IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i10p8048-d1147500.html
   My bibliography  Save this article

Current and Previous Green Technologies, Their Efficiency, Associated Problems, and Success Rates to Mitigate M. aeruginosa in Aquatic Environments

Author

Listed:
  • Zobia Khatoon

    (Numerical Simulation Group for Water Environment, Key Laboratory of Pollution Processes and Environmental Criteria of the Ministry of Education, Tianjin Key Laboratory of Remediation and Pollution Control for Urban Ecological Environment, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China)

  • Suiliang Huang

    (Numerical Simulation Group for Water Environment, Key Laboratory of Pollution Processes and Environmental Criteria of the Ministry of Education, Tianjin Key Laboratory of Remediation and Pollution Control for Urban Ecological Environment, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China)

  • Ahmer Bilal

    (Shandong Provincial Key Laboratory of Depositional Mineralization & Sedimentary Minerals, Shandong University of Science and Technology, Qingdao 260043, China)

  • Hammad Tariq Janjuhah

    (Department of Geology, Shaheed Benazir Bhutto University Sheringal, Upper Dir 18000, Pakistan)

  • George Kontakiotis

    (Department of Historical Geology-Paleontology, Faculty of Geology and Geoenvironment, School of Earth Sciences, National and Kapodistrian University of Athens, 15784 Athens, Greece)

  • Assimina Antonarakou

    (Department of Historical Geology-Paleontology, Faculty of Geology and Geoenvironment, School of Earth Sciences, National and Kapodistrian University of Athens, 15784 Athens, Greece)

  • Evangelia Besiou

    (Department of Historical Geology-Paleontology, Faculty of Geology and Geoenvironment, School of Earth Sciences, National and Kapodistrian University of Athens, 15784 Athens, Greece)

  • Mengjiao Wei

    (Numerical Simulation Group for Water Environment, Key Laboratory of Pollution Processes and Environmental Criteria of the Ministry of Education, Tianjin Key Laboratory of Remediation and Pollution Control for Urban Ecological Environment, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China)

  • Rui Gao

    (Numerical Simulation Group for Water Environment, Key Laboratory of Pollution Processes and Environmental Criteria of the Ministry of Education, Tianjin Key Laboratory of Remediation and Pollution Control for Urban Ecological Environment, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China)

  • Tianqi Zhang

    (Numerical Simulation Group for Water Environment, Key Laboratory of Pollution Processes and Environmental Criteria of the Ministry of Education, Tianjin Key Laboratory of Remediation and Pollution Control for Urban Ecological Environment, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China)

  • Ling Li

    (Numerical Simulation Group for Water Environment, Key Laboratory of Pollution Processes and Environmental Criteria of the Ministry of Education, Tianjin Key Laboratory of Remediation and Pollution Control for Urban Ecological Environment, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China)

Abstract

Frequent M. aeruginosa outbreaks pose a major risk to public health and have a detrimental effect on aquatic ecosystems. Researchers are looking into ways to stop and control M. aeruginosa blooms, a problem that affects both the aquatic environment and human health significantly. It is important to develop proper monitoring methods to identify M. aeruginosa blooms. However, the existing control and monitoring techniques have some drawbacks that limit the field’s applicability. Therefore, we must improve current methods for effectively monitoring and controlling M. aeruginosa blooms. Mitigation strategies should be customized for particular bodies of water utilizing techniques that are fast, economical, and field-applicable. This review critically identifies and evaluates green technologies, especially those focused on the presence of M. aeruginosa in freshwater, and compares and discusses problems with these green technologies. Furthermore, they were characterized and ranked according to their cost, effectiveness, and field applicability. A few suggestions for improvements were provided, along with ideas for future research projects that would take anticipated environmental changes into account.

