CO_(2)is one of the most important greenhouse gases(GHGs)in the earth’s atmosphere.Since the industrial era,anthropogenic activities have emitted excessive quantities of GHGs into the atmosphere,resulting in climate ...CO_(2)is one of the most important greenhouse gases(GHGs)in the earth’s atmosphere.Since the industrial era,anthropogenic activities have emitted excessive quantities of GHGs into the atmosphere,resulting in climate warming since the 1950s and leading to an increased frequency of extreme weather and climate events.In 2020,China committed to striving for carbon neutrality by 2060.This commitment and China’s consequent actions will result in significant changes in global and regional anthropogenic carbon emissions and therefore require timely,comprehensive,and objective monitoring and verification support(MVS)systems.The MVS approach relies on the top-down assimilation and inversion of atmospheric CO_(2)concentrations,as recommended by the Intergovernmental Panel on Climate Change(IPCC)Inventory Guidelines in 2019.However,the regional high-resolution assimilation and inversion method is still in its initial stage of development.Here,we have constructed an inverse system for carbon sources and sinks at the kilometer level by coupling proper orthogonal decomposition(POD)with four-dimensional variational(4DVar)data assimilation based on the weather research and forecasting-greenhouse gas(WRF-GHG)model.Our China Carbon Monito ring and Verification Support at the Regional level(CCMVS-R)system can continuously assimilate information on atmospheric CO_(2)and other related information and realize the inversion of regional and local anthropogenic carbon emissions and natural terrestrial ecosystem carbon exchange.Atmospheric CO_(2)data were collected from six ground-based monito ring sites in Shanxi Province,China to verify the inversion effect of regio nal anthropogenic carbon emissions by setting ideal and real experiments using a two-layer nesting method(at 27 and 9 km).The uncertainty of the simulated atmospheric CO_(2)decreased significantly,with a root-mean-square error of CO_(2)concentration values between the ideal value and the simulated after assimilation was close to 0.The total anthropogenic carbon emissions in Shanxi Province in 2019 from the assimilated inversions were approximately 28.6%(17%-38%)higher than the mean of five emission inventories using the bottomup method,showing that the top-down CCMVS-R system can obtain more comprehensive information on anthropogenic carbon emissions.展开更多
The 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories added the method of assimilating atmospheric CO_(2) concentrations to invert carbon sources and sinks;however,many global carbon ...The 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories added the method of assimilating atmospheric CO_(2) concentrations to invert carbon sources and sinks;however,many global carbon inversion models are not publicly available.In addition,our regional assimilation inversion system,CCMVS-R(China Carbon Monitoring,Verification and Supporting for Regional),needs a global carbon inversion model with higher assimilation efficiency to provide boundary conditions.Here,an inversion model based on the global atmospheric chemistry model GEOS-Chem and a more accurate and easier-to-implement ensemble square root Kalman filter(EnSRF)algorithm is constructed and used to infer global and China's carbon fluxes in 2019.Atmospheric CO_(2) concentrations from ObsPack sites and five additional CO_(2) observational sites from China's Greenhouse Gas Observation Network(CGHGNET)were used for data assimilation to improve the estimate.The inverted annual global terrestrial and oceanic carbon uptake is 2.12 and 2.53 Pg C per year,respectively,accounting for 21.1%and 25.1%of global fossil fuel CO_(2) emissions.The remaining 5.41 Pg C per year in the atmosphere is consistent with the global atmospheric CO_(2) growth rates of 5.44 Pg C per year reported by the National Oceanic and Atmospheric Administration(NOAA),showing that the inversion model can provide a reasonable estimate of global-scale natural carbon sinks.The inverted terrestrial carbon sink of China is 0.37 Pg C per year,accounting for approximately 13%of China's fossil CO_(2) emissions.展开更多
基金supported by the General Project of Top-Design of Multi-Scale Nature-Social ModelsData Support and Decision Support System for NSFC Carbon Neutrality Major Project(42341202)the Basic Scientific Research Fund of the Chinese Academy of Meteorological Sciences(2021Z014)。
