Predicting PbII adsorption on soils: the roles of soil organic matter, cation competition and iron (hydr)oxides

2013 ◽  
Vol 10 (6) ◽  
pp. 465 ◽  
Author(s):  
Zhenqing Shi ◽  
Herbert E. Allen ◽  
Dominic M. Di Toro ◽  
Suen-Zone Lee ◽  
James B. Harsh
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Mineral Content ◽  
Visual Minteq ◽  
Chemical Models ◽  
Wide Range ◽  
Model Predictions ◽  
Music Model ◽  
Diffuse Layer Model ◽  
Modelling Approach

Environmental context Lead is a common and persistent soil and water contaminant. This study provides a unique set of parameters for chemical models that can be used for predicting Pb adsorption by soil. The suggested modelling approach can be used to quantitatively predict Pb retention and release in soils with changing environmental conditions. Abstract Lead (PbII) adsorption on 14 non-calcareous New Jersey soils was studied with a batch method. Both adsorption edge and adsorption isotherm experiments were conducted covering a wide range of soil compositions, Pb concentrations and solution pHs. Visual MINTEQ was used to calculate the Pb adsorption equilibrium by coupling the Stockholm Humic Model, the CD-MUSIC model, a diffuse layer model and a cation exchange model for Pb reactions with soil organic matter (SOM), Fe (hydr)oxides, Al hydroxides and clay minerals. For model predictions, reactive organic matter (ROM), the fraction of SOM responsible for Pb binding, and reactive Al and FeIII in soils were quantified. The models predicted Pb adsorption to soils reasonably well with varying SOM and mineral content at various pHs and Pb concentrations. For 3.0<pH<6.0, the log partition coefficient root mean square error was 0.34. However at higher pHs the models were less successful. Both ROM and Al competition had a significant effect on model predictions. ROM was the dominant adsorption phase at pHs between 3.0 and 5.0. For pH>5.0, Pb adsorption to Fe (hydr)oxides became significant. The modelling approach presented in this study can be used to understand and quantitatively predict Pb adsorption on soil.

scholarly journals Spatial control of carbon dynamics in soil by microbial decomposer communities

2020 ◽  
Author(s):  
Holger Pagel ◽  
Björn Kriesche ◽  
Marie Uksa ◽  
Christian Poll ◽  
Ellen Kandeler ◽  
...  
Keyword(s):  
Organic Matter ◽  
Spatial Distribution ◽  
Soil Organic Matter ◽  
Distribution Patterns ◽  
Microbial Succession ◽  
Thin Sections ◽  
Spatial Control ◽  
Soil Organic Matter Turnover ◽  
Microbial Decomposer ◽  
Modelling Approach

&lt;p&gt;Trait-based models have improved the understanding and prediction of soil organic matter dynamics in terrestrial ecosystems. Microscopic observations and pore scale models are now increasingly used to quantify and elucidate the effects of soil heterogeneity on microbial processes. Combining both approaches provides a promising way to accurately capture spatial microbial-physicochemical interactions and to predict overall system behavior. The present study aims to quantify controls on carbon (C) turnover in soil due to the mm-scale spatial distribution of microbial decomposer communities in soil. A new spatially explicit trait-based model (SpatC) has been developed that captures the combined dynamics of microbes and soil organic matter (SOM) by taking into account microbial life-history traits and SOM accessibility. Samples of spatial distributions of microbes at &amp;#181;m-scale resolution were generated using a spatial statistical model based on Log Gaussian Cox Processes which was originally used to analyze distributions of bacterial cells in soil thin sections. These &amp;#181;m-scale distribution patterns were then aggregated to derive distributions of microorganisms at mm-scale. We performed Monte-Carlo simulations with microbial distributions that differ in mm-scale spatial heterogeneity and functional community composition (oligotrophs, copiotrophs and copiotrophic cheaters). Our modelling approach revealed that the spatial distribution of soil microorganisms triggers spatiotemporal patterns of C utilization and microbial succession. Only strong spatial clustering of decomposer communities induces a diffusion limitation of the substrate supply on the microhabitat scale, which significantly reduces the total decomposition of C compounds and the overall microbial growth. However, decomposer communities act as functionally redundant microbial guilds with only slight changes in C utilization. The combined statistical and process-based modelling approach derives distribution patterns of microorganisms at the mm-scale from microbial biogeography at microhabitat scale (&amp;#181;m) and quantifies the emergent macroscopic (cm) microbial and C dynamics. Thus, it effectively links observable process dynamics to the spatial control by microbial communities. Our study highlights a powerful approach that can provide further insights into the biological control of soil organic matter turnover.&lt;/p&gt;

scholarly journals Thermal fractionation of soil organic matter produces fine-scale distributions of SOM age

