ABSTRACT
Introduction: Cleaner productions in textile industry is achieved by reducing water and chemicals' consumption, saving energy, reducing production of air pollution and solid wastes, reducing toxicity and noise pollution through many solutions. The purpose of the present research was to apply Strengths, Weaknesses, Opportunities, Threats [SWOT] and Quality Systems Planning Matrix [QSPM] techniques in identifying and prioritizing production in raw materials' warehouse of Yazdbaf Textile Factory
Materials and Methods: In this research, effective internal and external factors in cleaner production were identified by providing the required information through field visit and interview with industry managers and supervisors of raw materials' warehouse. Finally, to form matrix of internal and external factors 17 important internal factors and 7 important external factors were identified and selected respectively. Then, QSPM matrix was formed to determine the attractiveness and priority of the selected strategies by using results of internal and external factors and SWOT matrixes
Results: According to the results, the total score of raw materials' warehouse in Internal Factor Evaluation [IFE] matrix is equal to 2.90 which shows the good situation of warehouse than the internal factors. However, the total score in External Factor Evaluation [EFE] matrix is 2.14 and indicates the relative weak situation of warehouse than the external factors
Conclusion: Based on the obtained results, continuity, monitor, and improvement of the general plan of qualitative control [QC] of raw materials and laboratory as well as more emphasis on quality indexes according to its importance in the production processes were selected as the most important strategies
Subject(s)
Textiles , Strategic PlanningABSTRACT
Background: the phenomenon of dust is a serious environmental problem in dry and semi dry regions. It has a destructive effect for the residents of such regions. Over two-thirds of Iran is in areas of dry and semi-dry climate conditions
Methods: in this research, dust fall measurements were taken in 41 stations across Yazd city using a marble dust collector [MDCO] located in different parts of the city. Next, the chemical characteristics of dust were determined using the XRF method. Finally, levels of dust fall across the 4 seasons of the year and status of the constituent elements of dust were determined through ArcGIS software and the Kriging technique. The Raster calculator function was used to make determinations of the effects of dust fall at each of the stations over the course of the year. Remote sensing system, along with maps taken from Landsat and the band combination technique were processed using ENVI software to extract vegetation density and building density maps of the studied region
Results: results showed that spring had the highest level of dust fall with a value of 200 g/cm[2]. In total, in 109 km[2] of the studied region had average dust fall of 110 g/m[2] that contributed to 12 057 tons of dust over Yazd city in 2015. The constituent elements of the dust fall according to decreasing amounts were as follows: Si>Ca>Al>C>Mg>Fe>K>Na>S>Ti>Cl>P>Mn>Sr>Zn
Conclusion: these results indicate accuracy of the Kriging technique for application in dust zoning. The factors of vegetation and green space were determined as effective on adsorbing dust. Increased building density and height of buildings also contributed to development of dust fall
ABSTRACT
Introduction: Micro pollutants have become one of the most important environmental concerns around the world. These natural and synthetic compounds have been called Endocrine Disrupting Chemicals [EDCs] due to their interfere with the normal function of the endocrine system in humans and animals. They include natural and synthetic hormones and their metabolites, surfactant, insecticide, as well as some pharmaceuticals and health care products. Because of these compounds effects, importance of their monitoring in Iran is perceived like other countries
Materials and Methods: This paper was carried out on the basis of studies accomplished from 2000 to 2017 and also the ones published in databases such as Google Scholar, Elsevier, Scopus, Science direct, Magiran, and SID using hormone removal, micro pollutant removal, removal hormones from wastewater, sex hormones removal, steroidal hormones, hormone removal from wastewater, and removal efficiency of micro pollutants as the keywords. PRISMA [Preferred Reporting Items for Systematic Reviews and Meta-Analyses] statement was used for selecting articles
