地球科学进展

地球科学进展 ›› 2026, Vol. 41 ›› Issue (1): 11 -24. doi: 10.11867/j.issn.1001-8166.2026.004

综述与评述 上一篇    下一篇

地表臭氧与植被相互作用的研究进展与展望
叶泽昱(), 周心易, 乐旭()   
  1. 气候系统预测与变化应对全国重点实验室，大气环境与装备技术协同创新中心，南京信息工程大学 环境科学与工程学院，江苏 南京 210044
  • 收稿日期:2025-11-23 修回日期:2025-12-25 出版日期:2026-01-10
  • 通讯作者: 乐旭 E-mail:202312120022@nuist.edu.cn;yuexu@nuist.edu.cn
  • 基金资助:
    国家重点研发计划项目(2023YFF0805403);国家自然科学基金项目(42275128)

Research Progress and Prospects on Surface Ozone-Vegetation Interactions

Zeyu Ye(), Xinyi Zhou, Xu Yue()   

  1. State Key Laboratory of Climate System Prediction and Risk Management, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
  • Received:2025-11-23 Revised:2025-12-25 Online:2026-01-10 Published:2026-03-10
  • Contact: Xu Yue E-mail:202312120022@nuist.edu.cn;yuexu@nuist.edu.cn
  • About author:Ye Zeyu, research area includes ozone ecological impacts. E-mail: 202312120022@nuist.edu.cn
  • Supported by:
    the National Key Research and Development Program of China(2023YFF0805403);The National Natural Science Foundation of China(42275128)
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地表臭氧与植被之间存在着深刻而复杂的双向反馈作用。一方面，臭氧通过叶片气孔进入植物体内，引发氧化应激反应并抑制光合作用，对全球粮食安全和森林健康构成严重威胁。另一方面，植被并非被动承受，它既是臭氧的“汇”（通过气孔吸收进行干沉降），也是其重要的“源”（通过排放生物源挥发性有机物参与光化学反应）。通过整合相关文献，系统量化了区域到全球尺度下臭氧对作物产量和陆地生产力的损伤作用，明确了植被通过源汇过程对臭氧污染的影响量级，并揭示了臭氧—植被相互作用的关键机制，即臭氧胁迫导致植被气孔关闭，削弱了其清除臭氧的干沉降能力，反馈加剧地表臭氧污染。此外，臭氧诱导的气孔关闭还通过抑制蒸腾作用，改变地表能量平衡（潜热通量减少、感热通量增加），产生增温减湿的生物地球物理效应，进而反馈影响区域气候与大气化学过程。尽管现有研究已初步揭示了这些以正反馈为主导的耦合机制，但仍面临核心控制实验存在不确定性、生态系统模型模拟能力不足以及对多因子协同胁迫认知有限等挑战。未来研究亟须整合多尺度观测、多因子控制实验与高性能耦合模式，以精确量化该系统内的复杂反馈，为协同治理臭氧污染与应对气候变化提供科学依据。

关键词: 地表臭氧, 气孔导度, 陆气耦合, 生物源挥发性有机物, 生态系统生产力

Surface ozone (O3) and terrestrial vegetation has profound and complex interactions that exert strong influences on atmospheric chemistry, ecosystem productivity, and regional climate. As a phytotoxic oxidant, O3 enters plant tissues through stomata, triggering oxidative stress and impairing photosynthetic functions. These physiological disruptions further reduce crop yields and ecosystem productivity, posing substantial threats to global food security and terrestrial carbon sink. Current syntheses estimate that present-day O3 pollution reduces global land sink by 1.5%~5%, with hotspots in eastern China and eastern U.S. Vegetation is not merely a passive recipient of O3 stress; rather, it actively modulates surface O3 concentrations through dual roles as both a sink and a source. On the one hand, stomatal uptake represents a major pathway for O3 dry deposition, accounting for approximately 45% of global O3 removal. On the other hand, vegetation emits Biogenic Volatile Organic Compounds (BVOCs), such as isoprene and monoterpenes, which act as key precursors for O3 formation under sunlight. Recent modeling studies suggest that BVOCs contribute more than 10% to summertime O3 concentrations in polluted regions such as China and U.S. A critical feedback arises from O3-vegetation coupling: elevated O3 induces stomatal closure as a protective response, which reduces the stomatal uptake of O3, weakens dry deposition, and ultimately enhances ambient O3 levels. In addition, O3-induced stomatal closure suppresses transpiration, altering surface energy partitioning by reducing latent heat flux and increasing sensible heat flux. These biophysical responses promote regional warming and drying, with consequent impacts on regional climate and hydrology, including temperature, humidity, precipitation, and runoff. For example, O3-vegetation interactions have been shown to increase summer surface temperatures by 0.2~0.8 K and reduce relative humidity by 3%~9% in eastern China. Despite progress in experimental and modeling approaches, substantial uncertainties persist. These include limitations of controlled-exposure experiments, inconsistencies in O3 damage parameterizations, and incomplete understanding of interactions between O3 stress and co-occurring drivers such as elevated CO2, nitrogen deposition, and extreme climate events. Future research should prioritize integrated multi-scale observational networks, multifactor manipulative experiments, and advanced Earth system models that tightly couple atmospheric chemistry with dynamic vegetation processes. Improved quantification of the O3-vegetation-climate interaction is essential for developing coordinated strategies that jointly address air quality improvement and climate change adaptation.

