MARCH 2002 (Amended July 2002)

Mercury Source Control &

Pollution Prevention Program

Evaluation

Final Report

Prepared for:

Association of Metropolitan Sewerage Agencies (AMSA)

(Under Grant from U.S. Environmental Protection Agency)

Prepared by:
DISCLAIMER

Although the information in this report has been funded wholly or in part by the United 

States Environmental Protection Agency under grant number CX 827577-01-0 with the 

Association of Metropolitan Sewerage Agencies (AMSA), it does not necessarily reflect the 

views of the Agency and no official endorsement should be inferred. Mention of trade 

names or commercial products does not constitute endorsement or recommendation for use.

Neither AMSA nor its contractor, Larry Walker and Associates, assume any liability 

resulting from the use or reliance upon any information guidance, suggestions, conclusions, 

or opinions contained in this work.
Table of Contents

Introduction..................................................................................................................................... 1

Procedure ........................................................................................................................................ 3

Selection of Case Studies............................................................................................................ 3

Source Identification and Data Sources...................................................................................... 7

Dental Loading........................................................................................................................ 7

Human Amalgam Waste Loading........................................................................................... 9

Load Calculation....................................................................................................................... 12

Commercial Activities .......................................................................................................... 12

Residential Sources............................................................................................................... 12

Other Sources........................................................................................................................ 12

Reduction Estimate ................................................................................................................... 12

Resulting Influent, Effluent and Biosolids Loads and Concentrations..................................... 12

Comparison to Effluent Limits................................................................................................. 12

Cost of Compliance................................................................................................................... 12

Results and Discussion ................................................................................................................. 12

Select Case Studies ................................................................................................................... 12

Calculate Load Estimates.......................................................................................................... 12

Identify Most Significant Sources............................................................................................ 12

Estimate Influent Reduction ..................................................................................................... 12

Estimate Resulting Effluent Concentrations............................................................................. 12

Assess Potential Compliance .................................................................................................... 12

Estimate Changes in Biosolids Mercury Levels....................................................................... 12

Determine Costs Associated with Compliance ......................................................................... 12

Sensitivity Analysis .................................................................................................................. 12

Variation of Dental Discharge and Human Waste Values.................................................... 12

Influence of Secondary School Values..................................................................................... 12

Probability-Based Model.......................................................................................................... 12

Findings......................................................................................................................................... 12

Effectiveness of Mercury Pollution Prevention and Source Control Programs ....................... 12

Potential for Wastewater Reductions.................................................................................... 12

Benefits to Other Media ........................................................................................................ 12

Compliance Assessment ........................................................................................................... 12

Impact of Assumptions ............................................................................................................. 12

Limitations of Analysis............................................................................................................. 12

Conclusions................................................................................................................................... 12

Recommendations......................................................................................................................... 12

References..................................................................................................................................... 12
List of Tables

Table 1. Mercury Water Quality Criteria ........................................................................1

Table 2. POTW Data..........................................................................................................................6

Table 3. Data Used for Calculation of Dental Loading Value...........................................................7

Table 4. Mercury Loadings in Dental Clinic Vacuum System Wastewater ..............................8

Table 5. Barron’s Estimates Applied to Skare’s Average and Low Values ............................ 10

Table 6. Human Waste Mercury Studies Cited ...............................................................................10

Table 7. Human Waste Mercury Calculations.................................................................................11

Table 8. Source Control Strategy’s and Their Respective Effectiveness ........................................16

Table 9. Range of Effluent Limits...................................................................................................18

Table 10. Annual Treatment Costs for Removing Mercury............................................................20

Table 11. Cost based on Reduction Needed ....................................................................................20

Table 12. Costs of P2 Programs.......................................................................................................21

Table 13. POTW Mass Balances .....................................................................................................23

Table 14. Closure of Measured and Estimated Influent Loads........................................................25

Table 15. Example of Load Estimation from Identified Sources ....................................................26

Table 16: Source Reduction Estimation Example ...........................................................................28

Table 17: Pollution Prevention and Source Control Source Reduction...........................................29

Table 18. Resulting Concentrations using Pollution Prevention/Voluntary Estimates ....................30

Table 19. Resulting Concentrations using Source Control/Regulatory Estimates...........................30

Table 20. Number of Agencies Meeting Criteria and 50% Factor of Safety Based on Average 

Effluent Concentrations....................................................................................................31

Table 21. Number of Agencies Meeting Criteria Based on Maximum Effluent 

Concentrations..................................................................................................................31

Table 22. Estimated Biosolids Mercury Levels...............................................................................32

Table 23. Pollution Prevention Using Maximum Effluent Concentrations for Cost 

Calculations ......................................................................................................................32

Table 24. Source Control Using Maximum Effluent Concentrations for Cost Calculations...........33

Table 25. Scenarios used to test dental and human waste assumptions...........................................33

Table 26. Results of Varying Dental and Human Waste Values.....................................................34

Table 27. Estimated Percent Contribution to Influent Loading from Commercial Sources............37

Table 28. Change in Source Control/Regulatory Reduction (g/day) Based on Varying Secondary 

School Influent Mercury Concentrations .........................................................................38

Table 29. Summary of Probability-Based Modeling of Mercury Reductions Achievable 

Through Pollution Prevention and Source Control Strategies .........................................41

Table 30. Results of Probability-Based Modeling of Mercury Reductions Achievable through 

Pollution Prevention and Source Control BMP Implementation Strategies: SRCSD......42

Table 31. Average Concentrations and Reductions Predicted by Model........................................46
List of Figures

Figure 1. Flow Chart of Processes Used............................................................................................5

Figure 2. SRCSD Percent Removal in Effluent vs. Influent Concentration....................................17

Figure 3. WLSSD Percent Removal in Effluent vs. Influent Concentration...................................17

Figure 4. Box Plots of Influent and Effluent + Biosolids................................................................24

Figure 5. Estimated Load Closure ...................................................................................................25

Figure 6. Top Three Commercial Sources.......................................................................................27

Figure 7. Average Source Contributions to Influent Mercury Load................................................27

Figure 8. Average Relative Contributions of Mercury Sources......................................................36

Figure 9. Change in Top Three Commercial Sources......................................................................38

Figure 10. Elevated Secondary School Value ..................................................................................38

Figure 11. Influent Mercury Source Pies.........................................................................................39

Figure 12. Influent Levels based on Monitoring Data and Load Model .........................................43

Figure 13. Effluent Levels based on Monitoring Data and Load Model.........................................43

Figure 14. Influent Concentration and Removal Efficiency............................................................44

Figure 15. Influent Reduction Resulting from Pollution Prevention Implementation.....................44

Figure 16. Effluent Reduction Resulting from Pollution Prevention Implementation....................45

Figure 17. Biosolids Mercury Reductions for 33 Danish Counties after Amalgam Separator 

Installation.......................................................................................................................50

List of Appendices

Appendix A. Plant Data Spreadsheets

Appendix B. Mercury Data and Calculations

Appendix C. Response to Comments

Appendix D. Sensitivity Analysis

Appendix E. Probability Model 
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Introduction

The effects of mercury exposure on human health and wildlife are driving a number of efforts to 

significantly reduce the level of this toxic, persistent, and bioaccumulative metal in the 

environment. Exposure to mercury, a neurotoxin, affects the brain and nervous system. Young 

children and developing fetuses are most susceptible to its harmful effects. Long-term exposure 

may cause, among other things, a loss of physical coordination and mental retardation. The 

consumption of fish from waters contaminated with mercury offers the greatest risk of exposure 

to this pollutant. [TriTAC, 2001].

Mercury enters waterbodies through several pathways including air deposition (from combustion 

and incineration processes), urban runoff, wastewater discharges, geothermal discharges, mine 

site runoff, and contaminated sediments.

Increased monitoring of mercury in the water column and fish tissue and the application of more 

stringent standards has led to increasingly stringent mercury effluent limits in NPDES permits. 

Some of the standards that have been used or proposed are listed in Table 1.

Table 1. Mercury Water Quality Criteria

Basis of Criteria ng/L

California Toxics Rule Saltwater Criterion 25

EPA Fish Tissue Methyl Mercury-based 

Criterion (Rivers & Streams) 17-181

EPA Fish Tissue Methyl Mercury-based 

Criterion (Lakes) 7.5-7.81

Great Lakes Initiative Human Health Criterion 3.1

Great Lakes Initiative Wildlife Criterion 1.3

Proposed Maine Freshwater Chronic Criterion 0.2

Currently, approximately 6% (253 of 4307) of the major publicly owned treatment works 

(POTWs) have NPDES permits with mercury effluent limits and approximately 10% of the 

major POTWs (423 of 4307) have monitoring requirements (Morris, 2001). As more monitoring 

for mercury is conducted, the number of agencies with effluent limits is likely to significantly 

increase. Of the agencies with limits, several (particularly in the Great Lakes region) have limits 

based on the Great Lakes Initiative (GLI) Wildlife Criterion (i.e., 1.3 ng/L) and have had 

difficulty meeting these limits (EPA, 2001).

In order to comply with permit requirements, POTWs with effluent limits for mercury have 

investigated a variety of strategies, including non-regulatory approaches such as pollution 

 

1 These are projected criteria for total mercury that have been calculated from the national fish tissue residue criteria 

for methylmercury using, as default values, draft bioaccumulation factors, trophic level-specific fish consumption 

rates, and dissolved methyl-to-total mercury translators.
Mercury Source Control and Pollution Prevention Program Evaluation

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prevention and source control, in an effort to achieve mercury reductions. National efforts to 

reduce mercury releases to the environment have already used source control and pollution 

prevention to target incineration of medical and dental wastes, disposal of consumer products 

(i.e., fever thermometers, thermostats, switches, fluorescent light bulbs) and dental office 

wastewater discharges. 

In addition to source control and pollution prevention programs, mercury has also been the target 

of legislation. Legislation to restrict mercury use in consumer products and in certain other 

applications has been introduced at the federal level as well as in many states throughout the 

country. Legislation has been proposed that prohibits the sale or supply of mercury fever 

thermometers (except by prescription), novelty items and automobile switches as well as 

prohibiting purchases of mercury by schools. Some bills propose the immediate removal of 

mercury switches from automobiles and provide technical assistance to wrecking yards to 

remove mercury switches. Yet another bill prohibits improper disposal of mercury containing 

products and requires POTWs to perform wastewater monitoring, source identification and 

pollution prevention. There is also a provision requiring that mercury containment traps be 

installed for facilities that have the potential to discharge trace amounts of mercury to the sewer 

system. Many states are creating task forces to come up with recommendations on how to 

regulate mercury as a solid and hazardous waste.

While pollution prevention and source control are effective tools for reducing the amount of a 

pollutant entering the environment, several factors influence a POTW’s ability to achieve 

mercury reductions and permit compliance using pollution prevention and source control. These 

factors include: 

• Initial influent mercury levels; 

• Percentage of the influent loading that can be attributed to specific sources; 

• Ability of the POTW to control a particular source; 

• Potential effectiveness and cost of the source control strategies employed; 

• Form of mercury present in the influent (i.e., particulate vs. dissolved);

• Treatment plant removal efficiencies at varying influent concentrations; and

• Final effluent limit that must be achieved and corresponding reduction needed to 

achieve this limit. 

The purpose of this project was to:

1. Determine the extent to which pollution prevention and source control programs can achieve 

measurable reductions of mercury in POTW influent, and if these reductions will enable 

POTWs to comply with new, lower effluent limits based on the criteria listed in Table 1. 

(Note: The term pollution prevention program, as used in this report, refers to a source 

control program that uses only voluntary approaches); and

2. Identify the beneficial impacts of wastewater source control on other pathways by which 

mercury enters the environment.

The following steps were taken to complete this assessment:
Mercury Source Control and Pollution Prevention Program Evaluation

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• Estimate mercury reduction in influent achievable through source control;

• Assess ability of POTW to comply with effluent limits based on these influent 

reductions;

• Compare impact of implementing source control programs (cost) with impact of 

additional POTW treatment costs; and

• Identify benefits of source control programs in addition to impacts on wastewater.

The procedure used and the results of this assessment are described in the following sections.

Procedure. This section describes the process, the assumptions and the data sources used in 

the analysis.

Results. The results of the analysis are presented with respect to estimated mercury influent 

loadings for each plant, reductions that may be achievable through pollution prevention, 

resulting effluent mercury levels and potential for each case study candidate to comply with 

future effluent limits. The impacts of the various assumptions made are also discussed in this 

section.

Findings. The implications of the results with respect to the potential effectiveness of 

mercury pollution prevention programs and regulatory impacts are discussed. The impacts 

on other media in addition to water are also considered. Limitations of the study are 

presented.

Conclusions and Recommendations. Overall conclusions are summarized. 

Recommendations for source control programs are presented. Areas requiring future study 

are identified.

Procedure 

A flow chart of the process used to reach final effluent concentrations based on pollution 

prevention activities can be found in Figure 1. The basic steps of this process included:

• Selection of Case Studies

• Source Identification

• Source Load Calculation

• Reduction Estimate

• Resulting Influent, Effluent and Biosolids Loads and Concentrations

• Comparison to Effluent Limits

• Cost of Compliance

These process steps are described in detail below.

Selection of Case Studies

Initial outreach to POTWs was based on plant size and geographic location. To encompass a 

range of possible mercury sources and concentrations, different size plants, spread throughout 

the country, were contacted. Spreadsheets were e-mailed to each agency asking for information 

such as the number of households, influent/effluent concentrations and number of dental offices 
Mercury Source Control and Pollution Prevention Program Evaluation

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4

in their service area (See “Plant Data Spreadsheet” in Appendix A). Several agencies provided 

data and information about their plants and service areas, some of which is shown in Table 2, 

below. The data entered into the Plant Data Spreadsheet were linked to a second spreadsheet 

which used source values from previous studies to calculate loadings (grams/day) for each 

identified source. 
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Figure 1. Flow Chart of Processes Used

Determine influent load as effluent +

biosolids (data foreffluent and biosoli ds

was less variable)

Assess influent/effluent data

MDL =

0.06 –

10 ppt

Analytical

method

Number of

data points (7-

353 effluent)

245.1 1631

Determine effectiveness (projected

% reduction) for each source control

strategy

Determine estimatedreduction from

each source by multiplying effectiveness

and source loading contributions

Dental source reduction =

10-86% effectiveness;

Hospitalsource reduction=

30% effectiveness

Identify source control

strategiesfor each source

Determine mass balance

closure using (effluent

+biosolids) andestimated

source loading

Add all source loadings

together to ge t a total

estimated influent loading

Dental load

based on

average of all

wastewater

data (35 – 98

mg/dentist/day)

Humanwaste

amalgam load

based on study

with recent US

data (11 – 67

ug/person/day)

Determine total estimated reduction for a

pollution prevention/voluntary program foreach

agencyby adding upreductions for the 3 biggest

commercial and 2 biggestresidential source

reductions

Determine total estimated reduction for a

source control/regulatoryprogram for each

agencyby adding upall reductions

Determine resulting influent load by

subtracting reductionfrom influent load

Determine removal efficiency as average %

removal basedon influent and effluent data

Determine e ffluent load as (reduced

influent load)*(removal efficiency)

Explore

relationship

between influent

concentration and

removal

Determine effluent concentration as (load)/(flow)

Compare effluent to water quality criteria

CTR = 25

ppt

GLI =

1-3 ppt

Maine (proposed)

= 0.2 ppt

Fish tissue =

7.8-18 ppt

Get source da ta a nd

determine source loading

contributions for each agency

Select Case Studies based

on quality of data

Cost of compliance
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Table 2. POTW Data

*The data in Table 2 for the Hampton Roads Sanitation District were changed in July 2002 to more accurately 

reflect actual monitoring information. Note that the value in the column for Method Detection Level (MDL) is a 

Quantitation Level (QL) not an MDL. Also, the % Non Detect value is the percent not quantifiable, rather than not 

detectable. The “effluent” values were obtained at the end of HRSD’s chlorine contact tanks, which is not the 

official effluent sampling site.

