IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v35y2021i15d10.1007_s11269-021-03013-z.html
   My bibliography  Save this article

Assessment the Quality of Bottled Drinking Water Through Mamdani Fuzzy Water Quality Index

Author

Listed:
  • Ghorban Asgari

    (Social Determinants of Health Research Center (SDHRC), Hamadan University of Medical Sciences)

  • Ensieh Komijani

    (Social Determinants of Health Research Center (SDHRC), Hamadan University of Medical Sciences)

  • Abdolmotaleb Seid-Mohammadi

    (Social Determinants of Health Research Center (SDHRC), Hamadan University of Medical Sciences)

  • Mohammad Khazaei

    (Hamadan University of Medical Sciences)

Abstract

In this investigation, an innovative index was developed based on the fuzzy inference system for assessing the quality of bottled drinking waters. A method was developed to aggregate the values obtained from the defuzzification step. A total number of 24 quality parameters revealing the characteristics of bottled were in terms of physiochemical, dietary, toxic, and pathogenic aspects were selected as the input parameters. 30 samples were taken from the independent brands found in the Hamadan province retail market to evaluate the bottled water quality index (BWQI). Results show that the values obtained from measuring the parameters are in the range of the standard levels set by national regulations. The BWQI scores obtained from samples were in the range of 61.2-73.8 attributing to the marginal and fair descriptive classes. The drinking bottled water samples had better scores because of low contents of NO3, NO2, Fe, Mn, Cu, and Zn that are subjugated public distribution systems having the severe standards on urban water treatment plants for in case safe water. The mineral bottled water samples examination indicated that they are generally affected by the mineral contents of sedimentary rocks and NO3 leaks from fertilizers used in the agricultural doings and also they do not elaborate the rigorous scrutiny system alike those donned in the public water distribution systems. Sensitivity analysis using the Monte Carlo algorithm reveals that the parameters NO3, Na, hardness, and NO2 have the most impact on the BWQI scores.

Suggested Citation

  • Ghorban Asgari & Ensieh Komijani & Abdolmotaleb Seid-Mohammadi & Mohammad Khazaei, 2021. "Assessment the Quality of Bottled Drinking Water Through Mamdani Fuzzy Water Quality Index," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(15), pages 5431-5452, December.
    • Handle: RePEc:spr:waterr:v:35:y:2021:i:15:d:10.1007_s11269-021-03013-z
    DOI: 10.1007/s11269-021-03013-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-021-03013-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11269-021-03013-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Margaret W. Gitau & Jingqiu Chen & Zhao Ma, 2016. "Water Quality Indices as Tools for Decision Making and Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(8), pages 2591-2610, June.
    2. W. Kip Viscusi & Joel Huber & Jason Bell, 2015. "The Private Rationality Of Bottled Water Drinking," Contemporary Economic Policy, Western Economic Association International, vol. 33(3), pages 450-467, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mojtaba Poursaeid & Amir Houssain Poursaeid & Saeid Shabanlou, 2022. "A Comparative Study of Artificial Intelligence Models and A Statistical Method for Groundwater Level Prediction," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(5), pages 1499-1519, March.
    2. Zehai Gao & Yang Liu & Nan Li & Kangjie Ma, 2022. "An Enhanced Beetle Antennae Search Algorithm Based Comprehensive Water Quality Index for Urban River Water Quality Assessment," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(8), pages 2685-2702, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Le Duc Anh & Ho Huu Loc & Kim N. Irvine & Tran Thanh & Luong Quang Tuong, 2021. "The waterscape of groundwater exploitation for domestic uses in District 12, Ho Chi Minh City, Vietnam," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(5), pages 7652-7669, May.
    2. Mohammad Ali Baghapour & Mohammad Reza Shooshtarian & Mahdi Zarghami, 2020. "Process Mining Approach of a New Water Quality Index for Long-Term Assessment under Uncertainty Using Consensus-Based Fuzzy Decision Support System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(3), pages 1155-1172, February.
    3. Russell Triplett & Chiradip Chatterjee & Christopher K. Johnson & Parvez Ahmed, 2019. "Perceptions of Quality and Household Water Usage: A Representative Study in Jacksonville, FL," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 25(2), pages 195-208, May.
    4. Valeria Mijares & Margaret Gitau & David R. Johnson, 2019. "A Method for Assessing and Predicting Water Quality Status for Improved Decision-Making and Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(2), pages 509-522, January.
    5. Ruoyu Wang & Huajin Chen & Yuzhou Luo & Patrick Moran & Michael Grieneisen & Minghua Zhang, 2019. "Nitrate Runoff Contributing from the Agriculturally Intensive San Joaquin River Watershed to Bay-Delta in California," Sustainability, MDPI, vol. 11(10), pages 1-16, May.
    6. David Bautista & Carlos Peña-Guzmán, 2019. "Simulating the Hydrological Impact of Green Roof Use and an Increase in Green Areas in an Urban Catchment with i-Tree: A Case Study with the Town of Fontibón in Bogotá, Colombia," Resources, MDPI, vol. 8(2), pages 1-14, April.
    7. Yaoze Liu & Sisi Li & Carlington W. Wallace & Indrajeet Chaubey & Dennis C. Flanagan & Lawrence O. Theller & Bernard A. Engel, 2017. "Comparison of Computer Models for Estimating Hydrology and Water Quality in an Agricultural Watershed," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(11), pages 3641-3665, September.
    8. Paul W. Ballantine & Lucie K. Ozanne & Rachel Bayfield, 2019. "Why Buy Free? Exploring Perceptions of Bottled Water Consumption and Its Environmental Consequences," Sustainability, MDPI, vol. 11(3), pages 1-11, February.
    9. Vanaja, Shiuli, 2021. "Are People Making Correct Choices? Drivers of Water Source Choices in Rural Jharkhand, India," 2021 Conference, August 17-31, 2021, Virtual 315156, International Association of Agricultural Economists.
    10. Yaoze Liu & Indrajeet Chaubey & Laura C. Bowling & Vincent F. Bralts & Bernard A. Engel, 2016. "Sensitivity and Uncertainty Analysis of the L-THIA-LID 2.1 Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(13), pages 4927-4949, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:35:y:2021:i:15:d:10.1007_s11269-021-03013-z. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.