2021 ◽  
Author(s):  
Shane Stoner ◽  
Carlos Sierra ◽  
Marion Schrumpf ◽  
Sebastian Dötterl ◽  
Susan Trumbore
Keyword(s):  
Thermal Stability ◽  
Organic Matter ◽  
Soil Organic Matter ◽  
Chemical Oxidation ◽  
Fine Scale ◽  
Mineral Association ◽  
Density Fractions ◽  
Chemical Complexity ◽  
Wide Range ◽  
Carbon Release

&lt;p&gt;Soil organic matter (SOM) is a complex collection of organic molecules of varying origin, structure, chemical activity, and mineral association. A wide array of laboratory methods exists to separate SOM based on qualitative, biological, chemical, and physical characteristics. However, all present conceptual and logistical limitations, including the requirement of a substantial amount soil material.&lt;/p&gt;&lt;p&gt;An newly applied alternative method of fractionation relies on a conceptual analogue between biochemical stability in soil and thermal stability, e.g. more persistent SOM will require higher temperatures (greater energy inputs) to decompose than less persistent SOM. This accounts for both chemical complexity and mineral association as main factors in determining SOM persistence.&lt;/p&gt;&lt;p&gt;In this method, carbon is released by heating SOM to 900&amp;#176;C at a constant rate. The peaks of carbon release are grouped into activation energy pools, CO&lt;sub&gt;2 &lt;/sub&gt;is collected, and analyzed for &lt;sup&gt;13&lt;/sup&gt;C and &lt;sup&gt;14&lt;/sup&gt;C. We seek to describe in finer detail the distribution of soil radiocarbon by adding another fractionation step following a different paradigm of SOM stability, and explore mineralogical effects on SOM quality and stability using thermal analysis, radiocarbon, and gas chromatography.&lt;/p&gt;&lt;p&gt;Here, we analyzed bulk soil and soil fractions derived from density separation and chemical oxidation, as well as mineral horizons dominated by diverse mineralogies. Density fractions contained a wide range of radiocarbon activities and that young SOM is stabilized across multiple fractions, likely due to organomineral complexation. Initial results showed that soil minerals with limited stabilization potential released C at lower temperatures than those with diverse stabilization mechanisms. High-temperature sub-fractions contained the oldest carbon across fractions and minerals, thus supporting the assumption that thermal stability can be used as a limited analogue for stability in soil. We present a fine-scale distribution of radiocarbon in SOM and discuss the potential of this method for comparison with other fractionation techniques.&lt;/p&gt;

scholarly journals Relationship between the mass of organic matter and carbon in soil

2008 ◽  
Vol 51 (2) ◽  
pp. 263-269 ◽  
Author(s):  
Silmara R. Bianchi ◽  
Mario Miyazawa ◽  
Edson L. de Oliveira ◽  
Marcos Antonio Pavan
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Organic Carbon ◽  
Soil Depth ◽  
Soil Surface ◽  
Soil Samples ◽  
Loss On Ignition ◽  
Oxidation Degree ◽  
Wide Range

The quantity of soil organic matter (SOM) was estimated through the determination of soil organic carbon (SOC) times a factor, which assumes that 58% of the SOM was formed by carbon. A number of soil samples with wide range of SOC content collected in the state of Paraná, Brazil were evaluated in the laboratory. SOC was measured by Walkley-Black method and the total SOM by loss on ignition. The SOC was positively correlated with SOM. The SOM/SOC ratio varied from 1.91 to 5.08 for the soils. It shows that Brazilian SOM has greater oxidation degree. Although, the SOM and SOC decreased with soil depth the SOM/SOC ratio increased. It showed that SOM in the subsoil contained more oxygen but less carbon than the SOM in the upper soil surface. The CEC/SOC also increased with depth indicating that the functional groups of the SOM increased per unity of carbon.

