THE RISE OF THE FINELY-ADVANCED TRANSBOUNDARY

ENVIRONMENTAL MODEL (FATE): A STATE-OF-THE-ART MODEL

PREDICTION OF THE GLOBAL SINK OF PERSISTENT ORGANIC

POLLUTANTS

Kawai, T.1, Handoh, I.C.1, and Takahashi, S.1

1 Centre for Marine Environmental Studies (CMES), Ehime University, Matsuyama, Japan

Abstract

The Finely-Advanced Transboundary Environmental model (FATE) was developed to better understand and

quantify the non-steady dynamics of Persistent Organic Pollutants (POPs) in the global environment. FATE

is a simulator that encodes POPs dynamics in the five environmental compartments (atmosphere, oceans,

cryosphere, soil, and vegetation), such as atmospheric advection and diffusion processes, and

bioconcentration processes in the vegetation and marine phytoplankton. We demonstrate the

FATE-predictions of the polychlorinated biphenyls (PCBs) #28 and #153, for the period of 1931-2100. Our

focus here is on the global sinks (degradations, and the removal to the deep oceans) of PCBs. The fractions of

annual global sinks in the environmental compartments varied significantly with the chlorination level of the

selected PCBs: The primary sinks in the past 80 years appeared to be degradations in the atmosphere and soil

for PCB#28 (58%) and PCB#153 (47%), respectively. PCB#153 removal to the deep ocean was a secondary

sink (21%), while this was not the case for PCB#28 (less than 1%).

Introduction

Modelling the dynamics of Persistent Organic Pollutants (POPs) is an important issue for 21st century

science. A rapid progress has been made in the development of numerical models for POPs dynamics, and

these models are capable of quantifying the long-range transport potential and the overall persistency of

POPs in the environment (See review of Fenner et al., 2005 1). However, high-resolution global models that

predict non-steady dynamics of POPs are yet to be developed (e.g., Malanichev et al., 2004 2; Leip and

Lammel, 2004 3). Model predictions of the POPs fate, such as environmental sinks on centennial timescales,

have not been reported even for well-known legacy POPs.

Considering above, we have developed a space-resolving, time-dependent, multi-compartment model to

predict the fate and transport of POPs, called the Finely-Advanced Transboundary Environmental model

(FATE). Our model is capable of quantifying the long-range transboundary transports, source-receptor

relationships, and persistent sinks of POPs, and may well be applicable to environmental risk assessments of

Vol. 71, 2009 / Organohalogen Compounds page 001599

POPs. We stress that the FATE incorporates oceanic biogeochemical processes, and thus quantifies POPs

removal to the deep oceans which are associated with phytoplankton detritus settling (Daches et al., 1999 4).

In this study, we outline the FATE and major physicochemical parameters and input/forcing data used in

the model runs that generate centennial predictions of two selected polychlorinated biphenyls (PCB #28 and

#153), and assess the global sinks.

Materials and methods

The FATE represents non-steady POPs dynamics within and across five environmental compartments:

atmosphere, ocean, cryosphere, soil, and vegetation

(Figure 1). The horizontal resolution is 2.5°×2.5°.

In the follow- ings, we briefly describe the

framework of, and integral input/forcing data of the

FATE.

Figure 1. Schematic diagram of the Finely-Advanced Transboundary Environmental model (FATE)

ATMOSPHERE: The model atmosphere, from the mean sea-level surface to the tropopause (100 hPa), is

divided into 10 sigma layers (σ = 0.95, 0.88, 0.76, 0.58, 0.43, 0.3, 0.19, 0.11, 0.05, and 0). The model solves

3D advection and diffusion, degradation, and gas/particle partitioning processes of POPs. Dry and wet

deposition and gaseous exchange with the underlying surfaces are calculated in the lowest atmospheric layer.

The degradation process of POPs in the atmosphere obeys a second-order equation of the POPs and OH

radical concentrations. Dry and wet deposition are parameterized by the methods of Tsyro and Erdman

(2000) 5, and Atlas and Jurado et al. (2005) 6, respectively. Gaseous exchange between the reference height in

the atmosphere ( 995.0=σ ) and the underlying compartments are formulated by a network of resistances for

the molecular and turbulent diffusions. The integrated mass transfer coefficients are estimated by the

Monin-Obukhov similarity theory.