POTW Community 

Size

Ave. 

Op. Size 

(MGD)

Average 

Inf. (ppt)

# 

Influent 

Samples

Average 

Eff. (ppt)

# 

Effluent 

Samples

Average 

Biosolids 

(g/day)

# 

Biosolid 

Samples

Analytical 

Method

MDL 

(ppt)

Time 

Period

% NonDetect 

(effluent)

Massachusetts Water 

Resource Authority 

(MWRA)

MA 2.5 M 375 260 12 30 12 340 245.1 10 1999-

2000

Hampton Road Sanitation 

District (HRSD)* VA 1.5 M 157 29-292 <5-29.5 5.7-21.1 245.7 5 QL 2000-

2001

86%*

Sacramento Regional 

County Sanitation District 

(SRCSD)

CA 1.1 M 157 227 105 9 116 113 164 1631 0.06 1998-

2000 0%

Northeast Ohio Regional 

Sewer District - Easterly 

(NEORSD-e)

401,167 104.1 143 19 3.56 19 55 19 0%

Northeast Ohio Regional 

Sewer District - Southerly 

(NEORSD-s)

597,936 109.5 323 10 3.17 11 144 366 0%

Northeast Ohio Regional 

Sewer District - Westerly 

(NEORSD-w)

123,170 31.2 113 7 3.11 11 16 366 0%

San Francisco - Southeast 

Plant

564,744 65 414 23 21 50 <0.323 2 0%

San Francisco - Oceanside 

Plant

224,033 17.6 237 12 51 18 <0.097 2 0%

Western Lake Superior 

Sanitary District 

(WLSSD)

MN 95,000 39 106 366 4.7 353 16.3 47 245.1 5 2000 58%

Palo Alto Regional Water 

Quality Control Plant CA 226,000 28 219 34 5.5 24 25.2 1631 10 1999-

2000 50%

Green Bay Metro 

Sewerage District 

(GBMSD)

WI 180,900 28 104 12 <7 12 18.9 40 245.7 7 2000 100%

Portland Water District -

Portland Plant ME 60,000 16.4 101 1 14 8 8.47 1631 0.2 2000 0%

Lewiston-Auburn WPCA ME 50,000 12.2 70 4

5 11 10.15 39 1631 0.2 1999-

2000 0%

Novato Sanitation District 

(NSD) CA 34,190 4.4 593 30 22.6 34 1631 10 1998-

2000 0%

Portland Water District -

Westbrook Plant ME 15,000 2.51 281 3 6.9 7 1.51 1631 0.2 2000 0%

2000

CA 2.5 2000

OH 1631 0.5

1631

43 36 133
Mercury Source Control and Pollution Prevention Program Evaluation

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To develop reasonable load reduction calculations, it was important to use data that accurately 

accounted for a majority of the mercury moving through each plant. Therefore, mass balance 

closures (influent = effluent + biosolids) were determined for each agency to assess the quality of 

available data. Influent, effluent and biosolids loads were determined based on flow and 

concentration data provided by each agency. Agencies used for the full calculation were selected 

based on the following criteria: 

• Number of influent and effluent samples reported

• Analytical method and detection limits

• Mass balance closure 

• Availability of all requested information.

Source Identification and Data Sources 

Many studies have been performed that attempt to identify sources of mercury from commercial, 

residential and industrial activities. In addition, research has been conducted on the effectiveness 

of pollution prevention and source control programs. Information on sources of mercury and 

effectiveness of pollution prevention was collected from various reports and Internet sites. In 

most cases, data obtained were averaged to obtain representative mercury concentrations and 

source flow data. A variety of commercial, industrial and residential sources were considered. 

Stormwater inflow and septage waste were also considered for agencies who provided data on 

these sources. The mercury data used for source loading calculations, and an explanation of how 

the final values were calculated can be found in Appendix B. Two of the most significant 

sources were dental office discharges and human waste associated with amalgam fillings. 

Literature values for these two sources were highly variable and based on several assumptions. 

Therefore, a sensitivity analysis (Appendix D) was conducted to assess the impact of varying 

these two values. By varying the dental and human waste values it was possible to get a sense of 

how influential the numbers used for these sources were on reduction estimates, mercury 

concentrations, compliance, and project costs. Dental and human waste loading data were 

chosen as discussed below.

Dental Loading

Mercury levels measured in dental wastewater were used to estimate loading contributions from 

dental offices to treatment plant influent. Several studies were available in which wastewater 

concentrations, water flow and consumption rates, and number of dentists had been measured 

[Rourke, 2000; SFWPPP, 1993; Barruci et al., 1992; NEORSD, 1997]. Because there is no way 

to conclude that any one of these studies is better then another, the data were treated equally. An 

unweighted average of the data from these studies resulted in a dental loading value of 56 

mg/dentist/day as shown in Table 3. Other studies measuring mercury discharges from dentists 

that were considered include those by Drummond et al., Cailas et al. and Arenholt-Bindslev and 

Larsen (Table 4) and Metropolitan Council Environmental Services (MCES). The differences 

between the values measured in Tables 3 and 4 are discussed below.

Table 3. Data Used for Calculation of Dental Loading Value

Barruci et al., 1992 35 mg/dentist/day 24 samples from 3 buildings

SFWPPP, 1993 46 mg/dentist/day 56 samples from 9 buildings
Mercury Source Control and Pollution Prevention Program Evaluation

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Rourke, 2000 98 mg/dentist/day 114 samples at 6 buildings

NEORSD, 1997 44 mg/dentist/day 37 samples at 5 facilities

AVERAGE 56 mg/dentist/day (0.056 g/dentist/day)

Table 4. Mercury Loadings in Dental Clinic Vacuum System Wastewater

Passing Chairside Trap 

(per chair)

Passing Chairside Trap 

(per chair)

Discharged

(per dentist)

Discharged 

(per dentist) (2) All data is 

given as:

 mg Hg/day soluble + solids settled solids(1) without amalgam 

removal equipment

without amalgam 

removal equipment

Mean 612 773 250 234

Median 499 522

N 58 66 10 275 (3)

Maximum 3298 842 1293

Minimum 20 65 8

Std. Dev. 529 733

Reference: Cailas, et al. (1994) Drummond, et al. 

(1995)

Arenholt-Bindslev

and Larsen (1996)

Berglund 

(2001)

(1) Supernatant passing chair had low mercury amount relative to solids, and also variable amount.

Drummond also measured the amount of mercury in solids retained in chairside traps.

The median value was 819 mg/chair/day (N = 57, Std. Dev. = 1032).

(2) Data for seven clinics, all operated with a chairside trap. Five operated with a vacuum filter, and two without a 

vacuum filter. 

(3) Some samples of wastewater and waste solids were collected over numerous days. Therefore, the “N”, or 

number of samples, is less than 275. However, the units for the data is “per day”, and the number of days of 

sample collection was 275 days.

The values listed in Table 4 are based on samples taken in the dental office. MCES (WEF, 1999) 

estimated that half of the mercury passing the chairside traps would be captured in a vacuum 

filter, commonly used with liquid-ring vacuum pumps. The other half, or 250-261 

mg/dentist/day (WEF, 1999) would be discharged from the clinic vacuum system and mixed in 

with the clinic’s other wastewater. A recent study by MCES estimated a dental loading 

contribution of 120 mg/dentist/day to the influent of two treatment plants (Anderson, 2001). 

This was based on a back-calculation from measured reductions in biosolids mercury levels and 

estimated grit removal rates resulting from installing amalgam removal equipment at all dental 

clinics in two treatment plant service areas (the result of 120 mg calculated out the same for each 

of the two service areas). A second study recently completed by MCES found a variable loading 
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rate from dentists, yet with a similar average loading rate of 234 mg/dentist/day (Berglund, 

2001), as compared to the other data in Table 4.

The basis for the calculations in this report is 56 mg/dentist/day (0.056 g/dentist/day). In the 

sensitivity analysis, loading values greater than 56 mg/dentist/day will be used, up to 150 

mg/dentist/day (with the understanding that the loadings may be higher than 56 mg/dentist/day 

based on data from Cailas, et al., Drummond et al., Arenholt-Bindslev & Larsen, and MCES). 

The measurements leading to the average of 56 mg/dentist/day may be lower than data in Table 4 

and lower than the 250-261 mg/dentist/day reported by the 1999 WEF monograph due to issues 

with: 

• Sampling location and amount of solids suspended in liquid fraction; and

• Subsampling prior to analysis and digestion methods of subsample.

Some portion of the amalgam that goes down the drain will settle in the collection system and 

leach back into the liquid fraction (which will contain particulate and dissolved mercury) over 

time. While there is a considerable amount of uncertainty regarding the fate and transport of 

solid amalgam in sewer lines, this settling could explain the difference in concentrations 

measured in the collection system (Table 3) and the concentrations measured in the dental office 

(Table 4). Another possible factor contributing to the differences in the values listed in Tables 3 

and 4 is the digestion method used as part of the sample analysis. The digestion process used for 

wastewater in Methods 245 and 1631 is appropriate for samples with low solids (i.e., values 

listed in Table 3). However, a more aggressive digestion method is used for high solids samples 

and may account for the higher mercury levels shown in Table 4.

It was assumed that the samples taken in the laterals leaving the dental offices (Table 3) 

represent the best estimate of the mercury actually leaving the dental office and the mercury 

leaching back into the liquid fraction at a given snapshot in time that will ultimately reach the 

treatment plant headworks. Therefore, 56 mg/dentist/day offers the best representation of the 

mercury that enters the treatment plant. Other viewpoints on this issue are addressed in 

Appendix C: Response to Comments.

Human Amalgam Waste Loading

In the case of human waste loadings associated with amalgam fillings, wastewater data was not 

readily available. Instead, the analysis used a calculated loading designed to best represent a 

typical U.S. population. A number of existing studies were reviewed to formulate the loading for 

this analysis. A Canadian study compiled data from a variety of sources and attempted to 

account for the relationship between number of fillings and human waste-amalgam mercury 

loadings. The resulting number was 11 μg/person/day [O’Conner Associates, 2000]. However, 

this was based on data averaging the number of fillings per person in Canada in the 1970’s. 

Another study, done by Barron (2001a, 2001b), found that the average number of amalgam 

surfaces is 16.6 per person (based upon Hyman data for the 1990 United States census). From 

this, the daily average mercury waste (urine + feces) is in the range of 27-39 μg/day/patient. 
Mercury Source Control and Pollution Prevention Program Evaluation

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‘Patient’ refers only to adults with amalgams. Restated, for all people beyond just those who 

have amalgams, the overall average number of amalgam surfaces is 10.8 per person. Therefore, 

the daily average loading is in the range of 17 to 26 μg/person/day. ‘Person’ here means all 

adults (>20 years), including those with and without amalgam fillings. The estimate based upon 

the Hyman data for fillings per person gives the high end of the above two ranges. The lower 

estimate is found by using Skare’s (1995) average and low values (Table 5). Skare’s curve fit 

was not used because the data included individual(s) with very high amalgam counts. 

Table 5. Barron’s Estimates Applied to Skare’s Average and Low Values

Surfaces U-Hg F-Hg Total Hg Units

Ave 40 1.7 64 65.7 μg/day/patient

Low 18 1.4 27 28.4 μg/day/patient

These values imply mercury waste loads of 1.64 (65.7÷40) and 1.58 (28.4÷18) μg/day PER 

AMALGAM SURFACE, respectively. The Barron estimate (2001b) uses 1.60 μg/day for this 

parameter. Doing so produces a human mercury waste result of 26.5 μg/day/adult ‘patient’, 

which is equivalent to an overall average of 17.2 μg/day/adult ‘person’. Table 6 summarizes 

human waste values calculated in the studies cited. Table 7 provides details of how these values 

were calculated.

Table 6. Human Waste Mercury Studies Cited

Reference Human Waste 

(μg/person/day)

Amalgam 

Surfaces

μg Hg/ 

surface /day

49.3 40 1.64 Skare 21.3 18 1.58

Barron 17.2 10.8 1.60

O’Conner 11.4 7.6 1.50

The value calculated by Barron, 17.2 μg/day/person, was used because it appears to be the most 

representative of the U.S. population. This number accounts for all people; the fact that some 

people have amalgam fillings and some don’t, has been factored into the 17.2 μg/day/person 

value.
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Table 7. Human Waste Mercury Calculations

Barron (2001b) O'Connor (2000) Skare (1995a) Skare (1995b) AMSA (2000)

[Revised] [1,2] [Table 4.2] [3] [Table 1 - low] [Table 1 - mid] [Page 11]

Per Adult Person (including just those with amalgam fillings)

Total Filling Surfaces/person 18.43 • • • • • • • • • • • •

Pct of surfaces that are amalgam 90% • • • • • • • • • • • •

Average amalgam surfaces / person 16.59 • • • 18.00 40.00 • • •

Hg Waste (u+f) per amalgam surface (μg/d) 1.60 • • • 1.58 1.64 • • •

Human Hg waste (u+f) in μg/d [1] 26.54 • • • 28.40 65.70 67.00

Convert to mg per year (multiply) 0.37 • • • 0.37 0.37 • • •

Human Hg waste (u+f) in mg/yr 9.69 • • • 10.37 23.98 • • •

Per Adult Person (including both those with and w/out amalgams)

Pct. Of population w/ fillings 65% • • • 75% 75% 65%

Overall avg. amalgam surfaces / person 10.78 7.60 13.50 30.00 • • •

Hg Waste (u+f) per amalgam surface (μg/d) 1.60 1.50 1.58 1.64 • • •

Overall avg. human waste (u+f) in μg/d/pers 17.25 11.44 21.30 49.28 • • •

Convert to mg per year (multiply) 0.37 0.37 0.37 0.37 • • •

Overall avg. human waste (u+f) in mg/yr/pers 6.30 4.17 7.77 17.99 • • •

Notes.

[1] Equation: Hg (u+f) = c + m * N 

c 0.00 (Hg = 0 when Amalgam surfaces = 0)

m 1.60 (Hg Waste per amalgam surface)

N 16.59 (No. of surfaces)

Hg (u+f) μg/d 26.54 u = urine wastes; f = fecal wastes

Skare data and curve fit include a person with 82 surfaces. The lower end of Skare's data seems more applicable to the US & Canada.

