How Effluent Data Affect Water Quality Based Effluent Limits - Case Studies

Transcription

1 How Effluent Data Affect Water Quality Based Effluent Limits - Case Studies Nick Muenks September 8, 2017 REGFORM 2017 Water Seminar

2 Cases of WQBEL Blues Case #1 - Dramatic decrease from limits used for design of a treatment plant expansion Case #2 - Imminent noncompliance Case #3 - Overly stringent ammonia limits

3 Ammonia Limits (mg/l) WQBEL Case #1 Ammonia limits for new treatment expansion reduced by 60% [CELLRA NGE] Limit 60% [CELLRA NGE]

4 WQBEL Case #2 Imminent non-compliance with proposed zinc limits. ZINC

5 WQBEL Case #3 Treatment plant ammonia limits reduced nearly to EPA s 2013 ammonia criteria.

6 WQBEL What Is It? An effluent limit established to achieve applicable water quality standards. Generally more stringent than TBELs. Derived through a process of data evaluation and statistical analyses. Typically based on effluent data collected by the permittee and/or assumptions provided by guidance.

7 WQBEL Basic Process EPA 1991 Technical Support Document for Water Quality-based Toxics Control (TSD) No No WQBEL Determine Applicable WQS Characterize Effluent and Receiving Water Determine if Reasonable Potential Exists Yes Calculate WQBEL

8 Step 1: Determine Applicable WQS Distance to classified waterbody Beneficial Uses Waterbody classification Applicable WQS Special designations (i.e. losing stream)

9 Step 2: Effluent and Receiving Water Characterization Pollutants Of Concern Mixing Considerations Critical Condition Assessment

10 Critical Condition Assessment Where Effluent Data Are Called to Action Maximum Effluent Concentration Data Variability Censored Data (e.g. non-detect) Effluent Flow

11 Step 3: Reasonable Potential Analysis (RPA) Often mass balance approach is used Focus on Critical Conditions Max effluent concentration Stream low flow Predict receiving water concentration Does predicted concentration exceed standards?

12 If RP then WQBEL Calculation Wasteload allocations Long term averages Effluent limits Average monthly limit Maximum daily limit

13 Cases of WQBEL Blues Case #1 - Dramatic decrease from limits used for design of a treatment plant expansion Case #2 - Imminent noncompliance Case #3 - Overly stringent ammonia limits

14 Case #1 Ammonia Limits The Issue Design ammonia limits for plant expansion Acute discharge conditions Based prior effluent data variability Proposed ammonia limits during permit renewal 60% lower than expansion design limits Coefficient of Variation Major factor

15 Case #1 Ammonia Limits - Assessment Proposed limits based on effluent data following expansion startup. Plant operating at ~65% design flow. Ammonia generally very low. Few elevated ammonia results as operations were tuned Increased data variability Coefficient of Variation (CV) Standard deviation/mean Affects Upper Tolerance Limits (UTLs) Impacts predicted effluent and receiving water concentrations Impacts effluent limits

16 Effluent Limits CV Effects on Effluent Limits As CV increases AML tends to decrease and MDL tends to increase Limits derived for acute conditions are more sensitive to changes in variability Coefficient of Variation

17 Ammonia Limits (mg/l) Case #1 Ammonia Limits Resolution? Potential resolution: use default assumption for coefficient of variation (CV) = 0.6, until additional data are collected [CELLRAN GE] Limit [CELLRAN GE] 33% Proposed Limit 0

18 Case #1 - Summary of Case Factors Analyses limited by acute conditions (intermittent short-term discharge), Variability in data during startup resulted in higher CV than used for design, Small adjustments in CV cause large swings in effluent limitation in acute discharge situations

19 Cases of WQBEL Blues Case #1 - Dramatic decrease from limits used for design of a treatment plant expansion Case #2 - Imminent noncompliance Case #3 - Overly stringent ammonia limits

20 Case #2 Zinc Limits The Issue Permittee facing imminent noncompliance with proposed zinc limits. Draft permit s reasonable potential analysis indicated high data variability (affects CV) 430 µg/l maximum µg/l minimum Maximum zinc value was abnormal, justified additional data review

21 Case #2 Zinc Limits - Assessment Initial data review 430 µg/l was incorrect and removed from the analyses Permit was revised Raised effluent limit Imminent non-compliance issue still unresolved Detailed data review Effluent data Reasonable potential analysis In stream hardness Sources of zinc

22 Case #2 Zinc Limits - Resolution Results Permittee s data indicated there was no reasonable potential Discrepancies in data used in the RPA process Correct effluent data were provided to MDNR

23 Case #2 - Summary of Case Factors Highly variable data should be reviewed for correctness and representativeness. Submitting correct data with DMRs. Assure data used for RPA are correct.

24 Cases of WQBEL Blues Case #1 - Dramatic decrease from limits used for design of a treatment plant expansion Case #2 - Imminent noncompliance Case #3 - Overly stringent ammonia limits

25 Ammonia Limit (mg/l) Case #3 Reduced Ammonia The Issue Treatment plant sees 35% reduction in ammonia limits proposed in draft permit EPA s 2013 Default Criterion

26 Case #3 Reduced Ammonia - Assessment Review of Reasonable Potential Analysis in Draft Permit. Data ranged from to 2.5 mg/l CV = 5.00 (extremely high) Review of RPA Spreadsheets Requested. 92% of summer samples were non-detect 57% of winter samples were non-detect High occurrence of censored data (non-detects) do not conform to assumptions in EPA s TSD.

27 Case #3 Reduced Ammonia - Assessment Non-detects (ND) Currently assigned a value of one-half the reported minimum level (RDL or MDL) Can have order of magnitude effects on CV TSD assumes data exhibit lognormal distribution General Rule of Thumb (Unified Guidance) <15% ND = lognormal = TSD assumptions. 15% - 50% ND s = may not conform to TSD assumptions >50% ND s = does not conform to TSD assumptions.

28 Ammonia Limit (mg/l) Case #3 Reduced Ammonia - Resolution Meeting with MDNR to discuss reasonable potential analyses and high frequency of non-detects. Consensus gained on non-conforming data Ammonia Limits: To be Continued.

29 Case #3 Summary of Case Factors Review highly variable data (e.g., have high CV). High frequency of non-detects may not conform to TSD assumptions, and may need additional analysis.

30 How Effluent Data Affect WQBELs Data Variability (CV) Assuring Data are Correct Censored Data Representative Data

31 Representative Data Collect Data Under Representative Conditions

32 Assure Proper Limits are Derived Assure Data Collected are Representative Sample type, location and QA Review Data & RPA Analyses Are reported data correct (value, units, etc.) & complete Are censored data identified and reported correctly Data used for derivation of limits are primarily from permittee Troubleshoot and solve data variation if possible MDNR is open to discussion Data Distribution (i.e. parametric, non-parametric). Methods for assessing data when they do not conform. Site-specific assessments.

33 Parting WQBEL Thoughts Can a permittee with effluent data below limits but exhibiting high variability really have reasonable potential? If facility consistently discharges the same effluent quality, below WQ standards, does reasonable potential really exist? What s the benefit of a written process to make reasonable potential determinations?

34 REGFORM 2017 Water Seminar Questions? Nick Muenks Water Quality Professional Geosyntec Consultants