Yi Xiao, Dongyang Li, Qigui Niu, Shicheng Zhang, Tianxue Yang, Jiaming Zhao, Minda Yu, Ming Yan, Beidou Xi
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引用次数: 0
Abstract
Although converting carbonaceous components in sewage
sludge into
value-added esters via pyrolysis presents significant resource recovery
potential, the complex temperature-dependent interconversion and the
limited molecular resolution of conventional analytical techniques
have impeded mechanistic elucidation and selective regulation. Here,
an integrated approach combining Fourier transform ion cyclotron resonance
mass spectrometry (FT-ICR MS), paired mass distance (PMD) network
analysis, interpretable machine learning, and density functional theory
(DFT) calculations was employed to elucidate the transformation network
of organooxygen species (OOSs) during sludge pyrolysis and enabled
the proposal of a cascade pathway governing ester enrichment. Esters,
unsaturated acids, saturated acids, and peptides/amides accounted
for over 95.7% of total OOSs. Ester content decreased at 300–400
°C and regenerated at 400–500 °C, consistent with
hydrolysis-esterification interconversion, defining a highly reactive
temperature window. Within this interval, dominant interconversion
pathways of peptides/amides ⇌ acids ⇌ esters were proposed,
suggesting a cascade transformation pathway of peptides/amides →
unsaturated acids → saturated acids → esters. The process
yielded an additional net benefit of 164.6–474.6 CNY/t over
conventional sludge disposal, with a carbon mitigation potential of
776.7 kg CO2e/t. These findings provide a molecular-scale
basis for engineering-directed process optimization of pyrolysis systems
targeting selective ester production from organic solid wastes.
期刊介绍:
ACS ES&T Engineering publishes impactful research and review articles across all realms of environmental technology and engineering, employing a rigorous peer-review process. As a specialized journal, it aims to provide an international platform for research and innovation, inviting contributions on materials technologies, processes, data analytics, and engineering systems that can effectively manage, protect, and remediate air, water, and soil quality, as well as treat wastes and recover resources.
The journal encourages research that supports informed decision-making within complex engineered systems and is grounded in mechanistic science and analytics, describing intricate environmental engineering systems. It considers papers presenting novel advancements, spanning from laboratory discovery to field-based application. However, case or demonstration studies lacking significant scientific advancements and technological innovations are not within its scope.
Contributions containing experimental and/or theoretical methods, rooted in engineering principles and integrated with knowledge from other disciplines, are welcomed.