Archaeal Poly (3-hydroxybutyrate) Polymer Production from Glycerol: Optimization by Taguchi Methodology

In this study the possibility of poly (3-hydroxybutyrate) production from glycerol was investigated and optimized by Halorcula sp. IRU1, a novel archaea isolated from Urmia lake, Iran in batch experiments. Using Taguchi methodology, three important independent parameters (glycerol, yeast extract and KH₂PO₄) were evaluated for their individual and interactive effects on poly (3-hydroxybutyrate) production. It was shown that the glycerol concentration was the most significant factor affecting the yield of poly (3-hydroxybutyrate). The optimum factor levels were a glycerol concentration of 8% (v/v), yeast extract 0.8% (w/v) and KH₂PO₄ 0.002% (w/v). The predicted value obtained for poly (3-hydroxybutyrate) production under these conditions was about 81.87%. We can conclude that Haloarcula sp. IRU1 has a high potential for synthesis of poly (3-hydroxybutyrate) from glycerol.     

Vermiculture and waste management: study of action of earthworms Elsinia foetida, Eudrilus euginae and Perionyx excavatus on biodegradation of some community wastes in India and Australia

The practice of vermiculture is at least a century old but it is now being revived worldwide with diverse ecological objectives such as waste management, soil detoxification and regeneration and sustainable agriculture. Earthworms act in the soil as aerators, grinders, crushers, chemical degraders and biological stimulators. They secrete enzymes, proteases, lipases, amylases, cellulases and chitinases which bring about rapid biochemical conversion of the cellulosic and the proteinaceous materials in the variety of organic wastes which originate from homes, gardens, dairies and farms. The process is odour free because earthworms release coelomic fluids in the decaying waste biomass which has anti-bacterial properties which kills pathogens. The species used in India were Indian blue (Perionyx excavatus), African night crawler (Eudrilus euginae) and the Tiger worm (Elsinia foetida). E. foetida was used in Australia. E. euginae was found to have higher feeding, growth and biodegradation capacity compared to other two species.Earthworm action was shown to enhance natural biodegradation and decomposition of wastes (60–80 percent under optimum conditions), thus significantly reducing the composting time by several weeks. Within 5 to 6 weeks, 95–100 percent degradation of all cellulosic materials was achieved. Even hard fruit and egg shells and bones can be degraded, although these may take longer.     

Usage of polystyrene disposable food dishes in the lightweight concrete making

The increasing use and subsequent accumulation of polystyrene containers has triggered a substantial environmental problem. This study investigated using varied percentages of solid waste polystyrene disposable food dishes in the production of lightweight concrete samples with 350 kilograms per cubic meter (kg/m³) of cement and a density of 1,300 kg/m³. The polystyrene disposable dishes were ground into beads of 0–3 millimeters (mm) and 3–6 mm in size. First, the characteristics of Type II Portland cement, polystyrene, and aggregates were examined. The following characteristics of concrete using ASTM International and British Standards Institution standards were tested: slump, compressive strength, ability to resist chloride ion penetration, and resistance of concrete to rapid freezing and thawing cycles. Scanning electron microscopy (SEM) and energy dispersive X‐ray spectroscopy analytical techniques were also used. The slump of samples varied between 40 and 70 mm and was not dependent on either the polystyrene percentage or the size of the polystyrene beads in the concrete samples (p‐value > .05). The compressive strength of the concrete samples after 90 days of curing, and using different percentages of polystyrene, varied between 96 and 113 kilograms per square centimeter (kg/cm²). The resistance of the samples to the freezing and thawing cycle and chloride ion penetration were affected unfavorably by the presence of the polystyrene. The SEM technique indicated that concrete samples containing 15% and 25% polystyrene had denser crystals and less void than concrete samples with 40% and 55% polystyrene.     

The formation of aerobic granular sludge for the treatment of real landfill leachate using a granular sequencing batch reactor at a constant volume

Leachate generated in a landfill may not be treated by conventional biological treatment due to its nature and complexity. The process of forming aerobic granules in batch sequencing reactors having features such as; reducing the settling process time and saving energy consumption and high decomposition rate have been noticed by researchers. In the present study, the structure of sequencing batch reactors (SBRs) was evaluated for the formation of granules, which were subsequently utilized for the treatment of landfill leachate. The experiment was initiated by using the GSBR, containing 1200 ml with different apparatuses, to develop granular sludge, and synthetic wastewater was added to reinforcement. The selected parameters for the operational hydraulic retention time (HRT) of the wastewater (6-h cycles) included feeding, idle, aeration, settling, and discharge. Furthermore, the controlled conditions were the dissolved oxygen (DO) range of 2–2.2 mg/L, temperature range of 20–23℃, and pH of 7.5–8.3. The chemical oxygen demand (COD), mixed liquor suspended solids (MLSS), and sludge volume index (SVI) daily were measured at the influent and effluent of GSBR reactor. The main properties of aerobic granular sludge were identified during the research procedures, and the remarkable settling and potent, high-density microbial structure of the granules were confirmed. The mean size of the formulated granules was estimated at 7.46 ± 1.8 mm, and the volume of the biomass also increased from approximately 1607 to 4137 mg/L through the granulation process. Moreover, 98% of the influent chemical oxygen demand (COD) could be removed by the formulated granular sludge, and the final-stage organic loading rate was estimated at 5.65 COD/m³/day. According to the results, GSBRs could be employed for the formulation of aerobic granular sludge for the treatment of landfill leachate.     

