In the frame of our research projects NKFIH K120620 'Paleoenvironmental reconstruction based on particle size and shape of aeolian dust deposits' and NKFIH KH130377 'Granulometric analysis of recent Saharan dust' we've published our new granulometric milestone papers! Critical questions of laser diffraction and automated static image analysis measurements, and problematic interpretations of grain size data were discussed in the following papers:
- Varga, Gy., Gresina, F., Újvári, G., Kovács, J., Szalai, Z. (2019). On the reliability and comparability of laser diffraction grain size measurements of paleosols in loess records. Sedimentary Geology 389, pp. 42-53.
- Varga, Gy., Kovács, J., Szalai, Z., Cserháti, Cs., Újvári, G., (2018). Granulometric characterization of paleosols in loess series by automated static image analysis. Sedimentary Geology 370, pp. 1-14.
- Varga, Gy., Újvári, G., Kovács, J. (2019). Interpretation of sedimentary (sub)populations extracted from grain size distributions of Central European loess-paleosol series. Quaternary International 502, Part A, pp. 60-70
On the reliability and comparability of laser diffraction grain size measurements of paleosols in loess records
Laser diffraction grain size data and size distributions of paleosols are widely used in paleoenvironmental reconstructions as physicochemical alteration-related proxies of past changes of the sedimentary environment. Different laser diffraction devices, optical theories, and optical settings are being applied nowadays, and ignorance of several uncertainty factors and drawbacks of this indirect grain size characterization approach has led to poorly comparable and reproducible granulometric datasets.
Here we present a detailed comparison of grain size results acquired by three state-of-the-art, widely used laser diffraction devices (Fritsch Analysette 22 Microtec Plus, Horiba Partica La-950 v2 and Malvern Mastersizer 3000). Grain size distributions were calculated using both the Fraunhofer and Mie scattering theories and a wide variety of optical settings (68 different complex refractive indices: 1.45–1.6–0.01i-1i) for 10 samples from loess-paleosol sequences of the Carpathian Basin.
Our findings demonstrate that optical settings have significant effects on grain size distributions, especially for the finest fractions (clay and fine silt populations). Interestingly, the selection of laser diffraction devices was an even more deterministic factor in grain size characterization as revealed by network analyses. Clustering of bulk and size-fractionated grain size records was primarily determined by the device used, and also by the applied optical settings. At the same time, the real physical differences of samples were found to be deterministic exclusively for the sand-sized fraction. As such, these findings emphasize the importance of the accurate description of applied methodological details in research papers, as comparability and reproducibility of granulometric datasets cannot be ensured with a lack of information about instrumental conditions and settings.
Granulometric characterization of paleosols in loess series by automated static image analysis
An automated image analysis method is proposed here to study the size and shape of siliciclastic sedimentary particles of paleosols of Central European loess sequences. Several direct and indirect measurement techniques are available for grain size measurements of sedimentary mineral particles. Indirect techniques involve the use of some kind of physical laws, however, all requirements for calculations are in many cases not known. Even so, the direct manual microscopic observation and measurement of large, representative number of grains is time-consuming and sometimes rather subjective. Therefore, automated image analyses techniques provide a new and perspective way to analyse grain size and shape sedimentary particles. Here we test these indirect (laser diffraction) and direct (automated static image analysis) techniques and provide new granulometric (size and shape) data of paleosols. Our results demonstrate that grain size data of the mineral dust samples are strongly dependent on shape parameters of particles, and shape heterogeneity was different between different size classes. Due to the irregular grain shape parameters, uncertainties have arisen also for determination of grain sizes. In this paper we present a possible correction procedure to reduce the differences among the results of the laser diffraction and image analysis methods. By applying new correction factors, results of the two approaches could become closer but the unknown thickness of particles remains a problem to solve.
The other presented correction procedure to assess the uncertain 3rd dimension of particles by their intensity-size relationships makes us able to reduce further the deviations of the two sizing methods.
Interpretation of sedimentary (sub)populations extracted from grain size distributions of Central European loess-paleosol series
Grain size proxies of aeolian dust deposits have widely been applied in environmental and sedimentary studies. However, large body of research papers are not taking into consideration that a complex grain size distribution curve cannot be an indicator of a single one environmental factor (e.g. wind speed/strength, transportation distance, aridity).
The aim of the present paper is to discuss the main differences of frequently used statistical methods and to provide possible interpretations of the results by applying these various approaches on the high-resolution loess-paleosol profile of Dunaszekcső, South Hungary (Central Europe). Beside single statistical descriptors (mean, median, mode) of grain size and simple indices of size-fraction ratios (U-ratio, Grain Size Index), some more complex algorithms were also used in our paper. The applied parametric curve-fitting, end-member modelling and hierarchical cluster analysis techniques are using the whole spectrum of the measured grain size distributions and provide a more reliable and more representative results even in case of small scale variations.
According to our findings, approaches which provide direct linkage among simple statistical descriptors and single atmospheric or other environmental elements are rather oversimplified as properties aeolian dust deposits are influenced by the integrated effects of several concurrent processes. Differences of more complex decomposition methods arise from the different approach and scope. End-members are determined from the unmixing based on the covariance structure of the whole grain size data-series of the section, while the parametric curve-fitting is based on the one-by-one deconvolution of the grain size distribution curves. End-members of loess-paleosol samples are regarded as representation of the average dust grain size distribution of various temporal sediment clusters of seasonal or other short-term intervals, while (sub)populations by parametric curve-fitting are proposed to illustrate process-related elements of background and dust storm depositional components for each sample. Results of cluster analysis represent similar grouping conditions as end-member modelling with a reduced sedimentary and genetically meaning.
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