Uncertainties in vegetated buffer strip function in controlling phosphorus export from agricultural land in the Canadian prairies

Environmental Science and Pollution Research - Vegetated buffer strips (VBSs) are widely encouraged as a cost-effective strategy to address phosphorus (P) pollution associated with agricultural...     

Effect of virtual water trade on freshwater pollution in trading partners: a systematic literature review

Environmental Science and Pollution Research - Systematic reviews are a more complete, repeatable, and less biased form of literature reviews leading to evidence-based conclusions. A systematic...     

Sustainable biofuels from algae

There is currently great interest in microalgae as sources of renewable energy and biofuels. Many algae species have a high lipid content and can be grown on non-arable land using alternate water sources such as seawater. This paper discusses in detail the issue of sustainability of commercial-scale microalgae production of biofuels with particular focus on land, water, nutrients (N and P) and CO₂ requirements and highlights some of the key issues in the very large scale culture of microalgae which is required for biofuels. The use of genetically modified algae is also considered.     

Experimental investigation,intelligent modeling and multi-characteristics optimization of dry WEDM process of Al–SiC metal matrix composite

Dry wire electrical discharge machining (WEDM) is an environmentally friendly modification of the oil WEDM process in which liquid dielectric is replaced by a gaseous medium. In the present work, parametric analysis has been fulfilled while dry WEDM of Al–SiC metal matrix composite. Experiments were designed and conducted based on L₂₇ Taguchi's orthogonal array to study the effect of pulse on time, pulse off time, gap voltage, discharge current, wire tension and wire feed on cutting velocity (CV) and surface roughness (SR). Firstly, a series of exploratory experiments has been conducted to identify appropriate gas and wire material based on the values of cutting velocity. After selection of best gas and best wire, they were used for later stage of experiments. Analysis of variances (ANOVA) has been performed to identify significant factors. In order to correlate relationship between process inputs and responses, an adaptive neuro-fuzzy inference system (ANFIS) has been employed to predict the process characteristics based on experimental observation. At the end, an artificial bee colony (ABC) algorithm has been associated with ANFIS models to maximize CV and minimize SR, simultaneously. Then the optimal solutions that obtained through ANFIS-ABC technique have been compared with numbers of confirmatory experiments. Results indicated that oxygen gas and brass wire guarantee superior cutting velocity. Also, according to ANOVA, pulse on time and discharge current were found to have significant effect on CV and SR. In modeling of CV and SR by ANFIS, it was resulted that the proposed method has superiority in prediction of them in the ranges of factors beyond the training condition. Also, association of ANFIS with ABC can find the optimal combination of process parameters accurately according to the confirmatory experiments.     

Prevalence of Norovirus Infection in Children and Adults with Acute Gastroenteritis,Tehran, Iran, 2008–2009

Noroviruses are one of important agents that cause acute viral gastroenteritis worldwide. These viruses are belonging to Caliciviridae family and are genetically diverse. To date, there is no valuable data about prevalence of norovirus infection and the dominant genogroup/genotype among Iranian population. The objective of this study was to determine the frequency of norovirus infection in Iranian patients with gastroenteritis referred to three hospitals of Tehran and to specify the dominant genogroup/genotype of this virus among our study population. A total of 293 patients with acute gastroenteritis were included in the study. Detection of norovirus was performed using RT-PCR method and confirmed by direct sequencing with specific designed primers for capsid region of norovirus genome. Phylogenetic analysis was performed using the neighbor-joining method. Norovirus strains identified in our study were subsequently categorized according to previously defined genogroup/genotypes. Of these, norovirus GII was dominant genogroup. Sixty-five percent (17 of 26) of positive samples were determined as GII and 35% (9 of 26) were determined as GI, respectively, in 2008–2009. And among 8 sequenced strains of genogroup II the most frequent genotype was GII.3. The results of this study indicated that norovirus must be considered as one of the infectious causes of acute gastroenteritis among Iranian population. We also found that GII.3 is more prevalent in our study population. To the best of our knowledge there is limited data about the role of noroviruses in children and adults’ acute gastroenteritis among Iranian patients and this prevalence and genotyping report of norovirus infection could be remarkable for further studies.     