EuroSOMNET – a European database of long-term experiments on soil organic matter: the WWW metadatabase

2002 ◽  
Vol 138 (2) ◽  
pp. 123-134 ◽  
Author(s):  
P. SMITH ◽  
P. D. FALLOON ◽  
M. KÖRSCHENS ◽  
L. K. SHEVTSOVA ◽  
U. FRANKO ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Soviet Union ◽  
Former Soviet Union ◽  
Agricultural Soils ◽  
Climatic Conditions ◽  
European Database ◽  
Wide Range ◽  
Long Term Experiments

Since 1997, the EuroSOMNET project, funded by the EU-ENRICH programme, has assembled a metadatabase, and separate experimental databases, of European long-term experiments that investigate changes in soil organic matter. In this paper, we describe the WWW-based metadatabase, which is a product of this project. The database holds detailed records of 110 long-term soil organic matter experiments, giving a wide geographical coverage of Europe, and includes experiments from the European part of the former Soviet Union, many of which have not been available previously. For speed of access, records are stored as hyper-text mark-up language (HTML) files. In this paper, we describe the metadatabase, the experiments for which records are held, the information stored about each experiment, and summarize the main characteristics of these experiments. Details from the metadatabase have already been used to examine regional trends in soil organic matter in Germany and eastern Europe, to construct and calibrate a regional statistical model of humus balance in Russia, to examine the effects of climatic conditions on soil organic matter dynamics, to estimate the potential for carbon sequestration in agricultural soils in Europe, and to test and improve soil organic matter models. The EuroSOMNET metadatabase provides information applicable to a wide range of agricultural and environmental questions and can be accessed freely via the EuroSOMNET home page at URL: http://www.iacr.bbsrc.ac.uk/aen/eusomnet/index.htm.

scholarly journals Assessing soil carbon and soil quality for sustainable agricultural systems in tropical hillslope soils using spectroscopic methods

2017 ◽  
Author(s):  
◽  
Bunjirtluk Jintaridth
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Quality ◽  
Management Practices ◽  
Soil Management ◽  
Agricultural Systems ◽  
Wide Range ◽  
The World