Results: Sexual reproduction of fish exposed to estrogenic compounds was changed. Phytoestrogens exist on a certain strain of clover which caused severe infertility in sheep grazing on them. Some studies have reported that a decrease in men's sperm and breast cancer in women are caused by exposure to estrogenic compounds
Conclusion: According to the current study, further studies are needed to determine the entry routes of steroid hormones into aquatic environment, the detection techniques and measurements, as well as the best removal method in Iran
Subject(s)
Humans , Female , Male , Animals , Water Purification , Environmental Pollution , Phytoestrogens , Endocrine Disruptors , Steroids/physiologyABSTRACT
Background: Data mining [DM] is an approach used in extracting valuable information from environmental processes. This research depicts a DM approach used in extracting some information from influent and effluent wastewater characteristic data of a waste stabilization pond [WSP] in Birjand, a city in Eastern Iran
Methods: Multiple regression [MR] and neural network [NN] models were examined using influent characteristics [pH, Biochemical oxygen demand [BOD[5]], temperature, chemical oxygen demand [COD], total suspended solids [TSS], total dissolved solid [TDS], electrical conductivity [EC] and turbidity] as the regression input vectors. Models were adjusted to input attributes, effluent BOD[5] [BODout] and COD [CODout]. The models performances were estimated by 10-fold external cross-validation. An internal 5-fold cross-validation was also used for the training data set in NN model. The models were compared using regression error characteristic [REC] plot and other statistical measures such as relative absolute error [RAE]. Sensitivity analysis was also applied to extract useful knowledge from NN model
Results: NN models [with RAE = 78.71 +/- 1.16 for BODout and 83.67 +/- 1.35 for CODout] and MR models [with RAE = 84.40% +/- 1.07 for BODout and 88.07 +/- 0.80 for CODout] indicate different performances and the former was better [P < 0.05] for the prediction of both effluent BOD5 and COD parameters. For the prediction of CODout the NN model with hidden layer size [H] = 4 and decay factor = 0.75 +/- 0.03 presented the best predictive results. For BODout the H and decay factor were found to be 4 and 0.73 +/- 0.03, respectively. TDS was found as the most descriptive influent wastewater characteristics for the prediction of the WSP performance. The REC plots confirmed the NN model performance superiority for both BOD and COD effluent prediction
Conclusion: Modeling the performance of WSP systems using NN models along with sensitivity analysis can offer better understanding on exploring the most significant parameters for the prediction of system performance. The findings of this study could build the foundation for prospective work on the characterization of WSP operations and optimization of their performances with a view to conducting statistical approaches
ABSTRACT
Introduction: The modeling aims to simulate or optimize a process in physical, chemical or biological environments and the derived model will provide a considerable assistance to generate data and predict unknown condition, in case of sufficient suitability. Unsuitable disposal and elimination of waste tires have polluted the environment and human life areas, it also have caused removal of a huge amount of recyclable materials and energy. Besides, attached growth biological processes of wastewater treatment are faced with very high costs of the beds used in such methods. Thus, this study targeted at the following topics: reuse of waste tires, reduction of the costs associated with preparation of biological wastewater treatment system beds, and increased productivity of refineries
Materials and Methods: The current experimental study was conducted in pilot scale, in which ability of Fixed Bed Sequence Batch Reactor [FBSBR] and Sequencing Batch Reactor [SBR] was evaluated by synthetic wastewater in diverse loadings. Ultimately, the derived data were analyzed using the statistical software packages SPSS and MS Excel
Results: The maximum removal efficiencies of dissolved chemical oxygen demand for FBSBR and SBR reactors were 98.3 % and 97.9 %, respectively. In addition, Stover-Kincannon model provided a very suitable fitness [R[2] > 0.99] for loading the bioreactor FBSBR
Conclusion: According to the results, not only waste tires can be reused, but also these wastes can be employed as a proper biological bed in wastewater refineries to improve their efficiency
