Bioaccumulation of trace elements in different tissues of three commonly available fish species regarding their gender,gonadosomatic index,and condition factor in a wetland ecosystem

In the present research, accumulation of Cd, Co, Cr, Cu, Mn, Ni, Pb, V, and Zn were determined in sediments and fillet, liver, kidney, gonads, and gills of three commonly fish species in the largest wetland ecosystem that is located in southwest of Iran; Shadegan wetland. Shadegan is one of the most important wetland that posses various fauna and flora but suffers inputs from agricultural and industrial activities. So, sediment samples and fish species including Barbus grypus, Barbus sharpeyi, and Cyprinus carpio were collected during winter 2009. Results showed that mean concentrations of trace elements (except Ni and Co) were high in liver and gills of B. grypus. Also trace elements had the most accumulation in liver of B. sharpeyi except for Cd (0.26 mg kg^− 1 d.w.) and Mn (13.45 mg kg^− 1 d.w.) that were high in gills. Beside, kidney is determined as target tissue for Ni and V in B. grypus and for Pb in C. carpio, due to their high concentration. Zn levels in all tissues of C. carpio showed the highest concentrations in comparison to other fish species. Generally, accumulations of most of the studied elements in B. grypus and B. sharpeyi were higher in females than in males, while in fillet and gonads of C. carpio, this trend was inverted. Bioaccumulation factors (BAFs) were determined for different tissues of fish species with respect to elemental concentrations in sediment. BAFs results indicated that Zn, Pb, and Cu have higher BAF than other elements. Also this investigation demonstrated that trace elements have different affinities with condition factor of studied fish species. Gonadosomatic index (GSI) and Pb showed positive correlation together in both B. sharpeyi and B. grypus, respectively, in females and males. Moreover, females of C. carpio showed significantly positive relation of GSI and all studied elements.     

Visitor impact on rocky shore communities of Qeshm Island, the Persian Gulf, Iran

The influence of visitors on macroinvertebrates of rocky intertidal shores was investigated in southern coasts of the Qeshm Island, the Persian Gulf, Iran. Qeshm Island located at the Strait of Hormuz, with an area of 1,491 km², is the largest island in the region. This island consists of a number of important natural habitat types including creeks, mangroves, corals, and sandy, muddy, and rocky shores that accommodate diverse marine flora and fauna communities. Two rocky shores were selected at the touristic beaches being visited regularly, and further two control locations selected at pristine shores. Intertidal macroinvertebrates were collected from six microhabitats including rock platforms, cobbles, boulders, crevices, sea walls, and rock pools during two different periods representing high and low tourist seasons. Species richness, density, and assemblage structure in heavily visited shores were compared with that of control locations. Striped barnacles (Balanus amphitrite) were present on platforms of all locations, thus the changes in their size were used as the obvious contrast associated with visitor’s impact. A total of 70 macroinvertebrate species from 11 phyla were recorded. Significant differences were detected in taxonomic richness, density, and assemblage structure of macroinvertebrates between heavily visited and pristine shores, suggesting that macroinvertebrates were adversely affected by visitors’ impact at heavily visited shores. The test of changes in species richness, density, and assemblage structure from high to low seasons yielded mixed results. The significant changes in density and assemblage structure from high to low seasons were only observed in one heavily visited shore. A significant reduction in size of striped barnacles was observed only in one heavily visited shore. The opportunistic or fugitive species (e.g., small macroalgae and barnacles) were dominant macroinvertebrates on heavily visited shores indicating early succession stage. The results presented here showed that macroinvertebrates were adversely affected by human activities in subtropical rocky shore.     