Key words: Surface ozone, Stomatal conductance, Land-atmosphere coupling, Biogenic volatile organic compounds, Ecosystem productivity

中图分类号: 

表1 BVOCs排放对地表O3 影响评估
Table 1 Assessment of the impact of BVOCs emissions on surface O3
区域时间方法指标贡献参考文献
全球2000—2019年GC-YIBsMDA81.75 nmol/mol［69］
中国2000—2019年GC-YIBsMDA84.39 nmol/mol（8.8%）［69］
中国2017年6~8月GC-YIBsMDA83.7 nmol/mol（6.0%）［70］
中国2018年6~8月WRF-ChemMDA88.6 nmol/mol（16.75%）［64］
中国东部2015年6~8月WRF-CMAQ［O3］3.90 nmol/mol（10.11%）［63］
中国东部2015年6~8月WRF-CMAQMDA111.65 nmol/mol （13.52%）［63］
中国华北平原2015年6~8月WRF-CMAQ［O3］5.00 nmol/mol［63］
中国华北平原2015年6~8月WRF-CMAQMDA115.15 nmol/mol［63］
中国华北平原2017年6~8月GC-YIBsMDA88.6 nmol/mol［70］
中国长江三角洲2015年6~8月WRF-CMAQ［O3］3.18 nmol/mol［63］
中国长江三角洲2015年6~8月WRF-CMAQMDA17.85 nmol/mol［63］
中国长江三角洲2017年6~8月GC-YIBsMDA811.8 nmol/mol［70］
中国珠江三角洲2011年7月WRF-ChemMDA110 nmol/mol［75］
中国珠江三角洲2011年11月WRF-ChemMDA13 nmol/mol［75］
中国珠江三角洲2015年6~8月WRF-CMAQ［O3］3.25 nmol/mol［63］
中国珠江三角洲2015年6~8月WRF-CMAQMDA112.71 nmol/mol［63］
中国珠江三角洲2017年6~8月GC-YIBsMDA86.7 nmol/mol［70］
中国四川盆地2015年6~8月WRF-CMAQ［O3］6.26 nmol/mol［63］
中国四川盆地2015年6~8月WRF-CMAQMDA117.59 nmol/mol［63］
中国四川盆地2017年6~8月GC-YIBsMDA812.9 nmol/mol［70］
美国2000—2019年GC-YIBsMDA85.36 nmol/mol（11.1%）［69］
美国2011年5~9月WRF-SMOKE-CAMx［O3］10%~19%［72］
欧洲—CHIMEREMDA12.5 nmol/mol（5%）［73］
南欧—CHIMEREMDA14.0 nmol/mol［73］
北欧—CHIMEREMDA11.3 nmol/mol［73］
地中海—CHIMEREMDA15.0 nmol/mol［73］
图1 基于剂量响应关系获得的O3 对作物产量的影响
（a）~（d）分别为小麦、大豆、水稻和玉米基于剂量响应关系估算的产量损失比例；青色和粉色柱分别为汇总的全球和中国范围损失比例的均值，误差棒表示1倍标准差；散点和误差棒表示各研究的结果（数值参见附表1）。
Fig. 1 Impacts of O3 on crop yield derived from dose-response relationships
（a）~（d） The estimated percentage yield losses of wheat， soybean， rice， and maize based on dose-response relationships. The cyan and pink bars represent the mean yield losses aggregated at the global scale and in China， respectively， with error bars indicating one standard deviation. The dots and error bars denote results from individual studies （values listed in Table Suppl. 1）.
图2 O3 导致陆地生产力的损失评估
蓝色柱表示全球尺度评估结果，橙色柱表示中国或东亚区域评估结果，绿色柱表示其他区域评估结果；误差棒表示1倍标准差或高、低敏感性下的评估结果范围，横虚线代表不同研究结果的中值，横坐标字母与数字为数据出处（数值和出处参见附表2）。
Fig. 2 Assessment of O3-induced losses in terrestrial productivity
The blue bars represent global-scale assessments， the orange bars represent assessments for China or East Asia， and the green bars represent results for other regions. Error bars indicate one standard deviation or the range between high-sensitivity and low-sensitivity estimates， and the horizontal dashed line denotes the median results across different studies （values listed in Table Suppl. 2）.