ABSTRACT
Background: The presence of heavy metals in the environment especially in water supplies have caused many concerns because of their toxicity and non-degradability. Hexavalent Chromium [Cr] is one of the most toxic metals which is used in many industries, so it is essential to remove it from industrial wastewater. In this study, we made a comparison between different adsorption isotherms in the chromium [VI] removal process using carbon nano tubes from aqueous solutions
Methods: This experimental study used atomic absorption spectrophotometry. To determine the adsorption isotherms, a synthetic sample with defined concentration of Cr [VI] was prepared and different doses of adsorbent were added to it. The effect of initial Cr concentration, pH, adsorbent dose, and reaction time on removal of Cr was investigated. Temperature and mix rate were steady during a defined time. At the end, Cr [VI] concentration measured and adsorbents equality capacities were calculated via formulas and graphs. Data analysis were performed using descriptive statistics
Results: Adsorption capacities [q[e]] increased with increasing of initial Cr concentration, and reaction time decreased with increasing adsorbent dose and pH. Correlation coefficients for Langmuir, and Freundlich isotherms in oxidized Multi-Walled Carbon Nano Tubes [MWCNTs] were 0.93, 0.874, and 0.714 and in oxidized Single-Walled Carbon Nano Tubes [SWCNTs] were 0.904, 0.868, and 0.711 respectively
Conclusion: Chromium ions adsorption in carbon nano tubes is accordant to Langmuir isotherm model, and MWCNTs have more cc than SWCNTs. Carbon nano tubes are effective adsorbents in removal of Cr [VI] from aqueous solutions
ABSTRACT
Background: Yazd waste stabilization pond facilities consist of three stabilization pond systems, module 1, module 2 and module 3 that AWSP module 1 has started its operation. The existing facilities have had several problems in their operation. The objectives of this research were to evaluate the performance of stabilization ponds in wastewater treatment of the city of Yazd, due to several problems in their operation, and to prepare a scheme of its upgrading, if necessary
Methods: During the period from December to June 2010, data analysis were carried out for both raw and treated wastewater
Results: Results of these investigations showed that the average effluent concentrations of Biochemical Oxygen Demand 5 [BOD[5]], Chemical Oxygen Demand [COD] and Suspended Solid [SS] taken from anaerobic pond and secondary facultative ponds of module 1 were 306.9, 135.18, 139.75 and 136.75, 69.025, 136.5 mg/L, respectively
Conclusion: These results indicated that the effluent of the anaerobic pond of module 1 was complied with the Iranian treated wastewater standards for agricultural reuse in terms of BOD[5] and COD concentrations; hence the secondary facultative ponds could be changed to other primary facultative ponds in order to increase the capacity of wastewater treatment plant
ABSTRACT
Chromium is one of the most important heavy metals, which its high levels in drinking water lead to several health adverse effects. This study was performed aiming at determining the effects of primary concentration of six-valent chromium, adsorbent dosage, contact time, and pH on the adsorption of chromium from water on bone char. Bone char was prepared using electric furnace at 450°C for 2 h. Pulverizing of bone char was carried out by standard ASTM sieves with the range of 0.5-1 mm. The structural characteristics and specific surface area were determined through conventional methods. The samples' chromium concentration was measured at a wavelength of 450 nm. Adsorption isotherm of chromium was assessed by Freundlich, Langmuir, and Temkin adsorption equation models. The main component of Bone char is calcium hydroxylapatite with surface area of 100m[2]/g. In this study, adsorption reached the equilibrium at lapse of 120 min, and the increase of adsorbent dose up to 0.7g/100ml leaded to increase in the chromium adsorption. However, higher level had no effect on adsorption efficiency. The results showed optimum adsorption took place better in acidic range of pH [pH=3]. Adsorption isotherm of chromium on bone char follows the Langmuir and Temkin models, and the maximum adsorption capacity the dimensionless coefficient [RL] were 2.025 mg/g and 0.15, respectively which indicates that an appropriate adsorption of chromium on bone char. Bone char is an inexpensive adsorbent, which can be used for adsorption of chromium from water based on surface properties