell et al. 2009 USA L. Pepin II.3 3.50% 119 3408

Powell et al. 2009 USA L. Pepin II.4 3.41% 96 2814

Powell et al. 2009 USA L. Pepin II.5 2.50% 53 2116

Powell et al. 2009 USA L. Pepin III.1 3.73% 126 3379

Powell et al. 2009 USA L. Pepin III.2 3.67% 125 3396

Powell et al. 2009 USA L. Pepin III.3 3.61% 134 3709

Powell et al. 2009 USA L. Pepin III.4 3.73% 145 3899

Powell et al. 2009 USA L. Pepin III.5 3.74% 122 3253

Powell et al. 2009 USA L. Pepin IV.1 2.93% 72 2473

Powell et al. 2009 USA L. Pepin IV.2 3.91% 146 3734

Powell et al. 2009 USA L. Pepin IV.3 3.99% 143 3586

Powell et al. 2009 USA L. Pepin IV.4 4.17% 153 3679

Powell et al. 2009 USA L. Pepin IV.5 2.89% 69 2388

Powell et al. 2009 USA L. Pepin V.1 4.22% 126 2989

Powell et al. 2009 USA L. Pepin V.2 4.47% 139 3099

Powell et al. 2009 USA L. Pepin V.3 4.30% 138 3213

Powell et al. 2009 USA L. Pepin V.4 4.26% 124 2913

Powell et al. 2009 USA L. Pepin V.5 4.22% 112 2664

Powell (2010) Norway Inner Oslofjord 2.84% 319 11239

Powell (2010) Norway Inner Oslofjord 2.78% 285 10245

Powell (2010) Norway Inner Oslofjord 2.52% 352 13952

Powell (2010) Norway Inner Oslofjord 2.51% 255 10147

Powell (2010) Norway Inner Oslofjord 2.69% 524 19494

Powell (2010) Norway Inner Oslofjord 2.49% 460 18462

Powell (2010) Norway Inner Oslofjord 2.81% 312 11103

Powell (2010) Norway Inner Oslofjord 2.94% 270 9170

Powell (2010) Norway Outer Oslofjord Assume 2% 525 26250

Powell (2010) Norway Outer Oslofjord Assume 2% 394 19700

CES, 2003 Germany

Rhine river, Wiesbaden, 

km 523 D5 <3.0 ng/g-dw*

CES, 2003 Germany

Rhine river, Koblenz, km 

603 D5 <3.0 ng/g-dw

CES, 2003 Germany

Rhine river, Leverkusen, 

km 712 D5 <3.0 ng/g-dw

CES, 2003 Germany

Rhine river, Emmerich, 

km 874 D5 <3.0 ng/g-dw

CES, 2003 Germany

Rhine river, Hollands 

Diep, km 1306 D5 <3.0 ng/g-dw

CES, 2003 UK, marine

Las St Abbs Mid 5 

Surface D5 <3.0 ng/g-dw

CES, 2003 UK, marine D5 <3.0 ng/g-dw

CES, 2003 UK, marine D5 <3.0 ng/g-dw

CES, 2003 UK, marine D5 <3.0 ng/g-dw

CES, 2003 UK, marine D5 <3.0 ng/g-dw

CES, 2003 UK, marine D5 <3.0 ng/g-dw

CES, 2003 UK, marine D5 <3.0 ng/g-dw

CES, 2003 UK, marine D5 <3.0 ng/g-dw

CES, 2003 UK, marine D5 <3.0 ng/g-dw

CES, 2003 Germany Rhine river, Koln, km 672 Assume 2% 6 300

CES, 2003 Germany, FW

Rhine river, Karlsruhe , 

km 377 Assume 2% 12 600

CES, 2003 Germany

Hall Dike Creek, 3.5 km 

downstream from STP Assume 2% 36 1815

CES, 2003 UK, marine River Mersey Assume 2% 53 2650

CES, 2003 Germany

Rhine river, Krefeld, km 

761 Assume 2% 91 4550

CES, 2003 UK, marine Cardiff Bay Assume 2% 228 11400
Page 15 of 24 

Table 2 (cont.). Collected field residue data on D5 in sediment. 

