Developing an anthropogenic carbon dioxides(CO_(2))emissions monitoring and verification support(MVS)capacity is essential to support the Global Stocktake(GST)and ratchet up Nationally Determined Contributions(NDCs).T...Developing an anthropogenic carbon dioxides(CO_(2))emissions monitoring and verification support(MVS)capacity is essential to support the Global Stocktake(GST)and ratchet up Nationally Determined Contributions(NDCs).The 2019 IPCC refinement proposes top-down inversed CO_(2)emissions,primarily from fossil fuel(FFCO_(2)),as a viable emission dataset.Despite substantial progress in directly inferring FFCO_(2)emissions from CO_(2)observations,substantial challenges remain,particularly in distinguishing local CO_(2)enhancements from the high background due to the long atmospheric lifetime.Alternatively,using short-lived and co-emitted nitrogen dioxide(NO_(2))as a proxy in FFCO_(2)emission inversion has gained prominence.This methodology is broadly categorized into plume-based and emission ratios(ERs)-based inversion methods.In the plume-based methods,NO_(2)observations act as locators,constraints,and validators for deciphering CO_(2)plumes downwind of sources,typically at point source and city scales.The ERs-based inversion approach typically consists of two steps:inferring NO_(2)-based nitrogen oxides(NO_(x))emissions and converting NO_(x)to CO_(2)emissions using CO_(2)-to-NO_(x)ERs.While integrating NO_(2)observations into FFCO_(2)emission inversion offers advantages over the direct CO_(2)-based methods,uncertainties persist,including both structural and data-related uncertainties.Addressing these uncertainties is a primary focus for future research,which includes deploying nextgeneration satellites and developing advanced inversion systems.Besides,data caveats are necessary when releasing data to users to prevent potential misuse.Advancing NO_(2)-based CO_(2)emission inversion requires interdisciplinary collaboration across multiple communities of remote sensing,emission inventory,transport model improvement,and atmospheric inversion algorithm development.展开更多
基金supported by the National Natural Science Foundation of China(No.42105094).
文摘Developing an anthropogenic carbon dioxides(CO_(2))emissions monitoring and verification support(MVS)capacity is essential to support the Global Stocktake(GST)and ratchet up Nationally Determined Contributions(NDCs).The 2019 IPCC refinement proposes top-down inversed CO_(2)emissions,primarily from fossil fuel(FFCO_(2)),as a viable emission dataset.Despite substantial progress in directly inferring FFCO_(2)emissions from CO_(2)observations,substantial challenges remain,particularly in distinguishing local CO_(2)enhancements from the high background due to the long atmospheric lifetime.Alternatively,using short-lived and co-emitted nitrogen dioxide(NO_(2))as a proxy in FFCO_(2)emission inversion has gained prominence.This methodology is broadly categorized into plume-based and emission ratios(ERs)-based inversion methods.In the plume-based methods,NO_(2)observations act as locators,constraints,and validators for deciphering CO_(2)plumes downwind of sources,typically at point source and city scales.The ERs-based inversion approach typically consists of two steps:inferring NO_(2)-based nitrogen oxides(NO_(x))emissions and converting NO_(x)to CO_(2)emissions using CO_(2)-to-NO_(x)ERs.While integrating NO_(2)observations into FFCO_(2)emission inversion offers advantages over the direct CO_(2)-based methods,uncertainties persist,including both structural and data-related uncertainties.Addressing these uncertainties is a primary focus for future research,which includes deploying nextgeneration satellites and developing advanced inversion systems.Besides,data caveats are necessary when releasing data to users to prevent potential misuse.Advancing NO_(2)-based CO_(2)emission inversion requires interdisciplinary collaboration across multiple communities of remote sensing,emission inventory,transport model improvement,and atmospheric inversion algorithm development.
