Development of a master plan for industerial solid waste management

Rapid industrial growth in the province of Khuzestan in the south west of Iran has resulted in disposal of about 1750 tons of solid waste per day. Most of these industrial solid wastes including hazardous wastes are disposed without considering environmental issues. This has contributed considerably to the pollution of the environment. This paper introduces a framework in which to develop a master plan for industrial solid waste management. There are usually different criteria for evaluating the existing solid waste pollution loads and how effective the management schemes are. A multiple criteria decision making technique, namely Analytical Hierarchy Process [AHP], is used for ranking the industrial units based on their share in solid waste related environmental pollution and determining the share of each unit in total solid waste pollution load. In this framework, a comprehensive set of direct, indirect, and supporting projects are proposed for solid waste pollution control. The proposed framework is applied for industrial solid waste management in the province of Khuzestan in Iran and a databank including GIS based maps of the study area is also developed. The results have shown that the industries located near the capital city of the province, Ahwaz, produce more than 32 percent of the total solid waste pollution load of the province. Application of the methodology also has shown that it can be effectively used for development of the master plan and management of industrial solid wastes

River water quality zoning: a case study of Karoon and Dez river system

Karoon-Dez River basin, with an area of 67000 square kilometers, is located in southern part of Iran. This river system supplies the water demands of 16 cities, several villages, thousands hectares of agricultural lands, and several hydropower plants. The increasing water demands at the project development stage including agricultural networks, fish hatchery projects, and inter-basin water transfers, have caused a gloomy future for water quality of the Karoon and Dez Rivers. A good part of used agricultural water, which is about 8040 million cubic meters, is returned to the rivers through agricultural drainage systems or as non-point, return flows. River water quality zoning could provide essential information for developing river water quality management policies. In this paper, a methodology is presented for this purpose using methods of -mean crisp classification and a fuzzy clustering scheme. The efficiency of these clustering methods was evaluated using water quality data gathered from the monitoring sampling points along Karoon and Dez Rivers. The results show that the proposed methodology can provide valuable information to support decision-making and to help river water quality management in the region