STAKEHOLDER MEETING REGARDING REVISIONS TO THE 

UNREGULATED CONTAMINANT MONITORING 

REGULATION 

April 7, 2010 

Crystal City Marriott 

8:30-9:00 Stakeholder Sign-in 

9:00-9:15 Introduction – Logistics and Agenda 

9:15-9:30 Welcome 

9:30-10:00 Overview of the UCMR Program 

10:00-10:30 UCMR 2 Status 

10:30-10:45 BREAK

10:45-11:15 Proposed Changes Between UCMR 2 and UCMR 3 

11:15-11:45 Sampling Design Considerations for UCMR 3 

11:45-12:00 Discussion 

12:00-1:15 LUNCH

1:15-2:45 UCMR 3 Candidate Selections and Rationale 

2:45-3:00 BREAK

3:00-3:30 Approval of Laboratories Supporting UCMR 3 

3:30-4:15 Establishment of Reporting Limits for UCMR 3 

4:15-5:00 Discussion 
Overview of the Unreg

Contaminant Monito

Program

David J. Munch

USEPA, OGWDW, SRM

Technical Support Cent

Cincinnati, Ohio
Overview

• Unregulated Contaminant Mo

(UCM) program 

• Regulatory justification for UC

– Safe Drinking Water Act (SDW– Contaminant Candidate List (C

• Unregulated Contaminant Mo

Regulation (UCMR) 

– UCMR cycles– UCMR implementation
Safe Drinking Wat

• Passed in 1974, amended in 198• Authorized EPA to set enforceabl

standards for contaminants in drinNational Primary Drinking Water (NPDWS)

• Outlined a “sound science” appro

NPDWS development that requireconsideration of: 

– Occurrence Data– Health Effects Data– Cost Benefit Analysis
Unregulated Contaminant M

Regulation

• UCM Rounds 1 (1988-1992, 6

contaminants) & 2 (1993-199contaminants) 

– State drinking water programs 

UCM program

– PWSs serving > 500 people we

to monitor
Safe Drinking Wat

• 1996 SDWA amendments ch

process of developing and reNPDWS

– Contaminant Candidate List – Unregulated Contaminant Mo

Regulation

– Regulatory Determination– Six-Year Review
General Flow of Regulato

Draft CCL

Final CCL

Final Rule 

(NPDWR)

No further action if make decision not to regulate (may develop health advisory). 

Preliminary 

Regulatory 

Determinations

Final Regulatory 

Determinations

Proposed Rule 

(NPDWR) Draft UCMR

Final UCMR

UCMR Monitoring 

Results

At each stage, need increased specificity and confidence 

supporting data used (e.g. health and occurrence).
Contaminant Candid

• SDWA requires EPA to list unregu

contaminants which may require a drinking water regulation in the fut

• Every five years CCL defines unre

contaminants for which EPA needs

– Occurrence data– Analytical methods– Potential health effects– Evaluation of treatment techniques
Contaminant Candid

• EPA considered approximately 7,500 p

chemical and microbial contaminants

• Screening process based on a contam

to occur in public water systems (PWSpotential for public health concerns

• Further detailed evaluations, public inp

judgment and review are the final contaselection tools 

• Final CCL 3 published September 2009

– 104 chemicals or chemical groups and 12 m

contaminants
Unregulated Contaminant M

Regulation

• 1996 Safe Drinking Water Ac

Amendments

– Redesigned the UCM program 

these requirements:

• Monitor no more than 30 contam

year cycle

• Monitor only a representative sam

serving 10,000 or fewer people

• Store analytical results in the Nat

Contaminant Occurrence Databa

• Direct implementation – EPA ma

in partnership with States
Unregulated Contaminant M

Regulation

• Collects occurrence data for s

drinking water contaminants thave health-based standards SDWA

• Develops a list of contaminan

based on the CCL, every five 

• Samples collected from “finis
Unregulated Contaminant M

Regulation

• UCMR groups contaminants 

tiers based on their priority anmethodologies

– Assessment Monitoring (List 1)

• Employs commonly used analytic

– Screening Survey (List 2)

• Uses more recently developed an

techniques

– Pre-Screen Testing (List 3)

• Utilizes new or specialized techn
Unregulated Contaminant M

Regulation

• Occurrence information is use

regulatory decision-making

– Evaluates and prioritizes conta

the CCL

– Supports the Administrator’s de

of whether (or not) to regulate contaminant under the drinking program
First Cycle of UC

• UCMR 1 (2001-2005, 26 contami

– Published in Federal Register (

September 17, 1999

– Required all large PWSs and a 

representative sample of small serving 

10,000 people to mon

contaminants on List 1

– Required a random selection o

and small PWSs to monitor for contaminants on List 2
Second Cycle of U

• UCMR 2 (2007-2011, 25 contami

– Current cycle – monitoring end

December 2010, data review w2011

– More PWSs included under Lis

Survey than for UCMR 1 to prorepresentative results

– Define monitoring schedules to 

Regional compliance efforts
UCMR Implement

• OGWDW, SRMD, Technical Supp

(Cincinnati)

– Review and track PWS applicability 

progress

– Coordinate Laboratory Approval Pro– Provide technical support for Region

PWSs and laboratories

– Coordinate outreach using the Intern

(The UCMR Update), notices and re

– Assist and support Regional complia
UCMR Implement

• OGWDW, SRMD, Technical Supp

(Cincinnati)

– Small PWS support

• Maintain lab and implementation contra

UCMR

• Support sample kit distribution• Responsible for data review and reporti• Prepare data for the NCOD

– Large PWS support

• Extract data from the Safe Drinking Wat

Review System (SDWARS) for evaluatiNCOD

• Support SDWARS reporting system and 
Extended UCMR Implement

• OGWDW, DWPD, Infrastructure B

– Responsible for SDWARS in the Ce

Exchange

• EPA Regional Offices

– Coordinate State partnership agreem– Assist States and PWSs with UCMR 

compliance and enforcement

• Partnering States

– Support various levels of monitoring 
Questions

Thank you
Status of the Second Cyc

Unregulated Contami

Monitoring Regulation (U

Brenda D. Parris

USEPA, OGWDW, SRMD

Technical Support Center

Cincinnati, Ohio
Timeframe of UCM

• August 22, 2005 – Proposal p• January 4, 2007 – Final rule p• 2007 – Early implementation• 2008-2010 – Sampling period • 2011 – Data analysis
UCMR 2 Applica

• Applicability date (June 30, 2005) is dir

the population served by a public wate

• Total PWSs = 4,626

PWS Population Served List 1 

10,000 or fewer 800 randomly selected 

10,001-100,000 All PWSs 2,946 

More than 100,000 All PWSs 400 

* Assessment Monitoring (List 1)* Screening Survey (List 2)
UCMR 2 Monito

• PWSs must monitor during a con

month period between 2008-2010

• Number of times a PWS samples 

related to the sample point source

– Surface water and ground water und

influence of surface water – must mduring their 12-month schedule (sammonths apart)

– Ground water – must monitor twice 

their 12-month schedule (sample fivmonths apart)

• EPA established a monitoring sch

PWSs

– PWSs were provided the opportunity 

pre-determined EPA schedule
UCMR 2 Monito

• Locations where a PWS collects s

directly related to the contaminan

– List 1 – collects samples at their en

distribution system (EPTDS)

• EPTDS – location where finished water 

distribution system

– List 2 – collects samples at their EP

their distribution maximum residenc(DSMRT) for the nitrosamines

• DSMRT – location allows for a sampling 

water in the distribution system
UCMR 2 List 1 Conta

Contaminant Name 

Two Priority Compounds (One Insecticide and On

Dimethoate 

Terbufos sulfone 

Five Flame Retardants

2,2',4,4'-tetrabromodiphenyl ether (BDE-47) 2,2',4,4',5-pentabromodiphenyl ether (BDE-99) 2,2',4,4',5,5'-hexabromobiphenyl (HBB) 2,2',4,4',5,5'-hexabromodiphenyl ether (BDE-153) 2,2',4,4',6-pentabromodiphenyl ether (BDE-100) 

