Detection of Anthropogenic CO_(2) Emission Signatures with TanSat CO_(2) and with Copernicus Sentinel-5 Precursor(S5P)NO_(2) Measurements:First Results

China’s first carbon dioxide(CO_(2))measurement satellite mission,TanSat,was launched in December 2016.This paper introduces the first attempt to detect anthropogenic CO_(2) emission signatures using CO_(2) observations from TanSat and NO_(2) measurements from the TROPOspheric Monitoring Instrument(TROPOMI)onboard the Copernicus Sentinel-5 Precursor(S5P)satellite.We focus our analysis on two selected cases in Tangshan,China and Tokyo,Japan.We found that the TanSat XCO_(2) measurements have the capability to capture the anthropogenic variations in the plume and have spatial patterns similar to that of the TROPOMI NO_(2) observations.The linear fit between TanSat XCO_(2) and TROPOMI NO_(2) indicates the CO_(2)-to-NO_(2) ratio of 0.8×10^(-16) ppm(molec cm^(-2))^(-1) in Tangshan and 2.3×10^(-16) ppm(molec cm^(-2))^(-1) in Tokyo.Our results align with the CO_(2)-to-NOx emission ratios obtained from the EDGAR v6 emission inventory.

基于TanSat的中国大陆CO_(2)浓度监测及驱动因子分析

基于2017年3月至2018年3月TanSat卫星观测的CO_(2)柱平均干空气混合比(XCO_(2)),利用美国航空航天局(NASA)的轨道碳观测2号(OCO-2)卫星数据与碳同化系统(CT)和总碳柱观测网络(TCCON)地面监测数据,验证了TanSat-XCO_(2)的数据精度和可靠性,分析了中国大陆五大区域XCO_(2)的区域特征,采用皮尔逊相关性分析和地理探测器的方法探讨了自然和社会经济因子对大气CO_(2)浓度的驱动作用.结果表明,TanSat卫星监测结果与OCO-2卫星监测结果基本一致,差异在(-3~3)×10^(-6)之间.XCO_(2)浓度整体随季节呈规律性波动.夏季我国大气XCO_(2)浓度区域差异明显,南部地区因人为影响较强,XCO_(2)浓度处于较高水平(>403×10^(-6)),北部地区植被的强光合作用使其XCO_(2)浓度(<401×10^(-6))低于其他地区,西部地区XCO_(2)趋势较其他区域相对平缓.归一化差值植被指数(NDVI)是影响XCO_(2)浓度变化的主要自然因子,NDVI与TanSat监测结果呈显著线性负相关(r=-0.658,P<0.05).化石燃料燃烧对XCO_(2)空间异质性的解释力最强,其与各自然因子的交互作用远大于单因子的驱动作用,且与降雨量的交互作用对大气XCO_(2)的影响最为显著(q=0.495).

A Cloud Detection Scheme for the Chinese Carbon Dioxide Observation Satellite(TANSAT)

Cloud detection is an essential preprocessing step for retrieving carbon dioxide from satellite observations of reflected sunlight. During the pre-launch study of the Chinese Carbon Dioxide Observation Satellite （TANSAT）, a cloud-screening scheme was presented for the Cloud and Aerosol Polarization Imager （CAPI）, which only performs measurements in five channels located in the visible to near-infrared regions of the spectrum. The scheme for CAPI, based on previous cloud- screening algorithms, defines a method to regroup individual threshold tests for each pixel in a scene according to the derived clear confidence level. This scheme is proven to be more effective for sensors with few channels. The work relies upon the radiance data from the Visible and Infrared Radiometer （VIRR） onboard the Chinese FengYun-3A Polar-orbiting Meteoro- logical Satellite （FY-3A）, which uses four wavebands similar to that of CAPI and can serve as a proxy for its measurements. The scheme has been applied to a number of the VIRR scenes over four target areas （desert, snow, ocean, forest） for all seasons. To assess the screening results, comparisons against the cloud-screening product from MODIS are made. The evaluation suggests that the proposed scheme inherits the advantages of schemes described in previous publications and shows improved cloud-screening results. A seasonal analysis reveals that this scheme provides better performance during warmer seasons, except for observations over oceans, where results are much better in colder seasons.

