Technology assessment for wastewater treatment using multiple-attribute decision-making

被引:63
|
作者
Kalbar, Pradip P. [1 ]
Karmakar, Subhankar [1 ]
Asolekar, Shyam R. [1 ]
机构
[1] Indian Inst Technol, Ctr Environm Sci & Engn, Bombay 400076, Maharashtra, India
关键词
Technology assessment; Multiple-attribute decision-making; Wastewater treatment; Sustainability assessment; Appropriate technology;
D O I
10.1016/j.techsoc.2012.10.001
中图分类号
D58 [社会生活与社会问题]; C913 [社会生活与社会问题];
学科分类号
摘要
A framework for technology assessment for wastewater treatment is proposed in this work. A case study of technology selection for high rise buildings in urban centres of India is used for evaluation and to test this framework. The multiple-attribute decision-making technique is used for ranking the alternatives. The three most commonly used wastewater treatment technologies viz., activated sludge process (ASP), sequencing batch reactors (SBR) and membrane bio-reactor (MBR) are evaluated. Seven criteria having indicators derived from life cycle assessment (LCA), life cycle costing (LCC) and criteria accounting for resource constraints, robustness of the system and sustainability are used for the evaluations. The technology assessment framework used in this work will help identify appropriate wastewater treatment technologies for various decision-making situations encountered while managing wastewaters. Importantly, this study validates the theory that it is the decision situation which decides the appropriateness of the technology and not the technology itself. Hence, the definition of appropriate technology given by Murphy et al. [4] is more convincing for water and sanitation technologies. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:295 / 302
页数:8
相关论文
共 50 条
  • [1] Selection of an appropriate wastewater treatment technology: A scenario-based multiple-attribute decision-making approach
    Kalbar, Pradip P.
    Karmakar, Subhankar
    Asolekar, Shyam R.
    JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2012, 113 : 158 - 169
  • [2] A Multiple-Attribute Decision-Making Approach to Reinforcement Learning
    Shi, Haobin
    Xu, Meng
    IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS, 2020, 12 (04) : 695 - 708
  • [3] A statistical approach to multiple-attribute decision-making with interval numbers
    Zhang, Q
    Ma, J
    Fan, ZP
    Chiang, WC
    INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2003, 34 (12-13) : 683 - 692
  • [4] Integrated project evaluation and selection using multiple-attribute decision-making technique
    Dey, Prasanta Kumar
    INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2006, 103 (01) : 90 - 103
  • [5] Grey Random Dynamic Multiple-attribute Decision-making Method
    Li, Haitao
    Wang, Jiefang
    Luo, Dang
    Pang, Dongyang
    PROCEEDINGS OF 2017 IEEE INTERNATIONAL CONFERENCE ON GREY SYSTEMS AND INTELLIGENT SERVICES (GSIS), 2017, : 221 - 229
  • [6] A statistical approach to multiple-attribute decision-making with interval numbers
    Zhang, Q. (zhang@jepson.gonzaga.edu), 1600, Taylor and Francis Ltd. (34): : 12 - 13
  • [7] AN EVIDENTIAL REASONING APPROACH FOR MULTIPLE-ATTRIBUTE DECISION-MAKING WITH UNCERTAINTY
    YANG, JB
    SINGH, MG
    IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1994, 24 (01): : 1 - 18
  • [8] Am method for multiple-attribute decision-making with incomplete attribute weight information
    Zhang, Y
    Fan, ZP
    Yu, CH
    PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT, VOLS 1 AND 2: MODERN INDUSTRIAL ENGINEERING AND INNOVATION IN ENTERPRISE MANAGEMENT, 2005, : 645 - 648
  • [9] Linguistic attribute hierarchies for multiple-attribute decision making
    Lawry, Jonathan
    He, Hongmei
    2007 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-4, 2007, : 1584 - 1589
  • [10] Multiple-Attribute Decision-Making Using Fermatean Fuzzy Hamacher Interactive Geometric Operators
    Shahzadi, Gulfam
    Zafar, Fariha
    Alghamdi, Maha Abdullah
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2021, 2021