Three Explosives

1,3-dinitrobenzene 

2,4,6-trinitrotoluene (TNT) Hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) 
UCMR 2 List 2 Conta

Contaminant Name 

Three Parent Acetanilides 

Acetochlor Alachlor Meto

Six Acetanilide Degradates 

Acetochlor ethane sulfonic acid (ESA) Alachlor ESAAcetochlor oxanilic acid (OA) Alachlor OA Metolachlor ESA Metolachlor OA

Six Nitrosamines

N-nitroso-diethylamine (NDEA) N-nitroso-dimethylam

(NDMA)

N-nitroso-di-n-butylamine (NDBA) N-nitroso-di-n-propyl

(NDPA)

N-nitroso-methylethylamine (NMEA) N-nitroso-pyrrolidine 
UCMR 2 Report

• Small PWSs serving 10,000 o

people are not responsible foassociated with analysis

– EPA coordinates sample analy

contracted laboratories

• Laboratories e-mail the data to E

– EPA examines the quality cont

and generates reports
UCMR 2 Report

• Large PWSs serving more tha

people are responsible for the associated with analysis

– PWS coordinates sample analy

approved laboratory, and that ldata to the Safe Drinking Wateand Review System (SDWARS 

– PWS reviews and can act upon 

SDWARS 2
Status of Small PWS M

• Monitoring and reporting through 

31, 2009

– 1,055 small PWSs sampled

• 575 List 1• 480 List 2

– 6,897 sample kits issued, including 

recollections

• 2,773 kits for List 1• 4,124 kits for List 2

– 2,535 monitoring reports issued

• A total of 52,756 small PWS results rep

– List 2 sampling mostly complete by 
Status of Large PWS M

• Monitoring and reporting through 

31, 2009 (approximate percentag

– 2,649 large PWSs monitored and re

• 2,649 List 1 • 593 List 2 

– 99% of large PWSs scheduled to sta

by 6/09 have reported data

– 310,477 large PWS results have be

SDWARS

• 191,556 List 1• 118,921 List 2
UCMR 2 Occurrenc

• Updated quarterly and posted in t

Contaminant Occurrence Databa

– www.epa.gov/safewater/databases/

index.html

– Zipped file contains a summary doc

and occurrence data (.txt)

• Data will continue to be added an

corrected upon further review

– Use caution when interpreting the d

dataset is complete
UCMR 2 Results T

• OGWDW has posted PWS result

through January 2010) to the web updates to occur ~quarterly

• 13 of 25 contaminants have not b• Detections above method reportin

– 5 of 6 nitrosamines (predominantly N– 6 of 11 insecticides/pesticides/degra– 1 of 3 explosives
Transitioning from UCMR 2 

• UCMR 2 monitoring activities are 

end in December 2010

• UCMR 2 data will be analyzed in • EPA anticipates proposing UCMR 
Questions

Thank You
Potential Changes Be

UCMR 2 and UCM

Daniel P. Hautman

USEPA, OGWDW, SRM

Technical Support Cente

Cincinnati, Ohio
Overview

• Improvements• Applicability• Data approval• Monitoring plans• Schedules• Conclusions/Questions
Improvement

• EPA learns new and better wa

implement UCMR

– Minor changes are customary be

cycles

• Lessons learned between UCMR 1 

– Define monitoring schedules– Simplify partnership agreements with 

• Lessons learned between UCMR 2 
Applicability Improv

• Base applicability on retail 

– UCMR 2: Applicability based on total popul

served plus those served by any consecutivsystem (PWS) receiving all or part of its “fin

– UCMR 3 potential change: Create a list of 

based solely on retail population according Drinking Water Information System (SDWIS

– Reasons for change:

• Resolve implementation complexities• Refine PWS selection• Improve exposure analysis• Obtain a more accurate representation of dr

consecutive systems
Applicability Improv

• Eliminate issues regarding pur

water

– UCMR 2: PWSs that purchase 100% 

were not subject to UCMR

– UCMR 3 potential change: PWSs t

100% of their water will be subject to all purchased sources will be considentry points that will require monitor

– Reason for change:

• Define more accurate sample point loca

States do not include their suppliers’ eninventory

• Improve exposure analysis• Obtain a more accurate representation 

consecutive systems
Data Approval Impro

• Require PWSs to explain rej

in the Safe Drinking Water Aand Review System (SDWA

– UCMR 2: PWSs are allowed to rejec

SDWARS but were not required to efor rejecting it

– UCMR 3 potential change: When d

rejected in SDWARS, PWSs must adexplaining why data were not approv

– Reasons for change:

• Data could be rejected by accident or wi
Monitoring Plan Impro

• Refine the approach to Ground 

Representative Monitoring Plan

– UCMR 2: GWRMPs proposed base

location, contamination susceptibility similarities of groundwater quality wsampling point required

– UCMR 3 potential change: The pro

must be the highest annual volume most consistently active in the repreShould the representative well go ofalternative location must be approve

– Reasons for change:

• Well selected may be seasonal or low u• Well may become permanently down pr
Schedule Improve

• Clarify terms for schedule 

adjustments

– UCMR 2: Schedules should be adju

monitoring plans but often PWSs do such changes

– UCMR 3 potential change: In SDW

that schedules must be adjusted basample point’s availability

• Seasonal location• Routine or emergency maintenance 

– Reason for change:

• EPA’s defined schedule may not match 

where a location may be temporarily do
Schedule Improve

• Clarify the difference betwe

and sample point schedule

– UCMR 2: Selecting different schedu

sample points was an implied option

– UCMR 3 potential change: In the S

directions, identify available schedu

• Remind PWSs that their sample points 

different schedules 

– Reasons for change:

• PWS could more effectively distribute re

three-year budget
Questions

Thank you
UCMR 3 

Sampling Design Consid

George Hallberg

Principal

The Cadmus Group, Inc.

Watertown, Massachusett
Overview

• Regulatory background for th

Unregulated Contaminant MoRegulation (UCMR) sampling 

• UCMR 3 sampling design con• Approach to tiered monitoring

– Assessment Monitoring (List 1)– Screening Survey (List 2)– Pre-Screen Testing (List 3)

• Implementation consideration
UCMR Backgroun

• UCMR program designed for Safe Dri

Act (SDWA) specifications 

• Under §1445(a)(2)(A) of SDWA, as am

1996, EPA required to:

– “vary the frequency and schedule for mon

on the number of persons served by the ssource of supply, and the contaminants lik

– ensure “that only a representative sample 

serving 10,000 persons or fewer are requand 

– “pay the reasonable cost of such testing a

analysis...” for small systems
PWS Types

• Community water system

– Public Water System (PWS) that su

the same population year-round

• Non-transient non-community wa

– PWS that supplies water to at least 

people at least six months per year, round

• Schools

• Transient non-community water s

– PWS that provides water where peo

remain for long periods of time

• Gas stations and campgrounds• Typically not applicable to UCMR, may 
PWS Sizes

• Small PWSs serve 10,000 or 

– Very small: 25-500 people– Small: 501-3,300– Medium: 3,301-10,000

• Large PWSs serve 10,001 to 

people

• Very large PWSs serve over 

people
UCMR 3 

Sampling Design Conside

• Based on sampling and stat

design used in UCMR 1 and 

– Reviewed with stakeholders– Peer reviewed– Two rounds of public commen
UCMR 3 

Sampling Design Conside

Data Quality Objectives• Unbiased national exposure estim

margin of error

• Account for differential occurrence• Stratify across system size and so

type to account for differences in vand management capacity

• Multiple sample events over multip

address temporal variability

• Allocation across states proportion

population served; at least two per 
UCMR 3 Assessment Mo

(List 1): Statistical App

• May maintain same statistical design 

Assessment Monitoring used in UCM

– Nationally representative sample of 800 sm– Census of large water systems– Consider including systems that purchase 

water

• Small system statistical sample comb

large system census data provides a for assessing contaminant occurrenc
Sample Allocation for Small 