The First Global Carbon Dioxide Flux Map Derived from TanSat Measurements

Space-borne measurements of atmospheric greenhouse gas concentrations provide global observation constraints for top-down estimates of surface carbon flux.Here,the first estimates of the global distribution of carbon surface fluxes inferred from dry-air CO_2 column (XCO_2) measurements by the Chinese Global Carbon Dioxide Monitoring Scientific Experimental Satellite (Tan Sat) are presented.An ensemble transform Kalman filter (ETKF) data assimilation system coupled with the GEOS-Chem global chemistry transport model is used to optimally fit model simulations with the Tan Sat XCO_2 observations,which were retrieved using the Institute of Atmospheric Physics Carbon dioxide retrieval Algorithm for Satellite remote sensing (IAPCAS).High posterior error reduction (30%–50%) compared with a priori fluxes indicates that assimilating satellite XCO_2 measurements provides highly effective constraints on global carbon flux estimation.Their impacts are also highlighted by significant spatiotemporal shifts in flux patterns over regions critical to the global carbon budget,such as tropical South America and China.An integrated global land carbon net flux of 6.71±0.76 Gt C yr^(-1) over12 months (May 2017–April 2018) is estimated from the Tan Sat XCO_2 data,which is generally consistent with other inversions based on satellite data,such as the JAXA GOSAT and NASA OCO-2 XCO_2 retrievals.However,discrepancies were found in some regional flux estimates,particularly over the Southern Hemisphere,where there may still be uncorrected bias between satellite measurements due to the lack of independent reference observations.The results of this study provide the groundwork for further studies using current or future Tan Sat XCO_2 data together with other surfacebased and space-borne measurements to quantify biosphere–atmosphere carbon exchange.

A New TanSat XCO2 Global Product towards Climate Studies

The 1st Chinese carbon dioxide(CO2)monitoring satellite mission,TanSat,was launched in 2016.The 1st TanSat global map of CO2 dry-air mixing ratio(XCO2)measurements over land was released as version 1 data product with an accuracy of 2.11 ppmv(parts per million by volume).In this paper,we introduce a new(version 2)TanSat global XCO2 product that is approached by the Institute of Atmospheric Physics Carbon dioxide retrieval Algorithm for Satellite remote sensing(IAPCAS),and the European Space Agency(ESA)Climate Change Initiative plus(CCI+)TanSat XCO2 product by University of Leicester Full Physics(UoL-FP)retrieval algorithm.The correction of the measurement spectrum improves the accuracy(−0.08 ppmv)and precision(1.47 ppmv)of the new retrieval,which provides opportunity for further application in global carbon flux studies in the future.Inter-comparison between the two retrievals indicates a good agreement,with a standard deviation of 1.28 ppmv and a bias of−0.35 ppmv.

A New Global Solar-induced Chlorophyll Fluorescence(SIF)Data Product from TanSat Measurements

The Chinese Carbon Dioxide Observation Satellite Mission(TanSat)is the third satellite for global CO2 monitoring and is capable of detecting weak solar-induced chlorophyll fluorescence(SIF)signals with its advanced technical characteristics.Based on the Institute of Atmospheric Physics Carbon Dioxide Retrieval Algorithm for Satellite Remote Sensing(IAPCAS)platform,we successfully retrieved the TanSat global SIF product spanning the period of March 2017 to February 2018 with a physically based algorithm.This paper introduces the new TanSat SIF dataset and shows the global seasonal SIF maps.A brief comparison between the IAPCAS TanSat SIF product and the data-driven SVD(singular value decomposition)SIF product is also performed for follow-up algorithm optimization.The comparative results show that there are regional biases between the two SIF datasets and the linear correlations between them are above 0.73 for all seasons.The future SIF data product applications and requirements for SIF space observation are discussed.

TanSat Mission Achievements： from Scientific Driving to Preliminary Observations

The Chinese global carbon dioxide monitoring satellite(TanSat)was successfully launched in December 2016 and has completed its on-orbit tests and calibration.TanSat aims to measure the atmospheric Carbon Dioxide column-averaged dry air mole fractions(X_(CO_2))with a precision of 4 ppm at the regional scale,and further to derive the CO_2 global and regional fluxes.Progress toward these objectives is reviewed and the first scientific results from TanSat measurements are presented.During the design phase,Observation System Simulation Experiments(OSSE)on TanSat measurements performed prior to launch measurements using a nadir and a glint alternative mode when considering the balance of stable measurements and reduces the flux uncertainty(64%).The constellation measurements of two satellites indicate an extra 10%improvement in flux inversion if the satellite measurements have no bias and similar precision.The TanSat on-orbit test indicates that the instrument is stable and beginning to produce X_(CO_2)products.The preliminary TanSat measurements have been validated with Total Carbon Column Observing Network(TCCON)measurements and have inter-compared with OCO-2 measurements in an overlap measurement.

