Abstract

Pore characteristics and chemical composition of soil aggregates from two contrasting soil types (Fe‐rich Alisol and SOM‐rich Phaeozem) were determined with synchrotron radiation X‐ray micro‐computed tomography (SR‐mCT) and scanning electron microscopy coupled with an energy‐dispersive X‐ray spectrometer (SEM–EDS). Data fusion to combine 3‐D SR‐mCT images and 2‐D SEM–EDS data was used to establish the relation between pore structure and cementing substances within the soil aggregates. The SR‐mCT analysis showed that Phaeozem aggregates had greater total measurable porosity and were more anisotropic (DA) than Alisol aggregates. Soil aggregates of 5–10, 2–5 and 0.5–2 mm diameter were measured and found to have a similar pore‐size distribution (PSD) across a range of pore sizes for the Alisol, but not for the Phaeozem. The SEM–EDS mapping revealed that Fe‐rich areas in Alisol aggregates were connected, whereas the carbon‐rich areas in Phaeozem aggregates were isolated. Wavelet analysis suggested that the Alisol aggregates might have been formed by global interactions among microaggregates and iron oxides, whereas the Phaeozem aggregates were formed by localized interactions among microaggregates and carbon, the main cementing agent. The heatmap analysis showed that iron oxide not only acts as a binding agent in Alisol aggregates, but also affects the pore size in addition to the pore shapes, whereas carbon functions only as a binding agent and has little effect on pore structure of the Phaeozem aggregates. The combination of SR‐mCT and SEM–EDS techniques provides a powerful tool for quantifying the pore characteristics of soil aggregates and investigating the interactions between the pore structure and cementing substances within the aggregates.HighlightsThe effects of different cementing substances on the pore structure of Fe‐rich and SOM‐rich soil aggregates. A multi‐scale analysis and data fusion method were applied to data from synchrotron imaging and SEM. Iron oxides affected only the pore structure of the Fe‐rich soil aggregates. The data fusion method has potential for understanding the key features of soil at the aggregate scale.

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