Improved geochemical modeling of lead solubility in contaminated soils by considering colloidal fractions and solid phase EXAFS speciation

Sjöstedt, C.; Löv, Å.; Olivecrona, Z.; Boye, K.; Kleja, D. B.

doi:10.1016/j.apgeochem.2018.01.014

Title: Improved geochemical modeling of lead solubility in contaminated soils by considering colloidal fractions and solid phase EXAFS speciation

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Abstract

Lead (Pb) is a common contaminant in soils at e.g. mining, shooting range, and glassworks sites. In order to make reliable risk assessments and appropriate decisions on various “gentle remediation options”, such as applying phosphate, compost, or zero-valent iron to soils, the binding mechanism of Pb and its speciation needs to be known. Multi-surface geochemical equilibrium models are useful tools for estimating trace metal solubility and speciation, but for Pb the predictions are often poor. This study evaluates the recent parameterization for Pb in the Visual MINTEQ code for its ability to predict the solubility of Pb at different pH values in four historically contaminated Swedish soils. As an independent validation of the model performance, the modeled solid-phase speciation was compared to measured Pb speciation retrieved using extended X-ray absorption fine structure (EXAFS) spectroscopy. Furthermore, potential artefacts by the presence of Pb colloids were investigated by filtering solutions through both 0.45 μm and 10 kDa filters. The model accuracy for predicting Pb solubility was improved compared with previous studies producing log root mean square error (RMSE) values below 0.42 in three out of four soils, just by using generic assumptions. The use of ultrafiltered (<10 kDa) instead of the 0.45more »« less

Authors:

; Löv, Å.; Olivecrona, Z.; Boye, K.; Kleja, D. B.

Publication Date:: Tue May 01 00:00:00 EDT 2018

Research Org.:: SLAC National Accelerator Lab., Menlo Park, CA (United States); Swedish Univ. of Agricultural Sciences (SLU), Uppsala (Sweden)

Sponsoring Org.:: USDOE Office of Science (SC), Biological and Environmental Research (BER); USDOE Office of Science (SC), Basic Energy Sciences (BES); Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (FORMAS)

OSTI Identifier:: 1433286

Alternate Identifier(s):: OSTI ID: 1469155

Grant/Contract Number:: AC02-76SF00515; 219-2012-868

Resource Type:: Published Article

Journal Name:: Applied Geochemistry

Additional Journal Information:: Journal Name: Applied Geochemistry Journal Volume: 92 Journal Issue: C; Journal ID: ISSN 0883-2927

Publisher:: Elsevier

Country of Publication:: United Kingdom

Language:: English

Subject:: 58 GEOSCIENCES; 37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; trace metals; contaminated soil; multi-surface geochemical modeling; mimetite; Visual MINTEQ; colloids

Citation Formats


                    Sjöstedt, C., Löv, Å., Olivecrona, Z., Boye, K., and Kleja, D. B. Improved geochemical modeling of lead solubility in contaminated soils by considering colloidal fractions and solid phase EXAFS speciation.  United Kingdom: N. p., 2018. 
Web.  doi:10.1016/j.apgeochem.2018.01.014.

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                    Sjöstedt, C., Löv, Å., Olivecrona, Z., Boye, K., & Kleja, D. B. Improved geochemical modeling of lead solubility in contaminated soils by considering colloidal fractions and solid phase EXAFS speciation.  United Kingdom.  https://doi.org/10.1016/j.apgeochem.2018.01.014

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                    Sjöstedt, C., Löv, Å., Olivecrona, Z., Boye, K., and Kleja, D. B. Tue .  
"Improved geochemical modeling of lead solubility in contaminated soils by considering colloidal fractions and solid phase EXAFS speciation".  United Kingdom.  https://doi.org/10.1016/j.apgeochem.2018.01.014.

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@article{osti_1433286,

  title        = {Improved geochemical modeling of lead solubility in contaminated soils by considering colloidal fractions and solid phase EXAFS speciation},

  author       = {Sjöstedt, C. and Löv, Å. and Olivecrona, Z. and Boye, K. and Kleja, D. B.},

  abstractNote = {Lead (Pb) is a common contaminant in soils at e.g. mining, shooting range, and glassworks sites. In order to make reliable risk assessments and appropriate decisions on various “gentle remediation options”, such as applying phosphate, compost, or zero-valent iron to soils, the binding mechanism of Pb and its speciation needs to be known. Multi-surface geochemical equilibrium models are useful tools for estimating trace metal solubility and speciation, but for Pb the predictions are often poor. This study evaluates the recent parameterization for Pb in the Visual MINTEQ code for its ability to predict the solubility of Pb at different pH values in four historically contaminated Swedish soils. As an independent validation of the model performance, the modeled solid-phase speciation was compared to measured Pb speciation retrieved using extended X-ray absorption fine structure (EXAFS) spectroscopy. Furthermore, potential artefacts by the presence of Pb colloids were investigated by filtering solutions through both 0.45 μm and 10 kDa filters. The model accuracy for predicting Pb solubility was improved compared with previous studies producing log root mean square error (RMSE) values below 0.42 in three out of four soils, just by using generic assumptions. The use of ultrafiltered (<10 kDa) instead of the 0.45 μm-filtered Pb concentrations lowered the RMSE with ~0.4 log units in two soils, giving a more accurate evaluation of the model performance. EXAFS proved to be a useful tool for validating and constraining the model, since the solid phase speciation did not exactly agree with the modeled results using default assumptions. However, a sample-specific optimization of the amount of “active” solid organic matter and Al + Fe hydroxides resulted in improved prediction of Pb solubility as well as better agreement with the EXAFS measurements. Solubility of Pb in the fourth, As-rich soil was probably controlled by Pb5(AsO4)3Cl (mimetite) with a solubility product constant of 10-83.53.},

  doi          = {10.1016/j.apgeochem.2018.01.014},

  journal      = {Applied Geochemistry},

  number       = C,

  volume       = 92,

  place        = {United Kingdom},

  year         = {Tue May 01 00:00:00 EDT 2018},

  month        = {Tue May 01 00:00:00 EDT 2018}

}

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