Middle pleistocene variations in palaeoclimate,palaeoenvironment and vegetation of the las tablas de daimiel national park (Spain)

The Middle Pleistocene palaeoclimate and palaeoenvironment evolution of the Las Tablas de Daimiel wetlands is described using a combination of sedimentology, pollen and δ¹³C and δ¹⁸O isotopic records of Unit B of core LT‐199906. This unit mostly contains fluvial and palustrine sediments. U/Th and amino acid racemization (AAR) dating and a comparison of the δ¹⁸O curve of Unit B with oceanic records suggests that Unit B spans the period from the end of Marine Isotope Stage (MIS) 10 (340 ka) to the first stages of MIS 7 (ca. 210 ka). MIS 9 was characterised by a regional vegetation dominated by Cupressaceae, with Pinus as a tree element. The water level was high and temperatures were very probably higher than during the Holocene. MIS 8 and the first substages of MIS 7 (7e, 7d and 7c) were dominated by xerophilous steppe vegetation in lowlands (elevations around 610 m above sea level) near to the wetland. At higher altitudes, far away from the wetland, there were fewer Pinus than in MIS 9, and a greater presence of warm, temperate and cool climate tree elements. The aquatic system in MIS 9 became shallower, with eutrophication and the accumulation of organic matter occurring; temperatures were similar to or lower than those of the Holocene. Copyright © 2011 John Wiley & Sons, Ltd.     

Shoreline spatial and temporal response to natural and human effects in Boujagh National Park,Iran

Shoreline variation and river deltas are among the most dynamic systems in marine environments. The related different variations in spatial and temporal scales play significant roles in land planning and different management applications. Modeling the dynamics of seashore of Boujagh National Park (BNP) which is located on the southern coast of the Caspian Sea in the Sefidrud Delta (SD), considering natural and anthropogenic factors, was the main objective of the current study. To achieve this goal, a combination of remote sensing data, historical data, and numerical simulations was utilized. The BNP covers an area of 3,270 ha and includes two international wetlands, Boujagh and Kiashahr. In earlier periods, this area faced severe morphological changes whereas recently its shoreline has experienced gradual variations. Accordingly, at the first stage, the shoreline variation from 2006 to 2017 was extracted by processing and classifying Operational Land Imager (OLI) and Thematic Mapper (TM) images from Landsat satellites using the Maximum Likelihood approach. In the second stage, the two dimensional MIKE21 model was utilized to identify wave and coastal current patterns and parameters for the year 2015. Morphologically, the results showed that, the shoreline of the BNP is affected by several natural and anthropogenic factors. Seaward advancement of the shoreline occurred in zones A (east zone) and C (west zone) due to Caspian Sea Level drop and sedimentation while retreating occurred at Zone B (north zone) influenced by wave and current patterns and reduction of the Sefidrud River flows. Also, the results imply that maintaining the existing conditions results in the disappearance of a considerable part of the ecological area in the BNP. Hence, to manage and preserve the coastline of the BNP complying with the current anthropogenic and natural factors, it is vital to take necessary management measures.     

Treatment of Synthetic Olefin Plant Wastewater at Various Salt Concentrations in a Membrane Bioreactor

The objective of this study was to investigate the effect of salt concentration on performance of a membrane bioreactor (MBR) for treating an olefin plant wastewater. For this purpose, a lab‐scale submerged MBR with a flat‐sheet ultrafiltration membrane was used for treatment of synthetic wastewater according to oxidation and neutralization unit of olefin plant. The synthetic wastewater was adjusted to have 500 mg/L chemical oxygen demand (COD). Trials on different concentrations of sodium sulfate (Na₂SO₄) (0–20 000 ppm) in the feed were conducted under aerobic conditions in the MBR. The results showed that increasing the salt concentrations causes an increase in the effluent COD, phenol, and oil concentrations. These results are due to reduction of the membrane filtration efficiency and also decline in the microbial activity that it is indicated by decreasing the sOUR in MBR. But in all the trials, the effluent COD and oil concentration was well within the local discharge limit of 100 and 10 mg/L, respectively. These results indicate that the MBR system is highly efficient for treating the olefin plant wastewater, and although high salt concentrations decreased organic contaminant removal rates in the MBR, the effluent still met the discharge limits for treating the olefin plant wastewater.     

Aquifer vulnerability assessment using GIS and fuzzy system: a case study in Tehran–Karaj aquifer,Iran

Aquifer vulnerability assessment techniques have been developed to predict which areas are more likely than others to become contaminated as a result of activities at or near the land surface. This research focuses on the evaluation of groundwater vulnerability to pollution in an urban area. Among several assessment methods, DRASTIC has been selected for this study. ArcGIS has been used to overlay and calculate different layers and obtain the vulnerability map. In order to show the importance of fuzzy algorithms in classification, both Boolean and fuzzy algorithms were used and compared. The fuzzy algorithm could recognize the areas with low and negligible vulnerability potentials whereas the Boolean model classified them as moderate. Two sensitivity tests, the map removal sensitivity analyses and single-parameter sensitivity analysis, were performed to show the importance of each parameter in the index calculation.     

Pre-processing data using wavelet transform and PCA based on support vector regression and gene expression programming for river flow simulation

An accurate estimation of flow using different models is an issue for water resource researchers. In this study, support vector regression (SVR) and gene expression programming (GEP) models in daily and monthly scale were used in order to simulate Gamasiyab River flow in Nahavand, Iran. The results showed that although the performance of models in daily scale was acceptable and the result of SVR model was a little better, their performance in the daily scale was really better than the monthly scale. Therefore, wavelet transform was used and the main signal of every input was decomposed. Then, by using principal component analysis method, important sub-signals were recognized and used as inputs for the SVR and GEP models to produce wavelet-support vector regression (WSVR) and wavelet-gene expression programming. The results showed that the performance of WSVR was better than the SVR in such a way that the combination of SVR with wavelet could improve the determination coefficient of the model up to 3% and 18% for daily and monthly scales, respectively. Totally, it can be said that the combination of wavelet with SVR is a suitable tool for the prediction of Gamasiyab River flow in both daily and monthly scales.     

