Progress and challenges in remotely sensed terrestrial carbon fluxes

碳汇 碳通量 初级生产 全球变化 环境科学 卫星 陆地生态系统 气候变化 大气科学 碳循环 碳纤维 水槽(地理) 大气碳循环 固碳 气候学 二氧化碳 地理 地质学 生态系统 生态学 海洋学 计算机科学 生物 地图学 算法 航空航天工程 复合数 工程类
作者
Tao Wang,Yao Zhang,Chao Yue,Yilong Wang,Xiaoyi Wang,Guanting Lyu,Jianjun Wei,Hui Yang,Shilong Piao
出处
期刊:Geo-spatial Information Science [Taylor & Francis]
卷期号:: 1-21 被引量:8
标识
DOI:10.1080/10095020.2024.2336599
摘要

Accurate evaluation of terrestrial carbon balance is essential for designing climate change mitigation policies, and capabilities of remote sensing techniques in monitoring carbon fluxes are widely recognized for their great contributions to regional and global carbon budget accounting. In this review, we synthesized satellite-based data and methodologies to estimate the main flux components of terrestrial carbon balance and their uncertainties over the past two decades. The global gross primary production (GPP) during the period 2001–2022 is 134 ± 14 PgC yr−1, and nearly half of them occurs in tropical forest regions such as South America and Africa. Less than 2% of global GPP is converted into a net carbon sink of 2.28 ± 1.12 PgC yr−1 using satellite-based atmospheric inversion during 2015–2020, and this sink is comparable to the stock change-based estimate (2.49 PgC yr−1) but twice as large as model-based estimate (1.08 ± 0.78 PgC yr−1). By decomposing satellite-derived net carbon balance into different terms including satellite-derived carbon emissions from land-use change and wildfires (3.55 PgC yr−1), we inferred that ~ 43% of global GPP would be respired through soil microbes (57.1 PgC yr−1), but which is higher than the previous bottom-up estimate (39–46 PgC yr−1). We then propose that an accurate remote sensing of terrestrial carbon balance requires to enhance representations of photosynthetic responses to rising CO2 and disturbances, develop satellite-constrained belowground carbon dynamics and separate natural fluxes from anthropogenic CO2 emissions, by integrating multi-source satellite sensors in orbit, revolutionized remote sensing capabilities with focused field campaigns in data-scarce regions.
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