Characterizing natural separation and purification during rural polluted water self-purification in the Dashi River: a multidimensional approach to DOM and microbial interactions
File(s)
Supporting information
Accepted version
Author(s)
Xie, Jin
Graham, Nigel
Yu, Wenzheng
Sun, Kening
Liu, Ting
Type
Journal Article
Abstract
The self-purification capacity of rivers, a natural analog to engineered separation processes, mitigates pollutants through complex physicochemical and biological interactions. This study deciphers these mechanisms along Beijing's Dashi River via a spatial gradient analysis of 15 sites. We integrated size-exclusion chromatography, excitation-emission matrix fluorescence spectroscopy with parallel factor analysis (EEM-PARAFAC), and microbial community profiling to link dissolved organic matter (DOM) transformation with metabolic functions. Downstream self-purification led to a >40 % decrease in terrestrial high molecular weight (HMW) DOM and the reduction of total phosphorus to below the detection limit (0.005 mg L−1). These changes, driven by microbial consortia (e.g., Pseudomonas), simplified DOM structure (evidenced by declining humification index and SUVA₂₅₄) and reduced the formation potential of disinfection by-products by over 60 %. However, a pollution event at Site 13 overwhelmed this capacity, causing a microbial diversity crash (Shannon index decreased by 1.56) and a rebound in turbidity, nutrients, and haloacetic acid yields (76.5 μg L−1). Our findings reveal the synergistic mechanisms of river self-purification and its thresholds, providing fundamental insights for assessing the assimilative capacity and inspiring the development of water purification technologies such as bio-augmented filtration and biofilm-based processes.
Date Issued
2026-04-05
Date Acceptance
2025-12-17
Citation
Separation and Purification Technology, 2026, 386
ISSN
1383-5866
Publisher
Elsevier BV
Journal / Book Title
Separation and Purification Technology
Volume
386
Copyright Statement
Copyright © 2025 Elsevier B.V. This is the author’s accepted manuscript made available under a CC-BY licence in accordance with Imperial’s Research Publications Open Access policy (www.imperial.ac.uk/oa-policy)
License URL
Publication Status
Published
Article Number
136553
Date Publish Online
2025-12-18