Sediment D5 residues D5 residues

Source Country Location Site %TOC (dw) (ng/g-dw)* (ng/g-OC)

Schlabach et al. 2007 Norway Inner Oslofjord Lysaker 2 Assume 2% 93 4650

Schlabach et al. 2007 Norway Inner Oslofjord Lysaker 1 Assume 2% 200 10000

Schlabach et al. 2007 Norway Inner Oslofjord Oslofj A1 Assume 2% 250 12500

Schlabach et al. 2007 Norway Inner Oslofjord Oslofj A2 Assume 2% 280 14000

Schlabach et al. 2007 Norway Inner Oslofjord Bekkelagsbassenget BB14 Assume 2% 690 34500

Schlabach et al. 2007 Norway Inner Oslofjord Bekkelagsbassenget BB5 Assume 2% 920 46000

Norden, 2005 Faroe IslanKaldakfjordur D5 <5 ng/g-dw

Norden, 2005 Sweden Nissan D5 <1 ng/g-dw

Norden, 2005 Sweden Nissan D5 <1 ng/g-dw

Norden, 2005 Denmark Coast area Kattegat D5 <2 ng/g-dw

Norden, 2005 Denmark Oresund, Lynetten D5 <3 ng/g-dw

Norden, 2005 Sweden Nissan Assume 2% 1.8 90

Norden, 2005 Norway Vrengansundet D5 <5 ng/g-dw

Norden, 2005 Sweden Goffandsdjupet 0-2 cm D5 <10 ng/g-dw

Norden, 2005 Iceland Sediment Assume 2% 7.4 370

Norden, 2005 Iceland Sediment Assume 2% 7.6 380

Norden, 2005 Sweden Landsorfsdjupet 0-2 cm D5 <20 ng/g-dw

Norden, 2005 Norway Leangbukta Assume 2% 12 600

Norden, 2005 Norway Bergsjoen D5 <30 ng/g-dw

Norden, 2005 Norway Bergsjoen D5 <30 ng/g-dw

Norden, 2005 Norway Rogden D5 <30 ng/g-dw

Norden, 2005 Norway Rogden D5 <30 ng/g-dw

Norden, 2005 Finland Espco coastal sea Assume 2% 19 950

Norden, 2005 Iceland Sediment Assume 2% 19 950

Norden, 2005 Iceland Sediment Assume 2% 39 1950

Norden, 2005 Finland Helsinki, vakai (old city bay) Assume 2% 58 2900

Norden, 2005 Sweden Riddarfjarden Assume 2% 77 3850

Norden, 2005 Norway Brodrene Sunde Verft Assume 2% 96 4800

Norden, 2005 Sweden Essingen Assume 2% 130 6500

Norden, 2005 Denmark Roskiide, coast area Assume 2% 2000 100000

Wang et al. (2010) Canada Site 1 Municipal WWTP Sediment Measured 905.7 65560

Wang et al. (2010) Canada Site 2 Municipal WWTP Sediment Measured 22.5 630

Wang et al. (2010) Canada Site 3 Municipal WWTP Sediment Measured 63.1 1869

Wang et al. (2010) Canada Site 4 Municipal WWTP Sediment Measured 151.1 4676

Wang et al. (2010) Canada Site 5 Municipal WWTP Sediment Measured 43.9 559

Wang et al. (2010) Canada Site 7 Municipal WWTP Sediment Measured 1110.7 18035

Wang et al. (2010) Canada Site 8 Industrial WWTP Sediment Measured 5836 2184019

Wang et al. (2010) Canada Site 9 Municipal WWTP Sediment Measured 804 67474

Wang et al. (2010) Canada Site 10 Municipal WWTP Sediment Measured 70.8 1510

Wang et al. (2010) Canada Site 11 Municipal WWTP Sediment Measured 1556 119294
Page 16 of 24 

Table 2 (cont.). Collected field residue data on D5 in sediment. 

Sediment D5 residues D5 residues

Source Country Location Site %OC (dw) (ng/g-dw)* (ng/g-OC)