LM以及CIA效应对TanSat 3个波段吸收光谱的影响

分析了Line Mixing(LM)以及Collision-Induced Absorption(CIA)效应对中国全球二氧化碳监测科学实验卫星(TanSat)反演CO2所用的CO2的1.61、2.06μm以及O20.76μm 3个波段气体吸收的影响。LM效应对CO2的1.61、2.06μm气体吸收截面的影响约2%,LM以及CIA效应对O20.76μm波段的影响,在翼部达到75%,在中心区域约2%。LM效应使谱线线型变窄,使谱线中心吸收波数处吸收截面增大,翼部区域吸收截面减小。考虑LM以及CIA效应后,减小采用传统Voigt线型计算截面存在的结构性误差。分析了气体吸收截面以及LM效应随温度、气压的变化情况,LM效应在压强较大以及温度较低时对吸收截面影响较大。最后,在3个波段选择合理的气压、温度以及波数间隔,建立三维吸收截面查找表,在满足计算精度的同时节约时间,满足卫星大量观测反演的需要。

Retrieval of global terrestrial solar-induced chlorophyll fluorescence from TanSat satellite

The first Chinese Carbon Dioxide Observation Satellite Mission(TanSat), which was launched on December 21, 2016, is intended to measure atmospheric CO_2 concentration.The high spectral resolution(0.044 nm) and high SNR(360 at 15.2 mW m^(-1) sr^(-1) nm^(-1)) measurements in the region of the O_2-A band of the Atmospheric Carbon dioxide Grating Spectroradiometer(AGCS) module onboard TanSat make it possible to retrieve solar-induced chlorophyll fluorescence(SIF) from TanSat observations at the global scale.This paper aims to explore the potential of the TanSat data for global SIF retrieval.A singular vector decomposition(SVD) statistical method was employed to retrieve SIF using radiance over a micro spectral window(～2 nm) around the Fe Fraunhofer lines(centered at 758.8 nm).The global SIF at 758.8 nm was successfully retrieved with a low residual error of 0.03 mW m^(-1) sr^(-1) nm^(-1).The results show that the spatial and temporal patterns of the retrieved SIF agree well with the global terrestrial vegetation pattern.The monthly SIF products retrieved from the TanSat data were compared with other remote sensing datasets, including OCO-2 SIF, MODIS NDVI, EVI and GPP.The overall consistency between TanSat and OCO-2 SIF products(R^2= 0.86) and the consistency of the spatial patterns and temporal variations between the TanSat SIF and MODIS vegetation indices and GPP enhance our confidence in the potential and feasibility of TanSat data for SIF retrieval.TanSat, therefore, provides a new opportunity for global sampling of SIF at fine spatial resolution(2 km × 2 km), thus improving photosynthesis observations from space.

TanSat: a new star in global carbon monitoring from China

Accurate monitoring of changes in atmospheric carbon dioxide(C02)coneentration and carbon sinks/sources distribution are an important prerequisite for comprehensively understanding the global carbon cycle and correctly predicting future climate change.Satellite remote sensing is the only method to achieve this monitoring with high resolution.Although spaceborne hyperspectral remote sensing sensors have been successfully applied to monitor the concentration of C02 in the upper troposphere,they are not sensitive to changes in C02 concentrations near the Earth's surface.W让h the rapid development of sensor technology,quantitative remote sensing algorithms,satellites equipped with near-infrared and short-wave infrared hyperspectral sensors dedicated to C02 monitoring have been successively launched.

A retrieval algorithm for TanSat XCO_2 observation: Retrieval experiments using GOSAT data

This study developed a highly accurate retrieval algorithm for the column-averaged CO2 dry-air mixing ratio (XCO2) to be observed by TanSat, China's carbon dioxide observation satellite that will be launched in 2015. The Greenhouse Gases Observing Satellite (GOSAT) L1B spectrum was applied in retrieval experiment, and the results were validated with ground-observed measurements from the Total Column Carbon Observing Network (TCCON). At mid-latitudes, most results fell in the 1% error region, which correspond to the performance of GOSAT algorithm. The results also showed seasonal variation in XCO2 in both hemispheres.

