臭氧污染对作物产量的影响:评估方法的进展与展望

doi:10.13287/j.1001-9332.202604.014

摘要/Abstract

摘要： 地表臭氧(O₃)浓度长期处于高位且持续时间不断延长,准确评估臭氧污染引发的作物产量损失,对维护区域及全球粮食安全具有重要意义。本文系统阐述了O₃污染对作物减产的伤害机制和作物自身的解毒机制,解析了O₃浓度响应、剂量响应和通量响应等农作物减产评估方法的局限性,聚焦机理模型改进与多方法耦合的创新实践,全面介绍了作物模型中嵌入O₃伤害和解毒模块的研究进展,展望了作物模型-机器学习混合框架在O₃伤害评估中的研究方向,并为量化O₃污染与极端气候事件的复合效应提供了机理性和实用性并存的新研究范式。本文可为精准评估气候变化背景下O₃污染对作物产量损失影响研究的持续推进提供参考。

关键词: 臭氧, 作物产量, 评估方法, 解毒机制, 作物模型, 机器学习

Abstract: The concentration of surface ozone (O₃) remains high for a long time and its duration continues to extend. Accurately assessing crop yield losses caused by ozone pollution is of great significance for maintaining regio-nal and global food security. We systematically elaborated on the damage mechanism of O₃ pollution on crop yield and the detoxification mechanism of crops, analyzed the limitations of crop yield assessment methods such as O₃ concentration response, dose response, and flux response. By focusing on innovative practices of mechanism model improvement and multi method coupling, we comprehensively introduced the research progress of embedding O₃ damage and detoxification modules in crop models, proposed the research direction of crop model machine learning hybrid framework in O₃ damage assessment. Moreover, we provided a new research paradigm that combined ratio-nality and practicality for quantifying the composite effects of O₃ pollution and extreme climate events. This review could provide reference for the continuous promotion of research on the impact of O₃ pollution on crop yield losses under the background of climate change.

Key words: ozone, crop yield, assessment method, detoxification mechanism, crop model, machine learning

吴荣军, 冯兆忠. 臭氧污染对作物产量的影响:评估方法的进展与展望[J]. 应用生态学报, 2026, 37(4): 1319-1328.

WU Rongjun, FENG Zhaozhong. Impact of ozone pollution on crop yields: Advances and prospects in assessment methods[J]. Chinese Journal of Applied Ecology, 2026, 37(4): 1319-1328.

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