Mineralogical and chemical evolution of ochreous precipitates from the Libiola Fe–Cu-sulfide mine (Eastern Liguria,Italy)

The mineralogical and chemical evolution of ochreous precipitates forming from acid mine drainage (AMD) from the abandoned Libiola Fe–Cu-sulfide mine (Eastern Liguria, Italy) was followed through a multianalytical approach (XRD, TEM, XRF, ICP) applied to surface precipitates and associated waters collected from several mine adits. The mineralogy of the precipitates changed significantly as a consequence of the variations of the chemical parameters of the circulating solutions (mainly pH, Eh, and sulfate concentrations) which, in turn, were mainly controlled by mixing with unpolluted stream and rill waters of the mining area. A progressive transition from jarosite-, to schwertmannite-, to goethite-, to ferrihydrite-, to amorphous-dominated precipitates was observed, mainly as a consequence of an increase in the pH of the associated solutions. This mineralogical evolution agrees well with the aqueous speciation and Eh–pH stability calculations performed on the waters associated with the different precipitate types. Furthermore, TEM analysis indicated that metastable pristine phases (schwertmannite) tend to transform progressively to well-crystallized more stable species, here represented by goethite. The comparison of the water chemistry and the crystal chemistry of the different precipitates showed a significant decrease in the Zn, Cu, Ni, Co contents in waters where the coexisting precipitates were almost exclusively composed of goethite. The distribution of V, Sr, As concentrations within the different precipitates showed that the most efficient scavenging phase for these elements was jarosite, whereas ferrihydrite efficiently took up Pb ions, and schwermannite acted as a natural sink for Cr.     

Probabilistic GIS-based method for delineation of urban flooding risk hotspots

Identifying urban flooding risk hotspots is one of the first steps in an integrated methodology for urban flood risk assessment and mitigation. This work employs three GIS-based frameworks for identifying urban flooding risk hotspots for residential buildings and urban corridors. This is done by overlaying a map of potentially flood-prone areas [estimated through the topographic wetness index (TWI)], a map of residential areas and urban corridors [extracted from a city-wide assessment of urban morphology types (UMT)], and a geo-spatial census dataset. A maximum likelihood method (MLE) is employed for estimating the threshold used for identifying the flood-prone areas (the TWI threshold) based on the inundation profiles calculated for various return periods within a given spatial window. Furthermore, Bayesian parameter estimation is employed in order to estimate the TWI threshold based on inundation profiles calculated for more than one spatial window. For different statistics of the TWI threshold (e.g. MLE estimate, 16th percentile, 50th percentile), the map of the potentially flood-prone areas is overlaid with the map of urban morphology units, identified as residential and urban corridors, in order to delineate the urban hotspots for both UMT. Moreover, information related to population density is integrated by overlaying geo-spatial census datasets in order to estimate the number of people affected by flooding. Differences in exposure characteristics have been assessed for a range of different residential types. As a demonstration, urban flooding risk hotspots are delineated for different percentiles of the TWI value for the city of Addis Ababa, Ethiopia.     

Liquefaction triggering in silty sands: effects of non-plastic fines and mixture-packing conditions

Acta Geotechnica - During recent seismic events, such as 2010 Darfield and 2016 Ecuador earthquakes, widespread liquefaction has been observed in sand deposits with silt content. Nevertheless, the...