[2] Interpretation of Skare ("low" = 18 surfaces, "mid" = 40 surfaces)

[3] Interpretation of O'Connor

Caution: Four digits used to show arithmetic, not to imply accuracy.

Interpretation by 

Barron (2001b)
Mercury Source Control and Pollution Prevention Program Evaluation

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12

Load Calculation

The first step in assessing the contribution of pollution prevention to effluent reduction was to 

estimate the quantity of mercury in treatment plant influent that is contributed from the identified 

sources. The following business categories and residential activities were determined to be 

potentially significant sources and were, therefore, included in the influent load calculation.

Commercial Activities

• Dental offices

• Hospitals

• Laboratories

• Universities

• Secondary schools

• Medical clinics

• Vehicle service facilities

• Industrial activities

Residential Sources

• Human waste (amalgam)

• Human waste 

(dietary)

• Laundry graywater

• Household products

• Improper disposal of mercury 

thermometers

Other Sources

• Industrial activity • Stormwater inflow

To estimate the load from each of the busine ss categories for a given community, the number of 

businesses in a category (provided by the case study POTW) was multiplied by an average flow 

and mercury concentration for this business category. The average flow and concentration 

values were compiled from the literature and from data provided by agencies that have 

conducted this type of sampling. Loadings from residential activities were estimated on a per 

person or per household basis also based on literature values and multiplied by the service area 

population or number of households (provided by the case study POTW). It was assumed that 

commercial and residential activities do not vary from community to community allowing 

pooling of available data and application of these data to each of the case studies. Industrial 

loadings, however, were based on community specific data provided by each case study 

participant. Equations used to estimate source loadings are shown in Table 11. Total influent 

loading was then determined as the sum of the loadings calculated for the individual residential, 

commercial, and industrial sources. Stormwater inflow and septage waste were estimated to be 

small contributions but were considered if the agency provided specific data.

Reduction Estimate

The next step in the process was to identify source control strategies for the sources listed above 

and to assign an effectiveness rating to each strategy. The predicted effectiveness of a control 

strategy was then multiplied by the estimated load for each applicable source to estimate a 

potential reduction achievable in the source’s loading through pollution prevention. The 

procedure for predicting effectiveness and estimating reductions is described below. The 

effectiveness of a source control strategy can be estimated on the basis of the level of 
Mercury Source Control and Pollution Prevention Program Evaluation

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13

participation expected and the maximum load reduction that may be achieved by the strategy. 

This is determined as the product of a participation factor and a load factor. 

The participation factor is an estimate of the portion of the targeted audience that will make the 

desired behavior change and implement the recommended practice. Ideally, implementation of a 

control strategy would result in the elimination of the source it was designed to address. In 

reality, only a certain percentage of the people and procedures addressed by the strategy will 

change. Pollution prevention programs typically rely on voluntary actions. In the case of 

residential sources, agencies do not have the legal authority to regulate residents so, in general, 

voluntary approaches are the only strategies available. There are other strategies that may seem 

useful for residential sources such as product bans or changing building codes. These strategies 

are often outside the jurisdiction of the local POTW. To pursue these strategies, efforts must be 

coordinated regionally or at the state level. In some cases, agencies have worked together and 

with state legislators to achieve product bans or restrictions (e.g., San Francisco Bay Area 

restrictions on the use of copper sulfate root control products, California ban on lindanecontaining head lice remedies, statewide bans on mercury fever thermometers). In other 

situations, the agency that the POTW must work with that has the authority to achieve the 

desired change is less cooperative. For example, in California, there is an ongoing and, so far, 

unsuccessful effort to change the state plumbing codes to allow the use of non-copper plumbing 

materials. Therefore, available approaches for residential sources are primarily voluntary and 

outreach-based. Product bans and other approaches requiring support by other groups are more 

difficult to accomplish and require longer time periods and greater resources than public 

education. Therefore, participation rates used in this study for strategies requiring cooperation 

with other agencies are typically lower than public education. 

For commercial sources, voluntary programs can be effective and may be more cost effective for 

the agency than working with the general public. Regulatory approaches are also available for 

commercial sources and will have higher participation rates than voluntary approaches during the 

initial stages of a program. Over time, an effective voluntary program can achieve participation 

rates comparable to regulatory programs. Specific participation rates used for this study are 

listed below. The participation rate used for dentists with respect to implementing BMPs on a 

voluntary basis is based on the results of surveys conducted regarding dental office waste 

management practices in San Francisco. San Francisco and other Bay Area agencies have 

worked with the dentists in its service area for a number of years educating them regarding the 

environmental impacts of mercury and recommended amalgam management practices. San 

Francisco Bay area dentists have been responding reasonably to data that is presented to them 

indicating that they are a major source of mercury in wastewater. The California Dental 

Association has been cooperating in recommending non-treatment related BMPs. However, 

their acceptance of separators remains to be seen. Surveys (231 responses from a possible 843 

dentists) and site visits (34 offices) conducted for San Francisco dentists both indicate that 

approximately 65% of the dentists are implementing the recommended BMPs (WERF, 2001). 

WLSSD has also worked closely with the dental community and, after 10 years, reports high 

rates of cooperation from the dentists (Tuominem, 2001). However, participation rates can vary. 

King County reported a lower BMP implementation rate of 38% (King County, 2000). 
Mercury Source Control and Pollution Prevention Program Evaluation

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14

The loading factor is the expected amount of pollutant load reduction from a source if there was 

100% participation. The loading factor varies depending on the sources that the strategy 

addresses. Loading factors are determined by estimating the amount of mercury coming from 

individual sources within a category and determining what portion of the loading is addressed. 

For example, sources of mercury from hospitals include mercury-containing equipment, mercury 

solutions and mercury present in the sewer lines. Each control strategy is then examined to 

determine the individual sources that it addresses. 

Business outreach and public education strategies are assumed to address all individual sources. 

For example, all programs related to thermometers and contact lens solutions have a loading 

factor of 100% because control strategies aimed at these sources would effectively eliminate the 

source. In the case of dentists, it was determined that approximately 80% of the dental amalgam 

wastes would be kept out of the drain because that is the approximate amount of material 

captured in standard traps. The load factor for amalgam separators is 95% because they are able 

to capture smaller particles and, therefore, a larger percentage of the amalgam wastes discharged. 

The load factor for stopping use of amalgam is 50% because it is estimated that about half the 

amalgam discharges in a practice come from placing fillings. The other half comes from 

removal of old amalgam fillings. This division between fillings placed and fillings removed is 

based on the responses of dentists surveyed in the San Francisco Bay Area (WERF, 2001).

The strategies available for addressing the identified sources and their predicted effectiveness are 

shown in Table 8. The participation and load factors are based on the results observed from 

various pollution prevention efforts. Some specifics include:

• The participation rate of 65% for the strategy targeting dental offices of voluntary 

implementation of BMPs is based on the results of surveys conducted in 2000 by Palo Alto, 

San Francisco, and Central Contra Costa Sanitary District (WERF, 2001; Brandenburg, 2000; 

Hughes, 2000). 

• The load factor is based on the percent capture of amalgam particles through chair-side traps 

and vacuum filters estimated by MWRA and MCES studies (MWRA, 1997; WEF, 1999). 

• The load factor for amalgam separators is based on the results of performance tests on 

separators. The participation factor associated with persuading dentists to stop using 

amalgam is based on the dental survey results mentioned above (WERF, 2001). 

• The participation factor for the other business categories is based on percent of businesses 

complying with BMPs seen by Palo Alto and West County in the first year of voluntary 

programs conducted by these agencies for vehicle service facilities and is approximately 50% 

(WERF, 2000). 

• The load factor for all the businesses that had BMP/modified purchasing are based on 

reductions measured by Detroit [Williams, 1997] and MWRA [MWRA/MASCO, 1995] for 

hospitals implementing these practices. For hospitals going to ‘Mercury-Free’ operation, the 

reductions may be greater than those observed in Detroit and Massachusetts. However, the 

reduction may not be 100% if there is residual mercury deposits in the laterals. In the 
Mercury Source Control and Pollution Prevention Program Evaluation

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15

absence of other data, the load factor is based on the results measured in these two studies 

(i.e., 60%).

• The vehicle service load factor is based on West County monitoring results for its vehicle 

service program (WERF, 2000).

• The thermometer exchange program participation rate is based on results of programs 

conducted by San Francisco, Palo Alto, and Connecticut. For each of these programs 

approximately 1% of the service area population turned in thermometers.

• A review of several surveys assessing increased awareness or behavior change resulting from 

public education programs was used to set participation rates for residential source control 

strategies. Residential participation rates (i.e., reported behavior change) are typically 5-10% 

with much lower participation seen for a more complicated strategy (like removing amalgam 

fillings or installing a graywater system). 

• Research regarding graywater systems has indicated that this is a complicated strategy for 

homeowners to implement. In some cases, it is not even possible due to space limitations. 

Graywater systems divert the water to landscaping and in densely populated areas not enough 

landscaping is available to accommodate the graywater discharges. Therefore, a lower 

participation rate is used (i.e., 2%).

• All participation rates used are the participation observed in the initial stages of a program, 

typically the first year. In this sort of time frame, regulatory approaches will have higher 

participation rates than voluntary programs. However, over time, participation rates for wellimplemented voluntary programs will approach the participation rates for regulatory 

programs. After ten years, WLSSD has a high level of cooperation with the dentists in its 

service area (i.e., close to 100%). Palo Alto’s vehicle service program had a 50% 

participation rate in its first year. After 5 years, participation and BMP implementation was 

over 90% (WERF 2000).
Mercury Source Control and Pollution Prevention Program Evaluation

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Table 8. Source Control Strategies and Their Respective Effectiveness

Source Control Strategy Participation 

Factor

Load 

Factor Effectiveness

COMMERCIAL

Voluntary programs

BMPs - Recycle all amalgam wastes 65% 80% 52%

Amalgam separators 10% 95% 10%

Stop using amalgam 25% 50% 13%

Permits/regulatory

BMPs - Recycle all amalgam wastes 95% 80% 76%

Amalgam separators 90% 95% 86%

Dentists

Stop using amalgam 90% 50% 45%

Hospitals

Laboratories

Universities

Secondary Schools

Medical Clinics

BMPs -Modify purchasing/ disposal 

practices (voluntary) 50% 60% 30%

Vehicle Service BMPs / Zero discharge 50% 80% 40%

Pottery Ceramics BMPs -Modify purchasing/ disposal 

practices (voluntary) 50% 60% 30%

RESIDENTIAL

Human Wasteamalgam Remove amalgam fillings – public outreach 2% 100% 2%

Human Wastedietary Uncontrollable

Laundry Graywater Graywater systems– public outreach 2% 100% 2%

Household products Substitute alternatives– public outreach 10% 100% 10%

Turn in Hg thermometers - public outreach 1% 100% 1%

Thermometers Work w/ pharmacies to not sell 50% 100% 50%

Local sales ban 90% 100% 90%

Contact Lens 

Solution Work w/ pharmacies to not sell 50% 100% 50%

Local sales ban 90% 100% 90%

INDUSTRIAL BMPs 90% 90% 81%

Resulting Influent, Effluent and Biosolids Loads and Concentrations

Source reduction estimates were made for each identified source of mercury. These reduction 

estimates were then added together to estimate an overall influent reduction. Reductions were 

calculated based on two types of programs, pollution prevention/voluntary and source 

control/regulatory. A pollution prevention program was an all voluntary program and was based 

on implementation of the top three commercial and top two residential voluntary strategies with 

respect to estimated achievable reduction. A source control program included regulatory 

elements for the largest sources (i.e., dentists) and was calculated by assuming implementation of 

all reduction strategies. These estimates were tailored to each plant based on existing pollution 

prevention efforts as some plants had already implemented many of the strategies listed in Table 

8 and other plants were just beginning their source control and pollution prevention programs.
Mercury Source Control and Pollution Prevention Program Evaluation

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17

Once a reduced influent concentration was established for each plant, reduced effluent 

concentrations could be calculated. Effluent reduction was determined using average removal 

efficiency calculated from influent and effluent data provided by each plant [(average influent –

average effluent)/ average influent]. The range of removal efficiencies from plant to plant was 

96% - 99%. Another approach to determining removal efficiencies was to consider any 

correlation between influent concentration and removal efficiency. It has been found that there 

may not be a linear correlation between influent and effluent concentration. Data provided by 

Western Lake Superior Sanitary District (WLSSD) and Sacramento Regional County Sanitation 

District (SRCSD) is shown in Figures 2 and 3. These figures indicate that as influent mercury 

concentration decreases, removal efficiency might also decrease. However, because of the 

variability of the data, no systematic approach for determining how much the removal efficiency 

decreases with decreasing influent could be established. Therefore, the average removal 

efficiency for each treatment plant was used as a best estimate. 

SRCSD

80%

84%

88%

92%

96%

100%

0 100 200 300 400 500 600 700 800

Influent Concentration (ng/L)

Figure 2. SRCSD % Removal in Effluent vs. Influent Concentration

WLSSD

20%

40%

60%

80%

100%

0 100 200 300 400 500 600 700 800

Influent Concentration (ug/L)

Figure 3. WL SSD % Removal in Effluent vs. Influent Concent ratio n
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Biosolids reductions were determined based on the mass balance equation (influent – effluent = 

biosolids). Reduced influent and effluent values were used to calculate the reduction that plants 

would see in their biosolids concentrations. Reduced biosolids concentration is another 

beneficial effect of pollution prevention efforts. 

Comparison to Effluent Limits 

Mercury effluent levels, resulting from implementation of pollution prevention programs with 

the predicted effectiveness, were first determined using the process described above. The levels 

were then compared to water quality-based effluent limits. Table 9 lists criteria representing the 

range of limits that POTWs are facing.

Table 9. Range of Mercury Criteria

Basis of Criteria ng/L

Fish Tissue-based Criterion (Rivers/Streams) 17-18

Fish Tissue-based Criterion (Lakes) 7.5-7.8

Great Lakes Human Health Criterion 3.1

Great Lakes Initiative Wildlife Criterion 1.3

Proposed Maine Criterion 0.2

Permits in the San Francisco Bay area have effluent limits based on the National Recommended 

Water Quality Criteria (12 ng/L). However, as these permits are reissued, the CTR criteria of 25 

ng/L will be used. Agencies in the Great Lakes area have permit limits based on the Great Lakes 

Water Quality Initiative Criterion (1.3 ng/L) and, in Maine, 0.2 ng/L was under consideration.

In January 2001, EPA issued a water quality criterion for methyl-mercury defined as a level in 

fish tissue. Implementation of this criterion will be complicated as states struggle to use the fish 

tissue concentration in a regulatory context by attempting to convert the value into a water 

column number. EPA has set up a workgroup to develop implementation guidance for the 

criterion and water-quality standards based on it. This guidance could result in changes in the 

way POTW compliance is defined. For the purposes of this study, water quality criteria 

calculated from the fish tissue criterion were considered by using default values to translate the 

fish tissue criterion to a water quality criterion. The calculated values are shown in Table 9. The 

actual values of water quality criteria developed from the fish tissue criterion will depend on the 

specific water body and its properties. 

