Effects of calcium hydroxide and calcium chloride addition to bentonite in iron ore pelletization.

Pyrite ash is created as waste from the roasting of pyrite ores during the production of sulphuric acid. These processes generate great amounts of pyrite ash waste that is generally land filled. This creates serious environmental pollution due to the release of acids and toxic substances. Pyrite ash waste can be utilized in the iron production industry as a blast furnace feed to process this waste and prevent environmental pollution. The essential parameters affecting the pelletization process of pyrite ash were studied using bentonite as a binder. Experiments were then carried out using bentonite and a mixture of bentonite with calcium hydroxide and calcium chloride in order to make the bentonite more effective. The metallurgical properties of pyrite ash, bentonite, calcium hydroxide, calcium chloride, a mixture of these and sintered pellets were studied using X-ray analysis. The crushing strength tests were carried out to investigate the strength of pyrite ash waste pellets. The results of these analyses showed that pyrite ash can be agglomerated to pellets and used in the iron production industry as a blast furnace feed. The crushing strength of the pellets containing calcium hydroxide and calcium chloride in addition to bentonite was better than the strength of pellets prepared using only bentonite binder.     

Single-source impact analysis using three-dimensional air quality models

Isolating the effects of an individual emissions source on secondary air pollutants such as ozone and some components of particulate matter must incorporate complex nonlinear processes, be sensitive to small emissions perturbations, and account for impacts that may occur hundreds of kilometers away. The ability to evaluate these impacts is becoming increasingly important for efficient air quality management. Here, as part of a recent compliance enforcement action for a violation of the Clean Air Act and as an evaluation of ozone response to single-source emissions plumes, two three-dimensional regional photochemical air quality models are used to assess the impact on ozone from approximately 2000 to 3000 excess t/month of nitrogen oxides emitted from a single power plant in Ohio. Periods in May, July, and August are evaluated. Two sensitivity methods are applied: the "brute-force" (B-F) method and the decoupled direct method (DDM). Using DDM, maximum 1-hr averaged ozone concentrations are found to increase by up to 1.8, 1.3, and 2.2 ppbv during May, July, and August episodes, respectively, and concentration increases greater than 0.5 ppbv occur in Ohio, Pennsylvania, Maryland, New York, West Virginia, Virginia, and North and South Carolina. B-F results for the August episode show a maximum 1-hr averaged ozone concentration increase of 2.3 ppbv. Significant localized decreases are also simulated, with a maximum of 3.6 ppbv in Ohio during the August episode and decreases of 0.50 ppbv and greater in Ohio, Pennsylvania, Maryland, West Virginia, and Virginia. Maximum increases are compared with maximum decreases for the August period using second-order DDM and are found, in aggregate, to be greater in magnitude by 42%. When evaluated during hours when ozone concentrations exceed 0.060 ppm, the maximum increases in ozone are higher than decreases by 82%. The spatial extent of ozone increase in both cases is about triple that of reduction.     

Mineral contents and proximate composition of Pistacia vera kernels

The mineral contents of Pistacia vera kernels were determined by inductively coupled plasma-atomic emission spectroscopy (ICP-AES). The minimum and maximum values of K, P, Ca, Mg, and S elements ranged from 6,333 to 8,064 mg/kg, 3,630 to 5,228 mg/kg, 1,614 to 3,226 mg/kg, 1,716 to 2,402 mg/kg, and 1,417 to 1,825 mg/kg, respectively. In addition, the mean values of Fe, Zn, Cu, Mn, B, Mo, Cr and Ni elements were determined as 42.48, 20.52, 12.81, 7.48, 11.31, 0.106, 0.511 and 1.67 mg/kg, respectively. Ash levels of kernels were found between 2.28 % (Urfa) and 2.79 % (Halebi). In addition, crude oil and protein contents were determined between 48.8 % (Halebi) to 55.3 % (Siirt) and 23.33 % (Uzun) to 27.16 % (Halebi), respectively.     

Some phenolic compounds of extracts obtained from Origanum species growing in Turkey

Caffeic acid, rosmarinic acid, rutin, apigenin 7-O-glucoside, apigenin, and acesetin were the main phenolic compounds of Origanum onites extracts in all applications. While acesetin contents ranged from 133.59 mg/100 g (U1) to 437.25 mg/100 g (S3), rosmarinic acid changed between 215.94 mg/100 g (U4) and 1120.56 mg/100 g (S2) in Origanum vulgare L. subsp. hirtum (Link) Ietsw. Both rosmarinic acid and acesetin were not found in U5 application. Only caffeic acid (19.39 mg/100 g) was found in U5 application. Rosmarinic acid contents of O. onites extract changed between 158.62 mg/100 g (U5) and 799.87 mg/100 g (S2). Generally, dominant phenolic compound of Origanum extracts was rosmarinic acid compared with other extracts. In addition, methanol:water:acetic acid mixture (S2) (95:4.5:0.5) was found as the best application. Phenolic contents of extracts obtained with U series mixtures were found low.     