Assessment Monitoring 

Size 

Category

Ground 

Water 

Systems

Surface 

Water 

Systems

500 and under 104

5 

501 to 3,300 259 48 

3,301 to 10,000 255 129 

Total 618 182 
UCMR 3 Screening Survey 

Statistical Approac

• Designed to ensure the data ca

to support regulatory determinarule development (if warranted)

• Account for possible laboratory 

issues related to use of recently or technically complex methods
UCMR 3 Screening Surve

Statistical Approac

• Considering similar approach as 

– National sample of 800 systems, a

across systems serving 100,000 o

• Small system (serving 10,000 or fewer) sa

overlap with Assessment Monitoring

• Sample again allocated across strata of sy

source water type 

• UCMR 3 proposing to include systems tha

of water

– Census of all systems serving 100,

(~400 systems)

• Adds further confidence in the sampling re

census of the largest systems

• Total number of systems ~1,2
UCMR Pre-Screen Testi

• Envisioned for use with metho

were in the early stages of devand/or very specialized (such for viruses or DNA/microchips

• Might be conducted by limited 

PWSs identified as vulnerable and/or State agencies) 

• No Pre-Screen Testing was sc

under UCMR 1 and 2
UCMR 3 Implementation Con

• Same sampling frequency for 

Assessment Monitoring (AM) aScreening Survey (SS) used in 

– Surface water systems (includin

groundwater under the direct infsurface water) would sample fouduring their year of monitoring

– Ground water systems would sa

times during their year of monito
UCMR 3 Implementation Con

• Same monitoring schedule for 

SS used in UCMR 2

– Months assigned to ensure coverage 

vulnerability and variability

– System monitoring spread across 3-y

provide temporal coverage and to aclab capacity 

• Year and months of monitoring assigned to sm• Large systems can re-define their year and m

monitoring with EPA coordination
UCMR 3 Implementation Con

• Sampling locations for AM an

chemicals

– All chemicals would be sample

points to the distribution system

– Metals proposed would also be 

the maximum residence time (Min the distribution systems
Questions

Thank You
UCMR 3 Potential Me

David J. Munch

USEPA, OGWDW, SRM

Technical Support Cente

Cincinnati, Ohio
Pharmaceutica

EPA Method 539 (LC/MS/MS), for

Determination of Hormones in Drinking Water 

Chromatography Tandem Mass Spectro

Location: EPTDS

• 17-

α-Ethynylestradiol

• 17-

β-Estradiol

• Equilin• Estriol• Estrone• Testosterone• 4-Androstene-3,17-dione
Single Contaminant 

EPA Method 522 (GC/MS), 

Determination of 1,4-Dioxane in Drinking Water 

Extraction and Gas Chromatography/Mass Sp

Selective Ion Monitoring, Version 

Location: EPTDS

• 1,4-Dioxane
Volatile Organic Com

EPA Method 524.3 (GC/MS), 

Measurement of Purgeable Organic Compounds in W

Column Gas Chromatography/Mass Spectrometr

Location: EPTDS

• 1,1-Dichloroethane• 1,2,3-Trichloropropane• 1,3-Butadiene• Bromochloromethane• Chlorodifluoromethane

• Chlorom• Methyl b• n-Propyl• sec-Buty
Metals

EPA Method 200.8 (ICP/MS), 

Determination of Trace Elements in Waters by Indu

Plasma - Mass Spectrometry, Version 

Location: EPTDS, MR

• Cobalt• Molybdenum• Strontium• Vanadium
Single Contaminant 

EPA Method 300.1 (IC), 1

Determination of Inorganic Anions in Drinking 

Chromatography, Revision 1.

Location: EPTDS

• Chlorate

– Gaseous chlorine– Potassium hypochlorite– Sodium hypochlorite
Perfluorinated Che

EPA Method 537 (LC/MS/MS)

Determination of Selected Perfluorinated Alkyl Acids 

by Solid Phase Extraction and Liquid Chromatograp

Spectrometry, Version 1.1

Location: EPTDS

• Perfluorooctane sulfonate (PFOS)• Perfluorooctanoic acid (PFOA)• Perfluorohexane sulfonic acid (PFHxS)• Perfluoroheptanoic acid (PFHpA)• Perfluorononanoic acid (PFNA)• Perfluorobutane sulfonic acid (PFBS)
Microbials

Location: EPTDS

• Enterovirus

– qPCR and cell culture

• Norovirus

– qPCR

• Indicators

– Total coliform– E. coli– Enterococci
Questions

Thank You
UCMR 3 Potential Conta

and Rationale - Chem

John Martin

Associate

The Cadmus Group, Inc

Watertown, Massachuset
Contaminant Prioriti

Stepwise prioritization process:• Initial list of ~140 contaminants based on 

Candidate List (CCL 3), as well as other econtaminants of concern 

• CCL 3 published in Fall 2009:

– EPA considered best available health effects a

information to evaluate thousands of unregula

– Multi-step process to select 104 chemicals/ch

12 microbiological contaminants

• Initial list pared down:

– Methods availability– Generally eliminated from inclusion if in previo

Contaminant Monitoring Regulation (UCMR) m

• Preliminary list further considered by EPA 

Region/State working group, and prioritizeffects data
Health Effects Data and 

Data

• Reference Dose (RfD)• Acceptable Daily Intake (ADI) • Minimal Risk Level (MRL)• Tolerable Upper Intake Level • No Observed Adverse Effect Level 

(NOAEL)

• Lowest Observed Adverse Effect Level 

(LOAEL)

• Lowest Oral Lethal Dose (LD50 )

• Health Advisory (HA)• Drinking Water Equivalent Level 

(DWEL)

• Health Reference Level (HRL)• EPA 10-4 Lifetime Cancer Risk

• Slope Factor• EPA Cancer Class • 95th Percentile Concentration (human 

exposure – urine, blood, serum)

So

• EPA

– Office of P

(OPP)

– Integrated 

System (IR

• Agency for Tox

Disease Regist

• California Offic

Health and Haz(OEHHA)

• Risk Assessme

(RAIS) 

• Registry of Tox

Substances (R

• Joint FAO/WHO 

Food Additives 

• Center for Dise• Institute of Med
Occurrence in Water Dat

• Unregulated Contaminant Monitoring (UC

(1988 – 1997)

• Six-Year Review Data (1998 – 2005)• National Inorganics and Radionuclides S

Data (1984 – 1986)

• Disinfection By-Product Information Colle

(DBP-ICR) Data (1997 – 1998)

• Community Water System Survey (CWSS• State Data: 

– New Jersey Department of Environmental Pro– Minnesota Pollution Control Agency

• Small-scale occurrence studies
Potential EPA Me

Assessment Monitoring (List 1) Screening S

Method 539 (LC/MS/MS) Location: EPTDS

Method 537 (LCLocation: EPTD

Method 522 (GC/MS) Location: EPTDSMethod 524.3 (GC/MS)Location: EPTDSMethod 200.8 (ICP/MS)Location: EPTDS, MRMethod 300.1 (IC) Location: EPTDS

GC - Gas ChromatographyMS - Mass SpectrometryICP - Inductive Coupled PlasmaIC - Ion Chromatography