Soil quality is a concept that integrates physical, chemical, and biological components and processes of soil across landscapes. Identifying and developing appropriate methods to quantify and assess changes in soil quality are necessary for evaluating soil degradation and improving management practices. Many parameters that are associated with soil quality depend on soil organic matter (SOM) levels and composition. The objectives of this research were to: 1) conduct a literature review of soil quality assessment techniques to evaluate soil quality across a wide-range of environments and agricultural practices; 2) determine if some standard soil sampling and analytical protocols could be identified or developed to enhance soil quality comparisons across a wide range of environments around the world; and 3) assess the efficacy of spectroscopic-based (i.e. near-infrared, mid-infrared, and visible range) analytical methods to evaluate soil organic matter fractions and soil quality. To assess soil quality for sustainable agricultural systems in hillslope soils using spectroscopic methods, surface soil samples (0-20 cm) were collected from hillslope agricultural sites in Bolivia, the Philippines and Indonesia which had differences in length of fallow, levels of soil degradation, and cultivation by landscape position. To determine the efficacy of spectroscopic-based on visible range, the use of the potassium permanganate test (MnOxC) for active organic carbon was studied. The MnOxC test was generally responsive to a range of fallow lengths among different agricultural fields and communities in Umala Municipality in Bolivia. A major objective of fallowing agricultural fields in this region is to restore soil fertility in the field after cropping. This general increase in MnOxC with increased length fallowing may be due to inputs of residue and roots from regrowth of native vegetation after cropping in fallowed areas and possible manure inputs from sheep that generally graze these fallow areas. In addition, higher concentrations of MnOxC were generally observed in non-degraded soil compared to that of degraded soil in all sampled communities in Cochabamba, Bolivia. Comparisons of soil quality among agroforestry and nonagroforestry sites were studied near Bogor, Indonesia. Both agroforestry and nonagroforestry sites had been managed with different types and rates (low, medium, and high) of amendments including manure, compost and chemical fertilizer. Soil MnOxC was generally higher with increasing amounts of added animal manure and in agroforestry areas compared to that of non-agroforestry areas. A set of soil samples was collected along a hill-slope transect from the top to the bottom of agricultural valley on Mindanao Island in the Philippines. The transect across the landscape was divided into summit, shoulder, backslope, footslope and toeslope landscape positions. Soil MnOxC from cultivated fields areas at each landscape position were generally lower than noncultivated areas at similar landscape positions. Among the non-cultivated sites, soil MnOxC was the highest at the summit position and the lowest at the backslope positions while soil MnOxC among cultivated sites were relatively similar across the hill-slope transect. This comparison of the use of the soil MnOxC test to determine changes in active C among a wide range of environmental conditions, cropping systems and soil management practices among agroecosystems with hillslopes in tropical countries around the world indicates that the soil MnOxC test is a sensitive indicator to assess changes in active C with changes in crop and soil management. Several advantages to using this procedure include its ease of use that requires a minimal of training for the field method, its low relative cost and growing research results that facilitate interpretation of the test results. Therefore, this method has potential for supporting management decisions, and sustainable management of agricultural systems in tropical hillslope ecosystems. The ability of visible/near-infrared (VNIR) spectroscopy to estimate soil organic carbon and carbon fractions from diverse soils in tropical hillslope agroecosystems around the world that were under different soil management and cropping systems was evaluated in this research. It was shown that VNIR spectroscopy could be an effective technique to estimate SOC and soil organic carbon fractions for a wide range of soils from tropical hillslope agroecosystems around the world. Several potential advantages of use of VNIR compared to conventional soil testing methods in developing countries are that it may allow for simultaneous evaluation of several soil properties and it can be done rapidly and possibly in the field. Diffuse Reflectance Fourier Transform Infrared Spectroscopy (DRIFT) is considered to be one of the most sensitive infrared techniques for analyzing the structural composition of soil organic matter. The benefit of the DRIFT technique is the ability to characterize the functional group composition of heterogeneous materials with minimal sample preparation. Results showed that this method can be used to characterize the functional groups of heterogeneous soil organic materials and it may be a more direct method to determine changes in soil organic matter and soil quality caused by soil management practices than several other chemical and spectral techniques. The high resolution of the spectra and quantitative estimations of functional groups can be used to analyze soil organic carbon composition. Therefore, in future work this technique has great potential to be an accurate and simple method for helping to understand the changes in the composition of soil organic carbon due to soil organic management practices and to estimate changes in soil quality resulting from those practices in these hillslope agroecosystems.

scholarly journals Identification and predictability of soil quality factors and indicators from conventional soil and vegetation classifications

2021 ◽  
Author(s):  
Paul Simfukwe ◽  
Paul W Hill ◽  
Davey L Jones ◽  
Bridget Emmett ◽  
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Soil Quality ◽  
Soil Type ◽  
Soil Classification ◽  
Biological Indicators ◽  
Soil Types ◽  
Quality Factors ◽  
Soil Attributes ◽  
Wide Range

Generally, the physical, chemical and biological attributes of a soil combined with abiotic factors (e.g. climate and topography) drive pedogenesis. However, biological indicators of soil quality play no direct role in traditional soil classification and surveys. To support their inclusion in classification schemes, previous studies have shown that soil type is a key factor determining microbial community composition in arable soils. This suggests that soil type could be used as proxy for soil biological function and vice versa. In this study we assessed the relationship between soil biological indicators with either vegetation cover or soil type. A wide range of soil attributes were measured on soils from across the UK to investigate whether; (1) appropriate soil quality factors (SQFs) and indicators (SQIs) can be identified, (2) soil classification can predict SQIs; (3) which soil quality indicators were more effectively predicted by soil types, and (4) to what extent do soil types and/ or aggregate vegetation classes (AVCs) act as major regulators of SQIs. Factor analysis was used to group 20 soil attributes into six SQFs namely; Soil organic matter , Organic matter humification , Soluble nitrogen , Microbial biomass , Reduced nitrogen and Soil humification index . Of these, Soil organic matter was identified as the most important SQF in the discrimination of both soil types and AVCs. Among the measured soil attributes constituting the Soil organic matter factor were, microbial quotient and bulk density were the most important attributes for the discrimination of both individual soil types and AVCs. The Soil organic matter factor discriminated three soil type groupings and four aggregate vegetation class groupings. Only the Peat soil and Heath and bog AVC were distinctly discriminated from other groups. All other groups overlapped with one another, making it practically impossible to define reference values for each soil type or AVC. We conclude that conventionally classified soil types cannot predict the SQIs (or SQFs), but can be used in conjunction with the conventional soil classifications to characterise the soil types. The two-way ANOVA showed that the AVCs were a better regulator of the SQIs than the soil types and that they (AVCs) presented a significant effect on the soil type differences in the measured soil attributes.

