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بهینه‌سازی زنجیره تأمین آب آب‌شیرین‌کن اسمز معکوس با رویکرد اقتصادی و زیست‌محیطی (پژوهش موردی زنجیره تأمین آب آب‌شیرین‌کن در استان هرمزگان) | ||
| محیط شناسی | ||
| مقاله 12، دوره 45، شماره 4، اسفند 1398، صفحه 773-786 اصل مقاله (972.75 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/jes.2020.292534.1007945 | ||
| نویسندگان | ||
| محمدرضا مهرگان1؛ حنان عموزاد مهدیرجی1؛ شهاب بینائی* 2؛ ولی علی پور3؛ حسین رضوی حاجی آقا4 | ||
| 1گروه مدیریت صنعتی، دانشکده مدیریت، دانشگاه تهران، تهران، ایران | ||
| 2گروه مدیریت صنعتی، پردیس بین المللی کیش دانشگاه تهران، کیش، ایران | ||
| 3دانشکده بهداشت، دانشگاه علوم پزشکی هرمزگان، بندرعباس، ایران | ||
| 4دانشکده مدیریت، دانشگاه خاتم، تهران، ایران | ||
| چکیده | ||
| مدیریت زنجیره تأمین پایدار، تعاملات بین ابعاد اقتصادی، زیست‌محیطی و اجتماعی را در برمی‌گیرد. این پژوهش، مدل ریاضی برنامه‌ریزی خطی طراحی زنجیره تأمین آب آب‌شیرین‌کن اسمز معکوس برای بهینه‌سازی ارزش فعلی خالص هزینه‌های سرمایه‌گذاری و بهره‌برداری کارخانه‌های آب‌شیرین‌کن، خطوط لوله انتقال آب و هزینه‌های زیست‌محیطی برای افق زمانی را معرفی می‌کند. هزینه‌های زیست‌محیطی شامل هزینه‌های مالیاتی ناشی از تولید گاز گلخانه‌ای CO2 و هزینه‌های زیست‌محیطی رقیق‌سازی پساب قبل از ورود به دریا است. مدل برای مطالعه موردی زنجیره تأمین آب آب‌شیرین‌کن اسمز معکوس پنج شهر در استان هرمزگان در افق زمانی 20 ساله پس از کدگذاری در نرم‌افزار متلب حل‌شده است. سهم هزینه بخش‌های زنجیره تأمین آب آب‌شیرین‌کن در بندرعباس با احتساب هزینه‌های زیست‌محیطی برحسب دلار آمریکا در مترمکعب آب شیرین و درصد شامل هزینه کل زنجیره تأمین 0.5334 (100%)، کارخانه آب‌شیرین‌کن 0.3640 (68.24%)، خط انتقال 0.0458 (8.59%)، مالیات دی‌اکسید کربن 0.0885 (16.59%) و رقیق‌سازی پساب 0.0351 (6.58%) است. هرچقدر هزینه رقیق‌سازی پساب بیشتر شود تأثیرات زیست‌محیطی بیشتر کاهش می‌یابد و برعکس. همچنین با کاهش مصرف انرژی سوخت‌های فسیلی در آب‌شیرین‌کن‌ها مقدار گاز CO2 کاهش می‌یابد. برنامه ریزان منابع آب می‌توانند از مدل ریاضی ارائه‌شده و نتایج این پژوهش برای گسترش ظرفیت آب‌شیرین‌کن استفاده کنند. | ||
| کلیدواژه‌ها | ||
| زنجیره تأمین آب آب‌شیرین‌کن؛ آب‌شیرین‌کن اسمز معکوس؛ مدل ریاضی؛ مدیریت زنجیره تأمین پایدار؛ تأثیر زیست‌محیطی | ||
| عنوان مقاله [English] | ||
| Optimization of Reverse Osmosis Water Desalination Supply Chain with Economic and Environmental Approach (Case Study: Water Desalination Supply Chain in Hormozgan Province) | ||
| نویسندگان [English] | ||
| Mohammad Reza Mehregan1؛ Hannan Amoozad Mahdiraji1؛ Shahab Binaee2؛ Vali Alipoor3؛ Hosein Razavi Haji Agha4 | ||
| 1Department of Industrial Management, Faculty of Management, University of Tehran, Tehran, Iran | ||
| 2Department of Industrial Management, Kish International Campus, University of Tehran, Kish, Iran | ||
| 3Faculty of Health, Hormozgan University of Medical Sciences , Bandar Abbas, Iran | ||
| 4Department of Management, Khatam University, Tehran, Iran | ||
| چکیده [English] | ||
Introduction The importance of examining the economic and environmental impacts of water purification using desalination technology and the supply of desalinated water according to the supply chain allows the decision maker to examine the system as a whole. For example, any delay in the distribution of water from storage tanks to consumers could disrupt the desalination process and affect overall performance of the water desalination supply chain. The activities of the desalination water supply chain include the acquisition of feed water and chemicals needed for desalination processes, the desalination process system, the storage of produced water and the distribution of fresh water to end users. Environmental impacts of reverse osmosis desalination can be broadly classified into three categories, including energy consumption, intakes and outfalls. Desalination outfalls results in known environmental impacts in seagrass habitats and phytoplankton communities, invertebrates and fish in areas surrounding outfalls. In this study, the environmental impacts of energy consumption resulting in CO2 emissions and the cost of dilution pre-discharge effluents that reduce the environmental impacts of salinity and chemicals are investigated. Most of the models mentioned in the literature have focused on optimizing the economic dimension of water supply systems. However, in the mathematical model they have neglected to detail the environmental aspects. This research has expanded the economic model presented by Al-Nory, et al. 2014, For the water supply supply chain in a way that considers environmental detail in addition to being able to minimize total investment and operational costs. According to library studies and searches so far in Iran, no research has been conducted to optimize reverse osmosis water supply chain with economic and environmental approach and this is the first research of its kind. Matherials & Methods The research method was based on Saunders research onion model. This research in terms of orientation is Developmental at design stage and is applied at test stage in organizations and industries. The data collection method is a study of documents, articles and semi-structured interviews for the purpose of conducting research. To conduct a case study, the supply chain of water desalination plants in