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Using a two site-reactive model for simulating one century changes of Zn and Pb concentration profiles in soils affected by metallurgical fallout
2012
Mallmann , Fábio Joel Kochem (Universidade Federal de Santa Maria, Santa Maria(Brésil). Departamento de Solos) | Rheinheimer , Danilo dos Santos (Universidade Federal de Santa Maria, Santa Maria(Brésil). Departamento de Solos) | Labanowski , Jérôme (Centre National de la Recherche Scientifique, Poitiers(France). UMR 6008, LCME, Université de Poitiers-ESIP) | Cambier , Philippe (INRA , Versailles (France). UR 0251 Physico-chimie et Ecotoxicologie des Sols d'agrosystèmes contaminés) | Lamy , Isabelle (INRA , Versailles (France). UR 0251 Physico-chimie et Ecotoxicologie des Sols d'agrosystèmes contaminés) | Santanna , Maria Alice (Universidade Federal de Santa Maria, Santa Maria(Brésil). Departamento de Física) | Tessier , Daniel (INRA , Versailles (France). UR 0251 Physico-chimie et Ecotoxicologie des Sols d'agrosystèmes contaminés) | Van Oort , Folkert (INRA , Versailles (France). UR 0251 Physico-chimie et Ecotoxicologie des Sols d'agrosystèmes contaminés)
Predicting the transfer of contaminants in soils is often hampered by lacking validation of mathematical models. Here, we applied Hydrus-2D software to three agricultural soils for simulating the 1900–2005 changes of zinc and lead concentration profiles derived from industrial atmospheric deposition, to validate the tested models with plausible assumptions on past metal inputs to reach the 2005 situation. The models were set with data from previous studies on the geochemical background, estimated temporal metal deposition, and the 2005 metal distributions. Different hypotheses of chemical reactions of metals with the soil solution were examined: 100% equilibrium or partial equilibrium, parameterized following kinetic chemical extractions. Finally, a two-site model with kinetic constant values adjusted at 1% of EDTA extraction parameters satisfactory predicted changes in metal concentration profiles for two arable soils. For a grassland soil however, this model showed limited applicability by ignoring the role of earthworm activity in metal incorporation.
Показать больше [+] Меньше [-]Modelling bioaccumulation of heavy metals in soil-crop ecosystems and identifying its controlling factors using machine learning
2020
Hu, Bifeng | Xue, Jie | Zhou, Yin | Shao, Shuai | Fu, Zhiyi | Li, Yan | Chen, Songchao | Qi, Lin | Shi, Zhou | Unité de Science du Sol (Orléans) (URSols) ; Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Key Laboratory of Environment Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences ; Zhejiang University [Hangzhou, China] | Institute of Land Science and Property, School of Public Affairs ; Zhejiang University [Hangzhou, China] | School of Earth Sciences [Hangzhou] ; Zhejiang University [Hangzhou, China] | InfoSol (InfoSol) ; Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Ningbo Planting Management Station ; Ningbo University (NBU)
The prediction and identification of the factors controlling heavy metal transfer in soil-crop ecosystems are of critical importance. In this study, random forest (RF), gradient boosted machine (GBM), and generalised linear (GLM) models were compared after being used to model and identify prior factors that affect the transfer of heavy metals (HMs) in soil-crop systems in the Yangtze River Delta, China, based on 13 covariates with 1822 pairs of soil-crop samples. The mean bioaccumulation factors (BAFs) for all crops followed the order Cd > Zn > As > Cu > Ni > Hg > Cr > Pb. The RF model showed the best prediction ability for the BAFs of HMs in soil-crop ecosystems, followed by GBM and GLM. The R2 values of the RF models for the BAFs of Zn, Cu, Cr, Ni, Hg, Cd, As, and Pb were 0.84, 0.66, 0.59, 0.58, 0.58, 0.51, 0.30, and 0.17, respectively. The primary controlling factor in soil-to-crop transfer of all HMs under study was plant type, followed by soil heavy metal content and soil organic materials. The model used herein could be used to assist the prediction of heavy metal contents in crops based on heavy metal contents in soil and other covariates, and can significantly reduce the cost, labour, and time requirements involved with laboratory analysis. It can also be used to quantify the importance of variables and identify potential control factors in heavy metal bioaccumulation in soil-crop ecosystems.
Показать больше [+] Меньше [-]Nitrogen balances and leaching in four agricultural catchments in southeastern Norway
1998
Bechmann, M. | Eggestad, H.O. | Vagstad, N. (Jordforsk, Centre for Soil and Environmental Research, N-1432 As (Norway))
Soil pollution and land contamination.. ed. 3
1996
Alloway, B.J. (Department of Soil Science, University of Reading, London Road, Reading RG1 5AQ (United Kingdom))
Using a two site-reactive model for simulating one century changes of Zn and Pb concentration profiles in soils affected by metallurgical fallout
2012
Mallmann, Fábio Joel Kochem | Rheinheimer, Danilo dos Santos | Labanowski, Jérôme | Cambier, Philippe | Lamy, Isabelle | Santanna, Maria Alice | Tessier, Daniel | Van Oort, Folkert
Predicting the transfer of contaminants in soils is often hampered by lacking validation of mathematical models. Here, we applied Hydrus-2D software to three agricultural soils for simulating the 1900–2005 changes of zinc and lead concentration profiles derived from industrial atmospheric deposition, to validate the tested models with plausible assumptions on past metal inputs to reach the 2005 situation. The models were set with data from previous studies on the geochemical background, estimated temporal metal deposition, and the 2005 metal distributions. Different hypotheses of chemical reactions of metals with the soil solution were examined: 100% equilibrium or partial equilibrium, parameterized following kinetic chemical extractions. Finally, a two-site model with kinetic constant values adjusted at 1% of EDTA extraction parameters satisfactory predicted changes in metal concentration profiles for two arable soils. For a grassland soil however, this model showed limited applicability by ignoring the role of earthworm activity in metal incorporation.
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