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Prediction and Comparison of Water Pollution Generated by Industry Sector in Iran

عنوان مقاله: Prediction and Comparison of Water Pollution Generated by Industry Sector in Iran
شناسه ملی مقاله: GETOROUD04_059
منتشر شده در چهارمین کنفرانس بین المللی اقتصاد سبز در سال 1396
مشخصات نویسندگان مقاله:

Parinaz Jansouz - University of Sistan and Baluchestan, Factually of Management and Economics, Department of Environment and NaturalResources Economics, P.O.Box: ۹۸۱۳۵-۹۸۷, Zahedan, Iran
Mohammad Abdolhosseini - Assistant Professor, Gorgan University of Agricultural Sciences and Natural Resources, Faculty of Waterand Soil Engineering, Department of Water Engineering

خلاصه مقاله:
Water scarcity in arid and semi-arid regions from one side and excessive and wrong use of water resources and its pollution on the other side are serious threats to sustainable development and environmental protection. Principally, water is used in three sectors: industry, agriculture, and drinking; and the water pollution is created in each one of these three sectors. Despite the low share of industry in water consumption, the created pollution by this sector is very diverse and dangerous. With respect to the the importance of this issue, this study offers an optimal model to predict the level of industrial water pollution on the basis of BOD index (kg/day) for eight sub-sector of industry during the years 2003-2018 by GMDH algorithm in Iran. Comparison of predicted and actual amount of water pollution shows that food, wood, paper, chemicals products, non-metallic mineral products, basic metals, and sundry industries have had increasing trends but textile industry has had decreasing trend during these years. Furthermore, the highest average emission amount of water pollution is related to the industry of food production and the lowest one is related to the industry of non-metallic mineral production

کلمات کلیدی:
Water Pollution, Prediction, Industry, Group Method of Data Handling (GMDH)

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/653724/