文摘CO_(2)is one of the most important greenhouse gases(GHGs)in the earth’s atmosphere.Since the industrial era,anthropogenic activities have emitted excessive quantities of GHGs into the atmosphere,resulting in climate warming since the 1950s and leading to an increased frequency of extreme weather and climate events.In 2020,China committed to striving for carbon neutrality by 2060.This commitment and China’s consequent actions will result in significant changes in global and regional anthropogenic carbon emissions and therefore require timely,comprehensive,and objective monitoring and verification support(MVS)systems.The MVS approach relies on the top-down assimilation and inversion of atmospheric CO_(2)concentrations,as recommended by the Intergovernmental Panel on Climate Change(IPCC)Inventory Guidelines in 2019.However,the regional high-resolution assimilation and inversion method is still in its initial stage of development.Here,we have constructed an inverse system for carbon sources and sinks at the kilometer level by coupling proper orthogonal decomposition(POD)with four-dimensional variational(4DVar)data assimilation based on the weather research and forecasting-greenhouse gas(WRF-GHG)model.Our China Carbon Monito ring and Verification Support at the Regional level(CCMVS-R)system can continuously assimilate information on atmospheric CO_(2)and other related information and realize the inversion of regional and local anthropogenic carbon emissions and natural terrestrial ecosystem carbon exchange.Atmospheric CO_(2)data were collected from six ground-based monito ring sites in Shanxi Province,China to verify the inversion effect of regio nal anthropogenic carbon emissions by setting ideal and real experiments using a two-layer nesting method(at 27 and 9 km).The uncertainty of the simulated atmospheric CO_(2)decreased significantly,with a root-mean-square error of CO_(2)concentration values between the ideal value and the simulated after assimilation was close to 0.The total anthropogenic carbon emissions in Shanxi Province in 2019 from the assimilated inversions were approximately 28.6%(17%-38%)higher than the mean of five emission inventories using the bottomup method,showing that the top-down CCMVS-R system can obtain more comprehensive information on anthropogenic carbon emissions.
基金financially supported by the General Project of Top-Design of Mlti-Scale Nature-Social Models,Data Support and Decision Support System for NSFC Carbon Neutrality Major Project and the Basic Scientific Research Fund of the Chinese Academy of Meteorological Sciences(2021Z014)。
文摘The 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories added the method of assimilating atmospheric CO_(2) concentrations to invert carbon sources and sinks;however,many global carbon inversion models are not publicly available.In addition,our regional assimilation inversion system,CCMVS-R(China Carbon Monitoring,Verification and Supporting for Regional),needs a global carbon inversion model with higher assimilation efficiency to provide boundary conditions.Here,an inversion model based on the global atmospheric chemistry model GEOS-Chem and a more accurate and easier-to-implement ensemble square root Kalman filter(EnSRF)algorithm is constructed and used to infer global and China's carbon fluxes in 2019.Atmospheric CO_(2) concentrations from ObsPack sites and five additional CO_(2) observational sites from China's Greenhouse Gas Observation Network(CGHGNET)were used for data assimilation to improve the estimate.The inverted annual global terrestrial and oceanic carbon uptake is 2.12 and 2.53 Pg C per year,respectively,accounting for 21.1%and 25.1%of global fossil fuel CO_(2) emissions.The remaining 5.41 Pg C per year in the atmosphere is consistent with the global atmospheric CO_(2) growth rates of 5.44 Pg C per year reported by the National Oceanic and Atmospheric Administration(NOAA),showing that the inversion model can provide a reasonable estimate of global-scale natural carbon sinks.The inverted terrestrial carbon sink of China is 0.37 Pg C per year,accounting for approximately 13%of China's fossil CO_(2) emissions.
基金supported by the National Natural Science Foundation of China(42341202)the Basic Scientific Research Fund of the Chinese Academy of Meteorological Sciences(2021Z014)。
