The terrestrial ecosystem in China mitigates 21%-45%of the national contemporary fossil fuel CO_(2) emissions every year.Maintaining and strengthening the land carbon sink is essential for reaching China’s target of ...The terrestrial ecosystem in China mitigates 21%-45%of the national contemporary fossil fuel CO_(2) emissions every year.Maintaining and strengthening the land carbon sink is essential for reaching China’s target of carbon neutrality.However,this sink is subject to large uncertainties due to the joint impacts of climate change,air pollution,and human activities.Here,we explore the potential of strengthening land carbon sink in China through anthropogenic interventions,including forestation,ozone reduction,and litter removal,taking advantage of a well-validated dynamic vegetation model and meteorological forcings from 16 climate models.Without anthropogenic interventions,considering Shared Socioeconomic Pathways(SSP)scenarios,the land sink is projected to be 0.26-0.56 Pg C a^(-1) at 2060,to which climate change contributes 0.06-0.13 Pg C a^(-1) and CO_(2) fertilization contributes 0.08-0.44 Pg C a^(-1) with the stronger effects for higher emission scenarios.With anthropogenic interventions,under a close-to-neutral emission scenario(SSP1-2.6),the land sink becomes 0.47-0.57 Pg C a^(-1) at 2060,including the contributions of 0.12 Pg C a^(-1) by conservative forestation,0.07 Pg C a^(-1) by ozone pollution control,and 0.06-0.16 Pg C a^(-1) by 20%litter removal over planted forest.This sink can mitigate 90%-110% of the residue anthropogenic carbon emissions in 2060,providing a solid foundation for the carbon neutrality in China.展开更多
Background:Large uncertainty in modeling land carbon(C)uptake heavily impedes the accurate prediction of the global C budget.Identifying the uncertainty sources among models is crucial for model improvement yet has be...Background:Large uncertainty in modeling land carbon(C)uptake heavily impedes the accurate prediction of the global C budget.Identifying the uncertainty sources among models is crucial for model improvement yet has been difficult due to multiple feedbacks within Earth System Models(ESMs).Here we present a Matrix-based Ensemble Model Inter-comparison Platform(MEMIP)under a unified model traceability framework to evaluate multiple soil organic carbon(SOC)models.Using the MEMIP,we analyzed how the vertically resolved soil biogeochemistry structure influences SOC prediction in two soil organic matter(SOM)models.By comparing the model outputs from the C-only and CN modes,the SOC differences contributed by individual processes and N feedback between vegetation and soil were explicitly disentangled.Results:Results showed that the multi-layer models with a vertically resolved structure predicted significantly higher SOC than the single layer models over the historical simulation(1900–2000).The SOC difference between the multi-layer models was remarkably higher than between the single-layer models.Traceability analysis indicated that over 80%of the SOC increase in the multi-layer models was contributed by the incorporation of depth-related processes,while SOC differences were similarly contributed by the processes and N feedback between models with the same soil depth representation.Conclusions:The output suggested that feedback is a non-negligible contributor to the inter-model difference of SOC prediction,especially between models with similar process representation.Further analysis with TRENDY v7 and more extensive MEMIP outputs illustrated the potential important role of multi-layer structure to enlarge the current ensemble spread and the necessity of more detail model decomposition to fully disentangle inter-model differences.We stressed the importance of analyzing ensemble outputs from the fundamental model structures,and holding a holistic view in understanding the ensemble uncertainty.展开更多
基金supported by the National Natural Science Foundation of China(42293323 and 42275128)the Natural Science Foundation of Jiangsu Province(BK20220031).
文摘The terrestrial ecosystem in China mitigates 21%-45%of the national contemporary fossil fuel CO_(2) emissions every year.Maintaining and strengthening the land carbon sink is essential for reaching China’s target of carbon neutrality.However,this sink is subject to large uncertainties due to the joint impacts of climate change,air pollution,and human activities.Here,we explore the potential of strengthening land carbon sink in China through anthropogenic interventions,including forestation,ozone reduction,and litter removal,taking advantage of a well-validated dynamic vegetation model and meteorological forcings from 16 climate models.Without anthropogenic interventions,considering Shared Socioeconomic Pathways(SSP)scenarios,the land sink is projected to be 0.26-0.56 Pg C a^(-1) at 2060,to which climate change contributes 0.06-0.13 Pg C a^(-1) and CO_(2) fertilization contributes 0.08-0.44 Pg C a^(-1) with the stronger effects for higher emission scenarios.With anthropogenic interventions,under a close-to-neutral emission scenario(SSP1-2.6),the land sink becomes 0.47-0.57 Pg C a^(-1) at 2060,including the contributions of 0.12 Pg C a^(-1) by conservative forestation,0.07 Pg C a^(-1) by ozone pollution control,and 0.06-0.16 Pg C a^(-1) by 20%litter removal over planted forest.This sink can mitigate 90%-110% of the residue anthropogenic carbon emissions in 2060,providing a solid foundation for the carbon neutrality in China.
基金This study is supported by the funding from the National Key Research and Development Program of China under grants 2017YFA0604600YC was supported by National Youth Science Fund of China(41701227).DL is supported by the National Center for Atmospheric Research,which is a major facility sponsored by the National Science Foundation(NSF)under Cooperative Agreement 1852977.DL’s computing and data storage resources,including the Cheyenne supercomputer(https://doi.org/10.5065/D6RX99HX),were provided by the Computational and Information Systems Laboratory(CISL)at NCAR.DSG receives support from the ANR CLAND Convergence Institute.
文摘Background:Large uncertainty in modeling land carbon(C)uptake heavily impedes the accurate prediction of the global C budget.Identifying the uncertainty sources among models is crucial for model improvement yet has been difficult due to multiple feedbacks within Earth System Models(ESMs).Here we present a Matrix-based Ensemble Model Inter-comparison Platform(MEMIP)under a unified model traceability framework to evaluate multiple soil organic carbon(SOC)models.Using the MEMIP,we analyzed how the vertically resolved soil biogeochemistry structure influences SOC prediction in two soil organic matter(SOM)models.By comparing the model outputs from the C-only and CN modes,the SOC differences contributed by individual processes and N feedback between vegetation and soil were explicitly disentangled.Results:Results showed that the multi-layer models with a vertically resolved structure predicted significantly higher SOC than the single layer models over the historical simulation(1900–2000).The SOC difference between the multi-layer models was remarkably higher than between the single-layer models.Traceability analysis indicated that over 80%of the SOC increase in the multi-layer models was contributed by the incorporation of depth-related processes,while SOC differences were similarly contributed by the processes and N feedback between models with the same soil depth representation.Conclusions:The output suggested that feedback is a non-negligible contributor to the inter-model difference of SOC prediction,especially between models with similar process representation.Further analysis with TRENDY v7 and more extensive MEMIP outputs illustrated the potential important role of multi-layer structure to enlarge the current ensemble spread and the necessity of more detail model decomposition to fully disentangle inter-model differences.We stressed the importance of analyzing ensemble outputs from the fundamental model structures,and holding a holistic view in understanding the ensemble uncertainty.
