Remarkable adsorption of hydroquinone as an anion contaminant by using the magnetic supported bimetallic (NiCu-MOF@MAC) nanocomposites in aqueous solutions.

The purposes of this work were to synthesize the core-shell magnetic and nonmagnetic supported bimetallic metal-organic frameworks (MOFs) on the walnut-based activated carbon by the facile preparation method to investigate the feasibility of the performance adsorption of hydroquinone in the aqueous solutions. Activated carbon as a substrate and nickel, copper, and trimesic acid were employed in the structure of the prepared MOFs. The adsorbents were characterized by XRD, FTIR, FESEM, EDX, TEM, BET, and VSM analysis. The goethite and magnetite phases were detected in the morphology of the magnetic adsorbent as confirmed by the XRD pattern. Increases in the pH value from 6 and the adsorption temperature led to a lower adsorption capacity of the samples. The maximum adsorption capacity for the well-dispersed nanoparticles of magnetic (NiCu-MOF@MAC and nonmagnetic (NiCu-MOF@AC) was calculated to be 303.03 and 454.54 mg/g by using linear Langmuir isotherm as an appropriate model, respectively. The achievements from the reusability evaluation illustrated that the magnetic bimetallic MOF nanocomposite could successfully be applied to remove hydroquinone from the wastewater on an industrial scale. The kinetic experimental data was in good agreement with the pseudo-second-order model.

Air pollution-related asthma profiles among children/adolescents: A multi-group latent class analysis.

BACKGROUND: This study aimed to investigate the asthma profile among children/adolescents and the relationship of the prevalence of air pollution profiles using latent class analysis (LCA). OBJECTIVES: In this cross-sectional study, a case rural community was selected in an industrial area, and two rural control communities were selected in unexposed areas. METHODS: Hourly concentrations of PM10, SO2, NO2, and total volatile organic compounds were obtained from the records of a fixed air quality monitoring station, and the concentrations of benzene, toluene, xylenes styrene were measured during six campaigns. Asthma data was collected using the International Study of Asthma and Allergies in Childhood in 7-18 years old children/adolescents. The modeling was conducted using LCA. RESULTS: A higher amount of air pollution indices were observed in the case than both control communities. LCA divided the participants into three clusters; "healthy" (92.8%), "moderate" (2.8%), and "severe" (4.4%). A higher probability of severe asthma (6.8%) was observed in the case than control communities (2.6% and 1.8%). Additionally, after adjusting for possible confounders, the odds of asthma was lower in the control communities than the case in both moderate and sever classes (Odds Ratios in the range of 0.135-0.697). CONCLUSIONS: This study indicates asthma profiles of children/adolescents and the higher prevalence of severe class in the area, explaining the possible effect of air pollution.

The implementation of data reconciliation for evaluating a full-scale petrochemical wastewater treatment plant.

Data reconciliation and mass balance analysis were conducted for the first time to improve the data obtained from a petrochemical wastewater treatment plant (WWTP), and the results were applied to evaluate the performance of the plant. Daily average values for 209 days from the inlet and outlet of the plant obtained from WWTP documentation center along with the results of four sampling runs in this work were used for data reconciliation and performance evaluation of the plant. Results showed that standard deviation and relative errors in the balanced data of each measurement decreased, especially for the process wastewater from 24.5 to 8.6 % for flow and 24.5 to 1.5 % for chemical oxygen demand (COD). The errors of measured data were -137 m3/day (-4.41 %) and 281 kg/day (7.92 %) for flow and COD, respectively. According to the balanced data, the removal rates of COD and 5-day biological oxygen demand (BOD5) through the aeration unit were equal to 37 and 46 %, respectively. In addition, the COD and BOD5 concentrations were reduced by about 61.9 % (2137 kg/day) and 78.1 % (1976 kg/day), respectively, prior to the biological process. At the same time, the removal rates of benzene, toluene, and styrene were 56, 38, and 69 %, respectively. The results revealed that about 40 % of influent benzene (75.5 kg/day) is emitted to the ambient air at the overhead of the equalization basin. It can be concluded that the volatilization of organic compounds is the basic mechanism for the removal of volatile organic compounds (VOCs) and it corresponds to the main part of total COD removal from the WWTP.

Optimal Design of Air Quality Monitoring Network and its Application in an Oil Refinery Plant: An Approach to Keep Health Status of Workers.