The TanSat mission： preliminary global observations

The Chinese global carbon dioxide monitoring satellite (Tan Sat) was launched successfully in December2016 and has completed its on-orbit tests and calibration. Tan Sat aims to measure the atmospheric column-averaged dry air mole fractions of carbon dioxide (XCO_2) with a precision of 4 ppm at the regional scale, and in addition, to derive global and regional CO2fluxes. Progress towards these objectives is reviewed and the first scientific results from Tan Sat measurements are presented. Tan Sat on-orbit tests indicate that the Atmospheric Carbon dioxide Grating Spectrometer is in normal working status and is beginning to produce L1B products. The preliminary Tan Sat XCO_2products have been retrieved by an algorithm and compared to NASA Orbiting Carbon Observatory-2 (OCO-2) measurements during an overlapping observation period. Furthermore, the XCO_2retrievals have been validated against eight groundsite measurement datasets from the Total Carbon Column Observing Network, for which the preliminary conclusion is that Tan Sat has met the precision design requirement, with an average bias of 2.11 ppm.The first scientific observations are presented, namely, the seasonal distributions of XCO_2over land on a global scale.

Effects of spectral sampling rate and range of CO_2 absorption bands on XCO_2 retrieval from TanSat hyperspectral spectrometer

The spectral sampling rate and range of CO2absorption bands are critical for the optimal design of hyperspectral instrument for CO2observation satellite.Undersampling of spectra in space-based spectrometer significantly contaminates signals measured in the CO21.61 lm-band.The CO2dry-air column(XCO2)error due to spectral undersampling can be up to*1 ppm,which is the target precision of the Chinese Carbon Satellite(TanSat)for a single sounding.Undersampling error depends on surface albedo,solar zenith angle,and scattering properties in the atmosphere.The spectral sampling rate is recommended to be greater than 2.0 pixels per full width at half maximum to avoid undersampling.Reduction of spectral resolution and the use of narrower spectral regions can improve spectral sampling with little changes in CO2retrieval sensitivity without losing much information.The full-band approach provides direct constraints on the wavelength-dependent surface albedo and particle scattering from the measurements.To keep a broader band,we recommend reduction of the spectral resolution by a factor of two.

Analysis of XCO_2 retrieval sensitivity using simulated Chinese Carbon Satellite(TanSat) measurements

We present a study on the retrieval sensitivity of the column-averaged dry-air mole fraction of CO2(XCO2) for the Chinese carbon dioxide observation satellite(TanSat) with a full physical forward model and the optimal estimation technique. The forward model is based on the vector linearized discrete ordinate radiative transfer model(VLIDORT) and considers surface reflectance, gas absorption, and the scattering of air molecules, aerosol particles, and cloud particles. XCO2 retrieval errors from synthetic TanSat measurements show solar zenith angle(SZA), albedo dependence with values varying from 0.3 to 1 ppm for bright land surface in nadir mode and 2 to 8 ppm for dark surfaces like snow. The use of glint mode over dark oceans significantly improves the CO2 information retrieved. The aerosol type and profile are more important than the aerosol optical depth, and underestimation of aerosol plume height will introduce a bias of 1.5 ppm in XCO2. The systematic errors due to radiometric calibration are also estimated using a forward model simulation approach.

碳卫星高光谱CO_2探测仪发射前光谱定标

为了完成碳卫星高光谱CO_2探测仪的发射前光谱定标,建立了光谱定标系统,并对定标系统设计、所采用的自动化数据采集和数据处理算法等进行了研究。根据CO_2探测仪的探测原理介绍了载荷的光谱性能要求,描述了定标系统的设计与所采用的仪器设备,说明了采用自动化数据采集、旋转积分球、功率校正与暗背景校正等改进的定标方法。最后,介绍了光谱定标的数据处理方法。发射前定标结果表明:载荷三个波段的ILS能量集中度分别大于0.80,0.81和0.78;FWHM分别为0.039 2~0.042 4nm,0.123~0.128nm和0.157~0.168nm;光谱采样率区间分别为2.12~2.95、1.97~2.27和1.92~2.26。对发射后实测太阳夫朗禾费光谱进行了评估,结果表明:中心波长偏差小于0.0013,0.058和0.065nm。CO_2探测仪整体的光谱性能指标能够达到系统设计要求。