Powell (2012) Japan Tokyo Bay Tokyo Bay A-4 3.21 415.09 12941

Powell (2012) Japan Tokyo Bay Tokyo Bay A-5 3.56 392.71 11023

Powell (2012) Japan Tokyo Bay Tokyo Bay A-6 3.55 310.48 8750

Powell (2012) Japan Tokyo Bay Tokyo Bay A-7 2.94 212.42 7222

Powell (2012) Japan Tokyo Bay Tokyo Bay B-4 3.83 251.88 6569

Powell (2012) Japan Tokyo Bay Tokyo Bay B-5 4.05 261.60 6458

Powell (2012) Japan Tokyo Bay Tokyo Bay B-6 3.91 259.57 6630

Powell (2012) Japan Tokyo Bay Tokyo Bay B-7 3.78 277.31 7333

Powell (2012) Japan Tokyo Bay Tokyo Bay C-4 3.46 186.27 5377

Powell (2012) Japan Tokyo Bay Tokyo Bay C-5 3.52 161.17 4583

Powell (2012) Japan Tokyo Bay Tokyo Bay C-6 3.36 151.01 4500

Powell (2012) Japan Tokyo Bay Tokyo Bay D-2 1.66 22.25 1338

Powell (2012) Japan Tokyo Bay Tokyo Bay D-3 3.32 116.13 3495

Powell (2012) Japan Tokyo Bay Tokyo Bay D-4 3.43 99.01 2885

Powell (2012) Japan Tokyo Bay Tokyo Bay E-2 0.42 14.53 3448

Powell (2012) Japan Tokyo Bay Tokyo Bay E-3 0.59 23.05 3939

Powell (2012) Japan Tokyo Bay Tokyo Bay E-4 0.56 13.65 2436

Powell (2012) Japan Tokyo Bay Tokyo Bay F-1 1.43 46.90 3289

Powell (2012) Japan Tokyo Bay Tokyo Bay F-2 0.32 7.00 2167

Powell (2012) Japan Tokyo Bay Tokyo Bay F-3 0.24 6.27 2667

Powell and Kozerski, 2007 Canada Lake Ontario Kingston Basin (surface) 2.4% 7.90 329

Powell and Kozerski, 2007 Canada Lake Ontario Niagara basin (surface) 4.6% 13.70 298

Powell and Kozerski, 2007 Canada Lake Ontario Rochester basin A (surface) 4.4% 25.00 568

Powell and Kozerski, 2007 Canada Lake Ontario Rochester basin G (surface) 4.4% 16.20 368

Powell and Kozerski, 2007 Canada Lake Ontario Missasauga basin (surface) 5.1% 4.00 78

Powell and Kozerski, 2007 Canada Lake Ontario Toronto Harbor July 2006 (su 2.1% 790.10 37624

*D5 concentrations <method detection limit, which are shown 
Page 17 of 24 

Table 3. Chronic toxicity information on D4 and D5 with benthic invertebrate species in standardized testin

BSAF = 2

cVMS Organism

OECD 

Guideline

Exposure 

Duration (d)

Acute or 

Chronic

Most 

sensitive 

endpoint

Spiked 

sediment? Conditions? %OC

NOEC 

(μg/g-dw)

NOEC 

(g/g-OC)

NOEC 

(g/g- lipid

D4 Chironomus tentans 218 14 Acute Survival >4.0 54 1350 2.70E+04 

Chironomus tentans 218 14 Acute Survival 1.5-3 120 8000 1.60E+05 Chironomus tentans 218 14 Acute Survival <1 65 6500 1.30E+05 

Mean = 80 5283 1.06E+05

STDEV = 35 3488 6.98E+04

Chironomus riparius 28 Chronic Emerg. RatioArtificial sediment 4.1% 44 1073 2.15E+04 Lumbriculus variegatus 225 28 Chronic Surv/Repro

Artificial sed, nonsync worms 2.4 <0.73 

Lumbriculus variegatus 225 28 Chronic Surv/Repro

Natural sed, sync 

worms 2.2 13 591 1.18E+04 

Lumbriculus variegatus BSAF study 28 BSAF

>4 

(highest 

dose) 

BSAF= 5

D5 Hyalella azteca

OPPTS 

850.1735 28 Chronic Growth Yes Natural sediment 4.8 130 2708 13542 

Hyalella azteca 28 Chronic Growth Yes

Natural - Lake 

Erie 0.5 62 12400 62000 

Hyalella azteca 28 Chronic Growth Yes

Natural - Lake 

Restoule 11.0 641 5827 29136 

Mean = 278 6979 34893

STDEV = 316 4947 24737

Chironomus riparius OECD 218 28 Chronic Male develop. Yes

Artificial sed, with 

food added daily 

to water 2.0 69 3450 17250 

Chironomus riparius OECD 218 28 Chronic Develop. Rate Yes

Artificial, 28-d 

food ration spiked 

to sediment at 

test initiation 3.2 70 2188 10938 

Mean = 70 2819 14094

STDEV = 1 893 4464

Lumbriculus variegatus OECD 225 28 Chronic Surv/Repro Yes Artificial sediment 3.7% 1272 34378 171892 Lumbriculus variegatus 

OPPTS 

850.1735 28 BSAF test Yes

Worm 

reproduction 

apparent

>336 

(highest 

dose) 
Page 18 of 24 

Table 4. Monitored D4 and D5 residues in biota from Lake Pepin (MN, USA) and 

Oslofjord (Norway), ranked by D5 concentration (ng/g-lipid). 

Location Species N %lipid

D4 

(ng/glipid)

STDEV 

(ng/glipid)D5 (ng/glipid)

STDEV 

(ng/glipid)

Outer Oslofjord Mussell (sp. B) 3 0.81 ND* 537 50

Outer Oslofjord Mussell (sp. A) 3 1.38 14 2 1029 55

Outer Oslofjord Worms 1 (composite) 0.32 16 1254

L. Pepin Burrowing mayfly 2 (composite) 2.54 309 36 3895 341

Outer Oslofjord Sea urchin 3 0.32 154 17 4159 761

Inner Oslofjord Mussel (sp. B) 2 0.90 21 4 4468 277

Inner Oslofjord Blue mussel 5 0.81 18 3 5333 1303

L. Pepin Midge 5 (composite) 0.85 888 304 18114 8860

Inner Oslofjord Mussel (sp. A) 2 0.76 36 8 34137 18322

Inner Oslofjord Worms 1 (composite) 0.32 2687 172777

*ND = Not detected
Page 19 of 24 

Figure 1. Probability distributions for D4 sediment concentrations (ng/g-dw) versus 

chronic toxicity NOEC values (ng/g-dw) for benthic invertebrate species. 

