Network-Based Methods for Deciphering the Oxidizability of Complex Leachate DOM with ^•OH/O₃ via Molecular Signatures

Area of Science:

• Environmental Chemistry
• Water Treatment Technologies
• Analytical Chemistry

Background:

• Landfill leachates contain complex dissolved organic matter (DOM) with unclear links between its components and oxidizability.
• Understanding DOM's molecular structure is crucial for effective treatment of concentrated leachates.

Purpose of the Study:

• To resolve the molecular signatures of DOM oxidized by hydroxyl radicals (•OH) and ozone (O3) in concentrated landfill leachates.
• To elucidate the inherent oxidizability and resistance of individual DOM constituents.
• To develop a framework integrating molecular signatures and machine learning for analyzing DOM reactivity.

Main Methods:

• Utilized Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS) to identify DOM molecular signatures.
• Applied a modified machine-learning framework to model the gradual fragmentation pathways of DOM during ozonation.
• Analyzed structural factors influencing DOM resistance to oxidation using SHAP values.

Main Results:

• Humic substances (humic acid, fulvic acid) dominate leachate DOM (35.9-51.7% TOC).
• Carboxyl-rich alicyclic molecules (CRAMs) and lignin-like substances are the most abundant components (40.2-54.5%).
• Molecular weight is the primary factor determining DOM resistance to •OH and O3 degradation, followed by (DBE-O)/C, S/C, and H/C ratios.

Conclusions:

• Developed a novel framework combining molecular characterization and machine learning to understand DOM reactivity in complex matrices.
• Identified specific oxidation pathways for CRAMs-DOM under •OH and O3 attack, leading to degradation.
• Findings provide insights for developing targeted management strategies for concentrated landfill leachates.