OCEANS: The current version of the ocean compartment does not include both horizontal and vertical

transports of POPs. Instead, the model ocean consists of a large number of boxes, each of which has a height

equal to the depth of the mixed layer. Within each box, POPs partitioning between dissolved and

sorbed/adsorbed in/on marine phytoplankton4, degradation, and removal to the deep ocean associated with

σ = 0.76

σ = 0.58

σ = 0.43

σ = 0.30

σ = 0.19

σ = 0.11

σ = 0.05

CRYOSPHERE OCEAN SOIL

Grass land Broadleaf

forest

Coniferous

forest

σ = 0.90

σ = 0.99

Tropopause (100 hPa)ATMOSPHERE

VEGETATION

Emission

Degradation3D advection

and diffusion

Cgas Cparticle

MIXED LAYER

DEEP OCEANCRYOSPHERE

Cdissolved

DegradationDegradation

σ = 0.995Gaseous exchange

Dry/wet depositions

Detritus settling

VEGETATION

Cgas Cliquid

Csolid CDOC

Cleaf

Gaseous exchange Bioconcentration

Dry/wet depositions

Gaseous exchange

Degradation

Degradation

σ = 0.995

DefoliationDry deposition

SOILDiffusion

Vol. 71, 2009 / Organohalogen Compounds page 001600

Table 1. Physicochemical parameters for PCB#28

and #153 that are used in the model (Malanichev et

al., 2004 2

). R and T are the universal gas

constant and the ambient temperature, respectively.

0T is 283.15 K. All variables are non-

dimensional, except for the degradation rate

constant for the atmosphere which has unit,

113 −− smoleccm

Table 2. Input/forcing data used in FATE

phytoplankton detritus settling are determined. The degradation process of POPs is governed by a first-order

equation of POPs concentration. We have assumed that the turnover time of phytoplankton biomass through

the growth and motality is 66.7 days 4

.

CRYOSPHERE: The model assumes no POPs emission from the cryosphere to the atmosphere (Wania and

Mackay, 1995 7

). However, POPs deposited to the cryosphere from the atmosphere by dry/wet deposition

degrade at the same degradation rate as that used for the oceans.

SOIL: The soil compartment consists of 10 uniform vertical layers that range from the soil top to a depth of

30 cm; each layer is 3 cm deep. 1-D (vertical)

molecular diffusion, degradation, and partitioning

between gaseous, solid, dissolved phases, and

sorbed on dissolved organic matter are calculated.

The degradation of POPs is described by a first

order equation with a degradation rate constant

specific for POPs.

VEGETATION: The vegetation is classified into

five plant functional types, evergreen broad-leaved

and needle-leaved forests, deciduous broad-leaved

and needle-leaved forests, and grassland. The

intake of POPs into the vegetation compartment is

governed by dry/wet deposition and gaseous

exchange with the atmosphere. The

bioconcentration factor is parameterized for each

plant functional type as an exponential function of

the octanol-air partition coefficient (Mclachlan and

Horstmann, 1998 8

). The transport of POPs from

vegetation (leaf layer) to the vegetation soil, is

described by defoliation.

PHYSICOCHEMICAL PARAMETERS: The main

physicochemical parameters, partitioning

coefficients and degradation rate constants, are

summarized in Table 1. It is generally accepted that

the partitioning coefficients depend on the ambient

temperature. This temperature dependency is taken

species Values/equations

PCB#28

PCB#153

PCB#28

PCB#153

PCB#28

PCB#153

PCB#28

PCB#153

PCB#28

PCB#153

PCB#28

PCB#153Soil

Octanol/air

Degradation rate constants

Atmosphere

Ocean

Parameters

Partition coefficients

Air/water

Octanol/water

( )[ ]0/1/17430exp/642.7 TTRT −−

( )[ ]0/1/18347exp/146.4 TTRT −−51031.6 ×61094.7 ×

( )[ ]0

8/1/18731exp1078.5 TT −×

( )[ ]0

10/1/110811exp1064.3 TT −×

( )RT/13720exp107.2 10−×

( )RT/15380exp1012.8 11−×

71033.1 −×

91060.1 −×

9104.7 −×

91017.1 −×

Sources/references

Breivik et al., 2007 9

Wind velocity

Temperature

Precipitation rate

Mixed layer depth World Ocean Atlas 1994 11

Primary production SeaWIFS and VGPM 12

GLC2000 13

and USGS glcc v2 14

Soil organic carbon

contentsISRIC-WISE

15

Terrestrial data

Variables

Emission

Climate data

NCEP/NCAR reanalysis 1 10

Land cover

Vol. 71, 2009 / Organohalogen Compounds page 001601

into account in air/water and octanol/air partitioning coefficients.