scholarly journals An inverse dielectric mixing model at 50 MHz that considers soil organic carbon

2021 ◽  
Author(s):  
Chang-Hwan Park ◽  
Aaron Berg ◽  
Michael H. Cosh ◽  
Andreas Colliander ◽  
Andreas Behrendt ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Moisture ◽  
Soil Organic Matter ◽  
Climate Models ◽  
Mineral Soil ◽  
Organic Matter Content ◽  
Mixing Model ◽  
Multiphase Model ◽  
Validation Experiment ◽  
Wide Range

Abstract. The prevalent soil moisture probe algorithms are based on a polynomial function that does not account for the variability in soil organic matter. Users are expected to choose a model before application: either a model for mineral soil or a model for organic soil. Both approaches inevitably suffer from limitations with respect to estimating the volumetric soil water content in soils having a wide range of organic matter content. In this study, we propose a new algorithm based on the idea that the amount of soil organic matter (SOM) is related to major uncertainties in the in-situ soil moisture data obtained using soil probe instruments. To test this theory, we derived a multiphase inversion algorithm from a physically based dielectric mixing model capable of using the SOM amount, performed a selection process from the multiphase model outcomes, and tested whether this new approach improves the accuracy of soil moisture (SM) data probes. The validation of the proposed new soil probe algorithm was performed using both gravimetric and dielectric data from the Soil Moisture Active Passive Validation Experiment in 2012 (SMAPVEX12). The new algorithm is more accurate than the previous soil-probe algorithm, resulting in a slightly improved correlation (0.824 0.848), 12 % lower root mean square error (RMSE; 0.0824 0.0725 cm3·cm−3), and 90 % less bias (−0.0042 0.0004 cm3·cm−3). These results suggest that applying the new dielectric mixing model together with global SOM estimates will result in more reliable soil moisture reference data for weather and climate models and satellite validation.

The role of active fractions of soil organic matter in physical and chemical fertility of Ferrosols

Soil Research ◽  
1998 ◽  
Vol 36 (5) ◽  
pp. 809 ◽  
Author(s):  
M. J. Bell ◽  
P. W. Moody ◽  
R. D. Connolly ◽  
B. J. Bridge
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Management Practices ◽  
Chemical Properties ◽  
Aggregate Stability ◽  
Infiltration Rate ◽  
Exchange Capacity ◽  
Organic C ◽  
Wide Range ◽  
Physical And Chemical

The relationships between fractions of soil organic carbon (C) oxidised by varying strengths of potassium permanganate (KMnO4) and important soil physical and chemical properties were investigated for Queensland Ferrosols. These soils spanned a wide range of clay contents (31-83%), pH values (4·4-7·9; 1 : 5 water), and total C contents (12· 1-111 g/kg). Carbon fractions were derived by oxidation with 33 mM (C1), 167 mM (C2), and 333 mM (C3) KMnO4, while organic C and total C were determined by Heanes wet oxidation and combustion, respectively. Aggregate stability was determined by wet sieving soil from the surface crust after 30 min of high intensity (100 mm/h), simulated rainfall on disturbed samples in the laboratory. The proportion of aggregates <0·125 mm (P125) was used as the stability indicator because of the high correlation between this size class and the final rainfall infiltration rate (r2 = 0qa86, n = 42). The soil organic C fraction most closely correlated with P125 was C1 (r2 = 0·79, n = 42). This fraction was also highly correlated with final, steady-state infiltration rates in field situations where there were no subsurface constraints to infiltration (r2 = 0·74, n = 30). Multiple linear regression techniques were used to identify the soil properties determining effective cation exchange capacity (ECEC, n = 89). Most variation in ECEC (R2 = 0 ·72) was accounted for by a combination of C1 (P < 0·0001) and pH (P < 0·0001). These results confirm the very important role played by the most labile (easily oxidised) fraction of soil organic matter (C1) in key components of the chemical and physical fertility of Ferrosols. Management practices which maintain adequate C1 concentrations are essential for sustainable cropping on these soils.

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