Electric Power Technology and Environmental Protection

【目的】传统烟气处理催化剂在复杂条件下的催化性能较低，无法满足生物质/固废掺烧烟气中氮氧化物（NOx ）和挥发性 有机化合物（VOCs）协同净化的需求，针对这一技术挑战，亟需开发协同净化催化剂以满足实际应用需求。【方法】本文综述了 NOx 选择性催化还原、VOCs催化氧化以及两者协同催化的反应机理，分别介绍了NOx 与脂肪族化合物、芳烃化合物以及含杂原 子化合物之间的相互作用机制及催化剂研究现状，阐明了氧化还原位点与酸性位点耦合机制对催化剂反应性能、选择性以及 稳定性的影响。【结果】（1）在NOx 和VOCs协同净化方面，主要通过NH3-SCR耦合HC氧化反应、NH3 /HC混合还原剂选择性催 化反应或HC-SCR反应三种路径进行。（2）研究人员可通过催化剂设计，精准调控活性位点的数量和空间分布，同时优化反应 路径以减少副产物的生成，实现高效协同催化反应性能。（3）此外，反应条件以及反应物形态也会影响催化剂协同反应性能，可 为高效协同净化催化剂提供技术路径指导。【结论】催化剂性能依赖于酸性位点与氧化还原位点的协同调控；未来可结合机器 学习优化活性位点设计以提升催化反应性能并开发抗SO2 /H2 O中毒的协同催化剂，以期为电力行业的NOx 和VOCs等多污染物 的高效协同净化提供参考。

[Objective] Conventional flue gas treatment catalysts demonstrate insufficient catalytic performance under complex operating conditions, to address the need for synergistic removal of nitrogen oxides (NOx ) and volatile organic compounds (VOCs) from biomass/solid waste co-combustion flue gases. Facing this technical challenge, there is an urgent requirement to develop advanced synergistic purification catalysts to meet practical application demands. [Methods] In this paper, the selective catalytic reduction of NOx , the catalytic oxidation of VOCs and their synergistic catalytic reaction mechanisms are reviewed, the interaction mechanisms between NOx and aliphatic compounds, aromatic compounds and heteroatom-containing compounds and the current status of catalysts are described, and the influence of the coupling mechanism of the redox sites and acidic sites on the reaction performance, selectivity and stability of the catalysts is elucidated.[Results] (1) The co-purification of NOx and VOCs is mainly achieved through three catalytic pathways: the coupling of NH3-SCR with hydrocarbon oxidation reactions, selective catalytic reactions using NH3 /HC mixed reducing agents, or hydrocarbon-SCR reactions. (2) Through rational catalyst design, researchers can precisely regulate the number and spatial arrangement of active sites while optimizing reaction pathways, thereby reducing byproduct generation and achieving superior synergistic catalytic performance. (3) Additionally, reaction conditions and reactant states significantly influence the synergistic catalytic performance, thereby providing critical technical pathway guidance for developing high-efficiency co-purification catalysts. [Conclusion] Catalyst performance depends on the synergistic modulation of acid sites and redox sites. Future studies may incorporate machine learning to optimize active site design for enhanced catalytic performance while developing synergistic catalysts with SO2 /H2 O poisoning resistance, thereby providing references for efficient co-purification of multi-pollutants (NOx , VOCs, etc.) in the power industry.