INPUT/FORCING DATA: The input/forcing data used in the FATE are summarized in Table 2 with

corresponding data sources and/or references. Each data are interpolated onto 2.5°×2.5° horizontal grids.

Yearly, 6-hourly, and monthly data were used for emission, meteorology, and oceanography, respectively. The

emission data, which was provided by Breivik et al. (2007) 9, has a significant uncertainty in the estimate. For

simplicity, we have adopted the high emission scenario. FATE runs were all forced with 6-hourly and

monthly mean climatologies, and yearly emission data sets, thus explicitly resolving the seasonal and

interannual variability in all instances.

Results and discussion

The FATE-predicted global sinks/contents in each of the five environmental compartments were divided into

the following four periods: i) 1931－1970, ii) 1971－2008, iii) 2009－2050, and iv) 2051－2100 (Table 3).

Figure 2 shows the geographical distribution of global sinks for the year 1970 (the peak of the PCBs

emission).

The soil was shown to be the dominant reservoir of both PCB#28 and #153. The fraction of PCB#28

contents in the oceans tend to be significantly larger than that of PCB#153. In the light of the chronology, the

global sinks of PCB#28 and #153 exhibit distinct differences: In the past 80 years, degradation in the

atmosphere was the largest sink of PCB#28 (58%), while degradation in soil dominated PCB#153 (47%).

Removal to the deep oceans was found to be secondary sink of PCB#153 (21%), while this was not the case

for PCB#28 (less than 1%). These differences could be explained in part by those of physicochemical

properties of PCB#28 and #153 (see Table 1): The relatively large Henry's law constant and degradation rate

constant of PCB#28 for the atmosphere appeared to enhanced the oceanic content and atmospheric sink of

PCB#28. Similarly, the relatively small octanol/water partitioning coefficients of PCB#28 suppressed the

removal to the deep oceans.

It should, however, be stressed that the current development of the FATE contained some oversimplified

processes. The key issues to be addressed are summarized as follows: 1) The FATE did not incorporate any

key terrestrial hydrological processes, such as infiltration and/or surface runoff. Mclachlan et al. (2002) 16

pointed out that the vertical transports of dissolved-phase POPs significantly modify the vertical distribution

of POPs within the soil. Since the soil is always a dominant reservoir of PCBs (Table 2), removal of PCBs

from the surface soil by infiltration and/or surface runoff are unlikely to be trivial. 2) There were no POPs

transports processes in the modelled oceans. Lohmann et al. (2006) 17

suggested that the dynamic deep water

formation could be more effective sink of PCBs more than the biogeochemical settling associated with

organic carbon. This implies the needs for incorporation of 3-D oceanic advection and diffusion processes

that profile the global thermohaline circulation. 3) In the oceanic biogeochemistry of the FATE, we assumed

Vol. 71, 2009 / Organohalogen Compounds page 001602

constant growth and detritus rates that were extrapolated from studies on natural lakes, which was not

realistic. These rates could critically depend on phytoplankton functional types and the ambient temperature.

We have developed the state-of-the-art model, FATE, in order to better understand and quantify the

dynamics of POPs in the global environment. The FATE-predicted global sinks of PCB#28 and #153 could

provide new insights into our current understanding of the fate and transport of POPs. Nevertheless, the

FATE is of necessarily limited value in addressing full dynamics of POPs, owing to uncertainties in the input

data sets (especially the emission data) and the paucity of model validation. In order to surmount this

difficulty, we have now devoted much effort to 1) evaluate the FATE by extensive observation, and to 2)

combining the FATE predictions and Bayesian uncertainty analysis.

Table 3. Summary of the FATE-predicted global contents and sinks of PCB#28 and #153.

Global sinks (contents) (%) Total

sink

(ton) Atmosphere Ocean Soil Vegetation Cryosphere

Removal to the

deep ocean

[1931-1970]

PCB#28 58.26 (2.99) 11.78 (2.77) 15.58 (65.90) 13.38 (28.29) 0.25 (0.06) 0.75 (-) 3494.2

PCB#153 18.85 (0.62) 0.43 (0.70) 35.34 (78.57) 17.33 (19.27) 0.52 (0.84) 27.54 (-) 306.2

[1971-2008]

PCB#28 57.14 (2.77) 10.85 (2.26) 19.64 (73.45) 11.48 (21.46) 0.29 (0.06) 0.60 (-) 6625.8

PCB#153 16.56 (0.44) 0.36 (0.45) 50.18 (86.82) 12.35 (10.68) 1.27 (1.60) 19.29 (-) 1176.8

[2009-2050]

