IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v16y2019i24p4919-d294522.html
   My bibliography  Save this article

Spatial Variations of Trace Metals and Their Complexation Behavior with DOM in the Water of Dianchi Lake, China

Author

Listed:
  • Yuanbi Yi

    (Institute of Surface-Earth System Science, Tianjin University, Tianjin 300072, China)

  • Min Xiao

    (Tianjin Key Laboratory of Water Resources and Environment, Tianjin Normal University, Tianjin 300387, China)

  • Khan M. G. Mostofa

    (Institute of Surface-Earth System Science, Tianjin University, Tianjin 300072, China)

  • Sen Xu

    (Institute of Surface-Earth System Science, Tianjin University, Tianjin 300072, China)

  • Zhongliang Wang

    (Tianjin Key Laboratory of Water Resources and Environment, Tianjin Normal University, Tianjin 300387, China)

Abstract

The dynamics of trace metals and the complexation behavior related to organic matter in the interface between water and sediment would influence water quality and evolution in the lake system. This study characterized the distribution of trace metals and the optical properties of dissolved organic matter (DOM) on the surface, and the underlying and pore water of Dianchi Lake (DC) to understand the origin of metals and complexation mechanisms to DOM. Some species of trace metals were detected and Al, Ti, Fe, Zn, Sr and Ba were found to be the main types of metals in the aquatic environment of DC. Ti, Fe, Sr and Ba predominated in water above the depositional layer. Al, Ti, Fe and Sr were the most abundant metallic types in pore water. Mn and Zn were the main type found at the southern lake site, reflecting the contribution of pollution from an inflowing river. The correlations between DOM and metals suggested that both originated from the major source as particulate organic matter (POM), associated with weathering of Ca-, Mg-carbonate detritus and Fe- or Mn-bearing minerals. High dynamics of DOM and hydrochemical conditions would change most metal contents and speciation in different water compartments. Proportions of trace metals in dissolved organic carbon (DOC) in natural waters were correlated with both DOM molecular weight and structure, different metals were regulated by different organic properties, and the same metal also had specific binding characteristic with DOM in various water compartments. This study highlighted the interrelation of DOM and metals, as well as the pivotal role that organic matter and nutrients played during input, migrations and transformations of metals, thereby reflecting water quality evolution in the lake systems.

Suggested Citation

  • Yuanbi Yi & Min Xiao & Khan M. G. Mostofa & Sen Xu & Zhongliang Wang, 2019. "Spatial Variations of Trace Metals and Their Complexation Behavior with DOM in the Water of Dianchi Lake, China," IJERPH, MDPI, vol. 16(24), pages 1-20, December.
  • Handle: RePEc:gam:jijerp:v:16:y:2019:i:24:p:4919-:d:294522
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/16/24/4919/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/16/24/4919/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Peng Zhang & Rui-Feng Liang & Peng-Xiao Zhao & Qing-Yuan Liu & Yong Li & Kai-Li Wang & Ke-Feng Li & Ying Liu & Peng Wang, 2019. "The Hydraulic Driving Mechanisms of Cyanobacteria Accumulation and the Effects of Flow Pattern on Ecological Restoration in Lake Dianchi Caohai," IJERPH, MDPI, vol. 16(3), pages 1-24, January.
    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. Yanan Wen & Min Xiao & Zhaochuan Chen & Wenxi Zhang & Fujun Yue, 2023. "Seasonal Variations of Dissolved Organic Matter in Urban Rivers of Northern China," Land, MDPI, vol. 12(2), pages 1-18, January.

    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. Jiancai Deng & Fang Chen & Weiping Hu & Xin Lu & Bin Xu & David P. Hamilton, 2019. "Variations in the Distribution of Chl- a and Simulation Using a Multiple Regression Model," IJERPH, MDPI, vol. 16(22), pages 1-16, November.
    2. Sorin Avram & Corina Cipu & Ana-Maria Corpade & Carmen Adriana Gheorghe & Nicolae Manta & Mihaita-Iulian Niculae & Ionuţ Silviu Pascu & Róbert Eugen Szép & Steliana Rodino, 2021. "GIS-Based Multi-Criteria Analysis Method for Assessment of Lake Ecosystems Degradation—Case Study in Romania," IJERPH, MDPI, vol. 18(11), pages 1-23, May.

    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:jijerp:v:16:y:2019:i:24:p:4919-:d:294522. 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.