scholarly journals Modelling lead(II) sorption to ferrihydrite and soil organic matter

2011 ◽  
Vol 8 (5) ◽  
pp. 485 ◽  
Author(s):  
Jon Petter Gustafsson ◽  
Charlotta Tiberg ◽  
Abubaker Edkymish ◽  
Dan Berggren Kleja
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Surface Complexation ◽  
Toxic Metal ◽  
Anthropogenic Sources ◽  
Model Parameters ◽  
Complexation Reaction ◽  
Surface Complexation Model ◽  
Organic Complexation ◽  
Bidentate Complex

Environmental contextLead(II) is a toxic metal pollutant with many anthropogenic sources. We show that lead(II) is bound more strongly to soil surfaces than previously understood. This knowledge may lead to better models for lead(II) dissolution from the soils, which will improve risk assessments for this metal. AbstractLead(II) adsorption to soil organic matter and iron (hydr)oxides is strong, and may control the geochemical behaviour of this metal. Here, we report the adsorption of Pb2+ (i) to 2-line ferrihydrite, and (ii) to a mor layer. The results showed that ferrihydrite has heterogeneous Pb2+ binding. Use of a surface complexation model indicated that ~1 % of the surface sites adsorbed Pb2+ more strongly than the remaining 99 %. Although only one surface complexation reaction was used (a bidentate complex of the composition (≡FeOH)2Pb+), three classes of sites with different affinity for Pb2+ were needed to simulate Pb2+ binding correctly over all Pb/Fe ratios analysed. For the mor layer, Pb2+ sorption was much stronger than current models for organic complexation suggest. The results could be described by the Stockholm Humic Model when the binding heterogeneity was increased, and when it was assumed that 0.2 % of the binding sites were specific for Pb. Use of revised model parameters for nine Vietnamese soils suggest that lead(II) binding was more correctly simulated than before. Thus, underestimation of lead(II) sorption to both (hydr)oxide surfaces and organic matter may explain the failure of previous geochemical modelling attempts for lead(II).

scholarly journals Temperature sensitivity of decomposition in relation to soil organic matter pools: critique and outlook

2005 ◽  
Vol 2 (4) ◽  
pp. 317-321 ◽  
Author(s):  
M. Reichstein ◽  
T. Kätterer ◽  
O. Andrén ◽  
P. Ciais ◽  
E.-D. Schulze ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Temperature Sensitivity ◽  
Model Parameters ◽  
Data Set ◽  
Organic Matter Quality ◽  
Higher Temperature ◽  
Soil Organic Carbon Pools ◽  
Q10 Values ◽  
Soil Organic Matter Quality

Abstract. Knorr et al. (2005) concluded that soil organic carbon pools with longer turnover times are more sensitive to temperature. We show that this conclusion is equivocal, largely dependent on their specific selection of data and does not persist when the data set of Kätterer et al. (1998) is analysed in a more appropriate way. Further, we analyse how statistical properties of the model parameters may interfere with correlative analyses that relate the Q10 of soil respiration with the basal rate, where the latter is taken as a proxy for soil organic matter quality. We demonstrate that negative parameter correlations between Q10-values and base respiration rates are statistically expected and not necessarily provide evidence for a higher temperature sensitivity of low quality soil organic matter. Consequently, we propose it is premature to conclude that stable soil carbon is more sensitive to temperature than labile carbon.

scholarly journals Modelling dynamic interactions between soil structure and the storage and turnover of soil organic matter

2020 ◽  
Vol 17 (20) ◽  
pp. 5025-5042
Author(s):  
Katharina Hildegard Elisabeth Meurer ◽  
Claire Chenu ◽  
Elsa Coucheney ◽  
Anke Marianne Herrmann ◽  
Thomas Keller ◽  
...  
Keyword(s):  
Climate Change ◽  
Organic Matter ◽  
Soil Organic Matter ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Bulk Density ◽  
Green Manure ◽  
Water Retention ◽  
Model Parameters ◽  
Soil Water Retention