The effects of low frequency noise on mental performance and annoyance

Low frequency noise (LFN) as background noise in urban and work environments is emitted from many artificial sources such as road vehicles, aircraft, and air movement machinery including wind turbines, compressors, and ventilation or air conditioning units. In addition to objective effects, LFN could also cause noise annoyance and influence mental performance; however, there are no homogenous findings regarding this issue. The purpose of this research was to study the effects of LFN on mental performance and annoyance, as well as to consider the role of extraversion and neuroticism on the issue. This study was conducted on 90 students of Iran University of Medical Sciences (54 males and 36 females). The mean age of the students was 23.46 years (SD?=?1.97). Personality traits and noise annoyance were measured by using Eysenck Personality Inventory and a 12-scale self-reported questionnaire, respectively. Stroop and Cognitrone computerized tests measured mental performance of participants each exposed to 50 and 70 dBA of LFN and silence. LFNs were produced by Cool Edit Pro 2.1 software. There was no significant difference between mental performance parameters under 50 and 70 dBA of LFN, whereas there were significant differences between most mental performance parameters in quiet and under LFN (50 and 70 dBA). This research showed that LFN, compared to silence, increased the accuracy and the test performance speed (p?<?0.01). There was no association between LFN and noise annoyance (p?>?0.01). Introverts conducted the tests faster than extraverts (p?<?0.05). This research showed that neuroticism does not influence mental performance. It seems that LFN has increased arousal level of participants, and extraversion has a considerable impact on mental performance.     

Assessment of heavy metal enrichment in the offshore fine-grained sediments of the Caspian Sea

Sampling of the offshore seabed sediments of southwestern part of the Caspian Sea was carried out by gravity corer in order to study heavy metal concentration and the physicochemical factors controlling their distribution in the fine-grained fraction. The grain size distribution, amount, and type of clay minerals, total organic carbon (TOC) content, and Eh–pH of the sediments were determined. The average concentrations of the heavy metals in ppm are Mn (563), Cu (207.5), Sr (187), Zn (94), Pb (26.3), Ni (14.5), Co (11.5), Cd (2.56), and Ag (1.04) in their order of abundances. Co and Zn mostly indicate increase in silt-size fraction of the sediments suggesting their probable detrital provenance but the Mn, Ni, Cu, Sr, Pb, Cd, and Ag concentrations show a similar trend to distribution of the clay-size fraction. The concentrations of Mn, Co, and Cd increase with increase in the TOC content but the Cu, Pb, Ni, Ag, and Sr concentrations decrease with increase of the TOC content. The amounts of Zn, Cu, Sr, Pb, Cd, and Ag increase with increase in the CaCO₃ content. The calculated enrichment factor indicates that the sediments are very strong to extremely enriched in Ag, significantly enriched in Cu and Cd, and depleted to mineral for Pb, Sr, Co, Ni, and Zn. Variations of the Cu, Sr, Cd, Ag, and Pb concentrations are similar to the clay and CaCO₃ distributions.     

Developing a fuzzy neural network-based support vector regression (FNN-SVR) for regionalizing nitrate concentration in groundwater

The aim of this study is to develop a fuzzy neural network-based support vector regression model (FNN-SVR) for mapping crisp-input and fuzzy-output variables. In this model, an artificial neural network (ANN) estimator based on multilayer perceptron (MLP) is considered as the kernel function of the SVR, whereas asymmetric triangular fuzzy H-level sets are assumed for model parameters including weight and biases of the ANN model. A genetic algorithm (GA) with real coding is implemented to optimize the model parameters during the training phase. To evaluate the efficiency and applicability of the proposed model, it is applied for simulating and regionalizing nitrate concentration in Karaj Aquifer in Iran. The goodness-of-fit criteria indicate a better performance of the FNN-SVR compared to some benchmark models such as geostatistic techniques as well as traditional SVR models with linear, quadratic, polynomial, and Gaussian kernel functions for modeling nitrate concentrations in groundwater.     

