Impact of green trust and green perceived quality on green purchase intentions: a moderation study

Environment, Development and Sustainability - The current study explores the role of green trust, green perceived risk and green perceived quality in changing green purchase intention....     

Investigating the quantitative and qualitative status of effluent in the wastewater treatment plant in Iran Central Iron Ore

The aim of present study was to investigate the quality of the produced effluent from different units of the Iran Central Iron Ore in Bafq city and comparison of effluent with the standards. This study presents the physicochemical and biological parameters data of effluent of three Sequencing batch reactors (SBR) with a capacity of 160 m³?d^?1. Most common parameters include pH, total suspended solids (TSS), total nitrogen (TN), total phosphorus (TP), biochemical oxygen demand (BOD₅), chemical oxygen demand (COD), heavy metals, and total coliforms and fecal coliforms as biological indicators. Then, for each SBR system, the average of each parameter was determined, and results were compared with the standard recommended by the Iranian Environmental Protection Agency. Based on the results, some of the parameters, including BOD₅, COD, and TSS in the wastewater treatment plant (WWTP) effluent, are higher than the permitted amount for discharge to the surface water. Considering the BOD₅, COD, and TSS concentration in WWTPs, the treated wastewater is only suitable for agricultural and irrigation use. Therefore, wastewater produced by Iran Central Iron Ore Co. will need additional treatment to achieve standard quality of water before discharge in surface water and adsorbent well.     

Application of polyamide thin-film composite layered on polysulfone-GO/TiO2 mixed matrix membranes for removal of nitrotoluene derivatives from petrochemical wastewaters

Release of harmful organic intermediates or byproducts during the manufacture of petrochemical compounds is a serious problem in petrochemical plants. In this work, polysulfone membranes blended with GO/TiO₂ nanocomposite were synthesized by phase inversion method and coated with a polyamide layer formed by interfacial polymerization to prepare a thin-film composite (TFC) sample. Analysis and characterization of the sample were carried out by XRD, FE-SEM, BET, FTIR/ATR, AFM, TGA, and zeta potential. Results indicated that incorporation of GO/TiO₂ into the membrane structure enhanced porosity, surface roughness, and macrovoid formation along the cross-section of the sublayer and permeability of the membrane. The TFC membranes were applied to remove mononitrotoluene (MNT) and dinitrotoluene (DNT) as the basic intermediates of toluene diisocyanate (TDI). The membranes demonstrated high efficiency (>?90%) for the removal of MNT and DNT according to the charge exclusion mechanism and Donnan effect. Application of the TFC membrane for treatment of wastewater in the TDI plant showed that the removal of pollutants is variable in the range of 45–65% and 53–69% for the membrane with the highest flux and highest rejection in different transmembrane pressure, respectively.

     

CYP1A1 and GSTs common gene variations and presbycusis risk: a genetic association analysis and a bioinformatics approach

Environmental Science and Pollution Research - Antioxidant enzymes such as glutathione S-transferases (GSTs) and cytochromes P450 (CYPs) are involved in the metabolism and detoxification of...     

Magnetic nanoparticles incorporation into different substrates for dyes and heavy metals removal—A Review

Environmental Science and Pollution Research - Substantial discharge of hazardous substances, especially dyes and heavy metal ions to the environment, has become a global concern due to...     

Behavioral intentions toward genetically modified crops in Southwest Iran: a multi-stakeholder analysis

This study examined the influencing factors of the self-reported behavioral intentions toward genetically modified (GM) crops using a multi-stakeholder approach in the Khuzestan Province in Southwest Iran. The study focused on three different groups, including: “agricultural students,” “agricultural private firms’ managers” and “rich-resource farmers.” Data were collected using a researcher-made questionnaire and was analyzed by SPSS (V20) and AMOS (V20). Results indicated that the respondents perceive more benefits than risks for GM crops and that the perception of benefits and risks, respectively, had positive and negative impacts on the self-reported behavioral intention of the respondents. The knowledge of the respondents regarding these crops had positive impacts on perception of benefits. The results showed that both managers and students worried about the food safety and impact of GM crops on human health while farmers worried about the environmental risks of GM crops. The results also revealed that those who are the most conscious about GM crops are more trusted. The findings also showed that the majority of the respondents hold a positive view of the potential of GM crops.     

Making spatial development scenario for south of Bushehr province,Iran, based on strategic foresight

In recent years, the science of foresight has been entered into planning activities by urban and regional planners and this science has impacted on planning activities. This study discusses spatial development in the south of Bushehr province using the foresight approach. The general aim of this research is to compile scenarios for the development of the mentioned study area which comprises the southern part of Bushehr province including four counties of Dayyer, Jam, Kangan and Asaluyeh. The main reason for selecting this region is their direct impressibility by major changes in the country’s oil and gas industry. This research has extremely made use of the Delphi and cross-impact analysis methods to develop foresight scenarios. Using the Delphi method, 30 initial factors were identified in the economic, political-security, linkages, science and technology, manufacturing, natural, social, infrastructural and residential issues and then the cross-impact matrix was used to investigate the impact of factors on each other. In the next step, the ranking of direct and indirect factors was determined by Micmac software and on this basis, the final refining in the selection of drivers was done. In the final stage, axes of future scenarios were presented and then the future scenarios were drawn. Results of this research indicate that two main drivers namely Iran’s international relations and energy resources are the main axes of scenarios. These two drivers have more uncertainty and higher importance than other factors and the results in four scenarios showing the possibility of each situation’s occurrence.     

Linear and non-linear relationships mapping the Henry’s law parameters of organic pesticides

This work aims to predict the air to water partitioning for 96 organic pesticides by means of the Quantitative Structure–Property Relationships Theory. After performing structural feature selection with Genetics Algorithms and Replacement Method linear approaches, it is found that among the most important molecular features appears the Moriguchi octanol–water partition coefficient, and higher lipophilicities would lead to compounds having higher Henry’s law constants. We also compare the statistical performance achieved by four fully-connected Feed-Forward Multilayer Perceptrons Artificial Neural Networks. The statistical results found reveal that the best performing model uses the Levenberg–Marquardt with Bayesian regularization (BR) weighting function for achieving the most accurate predictions.     

Decolouration of azo dyes by <Emphasis Type="Italic">Phanerochaete chrysosporium</Emphasis> immobilised into alginate beads

Background, aim and scope  

Because of high discharged volumes and effluent composition, wastewater from the textile industry can be considered as the most polluting amongst all industrial sectors, thus greatly requiring appropriate treatment technologies. Although some abiotic methods for the reduction of several dyes exist, these require highly expensive catalysts and reagents. Biotechnological approaches were proven to be potentially effective in the treatment of this pollution source in an eco-efficient manner. The white-rot fungi are, so far, the most efficient microorganisms in degrading synthetic dyes. This white-rot fungi’s property is due to the production of extracellular lignin-modifying enzymes, which are able to degrade a wide range of xenobiotic compounds because of their low substrate specificity. In this paper, we studied the ability of the white-rot fungus Phanerochaete chrysosporium immobilised into Ca-alginate beads to decolourise different recalcitrant azo dyes such as Direct Violet 51 (DV), Reactive Black 5 (RB), Ponceau Xylidine (PX) and Bismark Brown R (BB) in successive batch cultures. To the best of our knowledge, this is the first study on the immobilisation of P. chrysosporium into Ca-alginate beads for its application in dye decolouration.