D4: Sediment Exposure Ranking versus Chronic NOEC Ranking

D4 Sediment Concentration (ng/g-dw)

10-1 100 101 102 103 104 105

%Centile Ranking (Probability)

1

10

30

50

70

90

99

Lumbriculus variegatus

(28-d)

Chironomus riparius

(28-d)

Chironomus tentans

(14-d)

5th centile ecotox NOEC = 4100 ng/g-dw

95th centile exposure = 70 ng/g-dw

Difference of 60x

Cummulative prob. 0.25%

Exposure

Toxicity

N=62

intercept = -0.720

slope = 1.282

r 2 = 0.9350

intercept = -8.385

slope = 1.865

r 2 = 0.8553
Page 20 of 24 

Figure 2. Probability distributions for D4 sediment concentrations (ng/g-OC) versus 

chronic toxicity NOEC values (ng/g-OC) for benthic invertebrate species. 

D4: Sediment Exposure Ranking vs. Chronic NOEC Ranking - OC Based

D4 Sediment Concentration (ng/g-OC)

101 102 103 104 105 106 107 108

%Centile Rank

1

10

30

50

70

90

99

intercept = -8.186

slope = 1.326

r 2 = 0.9354

Lumbriculus variegatus

(28-d)

N=62

intercept = -2.516

slope = 1.160

r 2 = 0.8207

95th centile exposure

concentration = 3850 ng/g-OC

5th centile ecotox

chronic NOEC = 8.57E4 ng/g-OC

Difference of ~20x

Cummulative prob. 0.25%

Chironomus riparius

(28-d)

Chironomus tentans

(14-d), 3 values

D4 OC Solubility Limit = 9.3E5 ng/g-OC
Page 21 of 24 

Figure 3. Probability distributions for D5 sediment concentrations (ng/g-dw) versus 

chronic toxicity NOEC values (ng/g-dw) for benthic invertebrate species. 

D5: Sediment Exposure Ranking versus Chronic NOEC Values 

D5 Sediment residues (ng/g-dw)

100 101 102 103 104 105 106 107

%Centile ranking (Probability)

1

10

30

50

70

90

99

N=95

intercept = -2.985

slope = 1.48

r 2 = 0.9711

95th centile = 1330 ng/g-dw

Chironomus riparius (28-d)

Mean of two studies

Hyalella azteca (28-d), 

Mean of three values

Lumbriculus variegatus 

(28-d)

intercept = -5.830

slope = 1.067

r 2 = 0.9993

Chronic 

Toxicity

Exposure

5th centile ecotox 

NOEC = 8360 ng/g-dw

Difference of ~6x

Cummulative prob. 0.25%

Industrial WWTP

Sediment
Page 22 of 24 

Figure 4. Probability distributions for D5 sediment concentrations (ng/g-OC) versus 

chronic toxicity NOEC values (ng/g-OC) for benthic invertebrate species. 

D5: Sediment Exposure Ranking vs. Chronic NOEC Ranking - OC-Based

D5 Sediment Concentration (ng/g-OC)

101 102 103 104 105 106 107 108

%Centile ranking (Probability)

1

10

30

50

70

90

99 N=95

intercept = -5.083

slope = 1.405

r 2 = 0.9276

95th centile conc = 6.15E04 ng/g-OC

Exposure

Chronic 

Toxicity

Intercept = -8.41

slope = 1.211

r 2 = 0.9754

5th centile NOEC = 

 3.8 E05 ng/g-OC

Difference is ~6x

Collective probability 

of 0.25%.

Lumbriculus variegatus

Hyalella azteca

(mean of three values)

Chironomus riparius

(mean of two values)

Industrial WWTP

Sediment

D5 OC solubility, 2.5E6 ng/g-OC 
Page 23 of 24 

Figure 5. Probability distributions for D4 biota benthic invertebrate concentrations 

(ng/g-lipid) observed in Lake Pepin and Oslofjord organisms (Inner and 

Outer fjord) versus calculated biota chronic toxicity NOEC values (ng/glipid) for benthic invertebrate species (assumed D4 BSAF of 20; Powell et 

al., 2009). 