Abstract. Models of soil organic carbon (SOC) storage and turnover can be useful tools to analyse the effects of soil and crop management practices and climate change on soil organic carbon stocks. The aggregated structure of soil is known to protect SOC from decomposition and, thus, influence the potential for long-term sequestration. In turn, the turnover and storage of SOC affects soil aggregation, physical and hydraulic properties and the productive capacity of soil. These two-way interactions have not yet been explicitly considered in modelling approaches. In this study, we present and describe a new model of the dynamic feedbacks between soil organic matter (SOM) storage and soil physical properties (porosity, pore size distribution, bulk density and layer thickness). A sensitivity analysis was first performed to understand the behaviour of the model. The identifiability of model parameters was then investigated by calibrating the model against a synthetic data set. This analysis revealed that it would not be possible to unequivocally estimate all of the model parameters from the kind of data usually available in field trials. Based on this information, the model was tested against measurements of bulk density, SOC concentration and limited data on soil water retention and soil surface elevation made during 63 years in a field trial located near Uppsala (Sweden) in three treatments with different organic matter (OM) inputs (bare fallow, animal and green manure). The model was able to accurately reproduce the changes in SOC, soil bulk density and surface elevation observed in the field as well as soil water retention curves measured at the end of the experimental period in 2019 in two of the treatments. Treatment-specific variations in SOC dynamics caused by differences in OM input quality could be simulated very well by modifying the value for the OM retention coefficient ε (0.37 for animal manure and 0.14 for green manure). The model approach presented here may prove useful for management purposes, for example, in an analysis of carbon sequestration or soil degradation under land use and climate change.

Predicting Cr(vi) adsorption on soils: the role of the competition of soil organic matter

2020 ◽  
Vol 22 (1) ◽  
pp. 95-104
Author(s):  
Zhenqing Shi ◽  
Shimeng Peng ◽  
Xiaofeng Lin ◽  
Yuzhen Liang ◽  
Suen-Zone Lee ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Surface Complexation

Surface complexation models can predict Cr(vi) adsorption on soils after accounting for the competition from the soil organic matter.

scholarly journals Does the temperature sensitivity of decomposition vary with soil organic matter quality?

2005 ◽  
Vol 2 (4) ◽  
pp. 737-747 ◽  
Author(s):  
M. Reichstein ◽  
T. Kätterer ◽  
O. Andrén ◽  
P. Ciais ◽  
E.-D. Schulze ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Temperature Sensitivity ◽  
Model Parameters ◽  
Data Set ◽  
Organic Matter Quality ◽  
Higher Temperature ◽  
Soil Organic Carbon Pools ◽  
Q10 Values ◽  
Soil Organic Matter Quality

Abstract. Knorr et al. (2005) concluded that soil organic carbon pools with longer turnover times are more sensitive to temperature. We show that this conclusion is equivocal, largely dependent on their specific selection of data and does not persist when the data set of Kätterer et al. (1998) is analysed in a more appropriate way. Further, we analyse how statistical properties of the model parameters may interfere with correlative analyses that relate the Q10 of soil respiration with the basal rate, where the latter is taken as a proxy for soil organic matter quality. We demonstrate that negative parameter correlations between Q10-values and base respiration rates are statistically expected and not necessarily provide evidence for a higher temperature sensitivity of low quality soil organic matter. Consequently, we reckon it is premature to conclude that stable soil carbon is more sensitive to temperature than labile carbon.

Surface Complexation Model Parameters for Goethite (α-FeOOH)

1994 ◽  
Vol 164 (1) ◽  
pp. 119-125 ◽  
Author(s):  
David O. Lumsdon ◽  
Leslie J. Evans
Keyword(s):  
Surface Complexation ◽  
Model Parameters ◽  
Surface Complexation Model

Nickel and cadmium speciation in soils under long-term aerosol pollution

2021 ◽  
Author(s):  
Elena Fedorenko ◽  
Marina Burachevskaya ◽  
Victoria Severina ◽  
Anatoly Barakhov ◽  
Victoria Tsitsuashvili ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Power Plant ◽  
Power Plants ◽  
Emission Source ◽  
Anthropogenic Sources ◽  
Residual Fraction ◽  
Wide Range ◽  
Uncontaminated Soil ◽  
Mn Oxides

