A review on bisphenol A occurrences,health effects and treatment process via membrane technology for drinking water

Massive utilization of bisphenol A (BPA) in the industrial production of polycarbonate plastics has led to the occurrence of this compound (at μg/L to ng/L level) in the water treatment plant. Nowadays, the presence of BPA in drinking water sources is a major concern among society because BPA is one of the endocrine disruption compounds (EDCs) that can cause hazard to human health even at extremely low concentration level. Parallel to these issues, membrane technology has emerged as the most feasible treatment process to eliminate this recalcitrant contaminant via physical separation mechanism. This paper reviews the occurrences and effects of BPA toward living organisms as well as the application of membrane technology for their removal in water treatment plant. The potential applications of using polymeric membranes for BPA removal are also discussed. Literature revealed that modifying membrane surface using blending approach is the simple yet effective method to improve membrane properties with respect to BPA removal without compromising water permeability. The regeneration process helps in maintaining the performances of membrane at desired level. The application of large-scale membrane process in treatment plant shows the feasibility of the technology for removing BPA and possible future prospect in water treatment process.     

Extreme learning machines: a new approach for modeling dissolved oxygen (DO) concentration with and without water quality variables as predictors

In this paper, several extreme learning machine (ELM) models, including standard extreme learning machine with sigmoid activation function (S-ELM), extreme learning machine with radial basis activation function (R-ELM), online sequential extreme learning machine (OS-ELM), and optimally pruned extreme learning machine (OP-ELM), are newly applied for predicting dissolved oxygen concentration with and without water quality variables as predictors. Firstly, using data from eight United States Geological Survey (USGS) stations located in different rivers basins, USA, the S-ELM, R-ELM, OS-ELM, and OP-ELM were compared against the measured dissolved oxygen (DO) using four water quality variables, water temperature, specific conductance, turbidity, and pH, as predictors. For each station, we used data measured at an hourly time step for a period of 4 years. The dataset was divided into a training set (70%) and a validation set (30%). We selected several combinations of the water quality variables as inputs for each ELM model and six different scenarios were compared. Secondly, an attempt was made to predict DO concentration without water quality variables. To achieve this goal, we used the year numbers, 2008, 2009, etc., month numbers from (1) to (12), day numbers from (1) to (31) and hour numbers from (00:00) to (24:00) as predictors. Thirdly, the best ELM models were trained using validation dataset and tested with the training dataset. The performances of the four ELM models were evaluated using four statistical indices: the coefficient of correlation (R), the Nash-Sutcliffe efficiency (NSE), the root mean squared error (RMSE), and the mean absolute error (MAE). Results obtained from the eight stations indicated that: (i) the best results were obtained by the S-ELM, R-ELM, OS-ELM, and OP-ELM models having four water quality variables as predictors; (ii) out of eight stations, the OP-ELM performed better than the other three ELM models at seven stations while the R-ELM performed the best at one station. The OS-ELM models performed the worst and provided the lowest accuracy; (iii) for predicting DO without water quality variables, the R-ELM performed the best at seven stations followed by the S-ELM in the second place and the OP-ELM performed the worst with low accuracy; (iv) for the final application where training ELM models with validation dataset and testing with training dataset, the OP-ELM provided the best accuracy using water quality variables and the R-ELM performed the best at all eight stations without water quality variables. Fourthly, and finally, we compared the results obtained from different ELM models with those obtained using multiple linear regression (MLR) and multilayer perceptron neural network (MLPNN). Results obtained using MLPNN and MLR models reveal that: (i) using water quality variables as predictors, the MLR performed the worst and provided the lowest accuracy in all stations; (ii) MLPNN was ranked in the second place at two stations, in the third place at four stations, and finally, in the fourth place at two stations, (iii) for predicting DO without water quality variables, MLPNN is ranked in the second place at five stations, and ranked in the third, fourth, and fifth places in the remaining three stations, while MLR was ranked in the last place with very low accuracy at all stations. Overall, the results suggest that the ELM is more effective than the MLPNN and MLR for modelling DO concentration in river ecosystems.     

