Modelling of PFOS fate and transport - rpic-ibic.ca · Modelling of PFOS fate and transport ! ... Authors( Year( Kd( units( Koc( units( Soiltype/soilsource (Enevoldsen& Juhler! 2010!

Modelling of PFOS fate and transport

Thomas Franz, Adam Dawe, Lauren McDonald, Franz Environmental Inc.

Chris>ne Levicki, Health Canada John Miller, Environment Canada

Conceptual model

PFOS source area (e.g. FFTA)

Dissolved phase

Leachate

Groundwater flow

Drinking Water

Surface Water

•  Par>>oning from soil to pore water (to soil gas)

•  Transport of soil leachate through unsaturated zone

•  Mixing of soil leachate into groundwater

•  Transport in aquifer

Model capabilities •  The model was designed to back-‐calculate soil concentra>on at PFOS source loca>on for a given concentra>on in groundwater or surface water

• Now also does “forward” calcula>ons by simula>ng PFOS transport •  from soil to groundwater to receptor •  within groundwater to receptor

CCME, 2006

•  SQG = DF1 x DF2 x DF3 x DF4 x DF5 x CMAC

10 m

CMAC-‐DW

CMAC-‐AW

New: dilu%on at receptor (e.g. in wellbore or at groundwater -‐ surface water interface)

CCME, 2006

•  SQGPW = DF1 x DF2 x DF3 x DF4 x DF5 x CMAC

10 m

CMAC-‐DW

CMAC-‐AW

CCME, 2006

•  SQGPW = DF1 x DF2 x DF3 x DF4 x DF5 x CMAC

10 m

CMAC-‐DW

CMAC-‐AW

1 1 1

~7.3 ~2.4 to ~3.4

Cs = Kd Cw

Sorp%on

Higgins & Luthy, 2006) Tang et al., 2010

•  PFOS-‐surface electrosta>c •  PFOS-‐PFOS electrosta>c repulsion •  Hydrophobic sorp>on

foc increases à Kd increases Higgins & Luthy, 2006)

What affects sorption? • Hydrophobic sorp%on

•  Hydrophobic interac>on is the dominant mechanism of PFOS sorp>on to organic carbon,

•  Strong hydrophobic nature of its perfluoroalkyl chain (Higgins and Luthy, 2006).

•  Hydrophobic interac>on can also arise between the hydrophobic chains of different PFOS molecules.

•  Koc and foc (frac>on of organic carbon) are used to calculate adsorp>on coefficient (Kd)

What affects sorption? • Hydrophobic sorp%on

•  PFOS sorp>on increases in oil contaminated soil

Oil contaminated soil à Kd increases Chen et al., 2009

Higgins & Luthy, 2006)

What affects sorption? • PFOS-‐surface electrosta%c interac%on due to pH.

•  PFOS is nega>vely charged under all environmentally relevant pH values.

•  A mineral surface becomes more posi>vely charged (or less nega>vely charged) at lower pH.

•  Enhanced electrosta>c afrac>on force (or reduced electrosta>c repulsion force) results between the nega>vely charged PFOS molecules and the more posi>vely charged mineral surface at lower pH.

pH decreases à Kd increases

What affects sorption? • PFOS-‐PFOS electrosta%c interac%on.

•  Two adjacent PFOS molecules on a surface will repel each other due to their nega>vely charged sulfonate head groups.

•  A strong PFOS-‐PFOS repulsion tends to prevent these molecules gehng close to each other.

•  Thus, a solu>on with high ionic strength has a tendency to promote PFOS adsorp>on as a result of the suppressed electrosta>c repulsive force.

Higgins & Luthy, 2006)

What affects sorption? • PFOS-‐surface electrosta%c interac%on due to pH.

•  PFOS is nega>vely charged under all environmentally relevant pH values.

•  A mineral surface becomes more posi>vely charged (or less nega>vely charged) at lower pH.

•  Enhanced electrosta>c afrac>on force (or reduced electrosta>c repulsion force) results between the nega>vely charged PFOS molecules and the more posi>vely charged mineral surface at lower pH.

pH decreases à Kd increases

(Higgins & Luthy, 2006; Chen et al., 2009; Pan and You, 2010; You et al., 2010)

What affects sorption? • PFOS-‐surface electrosta%c interac%on due to ionic strength.

•  Electrosta>c interac>on can be significantly weakened at higher ionic strength due to the “double layer compression effect”.

