comparison of mpca stormwater benchmarks with historical industrial sector monitoring results

Caltha LLPCaltha LLPwww.calthacompany.com/?page_id=16

Industrial Stormwater BenchmarksIndustrial Stormwater Benchmarks ––Comparison of New Minnesota BenchmarkComparison of New Minnesota Benchmark

Concentrations To Historic IndustryConcentrations To Historic Industry--specificspecificTesting ResultsTesting Results

Loren J. LarsonManaging Partner

Caltha LLP, Minneapolis

Conference on the Environment | Brooklyn Park, Minnesota | November 9, 2010


OutlineOutlineOutline

• Background – Historical Context

• EPA Industrial Group Sampling

• Comparison of MPCA Benchmarks to PastData

• Projection of Future Results

• Summary


Key Historical EventsKey Historical EventsKey Historical Events

• 1972 Federal Water Pollution Control Act» NPDES permit program

• 1977-85 NURP Studies» Identified urban runoff as important factor impacting

water quality

• 1987 Amendment to Clean Water Act» Required stormwater discharge be addressed under

NPDES permitting program


Key Historical EventsKey Historical EventsKey Historical Events

• 1990 - EPA promulgates stormwater permit rules» Requires industrial facilities to be permitted by Sept. 1992

» Publishes Group Permit option

• 1990-1992 - General permits drafted by EPAand States

» 1991 MPCA publishes general permit

• 1992 – Most facilities permitted under State orEPA general permit


Group Permit OptionGroup Permit OptionGroup Permit Option

• Offered option to be covered under permitcustomized for industry sector

» Single company with multiple locations

» Multiple companies, trade associations

• EPA accepted Group Permit applications

• Applications required monitoring ofstormwater discharge from selected groupmembers

» Representative of group

» Wide geographic distribution


Typical Group Monitoring LocationTypical Group Monitoring LocationTypical Group Monitoring Location


Group Permit OptionGroup Permit OptionGroup Permit Option

• Selected facilities conducted monitoringand submitted data to EPA

• By 1992, most facilities in Groups hadState general permits available

» State permits were considerable less burdensome

• Ultimately Groups disbanded

• In Dec. 1995, EPA published Group dataand benchmarks in Federal Register


1995 Group Data1995 Group Data1995 Group Data

• Divided in similar sector designations (A–AC)still used today

» More subsectors

• Some parameters represented by most sectors» TSS, BOD, COD

• Some parameters represented by only a fewsectors

» TP, metals, toxic organics

• Range of number of results for each sector» 10 – 20, up to hundreds


MPCA BenchmarksMPCA BenchmarksMPCA Benchmarks

• All industrial sectors have one or morebenchmarks

• All sectors have benchmark for TotalSuspended Solids (TSS)


MPCA BenchmarksMPCA BenchmarksMPCA Benchmarks

NC State standards12TP

Median of NURP Results0.680.68Nitrate

Many based on FAV in Statestandards

Adjusted for hardness

Many based on FAV in Statestandards

Adjusted for hardness

120

25

100

2010 MPCABenchmarks *

Sb, Ar, Cd,Cu, Se,Ag,

Al, Pb, Hg,Ni, Zn

COD

BOD

TSS

Detection Limit x 3.18Detection Limit x 3.18

Ambient water quality criteriaAmbient water qualitycriteria

4x BOD benchmark120

POTW Secondary Treatment Standards30

Median of NURP Results100

Basis for EPABenchmark

1995 EPABenchmark

* Note: The same benchmarks are used by many States, therefore analysis and

conclusions apply across US


Distribution of Data:Distribution of Data:Distribution of Data:


Distribution of Data:Normal DistributionDistribution of Data:Distribution of Data:Normal DistributionNormal Distribution


Distribution of Data:Log Normal Distribution

Distribution of Data:Distribution of Data:Log Normal DistributionLog Normal Distribution


Comparison of All Sector DataTo MPCA Benchmarks

Comparison of All Sector DataComparison of All Sector DataTo MPCA BenchmarksTo MPCA Benchmarks

• Combine all 1995 industrial sectordata

• Compare MEDIAN to BenchmarkMedian (mg/L) / Benchmark (mg/L)


Comparison of All Sector DataTo MPCA Benchmarks

Comparison of All Sector DataComparison of All Sector DataTo MPCA BenchmarksTo MPCA Benchmarks

0

1

2

3

4

5

6

7

TSS TP BOD COD Cr Cd Ag Ni Al Fe Pb Cu Zn

Me

dia

n/B

en

ch

ma

rk

Median of all data = MPCA Benchmark

Insuff.data

Insuff.data

Insuff.data

Insuff.data


Individual Sector DataIndividual Sector DataIndividual Sector Data

• Conventional Wastewater Parameters» TSS, BOD, COD, TP

• Heavy metals» Fe, Zn

• Data expressed as “% of sector individualresults that exceed benchmark”