Suggested Citation

  • Zobia Khatoon & Suiliang Huang & Ahmer Bilal & Hammad Tariq Janjuhah & George Kontakiotis & Assimina Antonarakou & Evangelia Besiou & Mengjiao Wei & Rui Gao & Tianqi Zhang & Ling Li, 2023. "Current and Previous Green Technologies, Their Efficiency, Associated Problems, and Success Rates to Mitigate M. aeruginosa in Aquatic Environments," Sustainability, MDPI, vol. 15(10), pages 1-26, May.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:10:p:8048-:d:1147500
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/10/8048/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/10/8048/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yun Hwan Park & Sok Kim & Ho Seon Kim & Chulhwan Park & Yoon-E Choi, 2020. "Adsorption Strategy for Removal of Harmful Cyanobacterial Species Microcystis aeruginosa Using Chitosan Fiber," Sustainability, MDPI, vol. 12(11), pages 1-12, June.
    2. Donald M. Anderson, 1997. "Turning back the harmful red tide," Nature, Nature, vol. 388(6642), pages 513-514, August.
    3. Bin Zhang & Ying Yang & Wenjia Xie & Wei He & Jia Xie & Wei Liu, 2022. "Identifying Algicides of Enterobacter hormaechei F2 for Control of the Harmful Alga Microcystis aeruginosa," IJERPH, MDPI, vol. 19(13), pages 1-16, June.
    Full references (including those not matched with items on IDEAS)

    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. Byungkwan Jeong & Eui-Suk Jeong & Jacqueline Martha Malazarte & Yongsik Sin, 2016. "Physiological and Molecular Response of Prorocentrum minimum to Tannic Acid: An Experimental Study to Evaluate the Feasibility of Using Tannic Acid in Controling the Red Tide in a Eutrophic Coastal Wa," IJERPH, MDPI, vol. 13(5), pages 1-13, May.
    2. Guo, Qing & Wang, Yi & Dai, Chuanjun & Wang, Lijun & Liu, He & Li, Jianbing & Tiwari, Pankaj Kumar & Zhao, Min, 2023. "Dynamics of a stochastic nutrient–plankton model with regime switching," Ecological Modelling, Elsevier, vol. 477(C).
    3. Vanhoutte-Brunier, Alice & Fernand, Liam & Ménesguen, Alain & Lyons, Sandra & Gohin, Francis & Cugier, Philippe, 2008. "Modelling the Karenia mikimotoi bloom that occurred in the western English Channel during summer 2003," Ecological Modelling, Elsevier, vol. 210(4), pages 351-376.
    4. Liu, Chao & Wang, Luping & Zhang, Qingling & Yan, Yun, 2017. "Dynamical analysis in a bioeconomic phytoplankton zooplankton system with double time delays and environmental stochasticity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 682-698.
    5. Liu, Chao & Yu, Longfei & Zhang, Qingling & Li, Yuanke, 2018. "Dynamic analysis of a hybrid bioeconomic plankton system with double time delays and stochastic fluctuations," Applied Mathematics and Computation, Elsevier, vol. 316(C), pages 115-137.
    6. Xiangzheng Ren & Zhiming Yu & Lixia Qiu & Xihua Cao & Xiuxian Song, 2021. "Effects of Modified Clay on Phaeocystis globosa Growth and Colony Formation," IJERPH, MDPI, vol. 18(19), pages 1-17, September.
    7. Liu, He & Dai, Chuanjun & Yu, Hengguo & Guo, Qing & Li, Jianbing & Hao, Aimin & Kikuchi, Jun & Zhao, Min, 2023. "Dynamics of a stochastic non-autonomous phytoplankton–zooplankton system involving toxin-producing phytoplankton and impulsive perturbations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 203(C), pages 368-386.
    8. Xiangfeng Bu & Kai Liu & Jingyu Liu & Yunhong Ding, 2023. "A Harmful Algal Bloom Detection Model Combining Moderate Resolution Imaging Spectroradiometer Multi-Factor and Meteorological Heterogeneous Data," Sustainability, MDPI, vol. 15(21), pages 1-26, 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:gam:jsusta:v:15:y:2023:i:10:p:8048-:d:1147500. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.