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.     

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...     

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...     

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.

     

Removal of antibiotics from aqueous solutions by nanoparticles: a systematic review and meta-analysis

Environmental Science and Pollution Research - Antibiotics, as one of the emerging pollutants, are non-biodegradable compounds and long-term exposure to them may affect endocrine, hormonal, and...     

Application of 1D and 2D MFR reactor technology for the isolation of insecticidal and anti-microbial properties from pyrolysis bio-oils

Valuable chemicals can be separated from agricultural residues by chemical or thermochemical processes. The application of pyrolysis has already been demonstrated as an efficient means to produce a liquid with a high concentration of desired product. The objective of this study was to apply an insect and microorganism bioassay-guided approach to separate and isolate pesticidal compounds from bio-oil produced through biomass pyrolysis. Tobacco leaf (Nicotianata bacum), tomato plant (Solanum lycopersicum), and spent coffee (Coffea arabica) grounds were pyrolyzed at 10°C/min from ambient to 565°C using the mechanically fluidized reactor (MFR). With one-dimensional (1D) MFR pyrolysis, the composition of the product vapors varied as the reactor temperature was raised allowing for the selection of the temperature range that corresponds to vapors with a high concentration of pesticidal properties. Further product separation was performed in a fractional condensation train, or 2D MFR pyrolysis, thus allowing for the separation of vapor components according to their condensation temperature. The 300–400°C tobacco and tomato bio-oil cuts from the 1D MFR showed the highest insecticidal and anti-microbial activity compared to the other bio-oil cuts. The 300–350 and 350–400°C bio-oil cuts produced by 2D MFR had the highest insecticidal activity when the bio-oil was collected from the 210°C condenser. The tobacco and tomato bio-oil had similar insecticidal activity (LC₅₀ of 2.1 and 2.2 mg/mL) when the bio-oil was collected in the 210°C condenser from the 300–350°C reactor temperature gases. The 2D MFR does concentrate the pesticidal products compared to the 1D MFR and thus can reduce the need for further separation steps such as solvent extraction.     

Optimal temporal scale for the correlation of AOD and ground measurements of PM2.5 in a real-time air quality estimation system

Aerosol optical depth (AOD), an indirect estimate of particulate matter using satellite observations, has shown great promise in improving estimates of PM_2.5 (particulate matter with aerodynamic diameter less than or equal to 2.5 μm) surface. Currently, few studies have been conducted to explore the optimal way to apply AOD data to improve the model accuracy of PM_2.5 in a real-time air quality system. We believe that two major aspects may be worthy of consideration in that area: 1) an approach that integrates satellite measurements with ground measurements in the estimates of pollutants and 2) identification of an optimal temporal scale to calculate the correlation of AOD and ground measurements. This paper is focused on the second aspect, identifying the optimal temporal scale to correlate AOD with PM_2.5. Five following different temporal scales were chosen to evaluate their impact on the model performance: 1) within the last 3 days, 2) within the last 10 days, 3) within the last 30 days, 4) within the last 90 days, and 5) the time period with the highest correlation in a year. The model performance is evaluated for its accuracy, bias, and errors based on the following selected statistics: the Mean Bias, the Normalized Mean Bias, the Root Mean Square Error, Normalized Mean Error, and the Index of Agreement. This research shows that the model with the temporal scale: within the last 30 days, displays the best model performance in a southern multi-state area centered in Mississippi using 2004 and 2005 data sets.