Jafar Nouri

Despite the vital role of electricity in human life, the energy supply process produces all kinds of pollutants such as solid wastes. Unfortunately, due to the lack of specific charge of administration, lack of legal and statutory criteria for effective control, and lack of supervising organizations, in Iran the industrial wastes couldn’t be managed well. The quantity and quality of waste of power plants have been investigated, and then a questionnaire was sent to all stations. The results showed that the use of Mazut fuel and gas oil will increase the rate of wastes. In thermal-gas power plants, due to the consumption of natural gas and lack of water consumption in the production cycle, less wastes have been produced than the other thermal power plants. To determine and explain the factors affecting the production of waste in power plants, an interview was held in the presence of 40 experts in the field of power plant wastes, and after determining the factors affecting the rate of wastes in power plants, Analytical Hierarchy Processes (AHPs) were used for the weighing and prioritization of each of these factors. In the next step, according to the collected data, the conceptual model for the environmental management of power plants was provided. The most important factors in the production of wastes based on the type of fuel type are the type of power plant and the quality of water. Generally, power plant wastes are divided into three categories: ordinary, industrial, and hazardous. Ordinary wastes could be buried in the landfill of urban wastes. However, in the case of industrial and hazardous wastes, location for the landfill is necessary. Also, some wastes like clarifier sediments and combustion wastes could be reused in other industries in order to reduce the volume of these wastes and in some cases reduces the risk of as well.

As an appropriate tool, membrane process is used for desalination of brackish water, in the production of drinking water. The present study aims to investi

This is a two-phase study to investigate the socioeconomic impacts of the Caspian Sea Level Rise (CSLR) on Anzali International Wetland at the southern fringe of the Caspian Sea. In the first phase, a Landsat satellite image (2013) and digital elevation model (DEM) of the wetland were used to determine the areas vulnerable to the CSLR-induced flooding under four water level rise scenarios of 0.2 m, 0.6 m, 1 m, and 1.4 m. Then in the second phase, the possible effects of the CSLR on some market values of Anzali Wetland and the livelihood of the wetland-dependent communities were assessed based on the loss of agricultural and fishing products (as two main sources of livelihood for local people), as well as the loss of different land uses surrounding the wetland. According to the results, under the most optimistic CSLR scenario of 0.2 m, the wetland area will be expanded from 19,095 to 24,942 ha, while an expansion of 19,353 ha (from the current area of 19,095 ha to 38,448 ha) is expected under the most pessimistic CSLR scenario of 1.4 m. This will affect a minimum number of eight villages, including 4,518 inhabitants (under the CSLR scenario of 0.2 m) and a maximum number of 41 villages including 22,493 inhabitants (under the 1.4 CSLR scenario). These people will have to displace and move from their homes, which leads to several social ills. Depending on the severity of water level rise under various scenarios, 545, 646, 670, and 699 ha of the total area (790 ha) of fish ponds will be destructed, and total numbers of 70, 76, 83, and 93 units out of the 172 active industrial units are predicted to be inundated. In sum, the total loss values (damage to agriculture and fish farming) under the CSLR scenarios of 0.2, 0.6, 1, and 1.4 m were estimated to be $63 million (USD), $117 million, $151 million, and $184 million, respectively. Our research findings can help policy makers develop proper adaptation measures to prohibit or reduce the possible socio-economic damage caused by the CSLR in the future.

Management of air pollution in Tehran, Iran, has been a significant challenge for urban authorities in recent years owing to the number and complexity of the factors affecting the formation and spread of the pollutions. The present study used an integrated modeling approach involving Spatio, Temporal, Uncertainty Decision Support Systems (STUDSS) using Multi Criteria Decision Analysis (MCDA) and an Artificial Neural Network (ANN) for the virtual simulation and strategy assessment of air pollution. Since sources of air pollution and associated pollution control strategies are dependent on location, time and uncertain variables, Multi-Dimensional Decision Support System (MDDSS) can be efficient tool for urban air quality decision-making process. In order to model and evaluate air pollution, time-series data over a period of four years, screened and classified management strategies as well as other structural and environmental data such as land uses, terrain topography, heights of buildings, climatic conditions, population density and pollution sources were modeled using advanced software packages of MCDA and ANN. They were ultimately simulated and evaluated using the MDDSS. The results obtained from the implementation of the STUDSS showed that this tool could be used to provide sustainable solutions to air quality in metropolises and could respond to social satisfaction and economic development.

This paper represents an index model developed for the assessment of risk caused by river floods. The main purpose of this model is to evaluate the flood risk in the western coastal region of Mazandaran Province/Iran. The model assesses the risk at triple components, i.e. the flood occurrence probability, vulnerability and consequences, through identification and evaluation of effective criteria categorized into seven indexes (environmental, technical, economic, social, depth, population and sensitivity ones) that are involved in all stages of flooding (source, pathway and receptor). The flood risk in the developed model is defined by a dimensionless magnitude called as risk score between 0 and 100 for each zone of the area under assessment by calculating and combining of two newly defined factors: occurrence and vulnerability factor and impact factor. The model was applied in a case study, the Nowshahr flood in 2012. The results showed that: (i) the flood risk zoning was compared with observed data for aspect of the damages, and general agreement between them was obtained; (ii) for urban zones, which surrounded by two rivers, would easily be in critical condition and rescue operations face difficulties; and (iii) it is necessary to review the location of the emergency services, according the flood risk zoning.

The main objective of this study was to compare the removal efficiency of nutrients using Lactuca sativa, Medicago sativa and Phragmites australis in subsurface flow constructed wetlands with horizontal flow. In order to test water quality, fabricated reactors designed and the plants cultivated in the soil while their root were inside the wastewater. A long time study carried out from spring till end of autumn (9 months) in order to evaluate the difference in removal rate based on the seasonal changes. The highest removal rate was during summer which followed by spring and autumn. Thus, the effect of plants on the removal efficiency of organic matter (COD, BOD), TSS and nutrient (P and TN) appeared to be dependent on the seasonal growth. Phragmites australis the most sensitive species in order the removal of nutrient from wastewater.