Capability of vis-NIR spectroscopy and Landsat 8 spectral data to predict soil heavy metals in polluted agricultural land (Iran)

Heavy metals are toxic elements that have hazardous effect on the environment. They cause soil pollution as a result of their toxicity, potential reactivity, and mobility in soils. There are so many methods for the measurement of heavy metal concentrations in soils and aquatic systems. The traditional methods used for detecting heavy metal distribution in soil involve laboratory analysis and raster sampling. Both of them are expensive and time-consuming for large areas. Remote sensing techniques are used for obtaining the earth’s surface information, and these techniques have been used in the investigations of heavy metal distributions in preliminary analysis of soils as a rapid method. Today, near-infrared reflectance spectroscopy (NIRS) of soil characteristics has been of interest as a significant object. The present investigation is focused on the detection of heavy metals in contaminated soils by the application of reflectance spectroscopy in the spectral range of 350 to 2500 nm. This study also discusses the circumstances of the applied current methods for the detection and estimation of arsenic (As), cadmium (Cd), nickel (Ni), and lead (Pb) in contaminated agricultural soils. In the first part of laboratory spectroscopy, estimations were done using heavy metal reflectance spectroscopy and partial least square regression (PLSR) approaches, while in the second part, the heavy metal estimations were done using soil organic carbon reflectance spectroscopy through the PLSR approaches. Similar to the tasks above, estimations of As, Cd, Ni, and Pb by using Landsat 8 images were done in the forms of direct and indirect methods and the distribution of heavy metals in the study area was determined. Finally, the results obtained using direct and indirect methods were compared with the wet chemical measurements of heavy metals and organic carbon. It was found that although the direct detection of heavy metals using the images of Landsat 8 produced more accurate results than the indirect detections, the results obtained from laboratory spectroscopy corresponded more with the results from atomic adsorption spectroscopy. On the other hand, based on the fact that the soil has a complex content, the use of nonlinear methods, such as artificial neural networks in predicting soil heavy metal contents, could be regarded as a trusted method.     

Development of a new connection for precast concrete walls subjected to cyclic loading

The Industrialized Building System (IBS) was recently introduced to minimize the time and cost of project construction. Accordingly, ensuring the integration of the connection of precast components in IBS structures is an important factor that ensures stability of buildings subjected to dynamic loads from earthquakes, vehicles, and machineries. However, structural engineers still lack knowledge on the proper connection and detailed joints of IBS structure construction. Therefore, this study proposes a special precast concrete wall-to-wall connection system for dynamic loads that resists multidirectional imposed loads and reduces vibration effects (PI2014701723). This system is designed to connect two adjacent precast wall panels by using two steel U-shaped channels (i.e., male and female joints). During casting, each joint is adapted for incorporation into a respective wall panel after considering the following conditions: one side of the steel channel opens into the thickness face of the panel; a U-shaped rubber is implemented between the two channels to dissipate the vibration effect; and bolts and nuts are used to create an extension between the two U-shaped male and female steel channels. The developed finite element model of the precast wall is subjected to cyclic loads to evaluate the performance of the proposed connection during an imposed dynamic load. Connection performance is then compared with conventional connections based on the energy dissipation, stress, deformation, and concrete damage in the plastic range. The proposed precast connection is capable of exceeding the energy absorption of precast walls subjected to dynamic load, thereby improving its resistance behavior in all principal directions.     

Optimizing 3-D seismic survey design parameters using genetic algorithm—a case study in southwest of Iran

The crucial advantages of a 3-D seismic survey are the proper migration of the reflection points and the more accurate study on the structural and stratigraphic targets, reservoir characterization, and joint study. In this article we will focus on Pardis Project in southwest of Iran where no 3-D seismic survey has ever been carried out. The local geological information, previous 2-D seismic, VSP data, and interval velocity information obtained from check shots were taken into consideration to determine the requirements of the survey. The objective is to adequately sample the primary and secondary targets at the depth of 1,200 and 5,000 m, respectively. On the base of the logic dominating a genetic algorithm, the best operational layout was offered to satisfy the geophysical requirements looking forward to satisfy financial constraints. Using Genetic Algorithm Toolbox in MATLAB, we could formulate a mathematical constrained optimization problem. Applying this technique we derived nominal designs which are needed to be evaluated to make sure how well they could image the targets.     

The Use of Polyphenolic Compounds from Black Tea for the Solid Phase Extraction and Determination of Trace Iron in Drinking Water

A simple and selective solid phase extraction procedure for the trace analysis of iron(III) in water samples has been developed. Sodium dodecyl sulfate coated alumina, modified with polyphenolic compounds (extracted from black tea) was used for the extraction and preconcentration of iron(III) from water samples before determination by flame atomic absorption spectrometry. Due to the complexation reaction between iron(III) and polyphenol compounds, iron(III) was quantitatively extracted on the proposed sorbent and then eluted by 2.0 mL of HCl (1.0 mol/L). The effects of extraction parameters, such as pH and volume of sample solution, amount of polyphenolic compounds, type of eluting agent and the effect of interfering ions on the extraction of iron(III), were investigated. It was found that the proposed method had a good linear range (15.0–100.0 μg/L) and a low detection limit (10.0 μg/L). The procedure was successfully applied for iron determination in drinking water samples.