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Journal of Tianjin Normal University(Natural Science Edition) >

2026 , Vol. 46 >Issue 2: 26 - 34

DOI: https://doi.org/10.19638/j.issn1671-1114.20260204

Geography and Environmental Sciences

Comprehensive evaluation of water quality and PMF source analysis based on Monte Carlo: A case study of Mulan River

  • LI Guangyue ,
  • CHEN Jin ,
  • LIU Jihui ,
  • SHI Chengchun ,
  • LI Li ,
  • LI Jiabing ,
  • XIE Rongrong
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  • 1. College of Environmental Science and Resource Science, Fujian Normal University, Fuzhou 350007, China;
    2. Fujian Environmental Science Research Institute, Fuzhou 350013, China;
    3. Fujian Putian Environmental Monitoring Center Station, Putian 351100, Fujian Province, China;
    4. Fujian Key Laboratory of Pollution Control and Resource Recycling, Fujian Normal University, Fuzhou 350007, China;
    5. Digital Fujian Environmental Monitoring Internet of Things Laboratory, Fujian Normal University, Fuzhou 350007, China

Received date: 2024-11-27

  Online published: 2026-06-03

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Abstract

In order to improve the accuracy and credibility of the assessment of water environment and the traceability of pollution, based on the data from six routine monitoring sections of Mulan River from 2015 to 2019, the Monte Carlo simulation method was used to calculate the comprehensive pollution index (H). The influencing factors of the comprehensive pollution index were identified through correlation and sensitivity analysis. Finally, the positive matrix factor model (PMF) was used to trace the pollution. The results showed that: ① From 2015 to 2019, the H value in the study area was 0.67-0.81, and the water quality showed an overall improvement trend except for slight fluctuations in 2017 and 2018. There was a significant deterioration from upstream to downstream, with partial improvement in P4 section and P5 section in the middle reaches, which were influenced by land use types. ② Correlation analysis showed that P3 section in upstream had the greatest impact on the regional H value in 2015 and 2018, when pollution levels were severe, while P6 section in downstream had the greatest impact on the regional H value in 2016, 2017, and 2019, when pollution levels were relatively low. Sensitivity analysis showed that TN was the main influencing indicator of the comprehensive pollution index in the studied area. ③ PMF traceability results indicated that the order of contribution rates of pollution sources in the studied area during flood season were agricultural pollution (33.5%) > domestic sewage and industrial wastewater (31.0%) > organic pollution sources (21.2%) > seasonal effects (14.3%), and the order of contribution rates of pollution sources during non-flood season were agricultural pollution (25.0%) > domestic sewage (22.0%) > seasonal effects (20.3%) > organic pollution sources (18.1%) > industrial point sources (14.6%).

Key words： Mulan River; Monte Carlo simulation; comprehensive pollution index; comprehensive pollution index; positive matrix factor decomposition model (PMF)

Cite this article

LI Guangyue , CHEN Jin , LIU Jihui , SHI Chengchun , LI Li , LI Jiabing , XIE Rongrong . Comprehensive evaluation of water quality and PMF source analysis based on Monte Carlo: A case study of Mulan River[J]. Journal of Tianjin Normal University(Natural Science Edition), 2026 , 46(2) : 26 -34 . DOI: 10.19638/j.issn1671-1114.20260204

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