Origin of 1.8 Ga zircons in Post Eocene mafic dikes in the Roshtkhar area,NE Iran     

Elahe Alizadeh  Gholamreza Ghadami  Dariush Esmaeily  Changqian Ma  David R Lentz  Jafar Omrani 《International Geology Review》2018,60(15):1855-1882

The Roshtkhar area is located in the Khaf-Kashmar-Bardaskan volcano-plutonic belt to the northeastern Iran along the regional E–W trending Dorouneh Fault, northeastern of the Lut Block. There are several outcrops of subvolcanic rocks occurring mainly as dikes in the area, which intruded into Cenozoic intrusive rocks. We present U–Pb dating of zircons from a diabase dike and syenite rock using LA-ICP-MS that yielded an age of 1778 ± 10 Ma for the dike, indicating this Cenozoic dike has zircon xenocrysts inherited from deeper sources; and 38.0 ± 0.5 Ma, indicating an Late Eocene crystallization age for the syenite. Geochemically, the dikes typical of high-K calc-alkaline to shoshonitic magmas. Petrographic observations and major and trace element variations suggest that diabase melts underwent variable fractionation of clinopyroxene, olivine, and Fe-Ti oxides and minor crustal contamination during the differentiation process. Primitive mantle-normalized multi-element diagrams display enrichment in LILE, such as Rb, Ba, Th, U, and Sr compared to HFSE, as well as negative anomalies of Nb, Ta, P, and Ti, suggesting derivation from subduction-modified mantle. Chondrite-normalized REE plots show moderately LREE enriched patterns (<3.83 La_N/Yb_N <8.27), and no significant Eu anomalies. Geochemical modelling using Sm/Yb versus La/Yb and La/Sm ratios suggests a low-degree of batch melting (~1–3%) of a phlogopite-spinel peridotite source to generate the mafic dikes. The geochemical signatures suggest that the Roshtkhar mafic dikes cannot be related directly to subduction and likely resulted from melting of upper mantle in an extensional setting where the heat flow was provided from deeper levels. These dikes presumably derived the zircon xenocrysts from the assimilation of upper crust of Gondwanian basement. Processes responsible for partial melting of metasomatized lithospheric mantle and post-collision magmatism in NE Iran was triggered by heating due to asthenospheric upwelling in an extensional setting.  相似文献   

A benchmark study on problems related to CO2 storage in geologic formations   总被引：1，自引：0，他引：1  

Holger Class  Anozie Ebigbo  Rainer Helmig  Helge K. Dahle  Jan M. Nordbotten  Michael A. Celia  Pascal Audigane  Melanie Darcis  Jonathan Ennis-King  Yaqing Fan  Bernd Flemisch  Sarah E. Gasda  Min Jin  Stefanie Krug  Diane Labregere  Ali Naderi Beni  Rajesh J. Pawar  Adil Sbai  Sunil G. Thomas  Laurent Trenty  Lingli Wei 《Computational Geosciences》2009,13(4):409-434

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Comparing different statistical models for assessing Fe-contaminated soils based on VNIR/SWIR spectral data     

Mahboobeh Tayebi  Mehdi Naderi  Jahangard Mohammadi  Mohammad H. Tayebi 《Environmental Earth Sciences》2017,76(21):734

Two statistical models including partial least squares regression (PLSR) and principal component regression were comparatively utilized to determine the predictive accuracy of visible–near-infrared and short-wave infrared reflectance spectroscopy in quantifying the Fe concentration in contaminated soils. Two scenarios were applied to select the best model: Scenario I included all wavelengths (400–2450 nm) and Scenario II encompassed characteristic bands of Fe. Pre-processing techniques used to select the best model included: first and second derivatives (FD and SD), multiplicative scatter correction (MSC) and standard normal variate. The abilities of the predictive models were evaluated by splitting soil samples into two random groups (80 and 20%). The first group (80%) was used to evaluate calibration and validation sets by employing the cross‐validation method, and the second group (20%) was applied to test the models. The coefficient of determination (R ²), root mean square error and residual prediction deviation were calculated to evaluate the models. Applying Scenario I indicated that the PLSR model with SD pre-processing was a more accurate technique for predicting the Fe concentration, whereas in the Scenario II, the PLSR model with MSC pre-processing had a better performance. Comparing Scenarios I and II indicated that the more reliable models for predicting the soil Fe content could be constructed by the PLSR model with the SD pre-processing techniques and all wavelengths. The modeling results produced by the PLSR model with the SD pre-processing could be used to detect, map and monitor Fe-contaminated soils by proximal and remote sensing in the mining areas.  相似文献   

Central Composite Design Optimization of Biological Dye Removal in the Presence of Macroalgae Chara sp.     