The calculated effluent concentrations (based on applying estimated reductions to maximum 

observed and average effluent concentrations reported by the POTWs) were then compared to 

the range of criteria in Table 9. Compliance with criteria was determined ‘end-of-pipe’ (i.e., no 

dilution). Permits containing mercury effluent limits are often applied with no credit for dilution. 

This is either because the receiving water is impaired for mercury (303(d) listed) or because the 

receiving water is an effluent dominated water body. 
Mercury Source Control and Pollution Prevention Program Evaluation

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Cost of Compliance

The cost to comply with the criteria in Table 9 was determined based on the costs to implement 

the proposed pollution prevention programs and, as necessary, to construct additional treatment 

facilities where reductions through pollution prevention were inadequate. The costs to 

businesses targeted by pollution prevention programs was not considered. However, if treatment 

is required of dentists there would be a cost to install amalgam separators ($100 to $3000 

installed) and to maintain the system ($35 - $200/month) [Barron, 2001; Boyd, 2001].

Pollution prevention costs were estimated based on a review of the cost of effective pollution 

prevention programs and the cost to develop demonstration pollution prevention projects [LWA, 

2001; WERF, 2000]. The costs of several pollution prevention program elements are shown in 

Table 12. In general it was assumed that a pollution prevention/voluntary program would 

address dentists, two other business categories and a public education campaign. The program 

would be conducted on a voluntary basis and would roughly cost the following (based on the 

costs of pollution prevention programs shown in the Table 12):

• Program for dentists, voluntary - $100,000

• Voluntary BMP based program for other businesses - $50,000

• Public education program - $50,000 for agencies <20 MGD; $100,000 for agencies between 

20 and 100 MGD; $150,000 for agencies >100 MGD

The cost associated with a source control/regulatory program factors in costs of each strategy 

listed. In addition, costs for implementing a program with regulatory elements were considered. 

Implementing a regulatory or permit-based program is more costly than a voluntary program in 

that it requires more tracking and paperwork to assess compliance. However, permit based 

programs for small dischargers (e.g., dentists) do not have to be as resource intensive as standard 

pretreatment permits. Agencies have implemented general or group permits for small 

dischargers (e.g., photoprocessors) or have developed permits that have fewer requirements or 

are BMP-based. It was assumed that a regulatory program for dentists would be twice as costly 

as a voluntary program and, therefore, would have an annual cost of $200,000.

Treatment costs were determined based on a study conducted by the Sanitation Districts of Los 

Angeles County (LACSD) for the unit operations directly associated with mercury removal (i.e., 

reverse osmosis and ion exchange). Waste removal costs were estimated by ADVENT. This 

results in an annual treatment cost of $1,922,000/ MGD as shown in Table 10. 
Mercury Source Control and Pollution Prevention Program Evaluation

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20

Table 10. Annual Treatment Costs for Removing Mercury2

Unit Process Total Cost ($ 103/MGD) Reference Source

Reverse Osmosis 876 National Research Council

Ion Exchange 900 Bureau of Reclamation3

Brine treatment 146 ADVENT

Total 1922

These costs were applied to a portion of the total plant flow based on the reduction needed to 

meet proposed limits after the reductions achieved through pollution prevention were considered. 

The amount of flow treated was estimated as shown in Table 11.

Table 11. Cost Based on Reduction Needed

Reduction needed Portion of flow treated Annual cost multiplied by

>75% 100% 100%

50%-75% 75% 75%

25%-50% 50% 50%

0%-25% 25% 25%

 

2

Includes amortized capital and operation and maintenance costs.

3 Mercury and Cadmium Fact Sheet, Bureau of Reclamation, Technical Service Center, Denver, 

CO, September 1999.
Mercury Source Control and Pollution Prevention Program Evaluation

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Table 12. Costs of Pollution Prevention Programs

Source P2 Item Number in Target 

Audience

Annual/ Start-up 

Cost Source

Brochure/ Fact Sheets + distribution 900 $60,000 SFWPPP

Brochure/ Fact Sheets + distribution 500 $12,000 Palo Alto RWQCP

Outreach/advisory group 500 dentists $10,000 Palo Alto RWQCP

Outreach 100 $30,000 WLSSD

Dentists

Site visits 35 visits $12,000 SFWPPP

Thermometer exchange program 3.3 million people, 38,000 

thermometers $144,816 Connecticut DEP

Thermometer exchange program 790,000 people, 5000 

thermometers collected $70,000 SFWPPP

Thermometer exchange program 227,000 people, 1000 

thermometers

$15,000 Palo Alto RWQCP (KM)

Thermometer Sales ban/

legislation $15,000 Palo Alto RWQCP

Root killer sales ban legislation $30,000 Palo Alto RWQCP (KM)

Consumer 

Products

HHW Collection facility/event 76 collection events $ 2,660 Connecticut DEP

Site visits/inspections 330 facilities $20,000 Palo Alto RWQCP (KM)

Develop permits 330 facilities $50,000 Palo Alto RWQCP (KM)

Vehicle 

Service

Inspections/BMPs 46 facilities $50,000 West County

Secondary 

Schools Clean-out/ collection of chemicals 8 high schools $40,000 Connecticut DEP

Brochure development & printing 50,000 people, 6000 guides $12,000 Davis healthy gardens

General public outreach 50,000 people $40,000 Davis healthy gardens

Residential outreach 20,000 residents, 1000 

packets $12,000 Woodland O&G

Business outreach/ recognition 

program

200 businesses $20,000 Davis Partners Program

8 fact sheets/ BMPs, regulatory info 500 businesses $20,000 Davis Partners Program

Business workshops (2) 1000 businesses $27,000 Santa Monica New 

Development Program

Brochure/ fact sheets -general $15-20,000 General depending on 

size, number, etc.

Non-Hg 

Sources

Clean Bay Hardware program $20,000 Palo Alto RWQCP (KM)

Results and Discussion

The results of the analysis are discussed below in the following sections:

• Select Case Studies

• Calculate Load Estimates

• Identify Most Significant Sources

• Estimate Influent Reductions

• Determine Resulting Effluent Concentrations 

• Assess Potential Compliance 

• Estimate Changes in Biosolids Levels
Mercury Source Control and Pollution Prevention Program Evaluation

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22

• Determine Costs Associated with Compliance

• Assess Impact of Assumptions

Select Case Studies

A large quantity of quality information was received from a number POTWs throughout the 

mercury source control study. However, for the final report, only a few of these agencies were 

examined more closely. The selection of these final plants was based on four criteria as listed in 

the Procedure section. First, the quantity of data available for each plant’s influent, effluent and 

biosolids was evaluated. As shown in Table 2, Portland Water District’s Portland plant had only 

one influent sample and with the variability of influent mercury sampling, it was decided not to 

use Portland for the final calculations. Second, the analytical method used and subsequent 

detection limit were investigated. As shown in Table 2, Green Bay Municipal Sanitation District 

(GBMSD), the Massachusetts Water Resources Authority (MWRA) and Western Lake Superior 

Sanitation District (WLSSD) presently use EPA Method 245.1 for mercury analysis. This 

method has a higher detection limit than EPA Method 1631 and, due to the variance this causes 

in influent and effluent concentrations, it is not appropriate to compare plants that use Method 

245.1 to those using Method 1631. Only plants using EPA Method 1631 were included in the 

final calculations with the exception of WLSSD because they use an improved method of 245.1 

that has a lower detection limit of 5 ng/L. The third criterion involved a comparison of influent 

to effluent plus biosolids. Calculating this mass balance was useful for evaluating the 

consistency of the collected data. Comparisons between influent and effluent plus biosolids were 

used to identify plants with acceptable mass balance closure. The measured influent load is the 

product of average flow and average concentration. In addition, “Effluent + Biosolids” was 

calculated to provide another measure of influent load. The measured influent and effluent plus 

biosolids loads for each plant are compared in Table 13. 
Mercury Source Control and Pollution Prevention Program Evaluation

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23

Table 13. POTW Mass Balances

Box plots were created to show the distribution of influent data as well as effluent plus biosolids 

data. If the influent (i) and effluent + biosolids (e+b) boxes overlapped, the range of influent 

values was considered statistically equivalent to the effluent plus biosolids values. Based on the 

comparison shown in Figure 4, Portland Water District’s Portland plant was removed from the 

list, as well as Lewiston-Auburn Water Pollution Control Agency (LAWPCA) and GBMSD. 

San Francisco’s biosolids data was non-detect for 2000 and therefore did meet the mass balance 

criteria. 

Effluent Biosolids Effluent + 

Biosolids Influent

MWRA MA 2.5 M 42.6 340 383 369

HRSD VA 1.5 M 0.7 1.37 2.07 110

SRCSD CA 1.1 M 5.44 113 118 135

NEORSD - Easterly OH 401,167 1.4 55 56.4 56.3

NEORSD - Southerly OH 597,936 1.3 124 125.3 134

NEORSD - Westerly OH 123,170 0.36 16 16.4 13.3

San Francisco - SE CA 564,744 5.2 <0.323* 5.4 101

San Francisco - OS CA 224,033 3.4 <0.097* 3.4 15.8

WLSSD MN 95,000 0.69 16.3 17 15

Palo Alto CA 226,000 0.555 25.2 26.1 23.2

GBMSD WI 180,900 0.73 18.9 19.6 10.8

Portland M E 60,000 0.869 8.47 9.34 6.27

LAWPCA M E 50,000 0.23 10.15 10.38 3.23

Novato CA 34,190 0.38 ? ? 8.61

Westbrook M E 15,000 0.066 1.51 1.58 2.67

* 1/2 MDL was used in effluent + biosolids calculation

grams Hg / day Community 

Size POTW
Mercury Source Control and Pollution Prevention Program Evaluation

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24

The final criterion evaluated to select the case studies was the availability of all requested 

information. It was not possible to obtain enough data from Hampton Roads Sanitation District 

(HRSD) or Novato Sanitation District to make key calculations, therefore they were not included 

in the final assessment.

Therefore, the plants used as case studies were:

• Northeast Ohio Regional Sewer District, Ohio – Easterly Plant (NEORSD-e)

• Northeast Ohio Regional Sewer District, Ohio – Southerly Plant (NEORSD-s)

• Northeast Ohio Regional Sewer District, Ohio – Westerly Plant (NEORSD-w)

• Palo Alto Regional Water Quality Control Plant, California (Palo Alto)

• Sacramento Regional County Sanitation District, California (SRCSD)

• Portland Water District, Maine – Westbrook Plant (Westbrook)

• Western Lake Superior Sanitary District, Minnesota (WLSSD)

Calculate Load Estimates

Once the case study plants were selected, the next step was to calculate an influent load from the 

individual source loading contributions. Source loading contributions were determined using the 

procedure discussed above and the values listed in Appendix B. The estimated influent load for 

each plant was computed as the sum of the estimated mercury loads from each source. Percent 

closure estimates were obtained by using the estimated influent concentration as well as the 

measured effluent and biosolids concentrations and are presented in Table 14. The calculated 

influent load accounts for a large percentage of the measured influent load, the worst case being 

SRCSD, where 30% of its influent mercury is unaccounted for. A sample load calculation for 

one agency is shown in Table 15.

0

100

200

300

400

500

NEORSD e (i)

NEORSD e (e+b)

NEORSD s (i)

NEORSD s (e+b)

MWRA (i)

MWRA (e+b)

SF - SE (i)

SF - SE (e+b)

SRCSD (i)

SRCSD (e+b)

High Concentrations

grams/ day

0

10

20

30

40

50

Palo Alto (i)

Palo Alto (e+b)NEORSD w (i)

NEORSD w (e+b)

PWD port (i)

PWD port (e+b)

PWD west (i)

PWD west (e+b)

GBMSD (i)

GBMSD (e+b)

LAWPCA (i)

LAWPCA (e+b)

WLSSD (i)

WLSSD (e+b)

SF - OS (i)

SF - OS (e+b)

Low Concentrations

grams/ day

Figure 4. Box Plots of Influent and Effluent + Biosolids
Mercury Source Control and Pollution Prevention Program Evaluation

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Table 14. Closure of Measured and Estimated Influent Loads

POTW Flow 

(mgd)

Estimated 

Influent 

Load (g/d)

Measured 

Influent 

Load (g/d)

Effluent + 

Biosolids 

(g/d)

% closure 

(Estimated/ 

Measured)

% closure 

(Effluent+Biosolids/ 

Measured)

NEORSD - e 104.1 40.9 56.3 56.4 73% 100%

NEORSD - s 109.5 117.5 133 125 88% 94%

NEORSD - w 31.1 13.1 13.3 16.4 98% 123%

Palo Alto 28 20.1 23.2 25.8 87% 111%

SRCSD 157 88.2 135 118 65% 88%

Westbrook 2.51 2.4 2.7 1.58 90% 58%

WLSSD 39 11.7 15.6 17.0 75% 109%

The estimated mercury loadings were grouped into residential, commercial and industrial 

contributions as shown in Figure 5. Commercial sources represent the largest percentage of the 

influent loading, due largely to dental wastewater discharges. As shown in Figure 5, industrial 

mercury loads represent a relatively small portion of the total influent load.

0 20 40 60 80 100

NEORSD - e

NEORSD - s

NEORSD - w

Palo Alto

SRCSD

Westbrook

WLSSD

Figure 5. Estimated Load Closure

% Residential

% Commercial

% Industrial

% of influent load
Mercury Source Control and Pollution Prevention Program Evaluation

Final Report

26

Identify Most Significant Sources

The next step was to determine the sources that accounted for the greatest contributions to the 

influent loading. For the seven plants examined in this study, dentists, hospitals, medical clinics 

and vehicle service facilities represented the largest commercial mercury sources for each 

agency. Figure 6 shows the rankings for these top four commercial mercury sources. As the 

“First” rank exhibits, in all seven plants, dentists are the greatest contributors to the mercury 

load. The next greatest loading, or “Second” rank, comes from mainly hospitals (6 of 7 plants). 

Source # Conc Units Flow/ 

Facility Units Load Units Calculation

Commercial

Dentists 500 0.056 g/dentist/day 28.00 gm/day Number of dentists x concentration

Medical Clinics 80 4.3 μg/l 2800 gal/day 3.65 gm/day Number of medical clinics x flowx 

concentration

Hospitals 39 4.39 μg/l 120000 gal/day 77.76 gm/day Number of hospitals x flow x 

concentration

Laboratories 77 0.37 μg/l 11000 gal/day 1.19 gm/day flow x concentration x number

Universities 0.17 μg/l 48500 gal/day 0.00 gm/day flow x concentration x number

Secondary Schools 0.3 μg/l 7000 gal/day 0.00 gm/day flow x concentration x number

Vehicle Service 1284 1.2 μg/l 500 gal/day 2.92 gm/day flow x concentration x number

Pottery/ Ceramics 

Studios 200 0.31 μg/l 168 gal/day 0.04 gm/day number x flow x concentration

Estimated 

Commercial Load 113.55 gm/day

Residential

Population 1100000 100

gal/person/da

y

Number of 

Households 326000 168 gal/house/ day

Human Waste 

(amalgam) 17.2 μg/person/day 12.30 gm/day population x concentration x 65% population w/ fillings

Human Waste 

(dietary) 1.4 μg/person/day 1.54 gm/day population x concentration

Laundry Graywater 8.4 μg/person/day 9.24 gm/day population x concentraiton (1 load 

per person per week)

Household Products 0.021 μg/house/day 1.10E+08 gal/day 8.74 gm/day residential flow x concentration

Thermometers 2.3 μg/house/day 0.75 gm/day

number of households x 

22μg/house/day x 52% of 

households own hg therm.