» e.g., probability that any one sample exceedsbenchmark

• Only presenting results for sectors that areassigned that chemical benchmark


Total Suspended SolidsTotal Suspended SolidsTotal Suspended Solids

0%

10%

20%

30%

40%

50%

60%

70%

80%

A1 A3 B D E4 E1 F1 F3 G I K M O P2 P4 Q S U U U U V X Y AA AB

%o

fS

am

ple

sE

xceed

ing

MP

CA

Ben

chm

ark



0%

10%

20%

30%

40%

50%

60%

70%

80%


%o

fS

am

ple

sE

xceed

ing

MP

CA

Ben

chm

ark

A3.Log storage& handling

D. Asphalt &paving prod.

G. Mining

L. LandfillsU8. Fats/Oils

manufacturing



0%

10%

20%

30%

40%

50%

60%

70%

80%


%o

fS

am

ple

sE

xceed

ing

MP

CA

Ben

chm

ark

USPS


BODBODBOD

0%

20%

40%

60%

80%

A B D E E F F G I K M O P P Q S U U U U V X YAA AB

%o

fS

am

ple

sE

xc

eed

ing

MP

CA

Be

nch

mark


BODBODBOD

0%

20%

40%

60%

80%

A B D E E F F G I K M O P P Q S U U U U V X YAA AB

%o

fS

am

ple

sE

xc

eed

ing

MP

CA

Be

nch

mark

U8. Fats/Oils

manufacturing


CODCODCOD

0%

20%

40%

60%

80%

A C E E F H K N P P S U U U X Z AB

%o

fS

am

ple

sE

xce

ed

ing

MP

CA

Ben

ch

mark


CODCODCOD

0%

20%

40%

60%

80%


%o

fS

am

ple

sE

xce

ed

ing

MP

CA

Ben

ch

mark

U8. Fats/Oilsmanufacturing

A1. Saw Mills


Total PhosphorusTotal PhosphorusTotal Phosphorus

0%

20%

40%

60%

80%

A C E E F H K N P P S U U U X ZAB

%o

fS

am

ple

sE

xcee

din

gM

PC

AB

en

ch

mark


Total ZincTotal ZincTotal Zinc

0%

20%

40%

60%

80%

A1

A3 B D E4 E1 F1 F3 G I K M O P2 P4 Q S U U U U V X Y A

AAB

%o

fS

am

ple

sE

xceed

ing

MP

CA

Ben

ch

mark


Total IronTotal IronTotal Iron

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%


%o

fS

am

ple

sE

xce

ed

ing

MP

CA

Ben

ch

mark


Total IronTotal IronTotal Iron

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%


%o

fS

am

ple

sE

xce

ed

ing

MP

CA

Ben

ch

mark

M. Auto salvageF. Foundries


Influence of On-Site MaterialsInfluence of OnInfluence of On--Site MaterialsSite Materials

Compared stormwater results within twosubgroups:

1. TRI Reporters – facilities that processlarger quantities of chemical

2. Non TRI Reporters - facilities that usesmall quantities or none of chemical


Stormwater Results For TRI andNon-TRI Facilities

Stormwater Results For TRI andStormwater Results For TRI andNonNon--TRI FacilitiesTRI Facilities

50%

56%

21%

29%

40%

45%

51%54%

0%

50%

100%

TRI Non TRI TRI Non TRI TRI Non TRI TRI Non TRI

%o

fS

amp

les

Ex

cee

din

gB

en

chm

ark

CopperCopper AluminumLead Zinc


What is the probability a facilitywill meet its benchmarks?

What is the probability a facilityWhat is the probability a facilitywill meet its benchmarks?will meet its benchmarks?

• Benchmarks are not compared to singlevalues

• Minimum of four quarterly samples arecollected

• Mean of all samples is compared tobenchmark concentration


Example 1995 Dataset: TSSSector P. Transportation/Warehousing

Example 1995 Dataset: TSSExample 1995 Dataset: TSSSector P. Transportation/WarehousingSector P. Transportation/Warehousing

Y-A

xis


Two Possible TSS BenchmarksTwo Possible TSS BenchmarksTwo Possible TSS BenchmarksY

-Axis

65 mg/LDischarges to

wetlands

100 mg/L

All other discharges


Monte Carlo SimulationRandomly draw four samples, then calculate mean; 1,000 trials

Monte Carlo SimulationMonte Carlo SimulationRandomly draw four samples, then calculate mean; 1,000 trialsRandomly draw four samples, then calculate mean; 1,000 trials

Y-A

xis

Sample #1

Sample #2

Sample #3

Sample #4

…then calculate mean


ResultsResultsResults

19%34%Existing data set

% facilities meeting

65 mg/L benchmark

% facilities meeting100 mg/L benchmark


Scenario 2: Cut-off HighConcentrations

Scenario 2: CutScenario 2: Cut--off Highoff HighConcentrationsConcentrations

Y-A

xis

Limithighestvalues to< 500mg/L



33%44%Limit high values(<500 mg/L)



65 mg/L benchmark



Scenario 3: ResampleTake two additional samples

Scenario 3: ResampleScenario 3: ResampleTake two additional samplesTake two additional samples

Y-A

xis

Sample #5

Sample #6



21%36%Two extra samples

33%44%Limit high values(<500 mg/L)



65 mg/L benchmark



ConclusionsConclusionsConclusions

• Benchmarks more likely to be exceededare:

» TSS

» Metals, especially iron

• All industrial sectors are equally likely toexceed benchmarks for TSS

• For toxic chemicals and metals, volumeof use or storage on-site is not a goodpredictor of meeting benchmarks


ConclusionsConclusionsConclusions

• Certain industrial sectors are more likely toexceed other benchmarks

» Food sector – COD, BOD

» Sawmills – COD

» Primary metals/foundries – Fe, Cu

» Concrete plants – Fe

» Salvage yards – Al, Fe

• Improving chance of meeting benchmarksrequires active prevention program

• Resampling without corrective action does notimprove chances of meeting benchmarks


QuestionsQuestionsQuestions

Loren LarsonCaltha LLP

Minneapolis, [email protected]

(763) 208-6430

www.calthacompany.com

comparison of mpca stormwater benchmarks with historical industrial sector monitoring results

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