New insights into pollution source analysis using receptor models in the upper Yangtze river basin: Effects of land use on source identification and apportionment

被引：9
作者：
Ren X. [1 ]
Zhang H. [1 ]
Xie G. [1 ]
Hu Y. [1 ]
Tian X. [2 ]
Gao D. [2 ]
Guo S. [3 ]
Li A. [4 ]
Chen S. [1 ]
机构：
[1] Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu
[2] Sichuan Academy of Environmental Science, Chengdu
[3] China 19th Metallurgical Corporation, Chengdu
[4] College of Environment Sciences, Sichuan Agricultural University, Chengdu
来源：
Chemosphere | 2023年 / 334卷
基金：
中国国家自然科学基金;
关键词：
Land use; Receptor model; Redundancy analysis; River contaminants; Source analysis;
D O I：
10.1016/j.chemosphere.2023.138967
中图分类号：
学科分类号：
摘要：
To effectively control pollution and improve water quality, it is essential to accurately analyze the potential pollution sources in rivers. The study proposes a hypothesis that land use can influence the identification and apportionment of pollution sources and tested it in two areas with different types of water pollution and land use. The redundancy analysis (RDA) results showed that the response mechanisms of water quality to land use differed among regions. In both regions, the results indicated that the water quality response relationship to land use provided important objective evidence for pollution source identification, and the RDA tool optimized the procedure of source analysis for receptor models. Positive matrix decomposition (PMF) and absolute principal component score-multiple linear regression (APCS-MLR) receptor models identified five and four pollution sources along with their corresponding characteristic parameters. PMF attributed agricultural nonpoint sources (23.8%) and domestic wastewater (32.7%) as the major sources in regions 1 and 2, respectively, while APCS-MLR identified mixed sources in both regions. In terms of model performance parameters, PMF demonstrated better-fit coefficients (R2) than APCS-MLR and had a lower error rate and proportion of unidentified sources. The results show that considering the effect of land use in the source analysis can overcome the subjectivity of the receptor model and improve the accuracy of pollution source identification and apportionment. The results of the study can help managers clarify the priorities of pollution prevention and control, and provide a new methodology for water environment management in similar watersheds. © 2023
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共 103 条
  • [81] Wang Y., Duan X., Wang L., Zou H., Spatial temporal patterns and driving factors of industrial pollution and structures in the Yangtze River Economic Belt, Chemosphere, 303, (2022)
  • [82] Wu J., Li P., Wang D., Ren X., Wei M., Statistical and multivariate statistical techniques to trace the sources and affecting factors of groundwater pollution in a rapidly growing city on the Chinese Loess Plateau, Hum. Ecol. Risk Assess., 26, pp. 1603-1621, (2020)
  • [83] Wu N., Schmalz B., Fohrer N., Development and testing of a phytoplankton index of biotic integrity (P-IBI) for a German lowland river, Ecol. Indicat., 13, pp. 158-167, (2012)
  • [84] Xiao J., Gao D., Zhang H., Shi H., Chen Q., Li H., Ren X., Chen Q., Water quality assessment and pollution source apportionment using multivariate statistical techniques: a case study of the Laixi River Basin, China, Environ. Monit. Assess., 195, (2023)
  • [85] Xie D., Li X., Zhou T., Feng Y., Estimating the contribution of environmental variables to water quality in the postrestoration littoral zones of Taihu Lake using the APCS-MLR model, Sci. Total Environ., 857, (2023)
  • [86] Xin Y., Sun B., Zhu X., Yan Z., Zhao X., Sun X., Resourceful treatment of alcohol distillery wastewater by pulsed discharge, Bioresour. Technol., 244, pp. 175-181, (2017)
  • [87] Xu F., Li P., Chen W., He S., Li F., Mu D., Elumalai V., Impacts of land use/land cover patterns on groundwater quality in the Guanzhong Basin of northwest China, Geocarto Int., 37, pp. 16769-16785, (2022)
  • [88] Xu Y., Wang X., Cui G., Li K.L., Li Y., Yao B., Zhiliang, Source apportionment and ecological and health risk mapping of soil heavy metals based on PMF, SOM, and GIS methods in Hulan River Watershed, Northeastern China, Environ. Monit. Assess., 194, (2022)
  • [89] Yang B., Zhou L., Xue N., Li F., Li Y., Vogt R.D., Cong X., Yan Y., Liu B., Source apportionment of polycyclic aromatic hydrocarbons in soils of Huanghuai Plain, China: comparison of three receptor models, Sci. Total Environ., 443, pp. 31-39, (2013)
  • [90] Yang C., Zeng Z., Zhang H., Gao D., Wang Y., He G., Liu Y., Wang Y., Du X., Distribution of sediment microbial communities and their relationship with surrounding environmental factors in a typical rural river, Southwest China, Environ. Sci. Pollut. Control Ser., 29, pp. 84206-84225, (2022)
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