Constraint of satellite CO_(2)retrieval on the global carbon cycle from a Chinese atmospheric inversion system

Satellite carbon dioxide(CO_(2))retrievals provide important constraints on surface carbon fluxes in regions that are undersampled by global in situ networks.In this study,we developed an atmospheric inversion system to infer CO_(2)sources and sinks from Orbiting Carbon Observatory-2(OCO-2)column CO_(2)retrievals during 2015–2019,and compared our estimates to five other state-of-the-art inversions.By assimilating satellite CO_(2)retrievals in the inversion,the global net terrestrial carbon sink(net biome productivity,NBP)was found to be 1.03±0.39 petagrams of carbon per year(Pg C yr^(-1));this estimate is lower than the sink estimate of 1.46–2.52 Pg C yr^(-1),obtained using surface-based inversions.We estimated a weak northern uptake of 1.30 Pg C yr-1and weak tropical release of-0.26 Pg C yr^(-1),consistent with previous reports.By contrast,the other inversions showed a strong northern uptake(1.44–2.78 Pg C yr-1),but diverging tropical carbon fluxes,from a sink of 0.77 Pg C yr^(-1) to a source of-1.26 Pg C yr^(-1).During the 2015–2016 El Ni?o event,the tropical land biosphere was mainly responsible for a higher global CO_(2)growth rate.Anomalously high carbon uptake in the northern extratropics,consistent with concurrent extreme Northern Hemisphere greening,partially offset the tropical carbon losses.This anomalously high carbon uptake was not always found in surface-based inversions,resulting in a larger global carbon release in the other inversions.Thus,our satellite constraint refines the current understanding of flux partitioning between northern and tropical terrestrial regions,and suggests that the northern extratropics acted as anomalous high CO_(2)sinks in response to the 2015–2016 El Nino event.

Inversion and III-Posed Problem Solutions in Atmospheric Remote Sensing

With the swift advances in earth observation,satellite remote sensing and application of atmospheric radiation theory have been developed in the past decades,atmospheric sensing inversion with its algorithms is getting more and more importance.It is known that since a remote sensing equation falls into an integral equation of the first kind,thus leading to the fact that it is ill-posed and particularly the solution is unsteady,tremendous difficulties arise from the retrieval.This paper will present a simple review on the inversion techniques with some necessary remarks,before introducing the successful efforts with respect to such equations and the encouraging solutions achieved in recent decades by researchers of the world.

Application of Automatic Diagnostic Analysis on Atmospheric Horizontal Inversion Area and Freezing Rain Falling Area

The automatic diagnostic analysis on atmospheric horizontal inversion area is realized through changing the single atmospheric inversion into horizontal one based on the sounding data in Micaps system;the basic conceptual model INCLUDING atmospheric horizontal inversion area,ground 0 ℃ line,high altitude wet area,extreme point 0 ℃ line in inversion layer is buillt after the research on relationship between atmospheric horizontal inversion area and freezing rain falling area;automatic diagnostic analysis on freezing rain falling area is developed based on the conceptual model,the method is in accord well with the actual situation (freezing rain disaster weather occurred in most part of the south in beginning of 2008) and fitting rate reaches 94.4%,quantitative correlation coefficient between the area of freezing rain falling area and stations reporting freezing rain is 0.839.

Boundary Layer Characteristics and Numerical Simulation Analysis of Winter Dense Fog in Nanjing

Based on the boundary layer data of winter dense fog in 2007 from Nanjing University of Information Science & Technology,the profile characteristics of temperature,wind direction,wind speed and humidity in a dense fog weather on December 13-14 in 2007 were analyzed,as well as their evolution laws in the formation and dispersion of fog,and the boundary layer characteristics of winter dense fog in Nanjing were revealed,while the development of fog was simulated by means of mesoscale numerical model.The results showed that the formation and dispersion of fog was greatly affected by inversion and humidity in the surface layer,and the wind direction in the surface layer also had effect on the formation and dispersion of advection fog.Mesoscale numerical model could preferably simulate the evolution of temperature,humidity,vertical speed in the development of fog,and the simulation of water vapor content in the fog could forecast the formation and dispersion of fog.

Characteristics of Hydrologic Transfer between Soil and Atmosphere over Gobi near Oasis at the End of Summer

By utilizing the data observed at Dunhuang during August and September 2000 in the 'Field Experiment on Interaction between Land and Atmosphere in the Arid Region of Northwest China (FEILARNC)', the characteristics of the soil moisture, temperature, and atmospheric humidity are analyzed. It is found that the thickness of the soil temperature active layer is about 5 cm and much thinner than is typical, that not only the atmospheric humidity gradient is often inverted but also the soil moisture gradient in the shallow layer in the Gobi near oasis, that the diurnal variation of soil moisture can be divided into the four stages that are called the wet stage, the losing-water stage, the dry stage, and the attaining-water stage. It is shown that in soil moisture profiles, the depth of the soil moisture active layer is about 10 cm and soil moisture inversion is the main feature in the shallow layer during the wet stage. Such a feature as soil moisture inversion indicates that soil in the shallow layer can inhale moisture from the air through condensation in the nighttime and exhale moisture to the air through evaporation in the daytime. The condensation and evaporation constitute together the full respiration process of moisture on the ground. The formation of soil moisture inversion is related with the state of soil temperature and moisture, the intensity of atmospheric humidity inversion, and the atmospheric thermodynamic stability.

