ground water quality standards rules: pql stakeholder ... · 2/21/2017 · 3. formulated a pql...

Ground Water Quality Standards Rules:PQL Stakeholder Workgroup

Rachel Host, DWMS, Bureau of Environmental Analysis, Restoration and StandardsR. Lee Lippincott Ph.D., DSREH, Bureau of Environmental Assessment

Sandra Cohen, Rule Manager, DWMS, Bureau of Environmental Analysis, Restoration and Standards

February 21, 2017

Meeting Agenda

I. Welcome and IntroductionsII. OverviewIII. Data Acquisition

• Performance data submissionsIV. Potential Updates to Ground Water PQLs

• PQL derivation• Results of PQL re-evaluation• Recommendations for updates• Data gaps

V. DiscussionVI. Wrap Up and Next Steps

February 21, 2017 NJDEP GWQS Rules Stakeholder Process 2

Overview


Purpose of Today’s Meeting

• Share the results of the Department’s re-evaluation of the existing PQLs for Class II constituents and recently solicited performance data.

• Obtain feedback on potential updates to the PQLs that would inform the rulemaking process.

• Identify any concerns or additional information that should be considered.


What You Should Know About Today’s Meeting

• This is an informal, technical meeting to discuss information related to the selection and derivation of PQLs and potential updates for constituents in Class II ground waters.

• The information presented today is preliminary and for discussion purposes only and should not be considered as proposed or final PQLs.


Status of Action Items from Prior Meeting

I. Set new deadline for performance data submission.• Status: Deadline changed to January 20, 2017.

II. Send copy of the performance data solicitation letter to PQL workgroup members.

• Status: Email sent December 28, 2016 along with new deadline.

III. Check with OQA to obtain performance data submitted by labs as part of routine certification or other processes for which data is submitted.

• Status: NJDEP OQA no longer supports the NJQL database for performance data.


Status of Action Items (Continued)

IV. Request a small subset of lab performance data from SRP’s Electronic Data Deliverables.

• Status: Action not required due to sufficient response from outside labs. Instead, BEARS conducted phone solicitation for performance data from a list of certified laboratories from OQA DataMiner.


Data Acquisition


Related Terms and Definitions

• MDL - method detection limit or the lowest concentration at which a parameter can be reliably detected

• RL - reporting limit or the lowest concentration that the lab reports

• Often determined by the client, not by available technology, and is often not the most sensitive*

• Low Point on the Calibration Curve - lowest concentration standard used in the generation of a calibration file for a parameter

*Note: This is the definition of RL employed for ground water and drinking water PQLs but may not be consistent with other regulatory programs


Presenter

Presentation Notes

Practical quantitation level – lowest concentration of a constituent that can be reliably achieved among laboratories within specified limits of precision and accuracy during routine laboratory operating conditions.

Performance Data Submissions

• Performance data was arranged in a statistical package compatible format for analysis and recommendations by:

• Nonparametric traditional approach to PQL calculation• Bootstrap distribution analysis to generate Upper Control Limits

for MDL and RL values


Presenter

Presentation Notes

Constituent standard (GWQS) is the higher of the PQL or the ground water quality criterion.

Laboratory Name NJ Certified Lab ID Method(s)/SeriesALS ENVIRONMENTAL - MIDDLETOWN PA010 500, SW846

CAPE FEAR ANALYTICAL, LLC NC013 1600

EDGE ANALYTICAL, INC WA013 200, 500

ENVIROTEST LABORATORIES, INC. NY015 200, 500, 600

ESC LAB SCIENCES TN002 200, 500, 8000

EUROFINS EATON ANALYTICAL, INC CA008 200, 500

EUROFINS LANCASTER LABORATORIES ENVIRONMENTAL, LLC PA011 500, 600, 6000, SW846

EUROFINS SPECTRAL ANALYTICAL MA011 SW846

GEL LABORATORIES SC002 500, SW846

INTEGRATED ANALYTICAL LABORATORIES 14751 SW846

PA DEP BUREAU OF LABORATORIES PA059 200, 500, 600

SGS ACCUTEST, INC. - DAYTON 12129 200, 500, 600, SW846

TESTAMERICA EDISON 12028 SW846, 8000

TESTAMERICA LABORATORIES, INC. - SAVANNAH GA769 200, 500, 600

Performance Data Submissions

Presenter

Presentation Notes

9 new labs THANK STAKEHOLDERS

Potential Updates to Ground Water PQLs


Derivation of PQLsFrom GWQS Rules N.J.A.C. 7:9C-1.9(c)3ii:PQLs … shall be derived or selected for each constituent using the most sensitive analytical method* providing positive constituent identification from (c)3ii(1) and (2) below, in that order of preference:

(1) PQLs derived from Method Detection Limit (MDL) data from the New Jersey Department of Health and Senior Services Laboratory (DHSS) multiplied (*) by 5;

(2) PQLs derived from laboratory performance data that has been evaluated by the Department using the method of Sanders, Lippincott, and Eaton (See Sanders, P. et al., “Determining Quantitation Levels for Regulatory Purposes.” J. Amer. Water Works Assoc., 1996, March pp. 104-114).

