Prospectivity modeling of porphyry copper deposits: recognition of efficient mono- and multi-element geochemical signatures in the Varzaghan district,NW Iran

Acta Geochimica - The Varzaghan district at the northwestern margin of the Urumieh–Dokhtar magmatic arc, is considered a promising area for the exploration of porphyry Cu deposits in Iran. In...     

Spatio-temporal analysis of crime by developing a method to detect critical distances for the Knox test

The present study examined and compared spatio–temporal interaction of the theft of car parts, shop burglary and motorcycle theft in the central business district (CBD) of the city of Zanjan in Iran. The Knox test was selected to detect spatio–temporal interaction. This test has been criticized as being subjective because the selection of critical distances is arbitrary; thus, a method is proposed to detect critical distances in the Knox test using the mean distance, natural breaks classification of nearest neighbour (NN) distance and Ripley’s k function. Results show obvious differences between the spatio-temporal clusters of the three sets of crimes. They also indicate that changing the spatial cut-offs within a cluster creates different temporal patterns. Of the three criteria for determining critical distances, NN classification based on natural breaks showed more interactions than the other methods.     

An Improved Data-Driven Multiple Criteria Decision-Making Procedure for Spatial Modeling of Mineral Prospectivity: Adaption of Prediction–Area Plot and Logistic Functions

Natural Resources Research - Assigning realistic weights to targeting criteria in order to synthesize various geo-spatial datasets is one of the most important challenging tasks for mineral...     

Assessment of Various Fuzzy c-Mean Clustering Validation Indices for Mapping Mineral Prospectivity: Combination of Multifractal Geochemical Model and Mineralization Processes

This paper describes the application of an unsupervised clustering method, fuzzy c-means (FCM), to generate mineral prospectivity models for Cu?±?Au?±?Fe mineralization in the Feizabad District of NE Iran. Various evidence layers relevant to indicators or potential controls on mineralization, including geochemical data, geological–structural maps and remote sensing data, were used. The FCM clustering approach was employed to reduce the dimensions of nine key attribute vectors derived from different exploration criteria. Multifractal inverse distance weighting interpolation coupled with factor analysis was used to generate enhanced multi-element geochemical signatures of areas with Cu?±?Au?±?Fe mineralization. The GIS-based fuzzy membership function MSLarge was used to transform values of the different evidence layers, including geological–structural controls as well as alteration, into a [0–1] range. Four FCM-based validation indices, including Bezdek’s partition coefficient (V_Pc) and partition entropy (V_Pe) indices, the Fukuyama and Sugeno (V_FS) index and the Xie and Beni (V_XB) index, were employed to derive the optimum number of clusters and subsequently generate prospectivity maps. Normalized density indices were applied for quantitative evaluation of the classes of the FCM prospectivity maps. The quantitative evaluation of the results demonstrates that the higher favorability classes derived from V_FS and V_XB (N_d?=?9.19) appear more reliable than those derived from V_Pc and V_Pe (N_d?=?6.12) in detecting existing mineral deposits and defining new zones of potential Cu?±?Au?±?Fe mineralization in the study area.

     

A hybrid AHP-VIKOR approach for prospectivity modeling of porphyry Cu deposits in the Varzaghan District,NW Iran

Identifying highly favorable areas related to a particular mineralization type is the main objective of mineral prospectivity modeling (MPM). The northwestern portion of Ahar-Arasbaran porphyry copper belt (AAPCB) is situated within the Urumieh-Dokhtar magmatic belt (UDMB). Because of owning many worthwhile Cu-Mo and Cu-Au porphyry deposits, this area is entitled to incorporate diverse spatial evidence layers for the MPM. In this paper, a hybrid AHP-VIKOR, as an improved knowledge-driven MPM procedure has been proposed for integration of various exploration evidence layers. For this, the AHP is used to calculate important weights of spatial criteria while the VIKOR is applied to outline ultimate prospectivity model. Six effective spatial evidence layers pertaining to the Varzaghan District are selected: (1) multi-elemental geochemical layer of Cu-Mo-Bi-Au; (2) remotely sensed data of argillic, phyllic, and iron oxide alteration layers; and (3) geological and structural layers of Oligo-Miocene intrusions and fault. In addition, a fuzzy prospectivity model (γ?=?0.9) is implemented to assess the AHP-VIKOR approach. Two credible validation methods comprising normalized density index and success rate curve are adapted for quantitative evaluation of predictive models and enhancing the probability of exploration success. The achieved results proved the higher accuracy of the AHP-VIKOR model compared with the fuzzy model in delimiting the favorable areas.     

Equilibrium,Thermodynamic, and Kinetic Studies on Lead (II) Biosorption from Aqueous Solution by Saccharomyces cerevisiae Biomass

This paper presents a biosorption procedure for the preconcentration of Pb²⁺ ions using Saccharomyces cerevisiae biomass. The influence of several factors including pH, biomass dosage, contact time, and temperature on biosorption efficiency were optimized. At optimum value of all the equilibrium, thermodynamic, and kinetic parameters of Pb²⁺ ion biosorption was investigated by testing the Langmuir and Freundlich models and first and second order kinetic models were applied. The biosorption capacity of S. cerevisiae biomass was determined 89.6 mg/g, while the retained Pb²⁺ ions by S. cerevisiae were reversibly eluted using 5 mol/L HNO₃. Due to the high stability of S. cerevisiae the applied biomass can be used successively ten times with a slightly decrease (about 20%) in the recovery of Pb²⁺ ions. The calculated thermodynamic parameters, ΔG°, ΔH°, and ΔS° showed that the biosorption of Pb²⁺ ion onto S. cerevisiae biomass was feasible, spontaneous, and endothermic under examined conditions. The results of kinetic analysis showed that the biosorption processes of Pb²⁺ ions onto S. cerevisiae biomass followed pseudo second order kinetics.