LC - Liquid ChromaEPTDS - Entry Poin

SystemMR - Maximum Res
Pharmaceutica

EPA Method 539, forthcom

Determination of Hormones in Drinking Water 

Chromatography Tandem Mass Spectro

• 17-

α-Ethynylestradiol

• 17-

β-Estradiol

• Equilin• Estriol• Estrone• Testosterone• 4-Androstene-3,17-dione
17-α-Ethynylestra

Health Effects• LOAEL: 0.015 mg/kg-day

– Increased serum levels of alanine aminotr

aspartate aminotransferase (AST), and γ– 

glutamultransferase (GGT)

• NOAEL: 0.04 mg/kg-day

– Hematological effects

• HRL: 0.035 μg/L
17-α-Ethynylestra

Occurrence in Water

No. of 

Sites / 

Samples

No. of Sites / 

Samples with 

Detections (and %)

Va

M

Kolpin, et al., 2002, National Surface Water Reconnaissance

70 4 (5.7%) 

Snyder, et al., 2007, Finished and Raw Drinking Water 20 ND 

Snyder, 2008, Finished and Raw Drinking Water 20 ND 

Snyder, et al., 2008, Raw Water 19 1 (5.3%) Snyder, et al., 2008, Surface Water 18 ND 

Snyder, et al., 2008, Finished Water 33 ND 

Oxidative wastewater treatment additives (e.g., chlorine) may degrade 17-α

estrogenic activity (Lee, et al., 2008)
17-β-Estradio

Health Effects• JECFA ADI: 0.00005 mg/kg-day

– Estrogenic hormonal response

• HRL: 0.35 μg/L• California OEHHA Oral Slope Factor: 

day)-1

• Cancer HRL (set at 10-5 risk level): 0.0
17-β-Estradio

Occurrence in Water

No. of 

Sites / 

Samples

No. of Sites / 

Samples with 

Detections (and %)

Kolpin, et al., 2002, National Surface Water Reconnaissance – Method 1 70 7 (10%) Kolpin, et al., 2002, National Surface Water Reconnaissance – Method 2 85 9 (10.6%) 

Snyder, et al., 2007, Finished and Raw Drinking Water 20 ND Snyder, 2008, Finished and Raw Drinking Water 20 ND 

Snyder, et al., 2008, Raw Water 19 1 (5.3%) Snyder, et al., 2008, Surface Water 18 2 (11%) Snyder, et al., 2008, Finished Water 33 ND 

Oxidative wastewater treatment additives (e.g., chlorine) may degrade 17-β-estrogenic activity (Hu, et al., 2003)
Equilin

Health Effects• JECFA ADI: 0.00005 mg/kg-day

– Estrogenic hormonal response in post-me

women

– ADI for 17-β-estradiol (E2); E2 has structu

to equilin, so used as a toxicological surro

• HRL: 0.35 μg/L
Equilin

Occurrence in Water

No. of Samples

No. of Samples 

with Detections 

(and %)

Kolpin, et al., 2002, National Surface Water Reconnaissance 70 1 (1.4%) 
Estriol

Health Effects• JECFA ADI: 0.00005 mg/kg-day

– Estrogenic hormonal response in post-m

women 

– ADI for 17-β-estradiol (E2); E2 has struc

similarities to estriol, so used as a toxicosurrogate

• HRL: 0.35 μg/L
Estriol

Occurrence in Water

No. of Sites 

/ Samples

No. of Sites / 

Samples with 

Detections (and %)

Va

M

Kolpin, et al., 2002, National Surface Water Reconnaissance

70 15 (21.4%) 

Snyder, et al., 2007, Raw and Finished Drinking Water 20 ND 
Estrone

Health Effects• JECFA ADI: 0.00005 mg/kg-day

– Estrogenic hormonal response in post-me– ADI for 17-β-estradiol (E2); E2 has structu

equilenin, so used as a toxicological surro

• HRL: 0.35 μg/L
Estrone

Occurrence in Water

No. of 

Sites / 

Samples

No. of Sites / 

Samples with 

Detections (and %)

Kolpin, et al., 2002, National Surface Water Reconnaissance 70 5 (7.1%) 

Snyder, et al., 2007, Raw and Finished Drinking Water 20 2 (10%)

Snyder, et al., 2008 Source Water 18 11 (61%) Snyder, et al., 2008 Raw Water 19 15 (79%) Snyder, 2008, Raw Drinking Water 20 74% 

Swartz, et al., 2006, Ambient Water 14 10 (71%) 
Testosterone

Health Effects• JECFA ADI: 0.002 mg/kg-day• HRL: 14 μg/L
Testosterone

Occurrence in Water

No. of 

Sites / 

Samples

No. of Sites / 

Samples with 

Detections (and %)

Kolpin, et al., 2002, National Surface Water Reconnaissance 70 2 (2.8%) Kolodziej, et al., 2004, Surface Water

-- 18% 

Skadsen, et al., 2004, Finished Drinking Water

-- ND 

Snyder, et al., 2007, Raw and Finished Drinking Water

-- ND 
4-Androstene-3,17

Health Effects• JECFA ADI: 0.002 mg/kg-day

– ADI for testosterone; testosterone has 

similarities to 4-androstene-3,17-dionetoxicological surrogate

• HRL: 14 μg/L
4-Androstene-3,17

Occurrence in Water

No. of 

Sites / 

Samples

No. of Sites / 

Samples with 

Detections (and %)

Snyder, et al., 2007, Raw Drinking Water 20 1 (5%) 

Snyder, et al., 2007, Finished Drinking Water 20 ND 

Kolodziej and Sedlak, 2007 California Surface Water 89 16 (18%) 

Kolodziej, et al., 2004 California River, Irrigation Canal, and Tile Drain

11 River

15 Canal ND 

Debska, et al., 2004 Florida River -- -- 
Single Contaminant 

EPA Method 522, 2008

Determination of 1,4-Dioxane in Drinking Water 

Extraction and Gas Chromatography/Mass Sp

Selective Ion Monitoring, Version 

• 1,4-Dioxane
1,4-Dioxane

Health Effects• ATSDR MRL: 0.1 mg/kg-day• HRL: 700 μg/L• EPA Cancer Class: B2• EPA 10-4 Lifetime Cancer Risk: 0.3 mg/L

• IRIS Oral Slope Factor: 0.011 (mg/kg-day)-1

• Cancer HRL (set at 10-5 risk level): 30 μg/L 

• Draft Toxicological Review for 1,4-Dioxane (Ma• Draft IRIS RfD: 0.03 mg/kg-day

– NOAEL: 9.6 mg/kg-day– Liver and kidney toxicity in rats

• HRL: 210 μg/L• Draft Oral Slope Factor: 0.19 (mg/kg-day)-1• Cancer HRL (set at 10-5 risk level): 1.84 μg/L 
1,4-Dioxane

Occurrence in Water

Six-Year Review Data (1998 – 2005)

State No. of Samples No. of Samples with Detections (and %) No. of Sites No. of 

with Det

(and 

California 4,245 505 (11.9%) 218 24 (11
Volatile Organic Com

EPA Method 524.3, 2009 

Measurement of Purgeable Organic Compounds in W

Column Gas Chromatography/Mass Spectrometr

• 1,1-Dichloroethane• 1,2,3-Trichloropropane• 1,3-Butadiene• Bromochloromethane• Chlorodifluoromethane

• Chlorom• Methyl b• n-Propyl• sec-Buty
1,1-Dichloroeth

Health Effects• RAIS RfD: 0.2 mg/kg-day 

– NOAEL: 714 mg/kg-day– Decreased body weight gain

• HRL: 1,400 μg/L• EPA Cancer Class: C• California OEHHA Oral Slope Factor: 

(mg/kg-day)-1

• Cancer HRL (set at 10-5 risk level): 61

• CDC’s 95th Percentile Conc.: <detecti

1,367 blood samples (2003-2004)
1,1-Dichloroetha

Occurrence in Water

Unregulated Contaminant Monitoring (1988 – 19

Total No. of 

Systems

No. of System 

Detections

Percent of 

Detections

Valu

Me

Round 1 20,483 233 1.14% 

Round 2 24,808 184 0.74% 

Six-Year Review Data (1998 – 2005)

State No. of Samples No. of Samples with Detections (and %) No. of Sites No. of 

with Det

(and 

California 123,019 1,423 (1.16%) 4,080 35 (0.

