Removal of heavy metals Cr [VI], Cd [II] and Ni [II] from aqueous solution by bioabsorbtion of elaeagnus angustifolia

The problem of removing pollutants from water is an important process and is becoming more important with the increasing of industrial activities. One of the most important environmental problems is water resources pollution by Heavy metals. Bioabsorbtion is affordable adsorbents for the removal of heavy metals from aqueous solutions. This study explores the adsorption potential of Cr [VI], Cd [II] and Ni [II] by Elaeagnus angustifolia fruit powder in aqueous solution. The influences of several main parameters such as pH value of solution, sorbent amount, initial metal ion concentration, and contact time in batch experiments have been studied. The adsorption was depended on pH, adsorbent dosage, and contact time. Maximum removal of Cr [VI], Cd [II] and Ni[II] were obtained 7.19mg/g, 2.42 mg/g and 1.97 mg/g respectively. Adsorption isotherms were compared with both Langmuir and Freundlich adsorption models. The experimental data best fit with the Langmuir isotherm model. Experimental results show natural biosorbent was effective for the removal of pollutants from aqueous solution

Forecasting municipal solid waste generation by hybrid support vector machine and partial least square model

Forecasting of municipal waste generation is a critical challenge for decision making and planning, because proper planning and operation of a solid waste management system is intensively affected by municipal solid waste [MSW] streams analysis and accurate predictions of solid waste quantities generated. Due to dynamic and complexity of solid waste management system, models by artificial intelligence can be a useful solution of this problem. In this paper, a novel method of Forecasting MSW generation has been proposed. Here, support vector machine [SVM] as an intelligence tool combined with partial least square [PLS] as a feature selection tool was used to weekly prediction of MSW generated in Tehran, Iran. Weekly MSW generated in the period of 2008 to 2011 was used as input data for model learning. Moreover, Monte Carlo method was used to analyze uncertainty of the model results. Model performance evaluated and compared by statistical indices of Relative Mean Errors, Root Mean Squared Errors, Mean Absolute Relative Error and coefficient of determination. Comparison of SVM and PLS-SVM model showed PLS-SVM is superior to SVM model in predictive ability and calculation time saving. Also, results demonstrate which PLS could successfully identify the complex nonlinearity and correlations among input variables and minimize them. The uncertainty analysis also verified that the PLS-SVM model had more robustness than SVM and had a lower sensitivity to change of input variables

Environmentally sound water resources management in catchment level using DPSIR model and scenario analysis

Maharlou-Bakhtegan Catchment in the southern part of Iran is faced with water scarcity. This problem is exacerbated by environmental degradation, climate change effects, mismanagement of water resources, along with a major dependence of water demand supplies on the limited groundwater resources. In this study, a combined approach of DPSIR model along with the scenario analysis was employed to derive the optimal management strategies for the environmentally sound water resources management of Maharlou-Bakhtegan Catchment considering the conjunctive use of surface and groundwater resources. Cause-effect relationships were identified by DPSIR framework and 15 scenarios were developed based on them. For evaluating each scenario, 9 integrated water resources management indicators were introduced and evaluated by MODSIM. The results demonstrated that in scenario Scen-14, restriction for the irrigation area development, as well as other management solutions, which led to 100% supply of domestic and industrial water demands and 91% supply of agricultural water demands. Also in the last scenario the value 1.79 kg/m[3] was received by the Agricultural water productivity indicators. Moreover, by satisfying all IWRM indicators as well as enhancing zero for negative water balance of the aquifers in Scen-14, it is clearly indicated that this scenario revealed more efficient management solutions for the environmentally sound water resources management of the catchment

Development of water quality index [WQI] for Gorganrood river

There are several factors influencing the water quality based on its usage. The quality of drinking water is of the vital concern for human health and life. An essential attempt has to be done to develop a water quality index [WQI] corresponding with different conditions and characteristics of the relevant river" or water body such as geographical, hydrological, discharge rate and pollution sources. The index is not specifically focused on human health or aquatic life regulations. However, a water index based on some very important parameters can determine a simple indicator of water quality. In the present study, the Gorganrood water quality has been evaluated by available NSF water quality index. Subsequently, the nine present NSF parameters' weights have been changed and modified using the analytical hierarchy process [AHP] method as well as experts' opinions in the field in a way to satisfy local conditions. In the newly developed WQI, more weights are given to relation with these parameters it can be said that the factors like dissolved oxygen [Do], fecal coliform [Fc] and biological oxygen demand [BOD] when compared with NSF-WQI

Potential of natural bed soil in adsorption of heavy metals in industrial waste landfill