PCB#28 50.73 (1.49) 7.84 (1.23) 28.16 (79.38) 12.69 (17.89) 0.02 (0.00) 0.55 (-) 383.8

PCB#153 5.05 (0.08) 0.07 (0.06) 83.28 (95.68) 4.35 (2.50) 1.99 (1.67) 5.25 (-) 366.7

[2051-2100]

PCB#28 7.35 (0.08) 0.95 (0.06) 89.08 (98.45) 2.56 (1.41) 0.00 (0.00) 0.06 (-) 0.3

PCB#153 0.42 (0.01) 0.00 (0.00) 97.39 (98.75) 0.51 (0.26) 1.33 (0.98) 0.35 (-) 72.6

Figure 2. FATE-predicted geographical distributions of annual sinks of the year, 1970. Upper and lower

panels are the results of PCB#28 and #153, respectively.

(ng/yr)

(ng/yr)

Atmospheric sink (PCB#28) Terrestrial sink (PCB#28) Oceanic sink (PCB#28) Removal to the deep ocean (PCB#28)

Atmospheric sink (PCB#153) Terrestrial sink (PCB#153) Oceanic sink (PCB#153) Removal to the deep ocean (PCB#153)

Vol. 71, 2009 / Organohalogen Compounds page 001603

Acknowledgements

This work was supported by the Ehime University Global COE “Interdisciplinary Studies on Environmental

Chemistry” Programme under the Ministry of Education, Culture, Sports, Science and Technology, the

Government of Japan, and by Japan Society for the Promotion of Science Grant-in-Aid for Young Scientists

(B) (21710033).

References

1. Fenner K., Scheringer M., MacLeod M., Matthies M., McKone T., Stroebe M., Beyer A., Bonnell M., Gall

A.C.L., Klasmeier J., Mackay D., Meent D., Pennington D., Scharenberg B., Suzuki N. and Wania F. Environ.

Sci. Technol. 2005;39:1932.

2. Malanichev A., Mantseva E., Strukov B. and Vulykh N. Environ. Pollut. 2004;128:279.

3. Leip A. and Lammel G. Environ. Pollut. 2004;128:205.

4. Dachs J., Eisenreich S.J., Baker J.E., Ko F. and Jeremiason J.D. Environ. Sci. Technol. 1999;33:3653.

5. Tsyro S. and Erdman L. EMEP/MSC-W-TN 2000.

6. Jurado E., Jaward F., Lohmann R., Jones K.C., Sim R. and Dachs J. Environ. Sci. Technol. 2005;39: 2426.

7. Wania F. and Mackay D. Sci. Total Environ. 1995;160/161:211.

8. Mclachlan M.S. and Horstmann M. Environ. Sci. Technol. 1998;32:413.

9. Breivik K., Sweetman A., Pacyna J.M. and Jones K.C. Sci. Total. Environ. 2007;377:296.

10. Kalnay E., Kanamitsu M., Kistler R., Collins W., Deaven D., Gandin L., Iredell M., Saha S., White G.,

Woollen J., Zhu Y., Chelliah M., Ebisuzaki W., Higgins W., Janowiak J., Mo K.C., Ropelewski C., Wang J.,

Leetmaa A., Reynolds R., Jenne R. and Joseph D. BAMS 1996;77:437.

11. Monterey, G. I. and Levitus S. 1997 U.S. Gov. Printing Office, NOAA NESDIS: 5pp.

12. Beherenfeld, M.J., and Falkowski, P.G. Limnology and Oceanography 1997;42:1.

13. Fritz S., Bartholome E., Belward A., Stibig H.J., Eva H., Mayaux P., Bartalev S., Latifovic R., Kolmert S.,

Roy P.S., Agrawal S., Bingfang W., Wenting X., Ledwith M., Pekel J.F., Giri C., Mucher S., Badts E.,

Tateishi R., Champeaux J.L. and Defourny P. European Commission Joint Research Center 2003; EUR

20849 EN.

14. Loveland T.R., Reed B.C., Brown J.F., Ohlen D.O., Zhu J., Yang L. and Merchant J.W. Int. J. Remote

Sens. 2000;21:1303.

15. Batjes N.H. International Soil Reference and Information Centre (ISRIC), Wageningen 1996; Working

Paper and Preprint 96/05.

16. Mclachlan M.S., Czub G. and Wania F. Environ.Sci. Technol. 2002;36:4860.

17. Lohmann R., Jurado E., Pilson M.E.Q. and Dachs J. Geo. Res. Letter 2006;33:L12607.

Vol. 71, 2009 / Organohalogen Compounds page 001604