Multi-response optimization of Fenton process for applicability assessment in landfill leachate treatment

Fenton process, as a pretreatment method, was found to be effective in the primary treatment of mature/medium landfill leachate. However, the main problem of the process is the large amount of produced sludge that requires an accurate feasibility evaluation for operational applications. In this study, the response surface methodology was applied for the modeling and optimization of Fenton process in three target responses, (1) overall COD removal, (2) sludge to iron ratio (SIR) and (3) organics removal to sludge ratio (ORSR), where the latter two were new self-defined responses for prediction of sludge generation and applicability assessment of the process, respectively. The effective variables included the initial pH, [H₂O₂]/[Fe²⁺] ratio and Fe²⁺ dosage. According to the statistical analysis, all the proposed models were adequate (with adjusted R² of 0.9116–0.9512) and had considerable predictive capability (with prediction R² up to 0.9092 and appropriate adequate precision). It was found that all the variables had significant effects on the responses, specifically by their observed role in dominant oxidation mechanism. The optimum operational conditions obtained by overlay plot, were found to be initial pH of 5.7, [H₂O₂]/[Fe²⁺] ratio of 17.72 and [Fe²⁺] of 195 mM, which led to 69% COD removal, 2.4 (l sludge/consumed mole Fe²⁺) of SIR and 16.5 (gCOD removed/l produced sludge) for ORSR in verification test, in accordance with models-predicted values. Finally, it was observed that [H₂O₂]/[Fe²⁺] ratio and Fe²⁺ dosage had significant influence on COD removal, while Fe²⁺ dosage and [H₂O₂]/[Fe²⁺] ratio had remarkable effects on SIR and ORSR responses, respectively.     

APPLICATION OF SELECTED SOIL LOSS EQUATIONS TO TRAMPLED SOIL CONDITIONS1

ABSTRACT: Soil loss prediction equations (Universal Soil Loss Equation, Modified Universal Soil Loss Equation, and Onstad-Foster Method) were modified to reflect the impact of trampling on soil erosion. The erosion control practice factor, P, was replaced by a trampling ratio, Tr, which is a function of the change in soil erosion due to animal trampling. Trampling impact on soil erosion varied With soil type. The data are a preliminary attempt to account for the impact of trampling on soil erosion.     

Solid phase extraction for evaluation of occupational exposure to Pb (II) using XAD-4 sorbent prior to atomic absorption spectroscopy.

Lead is an important constituent widely used in different industrial processes. For evaluation of workers' exposure to trace toxic metal of Pb (II), solid-phase extraction (SPE) was optimized. SPE using mini columns filled with XAD-4 resin was developed with regard to sample pH, ligand concentration, loading flow rate, elution solvent, sample volume, elution volume, the amount of resins, and sample matrix interferences. Lead ions were retained on a solid sorbent and then eluted, followed by a simple determination of analytes with flame atomic absorption spectrometery. The obtained recoveries of metal ions were greater than 92%. This method was validated with 3 different pools of spiked urine samples; it showed a good reproducibility over 6 consecutive days as well as 6 within-day experiments. This optimized method can be considered successful in simplifying sample preparation for a trace residue analysis of lead in different matrices when evaluating occupational and environmental exposures is required.     

AHP based life cycle sustainability assessment (LCSA) framework: a case study of six storey wood frame and concrete frame buildings in Vancouver

Construction and building industry is in dire need for developing sustainability assessment frameworks that can evaluate and integrate related environmental and socioeconomic impacts. This paper discusses an analytic hierarchy process (AHP) based sustainability evaluation framework for mid-rise residential buildings based on a broad range of environmental and socioeconomic criteria. A cradle to grave life cycle assessment technique was applied to identify, classify, and assess triple bottom line (TBL) sustainability performance indicators of buildings. Then, the AHP was applied to aggregate the impacts into a unified sustainability index. The framework is demonstrated through a case study to investigate two six storey structural systems (i.e. concrete and wood) in Vancouver, Canada. The results of this paper show that the environmental performance of a building in Canada, even in regions with milder weather such as Vancouver, is highly dependent on service life energy, rather than structural materials.