Contact Lens 

Solution 0.044 μg/person/day 0.05 gm/day popluation x concentration

Estimated Residential 

Load 32.62 gm/day

Industrial 0.21 μg/l 8570000 gal/day 6.81 gm/day

152.98 gm/day

Measured Influent 0.199 μg/l 1.57E+08 gal/day 118.25 gm/day

Table 15. Example of Load Estimation from Identified Sources

Estimated Influent
Mercury Source Control and Pollution Prevention Program Evaluation

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27

Finally, the third greatest contribution to mercury loading comes from medical clinics for most 

of the plants, with vehicle service facilities and hospitals also contributing.

Based on average source contributions identified for each POTW, the largest residential source 

was human waste due to amalgam fillings for all seven plants. Laundry graywater and 

household products were the second and third largest sources respectively for all seven plants.

The relative contributions of each of the identified mercury sources are shown in Figure 7. The 

values shown in Figure 7 are the average percent contributions for the source for all seven plants. 

Dentists are the largest source by far when compared to average contributions from the other 

sources. Human waste amalgam and hospitals are the next most significant sources. 

0 1 2 3 4 5 6 7

First Second Third

Dentists

Hospitals

Medical Clinics

Vehicle Service

Number o f POTWS

Rank

Figure 6. Top Three Commercial Sources

0

5

10

15

20

25

30

35

40

Human Waste-Amalgam

Household Products

Laundry Graywater

Dentists

Medical ClinicsVehicle Service

Hospitals

Universities

Secondary Schools

Laboratories

Figure 7. Average Source Contributions to Influent Mercury Load % of Influent Load
Mercury Source Control and Pollution Prevention Program Evaluation

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28

Estimate Influent Reduction 

The estimated reduction achievable through pollution prevention was then determined for each 

plant. Load reductions were calculated using a participation factor, load factor and effectiveness 

for each identified control strategy as described in the Procedure section above. An example of 

the reduction estimate calculated for one plant is shown in Table 16.

Table 16. Source Reduction Estimation Example

Source

Estimated 

Load 

(gm/day)

Control strategy Participation 

Factor

Load 

Factor

EffectivenessLoad 

Reduction

Commercial

Voluntary programs

1.4 BMPs - Recycle all amalgam wastes 65% 80% 52% 0.7280

1.4 Amalgam separators 10% 95% 10% 0.1330

1.4 Stop using amalgam 25% 50% 13% 0.1750

Permits/regulatory

1.4 BMPs - Recycle all amalgam wastes 95% 80% 76% 1.0640

1.4 Amalgam separators 90% 95% 86% 1.1970

1.4 Stop using amalgam 90% 50% 45% 0.6300

Hospitals 0.3323 BMPs -Modify purchasing/ disposal 

practices (voluntary) 50% 60% 30% 0.0997

Laboratories 0.0154 BMPs -Modify purchasing/ disposal 

practices (voluntary) 50% 60% 30% 0.0046

Universities 0.0000 BMPs -Modify purchasing/ disposal 

practices (voluntary) 50% 60% 30% 0.0000

Secondary Schools 0.0477 BMPs -Modify purchasing/ disposal 

practices (voluntary) 50% 60% 30% 0.0143

Medical Clinics 0.0911 BMPs -Modify purchasing/ disposal 

practices (voluntary) 50% 60% 30% 0.0273

Vehicle Service 0.0545 BMPs / Zero discharge 50% 80% 40% 0.0218

Pottery Ceramics 0.0004 BMPs -Modify purchasing/ disposal 

practices (voluntary) 50% 60% 30% 0.0001

Commercial Total 1.9414

Residential

Human Waste-amalgam 0.1677 Remove amalgam fillings 2% 100% 2% 0.0034

Human Waste-dietary 0.0210 uncontrollable 0.0000

Laundry Graywater 0.1260 graywater systems 2% 100% 2% 0.0025

Household products 0.1192 Substitute alternatatives 10% 100% 10% 0.0119

0.1192 HHW collection 13% 100% 13% 0.0155

Thermometers 0.0112 Turn in Hg thermometers - low 1% 100% 1% 0.0001

0.0112 Work w/ pharmacies to not sell 50% 100% 50% 0.0056

0.0112 local sales ban 90% 100% 90% 0.0100

Contact Lens Solution 0.0007 Work w/ pharmacies to not sell 50% 100% 50% 0.0003

0.0007 local sales ban 90% 100% 90% 0.0006

Residential Total 0.4457

Industrial 0.0480 BMPs 90% 90% 81% 0.0389

Total Estimated Load 2.4352 1.4203

Average Influent Load 1.5771 0.9065

Max Reduction

Realistic Reduction

Dentists
Mercury Source Control and Pollution Prevention Program Evaluation

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29

Using this table it was possible to develop two reduction estimates, one for pollution prevention/ 

voluntary programs and another for source control (semi-regulatory) programs, as discussed 

previously. The pollution prevention (voluntary) reduction estimates included reduction 

strategies for the top three residential sources, top two commercial sources, and industrial 

sources. Human waste is considered uncontrollable, except to the extent that less amalgam 

filling are placed by dentists. For commercial sources, dentists were the major commercial 

contributors to the influent load for every agency. The pollution prevention (voluntary) 

reduction strategy used for dentists was to encourage BMPs or require amalgam separators for 

agencies that had tried BMPs. The source control method of estimating mercury reduction 

assumes that control strategies are implemented for all commercial, residential and industrial 

sources and that dentists have a regulatory program. The subsequent pollution prevention and 

source control percent reductions for each agency can be found in Table 17. The average 

pollution prevention reduction is 26% while the average source control reduction is 37%.

Table 17. Pollution Prevention and Source Control Reduction

POTW Flow 

(mgd)

Measured 

Influent Load 

(g/d)

% Reduction 

Pollution 

Prevention

% Reduction 

Source 

Control

NEORSD - e 104.1 56.3 24% 39%

NEORSD - s 109.5 133 20% 29%

NEORSD - w 31.1 13.3 29% 44%

Palo Alto 28 23.2 14% 14%

SRCSD 157 135 23% 32%

Westbrook 2.51 2.7 58% 90%

WLSSD 39 15.6 12% 12%

The estimated reductions for Palo Alto and WLSSD are low because these agencies have mature 

pollution prevention programs and have implemented many of the strategies listed in Table 12. 

Therefore, few additional reduction opportunities exist in their service areas.

Estimate Resulting Effluent Concentrations

After estimating the reduction of mercury in each plant’s influent, resulting effluent 

concentrations were calculated using each plant’s average reported removal efficiency. As 

mentioned previously, this is an optimistic assumption because as influent concentrations get 

lower it is likely that removal efficiencies decrease as well. Tables 18 and 19 report the reduced 

influent and effluent concentrations for the pollution prevention and source control programs, 

respectively. They also provide a comparison of the reduced effluent concentrations (“Pollution 

Prevention/Source Control Reduced Ave. Effluent”) to the effluent concentrations prior to source 

control (“Ave. Unreduced Effluent”).
Mercury Source Control and Pollution Prevention Program Evaluation

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Table 18. Resulting Concentrations Using Pollution Prevention/Voluntary Estimates

POTW Flow 

(mgd)

Ave. Measured 

Effluent + 

Biosolids 

(ppt)

Pollution 

Prevention 

Reduced 

Influent

(ppt)

Ave. Plant 

Removal 

Efficiency

Pollution 

Prevention 

Reduced Ave. 

Effluent 

(ppt)

Ave. 

Unreduced 

Effluent 

(ppt)

NEORSD - e 104.1 143 108 97% 3.25 3.56

NEORSD - s 109.5 302 209 99% 2.09 3.17

NEORSD - w 31.1 139 98.1 97% 2.94 3.11

Palo Alto 28 246 212 97% 5.32 5.50

SRCSD 157 199 154 96% 6.17 9.00

Westbrook 2.51 166 70.4 98% 1.41 6.90

WLSSD 39 115 102 96% 4.07 4.70

Table 19. Resulting Concentrations Using Source Control/Regulatory Estimates

POTW Flow 

(mgd)

Ave. Measured 

Effluent + 

Biosolids 

(ppt)

Source Control 

Reduced 

Influent 

(ppt)

Ave. Plant 

Removal 

Efficiency

Source Control 

Reduced Ave. 

Effluent 

(ppt)

Ave. 

Unreduced 

Effluent 

 (ppt)

NEORSD - e 104.1 143 87.8 97% 2.63 3.56

NEORSD - s 109.5 302 162 99% 1.62 3.17

NEORSD - w 31.1 139 78.5 97% 2.35 3.11

Palo Alto 28 246 211 97% 5.29 5.50

SRCSD 157 199 135 96% 5.39 9.00

Westbrook 2.51 166 16.3 98% 0.33 6.90

WLSSD 39 115 102 96% 4.06 4.70

Assess Potential Compliance

Using the reduced effluent concentrations it was possible to compare the new, reduced 

concentrations to the range of mercury criteria. Tables 20 and 21 list the number of plants (out 

of 7) that meet the mercury criteria based on no pollution prevention, pollution 

prevention/voluntary and source control/regulatory. Using average effluent concentrations, all 

agencies meet the 18 ppt criteria (and the 50% margin of error value, 9 ppt; see below for 

discussion) before any pollution prevention or source control is implemented. Pollution 

prevention and source control help one agency meet the 7.8 ppt criteria. Source 

control/regulatory also helps one agency meet the 1.3 ppt effluent criteria. None of the agencies 

are able to meet the 0.2 ppt criteria with pollution prevention or source control alone. Basing 

compliance on reductions achieved compared to maximum effluent concentrations for each 

plant, only 4 plants have maximum effluent levels prior to source control or pollution prevention 

that meet the 18 ppt criteria. Pollution prevention helps one agency and source control helps two 

agencies comply with the 18 ppt criteria. Both programs help two agencies comply with the 7.8 

ppt criteria. No agencies are able to meet the 1.3 ppt or 0.2 ppt criteria when maximum effluent 

concentrations are considered. 
Mercury Source Control and Pollution Prevention Program Evaluation

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31

Some of the reduced effluent concentrations are very close to the criteria used for evaluation as 

shown in Tables 20 and 21. It is important to recognize that plants do not operate to just meet 

criteria, there must be a safety factor. Effluent mercury levels resulting from reductions achieved 

through source control and pollution prevention are based on average values. Plants would be 

more likely to operate within a margin of safety to assure compliance. In some parts of the 

country, NPDES permit effluent limits are implemented as values never to be exceeded. Even 

one violation may result in stiff fines and other penalties. Therefore, plants designed to comply 

with these regulations are designed with margins of safety that will assure compliance at least 

99.9% of the time (corresponding to an exceedance once in three years)(Tschobanoglous, 2001). 

A less extreme approximation of the need to operate with a margin of safety to assure 

compliance is to assume that a plant would operate with a 50% margin of safety. Therefore, in 

addition to the number of plants meeting a criteria by comparing effluent values directly to water 

quality criteria in Tables 20 and 21, effluent levels are compared to values set at half the criteria. 

The second column of each set shows the number of agencies meeting a mercury level set at half 

the criteria to account for a 50% margin of safety.

Table 20. Number of Agencies Meeting Criteria and 50% Factor of Safety Based on 

Average Effluent Concentrations (Out of 7)

Criteria 18 

ppt

9 

ppt

7.8 

ppt

3.9 

ppt

1.3 

ppt

0.65 

ppt

0.2 

ppt

0.1 

ppt

No Program 7 7 6 3 0 0 0 0

Pollution Prevention 7 7 7 4 0 0 0 0

Source Control 7 7 7 4 1 1 0 0

Table 21. Number of Agencies Meeting Criteria and 50% Factor of Safety Based on 

Maximum Effluent Concentrations (Out of 7)

Criteria 18 

ppt

9 

ppt

7.8 

ppt

3.9 

ppt

1.3 

ppt

0.65 

ppt

0.2 

ppt

0.1 

ppt

No Program 4 2 2 0 0 0 0 0

Pollution Prevention 5 4 4 1 0 0 0 0

Source Control 6 4 4 2 0 0 0 0

Estimate Changes in Biosolids Mercury Levels

The biosolids concentrations after pollution prevention or source control were calculated using 

the resulting influent and effluent concentrations (influent – effluent = biosolids). Table 22 

shows the change in biosolids mercury levels from no pollution prevention to pollution 

prevention to source control. Pollution prevention and source control are able to reduce 

concentrations of mercury in biosolids by 11 – 90 %. It is possible that even more biosolids 

mercury reduction may be achieved as a result of pollution prevention and source control if the 

implemented practices reduce substantially the amount of particulate and solid materials 
Mercury Source Control and Pollution Prevention Program Evaluation

Final Report

32

discharged. Since particulate mercury that reaches the plant influent is more likely to end up in 

the biosolids than in the effluent. 

Table 22. Estimated Biosolids Mercury Levels

Biosolids Concentration (grams/day)

POTW

No P2 Pollution 

Prevention

Source 

Control

NEORSD - e 55.0 41.4 33.5

NEORSD - s 124 85.6 66.5

NEORSD - w 16.0 11.2 8.97

Palo Alto 25.2 21.9 21.8

SRCSD 113 87.9 76.8

Westbrook 1.51 0.66 0.15

WLSSD 16.3 14.4 14.4

Determine Costs Associated with Compliance

The potential cost associated with compliance for each plant was determined as follows. The 

reduction needed to achieve an effluent level of 1.3 ppt was determined based on the maximum 

observed effluent concentration for each plant. The cost to achieve the estimated reduction was 

determined using the cost estimates for pollution prevention and source control programs 

described in the Procedure section. Any additional reduction needed to meet 1.3 ppt was 

assumed to be accomplished through additional treatment, the cost of which was estimated as 

described in the Procedure section. The resulting cost calculations are shown in Tables 23 and 

24.

Table 23. Pollution Prevention Using Maximum Effluent Concentrations for Cost 

Calculations

POTW

Ave. Op. 

Size 

(MGD)

Max 

Eff. 

(ppt)

Reduction 

to achieve 

1.3 ppt

Reduction 

thru 

Pollution 

Prevention

Reduction 

thru 

Treatment 

after 

Pollution 

Prevention 

Annual 

Pollution 

Prevention 

Cost 

($1000)

Annual 

Treatment 

Cost ($1000) 

– With 

Pollution 

Prevention 

Annual 

Treatment 

Cost ($1000) 

– No 

Pollution 

Prevention

NEORSD-E 104.07 9.54 86% 24.3% 62.1% $350 $ 150,017 $ 200,023

NEORSD-S 109.49 5.84 78% 19.6% 58.1% $350 $ 157,830 $ 210,440

NEORSD-W 31.07 5.03 74% 29.4% 44.7% $300 $ 29,858 $ 44,787

Palo Alto 28 18.3 93% 13.8% 79.1% $250 $ 53,816 $ 53,816

SRCSD 157 24.9 95% 22.5% 72.2% $350 $ 226,316 $ 301,754

Westbrook 2.51 16.9 92% 57.5% 34.8% $250 $ 2,412 $ 4,824

WLSSD 39 29 96% 11.5% 84.0% $300 $ 74,958 $ 74,958
Mercury Source Control and Pollution Prevention Program Evaluation

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33

Table 24. Source Control Using Maximum Effluent Concentrations for Cost Calculations

POTW

Ave. Op. 

