Urban composite non-point source (UCNPS) has an increasing degree of influence on the urban receiving waters. However, there remains a dearth of precise techniques to characterize and evaluate the contribution of UCNPS. Therefore, this study developed a source analytical methodology system based fluorescence excitation-emission matrices spectroscopy (EEMs) and Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS).Specifically, it utilized parallel factor analysis (PARAFAC), two-dimensional correlation spectroscopy (2D-COS), end-member mixing analysis (EMMA), and non-metric multidimensional scaling (NMDS) to analysis UCNPS pollution characteristics and quantify its contributions to river DOM. The results of its application in typical hilly and plain urban within the Yangtze River Basin, China revealed that road and roof runoff exhibited high aromaticity and humic-like content, and the characteristics of pipe sediment was similar with domestic sewage. The component of Rivers had sequences of changes under rainfall perturbations. But terrestrial humic-like represented the initial input in all cases, and it can provide some indication of UCNPS input. The results of EMMA showed that the contribution of road runoff, roof runoff, pipeline sediment and domestic sewage to river DOM was 9.0 %-36.0 %, 2.6 %-19.1 %, 2.3 %-28.8 % and 5.9 %-25.9 %, respectively, and the specific contribution was mainly affected by rainfall level, regional terrain and drainage system. The methodology system of this study can provide technical support for the traceability and precise control of UCNPS pollution.
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http://dx.doi.org/10.1016/j.watres.2024.122406 | DOI Listing |
Water Res
December 2024
State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; Ministry of Education Key Laboratory of Yangtze River Water Environment, Tongji University, Shanghai 200092, China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, China.
Dissolved oxygen (DO) is essential for the health of aquatic ecosystems, supporting biogeochemical cycles and the decomposition of organic matter. However, continuous untreated external inputs from illicit discharges or sewer overflows, coupled with inadequate ecological base flow, have led to widespread river deoxygenation and serious ecological crises. This study demonstrates that chlorinated wastewater treatment plant (WWTP) effluent can significantly enhance DO levels in downstream rivers, particularly in areas with high pollution loads or poor ecological base flow.
View Article and Find Full Text PDFSci Total Environ
December 2024
Institute for Water Quality and Resource Management, TU Wien, Karlsplatz 13/226, 1040 Vienna, Austria.
Fluorescence fingerprinting is a technique to uniquely characterize water samples based on their distinct composition of dissolved organic matter (DOM) measured via 3D fluorescence spectroscopy. It is an effective tool for monitoring the chemical composition of various water systems. This study examines a river affected by several municipal and industrial wastewater treatment plant (WWTP) effluents and aims to source-tracing them via fluorescence fingerprints based on parallel factor analysis (PARAFAC) components.
View Article and Find Full Text PDFWater Res
December 2024
State Key Laboratory of Pollution Control and Resource Reuse, Key Laboratory of Urban Water Supply, Water Saving and Water Environment Governance in the Yangtze River Delta of Ministry of Water Resources, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, PR China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai, 200092, PR China. Electronic address:
Restricted to the complex nature of dissolved organic matter (DOM) in various aquatic environments, the mechanisms of enhanced iodinated disinfection byproducts (I-DBPs) formation in water containing both I and IO (designated as I/IO in this study) during the ultraviolet (UV)-chloramine sequential disinfection process remains unclear. In this study, four machine learning (ML) models were established to predict I-DBP formation by using DOM and disinfection features as input variables. Extreme gradient boosting (XGB) algorithm outperformed the others in model development using synthetic waters and in cross-dataset generalization of surface waters.
View Article and Find Full Text PDFEnviron Sci Technol
December 2024
Institute of Surface-Earth System Science, School of Earth System Science, Tianjin University, Tianjin 300072, China.
The priming effect (PE) is recognized as an important mechanism influencing organic matter transformation in aquatic systems. The land-ocean aquatic continuum (LOAC) has received large quantities of dissolved organic matter (DOM) from various sources, which is an ideal interface for PE research. Here, we investigated the PE process by utilizing such a coastal environment to explore the turnover of DOM in the LOAC system.
View Article and Find Full Text PDFEnviron Monit Assess
December 2024
Collaborative Innovation Center for Water Pollution Control and Water Security in Karst Region, Guilin University of Technology, 541004, Guilin, China.
Existing models often face limitations in the understanding and prediction of nitrate nitrogen (NO-N) concentrations in karst groundwater. In this study, to tackle this issue, a Gaussian function model was coupled with the Groundwater Modeling System (GMS) to simulate NO-N concentration changes in the southwest karst wetland of China. Additionally, fluorescence spectroscopy was employed to measure dissolved organic matter (DOM) components in the groundwater, providing insights into their variation and influence on NO-N dynamics.
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