•  For a posi>vely charged mineral surface, the amount of adsorbed PFOS tends to be reduced due to the weaker electrosta>c afrac>on. However, for a nega>vely charged surface, adsorp>on tends to increase as a result of weaker electrosta>c repulsion.

e.g. Ca2+ decreases à Kd increases

Reviewed partitioning studies • Method

•  Selected studies with low dissolved PFOS concentra>ons •  Went to original papers •  Eliminated duplica>ons and copies •  Problem: many studies are for marine sediments (not soil)

•  Results •  PFOS Koc ranges from 229 to 6310 (Kd from 0.08 to 250 L/kg) •  Median Koc 1441 L/kg (log Koc = 3.16 L/kg)

•  Programmed spreadsheet to determine median Koc •  Can add data to this spreadsheet and/or manually override Koc •  Programmed pseudo-‐func>on to simulate pH dependency

Typical Koc’s (L/kg) •  Benzene = 165.5 •  Toluene = 268 •  B(a)P = 787000 •  Naphthalene = 1837 •  TCE = 67.7 •  Acenaphthene = 6123

•  PFOS = 229 -‐> 6310

Authors Year Kd units Koc units Soil type / soil source Enevoldsen & Juhler 2010 15 L/kg 1500 L/kg Jyndevad (Denmark) soil, agricultural topsoil, A horizon, sandy soil Enevoldsen & Juhler 2010 17 L/kg 4048 L/kg Sj. Odde (Denmark) soil, agricultural topsoil, A horizon, clayey soil Ferry et al 2012 1.23 L/kg 3514 L/kg Minnesota aquifer material from landfill Ferry et al 2012 0.08 L/kg 229 L/kg same microcosm, but at end of 740 d study 3M 2001 18.3 L/kg 704 L/kg clay 3M 2001 9.72 L/kg 374 L/kg clay loam 3M 2001 35.3 L/kg 1260 L/kg sandy loam 3M 2001 7.42 L/kg 571 L/kg river sediment Chen et al., 2012 2012 38.0 L/kg 2659 L/kg marine sediment, S1, from Dalian coastal area, China Chen et al., 2012 2012 25.7 L/kg 2596 L/kg marine sediment, S2, from Dalian coastal area, China Chen et al., 2012 2012 25.1 L/kg 3101 L/kg marine sediment, S3, from Dalian coastal area, China Chen et al., 2012 2012 20.0 L/kg 2660 L/kg marine sediment, S4, from Dalian coastal area, China Chen et al., 2012 2012 15.8 L/kg 3774 L/kg marine sediment, S5, from Dalian coastal area, China Chen et al. 2009 12.3 L/kg 1349 L/kg soil from paddyfield in Panjin, China Higgins and Luthy 2006 16 L/kg 372 L/kg freshwater sediments (rivers and lakes) from USA Ahrens et al. 2011 1.5 L/kg 5012 L/kg sandy river sediment from Kogaigawa, Japan Ahrens et al. 2011 50.6 L/kg 3162 L/kg muddy river sediment from Sakuragawa, Japan Ahrens et al. 2011 27.6 L/kg 2512 L/kg muddy marine sediment from Tokyo Bay Ahrens et al. 2010 126 L/kg 6310 L/kg marine sediment cores from Tokyo Bay, Japan Kwadijk et al. 2010 224 L/kg 1445 L/kg 19 sediment samples from rivers, lakes, canals in Netherlands Labadie & Chevreuil 2011 251 L/kg 5012 L/kg sediment from Orge River, France (near Paris) Johnson et al. 2007 2.81 L/kg Ofawa sand Johnson et al. 2007 5.31 L/kg 265.5 L/kg kaolinite Johnson et al. 2007 7.52 L/kg 376 L/kg Lake Michigan sediment Johnson et al. 2007 7.88 L/kg goethite Johnson et al. 2007 8.9 L/kg high iron sand Johnson et al. 2007 18.3 L/kg 610 L/kg clay Johnson et al. 2007 9.72 L/kg 324 L/kg clay loam Johnson et al. 2007 35.3 L/kg 1177 L/kg sandy loam Johnson et al. 2007 7.42 L/kg river sediment

Model limitations •  Equilibrium par>>oning between soil, water, vapour phases

•  Assumes rela>vely low concentra>ons in soil / groundwater •  PFOS concentra>ons should be less than 10 mg/L •  Solubility = 500 to 600 mg/L (in freshwater), 12 mg/L (in seawater)

• Homogeneous geology •  However, can be different in unsaturated / saturated zones

• Uniform, unidirec>onal groundwater flow • Constant source concentra>on

Primary data requirements • Coordinates: x, y, z • Geometry of PFOS source •  Frac>on of organic carbon (foc) • Unsat zone thickness • Average linear groundwater velocity • Aquifer thickness • Dispersivity

Model comparison of predicted vs measured ground water concentrations Four sites evaluated for transport modeling and empirical Kd calcula>ons: • All at civilian or military airports •  3 FFTAs •  1 disposal site

Dissolved phase

Koc, foc-‐unsat, m

Koc, foc-‐sat, b, v, n, alfa

C=?

