Gui Yanchen, Wang Kai, Jin Zhe, Wang Heyuan, Deng Hanzhi, Li Xiangyi, Tian Xiangjun, Wang Tao, Chen Wei, Wang Tengjiao, Piao Shilong
Institute of Carbon Neutrality, Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China.
State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China.
Natl Sci Rev. 2024 Oct 22;11(12):nwae365. doi: 10.1093/nsr/nwae365. eCollection 2024 Dec.
Atmospheric CO growth rate (CGR), reflecting the carbon balance between anthropogenic emissions and net uptake from land and ocean, largely determines the magnitude and speed of global warming. The CGR at Mauna Loa Baseline Observatory reached a record high in 2023. We quantified major components of the global carbon balance for 2023, by developing a framework that integrated fossil fuel CO emissions data and an atmospheric inversion from the Global ObservatioN-based system for monitoring Greenhouse GAses (GONGGA) with two artificial intelligence (AI) models derived from dynamic global vegetation models. We attributed the record high CGR increase in 2023 compared to 2022 primarily to the large decline in land carbon sink (1803 ± 197 TgC year), with minor contributions from a small reduction in ocean carbon sink (184 TgC year) and a slight increase in fossil fuel emissions (24 TgC year). At least 78% of the global decline in land carbon sink was contributed by the decline in tropical sink, with GONGGA inversion (1354 TgC year) and AI simulations (1578 ± 666 TgC year) showing similar declines in the tropics. We further linked this tropical decline to the detrimental impact of El Niño-induced anomalous warming and drying on vegetation productivity in water-limited Sahel and southern Africa. Our successful attribution of CGR increase within a framework combining atmospheric inversion and AI simulations enabled near-real-time tracking of the global carbon budget, which had a one-year reporting lag.
大气二氧化碳增长率(CGR)反映了人为排放与陆地和海洋净吸收之间的碳平衡,在很大程度上决定了全球变暖的幅度和速度。莫纳罗亚基线观测站的CGR在2023年达到创纪录高位。我们通过开发一个框架来量化2023年全球碳平衡的主要组成部分,该框架将化石燃料二氧化碳排放数据与基于全球温室气体观测系统(GONGGA)的大气反演以及两个源自动态全球植被模型的人工智能(AI)模型相结合。我们将2023年与2022年相比CGR创纪录的增长主要归因于陆地碳汇的大幅下降(1803±197 TgC/年),海洋碳汇的小幅减少(184 TgC/年)和化石燃料排放的略有增加(24 TgC/年)贡献较小。全球陆地碳汇下降中至少78%是由热带碳汇下降造成的,GONGGA反演(1354 TgC/年)和AI模拟(1578±666 TgC/年)显示热带地区有类似的下降。我们进一步将这种热带地区的下降与厄尔尼诺引发的异常变暖和干燥对水资源有限的萨赫勒地区和南部非洲植被生产力的不利影响联系起来。我们在结合大气反演和AI模拟的框架内成功归因了CGR的增加,这使得能够对全球碳预算进行近实时跟踪,而此前该预算有一年的报告滞后。