five cities of Hormozgan province including Abu Musa, Bandar Abbas, Dargahan Qeshm, Sirik and Hormoz Island was selected. A supply chain network is assumed to be a graph G = (V, E) where V is the set of vertices containing relation (1) (1) V=N^s∪N^a∪N^d Where Nd represents the set of demand locations, Na the set of aggregator locations, and Ns the set of desalination plant locations. The objective function specified in relation (2) minimizes the total cost of investment and operation of both the plant and the water pipeline in supply chain. It also minimizes environmental impacts. (2) minTC=∑_(〖lN〗^s)▒〖c_l^T+c_l^enviT+∑_iE▒c_i^N 〗 Total water cost (TWC) is often cited in the literature of the desalination industry as a common comparison between projects. Table 1 compares the total cost of the objective functions and their components per cubic meter of fresh water. Table 1- Comparison of total cost of objective functions and their components per cubic meter of fresh water objective functions with its components Cost of one cubic meter of fresh water in US dollars (US $ / m3) TWC1 Plant - Total Investment, Operation, and Environmental Costs (Salinity Reduction + CO2) TWC2 Plant - Total Cost of Investment, Operation and Environment (Salinity Reduction) TWC3 Plant - Total investment and Operation costs, no environmental costs TWC4 Water pipeline - Total investment and Operation costs TWC5 Plant plus Water pipeline - Total Investment, Operation and Environmental Costs (Salinity Reduction + CO2) TWC6 Plant Plus Water pipeline - Total Investment, Operation, and Environmental Costs (Salinity Reduction) TWC7 Plant Plus Water pipeline - Total Investment and Operation Costs, No Environmental Costs TWC8 Environment - Costs (CO2 + Salinity Reduction) TWC9 Environment - Costs (CO2) TWC10 Environment - Costs (Salinity Reduction) Discussion of Results The mathematical model was coded in MATLAB software and solved using the opti- intlinprog solver from the OPTI TOOL BOX software suite. By modifying the parameters, the model sensitivity analysis and validated. Also, the model for water supply chain of existing water desalination towns of Abu Musa, Bandar Abbas, Dargahan Qeshm, Sirik and Hormuz is solved based on input data for 20 year time horizon presented in Table 2. Table 2. Comparison of total cost of objective functions and their components in terms of cubic meters of fresh water objective functions with its components unit Abu Musa Bandar Abbas Dargahan Qeshm Sirik Hormuz TWC1 US$/m3 0.6250 0.4875 0.6028 0.6122 0.6346 TWC2 US$/m3 0.5366 0.3991 0.5144 0.5238 0.5461 TWC3 US$/m3 0.4872 0.3640 0.4683 0.4759 0.4951 TWC4 US$/m3 0.1458 0.0458 0.0806 0.0698 0.1849 TWC5 US$/m3 0.7708 0.5333 0.0806 0.6820 0.8195 TWC6 US$/m3 0.6824 0.4449 0.5950 0.5936 0.7311 TWC7 US$/m3 0.6330 0.4098 0.5489 0.5457 0.6800 TWC8 US$/m3 0.1378 0.1235 0.1345 0.1363 0.1395 TWC9 US$/m3 0.0885 0.0885 0.0885 0.0885 0.0885 TWC10 US$/m3 0.0494 0.0351 0.0461 0.0479 0.0510 (Reference: Authors) Conclusions This research considers the optimization model of strategic and operational decisions with respect to the planning time horizon. The most important strategic and operational decisions modeled that are include optimizing the net present value of the costs of investing and operating the desalination plants, the environment, and water pipelines. Environmental costs include costs of CO2 emissions and brine diluting to reduce the environmental impacts of brine salinity and chemicals over the planning time horizon. The results show that the cost of freshwater is lower than the cost of research literature, mainly due to the low cost of subsidized energy in Iran. Regarding the objective function to reduce the environmental impacts of the brine salinity, the results show that the environmental objective is opposite to the cost objective. The higher the cost, the greater reduce the environmental impact, and the lower the cost, the greater the environmental impact. As the cost of brine disposal increases, freshwater production becomes more expensive. The Bandar Abbas desalination plant with a nominal capacity of 100,000 cubic meters per day generates 100,053,800 kg of greenhouse gas CO2 annually. Reducing energy consumption reduces the amount of greenhouse gas CO2. Recycling energy can partially reduce energy consumption to reduce CO2 emissions. But the main solution is to use renewable energy instead of fossil fuels. This research has some suggestions for future research including: 1- Complete Water Resources Optimization Model of Bandar Abbas City including Groundwater and Surface Water (Dams and Desalination Water) to Meet Water Needs and Understand the Real Value of Freshwater in a Sustainable Integrated Water Resources Planning Model, 2 - Consider the small components of investment, operating and environmental costs of the water desalination plant and other parts of the supply chain in a mathematical model to optimize and analyze them. | ||
| کلیدواژه‌ها [English] | ||
| Water Desalination Supply Chain (WDSC), Revers Osmosis Water Desalination, Mathematical Model, Sustainable supply chain management, Environmental impact | ||
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