Coevolution of Organic Substances and Soils

Coevolution of Organic Substances and Soils

electronic supplementary material

Coevolution of Organic Substances and Soils

Short-term evolution of hydration effects on soil organic matter properties and resulting implications for sorption of naphthalene-2-ol

Tatjana Schneckenburger • Gabriele E. Schaumann • Susanne K. Woche • Sören Thiele-Bruhn

Received: 22 December 2011 / Accepted: 12 March 2012

© Springer-Verlag 2012

Responsible editor: Friederike Lang

T. Schneckenburger • S. Thiele-Bruhn ()

Soil Science, FB VI Geography/ Geosciences, Universität Trier, Behringstr. 21, 54286 Trier, Germany

e-mail:

G. E. Schaumann

Institute for Environmental Sciences, Department of Environmental and Soil Chemistry, Universität Koblenz-Landau, Fortstrasse 7, 76829 Landau, Germany

S. K. Woche

Institute of Soil Science, Leibniz Universität Hannover, Herrenhäuser Str. 2, 30419 Hannover, Germany

() Corresponding author:

Sören Thiele-Bruhn

Tel. +49-651 201 2241

Fax: +49 651- 201 3809

e-mail:

SI 1: Derivative Fitting Method

In peat HR samples, superposed transitions were observed in DSC thermograms. So far, T* wasdetermined from thermograms with the tangent method (Fig. SI 1 a).Superposed transitions observed in peat HR could not be separated by the customary tangent method. Therefore separation was realized by the following approach.

The Multi-Gauss model uses the first derivative of the heat flow thermogram where the sigmoidal step transitions transform to peaks (Fig. SI 1 a).This visualizes the superposed transitions and eliminates baseline effects without loss of information. The superposed peaks are separated by the addition of peak functions (Fig. SI 1 b). Each peak function contains parameters of the respective transition: Transition temperature (T*), transition height (=change in heat capacity, ΔC), and the width (temperature range) of the transition.

Figure SI 1: Derivative fitting method for the evaluation of superposed transitions in DSC thermograms.

Eachtransition peak was described by a function derived from the Gaussian normal distribution (Sachs and Hedderich 2006, Equation 1).

(Eq. SI 1)

The function dH/dT (J g-1 s-2) is the time-based first derivative of heat flow at the temperature Tthat was calculated by Universal analysis (TA instruments, Germany). The step transition temperature Ti* corresponds tothe position of the peak maximum. A temperature range of six times the standard deviation of the peak (K) covers 99% of the peak area (transition intensity) (Sachs and Hedderich, 2006). Thus, the standard deviation in the Gauss-distribution was substituted by 1/6 the width ω (K) of the transition. The change in heat capacity ΔC (J g-1K-1) multiplied by the heating rate Rh(K s-1) corresponds to the area of the peak (height of step in original thermogram).

First derivative curves exported from Universal analysis were fitted by Eq. SI 1 (i = 2) using OriginPro7 (OriginLab Corporation, Northhampton, MA, USA). The average correlation coefficient R2of the fits was 0.995±0.009 and the reduced χ2 was 2.79 *10-10±5.27 *10-10.

SI 2: Non-linear calculation of wcrit(critical water content for the formation of freezable water)

For the calculation of wcrit in peat HR samples we considered that the specific melting energy of water in peat increased with increasing water content. It was assumed that the overall melting energy approaches the bulkwater melting energy of 333.5Jg-1 at very high water contents, when the amounts of non-freezable and surface-affectedwater become negligible compared to the amount of bulk water in a sample. An empirical equation was used (Eq. SI2),

(Eq. SI 2)

where ΔE(w)(J g-1) is the melting energy normalized to the mass of the dry soil sample,w(gg-1) is the water content, wcrit(gg-1)is the critical water content for the formationof freezable water, and ΔEbulk(J g-1) is the melting energy of bulk water. The parameterais a constant that was set to 0.30 (best fit) for the investigated HR samples. Fixing of the constant aseemed appropriate because a was assumed to be a material related constant.

Equation SI 2fulfils three boundary conditions identified from the considerations for the melting energy ofwater in a SOM matrix:

- ΔE(w) approaches the asymptote ΔE(w -> ∞) = ΔEbulk*w + (a -2)*ΔEbulk*wcrit with the slope ΔEbulk.

- The melting energy of water at wcritis zero:ΔE(wcrit) = 0

-Because the specific ΔE of water increases from 0 to 333.5 J g-1, the slope in wcrit is zero and approaches 333.5 J g-1, dΔE(wcrit)/dw = 0.

Figure SI 2 shows the regression curves of Eq.SI 2 on data of peat HR. The averagewcrit was 26.2 ± 0.3%. For comparison, a linear approach overestimated wcrit (30.2%), because at 30% water content there was stillfreezable water present in the samples.

Figure SI 2: Non-linear determination of the critical water content for the formation of non-freezable water wcrit in peat HR.

In general, results on wcritare in accordance with aprevious study where values for wcritof 23% ±7% and 29% ±2%were observed in two different peat samples(Schaumann 2005), determined by the linear approach. Here theauthors also considered a non-linear approach to be reasonable.The non-linear approach was meant to be an empirical description of the data only aiming to improve the accuracy of wcrit. It must be extended by a thermodynamically basedterm for the development of the specific melting energy of water for example includingpore diameter or surface-water interactions.

References

Schaumann GE (2005) Matrix relaxation and change of water state during hydration of peat. ColloidSurface65:163-170

Sachs L, Hedderich J (2006) Angewandte Statistik. Springer Verlag, 12th edition

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