Ali R. Khataee  Gholamreza Dehghan  Elahe Ebadi  Minoo Pourhassan 《洁净——土壤、空气、水》2010,38(8):750-757

Response surface methodology (RSM) was employed to investigate the effects of different operational parameters on the biological decolorization of a dye solution containing malachite green (MG) in the presence of macroalgae Chara sp. The investigated variables were the initial pH, initial dye concentration, algae amount, and reaction time. Central composite design (CCD) was used for the optimization of biological decolorization process. Predicted values were found to be in good agreement with experimental values (R² = 0.982 and Adj‐R² = 0.966), which indicated suitability of the employed model and the success of RSM. The results of optimization predicted by the model showed that maximum decolorization efficiency was achieved at the optimum condition of the initial pH 6.8, initial dye concentration 9.7 mg/L, algae amount 3.9 g, and reaction time 75 min. UV–VIS spectra and FT‐IR analysis showed degradation of MG.  相似文献   

Spatial variation assessment of groundwater quality using multivariate statistical analysis(Case Study: Fasa Plain,Iran)          下载免费PDF全文

Bahrami Mehdi  Khaksar Elmira  Khaksar Elahe 《地下水科学与工程》2020,8(3):230-243

Groundwater is considered as one of the most important sources for water supply in Iran. The Fasa Plain in Fars Province, Southern Iran is one of the major areas of wheat production using groundwater for irrigation. A large population also uses local groundwater for drinking purposes. Therefore, in this study, this plain was selected to assess the spatial variability of groundwater quality and also to identify main parameters affecting the water quality using multivariate statistical techniques such as Cluster Analysis (CA), Discriminant Analysis (DA), and Principal Component Analysis (PCA). Water quality data was monitored at 22 different wells, for five years (2009-2014) with 10 water quality parameters. By using cluster analysis, the sampling wells were grouped into two clusters with distinct water qualities at different locations. The Lasso Discriminant Analysis (LDA) technique was used to assess the spatial variability of water quality. Based on the results, all of the variables except sodium absorption ratio (SAR) are effective in the LDA model with all variables affording 92.80% correct assignation to discriminate between the clusters from the primary 10 variables. Principal component (PC) analysis and factor analysis reduced the complex data matrix into two main components, accounting for more than 95.93% of the total variance. The first PC contained the parameters of TH, Ca²⁺, and Mg²⁺. Therefore, the first dominant factor was hardness. In the second PC, Cl^-, SAR, and Na⁺ were the dominant parameters, which may indicate salinity. The originally acquired factors illustrate natural (existence of geological formations) and anthropogenic (improper disposal of domestic and agricultural wastes) factors which affect the groundwater quality.  相似文献   

The impact of acid rain on phosphorus leaching from a sandy loam calcareous soil of western Iran   总被引：1，自引：0，他引：1  

Mohsen Jalali  Elaheh Naderi 《Environmental Earth Sciences》2012,66(1):311-317

Simulated acidic precipitation (1:1 equivalent basis H₂SO₄:HNO₃) at pH values of 2.5, 3.0, 3.5, 4.0, 4.5, 5.0 and 7.0 were conducted using column leaching to determine impacts of simulated acid rain on phosphorus (P) leaching from a calcareous sandy loam soil over a 40-day period. Soil columns were irrigated every day to make a total of 1,061 mm, equivalent to 3.5 years of rainfall (based on average annual rainfall). Leachates were collected and analyzed for anions and cations. There was significant nonlinear correlation between the amount of P leached and the simulated acid rain (R ² = 0.61). Losses of P from the pH 2.5 and 7.0 treatments were 1.23, and 1.32 mg kg⁻¹, respectively. The results showed that the amount of P leached from pH 4 (1.46 mg kg⁻¹) and 5 treatments (1.52 mg⁻¹ kg⁻¹) were significantly larger than other treatments. Linear equation adequately described leaching of P in different treatments. The slope (mg kg⁻¹ day⁻¹) in the linear equation was defined as the leaching rate and for the pH 2.5 was 0.0354, and 0.0382 and 0.0406 for pH 4.5 and 7.0, respectively. The geochemical code Visual MINTEQ was used to calculate saturation indices. Leaching of P in different treatments was controlled by rate-limited dissolution of hydroxyapatite, β-tricalcium phosphate and to some extent octacalcium phosphate. The results indicate that acid rain in calcareous sandy loam soils may pose a risk in terms of groundwater contamination with P.  相似文献   

Application of inverse geochemical modelling for predicting surface water chemistry in Ekbatan watershed,Hamedan, western Iran     

Elahe Naderi Peikam  Mohsen Jalali 《水文科学杂志》2013,58(6):1124-1134

ABSTRACT

A study of surface water chemistry evolution was conducted by multivariate statistical analysis and inverse geochemical modelling using the PHREEQC computer program. Using hierarchical cluster analysis the 14 sampling sites were classified into three groups (recharge, transition and discharge areas). Water chemistry changed along a flow path so that waters with Ca–HCO₃ and Mg–Cl composition changed to Mg–Cl–HCO₃ waters. The order of abundance of the major cations was Mg > Ca > Na > K. Their average concentrations were 21, 19, 3.6 and 2.5 mg L^-1, respectively. Inverse geochemical modelling along flow paths indicated that the dissolution of sylvite and kaolinite, and precipitation of feldspars and andalusite, happened with Na entering the solution and Ca, Mg and K leaving the solution.