Environmental Science and Pollution Research

, Volume 16, Issue 2, pp 191–205 | Cite as

Long-range atmospheric transport of three toxaphene congeners across Europe. Modeling by chained single-box FATEMOD program

  • Jaakko PaasivirtaEmail author
  • Seija Sinkkonen
  • Vladimir Nikiforov
  • Fedor Kryuchkov
  • Erkki Kolehmainen
  • Katri Laihia
  • Arto Valkonen
  • Manu Lahtinen


Background, aims, and scope

Since toxaphene (polychlorocamphene, polychloropinene, or strobane) mixtures were applied for massive insecticide use in the 1960s to replace the use of DDT, some of their congeners have been found at high latitudes far away from the usage areas. Especially polychlorinated bornanes have demonstrated dominating congeners transported by air up to the Arctic areas. Environmental fate modeling has been applied to monitor this phenomenon using parallel zones of atmosphere around the globe as interconnected environments. These zones, shown in many meteorological maps, however, may not be the best way to configure atmospheric transport in air trajectories. The latter could also be covered by connecting a chain of simple model boxes. We aim to study this alternative approach by modeling the trajectory chain using catchment boxes of our FATEMOD model. Polychlorobornanes analyzed in biota of the Barents Sea offered one case to study this modeling alternative, while toxaphene has been and partly still is used massively at southern East Europe and around rivers flowing to the Aral Sea.

Materials and methods

Pure model substances of three polychlorobornanes (toxaphene congeners P26, P50, and P62) were synthesized, their environmentally important thermal properties measured by differential scanning calorimetry, as evaluated from literature data, and their temperature dependences estimated by the QSPR programs VPLEST, WATSOLU, and TDLKOW. The evaluated property parameters were used to model their atmospheric long-range transport from toxaphene heavy usage areas in Ukraine and Aral/SyrDarja/AmuDarja region areas, through East Europe and Northern Norway (Finnmarken) to the Barents Sea. The time period used for the emission model was June 1997. Usual weather conditions in June were applied in the model, which was constructed by chaining FATEMOD model boxes of the catchment’s areas along assumed maximal air flow trajectories. Analysis of the three chlorobornanes in toxaphene mixtures function as a basis for the estimates of emission levels caused by its usage. High estimate (A) was taken from contents in a Western product chlorocamphene and low estimate (B) from mean contents in Russian polychloroterpene products to achieve modeled water concentrations. Bioaccumulation to analyzed lipid of aquatic biota at the target region was estimated by using statistical calculation for persistent organic pollutants in literature.


The results from model runs A and B (high and low emission estimate) for levels in sea biota were compared to analysis results of samples taken in August 1997 at Barents Sea. The model results (ng g−1 lw): 4–95 in lipid of planktovores and 7–150 in lipid of piscivores, were in fair agreement with the analysis results from August 1997: 21–31 in Themisto libellula (chatka), 26–42 in Boreocadus saida (Polar cod), and 5–27 in Gadus morhua (cod) liver.


The modeling results indicate that the application of chained simple multimedia catchment boxes on predicted trajectory is a useful method for estimation of volatile airborne persistent chemical exposures to biota in remote areas. For hazard assessment of these pollutants, their properties, especially temperature dependences, must be estimated by a reasonable accuracy. That can be achieved by using measurements in laboratory with pure model compounds and estimation of properties by thermodynamic QSPR methods. The property parameters can be validated by comparing their values at an environmental temperature range with measured or QSPR-estimated values derived by independent methods. The chained box method used for long-range air transport modeling can be more suitable than global parallel zones modeling used earlier, provided that the main airflow trajectories and properties of transported pollutants are predictable enough.


Long-range air transport modeling of persistent, especially photo-resistant organic compounds using a chain of joint simple boxes of catchment’s environments is a feasible method to predict concentrations of pollutants at the target area. This is justified from model results compared with analytical measurements in Barents Sea biota in August 1997: three of six modeled values were high and the other three low compared to the analysis results. The order of magnitude level was similar in both modeled (planktovore and piscivore) and observed (chatka and polar cod) values of lipid samples. The obtained results were too limited to firm validation but are sufficient to justify feasibility of the method, which prompts one to perform more studies on this modeling system.

Recommendations and perspectives

For assessment of the risk of environmental damages, chemical fate determination is an essential tool for chemical control, e.g., for EU following the REACH rules. The present conclusion of applicability of the chained single-box multimedia modeling can be validated by further studies using analyses of emissions and target biota in various other cases. To achieve useful results, fate models built with databases having automatic steps for most calculations and outputs accessible to all chemical control professionals are essential. Our FATEMOD program catchments at environments and compound properties listed in the database represent a feasible tool for local, regional, and, according our present test results, for global exposure predictions. As an extended use of model, emission estimates can be achieved by reversed modeling from analysis results of samples corresponding to the target area.


Advection Catchment’s areas Chain of model boxes Chlorobornanes Degradation half-life times Degradation rates DSC Emission FATEMOD Joint trajectories Photolysis Temperature coefficients 


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Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Jaakko Paasivirta
    • 1
    Email author
  • Seija Sinkkonen
    • 1
  • Vladimir Nikiforov
    • 2
  • Fedor Kryuchkov
    • 2
  • Erkki Kolehmainen
    • 1
  • Katri Laihia
    • 1
  • Arto Valkonen
    • 1
  • Manu Lahtinen
    • 1
  1. 1.Department of ChemistryUniversity of JyväskyläJyväskyläFinland
  2. 2.Department of ChemistrySt. Petersburg State UniversitySt. PetersburgRussia

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