The Comparison of Lagrangian and Gaussian Models in Predicting of Air Pollution Emission Using Experimental Study,a Case Study: Ammonia Emission

Ammonia, as a colorless gas with a sharp odor, is considered as one of the created odors in the composting and landfill of solid waste. We used experimental data to study the robustness of AERMOD and the forward Lagrangian stochastic (FLS) in predicting ammonia emission in short range. The study area was Kahrizak landfill and composting plants, Tehran, Iran. The boundary layer parameters for the FLS were calculated on the basis of mean values of temperature, wind speed, and direction. While, the boundary layers of AERMOD were computed on the basis of exact meteorological data. The results depicted that AERMOD prediction at distances less than 1000 m from the sources and the locations inside the sources were poor. However, the results of FLS indicated more agreement with the field measurement, which the coefficient of determination was 0.83. Both models predicted, in the distance of 2000 m from the source, the ammonia concentration would be insignificant.     

Oxidative potential (OP) and mineralogy of iron ore particulate matter at the Gol-E-Gohar Mining and Industrial Facility (Iran)

Concentrations of total suspended particulate matter, particulate matter with aerodynamic diameter <2.5 μm (PM_2.5), particulate matter <10 μm (PM₁₀), and fallout dust were measured at the Iranian Gol-E-Gohar Mining and Industrial Facility. Samples were characterized in terms of mineralogy, morphology, and oxidative potential. Results show that indoor samples exceeded the 24-h PM_2.5 and PM₁₀ mass concentration limits (35 and 150 µg m^?3, respectively) set by the US National Ambient Air Quality Standards. Calcite, magnetite, tremolite, pyrite, talc, and clay minerals such as kaolinite, vermiculite, and illite are the major phases of the iron ore PM. Accessory minerals are quartz, dolomite, hematite, actinolite, biotite, albite, nimite, laumontite, diopside, and muscovite. The scanning electron microscope structure of fibrous-elongated minerals revealed individual fibers in the range of 1.5 nm to 71.65 µm in length and 0.2 nm to 3.7 µm in diameter. The presence of minerals related to respiratory diseases, such as talc, crystalline silica, and needle-shaped minerals like amphibole asbestos (tremolite and actinolite), strongly suggests the need for detailed health-based studies in the region. The particulate samples show low to medium oxidative potential per unit of mass, in relation to an urban road side control, being more reactive with ascorbate than with glutathione or urate. However, the PM oxidative potential per volume of air is exceptionally high, confirming that the workers are exposed to a considerable oxidative environment. PM released by iron ore mining and processing activities should be considered a potential health risk to the mine workers and nearby employees, and strategies to combat the issue are suggested.     

Artificial intelligence modeling to evaluate field performance of photocatalytic asphalt pavement for ambient air purification

In recent years, the application of titanium dioxide (TiO₂) as a photocatalyst in asphalt pavement has received considerable attention for purifying ambient air from traffic-emitted pollutants via photocatalytic processes. In order to control the increasing deterioration of ambient air quality, urgent and proper risk assessment tools are deemed necessary. However, in practice, monitoring all process parameters for various operating conditions is difficult due to the complex and non-linear nature of air pollution-based problems. Therefore, the development of models to predict air pollutant concentrations is very useful because it can provide early warnings to the population and also reduce the number of measuring sites. This study used artificial neural network (ANN) and neuro-fuzzy (NF) models to predict NO_x concentration in the air as a function of traffic count (T_r) and climatic conditions including humidity (H), temperature (T), solar radiation (S), and wind speed (W) before and after the application of TiO₂ on the pavement surface. These models are useful for modeling because of their ability to be trained using historical data and because of their capability for modeling highly non-linear relationships. To build these models, data were collected from a field study where an aqueous nano TiO₂ solution was sprayed on a 0.2-mile of asphalt pavement in Baton Rouge, LA. Results of this study showed that the NF model provided a better fitting to NO_x measurements than the ANN model in the training, validation, and test steps. Results of a parametric study indicated that traffic level, relative humidity, and solar radiation had the most influence on photocatalytic efficiency.