*Note: The most sensitive methods available may not be certified by Department’s OQA due to lack of performance data, etc.

NJDEP GWQS Rules Stakeholder ProcessFebruary 21, 2017

Presenter

Presentation Notes

Bootstrap analysis is an appropriate statistical method for generating a normal distribution when the data set (n) is relatively small.

Derivation of PQLs From Performance Data

Sanders, P. et al.• The regulatory level should be adequately quantifiable by the

majority of laboratories certified for a particular compound and method of interest.

• To determine a single regulatory level that most laboratories will be able to achieve, performance variations within the laboratory community must be taken into account.

• Median interlaboratory MDLs are multiplied by a variable factor that is determined from laboratory performance data.

• Bootstrap analysis is an appropriate statistical method for generating a normal distribution when the data set (n) is relatively small.February 21, 2017 NJDEP GWQS Rules Stakeholder Process 14

Reminder…

The recommendations presented here have to be verified for completeness from all available laboratory information gathered by the solicitation process and should be considered preliminary.


Summary of PQL Re-evaluation Results

Category VOCs PAHs Pesticides Metals and Cyanide

Additionalparameters

Total

Lower PQL 12 0 7 2 9 30No change 7 5 2 2 0 16Insufficientdata 0 0 0 0 3 3

Total 19 5 9 4 12 49


Volatile Organic Compounds (VOCs)

We evaluated 19 VOC parameters utilizing data received from 14 laboratories.

1. Calculated the traditional MDL*5 values (GWQS Rules N.J.A.C. 7:9C)

2. Compared these values to:• Low Point Calibration Data from 5 laboratories• Bootstrap UCL MDL calculation

3. Formulated a PQL recommendation for each parameter based on interlaboratory MDL and low point calibration data• In nearly every case we received data from 5 labs, and for several of

the parameters, there was performance data from 6+ labs.


Presenter

Presentation Notes

UCL – 95% chance of including the mean quantification capability of NJ certified labs.

VOC Parameter CASRN Existing PQL (µg/L)

Recommended PQL (µg/L)

# of Labs

1,1,2,2-Tetrachloroethane 79-34-5 1 1 11

1,1,2-Trichloroethane 71-55-6 2 1 11

1,2,3-Trichloropropane 96-18-4 0.03 0.03 5

1,2-Dichloroethane 107-06-2 2 0.7 5

1,2-Dichloropropane 78-87-5 1 0.5 5

1,3-Dichloropropene (cis and trans) 542-75-6 1 0.5 5

Acrolein 107-02-8 5 4 5

Acrylonitrile 107-13-1 2 2 5

Benzene 71-43-2 1 0.5 7

Bis(2-ethylhexyl) phthalate (DEHP) 117-81-7 3 3 5

Bromodichloromethane (Dichlorobromomethane) 75-27-4 1 0.5 5

Carbon tetrachloride 56-23-5 1 1 6

Dibromochloromethane (Chlorodibromomethane) 124-48-1 1 0.5 5

Ethylene dibromide (1,2-Dibromoethane) 106-93-4 0.03 0.03 5

Hexachlorobutadiene 87-68-3 1 1 5

Hexachloroethane 67-72-1 7 0.7 5

Nitrobenzene 98-95-3 6 1 5

Tetrachloroethylene (PCE) 127-18-4 1 0.5 5

Vinyl chloride 75-01-4 1 0.5 5

Lower PQL

No Change

Insufficient Data

Presenter

Presentation Notes

All methods submitted were based on SW846 and both full scan and Selective Ion Monitoring methods were considered

Polycyclic Aromatic Hydrocarbons (PAHs)

We evaluated 5 PAH parameters utilizing data received from 14 laboratories.


PAH Parameter CASRN Existing PQL (µg/L)


# of Labs

Benz(a)anthracene 56-55-3 0.1 0.1 5

Benzo(a)pyrene (BaP) 50-32-8 0.1 0.1 5

Benzo(b)fluoranthene (3,4-Benzofluoranthene) 205-99-2 0.2 0.2 5

Dibenz(a,h)anthracene 53-70-3 0.3 0.3 5

Indeno (1,2,3-cd)pyrene 193-39-5 0.2 0.2 7

Lower PQL

No Change

Insufficient Data

Presenter

Presentation Notes

Used newest advanced laboratory methods last time we set these standards, so the technology hasn’t progressed significantly since then…???

PAH - Selective Ion Monitoring (SIM methods)

PAH parameter recommendations if SIM data is used.


PAH Parameter CASRN Existing PQL (µg/L)


# of Labs

Benz(a)anthracene 56-55-3 0.1 0.1 5

Benzo(a)pyrene (BaP) 50-32-8 0.1 0.01 5

Benzo(b)fluoranthene (3,4-Benzofluoranthene) 205-99-2 0.2 0.2 5

Dibenz(a,h)anthracene 53-70-3 0.3 0.03 5

Indeno (1,2,3-cd)pyrene 193-39-5 0.2 0.02 7

Lower PQL

No Change

Insufficient Data

PesticidesWe evaluated 9 pesticide parameters utilizing data received from 14 laboratories.


