Simultaneous spectrophotometric determination of crystal violet and malachite green in water samples using partial least squares regression and central composite design after preconcentration by dispersive solid-phase extraction

In this paper, a simple, fast, and inexpensive method is introduced for the simultaneous spectrophotometric determination of crystal violet (CV) and malachite green (MG) contents in aquatic samples using partial least squares regression (PLS) as a multivariate calibration technique after preconcentration by graphene oxide (GO). The method was based on the sorption and desorption of analytes onto GO and direct determination by ultraviolet–visible spectrophotometric techniques. GO was synthesized according to Hummers method. To characterize the shape and structure of GO, FT-IR, SEM, and XRD were used. The effective factors on the extraction efficiency such as pH, extraction time, and the amount of adsorbent were optimized using central composite design. The optimum values of these factors were 6, 15 min, and 12 mg, respectively. The maximum capacity of GO for the adsorption of CV and MG was 63.17 and 77.02 mg g^?1, respectively. Preconcentration factors and extraction recoveries were obtained and were 19.6, 98% for CV and 20, 100% for MG, respectively. LOD and linear dynamic ranges for CV and MG were 0.009, 0.03–0.3, 0.015, and 0.05–0.5 (μg mL^?1), respectively. The intra-day and inter-day relative standard deviations were 1.99 and 0.58 for CV and 1.69 and 3.13 for MG at the concentration level of 50 ng mL^?1, respectively. Finally, the proposed DSPE/PLS method was successfully applied for the simultaneous determination of the trace amount of CV and MG in the real water samples.     

Examining Relationships Between Socioeconomic Factors and Landscape Metrics in the Southern Basin of the Caspian Sea

Socioeconomic forces are not only among the main drivers of landscape dynamics; they are also influenced by landscape patterns. Landscape structure and functions are closely related to natural and social factors. The objective of this study was to investigate the relationships among some human-related factors and landscape ecological metrics as landscape pattern indicators and to identify suitable metrics for modeling these relationships. To this goal, landscape ecological metrics were calculated for each of the 32 counties of Mazandaran and Guilan provinces located in the southern basin of the Caspian Sea using land use/cover maps in class level. Stream network metrics were calculated using a digital elevation model, road density metrics were calculated using map of main roads separately, and significant metrics were selected according to results of correlation tests and factor analysis. The correlations between these metrics and socioeconomic factors were tested, and their relationships were modeled with multiple linear regressions. Significant relationships were found among socioeconomic factors and landscape ecological metrics, and land use/cover data are applicable for modeling socioeconomic factors, especially demographic and employment structure factors. Among the landscape metrics applied in this study, road density, mean patch size, mean nearest neighbor distance, and percentage of a land use/cover class in landscape were important metrics for predicting socioeconomic factors. Our findings indicated that road density metric and percentages of urban class are useful for predicting urban socioeconomic factors and percentage of agriculture and forest classes in the landscape are suitable metrics for predicting rural socioeconomic factors.     

The potential use of ultrasound-assisted bleaching in removing heavy metals and pigments from soybean oil using kinetic,thermodynamic and equilibrium modeling

Environmental Science and Pollution Research - In this research, the sorption behavior (kinetic, isotherm, and thermodynamic modeling) of heavy metals (Cu (II) and Fe (II)) and pigments (carotenoid...     

Heavy metal concentration in sediment, benthic, benthopelagic, and pelagic fish species from Musa Estuary (Persian Gulf)

The concentration of Cd, Co, Cu, Ni, and Pb was measured in sediment and three fish species collected from Musa Estuary, Persian Gulf. The concentration order of heavy metals in sediment were Ni > Co > Cu > Pb > Cd >. Concentrations of the heavy metals in the fish were apparently different among the three species. The concentrations of Cd and Ni in fish were Johnius belangerii > Euryglossa orientalis > Liza abu, while the Co and Cu levels were L. abu > E. orientalis > J. belangerii and E. orientalis > L. abu > J. belangerii, respectively. Result of regression analysis showed that there were no significant relationships between metal concentration in fish tissues and sediment, except for Ni concentration in the J. belangerii liver. The concentrations of studied metals in fish muscle were below the permissible limits proposed by FAO, WHO, and EC.     

