2016 aehs statistics sediment forensic presentation cherry

Forensic Sediment Evaluation: Differentiating Basin Derived Media vs. Anthropogenic Sources using Multivariate StatisticsEric M. Cherry, Principal ScientistGina Groom, MPH Health Scientist

Hexagon Environmental Solutions LLCEnvironmental Chemistry | Forensics | Data Evaluation | Risk Analysis

Every Story has a Beginning• A Little History

• Geochemical Prospecting• Geophysics (statistics on a sphere)• Multivariate Analysis since 1980 (punch cards)• Learning to “keep it simple”

• Initiating Quotes• “What do you mean these metals came from the

watershed? There is a source right here.” Opposing counsel

• “What do you mean that most of these PAHs came from upstream? That’s undeveloped land and there are sources here in the harbor!” Senior technical colleague

• “We use accepted protocols and high precision analytical instruments, so that we can put data in spreadsheets then run statistical models, and ultimately derive a reasonable story of what is going on. We are high-tech story tellers!” Eric Cherry

Hexagon Environmental Solutions2

Sediment Assessment - Fundamental Questions • Do the sediments in this river or harbor pose

a risk to the aquatic ecosystem or to human health?

• If so, by what chemicals or elements?

• If so, where?

• If so, who is responsible and who will pay?


• What are these sediments composed of?

• Are there multiple chemical signatures in the sediments?

• Are there locations that are clearly different from others?

• How are they different?

• Can we identify a specific source?

• Do these sediments pose a risk?

• Why is the question being asked?

• Who is the audience?

• Who are the Stakeholders?

Approaches to Sediment Evaluation


• Traditional Approach• Develop and Implement Sampling &

Analysis Plan

• Calculate chemical-specific distributions

• Compare to Sediment Quality Values

• Refine and Delineate Impacted Areas

• Develop and Implement Remedial Plan

• Obtain Funds from PRPs/RPs

• Alternate Forensic Approach• Develop and Implement Tiered and Sequential

Sampling & Analysis Plan

• Evaluate multiple chemical relationships to identify associated and unique sample groups by multivariate methods

• Conduct supplemental sampling for delineation, sequential extraction and toxicity testing

• Refine and Delineate Impacted Areas based on supplemental testing

• Develop and Implement Remedial Plan

• Obtain Funds from PRPs/RPs

The Traditional Approach to Sediment Evaluation

• Identify Contamination based on Criteria or Limit• Freshwater

Lowest Effects Level (LEL)Probable Effects Level (PEL)Severe Effects Level (SEL)

• Marine Effects Range Low (ERL)Effects Range Medium (ERM)

• State Values• International Values


USEPA/Weston, 2012. Sediment Assessment Report – St. Louis Bay-St. Louis River Area of Concern. DCN 1023-2A-ATMN

The Math of How the Traditional Approach Works

• Obtain sediment data for arsenic (or other chemical)

• Sort by Concentration• Compare to Consensus

Value

• Green Data Set• 43.8% Exceed Tel• 5.5% Exceed Background• 1.8% Exceed PEL• 0.0% Exceed SEL


Background Metals vs. Potentially Impacted Sediments

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1 11 21 31 41 51 61 71 81 91 101 111 121 131 141 151 161

S ample Number

Severe Effects Level 33 mg/kg

Probable Effects Level 17 mg/kg

Threshold Effects Level 5.9 mg/kg

Background = mean + 2 sd 13.9 mg/kg

Arsenic vs. Consensus Value

Evaluation of Traditional Approach

• Advantages of Traditional Approach

• Easy to perform evaluation

• Clear decision points

• Delineation sampling to refine extent of impact

• Very conservative approach (i.e. “protective”)

• Easy to communicate to Stakeholders

• Disadvantages• Default classification of “contamination”

based on Consensus values (how do we define contamination?)

• Non-holistic

• Is not capable of identifying natural relationships

• Oversimplifies a complex system

• Probably overestimates extent of toxic impacts

• More expensive to implement remedy


Overview of the Forensic Approach• Defining “Forensics”

• It’s all about “making the argument” in a science-based and logical manner

• Start with a “Single Blind” approach to identify what the data is saying chemically, then expand to spatial relationships (minimize investigator bias)

• Does not require, but may include, advanced analytical methods

• Does include more sophisticated data evaluation techniques

• Objective is to translate complex information into a story that is understandable to multiple Stakeholders

• Forensic Toolbox• Given . . . A big data set!