D4: Invertebrate Exposure Ranking vs. Chronic NOEC Ranking

(BSAF assumed = 20 OC/lipid)

D4 Biota Concentration (ng/g-lipid)

100 101 102 103 104 105 106 107 108 109

%Centile Ranking (Probability)

1

10

30

50

70

90

99

Lumbriculus variegatus

(28-d)

Chironomus riparius

(28-d)

Chironomus tentans

(14-d), 3 values

intercept = -9.911

slope = 1.326

r 2 = 0.93539

5th centile ecotox

NOEC= 1.72E6 ng/g-lipid

intercept = -1.777

slope = 0.9120

r 2 = 0.8919

95th centile exposure

concentration = 5653 ng/g-lipid

Difference of 304x

Cummulative prob. 0.25%

Blue mussel (Inner)

Mussel (B-Inner)

Mussel (A-Inner)

Burrowing mayfly

Midge

Worms (Inner)

Exposure Toxicity

Mussel (A-Outer)

Worms (Outer)

Sea urchin (Outer)
Page 24 of 24 

Figure 6. Probability distributions for D5 biota benthic invertebrate concentrations 

(ng/g-lipid) observed in Lake Pepin and Oslofjord organisms (Inner and 

Outer fjord) versus calculated biota chronic toxicity NOEC values (ng/glipid) for benthic invertebrate species (assumed D5 BSAF of 5; Powell et 

al., 2009). 

D5: Invertebrate Exposure Ranking vs. Chronic NOEC Ranking

(BSAF assumed = 5 OC/lipid)

D5 Biota Concentration (ng/g-lipid)

102 103 104 105 106 107 108 109

%Centile ranking (Probability)

1

10

30

50

70

90

99

intercept = -6.986

slope = 0.9308

r 2 = 0.7618

5th centile chronic ecotox

NOEC = 5.47 E5 ng/g-lipid

intercept = -3.990

slope = 1.065

r 2 = 0.9394

95th centile exposure

concentration = 1.9 E5 ng/g-lipid

Differential of ~3x

Cumulative prob. of 0.25%

Mussel (B-Outer)

Mussel (A-Outer)

Worms (Outer)

Burrowing mayfly

Sea urchin (Outer)

Mussell (B-Inner)

Blue mussel (Inner)

Midge

Mussel (A-Inner)

Worms (Inner)

Chironomus riparius (28-d),

Mean of two values

Lumbriculus variegatus 

(28-d)

Hyalella azteca

(28-d)

Exposure

Toxicity
ATTACHMENT 4 

 
Page 1 of 2

Attachment 4 

Powell, 2012 

David E. Powell 

Dow Corning Corporation 

Midland, MI 48686 

Sediments were collected November 2011 as part of a preliminary monitoring assessment of 

three cyclic volatile methylsiloxane (cVMS) materials in the aquatic ecosystem of Tokyo Bay 

(SIAJ 2012). The three cVMS materials that were examined were Octamethylcyclotetrasiloxane 

(D4; CAS No. 556-67-2), Decamethylcyclopentasiloxane (D5; CAS No. 541-02-6) and 

Dodecamethylcyclohexasiloxane (D6; CAS No. 540-97-6). Surface sediments (surface 1-cm of 

sediment) were collected following a systematic probability sampling design based on a 5-km 

mesh grid that extended across the bay and about 30 km seaward from the head to the foot of 

the bay (defined study area of 500 km2

). 

Concentrations of the three cVMS materials in surface sediments of Tokyo Bay were lognormally distributed over the study area, with concentrations decreasing with increasing 

distance from point-source discharges at the head of the bay. Generally, concentrations of the 

three cVMS materials were less than or equal to the method detection limit in sediments 

towards the foot of the bay. Because concentration gradients existed across the surface 

sediments, the study area in Tokyo Bay was stratified based on the log-normally distributed 

concentrations. Mean concentrations and standard deviations for the study area were 

calculated using methods for a stratified experimental design (Gilbert 1987). Results from the 

systematic stratified design resulted in very precise estimates of mean concentrations of the 

cVMS materials in surface sediment of the study area in Tokyo Bay (Table 1). 

References: 

Gilbert, R.O. 1987. Statistical methods for environmental pollution monitoring. Van Nostrand 

Reinhold, New York, NY. 320 pp. 