Development of higher welfare could not be realized unless by energy consumption and other natural resources. Growth of industrial complexes has shown an unprecedented trend during recent years. Many of these towns have no treatment systems for the industrial wastes leachates. Besides, the chemical composition of wastes in such complexes varies considerably due to the different kinds of industries. It is endeavored in the present work to study the natural potential of soil to treat leachate of such industrial wastes. For this purpose, the Aliabad industrial complex in Tehran-Garmsar road was selected as the study area. The potential of adsorption of elements such as nickel, copper, cadmium, zinc, chromium, lead and manganese was investigated. The results indicated that the soil potential to adsorb heavy metals [except for manganese] was very high [95%] in the adsorption of heavy metals [except for manganese]. Further, chemical partitioning studies revealed that heavy metals are associated with various soil phases such as loosely bonded ions, sulfide and organics to various extents. Among the mentioned soil phases, one can deduce that major portion of metal contaminants is absorbed as loosely bonded ions. Organic bond and sulfide bond are in the 2 [nd] and 3 [rd] positions of metal contaminants adsorption, respectively. The results of the present study apparently showed that soil column had ample capacity to adsorb metal contaminants. Thus, determination of soil potential in adsorption of heavy metals during site selection is as important criteria

Development of an entropy- based fuzzy eutrophication index for reservoir water quality evaluation

Eutrophication phenomenon is one of the most common water quality problems in reservoirs in many regions. Determining the trophic status of the reservoirs is not a precise process and contains vagueness. Fuzzy set and entropy theories are concepts which can model uncertainty and imprecision in the data and the analysis. In this study, an Entropy-based Fuzzy Eutrophication Index model has been developed for classification of trophic level of Satarkhan Reservoir in the north-western part of Iran. Through the Fuzzy Synthetic Evaluation technique, trophic levels were considered as fuzzy sets and a fuzzy evaluation matrix was formed by defining the membership function of water quality indicators. The indicators were weighed by integrating both objective and subjective criteria. In this regard, the entropy method was used to determine the objective weights of the indicators based on the amount of useful information available in the data set and the subjective weight was determined by the analytical hierarchy process using a pairwise comparison done by the expert judgment. Classification of the trophic status of the reservoir was determined by multiplying the weighed vector by the fuzzy evaluation matrix. The results showed that critical months for eutrophication in Satarkhan reservoir occur in autumn and spring after the overturning phenomena. The strength of the results of developed entrophy-based fuzzy entrophication index is that the trophic level in each month was expressed with a degree of certainty. Also due to the ability of the model to integrate different kinds of objective and subjective quality observations considering the information included in the data, the proposed model is more robust than the previous index models such as Trophic Status Index and fuzzy trophic index

Water quality trading using tradable discharge permit in a river and assessment of its cost-effectiveness

Localizing water resource management with optimum waste allocation approach in rivers is one of the strategies for reducing the pollution. In this regard, a water quality trading program among pollution sources can fulfill this issue. This program is achieved through a tradable discharge permits system which is based on the river self purification capacity and creates an economical incentive to reduce the pollutants. Water quality trading emerges from the concept of hydrology and economy based on the transfer coefficient which is the fraction of pollution load that is transferred from the upstream to the downstream. Transfer coefficient is obtained from the water quality model. In this paper, execution of a tradable discharge permit program for the index pollutants has been assessed. Finally the results are analyzed for evaluating the cost effectiveness

Solidification/stabilization of heavy metals from air heater washing wastewater treatment in thermal power plants

In the present investigation, for the first time in Iran, dewatered sludge waste from air heater washing wastewater treatment of a thermal power plant was subjected to investigation of the cement base stabilization and solidification experiments in order to reduce the mobility of heavy and other hazardous metals as well as increasing the compressive strength of the solidified product for possible reuse of the waste. The solidification was done with two cement based mix designs with different waste/cement ratio is different samples. The results of leaching test on the solidified samples revealed that regarding the sand-cement mixture even with 25% waste/cement ratio, the leaching of heavy metals has completely been controlled up to 95%. In cement stabilization process the leaching of V, Ni, Zn and Cr could be decreased from 314.1, 209.1, 24.8 and 5.5 mg/L respectively in the raw waste to 6, 32.1, 3.6 and 3.6 mg/L in a mixture with 20% waste/cement ratio. During stabilization with cement-sand, the TCLP leachate contents of mentioned metals have been decreased to 4.2, 16.2, 2.5 and 2.2 mg/L with waste/cement ratio of 20%. X-ray diffraction studies showed that portlandite, calcite, lime, larnite and quartz have been shaped during the stabilization process. The compressive strength test results revealed that in both mixture samples, decreasing the compressive strength with increasing the amount of waste content in the mixture occurs. In sand-cement solidified samples with waste/cement ratio 25% and in cement solidified samples with waste/cement ratio 20%, a 40% decrease occurs in the compressive strength in comparison with the waste free mixtures