• Pair-wise regression (Fe:As, Pb:Zn)

• Cluster Analysis (Family Associations)

• Principal Component Analysis

• Concentration Distributions

• Spatial Distribution of Families

• Association of Family Composition Profiles to Potential Source Profiles

• Toxicity Testing and Sequential Extraction

• Infographics! Hexagon Environmental Solutions

8

Forensics – Doing the Math!


Meet the Stakeholders!• What are our goals?

• Understand the concerns• Protect/Restore the environment• Be true to the science• Understand the physical system• Be fiscal stewards with limited resources• Communicate clearly and involve

stakeholders


I’m Roy the

Regulator

I’m Black Hat

Industries

I’m Freddy Fisherman,

Nature Lover

Quick Summary with Legos!


Sediments are “in the Basin”Complex mixture, but we have a sampling and analysis plan . . . And a sequential protocol for data evaluation

Each sample (n=10) contains target and non-target analytes

Quick Summary with Legos!


Target analyte concentrations vary within a sample and total (sum) of analytes varies

Relative proportions of different analytes may vary between samples, and some analytes may be absent

Dealing with real data

• Given a real data set, what are the questions?• What are the baseline relationships

between chemical parameters?

• Where are the commonalities?

• Where are the differences?

• What is unique?

• What are the methods?• Regression – line, lines, shotguns• Cluster Analysis – family groups• Principal Component – prom night• Confounders - yea, that influences things• Spatial Relationships – there but not here• Supplemental evaluation – how bad is it,

really• Infographics – every picture tells a story• Conclusions – many legs make a stable

table


Regression and Cross-Plots


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Fe

Zn

Pb

Cu

Cr

Ni

As

Cd

Hg

2b-TIN

3b-TIN

Matrix Plot of Fe, Zn, Pb, Cu, Cr, Ni, As, Cd, Hg, 2b-TIN, 3b-TIN

Fe

Zn

Pb

Cu

Cr

Ni

As

Hg

Cd

2Sb

3Sb

Fe:CdShotgun(?)

HgOutlier!

Zn:PbMulti-Linear

Fe:NiLinear

Regression and Cross-Plots: Parsed!


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Fe

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2b-TIN

3b-TIN

Matrix Plot of Fe, Zn, Pb, Cu, Cr, Ni, As, Cd, Hg, 2b-TIN, 3b-TIN

Cluster Analysis – Finding Family Groups


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Observations

Sim

ilari

ty

DendrogramComplete Linkage, Pearson Distance

• Purpose is to classify samples based on criteria

• Multiple methods are available

• Evaluator judgement should be based on project requirements

• Data pre-processing may be necessary

Clusters by Relative Proportion of Target Metals


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Mean ALL Group MCA D 1n=151

Group MCA D 4n=51

Group MCA D 3n=5

Group MCA D 5n=4

Group MCA D 2n=2

Group MCA D 7n=2

Group MCA D 6n=1

Relative Metal Proportions in MCA Cluster Groups

Zn Pb Cu Cr Ni As

Clusters by Concentration


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Mean ALL Group MCA D 1n=151

Group MCA D 4n=51

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Group MCA D 5n=4

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Group MCA D 7n=2

Group MCA D 6n=1

Cum

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Cumulative Metal Concentrations in MCA Cluster Groups

Zn Pb Cu Cr Ni As

Principal Component Analysis – Let’s Dance


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Principal Component 1 (from MCA D Groupings)

Group 1 PCA 2 Group 4 PCA 2 Group 3 PCA 2 Group 5 PCA 2

Group 2 PCA 2 Group 7 PCA 2 Group 6 PCA 2

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Principal Component 1 (from MCA D Groupings)

Group 1 PCA 2 Group 4 PCA 2 Group 3 PCA 2 Group 5 PCA 2

Group 2 PCA 2 Group 7 PCA 2 Group 6 PCA 2

What about those Anthropogenic Metals!


y = 0.1202x - 0.3098R² = 0.8416

y = 0.0003x + 0.0078R² = 0.0005

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Trib

utyl

Tin

(mg/

kg)

Arsenic (mg/kg)

Tributyltin vs. Arsenic

As As-lo Linear (As) Linear (As-lo)

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Arsenic (mg/kg)

Tributyltin vs. Arsenic

TBT Fraser Shipyard TBT Other Howard's Bay

Tributyltin is an anthropogenic organometallic compoundIts primary function is as an additive to marine paints to prevent biofouling on ships. It is intentionally toxic.

Tributyltin and other Metals: Paint formulations?


