Characterizing the Accelerated Global Carbon Emissions from Forest Loss during 1985–2020 Using Fine-Resolution Remote Sensing Datasets

Author:

Liu Wendi123,Zhang Xiao12,Xu Hong4,Zhao Tingting125,Wang Jinqing123,Li Zhehua123,Liu Liangyun123ORCID

Affiliation:

1. Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

2. International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China

3. University of Chinese Academy of Sciences, Beijing 100049, China

4. The High-Tech Research & Development Center (HTRDC) of the Ministry of Science & Technology, Beijing 100044, China

5. College of Geomatics, Xi’an University of Science and Technology, Xi’an 710054, China

Abstract

Previous studies on global carbon emissions from forest loss have been marked by great discrepancies due to uncertainties regarding the lost area and the densities of different carbon pools. In this study, we employed a new global 30 m land cover dynamic dataset (GLC_FCS30D) to improve the assessment of forest loss areas; then, we combined multi-sourced carbon stock products to enhance the information on carbon density. Afterwards, we estimated the global carbon emissions from forest loss over the period of 1985–2020 based on the method recommended by the Intergovernmental Panel on Climate Change Guidelines (IPCC). The results indicate that global forest loss continued to accelerate over the past 35 years, totaling about 582.17 Mha and leading to total committed carbon emissions of 35.22 ± 9.38 PgC. Tropical zones dominated global carbon emissions (~2/3) due to their higher carbon density and greater forest loss. Furthermore, global emissions more than doubled in the period of 2015–2020 (1.77 ± 0.44 PgC/yr) compared to those in 1985–2000 (0.69 ± 0.21 PgC/yr). Notably, the forest loss at high altitudes (i.e., above 1000 m) more than tripled in mountainous regions, resulting in more pronounced carbon emissions in these areas. Therefore, the accelerating trend of global carbon emissions from forest loss indicates that great challenges still remain for achieving the COP 26 Declaration to halt forest loss by 2030.

Funder

National Natural Science Foundation of China

Open Research Program of the International Research Center of Big Data for Sustainable Development Goals

Publisher

MDPI AG

Reference77 articles.

1. FAO (2020). Global Forest Resources Assessment 2020: Main Report, Food and Agriculture Organization of the United Nations.

2. Global land use changes are four times greater than previously estimated;Winkler;Nat. Commun.,2021

3. Global Hydroclimatological Teleconnections Resulting from Tropical Deforestation;Avissar;J. Hydrometeorol.,2005

4. Baseline map of carbon emissions from deforestation in tropical regions;Harris;Science,2012

5. Global Carbon Budget 2023;Friedlingstein;Earth Syst. Sci. Data,2023

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3