The roles of environmental conditions in the pollutant emission-induced gross primary production change: Co-contribution of meteorological fields and regulation of its background gradients

环境科学 初级生产 大气科学 空气质量指数 碳循环 污染物 气候变化 云量 温室气体 全球变化 气候学 气象学 生态系统 生态学 云计算 物理 计算机科学 生物 地质学 操作系统
作者
Xuan Gui,Lunche Wang,Qian Cao,Shiyu Li,Weixia Jiang,Shaoqiang Wang
出处
期刊:Progress in Physical Geography [SAGE Publishing]
卷期号:47 (6): 852-872
标识
DOI:10.1177/03091333231186893
摘要

Anthropogenic emissions affect vegetation photosynthesis and carbon flux through meteorological variations induced by aerosols and clouds. However, the insufficient consideration of meteorological conditions limits the understanding of relevant mechanisms, and further inhibits the projection of future terrestrial carbon balance. Based on multiple sets of model simulations, we characterized changes in gross primary production (GPP) due to three typical individual pollutants emissions (black carbon, organic carbon, and sulfate), quantified the relative contributions of co-varied environmental factors, and explored the regulatory roles of background meteorological conditions across China. Our results showed that the heterogeneous GPP enhancement induced by emissions was dominated by cloud cover (CC) change. During its short-term effect, air temperature (T air ), vapor pressure deficit (VPD), and radiation (both quality and quantity) played a collectively non-negligible role in GPP variation, among which the universal diffuse radiation fertilization effect was generally far less than the benefits of brighter, cooler, and wetter environmental conditions. However, the sensitivity of GPP to an individual environmental variable was also altered by background meteorological gradients, whose changing pattern differed substantially among factors, indicating that the meteorological-regulated vegetation optimal photosynthetic range was a trade-off among heat, water, and light instead of being controlled by the univariable. This study implies that a deeper understanding of concurrent environmental variables is an effective way to reduce uncertainties in assessing the terrestrial carbon cycle perturbation exerted by human-induced emissions, especially under future scenarios with ongoing climate change.

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