BACKGROUND: Industrial air pollution is a growing challenge to humane health, especially in developing countries, where there is no systematic monitoring of air pollution. Given the importance of the availability of valid information on population exposure to air pollutants, it is important to design an optimal Air Quality Monitoring Network (AQMN) for assessing population exposure to air pollution and predicting the magnitude of the health risks to the population. METHODS: A multi-pollutant method (implemented as a MATLAB program) was explored for configur-ing an AQMN to detect the highest level of pollution around an oil refinery plant. The method ranks potential monitoring sites (grids) according to their ability to represent the ambient concentration. The term of cluster of contiguous grids that exceed a threshold value was used to calculate the Station Dosage. Selection of the best configuration of AQMN was done based on the ratio of a sta-tion's dosage to the total dosage in the network. RESULTS: Six monitoring stations were needed to detect the pollutants concentrations around the study area for estimating the level and distribution of exposure in the population with total network efficiency of about 99%. An analysis of the design procedure showed that wind regimes have greatest effect on the location of monitoring stations. CONCLUSION: The optimal AQMN enables authorities to implement an effective program of air quality management for protecting human health.

Quality modeling of drinking groundwater using GIS in rural communities, northwest of Iran.

Given the importance of groundwater resources in water supply, this work aimed to study quality of drinking groundwater in rural areas in Tabriz county, northwest of Iran. Thirty two groundwater samples from different areas were collected and analyzed in terms of general parameters along with 20 heavy metals (e.g. As, Hg and …). The data of the analyses were applied as an attribute database for preparing thematic maps and showing water quality parameters. Multivariate statistical techniques, including principal component analysis (PCA) and hierarchical cluster analysis (CA) were used to compare and evaluate water quality. The findings showed that hydrochemical faces of the groundwater were of calcium-bicarbonate type. EC values were from 110 to 1750 µs/cm, in which concentration of salts was high in the east and a zone in north of the studied area. Hardness was from 52 to 476 mg/l and CaCO3 with average value of 185.88 ± 106.56 mg/L indicated hard water. Dominant cations and anions were Ca(2+) > Na(+) > Mg(2+) > K(+) and HCO3 (-) > Cl(-) > SO4 (2-) > NO3 (2), respectively. In the western areas, arsenic contamination was observed as high as 69 µg/L. Moreover, mercury was above the standard level in one of the villages. Eskandar and Olakandi villages had the lowest quality of drinking water. In terms of CA, sampling sites were classified into four clusters of similar water quality and PCA demonstrated that 3 components could cover 84.3% of the parameters. For investigating arsenic anomaly, conducting a comprehensive study in the western part of studied area is strongly recommended.

The simultaneous removal of calcium, magnesium and chloride ions from industrial wastewater using magnesium-aluminum oxide.

In this article, a method for simultaneous removal of calcium, magnesium and chloride by using Mg0.80Al0.20O1.10 as a Magnesium-Aluminum oxide (Mg‒Al oxide) was investigated. Mg‒Al oxide obtained by thermal decomposition of the Mg-Al layered double hydroxide (Mg-Al LDH). The synthesized Mg‒Al oxide were characterized with respect to nitrogen physicosorption, X-ray diffraction (XRD) and field emission scan electron microscopy (FESEM) morphology. Due to high anion-exchange capacity of Mg‒Al oxide, it was employed in simultaneously removal of Cl(-), Mg(+2) and Ca(+2) from distiller waste of a sodium carbonate production factory. For this purpose, experiments were designed to evaluate the effects of quantity of Mg‒Al oxide, temperature and time on the removal process. The removal of Cl(-), Mg(+2) and Ca(+2) from wastewater was found 93.9%, 93.74% and 93.25% at 60°C after 0.5 h, respectively. Results showed that the removal of Cl(-), Mg(+2) and Ca(+2) by Mg‒Al oxide increased with increasing temperature, time and Mg‒Al oxide quantity.

Synthesis and physicochemical characterizations of nanostructured Pt/Al2O3-CeO2 catalysts for total oxidation of VOCs.

Pt/Al(2)O(3)-CeO(2) nanocatalysts with Pt loading of 1% and ceria loading of 10, 20 and 30% were successfully prepared via wet impregnation method to be utilized in catalytic oxidation of BTX. The nanocatalysts were characterized using XRD, FESEM, TEM, N(2) adsorption, FTIR and TPR-H(2) techniques. The XRD patterns confirmed the formation of cerium oxide as the crystalline phase on alumina with the average crystallite size of 8.1-8.7 nm, derived by Scherrer equation. FESEM images confirmed that these nanocatalysts had ceria particles in nano-ranges. TEM analysis showed that platinum particles were fairly well dispersed on Al(2)O(3)-CeO(2) with an average size of 5-20 nm. BET surface area presented large surface area for nanocatalysts. TPR patterns showed that by adding 1% platinum to support, the reducibility is highly increased. These patterns also revealed the promoting effect of ceria on reducibility of Pt and Al(2)O(3). The results of toluene oxidation indicated that the synthesized nanocatalysts were highly active and able to remove nearly 100% of toluene and xylene and about 85% of benzene as representative VOCs. The presence of nanoparticles along with good characteristics of the synthesized nanocatalysts presented them as highly efficient materials for catalytic oxidation of VOCs.