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.     

Simultaneous Removal of Nitrate and Natural Organic Matter from Drinking Water Using a Hybrid Heterotrophic/Autotrophic/Biological Activated Carbon Bioreactor

Simultaneous removal of nitrate ([Formula: see text]) and natural organic matter (NOM) from drinking water using a hybrid heterotrophic/autotrophic/BAC bioreactor (HHABB) was studied in continuous mode. The HHABB consisted of three compartments: ethanol heterotrophic part, sulfur autotrophic part, and biological activated carbon (BAC)-part (including anoxic and aerobic sections). Experiments were performed with [Formula: see text] concentration 30?mg N/L, [Formula: see text] loading rate 0.72?kg N/m(3)/d, C?:?N ratio 0.53, and three concentrations of NOM (0.6, 2.6, and 5.7?mg C/L). Overall denitrification rate and efficiency of the HHABB were not affected by NOM concentration and were in the suitable ranges of 0.69-0.70?kg N/m(3)/d and 96.0%-97.7%, respectively. NOM removal at concentration 0.6?mg C/L was not efficient because of organic carbon replacement as soluble microbial products. At higher NOM concentrations, total NOM removal efficiencies were 55%-65%, 55%-70%, and 55%-65% for dissolved organic carbon, trihalomethane formation potential, and UV absorbance at 254?nm (UV(254)), respectively. The more efficient compartments of the HHABB for the removal of NOM were the ethanol heterotrophic phase and aerobic BAC-phase. The efficiency of the HHABB in the removal of NOM was considerable, and the effluent dissolved organic carbon and trihalomethane formation potential concentrations were relatively low. This study indicated that the HHABB without the anoxic BAC-phase could be a feasible alternative for simultaneous removal of [Formula: see text] and NOM from drinking water at full scale.     

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.     

Biomass and nutrient concentration of sweet corn roots and shoots under organic amendments application

Two field experiments were conducted at the Waimanalo research station on the island of O'ahu, Hawaii to study the effect of chicken (CM) and dairy (DM) manures on biomass and nutrient concentration in sweet corn roots and shoots. Sweet corn (super sweet 10, Zea Mays L. subsp. mays) was grown for two consecutive growing seasons under four rates of application (0, 168, 337, and 672 kg ha^{? 1} total N equivalent) and one time (OTA) or two time (TTA) applications of organic manure types and rates. There were significant effects of types, rates, and number of manure applications on dry biomass and macro- and micro-nutrient concentration in roots and shoots tissues. Results of root tissue indicated a significant accumulation of N and C under CM and DM treatments compared with the control treatment. Manure application rates significantly increased the accumulation of N and C in root tissue. Dry weight of roots and shoots and both macro- and micro-nutrient contents in the plant tissues significantly increased under TTA treatment compared with OTA treatment. There was a significant correlation (r² = 0.46 to 0.81) between root biomass, macro-, and micro-nutrient contents during both growing seasons. The results of the study indicates that amending soils with CM at the highest application rate provided the best crop performance in terms of root and shoot biomass, crop N, C, and other macro- and micro-nutrients.     

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.     

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.     

Fuzzy Possibilistic Modeling for Closed Loop Recycling Collection Networks

Nowadays, in the competitive market, commercial companies due to their economic problems and also restrictions imposed by international organizations to comply with environmental regulations are making noticeable efforts to reduce the level of their wastes in their manufacturing systems and consequently the level of waste in consumers’ products. In harmony with this issue, one of the most effective ways which has successfully been used and proven to be economically profitable is to take products lifecycles into consideration. Consideration of products lifecycle has made supply chain practitioners to investigate the reverse logistics activities in addition to forward logistics activities. Hence, corporations, in order to reduce their cost on the one hand and boosting their efficiency on the other hand, were obligated to employ closed loop supply chain models to concurrently benefit from its economical and environmental advantages. Therefore, in this paper, a mixed nonlinear facility location–allocation model is proposed for recycling collection centers. The considered closed loop logistics model consists of multiple echelons, multiple suppliers, multiple collection centers, multiple time period and also multiple facilities. In real-life problems parameters like demand, cost, capacity, distances, and quantities of returned products are always uncertain. Therefore, in order to solve a realistic problem, foregoing parameters are considered as fuzzy in our proposed model. Subsequently, to solve fuzzy mixed nonlinear programming model, one of the most effective technique in the literature is used. Additionally, in order to demonstrate the behavior of the parameters employed in the model, a comprehensive sensitivity analysis is conducted. Computational results demonstrate that the proposed model can show favorable efficiency in solving supply chain problems.     

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.     

Visitor impact on rocky shore communities of Qeshm Island, the Persian Gulf, Iran

The influence of visitors on macroinvertebrates of rocky intertidal shores was investigated in southern coasts of the Qeshm Island, the Persian Gulf, Iran. Qeshm Island located at the Strait of Hormuz, with an area of 1,491 km², is the largest island in the region. This island consists of a number of important natural habitat types including creeks, mangroves, corals, and sandy, muddy, and rocky shores that accommodate diverse marine flora and fauna communities. Two rocky shores were selected at the touristic beaches being visited regularly, and further two control locations selected at pristine shores. Intertidal macroinvertebrates were collected from six microhabitats including rock platforms, cobbles, boulders, crevices, sea walls, and rock pools during two different periods representing high and low tourist seasons. Species richness, density, and assemblage structure in heavily visited shores were compared with that of control locations. Striped barnacles (Balanus amphitrite) were present on platforms of all locations, thus the changes in their size were used as the obvious contrast associated with visitor’s impact. A total of 70 macroinvertebrate species from 11 phyla were recorded. Significant differences were detected in taxonomic richness, density, and assemblage structure of macroinvertebrates between heavily visited and pristine shores, suggesting that macroinvertebrates were adversely affected by visitors’ impact at heavily visited shores. The test of changes in species richness, density, and assemblage structure from high to low seasons yielded mixed results. The significant changes in density and assemblage structure from high to low seasons were only observed in one heavily visited shore. A significant reduction in size of striped barnacles was observed only in one heavily visited shore. The opportunistic or fugitive species (e.g., small macroalgae and barnacles) were dominant macroinvertebrates on heavily visited shores indicating early succession stage. The results presented here showed that macroinvertebrates were adversely affected by human activities in subtropical rocky shore.