Illinois

6 ND

2 N

North Carolina 19,837 115 (0.58%) 2,493 24 (0.

Ohio 9,350 57 (0.61%) 2,537 19 (0.

South Dakota 1,110 ND 281 N
1,2,3-Trichloropro

Health Effects• IRIS RfD: 0.006 mg/kg-day 

– NOAEL: 8 mg/kg-day– Alterations in clinical chemistry and reduction in RB

• DWEL: 0.2 mg/L• HRL: 42 μg/L• RAIS Oral Slope Factor: 7 (mg/kg-day)-1• Cancer HRL (set at 10-5 risk level): 0.05 μg/L

• IRIS RfD: 0.004 mg/kg-day

– BMDL (ADL): 1.1 mg/kg-day– Increased absolute liver weight in male rats 

• HRL: 28 μg/L• IRIS Oral Slope Factor: 30 (mg/kg-day)-1• Cancer HRL (set at 10-5 risk level): 0.01 μg/L
1,2,3-Trichloropro

Occurrence in Water

Unregulated Contaminant Monitoring (1988 – 19

Total No. of 

Systems

No. of System 

Detections

Percent of 

Detections

Valu

Me

Round 1 17,392 44 0.25% 0

Round 2 24,088 19 0.08% 

Six-Year Review Data (1998 – 2005)

State No. of Samples No. of Samples with Detections (and %) No. of Sites No. of 

with Det

(and 

California 113,128 4,977 (4.40%) 3,939 157 (3Illinois 11 4 (36.36%)

6 4 (66.

North Carolina 19,840 18 (0.09%) 2,493 5 (0.2

Ohio 9,283 1 (0.01%) 2,532 1 (0.0

South Dakota 1,110 1 (0.09%) 281 1 (0.3
1,3-Butadiene

Health Effects• EPA Cancer Class: B2• California OEHHA Oral Slope Factor: 

day)-1

• Cancer HRL (set at 10-5 risk level): 0.1Occurrence in Water• No data for 1,3-butadiene occurrence 
Bromochlorometh

Health Effects• EPA HA RfD: 0.01 mg/kg-day

– Increased liver-to-body weight ratio and 

and vacuolization of hepatocytes

• DWEL: 0.5 mg/L• HRL: 70 μg/L• EPA Cancer Class: D
Bromochlorometh

Occurrence in Water

Unregulated Contaminant Monitoring (1988 – 19

Total No. of 

Systems

No. of System 

Detections

Percent of 

Detections

Valu

Me

Round 1 12,881 65 0.5% 

Round 2 22,974 106 0.46% 

Six-Year Review Data (1998 – 2005)

State No. of Samples No. of Samples with Detections (and %) No. of Sites No. of 

with Det

(and 

California 117,632 40 (0.03%) 4,035 19 (0.

North Carolina 19,842 31 (0.16%) 2,493 29 (1.Ohio 9,291 23 (0.25%) 2,533 21 (0.

South Dakota 1,110 1 (0.09%) 281 1 (0.3
Chlorodifluoromet

Health Effects• RTECS Oral Chronic LOAEL: 13.5 mg

– Degenerative effects on brain and coverin

blood cell count (unspecified); and nutritiometabolic effects, such as weight loss or dgain 

• HRL: 31.5 μg/LOccurrence in Water• No data for occurrence of chlorodifluo

water
Chloromethan

Health Effects• EPA HA RfD: 0.004 mg/kg-day

– Mild neurological effects in humans occup

exposed to chloromethane

• HRL: 28 μg/L• RAIS Oral Slope Factor: 0.013 (mg/kg• DWEL: 0.1 mg/L• EPA Cancer Class: D• Cancer HRL (set at 10-5 risk level): 26
Chloromethan

Occurrence in Water

Unregulated Contaminant Monitoring (1988 – 19

Total No. of 

Systems

No. of System 

Detections

Percent of 

Detections

Valu

Me

Round 1 20,246 248 1.22% 

Round 2 23,478 528 2.25% 

Six-Year Review Data (1998 – 2005)

State No. of Samples No. of Samples with Detections (and %) No. of Sites No. of 

with Det

(and 

California 112,636 616 (0.55%) 4,046 142 (3Illinois 1,754 100 (5.70%) 740 51 (6.North Carolina 19,854 336 (1.69%) 2,493 223 (8Ohio 9,294 128 (1.38%) 2,533 87 (3.

South Dakota 1,110 4 (0.36%) 281 4 (1.4
Methyl Bromid

Health Effects• IRIS RfD: 0.0014 mg/kg-day

– NOAEL: 1.4 mg/kg-day– Epithelial hyperplasia in the forestomac

• DWEL: 0.05 mg/L• HRL: 9.8 μg/L• EPA Cancer Class: D
Methyl Bromid

Occurrence in Water

Unregulated Contaminant Monitoring (1988 – 19

Total No. of 

Systems

No. of System 

Detections

Percent of 

Detections

Valu

Me

Round 1 20,198 155 0.77% 

Round 2 23,328 175 0.75% 

Six-Year Review Data (1998 – 2005)

State

No. of 

Samples

No. of Samples 

with Detections 

(and %)

No. of Sites No. of 

with Det

(and 

California 112,570 72 (0.06%) 4,041 51 (1.

Illinois

6 ND

2 N

North Carolina 19,855 23 (0.12%) 2,493 22 (0.

Ohio 9,269 52 (0.56%) 2,531 41 (1.

South Dakota 1,110 ND 281 N
n-Propylbenzen

Health Effects• RTECS LOAEL: 2.5 mg/kg-day

– Effects on the blood, such as changes 

• RTECS LD50 : 6,040 mg/kg

– Behavioral effects, such as somnolence 

depressed activity)

• HRL: 5.83 μg/L
n-Propylbenze

Occurrence in Water

Unregulated Contaminant Monitoring (1988 – 19

Total No. of 

Systems

No. of System 

Detections

Percent of 

Detections

Valu

Me

Round 1 12,724 42 0.33% 

Round 2 22,970 54 0.24% 

Six-Year Review Data (1998 – 2005)

State No. of Samples No. of Samples with Detections (and %) No. of Sites No. of 

with Det

(and 

California 115,072 12 (0.01%) 4,033 9 (0.2

North Carolina 19,831 14 (0.07%) 2,493 11 (0.