Application of life cycle assessment of system solution scenarios for municipal solid waste management in Turkey

Journal of Material Cycles and Waste Management - In this study, an average waste composition was determined using the Provincial Environmental Status Reports of 81 provinces in Turkey for 2019,...     

Research on recycle of waste fluorescent lamp glasses and use as mineral filler in asphalt mixture

Journal of Material Cycles and Waste Management - In this study, utilization of waste fluorescent lamp as mineral filler in asphalt mixture was investigated. The phosphorus powder of fluorescent...     

Protective effects of melatonin and vitamin E in acetamiprid-induced nephrotoxicity

Environmental Science and Pollution Research - Investigation of probable toxic effects of acetamiprid (ACMP) on kidney and comparative analysis of the probable protective effects of vitamin E and...     

Mineral contents of seed and seed oils of Capparis species growing wild in Turkey

The mineral contents of seed and seed oils of Capparis species growing wild in Turkey were established by inductively coupled plasma–atomic emission spectrometry. Capparis spinosa var. spinosa (2010) and Capparis ovata var. canescens variety (2009) were determined to be rich in terms of mineral matter as 19,514.60 and 16,995.92 ppm as a total, respectively. C. spinosa var. spinosa collected from Mu?la-Milas region (2009) had the highest amount of Ca with 1,010.67 ppm in C. spinosa species and in C. ovata species. C. ovata var. canescens collected from Ankara-Beypazar? (2010) region had the highest amount of Ca with 833.92 ppm Ca amount in C. spinosa var. spinosa, inermis, herbaceae seeds decreased in 2010. C. spinosa var. inermis collected from Antalya-Serik (2010) in C. spinosa species had rich amount of Ca with 123.78 ppm and C. ovata var. palaestina seed oils collected from Mardin-Savur region (2009) had rich amount of Ca with 253.71 ppm in C. ovata species. The oil of C. spinosa var. herbaceae variety collected from Mardin-Midyat region (2010) was determined to have the highest major mineral matter (Ca, K, Mg, Na, and P) with 1,424.37 ppm in C. spinosa species. It was also determined that as a result, caper seed and oils were found to be important sources of nutrients and essential elements.     

Modeling 4-Chlorophenol Removal from Aqueous Solutions by Granular Activated Carbon

Since phenols and phenolic compounds in many industrial wastewaters are toxic organic contaminants for humans and aquatic life, to remove these compounds via the most efficient way is very important for environmental remediation treatment. In this context, almost all of the isotherm models (Freundlich, Langmuir, Temkin, Redlich–Peterson, Sips, and Khan) for adsorption in the literature were applied to explain the adsorption mechanism of 4-chlorophenol on activated carbon in this study. Also theoretical modeling data were obtained using model equations; interpolation and analysis of variance were made to compare data by using statistics software. In addition, the thermodynamic and kinetic studies for adsorption mechanism were included in the article. The adsorption of 4-chlorophenol on activated carbon fits well to the pseudo-first-order kinetic model than the pseudo-second-order, intraparticular diffusion and Bangham models. It is also indicated that 4-chlorophenol adsorption by granular activated carbon would be attributed to a type of transition between physical and chemical adsorption rather than a pure physical or chemical adsorption process. As a result, an environmental remediation problem and the adsorption mechanism on activated carbon that can be regarded as a solution to this problem are described and explained using the mathematical models and calculations in this study.     

Estimating soil temperature using neighboring station data via multi-nonlinear regression and artificial neural network models

The aim of this study is to estimate the soil temperatures of a target station using only the soil temperatures of neighboring stations without any consideration of the other variables or parameters related to soil properties. For this aim, the soil temperatures were measured at depths of 5, 10, 20, 50, and 100 cm below the earth surface at eight measuring stations in Turkey. Firstly, the multiple nonlinear regression analysis was performed with the “Enter” method to determine the relationship between the values of target station and neighboring stations. Then, the stepwise regression analysis was applied to determine the best independent variables. Finally, an artificial neural network (ANN) model was developed to estimate the soil temperature of a target station. According to the derived results for the training data set, the mean absolute percentage error and correlation coefficient ranged from 1.45% to 3.11% and from 0.9979 to 0.9986, respectively, while corresponding ranges of 1.685–3.65% and 0.9988–0.9991, respectively, were obtained based on the testing data set. The obtained results show that the developed ANN model provides a simple and accurate prediction to determine the soil temperature. In addition, the missing data at the target station could be determined within a high degree of accuracy.