Floating roof storage tank boilover

Storage tanks are important facilities for the major hazard installations (MHIs) to store large quantity of crude oil. There is several fire types can occur with large diameter open top floating roof storage tanks. Boilover is considered one of the most dangerous fires in large-scale oil tank. The world has witnessed many incidents due to boilover in floating roof storage tank. Boilover problem has been studied in experiments and by models to understand how to control the boilover phenomena. An experimental study has been carried out in Jebel Dhanna (JD) terminal area by Abu Dhabi Company for Onshore Oil Operations (ADCO) with support of Resource Protection International (RPI) consultant. 2.4 m diameter and 4.5 m diameters pans have been used to study the characteristics of the large oil-tank fires (i) to gain more knowledge of the boilover phenomenon of crude oil (ii) verify if the crude oil stored by ADCO would boilover (ii) estimation of rate of hot-zone growth and the period needed from ignition to boilover (iii) estimation of radiant heat and consequences of boilover. This paper presents an overview on the floating roof storage tank boilover. The paper also presents briefly boilover experimental research study carried out by ADCO.     

Ethnobotanical survey about medicinal plants used in traditional treatment of insomnia,asthenia, and oral and gum infections in the region Fez-Meknes,Morocco

Environmental Science and Pollution Research - An ethnobotanical survey was conducted among herbalists in the north-central region of Morocco using a questionnaire in order to highlight knowledge...     

Statistical modeling and response surface optimization on natural weathering of wood–plastic composites with calcium carbonate filler

Journal of Material Cycles and Waste Management - An experimental mixture design was used to determine the optimum composition of wood–plastic composites (WPCs), manufactured from recycled...     

Age at first marriage and its relation to fertility in Bangladesh

The 2007 Bangladesh Demographic and Health Survey(BDHS)data are exploited to examine the effects of socioeconomic and demographic factors on age at first marriage linkage to reproductive behavior of Bangladeshi women.The mean age at first marriage of women is found to be 15.48 years.Multivariate logistic regression technique shows that place of residence,religion,region,wealth index,education,and occupation are significantly important factors for determining age at first marriage.The relationship between marriage and fertility suggests that women who marry at a younger age produce more children than women who marry late.Findings of this study show that if the age at first marriage of adolescents is increased by 1 year,the age at first birth is postponed by 0.728 years.With the increase in age at first marriage,the fecundability of women sharply rises,whereas the proportion of temporary sterility decreases.Although there is a positive association between age at first marriage and age-specific marital fertility rates,the total parity per woman at the end of the reproductive period is expected to reduce by 0.196 for each 1-year delayed marriage.     

Changes in water-extractability of soil inorganic phosphate induced by chloride and sulfate salts

GOAL, SCOPE AND BACKGROUND: One of the principal experimental variables which effect the results of phosphorus (P) sorption studies is the ionic composition, in addition to both species and concentrations of the contacting solution. In spite of the realization that ionic species, concentrations and their compositions effect P sorption and/or desorption, most of the salt-related studies are confined to Cl- (anion) in association with different cations. While the knowledge about the comparative response of P to Cl- and SO4(2-) ions was lacking, the current study was conducted to evaluate the comparative effects of anions (in association with cations) on inorganic P release and P fractions in the soil. METHODS: The test soil was amended with livestock compost manure (OP); KH2PO4 (IPk) or Ca(H2PO4)2 (IPc) at a rate of 1ppm. Soil was subjected to one salt and nine subsequent water extractions and different P fractions were measured. Four salt types, NaCl, Na2SO4, KCl and K2SO4, were used at levels of 0.5 M. RESULTS: Irrespective of P sources, P release was substantially increased in the salt-pretreated soil as compared to the non-saline soil. Sulfate salts released more P in subsequent water extractions than Cl-. Phosphorus release decreased for salt types with Na2SO4 > NaCl > K2SO4 > KCl and for P sources with OP approximately IPk > Control (without P application) > IPc, respectively. DISCUSSION: No previous study was found to compare the results of more P release by SO4(2-) than Cl- salt. Most of the previous studies focused on anion sorption capacities, but the mechanism for their adsorption is not fully known. Most of the authors suggested that the mechanisms of SO4(2-) and PO4(3-) adsorption are similar, and that both ions compete for the same sorption sites (Kamprath et al. 1956, Couto et al. 1979, Pasricha and Fox 1993). Although adsorbed SO4(2-) does not compete strongly with PO4(3-), there is likely to be some competition for sorption between these anions which may cause comparatively more P release by SO4(2-) than Cl- salts. Higher P release by Na-saturation could be due to the release of P associated with oxide surfaces or due to dissolution of Ca-P phases (Curtin et al. 1987). CONCLUSIONS: Study clearly showed that not only cations species differ for P desorption capacity, but associated anions also play a vital role in the fate of P under saline environments. Synergetic effects exist between Na and SO4(2-) ions which enhanced the P release. This study has also confirmed the fact that P from organic sources is available as well as from inorganic P sources. However, P release depends more on the type of P source applied than on total P. RECOMMENDATIONS AND PERSPECTIVES: It is highly recommended that more than one anion species must be used in the research plans for evaluating the P response in a saline environment. The results have important implications from the point of view of research, as most of the researchers focus on different cations only for evaluating P response to salts from an environmental point of view. However, our study has made it clear that anions in association with cations differed for their effects on P release.     