Size 

(MGD)

Max 

Eff. 

(ppt)

Reduction 

to achieve 

1.3 ppt

Reduction 

thru Source 

Control

Reduction 

thru 

Treatment 

after Source 

Control

Annual 

Source 

Control 

Cost 

($1000)

Annual 

Treatment 

Cost ($1000) 

- with Source 

Control

Annual 

Treatment 

Cost ($1000) 

- No P2

NEORSD-E 104.07 9.54 86% 38.6% 47.8% $700 $ 100,011 $ 200,023

NEORSD-S 109.49 5.84 78% 28.9% 48.9% $700 $ 105,220 $ 210,440

NEORSD-W 31.07 5.03 74% 43.5% 30.6% $600 $ 29,858 $ 44,787

Palo Alto 28 18.3 93% 14.3% 78.6% $300 $ 53,816 $ 53,816

SRCSD 157 24.9 95% 32.3% 62.4% $600 $ 226,316 $ 301,754

Westbrook 2.51 16.9 92% 90.1% 2.2% $550 $ 1,206 $ 4,824

WLSSD 39 29 96% 11.7% 83.9% $450 $ 74,958 $ 74,958

Sensitivity Analysis

The impacts of the assumptions made in the above analysis were assessed in several ways. One 

approach was to vary the load values used for human waste and dental discharges to evaluate the 

impact of these numbers on the results. Subsequent sections provide details on the impacts of 

varying the school loading contribution and how a probability-based model was used to assess 

the impacts of the assumptions.

Variation of Dental Discharge and Human Waste Values 

The impact of the load values used for dental and human waste estimates was assessed as 

follows. Dental values were varied from 0.035 – 0.15 g/dentist/day to encompass the range of 

dental values found in the literature. Similarly, human waste values were varied from 11 – 43.6 

μg/person/day. The cases examined are shown in Table 25.

Table 25. Scenarios used to test dental and human waste assumptions

Dental Discharge Estimate 

(g/dentist/day)

Human Waste Amalgam Estimate 

(μg /person/day)

0.056* 17.2*

0.035 11

0.035 43.6

0.15 11

0.15 43.6

*Base case

These values were carried through the reduction calculations to see the impact of using each of 

these scenarios on mass balance closure, influent reduction, effluent concentration, compliance 

and cost. Except for the mass balance closures, the values for human waste did not affect the 

calculation. Trends associated with varying these values were the same for the pollution 

prevention scenario and the source control scenario. Table 26 shows selected results for the 

pollution prevention scenario. More detailed results can be found in Appendix D.
Mercury Source Control and Pollution Prevention Program Evaluation

Final Report

34

Mass balance closures ranged from 96% to 192% when the high dental discharge number was 

used (i.e., 0.15 g/dentist/day). Using the 0.035/11 scenario resulted in low mass balance closures 

ranging from 56.5% to 77%. The mass balances that stayed closest to 100% closure were for the 

base case and the 0.035/43.6 scenario.

Estimated influent reductions ranged from a low of 7% to greater than 100% reduction. 

Reductions corresponded to the dental value used with much higher reductions seen when the 

0.15 value was used. Reductions exceeding 100% were only seen when the high dental value 

was used. Similarly, variation in resulting influent and effluent concentrations also corresponded 

to the dental value used. In some cases, the use of the 0.15 g/dentist/day resulted in negative 

influent and effluent concentrations.

Compliance assessments were not impacted significantly by the scenarios. However, 

compliance did result slightly more often in the cases where 0.15 g/dentist/day was used as the 

assumed dental loading.

Treatment costs varied only slightly from case to case. The assumptions only had significant 

impact in those situations where no treatment was needed to achieve compliance. It should be 

noted that for 4 of the 6 situations where no treatment was necessary, the estimated effluent 

concentration was less than zero.

Figure 8 compares the average relative loadings from different sources for the different 

scenarios. Dentists were the largest source in every case, regardless of the loading values used. 

However, the percent of influent load attributed to dentists varied from approximately 25% to 

over 100%, depending on the value used for dentists. The final value used for this study resulted 

in dentists contributing on average 35% of the influent load. This seems plausible in that dentists 

are determined to be the main contributor to influent loading of mercury without the estimate 

being greater than 100% of influent mercury. Human waste contribution did not vary greatly 

between scenarios. Average contribution to influent loading ranged from 8 – 18%, depending on 

the value used for human waste loading. The final value used accounted for on average 13% of 

influent loading.

Table 26. Results of Varying the Dental and Human Waste Values 

(g/dentist/day, μg /person/day)

Percent Closure (Estimated / Measured)

POTW 0.056, 17.2 0.035, 11 0.035, 43.6 0.15, 11 0.15, 43.6

NEORSD-e 73% 56.5% 71.6% 129% 145%

NEORSD-s 88% 70.3% 88.5% 158% 177%

NEORSD-w 98% 77.2% 97.0% 172% 192%

Palo Alto 87% 66.1% 93.0% 150% 177%

SRCSD 65% 54.2% 71.5% 96.8% 114%

Westbrook 90% 68.5% 80.3% 175% 187%

WLSSD 75% 58.8% 71.7% 132% 145%
Mercury Source Control and Pollution Prevention Program Evaluation

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35

Table 26. (cont’d.)

Percent Reduction due to Pollution Prevention/Voluntary

POTW 0.056, 17.2 0.035, 

11/43.6

0.15, 

11/43.6

NEORSD-e 24% 17% 55%

NEORSD-s 20% 15% 41%

NEORSD-w 29% 22% 62%

Palo Alto 14% 9% 34%

SRCSD 23% 18% 43%

Westbrook 58% 40% 135%

WLSSD 12% 7% 30%

Reduced Effluent Concentration due to Pollution Prevention/Voluntary (ppt)

POTW 0.056, 17.2 0.035, 

11/43.6

0.15, 

11/43.6

NEORSD-e 3.25 3.54 1.92

NEORSD-s 2.09 2.32 1.05

NEORSD-w 2.94 3.25 1.57

Palo Alto 5.32 5.61 4.06

SRCSD 6.17 6.53 4.52

Westbrook 1.41 1.98 -1.16

WLSSD 4.07 4.26 3.22

Number of Agencies Meeting 6 ppt Criteria Based on Average Effluent

POTW 0.056, 17.2 0.035, 

11/43.6

0.15, 

11/43.6

Nothing 5 5 5

Pollution Prevention 6 6 7

Source Control 7 7 7

Number of Agencies Meeting 1.3 ppt Criteria Based on Average Effluent

POTW 0.056, 17.2 0.035, 

11/43.6

0.15, 

11/43.6

Nothing 0 0 0

Pollution Prevention 0 0 2

Source Control 1 1 4

Annual Treatment Costs With Pollution Prevention/Voluntary Maximum Effluent ($1000)

POTW 0.056, 17.2 0.035, 

11/43.6

0.15, 

11/43.6

NEORSD-e $ 150,017 $ 150,017 $ 100,011

NEORSD-s $ 157,830 $ 157,830 $ 105,220

NEORSD-w $ 29,858 $ 44,787 $ 14,929

Palo Alto $ 53,816 $ 53,816 $ 40,362

SRCSD $ 226,316 $ 226,316 $ 0

Westbrook $ 2,412 $ 4,824 $ 3,618

WLSSD $ 74,958 $ 74,958 $ 56,219
Mercury Source Control and Pollution Prevention Program Evaluation

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36

Figure 8. Average Relative Contributions of Mercury Sources

(g/dentist/day, μg /person/day)

0

20

40

60

80

100

Human Waste-Amalgam

Household Products

Laundry Graywater

Dentists

Medical Clinics

Vehicle Service

Hospitals

Universities

Secondary Schools

Laboratories

0.035 / 11

% of Influent Load

0

20

40

60

80

100

Human Waste-Amalgam

Household Products

Laundry Graywater

Dentists

Medical Clinics

Vehicle Service

Hospitals

Universities

Secondary Schools

Laboratories

0.035 / 43.6

% of Influent Load

0

20

40

60

80

100

Human Waste-Amalgam

Household Products

Laundry Graywater

Dentists

Medical Clinics

Vehicle Service

Hospitals

Universities

Secondary Schools

Laboratories

0.15 / 11

% of Influent Load

0

20

40

60

80

100

Human Waste-Amalgam

Household Products

Laundry Graywater

Dentists

Medical Clinics

Vehicle Service

Hospitals

Universities

Secondary Schools

Laboratories

0.15 / 43.6

% of Influent Load

0

5

10

15

20

25

30

35

40

Human Waste-Amalgam

Household Products

Laundry Graywater

Dentists

Medical ClinicsVehicle Service

Hospitals

Universities

Secondary Schools

Laboratories

0.056/17.2 (Base Case)

% of Influent Load
Mercury Source Control and Pollution Prevention Program Evaluation

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37

Influence of Secondary School Values

It has been suggested that secondary schools may release as much mercury as hospitals, even 

though the limited data available for this study showed schools to release approximately 0.3 

g/day to the sewers. Increasing the value used for schools in the loading calculations to be the 

same as the hospital value (4.39 g/day) produced an average change in secondary school 

contribution to influent loading from 0.48% to 7.00%. The percent contribution to influent 

loading from commercial sources did not change drastically with the increased loading from 

schools (Table 27). However, when examining the top three sources of mercury for each plant, 

secondary schools changed the distribution significantly (Figure 9). In the original calculations, 

secondary schools were not in the top three commercial sources of mercury, only dentists, 

hospitals, medical clinics and vehicle service stations contributed. When the increased loading 

from secondary schools was introduced, the hospital and medical clinic influence decreased as 

secondary schools were the second biggest source in 3 of 7 plants and the third biggest source in 

2 of 7 plants. The change in maximum reduction possible (source control reduction) upon using 

the higher number for schools was not significant enough to change the number of plants able to 

meet water quality criteria using source control and pollution prevention except at Westbrook 

(Table 28). The change in criteria met at Westbrook is not necessarily a true representation due 

to the fact that source control reduction (with schools at 4.39 g/day) is 103%. This produces a 

less than zero grams/day influent concentration.

Table 27. Estimated Percent Contribution to Influent Loading from Commercial Sources

POTW Schools = 

0.3 g/day

Schools = 

4.39 g/day

NEORSD-e 48% 52%

NEORSD-s 27% 29%

NEORSD-w 62% 65%

Palo Alto 51% 57%

SRCSD 36% 36%

Westbrook 72% 96%

WLSSD 50% 57%
Mercury Source Control and Pollution Prevention Program Evaluation

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38

Figure 9. Change in Top Three Commercial Sources

Table 28. Change in Source Control/Regulatory Reduction (g/day) Based on Varying 

Secondary School Influent Mercury Concentrations

POTW Schools = 

0.3 g/day

Lowest 

Effluent 

Criteria Met 

Schools = 

4.39 g/day

Lowest 

Effluent 

Criteria Met 

NEORSD-e 21.8 7.8 22.5 7.8

NEORSD-s 36.0 7.8 36.8 7.8

NEORSD-w 7.1 7.8 7.2 7.8

Palo Alto 3.7 7.8 3.7 7.8

SRCSD 38.4 7.8 39.4 7.8

Westbrook 1.4 1.3 1.6 0.2

WLSSD 2.0 7.8 2.3 7.8

Figure 10. Elevated Secondary School Value

0

5

10

15

20

25

30

35

40

Human Waste-Amalgam

Household Products

Laundry Graywater

Dentists

Medical ClinicsVehicle Service

Hospitals

Universities

Secondary Schools

Laboratories

Secondary School = 4.39 ug/L

% of Influent Load

0 1 2 3 4 5 6 7

First Second Third

Schools = 4.39 g/day

Dentists

Hospitals

Medical Clinics

Vehicle Service

Secondary Schools

Number o f POTWS

Rank
Mercury Source Control and Pollution Prevention Program Evaluation

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39

A few wastewater treatment authorities have attempted to identify their most significant sources 

of mercury in treatment plant influent separately from this study. Their estimated source loading 

breakdowns are shown in Figure 11 for comparison. Please note that these source loading 

estimates are just a few examples of the potential variation from plant to plant.

Figure 11. Influent Mercury Source Pies

Probability-Based Model

The impact of the assumptions made for the analysis were also assessed by estimating 

uncertainty and confidence limits for mercury reductions in influent and effluent through 

implementation of different mercury reduction strategies.

Probability-based modeling procedures were applied to the reduction estimates previously 

developed. The basic calculation of loads, load reductions, and influent and effluent 

concentrations were performed as described previously in this report. Loading values for 

specific mercury sources were the same as described previously, unless noted. Confidence limits 

for mercury concentrations and percent reductions in influent and effluent were estimated by 

incorporating variability for the following values in the reduction model:

• Dental loads. Variance in mean mercury concentrations from dentists is estimated by 

resampling (i.e., using randomly selected values from the entire data set for each iteration of 

the calculation) the distribution of mean mercury loads (g/dentist/day) for all dentists 

sampled in the SF 1992, SF 1993, NEORSD 1997, and SF 2000 studies. 

Palo Alto (1997)

Residents

46%

Unknown Sources

7%

Other Known Sources

1% Stanford University

3%

Employee-Related 

Human Waste

3%

Dentists

9%

Water Supply

22%

Permitted Industries

6%

Storm Water

3%

San Francisco (2000)

Other 

Industrial/Commercial

2%

Residential

43%

Schools

3%

Hospitals

3%

Other

20%

Dentists

29%

MWRA (1997)

Dental Offices

13% Septage

<1%

Corrosion

<1%

Water Supply

<1%

Infiltration

31%

DITP Recycle

7%

Residential Sewage

13%

Inflow

11%

Unknown Commercial

19%

Permitted Industries

3%

WLSSD (1997)

Unknown

34%

Surveyed Businesses 

(dentists, hopsitals, 

universities)

44%

Residential

14%

Permitted Industries

8%
Mercury Source Control and Pollution Prevention Program Evaluation

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40

• Participation factors. Variance in participation for each control strategy (e.g., BMP 

implementation) is estimated based on survey results where available (e.g., dental practices 

survey) and the number of sources in each agency. The variable participation for a control 

strategy is combined with the fixed estimate of mercury load reduction associated with

implementing each specific control strategy to provide the total reduction in mercury loads.

• Average influent and effluent concentrations. Variance of 12-month average influent and 

effluent mercury concentrations is estimated by resampling the available monitoring data for 

each agency. A comparison between the monitoring data and the model values for influent 

and effluent concentrations is shown in Figures 12 and 13.