The current and future of terrestrial carbon balance over the Tibetan Plateau

The contemporary carbon balance over the Tibetan Plateau is highly uncertain with a ten-fold difference between various estimates.In a warming world,the potential exists for a large carbon release from its permafrost which could compromise China’s 2060 carbon-neutral goal.Here,we used a satellite-and inventory-based approach,ecosystem models,and atmospheric inversions to estimate that the carbon sink was 33.12–37.84 TgC yr^(–1)during 2000–2015.The carbon sink induced by climate change and increasing CO_(2) levels largely overcompensated for a livestock grazing-induced carbon source of 0.38TgC yr^(-1).By 2060,the carbon sink is projected to increase by 38.3–74.5% under moderate to high emissions scenarios,with the enhanced vegetation carbon uptake outweighing the warming-induced permafrost carbon release.The restoration of degraded grassland could sequestrate an additional 9.06 TgC yr^(-1),leading to a total carbon sink of 57.78–70.52 TgC yr^(-1).We conclude that the Tibetan Plateau’s ecosystems absorbed two-and-a-half times the amount of its cumulative fossil CO_(2) emissions during 2000–2015 and that their carbon sinks will almost double in strength in the future,helping to achieve China’s pledge to become carbon neutral by 2060.

针对中国陆地碳汇反演的大气二氧化碳浓度观测网络最优化设计

精准估算陆地生态系统碳汇对中国制定碳减排措施、实现碳中和目标有重要科学支撑作用.大气反演方法基于大气二氧化碳浓度观测数据,可有效估算地面二氧化碳通量的时空分布.目前中国陆地生态系统碳汇的大气反演估算仍有巨大不确定性,其中一个重要瓶颈在于缺乏足够的二氧化碳观测站点.本文研发了针对中国区域的大气反演框架,提出了二氧化碳观测网络的站点布设方案以最大程度降低中国陆地碳汇反演估算的不确定性.研究表明,在现有站点基础上,亟需在生长季植被生产力较高的东南、东北、华北和青藏高原地区增设二氧化碳观测站点.若在中国建设30个大气二氧化碳观测站点可将碳汇估算不确定性从每年10亿吨碳降低至3亿吨碳;建设60个站点可将不确定性进一步降低至每年2亿吨碳.这些站点将是“天-空-地”综合碳观测系统的重要组成部分,服务于中国二氧化碳收支反演和精准核算.

The status of carbon neutrality of the world’s top 5 CO_(2) emitters as seen by carbon satellites

China,the Unite States(US),the European Union(EU),India,and Russia are the world’s top 5 fossil fuel and cement CO_(2)(FFC)emitting countries or regions(CRs).It is very important to understand their status of carbon neutrality,and to monitor their future changes of net carbon fluxes(NCFs).In this study,we implemented a well-established global carbon assimilation system(GCAS,Version 2)to infer global surface carbon fluxes from May 2009 to December 2019 using both GOSAT and OCO-2 XCO_(2)retrievals.The reductions of flux uncertainty and XCO_(2)bias,and the evaluation of posterior flux show that GCAS has comparable and good performance in the 5 CRs.The results suggest that Russia has achieved carbon neutrality,but the other 4 are still far from being carbon neutral,especially China.The mean annual NCFs in China,the US,the EU,India,and Russia are 2.33±0.29,0.82±0.20,0.42±0.16,0.50±0.12,and-0.33±0.23 PgC yr^(−1),respectively.From 2010 to 2019,the NCFs showed an increasing trend in the US and India,a slight downward trend after 2013 in China,and were stable in the EU.The changes of land sinks in China and the US might be the main reason for their trends.India’s trend was mainly due to the increase of FFC emission.The relative contributions of NCFs to the global land net carbon emission of China and the EU have decreased,while those of the US and India have increased,implying the US and India must take more active measures to control carbon emissions or increase their sinks.This study indicates that satellite XCO_(2)could be successfully used to monitor the changes of regional NCFs,which is of great significance for major countries to achieve greenhouse gas control goals.

Trends and drivers of anthropogenic NOx emissions in China since 2020

Nitrogen oxides(NOx),significant contributors to air pollution and climate change,form aerosols and ozone in the atmosphere.Accurate,timely,and transparent information on NOx emissions is essential for decision-making to mitigate both haze and ozone pollution.However,a comprehensive understanding of the trends and drivers behind anthropogenic NOx emissions from Chinadthe world's largest emitterdhas been lacking since 2020 due to delays in emissions reporting.Here we show a consistent decline in China's NOx emissions from 2020 to 2022,despite increased fossil fuel consumption,utilizing satellite observations as constraints for NOx emission estimates through atmospheric inversion.This reduction is corroborated by data from two independent spaceborne instruments:the TROPOspheric Monitoring Instrument(TROPOMI)and the Ozone Monitoring Instrument(OMI).Notably,a reduction in transport emissions,largely due to the COVID-19 lockdowns,slightly decreased China's NOx emissions in 2020.In subsequent years,2021 and 2022,reductions in NOx emissions were driven by the industry and transport sectors,influenced by stringent air pollution controls.The satellite-based inversion system developed in this study represents a significant advancement in the real-time monitoring of regional air pollution emissions from space.