Simultaneous monitoring of SARS-CoV-2, bacteria,and fungi in indoor air of hospital: a study on Hajar Hospital in Shahrekord,Iran

The novel SARS-CoV-2 outbreak was declared as pandemic by the World Health Organization (WHO) on March 11, 2020. Understanding the airborne route of SARS-CoV-2 transmission is essential for infection prevention and control. In this study, a total of 107 indoor air samples (45 SARS-CoV-2, 62 bacteria, and fungi) were collected from different wards of the Hajar Hospital in Shahrekord, Iran. Simultaneously, bacterial and fungal samples were also collected from the ambient air of hospital yard. Overall, 6 positive air samples were detected in the infectious 1 and infectious 2 wards, intensive care unit (ICU), computed tomography (CT) scan, respiratory patients’ clinic, and personal protective equipment (PPE) room. Also, airborne bacteria and fungi were simultaneously detected in the various wards of the hospital with concentrations ranging from 14 to 106 CFU m^?3 and 18 to 141 CFU m^?3, respectively. The highest mean concentrations of bacteria and fungi were observed in respiratory patients’ clinics and ICU wards, respectively. Significant correlation (p < 0.05) was found between airborne bacterial concentration and the presence of SARS-CoV-2, while no significant correlation was found between fungi concentration and the virus presence. This study provided an additional evidence about the presence of SARS-CoV-2 in the indoor air of a hospital that admitted COVID-19 patients. Moreover, it was revealed that the monitoring of microbial quality of indoor air in such hospitals is very important, especially during the COVID-19 pandemic, for controlling the nosocomial infections.

     

Removal of chromate ions from leachate-contaminated groundwater samples of Khan Chandpur,India, using chitin modified iron-enriched hydroxyapatite nanocomposite

Environmental Science and Pollution Research - Chromite ore processing residues (COPR) are real environmental threats, leading to CrO42-, i.e., Cr (VI) leaching into groundwater. It is of serious...     

Biodegradable Nanocomposite Film Based on Gluten/Silica/Calcium Chloride: Physicochemical Properties and Bioactive Compounds Extraction Capacity

Journal of Polymers and the Environment - In this study, a biodegradable wheat gluten (WG) film containing calcium chloride and nano silica (WG/CaCl2/SiO2) was prepared and the physicochemical...     

Application of quadratic regression model for Fenton treatment of municipal landfill leachate

The effectiveness of Fenton process in municipal landfill leachate treatment, as a pre- or post-treatment approach, has been demonstrated. However, no general recommendations of universal validity could be made in the term of optimized conditions affecting Fenton process. At the first stage of this study, collected leachate samples from Aradkooh site, Tehran, Iran, were investigated using one-factor-at-a-time method to find out optimum coagulation pH and flocculation time values. Subsequently, the obtained results in addition to data issued previously by the authors were employed to develop a predictive model of the true response surface, namely chemical oxygen demand (COD) removal efficiency. Finally, the main parameters of Fenton procedure, i.e. initial pH, [H(2)O(2)]/[Fe(2+)] molar ratio, Fe(2+) dosage, and coagulation pH were optimized taking advantage of the above-mentioned quadratic model. The derived second-order model included both significant linear and quadratic terms and seemed to be adequate in predicting responses (R(2)=0.9896 and prediction R(2)=0.6954). It was found that the interaction between initial pH and Fe(2+) dosage has a significant effect on COD removal. While, the optimal [H(2)O(2)]/[Fe(2+)] molar ratio was independent of ferrous ion dosage. The optimum conditions for the maximum COD removal of 50.76% for the parameters of initial pH, [H(2)O(2)]/[Fe(2+)] molar ratio, Fe(2+) dosage, and coagulation pH were found to be 5.8, 8.0, 22,500mg/L, and 8.7 respectively.