• Treatment plant removal efficiency. The probability based model accounted for the 

relationship between influent concentration and removal efficiency. This relationship is 

shown in Figure 14. Variance in mercury removal efficiency for each agency is based on an 

analysis of covariance (ANCOVA) model of influent and effluent data for all 7 agencies. 

The variance is estimated as the standard deviation of the residuals of the ANCOVA model. 

The data used to model these parameters is summarized in Table 29.

The mercury reduction model was run for 500 iterations for each agency and mercury reduction 

scenario (i.e., pollution prevention and source control program implementation). The influent 

and effluent mercury concentrations and percent reductions are recorded for each iteration, and 

the resulting data represent the distribution of mean estimates for each result. Confidence limits 

(95% CL) for each estimate are calculated as the 0.025th and 0.975th percentiles of the set of 

estimates. The accuracy of the model and adequacy of the input data are assessed by comparing 

the effluent and influent concentrations from the model to the distribution of 12-month averages 

estimated from monitoring data for each agency. A summary of the model is provided in Table 

29.

Results

The following results are provided in Appendix E for each agency and mercury reduction 

strategy. An example is shown in Table 30.

• Estimates of mean mercury concentrations in influent and effluent, based on the source load 

model and monitoring data, with 95% CL; and

• Estimates of mean reductions in mercury concentrations (and loads) in influent and effluent 

with 95% CL, based on the source load model.

A comparison of influent mercury levels predicted by the model before and after pollution 

prevention program implementation is shown in Figure 15. A comparison of effluent mercury 

levels predicted by the model before and after pollution prevention program implementation is 

shown in Figure 16. Results for the source control program showed similar variations. Mean 

values predicted by the model for each agency are summarized in Table 31. Average effluent 

reductions predicted by the model are lower than reductions calculated as part of the analysis 

because the model accounted for the relationship between influent concentration and plant 

removal efficiency. As can be seen in the figures, the results predicted by the model give a wide 

range of values for resulting effluent concentrations because of the variability of the data used to 

develop the model. 
Mercury Source Control and Pollution Prevention Program Evaluation

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41

Table 29. Summary of Probability-Based Modeling of Mercury Reductions 

Achievable Through Pollution Prevention and Source Control Strategies 

SOURCE LOADS Fixed 

Estimate

Resample 

Estimate

Fixed 

Estimate

Resample 

Estimate (3)

Fixed 

Estimate

Resample 

Estimate (3)

Dentists X X X

Medical Clinics X (2) (2) X

Vehicle Service X (2) (2) X

Hospitals X (2) (2) X

Universities X (2) (2) X

Human Waste, Amalgam X X X

Human Waste, Dietary X X X

Laundry Graywater X X X

Household Products X X X

Thermometers X X X

Contact Lens Solution X X X

Industrial (4) (4) (4)

INFLUENT DATA

Influent Load

Avg. Hg Concentration

Percent Hg Reduction

Treatment Efficiency

(% Removal)

EFFLUENT DATA

Avg. Hg Concentration

Avg. Percent Hg Reduction

(2) BMP reductions implemented only for 3 largest commercial sources for each agency. 

(1) Can be calculated as resampled estimate based on monitoring data.

(4) Assumed that BMPs for Industrial Hg reduction already implemented for all scenarios. 

(3) Post-BMP loads based on fixed percent reduction and variable participation in BMPs.

Calculation with Model estimates:

(Post-BMP [Hg} - Pre-BMP [Hg]) ÷ Pre-BMP [Hg]

Model Estimate Monitoring Data

Calculation:

• Hg Source Loads

Calculation with Model estimates:

100% x (HgPost-BMP - HgPre-BMP ) ÷ HgPre-BMP

Not Estimated

Resampled 12-month avg. for comparison 

to modeled estimates

Calculation:

• Hg Loads ÷ Mean Plant Discharge

Regression Model with random error; adjusted for each agency:

Ln(1-%Removal) = b Intercept + Ln[HgInf ]•m + b plant + Error St.Dev,

Model Estimate Monitoring Data

Calculation:

Influent Hg x (1 - % removal)

Resampled 12-month avg. for comparison 

to modeled estimates

Pre-Pollution 

Prevention/Source Control 

Implementation

Post-Pollution Prevention 

Implementation

Post-Source Control 

Implementation 
Mercury Source Control and Pollution Prevention Program Evaluation

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42

Table 30. Results of Probability-Based Modeling of Mercury Reductions Achievable 

Through Pollution Prevention and Source Control BMP Implementation Strategies: 

SRCSD.

12-Sample Mean Influent Hg, ng/L %Reduction 12-Sample Mean Effluent Hg, ng/L %Reduction

Monitoring 

Data (1)

Load 

Model,

PreP2/SC

Load 

Model,

P2

Load 

Model,

SC

P2 

Program

SC 

Program

Monitoring 

Data (1)

Load 

Model,

PreP2/SC

Load 

Model,

P2

Load 

Model,

SC

P2 

Program

SC 

Program

Count 500 500 500 500 500 500 500 500 500 500 500 500

Average 198 245 180 174 26.4% 32.6% 8.7 9.7 9.4 9.0 2.4% 3.1%

SE 28.4 30.5 23.5 23.3 4.2% 4.2% 0.6 5.2 5.1 4.4 0.4% 0.5%

LL95 149.7 189.2 138.2 134.3 18.4% 24.6% 7.5 3.2 3.1 3.2 1.6% 2.2%

Median 193.5 243.9 178.5 170.5 26.5% 32.7% 8.6 8.5 8.3 8.0 2.4% 3.1%

UL95 263.8 305.7 227.4 225.6 34.1% 40.3% 10.0 22.4 21.9 19.5 3.3% 4.0%

Min 117.9 156.9 123.1 112.4 15.2% 21.7% 7.1 2.4 2.4 1.7 1.3% 1.9%

Max 303.8 331.4 259.0 250.2 36.3% 44.1% 11.1 40.3 39.5 31.7 3.5% 4.6%

(1) Estimated from resampled monitoring data distribution.

P2 = Pollution Prevention

SC = Source Control
Mercury Source Control and Pollution Prevention Program Evaluation

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43

Figure 12. Influent Levels Based on Monitoring Data and Load Model

Figure 13. Effluent Levels Based on Monitoring Data and Load Model

0

100

200

300

400

500

600

Influent Hg, ng/L

NEORSD-ENEORSD-S

NEORSD-W

PALO ALTO

SRCSD

WESTBROOK

WLSSD

Influent Hg, ng/L, Load Model

Influent Hg, ng/L, Monitoring Data

0

2

4

6

8

10

12

14

16

18

Effluent Hg, ng/L

NEORSD-ENEORSD-S

NEORSD-W

PALO ALTO

SRCSD

WESTBROOK

WLSSD

Effluent Hg, ng/L, Load Model

Effluent Hg, ng/L, Monitoring Data
Mercury Source Control and Pollution Prevention Program Evaluation

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44

Figure 14. Influent Concentration and Removal Efficiency

Figure 15. Influent Reduction Resulting from Pollution Prevention Implementation

-6

-5

-4

-3

-2

-1

0

ln[transmittal]

2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5

ln[Inf Hg]

WLSSD

Westbrook

SRCSD

Palo Alto

NEORSD-W

NEORSD-S

NEORSD-E

Treatment Efficiency: Transmittal of Hg vs. Influent Hg concentration 

Transmittal = (1-% Removal)

0

100

200

300

400

500

600

Influent Hg, ng/L

NEORSD-ENEORSD-S

NEORSD-W

PALO ALTO

SRCSD

WESTBROOK

WLSSD

Influent Hg, ng/L , post-SC

Influent Hg, ng/L, pre-SC

Influent Hg, post-P2/SC

Influent Hg, pre -P2/SC
Mercury Source Control and Pollution Prevention Program Evaluation

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45

Figure 16. Effluent Reduction Resulting from Pollution Prevention Implementation

0

2

4

6

8

10

12

14

16

18

Effluent Hg, ng/L

NEORSD-ENEORSD-S

NEORSD-W

PALO ALTO

SRCSD

WESTBROOK

WLSSD

Effluent Hg, ng/L , post-P2

Effluent Hg, pre Effluent Hg, ng/L, pre-P2 -P2/SC

Effluent Hg, post-P2/SC
Mercury Source Control and Pollution Prevention Program Evaluation

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Table 31. Average Concentrations and Reductions Predicted by Model

Findings

The purpose of this project was to determine if pollution prevention and/or source control 

programs have the potential to achieve the reductions necessary to enable POTWs to comply 

with current and proposed NPDES permit effluent limits for mercury. The analysis conducted 

was based on the use of existing data. However, a variety of assumptions were necessary to 

apply the collected data to the POTWs used as case studies. As a result, this analysis has certain 

limitations. The findings regarding the effectiveness of mercury pollution prevention programs, 

assessment of potential compliance, the impact of the assumptions made, and limitations of the 

analysis are discussed below.

Effectiveness of Mercury Pollution Prevention and Source Control Programs

The effectiveness of mercury pollution prevention and source control programs may be 

considered with respect to the direct benefit of achieving reductions in wastewater influent. 

Mercury pollution prevention and source control programs may also achieve significant 

reductions to other waste streams resulting in overall reductions of mercury entering the 

environment. The benefits to other environmental media were not evaluated quantitatively in 

Post-Pollution Prevention(voluntary) Influent and Effluent Quality

Mean Influent, 

ng/L

Percent 

Reduction

Mean Effluent, 

ng/L

Percent 

Reduction

NEORSD-E 145.9 33.0% 3.1 3.2%

NEORSD-S 181.3 31.5% 3.0 3.0%

NEORSD-W 167.7 28.9% 3.2 2.7%

Palo Alto 244.1 30.3% 4.5 2.8%

SRCSD 243.9 26.5% 8.3 2.4%

Westbrook 313.8 35.9% 3.3 3.5%

WLSSD 101.5 32.6% 8.5 3.1%

Post-Source Control (regulatory) Influent and Effluent Quality

Mean Influent, 

ng/L

Percent 

Reduction

Mean Effluent, 

ng/L

Percent 

Reduction

NEORSD-E 92.7 41.3% 3.2 4.2%

NEORSD-S 117.5 41.3% 3.0 4.2%

NEORSD-W 104.2 43.2% 3.0 4.4%

Palo Alto 136.1 43.1% 4.2 4.4%

SRCSD 170.5 32.7% 8.0 3.1%

Westbrook 131.1 54.5% 2.9 6.1%

WLSSD 68.9 39.4% 8.8 3.9%
Mercury Source Control and Pollution Prevention Program Evaluation

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47

this study but several reduction opportunities were identified. Effectiveness with respect to 

wastewater reductions and benefits to other media are discussed below.

Potential for Wastewater Reductions 

Using the basic scenario described in this report (i.e., setting dental discharges at 0.056 

g/dentist/day and human waste from amalgam at 17 μg/person day), the results of the analysis 

described above indicate the following about wastewater mercury pollution prevention programs.

Influent load reductions for mercury achievable through pollution prevention activities for the 

POTW case studies on average ranged from 12% to 90% depending on the agency’s existing 

pollution prevention efforts and the extent of additional pollution prevention conducted (i.e., 

pollution prevention or source control programs). For agencies like the Palo Alto Regional 

Water Quality Control Plant, Palo Alto, California and the Western Lake Superior Sanitary 

District (WLSSD), Duluth, Minnesota with mature pollution prevention programs, there is not 

much additional reduction available because most strategies have already been implemented. 

For example, both agencies have worked extensively with dentists and have high rates of 

participation/cooperation from the dental community with respect to implementation of 

recommended amalgam management practices. WLSSD has close to 100% cooperation from 

the dental community, so their influent and effluent concentrations used in the analysis reflect 

this level of participation. To project any further mercury reduction, source control strategies 

other than voluntary implementation of best management practices (BMPs) would have to be 

considered (i.e., regulation, and use of amalgam separators).

Average influent mercury concentrations for the POTW case studies prior to the pollution 

prevention considered in this analysis ranged from 106 ng/L to 323 ng/L. Average effluent 

concentrations prior to the pollution prevention considered in this analysis ranged from 3.1 ng/L 

to 9 ng/L. Maximum effluent concentrations ranged from 5 to 29 ng/L. Influent load reductions 

from pollution prevention resulted not only in effluent reductions but also in biosolids 

reductions, which may also have positive implications for POTW operations.

The largest source of mercury in wastewater influent is discharges from dental offices. The next 

largest sources are domestic sources (human waste, household products, and laundry graywater) 

and hospitals. Of the domestic sources, human waste is considered uncontrollable and laundry 

graywater is considered very difficult to effectively control. Household products are controllable 

to the extent that residents can be persuaded to stop using them or to the extent that their 

availability can be restricted through product bans. Legislative efforts to restrict the availability 

of certain mercury containing products may prove effective in reducing discharges from 

household products. The sources with the greatest potential for achieving measurable reductions 

in wastewater influent are dental offices and hospitals.

Benefits to Other Media

Another important benefit of pollution prevention programs, although not quantified in this 

report, is their beneficial impact on other media. Restriction or elimination of mercurycontaining products (e.g., thermometers, thermostats, blood pressure cuffs) will also reduce the 

amount of mercury released to the environment through improper disposal as solid waste or 
Mercury Source Control and Pollution Prevention Program Evaluation

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48

medical waste (and then to landfills, incinerators, or steam autoclaves). Similarly, educating the 

dental community regarding proper disposal of amalgam wastes will reduce the amount of these 

wastes that are transferred to solid waste or infectious waste (which gets incinerated or 

autoclaved). One finding of the San Francisco dental surveys and site inspections was that 

dentists believed that they were properly disposing of scrap amalgam as hazardous waste 

(WERF, 2001). However, the site inspections revealed that many of them were disposing of 

amalgam wastes as biohazardous/medical waste. The result of this was that, while disposal to 

the sewer was prevented, the ultimate release of the mercury would be through incineration to 

the air. As a result of this finding, education of dentists has included the message to dispose of 

amalgam through certified recyclers and not as medical waste. While no additional reductions in 

wastewater are likely to be achieved by this action, the overall release of mercury to the 

environment will be reduced. This reduction depends on the proper recycling mechanism being 

available. Local agencies can help accomplish this by identifying recyclers and providing this 

information to the appropriate businesses.

Other indirect benefits of wastewater source control and pollution prevention programs include 

increasing public awareness of mercury pollution issues and the potential to create partnerships 

with other agencies that have more direct control over certain waste streams and established 

communication vehicles. Increased public awareness may result in more successful legislative 

activity at both the state and federal level. Working with other agencies and businesses (i.e., 

health departments, solid waste programs, air programs, recycling companies, environmental 

organizations, etc.) may result in more widespread communication to both the general public and 

the business community that may result in behavior changes that achieve reductions in 

environmental releases.

The Wisconsin Department of Natural Resources (WDNR) has been working with municipalities 

and is developing a Municipal Mercury Pollutant Minimization Program to help agencies comply 

with the GLI mercury effluent requirements (Case, 2001). The program’s goals include reducing 

mercury use through promotion of alternative products and reducing mercury releases through 

recycling and improved waste management. Program elements include establishing partnerships 

and working with a variety of mercury sources including medical facilities, dental clinics, 

secondary schools, colleges, industry and the general public. Effectiveness measurement is an 

important element of the program. 