<p>Coal mining and burning are major anthropogenic sources of atmospheric particles and heavy metals (HMs) (Wang et al., 2011).Coal dust contains a wide range of metal including Ni and Cd. Sequential extractions are the most used methods to estimate the mobility of metals closely related to bioavailability. The classic sequential extraction methods by Tessier (Tessier et al., 1979) are the most popular method of HMs. The aim of this work was to study the speciation of Ni and Cd in soils under anthropogenic contamination with combustion products from the Novocherkassk power plant (NPP).</p><p>The monitoring plots were arranged along predominant wind direction at 1.6 and 15 km from the emission source. The studied soils are represented by Haplic Chernozem. The properties of the soil were: pH - 7.3-7.4; 28.6-30.9% of silt, the content of organic carbon is 3.0-3.7%; carbonates - 0.3%; content of nonsilicate Fe – 3.8-3.9%; CEC – 35-37 cmol kg<sup>–1</sup>. Areas located within 4 km from the power plants are subjected to the highest ecological disturbances; and a zone almost free from contamination is located beyond 15 km (Minkina et al., 2013).</p><p>It was found that the total content of Ni (39.0 mg kg<sup>–1</sup>) and Cd (0.1 mg kg<sup>–1</sup>) in the unpolluted soil far away from NPP (at 15 km) matching the background metal content in Haplic Chernozem was almost four times lower (145 mg kg<sup>–1</sup> and 3.8 mg kg<sup>–1</sup> accordingly) than in the soil located under the influence of aerosol emissions (at 1.6 km). In an uncontaminated soil occurring far from the emission source, 62–64% of total Ni and Cd fractions are concentrated in the residual fraction characterizing the metal bond with silicates. The following distribution of Ni among the fractions in the uncontaminated soil is noted: residual fraction > bound to organic matter > bound to Fe-Mn oxides > bound to carbonates > exchangeable. In uncontaminated soil, the following fractional distribution of Cd is observed: residual fraction> bound to Fe-Mn oxides > bound to organic matter > bound to carbonates > exchangeable.</p><p>Metals accumulate in the soil occurring near the power plant (at 1.6 km), which increases the total contents of Ni and Cd and their mobile (exchangeable and carbonate-bound) compounds in 18 and 33 times accordingly. With increasing pollution, the share of the residual fraction decreases (up to 42-47%) and the amount of the most mobile HM compounds increases. The high mobility in soils is established for Cd (exchangeable fraction was 9%). An increase in the Ni and Cd content in the soil increases its adsorption on the surface of Fe oxides (up to 20% and 27% accordingly). The role of soil organic matter in the absorption of Ni (up to 15%) is also noticeable.</p><p>Thus, the largest contributions to the adsorption and retention of metals are made by silicates, as well as nonsilicate Fe compounds for Cd and soil organic matter and nonsilicate Fe for Ni.</p><p>This work was supported by the Russian Science Foundation, project no. 19-74-00085</p>

Metal Ions Binding to Natural Organic Matter Extracted from Wheat Bran: Application of the Surface Complexation Model

2000 ◽  
Vol 225 (2) ◽  
pp. 329-339 ◽  
Author(s):  
Corinne Ravat ◽  
Fanny Monteil-Rivera ◽  
Jacques Dumonceau
Keyword(s):  
Organic Matter ◽  
Metal Ions ◽  
Natural Organic Matter ◽  
Wheat Bran ◽  
Surface Complexation ◽  
Surface Complexation Model

scholarly journals Implementation and initial calibration of carbon-13 soil organic matter decomposition in Yasso model

2021 ◽  
Author(s):  
Jarmo Mäkelä ◽  
Laura Arppe ◽  
Hannu Fritze ◽  
Jussi Heinonsalo ◽  
Jari Liski ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Soil Carbon ◽  
Carbon Isotope ◽  
Atmospheric Carbon Dioxide ◽  
Carbon Sink ◽  
Organic Matter Decomposition ◽  
Model Parameters ◽  
Soil Organic Matter Decomposition ◽  
Carbon Dioxide Concentrations

Abstract. Soil carbon sequestration has gained traction as a mean to mitigate rising atmospheric carbon dioxide concentrations. Verification of different methods’ efficiency to increase soil carbon sink requires, in addition to good quality measurements, reliable models capable of simulating the effect of the sequestration practices. One way to get insight of the methods’ effects on carbon cycling processes is to analyse different carbon isotope concentrations in soil organic matter. In this paper we introduce a carbon-13 isotope specific soil organic matter decomposition add-on into the Yasso soil carbon model and assess its functionality. The new 13C-dedicated decomposition is straightforward to implement and depends linearly on the default Yasso model parameters and the relative carbon isotope (13C/12C) concentration. Despite of their simplicity, the modifications considerably improve the model behaviour in a 50-year long simulation.

Soil Organic Matter

1978 ◽  
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter
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