Disposal Site Soil and Ground Water Concentrations

33.0

11.8

21

34.5

26.1

3

0.077

0.160

33.0 = Ground Water Concentra>on, units of ug/L

0.077 = Soil Concentra>on, units of mg/Kg

Oil Disposal Pit

28

FFTA 1 – Shallow Ground Water Contours

Fire Training Area

FFTA 1 – Soil and Ground Water Concentrations

4400

2100

600

2.8

<0.02 = Ground Water Concentra>on, units of ug/L

2800 = Soil Concentra>on, units of mg/Kg

Fire Training Area

Model result with literature Koc (Koc = 1445 L/kg; Kd,sat = 2.17 L/kg)

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

0 5 10 15 20 25 30 35 40 45 50

Concen

tra>

on (m

g/L)

Distance from source (m)

Predicted vs Measured PFOS Concentra>ons in Ground Water

Predicted

Measured

Model “calibration” • Match between observed and modelled PFOS concentra>ons was not very good using literature Koc (Kd) values

• Approach to improve model results:

•  1) Derived site-‐specific Kd values based on co-‐located soil and groundwater samples from the site(s) -‐> re-‐run model

•  2) Adjust Kd to obtain best fit -‐> “brute force”

Empirical Koc’s • Calculated “empirical” Kd by comparing co-‐located soil and groundwater sample concentra>ons

• Calculated Koc from Kd = Koc foc •  foc based on site-‐specific data

• Empirical Koc values range from 85 to 7619 (L/kg) • Literature Koc values range from 229 to 6310 (L/Kg)

Model result with median empirical Kd (Kd = Koc foc = 1.6 L/kg ; Koc = 424 L/kg)

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

0 5 10 15 20 25 30 35 40 45 50

Concen

tra>

on (m

g/L)



Predicted

Measured

Brute Force – best fit • Excel SOLVER used to adjust Kd

-‐> obtain best fit between observed and modelled PFOS concentra>ons

Model result with best fit Kd (Kd sat = 0.1 Kd unsat) (Kd,sat = 0.514 L/kg; Koc = 342 L/kg)

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

0 5 10 15 20 25 30 35 40 45 50

Concen

tra>

on (m

g/L)



Predicted

Measured

Adjust other model parameters

• Koc alone is not the problem… • Modified transverse (horizontal) dispersivity to achieve befer match

• Likely unrealis>c dispersivity value

Adjust transverse dispersivity (transverse = longitudinal dispersivity) (Kd,sat = 1.2 L/kg)

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

0 5 10 15 20 25 30 35 40 45 50

Concen

tra>

on (m

g/L)



Predicted

Measured

Conclusions •  Simple mathema>cal model for PFOS fate & transport has been developed.

•  Runs in Excel, easy to use, has a series of limita>ons. •  Limita>ons are similar to other models used for guideline development and risk assessment

•  Use with cau>on for site specific applica>ons •  Primary afenua>on process for PFOS is par>>oning (sorp>on).

•  Greatest uncertainty for modelling of PFOS stems from par>>oning coefficient •  Review of Koc’s

•  Empirical Koc’s range from 85 to 7619 L/kg •  Literature Koc’s range from 229 to 6310 L/kg

• Model results match field data befer for Koc’s at the low end of the range (i.e. less sorp>on / more mobile)

Recommenda>ons

• For assessment of PFOS fate & transport, we need to collect •  foc data in unsaturated soil zone •  foc data in aquifer (groundwater transport) zone • Collect data pairs of “co-‐located” soil and groundwater directly below source to determine site-‐specific Kd

• pH

Acknowledgments •  Sanya Petrovic, Health Canada • Brian Asher, Health Canada •  Luigi Lorusso, Health Canada •  Jo-‐Ann Aldridge, Environment Canada • Philippa Coureton, Environment Canada

Disposal Site Soil and Ground Water Concentrations

33.0

11.8

21

34.5

26.1

3

0.077

0.160

33.0 = Ground Water Concentra>on, units of ug/L

0.077 = Soil Concentra>on, units of mg/Kg

Oil Disposal Pit

28

Cold lake – best solution, solve for unsat and sat Kd (0 <= unsat kd <= sat Kd

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0 50 100 150 200 250 300 350 400

Concen

tra>

on (m

g/L)



Predicted

Measured

Documents

Modelling of PFOS fate and transport - rpic-ibic.ca · Modelling of PFOS fate and transport ! ... Authors( Year( Kd( units( Koc( units( Soiltype/soilsource (Enevoldsen& Juhler! 2010!