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Integrating national integrated assessment model and land-use intensity for estimating China's terrestrial ecosystem carbon storage.

Authors :
Wang, Yuanhui
Song, Changqing
Gao, Yifan
Ye, Sijing
Gao, Peichao
Source :
Applied Geography. Jan2024, Vol. 162, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

Carbon emission reduction in China matters to global climate change mitigation. China has been experiencing extensive land changes, which profoundly influence terrestrial ecosystem carbon storage (TECS) and carbon emissions. Scholars have predicted influences of land changes on TECS in China with scenarios obtained from global integrated assessment models (IAMs), which lack national details. Moreover, universally existing variations in land-use intensity have not been considered when estimating influences on TECS. This study simulated changes of land-use intensity of China from 2000 to 2050 using CLUMondo under China-specified policies for sustainable development modeled by a national IAM named Threshold21-China. We proposed a more precise TECS estimation method by distinguishing land-vegetation and land-soil types. Results demonstrated that under scenario with preceding policies, the total TECS can increase by 865.5 Tg C from 2000 to 2050. Through implementing preceding policies, TECS loss by conversions from cultivated land to artificial surfaces can decline by 82 Tg C, and new TECS accumulated by increased and densified forests can increase by 73 Tg C. Mountainous and rapidly urbanizing regions are sensitively influenced and need more restrict land change management policies. This study demonstrates the significance of sustainable development policies for TECS conservation and indicates specific critical regions. • Introducing national IAM into land change simulation. • Considering land-use intensities in land change simulation. • Proposing an improved TECS estimation method. • Estimating influences of land changes on China's TECS. • TECS accumulation could be improved under sustainable policies. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01436228
Volume :
162
Database :
Academic Search Index
Journal :
Applied Geography
Publication Type :
Academic Journal
Accession number :
174470935
Full Text :
https://doi.org/10.1016/j.apgeog.2023.103173