Silicone Industry Association of Japan (SIAJ). 2012. Pre-research for the interannual variability 

survey (5-year monitoring survey) of cyclic volatile methylsiloxanes in sediment and aquatic 

biota in Tokyo Bay. Test result report. Environmental Control Center Co., Ltd. Kitakanto 

Branch. 3-15-12 Honmachihigashi, Chuo-ku, Saitama-shi, Saitama, Japan, 338-0003. 
Page 2 of 2

Table 1. Mean uncensored concentrations of D4, D5, and D6 in surface sediments of the 500 km2 study area in 

2012). Samples were collected by systematic sampling based on a fixed 5-km mesh grid. The study area was 

based on the log-normally distributed concentrations observed across surface sediments of the defined study arconcentrations and standard deviations were estimated using methods for a stratified design (Gilbert 1987).  D4 D5 

Measurement basis Mean SD Range Mean SD Range Mean Concentration (ng/g dw) 5.9 1.1 0.20-26 160 11 6.3-420 32 Concentration (ng/g ww) 1.6 0.25 0.15-6.1 45 2.8 4.8-110 9.1 Concentration (ng/g TOC) 200 28 59-680 5400 190 1300-13000 1200 Analytical method detection limit (MDL) based on concentrations measured in wet sediments were: 

 D4: 0.90 ng/g ww  D5: 0.56 ng/g ww  D6: 0.52 ng/g ww 
ATTACHMENT 5 

 
Page 1 of 5

Attachment 5 

Kim, 2012 

Major Factors Impacting Environmental Levels1

 of Siloxanes (D4/D5) at POTWs 

Jaeshin Kim, August 1, 2012 Dow Corning Corporation 

I. INTRODUCTION 

Recently, the USEPA proposed major factors to develop a monitoring program design by a DOptimal Design process. Those factors are listed as below. 

 Influent sources 

1) Population size served by the POTW (High/Medium/Low) 

 POTW characteristics 

2) Treatment types (activated sludge, other secondary treatment types). Other 

secondary treatment types could include trickling filter, oxidation ditch or lagoons. 

3) Total Suspended Solids (TSS) in effluent (high/low). 

 Receiving body characteristics 

4) Geography (North, South) 

5) Receiving body flow (lake/ low flow stream/high flow river) 

6) Organic content of receiving body (high/low) 

Although these factors can impact the concentrations of D4 and D5 in the environment, a more 

systematic evaluation of the factors is needed using what is already known about the 

physicochemical properties and environmental monitoring of D4 and D5 to inform the 

appropriate path forward. 

In order to employ a D-Optimal Design approach, a set of input parameters (or factors) is 

required which influence the output (i.e., environmental concentration of D4 and D5). Major 

factors are selected by the following three criteria (CR). 

 CR 1: Major factors should be selected based on proper understanding or evidence of 

the input-output relationship. 

 CR 2: The selected factors should be independent of each other. 

 CR 3: The quantity of the factors should be known prior to the monitoring program. 

To apply the criteria, it is critical to assess the physicochemical properties of D4 and D5 (i.e. 

highly volatile, practically insoluble in water, preferential partitioning to organic phases, and nonbiodegradable). 

II. APPLICATION OF THE CRITERIA 

                                                      

1 The “levels” is interpreted as “environmental concentrations” as implied in the section of Charge of the EPA

proposal and also mentioned during the conference call on Tuesday, July 24, 2012.
Page 2 of 5

A. Criterion 1 

Based on CR 1, the following three factors are not important factors for the output of D4/D5 

environmental concentrations. The reasons are provided below. 

1) Population size served by the POTW 

When D4/D5 enters the wastewater stream from households, its total mass is 

proportional to population. However, their concentrations in the influent are dependent 

upon the flow rate and per capita usage rate in addition to population. Based on the 

USEPA NPDES database (total 10,415 POTWs2

), there is no significant correlation (r= –

0.001843, p< 0.05) between population and per capita wastewater flow rate as shown in 

the graph below. The per capita wastewater flow rate vary in a wide range as shown in 

the figure below (a median of 421 L/d-cap). 

In a typical simple case where each person consumes a certain amount of D4/D5 and 

water per day, D4/D5 concentrations in the wastewater influent are expected to constant 

and independent of the population size. For example, when the average of per capita 

usage of D5 is 103 g/yr-cap, the down-the-drain rate is 9.5%,3

 and per capita water 

consumption is 200 L/g-cap, the total D5 concentration in influent would be 134 μg/L. 

In reality, however, there are additional factors to be considered. Since a typical POTW 

may intake industrial wastewater and other source such as storm water, the overall 

incoming flow rate can be much higher than the water consumption by people, making 

                                                      

2 The database for 10,415 POTWs is also found in iSTREEM as an input data set and the POTWs discharge influents

to rivers or lakes.

3 These values were submitted to the Canada D5 Board of Review.

100

1000

10000

100000

10 100 1,000 10,000 100,000 1,000,000 10,000,000

Per capita

wastewater flow

rate (L/d‐cap)

Population served

Per capita wastewaterflow rate (L/d‐cap) vs. Population Served

Correlation factor = ‐0.001843
Page 3 of 5

influent D4/D5 concentrations increased or decreased. It is hard to estimate influent 

D4/D5 concentrations without the information of the additional wastewater source. 