In regression analysis, one must consider both statistical relevance and physical plausibility.

y = 1.1072x - 0.0618R² = 0.6488

y = 0.0191x + 0.0017R² = 0.1018

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utyl

Tin

(mg/

kg)

Mercury (mg/kg)

Tributyltin vs. Mercury

Hg Hg-lo

Linear (Hg) Linear (Hg-lo)

y = 0.4659x - 0.128R² = 0.779

y = 0.0238x - 0.0096R² = 0.2448

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utyl

Tin

(mg/

kg)

Cadmium (mg/kg)

Tributyltin vs. Cadmium

Cd Cd-lo

Linear (Cd) Linear (Cd-lo)

y = 0.0053x - 0.0046R² = 0.6287

y = -1E-05x + 0.0099R² = 0.002

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utyl

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Lead(mg/kg)

Tributyltin vs. Lead

Pb Pb-lo

Linear (Pb) Linear (Pb-lo)

Confounding Variables

• A confounding variable is something that may affect the correlates with the dependent and independent variable

• It is a factor that may need to be adjusted for in interpreting a data set

• Potential confounders for metals in sediments include grainsize and organic carbon

• Important general questions• Where do sediments actually

come from?• How is the sediment source area

characterized?• What changes have happened in

the source area and when?• What changes have happened in

the receiving are (sediment basin) and when?


Grainsize as a Confounding Factor


y = 0.2476x + 7.4777R² = 0.5784

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Percent Silt+Clay

Nickle vs Grain Size

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Percent Silt+Clay

Nickle vs Grain Size

<LEL samples = 31.2% n=128

>LEL & <PEL samples=65.1% n=267

>PEL samples=3.7% n=15

That Next? Supplemental Analyses

• Sequential Extraction• Surrogate for bioavailability

• More expensive than standard analyses

• Easily soluble

• Carbonate bound

• Organic bound

• Iron Oxide bound

• Residual

• Sediment toxicity testing• Surrogate for actual toxicity based

on specified organisms

• More expensive than chemical analysis or sequential extraction

• Probably best estimate of actual ecological toxicity measure


Spatial Distribution – “Taking the blinders off”

• How does “what the data says” from compositional profiles compare with “location of samples”?

• How does the “location of samples” compare with reasonable “potential source areas”?

• Example from large sediment study

• Active marine harbor

• Urban setting

• Drainage basin characterized by mixed industry, agriculture and large forest tracts


PAH Profiles and PCA Diagram


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Title

Title

Sediment PAH - PCA ResultsPC 1 vs PC 2

Sed PAH Group A Sed PAH Group B Sed PAH Group C

Sed PAH Group D Sed PAH Group E Sed PAH Group F

Sed PAH Group G Sed PAH Group H Sed PAH Group I

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NAP

1mN

AP2m

NAP AN

YAC

EFL

UAN

TPH

EFL

APY

RBa

ACH

RBb

FBk

FBa

PBe

PD

BA PER IP

BPE

PAH 1462 Group A n=677 (46.31%)

0.000.020.040.060.080.100.120.140.160.18

NAP

1mN

AP2m

NAP AN

YAC

EFL

UAN

TPH

EFL

APY

RBa

ACH

RBb

FBk

FBa

PBe

PDB

APE

R IPBP

E

PAH 1462 Group D n=40 (2.74%)

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NAP

1mN

AP2m

NAP AN

YAC

EFL

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RBa

ACH

RBb

FBk

FBa

PBe

PDB

APE

R IPBP

E

PAH 1462 Group F n=13 (0.89%)

Spatial Distribution after Cluster Analysis


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7,600,0007,610,0007,620,0007,630,0007,640,0007,650,0007,660,000

Nor

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Easting

Sediment PAH Group A Distributions

Sed Samples Group A

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Sediment PAH Group D Distributions

Sed Samples Group D

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7,600,0007,610,0007,620,0007,630,0007,640,0007,650,0007,660,000

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thin

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Easting

Sediment PAH Group F Distributions

Sed Samples Group F

Urban Background Petroleum Combustion and Asphalt/Creosote

Coal and Natural Diagenetic PAHs

Conclusions• Clearly identify the goals and objectives of a sediment project

prior to establishing all methods of evaluation

• Application of multivariate statistical methods in a forensic approach can identify relationships within the basin

• Professional judgement combined with proper application of methods is essential for resolving the story in complex data sets

• Multiple lines of evidence can help to determine whether high concentration samples are associated with natural materials or anthropogenic sources of contamination

• Forensic methods of data evaluation may be slightly more expensive during investigation, but are negligible in comparison to undertaking remediation of natural sediments without significant contribution from anthropogenic sources.


Questions?

2016 aehs statistics sediment forensic presentation cherry

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