表2 植被气孔吸收对O3 沉降速率和浓度的影响
Table 2 Impacts of vegetation stomatal uptake on O3 deposition velocity and concentrations
区域时间方法指标贡献参考文献
全球1948—2014年LM4.0昼间Vd40%~75%［74］
中国东北半干旱区1948—2014年LM4.0昼间Vd<25%［74］
中国2017年6~8月GC-YIBsMDA8 O3-2.7 nmol/mol （-4.5%）［72］
中国2017年6~8月WRF-Chemgs 抑制对MDA8贡献1.3~2.2 nmol/mol （3%~5%）［77］
中国东部—ModelE2-YIBsgs 抑制对MDA8贡献2.1 nmol/mol［25］
中国华北平原2014—2017年GC-YIBsgs 抑制对MDA8贡献0.95 nmol/mol （5.7%）［67］
中国华北平原2014—2017年GC-YIBsgs 抑制对Vd 贡献-5.20%［67］
中国华北平原2017年6~8月WRF-Chemgs 抑制对MDA8贡献4.0~7.5 nmol/mol［77］
中国长江三角洲2014—2017年GC-YIBsgs 抑制对MDA8贡献1.4 nmol/mol （8.4%）［67］
中国长江三角洲2014—2017年GC-YIBsgs 抑制对Vd 贡献-14.20%［67］
美国东部—ModelE2-YIBsgs 抑制对MDA8贡献1.8 nmol/mol［25］
欧洲2003年GFDLgs 抑制对Vd 贡献-70%［76］
西欧—ModelE2-YIBsgs 抑制对MDA8贡献1.3 nmol/mol［25］
图3 O3-植被相互作用对温度和湿度的影响评估
（a）和（b）分别为O3-植被相互作用对地表温度和相对湿度的影响；蓝色柱表示全球尺度评估结果，橙色柱表示中国区域评估结果，绿色柱表示美国区域评估结果；误差棒表示1倍标准差或高、低敏感性下的评估结果范围，横坐标字母和数字为数据出处（数值和出处参见附表3）。
Fig. 3 Assessment of the impacts of O3-vegetation interactions on temperature and humidity
（a） and （b） show the impacts of O3-vegetation interactions on surface temperature， and relative humidity， respectively. The blue bars represent global-scale assessments， the orange bars represent assessments for China， and the green bars represent results for U.S. error bars indicate one standard deviation or the range between high-sensitivity and low-sensitivity estimates （values listed in Table Suppl. 3）.
图4 O3-植被相互作用对地表能量通量的影响评估
（a）和（b）分别为O3-植被相互作用对地表能量通量贡献的绝对变化和相对变化；青色柱表示潜热通量，粉色柱表示感热通量；实心柱为全球评估，空心柱为中国区域评估，圆点填色柱为美国区域评估；误差棒表示1倍标准差或高、低敏感性下的评估结果范围，横坐标为数据出处（数值和出处参见附表3）。
Fig. 4 Assessment of the impacts of O3-vegetation interactions on surface energy fluxes
（a） and （b） show the absolute changes and relative changes in surface energy fluxes induced by O3-vegetation interactions， respectively. Cyan bars represent latent heat flux， and pink bars represent sensible heat flux. Solid bars indicate global-scale assessments， empty bars indicate assessments for China， and filled bars indicate results for the U.S. Error bars represent one standard deviation or the range between high-sensitivity and low-sensitivity estimates （values listed in Table Suppl. 3）.
图5 O3-植被相互作用及其环境和气候效应流程图
Fig. 5 Schematic diagram of O3-vegetation interactions and their environmental and climatic effects
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