Ohio 9,288 4 (0.04%) 2,533 4 (0.1
sec-Butylbenze

Health Effects• RTECS LOAEL: 4.42 mg/kg-day

– Associated with behavioral changes, su

alteration of classic conditioning

• HSDB LD50 : 2,240 mg/kg

• HRL: 10.3 μg/L
sec-Butylbenze

Occurrence in Water

Unregulated Contaminant Monitoring (1988 – 19

Total No. of 

Systems

No. of System 

Detections

Percent of 

Detections

Valu

Me

Round 1 12,343 28 0.23% 

Round 2 22,974 34 0.15% 0

Six-Year Review Data (1998 – 2005)

State No. of Samples No. of Samples with Detections (and %) No. of Sites No. of 

with Det

(and 

California 114,109 9 (0.01%) 4,006 8 (0.2

North Carolina 19,843 10 (0.05%) 2,493 8 (0.3

Ohio 9,288 4 (0.04%) 2,533 3 (0.1South Carolina 1,110 ND 281 N
Metals

EPA Method 200.8, 1994 

Determination of Trace Elements in Waters by Indu

Plasma - Mass Spectrometry, Version 

• Cobalt• Molybdenum• Strontium• Vanadium
Cobalt

Health Effects• ATSDR Interim MRL: 0.01 mg/kg-day 

– Blood increased hemoglobin, polycythem

respiratory-effects on lung function 

• RAIS RfD: 0.02 mg/kg-day• HRL: 70 μg/L• CDC’s 95th Percentile Conc.: 

– 1.32 μg/L for 2,465 urine samples (1999 – – 1.28 μg/L for 2,690 urine samples (2001 – – 1.16 μg/L for 2,558 urine samples (2003 – 
Cobalt

Occurrence in Water

National Inorganics and Radionuclides Survey (NIRS) (1

Total No. of 

Systems

No. of System 

Detections

Percent of 

Detections

Value 

Medi

989 3 0.30% 9.7 

Six-Year Review Data (1998 – 2005)

State No. of Samples No. of Samples with Detections (and %) No. of Sites No. of 

with Det

(and 

California 2,266 74 (3.27%) 67 10 (14Illinois 26 1 (3.85%) 22 1 (4.5

Ohio 73 3 (4.11%) 25 3 (12
Molybdenum

Health Effects• IRIS RfD: 0.005 mg/kg-day

– LOAEL: 0.14 mg/kg-day– Increased uric acid levels

• Institute of Medicine (IOM) Tol

Upper Intake Level: 0.03 mg/kg

• HRL: 35 μg/L• DWEL: 0.2 mg/L• EPA Cancer Class: D
Molybdenum

Occurrence in Water

National Inorganics and Radionuclides Survey (NIRS) (1

Total No. of 

Systems

No. of System 

Detections

Percent of 

Detections

Value 

Medi

989 77 7.79% 10 

Six-Year Review Data (1998 – 2005)

State No. of Samples No. of Samples with Detections (and %) No. of Sites No. of 

with Det

(and 

California 2,287 1,132 (49.50%) 161 107 (66

Illinois 1,922 263 (13.68%) 867 153 (17

Ohio 76 34 (44.74%) 26 13 (50
Strontium

Health Effects• IRIS RfD: 0.6 mg/kg-day

– NOAEL: 190 mg/kg-day– Rachitic bone

• HRL: 4,200 μg/L• DWEL: 20 mg/L• EPA Cancer Class: D
Strontium

Occurrence in Water

National Inorganics and Radionuclides Survey (NIRS) (1

Total No. of 

Systems

No. of System 

Detections

Percent of 

Detections

Value 

Medi

989 980 99.09% 0.1

Six-Year Review Data (1998 – 2005)

State No. of Samples No. of Samples with Detections (and %) No. of Sites No. of 

with Det

(and 

Illinois 21 21 (100%) 19 19 (1Ohio 77 75 (97.40%) 32 30 (93
Vanadium

Health Effects• ATSDR Interim MRL: 0.003 mg/kg-d

– Altered renal function indicated by incre

urea and mild histological changes

• RAIS RfD: 0.007 mg/kg-day• HRL: 21 μg/L
Vanadium

Occurrence in Water

National Inorganics and Radionuclides Survey (NIRS) (1

Total No. of 

Systems

No. of System 

Detections

Percent of 

Detections

Value 

Medi

989 146 14.76% 7.3 

Six-Year Review Data (1998 – 2005)

State No. of Samples No. of Samples with Detections (and %) No. of Sites No. of 

with Det

(and 

California 25,784 16,688 (64.7%) 2,698 1,824 (Illinois 19 ND 17 NOhio 71 ND 23 N
Single Contaminant 

EPA Method 300.1, 199

Determination of Inorganic Anions in Drinking 

Chromatography, Revision 1.

• Chlorate

– Gaseous chlorine– Potassium hypochlorite– Sodium hypochlorite
Chlorate

C

Health Effects• OPP RfD: 0.03 mg/kg-day

– Thyroid hypertrophy and mineralization 

• HRL: 210 μg/L
Chlorate

C

Six-Year Review Data (1998 – 2005)

State No. of Samples No. of Samples with Detections (and %) No. of Sites No. of 

with Det

(and 

California 1,205 945 (78%) 45 24 (5

Occurrence in Water

Disinfection By-Product Information Collection Rule (DBP-IC

No. of Samples No. of Samples with Detections (and %) Value of D

Median 

1,719 1,490 (86.7%) 120 
Chlorate

C

Occurrence in Water (cont.)

Sample Type Source No. of Samples No. of S

Detectio

Source Water Samples Bolyard, et al., 1992 14 2 Samples Disinfected with Hypochlorite Solution Bolyard, et al., 1992 14 14 Hypochlorite Solution Samples Bolyard, et al., 1992 14 14 Hypochlorite Solution Samples (4 months later) Bolyard, et al., 1992 14 14 Source Water from Utilities that use Hypochlorite Solution Disinfection Bolyard, et al., 1993 15 2 Drinking Water from Utilities that use Hypochlorite Solution Disinfection Bolyard, et al., 1993 16 16 Source Water from Utilities that use Gaseous Chlorine Disinfection Bolyard, et al., 1993 16 2 (Drinking Water from Utilities that use Gaseous Chlorine Disinfection Bolyard, et al., 1993 28 3 
Perfluorinated Che

EPA Method 537, 2009 

Determination of Selected Perfluorinated Alkyl Acids 

by Solid Phase Extraction and Liquid Chromatograp

Spectrometry, Version 1.1

• Perfluorooctane sulfonate (PFOS)• Perfluorooctanoic acid (PFOA)• Perfluorohexane sulfonic acid (PFHx• Perfluoroheptanoic acid (PFHpA)• Perfluorononanoic acid (PFNA)• Perfluorobutane sulfonic acid (PFBS
Perfluorooctane sulfonate 

Health Effects

• EPA Provisional HA: 0.2 μg/L 

– NOAEL: 0.03 mg/kg-day– Decreased body weights, increased liver w

serum total cholesterol, lowered triiodothyconcentration, and lowered estradiol level

• FR NOAEL: 0.1 mg/kg-day

– Reduced F2 body weight

• HSDB LD50 : 251 mg/kg

• HRL: 0.2 μg/L• CDC’s 95th Percentile Conc.: 54.6 μg/

serum samples (2003 – 2004); detects samples
Perfluorooctane sulfonat

Occurrence in Water

No. of Sites/ 

Samples

No. of Sites/ 

Samples with 

Detections (and 

New Jersey Department of Environmental Protection (2007) 23 13 (57%) 

Goeden and Kelly, 2006, Minnesota Municipal Wells 37 6 (16.2%) Goeden and Kelly, 2006, Minnesota Private Wells 26 ND 

Goeden and Kelly, 2006, Minnesota Non-Community Wells 22 ND 
Perfluorooctanoic acid 

Health Effects• EPA Provisional HA: 0.4 μg/L

– LOAEL: 0.46 mg/kg-day– Increased maternal liver weight at term

• HRL: 1.1 μg/L• CDC’s 95th Percentile Conc.: 9.8 μg/

serum samples (2003 – 2004); detectsamples
Perfluorooctanoic acid 

Occurrence in Water

No. of Sites/ 

Samples

No. of Sites

Samples wit

Detections (an

New Jersey Department of Environmental Protection (2007) 23 18 (78%) 

Goeden and Kelly, 2006, Minnesota Municipal Wells 37 6 (16.2%) 

Goeden and Kelly, 2006, Minnesota Private Wells 26 1 (3.8%)

Goeden and Kelly, 2006, Minnesota Non-Community Wells 22 ND Emmett, et al., 2006, Ohio Municipal Distribution System (2002 – 2005)

-- --

Emmett, et al., 2006, Ohio Private Wells (2002 – 2005)

-- -- 
Perfluorohexane sulfonic ac

Health Effects• NOAEL: 10 mg/kg-day

– Immuno/lumphoret, neurological, reprodu

developmental effects

• HRL: 70 μg/L• CDC’s 95th Percentile Conc.: 8.30 μg/

serum samples (2003 – 2004); detects samples
Perfluorohexane sulfonic ac

Occurrence in Water

Albany, New York Rain, Snow, Surface Runoff, and Lake Samp

(Kim and Kannan, 2007)

Sample Source No. of Samples Value of De

Range 

Lake water 11 <LOQ – 0.00405 

Rain water 11 ND – 0.00036 Snow 21 ND – 0.00035 Surface runoff 14 ND – 0.0135 
Perfluorohexane sulfonic ac

Occurrence in Water (cont.)

