碳循环
环境科学
大气碳循环
温室气体
碳纤维
大气科学
二氧化碳
地球大气中的二氧化碳
碳汇
气候变化
气候学
化学
生态系统
生态学
地质学
材料科学
复合材料
有机化学
复合数
生物
作者
V. Rachel Chimuka,Claude-Michel Nzotungicimpaye,Kirsten Zickfeld
标识
DOI:10.5194/bg-20-2283-2023
摘要
Abstract. Land and ocean carbon sinks play a major role in regulating atmospheric CO2 concentration and climate. However, their future efficiency depends on feedbacks in response to changes in atmospheric CO2 concentration and climate, namely the concentration–carbon and climate–carbon feedbacks. Since carbon dioxide removal (CDR) is a key mitigation measure in emission scenarios consistent with global temperature goals in the Paris Agreement, understanding carbon cycle feedbacks under negative CO2 emissions is essential. This study investigates land carbon cycle feedbacks under positive and negative CO2 emissions using an Earth system model of intermediate complexity (EMIC) driven with an idealized scenario of symmetric atmospheric CO2 concentration increase (ramp-up) and decrease (ramp-down), run in three modes. Our results show that the magnitudes of carbon cycle feedbacks are generally smaller in the atmospheric CO2 ramp-down phase than in the ramp-up phase, except for the ocean climate–carbon feedback, which is larger in the ramp-down phase. This is largely due to carbon cycle inertia: the carbon cycle response in the ramp-down phase is a combination of the committed response to the prior atmospheric CO2 increase and the response to decreasing atmospheric CO2. To isolate carbon cycle feedbacks under decreasing atmospheric CO2 and quantify these feedbacks more accurately, we propose a novel approach that uses zero emission simulations to quantify the committed carbon cycle response. We find that the magnitudes of the concentration–carbon and climate–carbon feedbacks under decreasing atmospheric CO2 are larger in our novel approach than in the standard approach. Accurately quantifying carbon cycle feedbacks in scenarios with negative emissions is essential for determining the effectiveness of carbon dioxide removal in drawing down atmospheric CO2 and mitigating warming.
科研通智能强力驱动
Strongly Powered by AbleSci AI