Heavy metal mobility assessment in sediments from the Odiel River (Iberian Pyritic Belt) using sequential extraction

The Tessier sequential extraction scheme (SES) was applied to sediments from the Odiel river catchment (Iberian Pyritic Belt, SW of Spain), one of the most acid rivers on Earth, to assess the chemical association (exchangeable, carbonatic, bound to manganese and iron oxides, bound to organic matter and residual mineral) of heavy metals (Zn, Cd, Pb, Cu, Cr, Mn, Ni, Fe, and Hg). Sediments are very heterogeneous in their textural characteristics, showing different grain size. Twenty-seven samples were studied from from areas along the Odiel River, from the source to the mouth, with special interest in the Odiel Marshes Natural Park due to its ecological significance. Samples were classified as sandy (especially at the river mouth with low iron oxide and organic matter content) and clay-silty (in the middle of the river catchment with high iron oxide content). The numerous sandy samples with low pH values explain the low levels of metals upstream, although potential metals contributions arise from mining and ore. However, the presence of sulfate in the mining area and carbonate at the mouth may explain the high presence of lead and iron in these sandy zones. Some percentage of mobile Ni, Cu, and Zn were detected in the mining area, but the elevated relative percentage of exchangeable Cd in the estuary is even more remarkable. The percentage of Zn bound to carbonate is considerable in the catchment but especially in the estuary. However, Cu is only detected in the carbonate phase downstream, in spite of the low concentration of carbonate, which represents a drawback in the application of the Tessier SES to these types of samples. Finally, relatively high percentages of residual, non-mobile, Hg and Pb were observed, in the estuarine and mining areas, respectively. Sand, lime, and clay fractions of representative samples from Areas I, II, and III were used in a metal speciation study. Mainly, the elements analyzed had accumulated in the non-residual fractions. In the mining area of the Pyrite Belt, the elements analyzed are mainly bound to Fe–Mn oxides (Fe + Mn + Cu + Cr + Pb + Mn ± Zn) and the organic matter/sulfide fraction (Ni + Zn + Hg ± Cd), independent of sediment grain size. In conclusion, we show that the results of the study of chemical speciation in sediments from acid rivers are independent of the sediment grain size considered.     

Determination of the relative thermal conductivity of solid samples by X-ray diffraction device

The thermal conductivity (TC) of metal and rock samples was determined, under ambient conditions, using standard X-ray diffraction equipment in which only the diffractometer sample holder had been modified from the original. As the method is comparative, standard reference materials were used: a copper standard for the analysis of metals and marble for the rock specimens. The marble was analyzed beforehand using a quick thermal conductivity meter QTM. In experimental measurements of TC the mean reproducibility value appears to be about 4% while the accuracy is about 5% for the examined rocks, and better for metals.     

Analyzing the spatial interactions between rainfall levels and flooding prediction in São Paulo

Rainfall is one of the primary triggers for many geological and hydrological natural disasters. While the geological events are related to mass movements in land collapse due to waterlogging, the hydrological ones are usually assigned to runoff or flooding. Studies in the literature propose predicting mass movement events as a function of accumulated rainfall levels recorded at distinct periods. According to these approaches, a two-dimensional rainfall levels feature space is segmented into the occurrence and non-occurrence decision regions by an empirical critical curve (CC). Although this scheme may easily be extended to other purposes and applications, studies in the literature need to discuss its use for flooding prediction. In light of this motivation, the present study is unfolded in (1) verifying that defining CCs in the rainfall levels feature space is a practical approach for flooding prediction and (2) analyzing how geospatial components interact with rainfall levels and flooding prediction. A database containing the rainfall levels recorded for flooding and non-flooding events in São Paulo city, Brazil, regarding the period 2015–2016, was considered in this study. The results indicate good accuracy for flooding prediction using only partial rain, which can be improved by adding physical characteristics of the flooding locations, demonstrating a direct correlation with spatial interactions, and rainfall levels.