Pesticide Parameter CASRN Existing PQL (µg/L)


# of Labs

Aldrin 309-00-2 0.04 0.02 5

alpha-BHC- (alpha-HCH) 319-84-6 0.02 0.02 6

beta-BHC (beta-HCH) 319-85-7 0.04 0.02 6

Chlordane 57-74-9 0.5 0.2 6

Dieldrin 60-57-1 0.03 0.02 6

Heptachlor 76-44-8 0.05 0.02 6

Heptachlor epoxide 1024-57-3 0.2 0.02 6

Simazine 122-34-9 0.8 0.04 PesticideControl

Demeton 8065-48-3 1 1 2

Lower PQL

No Change

Insufficient Data

Metals and Cyanide

We evaluated 4 parameters utilizing data received from 14 laboratories.


Parameter CASRN Existing PQL (µg/L)


# of Labs

Arsenic (Total) 7440-38-2 3 3 8

Thallium 7440-28-0 2 0.5 7

Cobalt 7440-48-4 0.5 0.5 3

Cyanide (free Cyanide) 57-12-5 6 0.03* 3

Lower PQL

No Change

Insufficient Data

*Note: Tight statistical spread of lab data for Cyanide allowed us to make a recommendation to lower the PQL.

Presenter

Presentation Notes

*Tight statistical spread of lab data for cyanide allowed us to make a recommendation to lower the PQL. However, stakeholder input would be appreciated.

Additional Parameters


Parameter CASRN Existing PQL (µg/L)


# of Labs

1,1-Biphenyl 92-52-4 10 5* 3

1,2-Diphenylhydrazine 122-66-7 20 10* 3

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) 1746-01-6 0.00001 0.00001 2

2,4,6-Trichlorophenol 88-06-2 20 2 5

2,4-Dinitrophenol 51-28-5 40 10 5

2,4-Dinitrotoluene/2,6-Dinitrotoluene Mix 25321-14-6 10 5 6

3,3-Dichlorobenzidine 91-94-1 30 5 5

4-Chloroaniline (p-Chloroaniline) 106-47-8 10 5* 3

Acrylamide 79-06-1 0.2 0.2 1

Benzidine 92-87-5 20 7 6

Bis(2-chloroethyl) ether 111-44-4 7 1 8

Epichlorohydrin 106-89-8 5 5 3

Lower PQL

No Change

Insufficient Data

*Note: Tight statistical spread of lab data allowed us to make a recommendation to lower the PQL.

Data Gaps

• Insufficient data for:• 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD)• Acrylamide• Epichlorohydrin


Presenter

Presentation Notes

Do we want more lab data?

Data Gaps (continued)

• Only 6 labs confirmed availability of Selective Ion Monitoring (SIM) for methods/parameters of interest:

• ESC Lab Sciences• Eurofins Eaton Analytical, Inc.• SGS Accutest Inc.,- Dayton• TestAmerica Edison• TestAmerica Denver• Integrated Analytical


Presenter

Presentation Notes

Do we want more lab data?

New Interlaboratory Performance Data

• Received 02/03/2017• 9 laboratories submitted data

• Several were under the same corporate umbrella (e.g. Test America)

• Submitted MDL and RDL (Reliable Detection Level) performance Data

• RDL = 4*MDL• Georgian, T., Osborn, K; Quality Assurance 10(1):1-9 · February 2003


New Interlaboratory Performance Data (cont.)

• This additional data enabled us to lower the PQL recommendations for:• 1,2 Dichloroethane• Hexachloroethane• Nitrobenzene

• We were also able to calculate PQLs for other parameters where the PQL is currently not the driver.

• PQLs were calculated for 113 parameters. • An additional 103 parameters had insufficient data (less than the minimum of 5

data points).


• 1,1’ Biphenyl • 4 Chloroaniline• 1,2-Diphenylhydrazine

Questions

1. Do we offer a final lab solicitation for the parameters where there is insufficient data from the first two solicitations?

2. In several cases, the low point data supplied by the labs was lower than the median MDL*5. Should the recommendation be based on the median lowest calibration standard?

3. Stakeholder input on Cyanide PQL, 1,1’ Biphenyl, 4 Chloroaniline and 1,2-Diphenylhydrazine PQLs?


Presenter

Presentation Notes

Should the Department institute a policy for improved analytical SIM methods by requiring that these techniques be utilized when the PQL is the regulatory driver?

Summary

•Evaluated interlaboratory data for 49 parameters.•Calculated recommended PQLs following the Department’s standard methods outlined in the regulations.

•Additional statistical techniques were used to augment and support the PQL recommendations.

•Criteria review is still in progress and that may identify new PQL driven parameters.


Discussion


Wrap up and next steps


Thank you for your participation


ground water quality standards rules: pql stakeholder ... · 2/21/2017 · 3. formulated a pql...

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