At any rate, population alone cannot be an important factor for the D4/D5 environmental 

concentration. It is preferable that, among POTWs which do not receive industrial 

wastewater,4 facilities with high D4/D5 influent concentrations should be selected for the 

monitoring program. Since it is agreeable in general that the removal efficiency for a 

particular POTW type is similar, monitoring POTWs with low D4/D5 influent 

concentrations is not necessary. Since it is typically hard to measure low D4/D5 

concentrations (e.g., <3 μg/L in wastewater effluent), we can reasonably predict the 

effluent concentration based on the removal efficiency of the same treatment type. In 

summary, instead of population as a major input variable, influent D4/D5 concentration 

at a high level can be used as an input constant. 

2) Geography 

The factor of geography was considered because volatilization and solubility of D4 and 

D5 are dependent on temperature during wastewater treatment. The USEPA thinks that 

partition of D4/D5 to air would decrease as temperature decreases. Although this 

thought is not wrong, one should consider that the air-water partition coefficient (KAW) is 

VERY high over a typical range of wastewater treatment (e.g., 10 ~ 20 °C). This 

thermodynamic factor is therefore not a significant factor for the actual volatilization of 

D4/D5 during wastewater treatment. Rather the diffusive transport at the air-water 

interface is the rate determining step. In this regards, the volatilization/aeration rate at 

active sludge process is the most important to determine the removal of D4/D5 to the air 

compartment rather than the change of KAW values. 

In case of lagoon systems where no additional aeration is supplied, the overall 

volatilization can be more affected by the wind speed, which affects the transport of the 

chemical at the interface more than the water temperature (which affects diffusivity at the 

air-water interface). Even under a calm condition, the overall effect of temperature on 

effluent concentration is expected to be small (e.g., <±20%) with additional consideration 

of partition to suspended solid at different temperatures. 

Thus, the factor of geography seems to be a minor factor for D4/D5 environmental 

concentrations. 

3) Receiving body flow (lake/ low flow stream/high flow river) 

D4/D5 concentration in the receiving water body is influenced not only by the stream 

flow but also by the discharge flow rate from POTWs. Thus, the dilution factor is a better 

factor than the receiving body flow rate. 

We propose to use dilution factor as an input variable and select POTWs with low and 

high values of dilution factor. 

                                                      

4 This can be done by excluding large wastewater flow rates per capita and/or only including small wastewater flow

rates. Note that the minimum wastewater flow is 189 L/d‐cap based on the NPDES database.
Page 4 of 5

B. Criterion 2 

The second criterion (CR 2) describes that the selected factors should be independent. 

According to this criterion, the two factors of treatment types and effluent TSS concentration 

should be reconsidered due to the reason as follows. 

Total Suspended Solids (TSS) is an operational performance parameter required for permit 

compliance by POTWs. Because of this, TSS is already constrained. Further, it is an 

indicator of plant performance along with ammonia and BOD levels which are typically used 

collectively to know if a monitored plant is operating properly. This is a key factor in eventual 

site selection. High TSS is normally associated with plant upsets following rain events. 

However, baseline TSS levels are treatment-type dependent (these are also reflected in 

POTW NPDES permits) such that a “low” level of TSS concentration in lagoon effluent is a 

“high” level of TSS concentration in activated sludge effluent. 

In addition to effluent TSS concentration, the D4/D5 concentration in the TSS phase is also 

important. In most cases, the D4/D5 concentration in the TSS phase is strongly dependent 

on the degree of aeration during the wastewater treatment because D4/D5 removed by 

aeration is predominantly from the solid phase. The solid phase concentration is expected to 

decrease in the order that follows, for example: lagoons with no aeration > oxidation ditch > 

trickling filter > activated sludge with surface aeration > activated sludge with bubble 

aeration. It should be noted that the mass fraction in the water phase is much smaller than 

the mass fraction in the solid phase in the influent. 

Since we can establish a general trend that TSS effluent concentration and solid phase 

D4/D5 concentration are dependent on treatment types, we propose to combine the two 

important factors of effluent TSS concentration and solid phase D4/D5 concentration into a 

single factor of treatment type with three levels such as low, medium and high for TSS 

concentration and solid phase D4/D5 concentration. 

C. Criterion 3 

Since the selection of monitoring POTW sites is the immediate goal, the input monitoring 

parameter should be also known prior to execution of the monitoring program. In this regard, 

the factor of organic content of receiving body is in question. Unless there is accurate 

database of the organic content for all the receiving water bodies near POTWs, it is 

impossible to locate sites with low or high organic content. Organic content is also highly 

dependent on season and subjected to watershed factors such as extent of extent of 

riparian zone. We assume that the monitoring program will measure the organic contents 

and use the information to support the concentration of D4/D5 in the sediment. In other 

words, the factor will be evaluated after, not before, the monitoring program. Thus, the 

organic content of the receiving water body cannot be used as a major factor for a DOptimal procedure unless there is a well-established database for the item. 

