Temporal trends and source apportionment of water pollution in Honghu Lake, China

被引:16
|
作者
Chen, Shuai [1 ,2 ]
Wang, Simeng [1 ]
Yu, Yanxi [3 ]
Dong, Mingjun [1 ]
Li, Yanqiang [1 ]
机构
[1] Hubei Univ, Coll Resources & Environm, Wuhan 430062, Hubei, Peoples R China
[2] Wuhan Kunjian Ecol Environm Planning & Design Co, Wuhan 430062, Hubei, Peoples R China
[3] Univ Sydney, Sch Chem & Biomol Engn, Darlington, NSW 2006, Australia
基金
国家重点研发计划;
关键词
Water quality; Temporal trend; CCME-WQI; Source apportionment; Water pollution control; MULTIVARIATE STATISTICAL TECHNIQUES; ECOLOGICAL RISK-ASSESSMENT; SURFACE-WATER; HEAVY-METALS; QUALITY ASSESSMENT; SOURCE IDENTIFICATION; SPATIAL-DISTRIBUTION; NUTRIENT TRANSPORT; TRACE-ELEMENTS; RIVER-BASIN;
D O I
10.1007/s11356-021-14828-z
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Honghu Lake, the largest shallow lake in Jianghan Plain of China, is essential for maintaining ecosystem functioning in this region. However, water pollution and high disturbance are seriously threatening the ecological security of this lake. To explore the causes of water quality fluctuations in Honghu Lake, the water quality index method (CCME-WQI), multivariate statistical, and source apportionment techniques were adopted to characterize temporal trends in lake water quality (2004-2017), identify the main driving factors of water quality indicators, and quantify the contribution of various pollution sources. Besides, the water periods of the lake have been reclassified due to the seasonal variation of rainfall in the study area. The results of CCME-WQI showed that the water quality in Honghu Lake initially improved over 2004-2011, with better water quality in the wet period than in the dry periods, while the results over 2012-2017 were found to be opposite. Correlation analysis identified untreated industrial wastewater (UIW) as the main pollution source affecting CODMn concentrations in Honghu Lake, while untreated domestic sewage discharge (UDS) was identified as the main pollution source affecting BOD and F. coli concentrations. The main pollution sources affecting nutrient indicators were rainfall and enclosure aquaculture (EA). Principal component analysis (PCA) combined with absolute principal component score-multiple linear regression model (APCS-MLR) further appointed the source contribution of each pollution source to water quality indicators. The results showed that EA in 2012 was reduced by 81% compared with 2004, resulting in the contribution of EA to NH3-N, TP, and TN decreased by 0.2 mg L-1, 0.039 mg L-1, and 0.37 mg L-1, respectively. Compared with 2012, UIW was reduced by 65% in 2016, resulting in the contribution of UIW to CODMn decreased by 1.17 mg L-1. In addition, compared with 2004, UDS decreased by 85% in 2016, and the contribution of UDS to BOD and F. coli decreased by 0.7 mg L-1 and 887 cfu L-1, respectively. Based on the results of APCS-MLR, it was predicted that the concentrations of COD and TP in Honghu Lake would meet the water quality requirements after 2017. However, the rainfall non-point source pollution must be further controlled to achieve the desired level of TN concentration. This study provided an accurate method for analyzing lake water pollution, and the results can provide a valuable reference for optimizing water quality management and pollution control strategies within Honghu Lake.
引用
收藏
页码:60130 / 60144
页数:15
相关论文
共 50 条
  • [21] Application of Composite Water Quality Identification Index on the water quality evaluation in spatial and temporal variations: a case study in Honghu Lake, China
    Ban, Xuan
    Wu, Qiuzhen
    Pan, Baozhu
    Du, Yun
    Feng, Qi
    ENVIRONMENTAL MONITORING AND ASSESSMENT, 2014, 186 (07) : 4237 - 4247
  • [22] Present status of organochlorine pesticides contamination in water from Honghu Lake, China
    Gong, Xiangyi
    Qi, Shihua
    Wang, Yanxin
    2010 4TH INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICAL ENGINEERING (ICBBE 2010), 2010,
  • [23] Particulate pollution in urban Chongqing of southwest China: Historical trends of variation, chemical characteristics and source apportionment
    Chen, Yuan
    Xie, Shao-dong
    Luo, Bin
    Zhai, Chong-zhi
    SCIENCE OF THE TOTAL ENVIRONMENT, 2017, 584 : 523 - 534
  • [24] Application of Composite Water Quality Identification Index on the water quality evaluation in spatial and temporal variations: a case study in Honghu Lake, China
    Xuan Ban
    Qiuzhen Wu
    Baozhu Pan
    Yun Du
    Qi Feng
    Environmental Monitoring and Assessment, 2014, 186 : 4237 - 4247
  • [25] Spatial variation and source apportionment of water pollution in Qiantang River (China) using statistical techniques
    Huang, Fang
    Wang, Xiaoquan
    Lou, Liping
    Zhou, Zhiqing
    Wu, Jiaping
    WATER RESEARCH, 2010, 44 (05) : 1562 - 1572
  • [26] Hydrochemical evaluation of surface water quality and pollution source apportionment in the Luan River basin, China
    Wang, Huiliang
    Li, Xuyong
    Xie, Ying
    WATER SCIENCE AND TECHNOLOGY, 2011, 64 (10) : 2119 - 2125
  • [27] Source Apportionment of Heavy Metals in the Sediments of Hongfeng Lake, China
    Jiang, Hong
    A, Yinglan
    Kitano, Masaharu
    Fu, Qing
    Wang, Guoqiang
    Zheng, Binghui
    JOURNAL OF THE FACULTY OF AGRICULTURE KYUSHU UNIVERSITY, 2012, 57 (01): : 195 - 199
  • [28] Research Advances of Groundwater Nitrate Pollution and Source Apportionment in China
    Tu C.-L.
    Chen Q.-S.
    Yin L.-H.
    Li Q.
    He C.-Z.
    Liu Z.-N.
    Huanjing Kexue/Environmental Science, 2024, 45 (06): : 3129 - 3141
  • [29] Distribution, pollution status, and source apportionment of trace metals in lake sediments under the influence of the South-to-North Water Transfer Project, China
    Zhuang, Wen
    Ying, Samantha C.
    Frie, Alexander L.
    Wang, Qian
    Song, Jinming
    Liu, Yongxia
    Chen, Qing
    Lai, Xiaoying
    SCIENCE OF THE TOTAL ENVIRONMENT, 2019, 671 : 108 - 118
  • [30] Characteristics and Source Apportionment of VOCs in a City with Complex Pollution in China
    Wang, Yu
    Yang, Guang
    Wang, Litao
    Zhao, Le
    Ji, Shangping
    Qi, Mengyao
    Lu, XiaoHan
    Liu, Zhentong
    Tan, Jingyao
    Liu, Yingying
    Wang, Qing
    Xu, Ruiguang
    AEROSOL AND AIR QUALITY RESEARCH, 2020, 20 (10) : 2196 - 2210