Minnesota’s Ambient Environment (2006 – 200

Sample Source No. of Samples No. of Samples with Detections (and %) V

Rural shallow ground water 22 ND 

Urban shallow ground water 29 11 (38%) Mississippi & Minnesota rivers and tributaries 34 1 (3%) 

Mississippi & Minnesota rivers 35 2 (6%) 

Surface water 16 3 (19%) Brainerd area Mississippi river

8 ND 

Mississippi river 22 5 (23%) 

City Road drainage ditch surface water

3 3 (100%) 

Rice Lake

3 3 (100%) 
Perfluoroheptanoic acid 

Health Effects• CDC’s 95th Percentile Conc.: 0.400 μg/L for 

samples (2003 – 2004); detects in 6.2% of sa

Occurrence in Water

Albany, New York Rain, Snow, Surface Runoff, and Lake Samp

(Kim and Kannan, 2007)

Sample Source No. of Samples Value of Dete

Range 

Lake water 11 0.00115 – 0.0127 Rain water 11 <LOQ – 0.00232 Snow 21 <LOQ – 0.00161 Surface runoff 14 <LOQ – 0.00644 
Perfluoroheptanoic acid 

Occurrence in Water (cont.)

Minnesota’s Ambient Environment (2006 – 200

Sample Source No. of Samples No. of Samples with Detections (and %) V

Rural shallow ground water 22 ND 

Urban shallow ground water 29 13 (45%) 

Mississippi & Minnesota rivers and tributaries 34 1 (3%) 

Mississippi & Minnesota rivers 35 8 (23%) 

Surface water 16 7 (44%) 

Brainerd area Mississippi river

8 ND 

Mississippi river 22 4 (18%) 

City Road drainage ditch surface water

3 3 (100%) 

Rice Lake

3 3 (100%) 
Perfluorononanoic acid 

Health Effects• LOAEL: 54 mg/kg-day

– Death of all 10 mice before day 14

• LOAEL: 0.5 mg/kg-day

– Hepatic effects

• HRL: 3.5 μg/L• CDC’s 95th Percentile Conc.: 3.20 μg/

serum samples (2003 – 2004); detects samples
Perfluorononanoic acid 

Occurrence in Water

Albany, New York Rain, Snow, Surface Runoff, and Lake Samp

(Kim and Kannan, 2007)

Sample Source No. of Samples Value of De

Range 

Lake water 11 ND – 0.00351 Rain water 11 <LOQ – 0.00348 

Snow 21 <LOQ – 0.00494 

Surface runoff 14 <LOQ – 0.00590 
Perfluorononanoic acid 

Occurrence in Water (cont.)

Minnesota’s Ambient Environment (2006 – 200

Sample Source No. of Samples No. of Samples with Detections (and %) V

Rural shallow ground water 22 ND 

Urban shallow ground water 29 1 (3%) 

Mississippi & Minnesota rivers and tributaries 34 1 (3%) 

Mississippi & Minnesota rivers 35 9 (26%) 

Surface water 16 1 (6%) 

Brainerd area Mississippi river

8 2 (25%) 

Mississippi river 22 ND 

City Road drainage ditch surface water

3 1 (33%) 

Rice Lake

3 ND 
Perfluorobutane sulfonic a

Health Effects• Minnesota Department of Public Health RfD: 0.0014 m

– NOAEL: 60 mg/kg-day– Decreased hemoglobin and hematocrit and histological c

and a co-effect of increased liver weight with increased i

hepatocellular hypertrophy

• HRL: 9.8 μg/L• CDC’s 95th Percentile Conc.: <limit of detection in 2,09

(2003 – 2004)

Occurrence in Water

North Carolina Cape Fear Drainage Basin (2006) (Nakayam

No. of Sites No. of Samples % of Samples Detected > LOQ (0.001 μg/L) Valu

Me

80 100 39.2% 0.0
Perfluorobutane sulfonic a

Occurrence in Water (cont.)

Minnesota’s Ambient Environment (2006 – 200

Sample Source No. of Samples No. of Samples with Detections (and %) V

Rural shallow ground water 22 ND 

Urban shallow ground water 29 5 (17%) 

Mississippi & Minnesota rivers and tributaries 34 1 (3%) 

Mississippi & Minnesota rivers 35 5 (14%) Surface water 16 3 (19%) Brainerd area Mississippi river

8 2 (25%) 

Mississippi river 22 ND 

City Road drainage ditch surface water

3 3 (100%) 

Rice Lake

3 3 (100%) 
Questions

Thank You
UCMR 3 Potenti

Contaminants and Rat

Microbes

Sandhya Parshionikar

USEPA, OGWDW, SRM

Technical Support Cente

Cincinnati, Ohio
Overview 

• Microbial contaminants bei

considered for the third cycUnregulated Contaminant Regulation (UCMR 3)

• Rationale for consideration• Sampling approach• Laboratory analyses• Methods
Potential UCMR 3 Mic

Contaminants

• Two Contaminant Candida

(CCL 3) microbial contamin

–Enterovirus– Norovirus
Rationale

• Both microbes are CCL 3 cont• Limited occurrence information 

undisinfected systems located sensitive aquifers
Rationale – con

• Recent Borchardt study showe

– Statistically significant correlation 

viral quantitative polymerase cha(qPCR) and self reported AGI (acgastrointestinal illness)

• qPCR may be used as an indicator 

vulnerability and potential disease i

– Significant viral occurrence in pu

systems (PWSs) with low total cooccurrence or no E. coli (EC) occ
Potential Sampling A

• List 3 sampling

– Selection of small systems (serving 

1,000)

– 800 undisinfected ground water sy

potentially those located in karst or bedrocks

– Possibly sampling at entry point to

distribution system

– Single sample event– EPA covers sampling costs– Contractors would perform samplin
Potential Laboratory A

• Enterovirus• Norovirus• Indicators

– Total coliform – E. coli– Enterococci– Bacteriophage– Aerobic Spores
Potential Metho

• Enterovirus and Norovirus

– qPCR protocol similar to that u

Borchardt

• Enterovirus

– Cell culture by ICR method wit

replaced by nanoceram filter

• New filter is 10-fold less expensiv• Recovery equivalent to 1MDS
Questions

Thank you
Approval of Laborat

Supporting UCMR 

Daniel P. Hautman

USEPA, OGWDW, SRM

Technical Support Cente

Cincinnati, Ohio
Overview

• Third cycle of the Unregulated 

Contaminant Monitoring Regu(UCMR 3)

