Tag: particle size analysis

A new depositional model for sand-rich loess on the Buckley Flats outwash plain, northwestern Lower Michigan

This landscape was originally interpreted as loess mixed with underlying sands. This paper re-evaluates this landscape through a spatial analysis of data from auger samples and soil pits. To better estimate the loamy sediment’s initial textures, we utilized “filtered” laser diffraction data, which remove much of the coarser sand data. Our new model for the origin of the loamy mantle suggests that the sands on the uplands were generated from eroding gullies and saltated onto the uplands along with loess that fell more widely.

Particle Size Analysis Toolpack v2

A zip file containing a suite of tools for analyzing continuous particle size curves from laser diffractometry. Includes: export templates for Malvern software, analysis template for recommended quality control procedure, reporting templates for organized presentation of results with additional metrics, and a data filter for removing the larger particle size peak from bimodal curves.

Thin, pedoturbated, and locally sourced loess in the western Upper Peninsula of Michigan

County soil surveys document thin loess deposits across large tracts of Michigan’s western Upper Peninsula (UP), which we informally call the Peshekee loess. Our study is the first to examine the distribution, thickness and textural characteristics of these loess deposits, and speculate as to their origins. We introduce and describe a method by which the mixed sand data are removed, or “filtered out,” of the original particle size data, to better reflect the original textural characteristics of the loess.

Precision of soil particle size results using laser diffractometry

Because laser diffractometry produces much more detailed data than does traditional pipette analysis, and because a much smaller sample is used in the analysis, precision or repeatability of laser-produced PSA data is a concern. The approach presented provides both a simple method for assessing the variation in PSA data sets and establishes a comparable standard for determining when additional measurements are needed to find a more precise result.