Income inequality,ecological footprint,and carbon dioxide emissions in Asian developing economies: what effects what and how?

The reduction of income inequality and environmental vulnerability is the most important factor, through which we can achieve the target of Sustainable Development Goals (SDGs). The past papers have investigated the nexus between income inequality and carbon emissions; however, the relationship between income inequality and carbon emissions along with ecological footprint has not been studied in the case of developing countries. To this end, this study analyzed the impact of income inequality on both carbon emissions and ecological footprint as well as the impact of carbon emission and ecological footprint on income inequality by using the dataset from 2006 to 2017 for the 18 Asian developing economies. This study confirmed the positive relationship between carbon emissions, ecological footprint, and income inequality under the methodology of Driscoll and Kraay (D&K) standard error approach. Specifically, a higher-income gap is destructive for environmental degradation, whereas increasing level of carbon emissions and ecological footprint also leads to rising income inequality in the investigated region. Furthermore, foreign direct investment (FDI), easy access to electricity, and population growth control income inequality, but they have a detrimental effect on both ecological footprint and carbon emissions. The empirical findings also provide some important policy implications.

     

Temporal variations in the level of chlordecone in seawater and marine organisms in Martinique Island (Lesser Antilles)

Environmental Science and Pollution Research - The present study, conducted in the Galion Bay in Martinique, aims to highlight the temporal and seasonal variations of chlordecone contamination (an...     

Residues of polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs) and organochlorine pesticides in organically-farmed vegetables

The residues of polyaromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs) in soils from organic farms and their uptake by four varieties of organic-produced potatoes and three varieties of organic carrots from England were investigated. Samples of the soils, crop peels and cores were all Soxhlet-extracted in triplicate, cleaned up by open-column chromatography and analysed by a multi-residue analytical method using gas chromatography with mass selective detection. The concentrations of PAHs, PCBs and OCPs in soils from organic farms ranged from 590+/-43 to 2301+/-146 microg/kg, 3.56+/-0.73 to 9.61+/-1.98 microg/kg and 52.2+/-4.9 to 478+/-111 microg/kg, respectively. Uptake by different crop varieties were 8.42+/-0.93 to 40.1+/-4.9 microg/kg sigmaPAHs, 0.83+/-0.19 to 2.68+/-0.94 microg/kg sigmaPCBs and 8.09+/-0.83 to 133+/-27 microg/kg sigmaOCPs. Residue uptake from soils depended on plant variety; Desiree potato and Nairobi carrot varieties were more susceptible to PAH contamination. Likewise, uptake of PCBs and OCPs depended on potato variety. There were significant positive correlations between the PCB and OCP concentrations (P<0.05) in soils and carrots but no significant correlation was found between the concentrations of any contaminants in soils and potatoes. Peeling carrots and potatoes was found to remove 52-100% of the contaminant residues depending on crop variety and the properties of the contaminants. Soil-crop bioconcentration factors (BCFs) decreased with increasing logK(ow) for PAHs up to about 4.5 and for PCBs up to about 6.5, above which no changes were discernible for either class of contaminants. No relationship was observed between soil-crop BCFs and logK(ow) for OCPs, most likely because their concentrations were low and variable.