The program is based on over 4 years of pilot work with municipal agencies. The pilot work has 

already shown that municipal mercury reduction activities will have benefits beyond wastewater 

reductions. As a result, WDNR is exploring approaches to provide POTWs with credit for 

benefits to other media as an offset against final effluent discharge compliance. Another added 

benefit recognized by WDNR is that outreach activities often reach audiences outside of a 

POTW’s service area. WDNR is exploring approaches to provide some type of credit for this 

benefit as well.

Compliance Assessment

While measurable reductions are expected as a result of mercury pollution prevention programs, 

these reductions do not appear to have a significant impact on a POTW’s ability to comply with 
Mercury Source Control and Pollution Prevention Program Evaluation

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49

the more stringent effluent limits evaluated in this study. However, pollution prevention or 

source control may result in adequate reductions to achieve permit limits under certain 

circumstances (i.e., reduction needed is reasonable, as in the case of achieving the 7.8 ng/L limit 

developed from the fish tissue criterion using default values). For limits based on the CTR (i.e., 

25 ng/L), or other less stringent criteria (i.e., based on fish tissue criterion for rivers and streams, 

17-18 ng/L), the case study POTWs could generally comply prior to implementing pollution 

prevention. For the Great Lakes Criteria (i.e., 1.3 ng/L), none of the POTWs were able to 

comply even after the estimated reductions based on pollution prevention (all voluntary) efforts 

were calculated. One agency was able to comply on the basis of a source control/semiregulatory program. For the intermediate standard of 7.8 ng/L, the two POTWs that could not 

comply prior to pollution prevention were projected to be able to achieve that level after the 

implementation of a source control/semi-regulatory program.

One of the limitations of this study is that it is theoretical in nature. There are very few examples 

of mercury source control programs that have been in place long enough to yield measurable 

results. However, some examples that may give an indication of the potential effectiveness of 

mercury pollution prevention and source control programs include the programs implemented by 

the Palo Alto Regional Water Quality Control Plant, Palo Alto, California, the Western Lake 

Superior Sanitary District (WLSSD), Duluth, Minnesota, and Metropolitan Council 

Environmental Services (MCES), St. Paul, Minnesota, and experiences in Denmark.

As noted previously, WLSSD and Palo Alto have both implemented most, if not all, of the 

recommended pollution prevention strategies described in this analysis. Source control strategies 

that have not been implemented include regulating dentists and requiring amalgam separators. 

Neither of these POTWs is able to consistently achieve effluent concentrations below 3.1 ng/L. 

Palo Alto’s reported maximum and average effluent concentrations were 18.3 ng/L and 5.5 ng/L 

respectively and WLSSD reported maximum and average effluent concentrations of 29 ng/L and 

4.7 ng/L respectively. Therefore, in these two communities pollution prevention has not been 

able to achieve very low mercury effluent levels.

MCES conducted a study, in cooperation with the Minnesota Dental Association, to assess the 

reduction of mercury levels in biosolids resulting from the installation and operation of amalgam 

removal equipment in dental clinics (Anderson, 2001). MCES obtained baseline data for 

mercury loadings in biosolids for two treatment plants (Hastings and Cottage Grove). Amalgam 

removal equipment was then installed in all the dental clinics in the Hastings service area and all 

but one dental clinic in the Cottage Grove service area. Mercury biosolids levels dropped 44% 

and 29% for the Hastings and Cottage Grove treatment plants respectively during the period 

when the removal equipment was in operation at the dental clinics. Because influent and effluent 

monitoring were not conducted for this study, no information is presented regarding the impact 

of amalgam removal equipment on treatment plant effluent levels of mercury. However, 

operation of amalgam removal equipment by dentists appears to have the potential to reduce 

biosolids mercury levels.

In Denmark, several POTWs have required that dentists in their service area to install amalgam 

separators (Arenholt-Bindslev, 1999). Agencies were surveyed in 1999 to assess the 
Mercury Source Control and Pollution Prevention Program Evaluation

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50

effectiveness of this strategy with respect to mercury reductions. Out of 273 counties surveyed, 

174 indicated that amalgam separators had been installed in all dental offices in the service area. 

Of these counties, 45 provided adequate data to calculate reductions in mercury levels in 

treatment plant biosolids after the separators had been installed. Reductions for 33 of the plants 

providing data are compared to initial mercury biosolids levels in Figure 17. Approximately half 

of the agencies observed no statistically significant change in biosolids concentrations after the 

installation of amalgam separators. Reductions ranged from 14% to 80% for those agencies 

experiencing measurable reductions (other than the one value at 14%, the range of the data was 

32% to 80%). There appears to be some correlation between initial biosolids levels (i.e., prior to 

installation of amalgam separators) and reduction achieved. Many of the Danish areas observing 

no significant changes in biosolids concentrations had relatively low initial levels. No data was 

reported regarding effluent levels. However, because of the particulate nature of amalgam, it is 

likely that reductions in effluent were no greater than reductions seen in the biosolids. An 80% 

reduction would not be adequate for most of the agencies in this study to achieve the most 

stringent effluent limits (i.e., 1.3 ng/L or lower). The Danish results indicate that the 

effectiveness of regulation and amalgam separators is highly variable. While significant 

measurable reductions were achieved in some cases, other cases resulted in no significant 

change.

Figure 17. Biosolids Mercury Reductions for 33 Danish Counties After Amalgam 

Separator Installation

0

10

20

30

40

50

60

70

80

90

0 2 4 6 8 10 12 14 16

Initial Biosolids Hg Levels (mg/kg)

% reduction

The controllability of influent sources and the effectiveness of voluntary programs ultimately 

impact a POTW’s ability to meet the more stringent effluent limits. As noted previously, 

pollution prevention is based on voluntary actions. While regulatory approaches may be 

available for commercial sources, they are labor intensive and therefore only cost effective for 

the largest sources (i.e., dentists). Regulatory approaches are not available for residential 

activities because POTWs lack the legal authority to regulate domestic users. In addition, some 

domestic sources are essentially uncontrollable (i.e., human waste). Product bans are one 
Mercury Source Control and Pollution Prevention Program Evaluation

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51

approach being explored in several states, but their impact on wastewater levels of mercury 

remains to be seen. Overall there is a limit to the potential effectiveness of pollution prevention. 

On average, residential sources accounted for approximately 25% of the influent loading. 

Therefore, even if commercial and industrial mercury discharges could be completely 

eliminated, the maximum reduction achievable is about 75%. As noted above, for the more 

stringent effluent limits, reductions greater than 75% are needed for most agencies to 

consistently meet these levels. 

The estimated annual cost of the pollution prevention program ranged from $250,000 to 

$350,000 depending on the size of the service area. The estimated annual cost of the source 

control program ranged from $300,000 to $700,000. Because pollution prevention was not 

adequate to achieve consistent compliance with 1.3 ng/L, additional POTW treatment would also 

be necessary. The annual total cost of this additional treatment ranged from $1.2 to $226 million 

per POTW depending on the size of the POTW and the reduction needed. Interestingly, the cost 

of treatment without pollution prevention was not significantly different, ranging from $4.8 to 

$300 million annually.

Impact of Assumptions

The assumptions that impacted the results most heavily were the values assumed for dental 

discharges and human waste associated with amalgam and the assumptions regarding percentage 

removals through POTWs. While the values assumed for the first two parameters had a 

significant impact on the estimated load reductions and resulting effluent concentrations, they 

did not have a significant impact on the ability of POTWs to comply with effluent limits or the 

estimated cost to comply with these limits. Regardless of the values chosen, dental discharges 

accounted for the largest portion of influent loadings and, therefore, represent the source for 

which pollution prevention and source control efforts would be expected to be most effective 

with respect to measurable reductions. The percent removals of mercury at each plant need to be 

studied in more depth. It is difficult to predict the concentration of mercury in the effluent based 

on the concentration in the influent. As noted in the discussion regarding the probability-based 

model, there is some indication that as influent concentrations decrease, the percent removal in 

the effluent also decreases. The method for determining effluent from influent in this study was 

the most reasonable available method.

Limitations of Analysis

As noted previously, several assumptions were incorporated into the estimate of effluent mercury 

reductions achievable through pollution prevention. These limitations are listed below:

• Dental discharge data is primarily the liquid fraction of mercury measured in the lateral 

leaving the dental facility. While these values were measured as total mercury, they may 

underestimate the amount of mercury that leaves the dental facility each day, because some 

of the mercury (as amalgam) will settle out and may leach back into the water at a later date. 

Other studies, as noted previously, have estimated that larger amounts of mercury may be 

discharged from dental offices. However, for the purposes of this calculation, a conservative 

estimate of the amount of mercury that reaches the treatment plant is used. It is assumed that 

this is best represented by the mercury in the liquid fraction (both smaller amalgam 
Mercury Source Control and Pollution Prevention Program Evaluation

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52

particulates and dissolved) leaving the dental facility but this would need to be confirmed by 

further monitoring and research.

• The mercury levels from human waste are based on measurements of the human waste itself 

rather than the amount in the wastewater stream. These measurements are for total mercury, 

which may overestimate the amount that reaches the treatment plant influent.

• There is some uncertainty regarding total and dissolved mercury measurements and 

analytical techniques used for the measurements made both by the case study POTWs and by 

the agencies conducting analysis of sources that were used in this report. These uncertainties 

may decrease the confidence level associated with the mass balances. For instance, the 7470 

digestion method, typically used for wastewater analysis, does not dissolve larger particles of 

amalgam and, therefore, would not generate an accurate measure of the mercury content. 

This is a concern for samples that are high in amalgam solids. However, the digestions used 

for wastewater dental samples (if they have relatively low solids content) are aggressive 

enough to dissolve the amalgam in the particles in these samples. 

• The uncertainties regarding the form of mercury (i.e., particulate vs. dissolved) may also 

impact the levels of mercury estimated in the POTW influent and effluent and may, 

therefore, affect the mass balance determinations. It may also impact the effectiveness of 

source control programs and other efforts seeking to reduce mercury effluent levels. If 

mercury is reaching the plant as larger particulates, it is likely to be removed in the grit 

chambers or it will enter the biosolids, not the effluent. Source control efforts that remove 

larger solids will not necessarily have much impact on influent and effluent levels. However, 

removal of larger particles still meets the goal of reducing release of mercury into the 

environment. Overall, the form of mercury and how this affects its movement through the 

treatment plant requires further study to accurately predict the relationship between source 

control and effluent reductions. 

Regardless of these limitations, discharges from dentists appear to represent the largest 

contributor to mercury influent levels. Human waste, while a significant source, represents a 

small contribution relative to dentists.

Another limitation of this analysis is the use of average removal efficiencies when calculating 

effluent concentrations based on influent reductions. As noted, there is some indication that 

POTW removal efficiencies will decrease as influent concentration decreases. The probabilitybased model, for example, predicts much lower effluent reductions than influent reductions. A 

better correlation between removal efficiency and influent concentrations could increase the 

accuracy of this analysis.

This report only attempts to quantify mercury reductions in effluent and, to some extent, in 

biosolids. Other reductions in environmental releases of mercury were only evaluated 

qualitatively. It is possible that the reductions in releases to other media are equally significant 

and may merit further evaluation.

It must be recognized that this study was geared towards creating an ‘average’ community, in 

terms of size and potential sources of mercury. Some communities, especially smaller ones, may 
Mercury Source Control and Pollution Prevention Program Evaluation

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53

be more heavily influenced by sources such as schools and laboratories that were considered to 

be a small influence in the ‘average’ community approach.

This report is a theoretical study on the impacts of mercury source control efforts on POTW 

effluents. As noted above, there is very little experimental verification of predicted results 

because few POTWs have conducted extensive mercury source control programs over a long 

enough time period to determine the level of reduction that is achievable. For other pollutants, 

POTWs have found that, over a period of years, pollution prevention and source control can 

achieve significant reduction under the right circumstances (WERF, 2000).

Conclusions

The results of this study indicate that mercury source control and pollution prevention programs 

have the potential to achieve measurable reductions in POTW influent and to have positive 

impacts with respect to reducing other environmental releases of mercury. Source control and 

pollution prevention may also be effective in helping POTWs achieve effluent limits assuming 

the required reduction falls within a specific range. The results of this study indicated that, based 

on the assumptions made, pollution prevention or source control are potentially effective in 

achieving sufficient reductions to enable POTWs to meet effluent limits that are 7.8 ng/L or 

greater. However, if more stringent effluent limits are in effect such as the 3.1 or 1.3 ng/L limits 

that have been imposed on POTWs in the Great Lakes Region, pollution prevention or source 

control with no treatment process modifications will not be effective in achieving these limits. 

Regardless of the potential for meeting effluent limits through pollution prevention and source 

control alone, these efforts have many benefits as described in this report and should be 

considered as an essential tool in any mercury reduction effort. Reduction of mercury at its 

sources will have positive impacts for wastewater influent and biosolids and for other media. 

Pollution prevention efforts targeting sources of mercury should focus on dental offices and 

medical facilities (hospitals) to have the greatest potential for achieving measurable reductions. 

With respect to dental offices, implementation of BMPs, such as good housekeeping and proper 

management of existing filters, should be required as the initial approach. However, if additional 

reductions are needed, regulatory approaches and the required installation of treatment should be 

considered. For hospitals and medical facilities, implementation of BMPs and purchasing 

policies promoting non-mercury containing items has proven effective with respect to reducing 

mercury wastewater discharges from these facilities.

Recommendations

Areas requiring further study to obtain a better understanding of mercury sources and the 

potential for reductions were identified in this report and include:

• Additional study of the relationship between influent mercury concentrations and removal

efficiencies through the treatment plant would help clarify the relationship between influent 

reductions and resulting effluent concentrations. Present data shows that the relationship is 

not linear. Additional study also is needed with respect to the portion of mercury present in 

wastewater in solid form and in liquid form. The form of mercury present in wastewater will 
Mercury Source Control and Pollution Prevention Program Evaluation

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54

have a significant impact on its travel through the treatment process and the reductions that 

are ultimately achievable as a result of source control and pollution prevention efforts. 

• To gain a more complete understanding of mercury sources in wastewater treatment plant 

influent, a more comprehensive effort to assess total mercury discharges from dental offices 

should be conducted. In addition, research that more directly measures mercury in 

wastewater resulting from human wastes should be conducted. 

• To further assess the feasibility of reducing mercury levels in laundry graywater, research 

could be conducted to ascertain the origin of mercury in the graywater (i.e., does it come 

from dirt or clothing dyes).

• Recommended practices for larger sources such as dentists may have a significant impact on 

the magnitudes of reductions achievable by these sources. Certain practices will have greater 

impacts than others will. For example, attention should be given to screenings 

disposal/handling at dental offices. It would be helpful to have a standard protocol for 

disposal/handling and to get cooperation from state agencies to aid in disposal to facilitate 

implementation of BMPs by dentists and other sources.

• Additional monitoring and evaluation of discharges from schools should be conducted to 

determine if this is a significant mercury source. There is some indication that schools with 

laboratories have the potential to discharge significant quantities of mercury. 
Mercury Source Control and Pollution Prevention Program Evaluation

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55

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