• Tentative steps under the UC

Laboratory Approval Program 

• Maintaining approval• Conclusions/Questions
Approach for UCM

• UCMR 3 still in planning stag

options are being considered

• UCMR 2 laboratory approval 

certainly be used as a guide
General Expectat

• Laboratory Approval Program wil

the process used in UCMR 2

• Water systems would need to use 

UCMR-approved laboratories for 

• Labs would need to meet the req

equipment, laboratory performancreporting criteria to become appro

• Labs would still need to be appro

already certified by state, primacy accredited through the National EAccreditation Conference (NELACparticular method
General Proced

• Laboratory approval proces

UCMR 2 and envisioned for 

– Step 1: Request to participate – Step 2: Application– Step 3: EPA review of applicat– Step 4: Proficiency Testing– Step 5: EPA approval
Step 1

• Request to participate and re

– Submit a written participation r

EPA Lab Approval Coordinator

– EPA provides registration mate– Submit complete registration m

90 days of publication in Feder

– EPA provides a custom applica

based on registration informati
Step 2

• Application Package

– Separate application for each m– Lab would receive a copy of th

Approval Manual

– Package would be submitted w

days after publication in the FeRegister

– A postcard notifying lab would 

receipt of application by EPA
Step 2 continue

• Completed application package a

include:

– Precision, accuracy and minimum re

(MRL) studies with documentation

– Documentation of certification or acc

drinking water compliance analysesmethods as requested

– Personnel and quality assurance inf– Description of analytical equipment 

handling procedures
Step 3

• Review of Application Packag

– EPA would review the package 

request more information

– Postcard notifying lab would be 

successful completion of the appackage

– Once the application has been 

the lab could participate in the corresponding PT studies
Step 4

• Proficiency Testing

– EPA would provide PT sample– Analyze PT sample(s) for each – Labs may have three opportun

analyze PT samples

– Only one successful analysis o

per method would be required
Step 5

• EPA Approval

– Once all steps are completed, 

grant formal written approval (bmethod)
After Approva

• Maintaining approval

– Adhere to quality assurance/qu

(QA/QC) measures in both the the rule language

– Post occurrence data and requ

via the Safe Drinking Water AcReview System (SDWARS) witprescribed timeframe

– Participate and pass on-site an

audits
Questions

Thank You
Establishment of Rep

Limits for UCMR 

John Martin

Associate

The Cadmus Group, Inc

Watertown, Massachuset
Overview

• History of the lowest concentration min

level (LCMRL) and minimum reporting 

– Definitions– Applications

• New developments in the LCMRL/MRL 

– Former Procedure (UCMR 2)– Procedure Anticipated for (UCMR 3)

• Implications for laboratories in UCMR 3

– Daily Check at or Below MRL– LCMRL Calculator
Definitions - LCM

• LCMRL - lowest spiking conc

which 50-150% recovery expof the time by a single analys

– Estimate of the lowest concent

which measurements of specifcan repeatedly be made of tha

– Simultaneous application of pre

accuracy
Definitions - MR

• MRL - estimate of an LCMRL 

95% confidence, achievable bcapable analyst/laboratory at of the time

– Assuming good instrumentatio

experienced analysts, 95% conachievable by 75% of laboratornationwide
Definitions - MR

• Intended to achieve quality ac

nation’s laboratories while prenational laboratory system ca

• Selection of the 95% confiden

75% frequency mirrors data qobjectives (DQOs) establishepractical quantitation limit (PQ
Applications

• MRL used in UCMR 1

– General reporting level– Typically reflects lowest instrum

calibration standard

• LCMRL and Associated Statis

Defined MRL

– UCMR 2

• Revised LCMRL and MRL

– UCMR 3
Former LCMRL Pro

• Process seven+ replicates at four

concentrations through entire me

• Graph measured vs. true concent• Regress data using Ordinary Lea

(OLS)

• 99% prediction interval• DQO lines from origin

– 150% recovery

– 50% recovery

Winslow, et al., 2006. Environ. Sci. Technol. 40(1), 281-2
Former LCMRL Pro

Perchlorate in DI Water

Spiked Concentration (ug/L)

0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0

Measured Concentration (ug/L) 0.1 0.2 0.3 0.4 0.5

0.6

Perpendicular to the 

LCMRL = 0.15 u

LCMRL by Ordinary Least Squar

= regression line= +50%= 99% prediction interval
Former MRL Proc

• Generate LCMRLs from mult

laboratories

• Three or more laboratories

• Mean of LCMRLs + 3 SD

• Two laboratories

• |LCMRL1 – LCMRL2| + 3 SD
Why EPA Revised LCMRL 

• Helps correctly identify the lowest 

concentration within the DQO bou

– Addresses bias in calibration and an

– Addresses potential skew in measur

cannot assume a normal distribution

– Addresses change in variance over 

concentration range

• Procedures underwent second pe

(2008)
Revised LCMRL Pro

• Process four+ replicates at se

concentrations through entire 

• Graph measured vs. true con

• Regress data using Weighted 

Squares

• Probability distribution for spi

– Function of spiking concentrati
Revised LCMRL Pro
Revised LCMRL Pro
Revised LCMRL Ca

• Downloadable tool

– Input method information

– Upload spike concentrations and me

– Will be available on EPA’s website

• LCMRL determination used in 

development

• Laboratories not required to d

LCMRLs for UCMR 3

• Ability to quantitate at MRL re
Revised MRL Proc

• Raw data from LCMRL study 

Bayesian Bootstrap procedur

– Results weighted to generate l

of simulated values for LCMRL

– Values combined to estimate o

distribution

• MRL computed as 95% uppe

confidence limit for 75th perce
MRL Verification Pro

• MRL verification procedure

– Easier than LCMRL determinat– Replaces yearly minimum dete

(MDL) study with single-day pr

• Part of the Initial Demonstration o

(IDC) for each analytical method

• Daily check sample required

– For each analyte demonstrate 

recovery at or below MRL (one 

– Re-run those that do not pass 
MRL Verification Pro

• At least seven replicate samples are fo

below MRL and processed through enprocedure

• Calculate a prediction interval of result

– t = the two-sided Student's t value with n-1 or d

and confidence level (1-

α);

– s = the sample standard deviation of n replicate 

or below the MRL

Dixon, W.J. and F.J. Massey, Jr., 1983. “Introduction to SMcGraw-Hill Book Company, Fourth Edition, p. 92.

Prediction Interval    

Mean s t



( , /) df 1 2


MRL Verification Pro

• DQOs

– Confidence level for two-tailed Student’s t v– Allowable data quality interval = 50 to 150% – Outliers cannot be discarded

• For specified confidence (99%) and nu

replicates (7), the factoris constant (= 3.963)

• PIR = Mean of LCMRL results ± 3.963(

t

n ( , /) df 1 2

1

1



  
MRL Verification Pro

MRL verification example: estriol, EPA • Seven replicates, true fortified conc. = 1

• Mean of results = 0.899 ng/L

• Standard deviation, s = 0.076 ng/L

• PIR = 0.899 ng/L ± 3.963 * 0.076 ng/L

• PIR = 0.899 ng/L ± 0.3012 ng/L

– Lower PIR % Rec = 0.5978 ng/L/1.1 ng/L * 100 

– Upper PIR % Rec = 1.200 ng/L/1.1 ng/L * 100 = 
Summary

• Two procedures

– LCMRL: single-laboratory quan

determined during method deve

– MRL Verification: initial demons

capacity (IDC) and daily check pre-defined MRL

• Both LCMRL and MRL proced

into account simultaneous apprecision and accuracy
Acknowledgme

• Peer review of the updated proced

– William Foreman, United States Geo

– Maliha Nash, USEPA

– John Nocerino, USEPA, National Ex

Laboratory, Las Vegas

– Anita Singh, USEPA

– Lynn Vanatta, Air Liquide

– X. Jin Yang, Ph.D., Environmental F

Analytical Science Department of EnClimate Change, Australia
Questions

Thank You