A mathematical model to predict the composition and generation of hospital wastes in Iran

The aim of this study is to investigate the quality and quantity of hospital wastes in Iran. The generated hospital wastes have been estimated by the number of hospitals and the number of active beds in each province of Iran in 2001. All data and information have been gathered from: (i) Iran Statistics Center, (ii) literature review, and (iii) hospital waste investigations for an average hospital. Physical analyses have been conducted in terms of various materials (plastic, textile, paper, metal, and others) and components (biological, infectious, medical, and regular wastes). Based on the above-mentioned investigation and information, a mathematical model has been developed to calculate the generation of (infectious) hospital wastes for any desired year. Utilizing the model, generated infectious hospital wastes has been estimated as 698,937 tones for 2008 (short-term) and 3,494,387 tones for 2028 (long-term period). If the real infectious wastes are collected separately, then the generated infectious wastes will be reduced by 15.1% of the above-mentioned amount (139,787 tones for 2008, and 698,877 tones for 2028). Results of physical analysis show the components of the hospital waste as: (a) infectious, 67.3%; (b) medical, 8.8%; (c) biological, 1.8%; and (d) common municipal wastes, 22.1%. An appropriate collection method requires training the staff at hospitals along with preparation of the required facilities. Of course, both of these requirements are cost intensive.     

Performance of Cow Dung Reinforced Biodegradable Poly(Lactic Acid) Biocomposites for Structural Applications

In this work, performance of cow dung (CD) reinforced poly(lactic acid) (PLA) biocomposites was investigated for the potential use in load bearing application. CD of average 4 mm size was blended with PLA at different CD ratios (0–50 wt%) and their effects on the biocomposite properties were studied. The results showed an improvement in the flexural properties, while the tensile and impact strength dropped by 20 and 28% with the addition of 50% CD. The decline in the tensile and impact strength was due to micro-cracking and voids formation at higher CD content. Also, the incorporation of CD slightly decreased the thermal stability of the biocomposite. However, dynamic mechanical properties of the biocomposites generally improved. SEM analysis of tensile and impact fractured surfaces indicated that the CD had a reasonable adhesion with matrix. Moreover, the SEM micrographs of soil burial studies showed an accelerated degradation of higher CD wt% biocomposites.     

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.

     

Estimation of soil specific surface area using some mechanical properties of soil by artificial neural networks

Soil specific surface area (SSA) is an important property of soil. Depending on the measurement techniques, determination of the SSA is costly and time consuming. Hence, a limited number of studies have been conducted to predict the SSA from the soil variables. In this study, the soil samples were taken from the literature. Fractal parameters (FP) were calculated by the model of Bird et al. (European Journal of Soil Science 51, 55–63, 2000) used as the input variables to predict the SSA. Some studies have been carried out on the prediction capability of the different parameters using the artificial neural networks (ANNs). The ANNs were further used and 20 models were developed to investigate the value of input variables to predict the SSA. The results showed that the PTF13 (RMSE?=?0.13) and PTF18 (RMSE?=?0.13) with the input variables of particle-size distribution and Atterberg limits revealed better performance than the other PTFs (in the training step). It is because of the fact that free swelling index (FSI) and Atterberg limits were closely correlated to the soil clay mineralogy as one of the important factors controlling the SSA. In general, this results demonstrated that the PTF9 with the variables of sand, clay, plastic limit (PL), liquid limit (LL), and FSI showed the best (RMSE?=?0.37) results in the estimation of the SSA. In conclusion, there was not a strong correlation between the soil mechanical properties and SSA but also ANNs were a suitable method to predict the SSA from the soil variables.