In addition, there is a concern about the factor of effluent TSS concentration. In general, the 

variation of reported effluent TSS concentration varies significantly depending on operation 

parameters at each site and even the way of sampling. Monitoring at limited times might 

induce a false information on the performance of a POTW. For example, the actual TSS 

concentration might be relatively high from an activated sludge at a particular sample time 

site although its mean concentration is low. For this reason, it is much safer to use D4/D5 

concentration in the TSS phase as a major factor and to measure TSS concentration to 

support the overall effluent concentration. Monitoring of TSS during sampling efforts will be 

a key variable to assess as part of the larger effort. 
Page 5 of 5

III. SUMMARY & SUGGESTIONS 

We have applied three criteria to evaluate six major factors proposed by the USEPA. All the 

factors of the USPEA are incomplete to be used as inputs for a D-Optimal procedure. Instead, 

we proposed a new set of input factors as listed below. 

 Input variables 

1) Treatment type (3 levels: low/medium/high for TSS concentration and solid phase 

D4/D5 concentration): for example, 

a. Low: activated sludge with bubble aeration (i.e., low TSS concentration and 

solid phase D4/D5 concentration) 

b. Medium: a trickling filter 

c. High: a lagoon without aeration (i.e., high TSS concentration and solid phase 

D4/D5 concentration) 

2) Dilution factor (2 levels: low/high) 

 Input constant 

3) Predicted influent total concentration of D4/D5: only high concentration is needed. 

We can estimate effluent concentration from the same treatment type assuming the 

removal efficiency is same for the same type. 

Thus, all six combinations (3×2, the full factorial) are suggested according to the new 

proposal. The total number could be reduced by a D-Optimal procedure (possible to three). 

The monitoring program will measure actual D4/D5 concentration in water and TSS of 

effluent and receiving water, TSS concentration in effluent, and organic content in sediment 

of receiving water body. 
ATTACHMENT 6 
Page 1 of 2

Attachment 6 

 MoE Analysis 

Margin of error expresses the amount of random sampling error in the estimation of a 

parameter, such as mean concentration. As depicted in the figure and table below, the margin 

of error is one-half the width of the 95% confidence interval about the mean (i.e., the 95% 

confidence limit) expressed on a percentage basis. For example, the margin of error for a mean 

concentration based on n=5 samples collected from a population having an estimated CV= 20% 

is ±24.8%. If the mean concentration was 100 then the 95% confidence interval about the mean 

would be 75.2 to 124.8. Similarly, the margin of error for a mean concentration based on n=5 

samples collected from a population having an estimated CV= 50% is ±62.1%, giving a 95% 

confidence interval about the mean of 37.9 to 162.1. 

Total variability across a population is a function of temporal and spatial variability. For the 

cVMS materials, spatial variability is the principle consideration for environmental parameters 

(i.e., concentrations in sediment and biota) whereas temporal variability is the principle 

consideration for WWTP parameters (i.e., concentrations in influent, effluent, and biosolids). 

Within a defined system such as Lake Pepin the CV for concentrations of D5 in sediment 

ranges from about 15% (for concentrations expressed on the basis of organic carbon) to 25% 

(for concentrations expressed on the basis of wet weight), based on simple random sampling. 

The CV for concentrations of D5 in Tokyo Bay sediments (collected following a systematic 

probability sampling design) ranges from about 3.5% (for concentrations expressed on the basis 

of organic carbon) to 6.9% (for concentrations expressed on the basis of wet weight or dry 

weight). 

Temporal variability associated with concentrations in a WWTP is not known, but could be 

estimated from the available data. I suspect that the CV for concentrations in influent are 

>100% over a 24-h period. In contrast, CVs for concentrations in effluent and biosolids will be 

much lower because concentrations in these matrices are integrated over the retention time 

within the WWTP. 
Page 2 of 2

1 2 3 4 5 6 7 8 9 10

100

80

60

40

20

0

Number of samples

Margin of error (%)

CV=10%

CV=20%

CV=30%

CV=40%

CV=50%

Margin of Error Power Curves

Margin of Error (%)

Number of Samples CV=10% CV=20% CV=30% CV=40% CV=50%

2 89.8 179.7 269.5 269.5 449.2

3 24.8 49.7 74.5 74.5 124.2

4 15.9 31.8 47.7 47.7 79.6

5 12.4 24.8 37.3 37.3 62.1

6 10.5 21.0 31.5 31.5 52.5

7 9.2 18.5 27.7 27.7 46.2

8 8.4 16.7 25.1 25.1 41.8

9 7.7 15.4 23.1 23.1 38.4

10 7.2 14.3 21.5 21.5 35.8