Being able to predict the behavior of trace elements in the environment is crucial for environmental risk assessment studies. For this reason, modeling, in addition to experimental methods, has become an indispensable tool to better understand the (bio)-geochemistry of trace elements and the processes involved in their availability, transport and ecotoxicity. In this chapter we briefly outline the development of geochemical modeling over time and its basic principles. A comprehensive description of the state-of-the-art ion-binding and surface complexation models presently available for dissolved and particulate organic matter, metal (hydr)oxides of aluminum, iron, manganese and silica and clay minerals is given. A significant part of this chapter is dedicated to the application of these models for studying surface waters and soils. The most common model platforms used for this purpose together with the available (thermodynamic) databases of model parameters are summarized. In two separate sections we highlight the application of an assemblage model (with submodels for the various adsorbents) to describe trace element solid-solution partitioning and speciation in surface waters and soils; here particular attention is given to the derivation of site-specific inputs concerning the geochemical reactive metal content and the contents of adsorbents metal (hydr)oxides, clay and organic matter). Consideration is therefore given to the most recent developments in bio-geochemical modeling to link metal speciation to bioavailability, biotic accumulation and toxicity. Finally, future prospects of geochemical modeling are discussed, giving an overview of the potential directions for development.

Benedetto De Vivo, H.E.B., Di Bonito M, Stephen Lofts, Jan E. Groenenberg (2018). Chapter 11 - Models of Geochemical Speciation: Structure and Applications. NLD : Elsevier Science BV [10.1016/B978-0-444-63763-5.00012-4].

Chapter 11 - Models of Geochemical Speciation: Structure and Applications

Di Bonito M
Primo
Writing – Original Draft Preparation
;
2018

Abstract

Being able to predict the behavior of trace elements in the environment is crucial for environmental risk assessment studies. For this reason, modeling, in addition to experimental methods, has become an indispensable tool to better understand the (bio)-geochemistry of trace elements and the processes involved in their availability, transport and ecotoxicity. In this chapter we briefly outline the development of geochemical modeling over time and its basic principles. A comprehensive description of the state-of-the-art ion-binding and surface complexation models presently available for dissolved and particulate organic matter, metal (hydr)oxides of aluminum, iron, manganese and silica and clay minerals is given. A significant part of this chapter is dedicated to the application of these models for studying surface waters and soils. The most common model platforms used for this purpose together with the available (thermodynamic) databases of model parameters are summarized. In two separate sections we highlight the application of an assemblage model (with submodels for the various adsorbents) to describe trace element solid-solution partitioning and speciation in surface waters and soils; here particular attention is given to the derivation of site-specific inputs concerning the geochemical reactive metal content and the contents of adsorbents metal (hydr)oxides, clay and organic matter). Consideration is therefore given to the most recent developments in bio-geochemical modeling to link metal speciation to bioavailability, biotic accumulation and toxicity. Finally, future prospects of geochemical modeling are discussed, giving an overview of the potential directions for development.
2018
Environmental Geochemistry (Second Edition)
237
305
Benedetto De Vivo, H.E.B., Di Bonito M, Stephen Lofts, Jan E. Groenenberg (2018). Chapter 11 - Models of Geochemical Speciation: Structure and Applications. NLD : Elsevier Science BV [10.1016/B978-0-444-63763-5.00012-4].
Benedetto De Vivo, Harvey E. Belkin, Annamaria Lima; Di Bonito M; Stephen Lofts; Jan E. Groenenberg
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/846283
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