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.     

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.

     

Sustainable development conflict over freeway construction

Environmental disputes arise due to opposing views of various groups about their environmental concerns and their economic or developmental interests. Development and protection of the environment constitute two main contradictory objectives within the sustainable development paradigm, which are often in conflict. The decision support system, GMCR II, which implements the graph model for conflict resolution, is employed to model and analyze an environmental dispute arising over the construction of a new freeway between the Iranian capital, Tehran, and the city of Chalous located in the north of the country. This study demonstrates that the graph model for conflict resolution can be used as a methodology to promote a reasonable balance between economic development and environmental protection from a strategic viewpoint. In addition to systematically modelling the conflict by putting the existing information into proper perspective, it is shown how conflict analysis can be used for comparing alternative scenarios and predicting possible future outcomes. Readers should send their comments on this paper to: BhaskarNath@aol.com within 3 months of publication of this issue.     

A simplified model for reservoir operation considering the water quality issues: Application of the Young conflict resolution theory

In this study, an algorithm combining a multi-objective genetic algorithm (GA)-based optimization model and a water quality simulation model is developed for determining a trade-off curve between objectives related to the allocated water quantity and quality. To reduce the run-time of the GA-based optimization model, the main problem is decomposed to long-term and annual optimization models. The reliability of water supply is considered to be the objective function in the long-term stochastic optimization model, but the objective functions of the annual models are related to both the allocated water quantity and quality. The operating policies obtained using this long-term model provide the time series of the optimum reservoir water storages at the beginning and the end of each water year. In the next step, these optimal reservoir storage values are considered as constraints for water storage in the annual reservoir operation optimization models. The epsilon-constraint method is then used to develop a trade-off curve between the reliability of water supply and the average allocated water quality. The Young conflict resolution theory, which incorporates the existing conflicts among decision-makers and stakeholders, is used for selecting the best solution on the trade-off curve. The monthly reservoir operating rules are then calculated using an Adaptive Neuro-Fuzzy Inference System, which is trained using the optimal operating policies. The proposed model is applied to the 15-Khordad Reservoir in the central part of Iran. The results show that this simplified procedure does not reduce the accuracy of the reservoir operating policies and it can effectively reduce the computational burden of the previously developed models.     

Optimal redesign of groundwater quality monitoring networks: a case study

Assessment and redesign of water quality monitoring networks is an important task in water quality management. This paper presents a new methodology for optimal redesign of groundwater quality monitoring networks. The measure of transinformation in discrete entropy theory and the transinformation–distance (T–D) curves are used to quantify the efficiency of sampling locations and sampling frequencies in a monitoring network. The existing uncertainties in the T–D curves are taken in to account using the fuzzy set theory. The C-means clustering method is also used to classify the study area to some homogenous zones. The fuzzy T–D curve of the zones is then used in a multi-objective hybrid genetic algorithm-based optimization model. The proposed methodology is utilized for optimal redesign of monitoring network of the Tehran aquifer in the Tehran metropolitan area, Iran.