Application of 1D and 2D MFR reactor technology for the isolation of insecticidal and anti-microbial properties from pyrolysis bio-oils

Valuable chemicals can be separated from agricultural residues by chemical or thermochemical processes. The application of pyrolysis has already been demonstrated as an efficient means to produce a liquid with a high concentration of desired product. The objective of this study was to apply an insect and microorganism bioassay-guided approach to separate and isolate pesticidal compounds from bio-oil produced through biomass pyrolysis. Tobacco leaf (Nicotianata bacum), tomato plant (Solanum lycopersicum), and spent coffee (Coffea arabica) grounds were pyrolyzed at 10°C/min from ambient to 565°C using the mechanically fluidized reactor (MFR). With one-dimensional (1D) MFR pyrolysis, the composition of the product vapors varied as the reactor temperature was raised allowing for the selection of the temperature range that corresponds to vapors with a high concentration of pesticidal properties. Further product separation was performed in a fractional condensation train, or 2D MFR pyrolysis, thus allowing for the separation of vapor components according to their condensation temperature. The 300–400°C tobacco and tomato bio-oil cuts from the 1D MFR showed the highest insecticidal and anti-microbial activity compared to the other bio-oil cuts. The 300–350 and 350–400°C bio-oil cuts produced by 2D MFR had the highest insecticidal activity when the bio-oil was collected from the 210°C condenser. The tobacco and tomato bio-oil had similar insecticidal activity (LC₅₀ of 2.1 and 2.2 mg/mL) when the bio-oil was collected in the 210°C condenser from the 300–350°C reactor temperature gases. The 2D MFR does concentrate the pesticidal products compared to the 1D MFR and thus can reduce the need for further separation steps such as solvent extraction.     

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.     

Optimal temporal scale for the correlation of AOD and ground measurements of PM2.5 in a real-time air quality estimation system

Aerosol optical depth (AOD), an indirect estimate of particulate matter using satellite observations, has shown great promise in improving estimates of PM_2.5 (particulate matter with aerodynamic diameter less than or equal to 2.5 μm) surface. Currently, few studies have been conducted to explore the optimal way to apply AOD data to improve the model accuracy of PM_2.5 in a real-time air quality system. We believe that two major aspects may be worthy of consideration in that area: 1) an approach that integrates satellite measurements with ground measurements in the estimates of pollutants and 2) identification of an optimal temporal scale to calculate the correlation of AOD and ground measurements. This paper is focused on the second aspect, identifying the optimal temporal scale to correlate AOD with PM_2.5. Five following different temporal scales were chosen to evaluate their impact on the model performance: 1) within the last 3 days, 2) within the last 10 days, 3) within the last 30 days, 4) within the last 90 days, and 5) the time period with the highest correlation in a year. The model performance is evaluated for its accuracy, bias, and errors based on the following selected statistics: the Mean Bias, the Normalized Mean Bias, the Root Mean Square Error, Normalized Mean Error, and the Index of Agreement. This research shows that the model with the temporal scale: within the last 30 days, displays the best model performance in a southern multi-state area centered in Mississippi using 2004 and 2005 data sets.     

On-line production of ferrate with an electrochemical method and its potential application for wastewater treatment – A review

A number of studies on the oxidation of various organic/inorganic contaminants by ferrate(VI) were reported in the 1980s and 1990s. The exploration of the use of ferrate(VI) for water and wastewater treatment has been well addressed recently. However, challenges have existed for the implementation of ferrate(VI) technology in practice due to the instability of a ferrate solution or high production cost of solid ferrate products. The research has been carried out aiming at the generation and application of ferrate(VI) in situ. This paper thus reviews ferrate chemistry and its overall performance as a water treatment chemical, discusses the factors affecting the ferrate yield efficiency using the electrochemical method, and finally, summarises the work on the production and use of ferrate in situ which is currently under study.     

The Effect of Water Harvesting Techniques on Runoff,Sedimentation, and Soil Properties

This study addressed the hydrological processes of runoff and sedimentation, soil moisture content, and properties under the effect of different water harvesting techniques (treatments). The study was conducted at three sites, representing environmental condition gradients, located in the southern part of the West Bank. For each treatment, the study evaluated soil chemical and physical properties, soil moisture at 30 cm depth, surface runoff and sedimentation at each site. Results showed that runoff is reduced by 65–85% and sedimentation by 58–69% in stone terraces and semi-circle bunds compared to the control at the semi-humid site. In addition, stone terraces and contour ridges significantly reduced the amount of total runoff by 80% and 73%, respectively, at the arid site. Soil moisture content was significantly increased by water harvesting techniques compared to the control in all treatments at the three study sites. In addition, the difference between the control and the water harvesting structures were higher in the arid and semi-arid areas than in the semi-humid area. Soil and water conservation, via utilization of water harvesting structures, is an effective principle for reducing the negative impact of high runoff intensity and subsequently increasing soil moisture storage from rainfall. Jessour systems in the valley and stone terraces were effective in increasing soil moisture storage, prolonging the growing season for natural vegetation, and decreasing the amount of supplemental irrigation required for growing fruit trees.     

Fluoride removal by a continuous flow electrocoagulation reactor

Long-term consumption of water containing excessive fluoride can lead to fluorosis of the teeth and bones. Electrocoagulation (EC) is an electrochemical technique, in which a variety of unwanted dissolved particles and suspended matter can be effectively removed from an aqueous solution by electrolysis. Continuous flow experiments with monopolar aluminium electrodes for fluoride removal were undertaken to investigate the effects of the different parameters such as: current density (12.5-50A/m(2)), flow rate (150-400 mL/min), initial pH (4-8), and initial fluoride concentration (5-25mg/L). The highest treatment efficiency was obtained for the largest current and the removal efficiency was found to be dependent on the current density, the flow rate and the initial fluoride concentration when the final pH ranged between 6 and 8. The composition of the sludge produced was analysed using the X-ray diffraction (XRD) spectrum. The strong presence of the aluminium hydroxide [Al(OH)(3)] in the above pH range, which maximizes the formation of aluminium fluoride hydroxide complex [Al(n)F(m)(OH)(3n-m)], is the main reason for defluoridation by electrocoagulation. The results obtained showed that the continuous flow electrocoagulation technology is an effective process for defluoridation of potable water supplies and could also be utilized for the defluoridation of industrial wastewater.     

Optimization of membrane-based CO2-removal from natural gas using simple models considering both pressure and temperature effects

Simple models for permeability and selectivity variations of the CO₂/CH₄ system in 6FDA-2,6-DAT membrane have been derived that include both temperature and pressure effects simultaneously in a single equation. The proposed models were used in MATLAB, for a membrane-based CO₂-removal process design for natural gas sweetening. The effects of the following factors on design parameters were examined: feed temperature, feed pressure and permeate pressure. The effect of permeate pressure was found to be very significant in the optimization process. In order to reduce hydrocarbon losses to below 2%, a two-stage membrane process was modeled and simulated in MATLAB, and the extent of desired hydrocarbon recovery was shown to be crucial in the optimization process. It has also been shown that there exist minima for the total required area of the two-stage membrane-based process, and as the CO₂ load increases in the feed, the position of these minima shift to higher values of methane loss.     

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.