CO_2高光谱遥感仪器的光谱参数和信噪比需求

卫星短波红外CO_2遥感获得大气低层CO2浓度信息,已成为目前国际热点研究领域。结合气候变化及碳源、汇观测需求,利用高精度大气辐射传输模式研究了高光谱分辨率、高精度CO_2探测目标的可实现性。针对高光谱CO_2探测器光栅分光、阵列探测器特点,分析了光谱分辨率、光谱采样率等关键技术指标对CO_2探测的可能影响;基于辐射敏感度因子分析了不同探测精度要求下的信噪比需求。结果表明:高光谱CO_2探测器首先应具有足够高的光谱分辨率,以便从太阳反射连续谱段中分辨出CO2吸收线;为保证CO_2光谱的准确性,光谱仪所用探测器面元应该保证光谱采样率大于2;尽管探测边界层内CO2浓度1%变化所要求的信噪比难以达到,但探测整层大气CO_2浓度1%的变化所需要的信噪比是可以实现的。

基于碳卫星的中国东北地区叶绿素荧光反演

【目的】实现基于简化物理模型方法的碳卫星叶绿素荧光反演,并将反演结果与OCO-2荧光产品进行对比。【方法】文章选取770.1 nm处受大气影响较小的KI夫琅和费暗线,利用碳卫星的L1B级星下点观测数据和对日定标数据,以中国东北为研究区,利用基于简化物理模型的荧光提取算法,反演得到中国东北地区2018年7月的叶绿素荧光信息,并利用同期MODIS数据的云掩膜产品来剔除受云影响的区域,得到晴空条件下的荧光结果。【结果】该研究反演得到的东北地区2018年7月荧光结果值介于-3～7 mW/m^2/sr/nm之间,荧光强度较大的点分布在锡林郭勒盟中西部,辽宁省的中部和东部,吉林省的西南部以及黑龙江的西部地区。【结论】将该文反演结果与OCO-2卫星的荧光产品进行对比,发现两者之间具有很好的一致性,说明基于简化物理模型的反演算法可以较好地实现碳卫星的叶绿素荧光反演。

试验区碳卫星载荷航空校飞综合试验方案设计

为了充分了解全球碳循环过程及其对气候的影响,并对CO_2排放状况提供数据支撑,扩大我国在国际气候变化方面的话语权,国家高技术研究发展计划(863计划)支持开展了"全球二氧化碳监测科学实验卫星与应用示范"项目的研究,卫星搭载了高光谱与高空间分辨率CO_2探测仪(以下简称CO_2探测仪)与云与气溶胶探测仪(以下简称CAPI探测仪),它们的监测数据将用于精确反演全球大气CO_2含量,为全球大气环境变化、温室气体探测、光化学过程、气候变迁等方面的研究与业务的需求发展提供技术依据。CO_2探测仪作为我国首台温室气体遥感监测仪器,研制难度极大,亟需通过航空校飞试验完善载荷发射前的试验环,对载荷功能和性能进行有效评估,以进一步降低卫星发射后的运行风险。此外通过航空校飞获取的对地观测数据还将为CO_2浓度反演算法的开发与验证提供较为理想的模拟数据集,对卫星发射前数据应用技术体系的贯通和卫星发射后的航空伴飞验证具有极大助益,同时为我国机载温室气体探测积累了宝贵前期经验。课题利用我国正在研制的碳卫星载荷,CO_2探测仪和CAPI探测仪,通过适应性改造,搭载在航空飞行平台上进行2个试验区的航空校飞综合试验及其地基同步综合观测试验,验证CO_2探测仪载荷对CO_2探测的功能及部分性能指标;同时为大气CO_2浓度反演算法提供试验数据,并综合地基观测等手段对校飞反演数据进行精度检验,为卫星发射后尽快发挥效益奠定技术基础。

中国二氧化碳科学实验卫星高光谱探测仪光谱指标影响分析及优化方案

中国第一颗二氧化碳科学试验卫星(碳卫星:TanSat)将搭载高光谱分辨率的光栅光谱仪.信噪比、光谱分辨率、光谱范围和光谱采样频率是决定卫星遥感监测大气二氧化碳精度的核心指标.利用中国科学院大气物理研究所自主研发的碳卫星仪器指标模拟分析系统和短波红外反演算法,分析和论证了碳卫星二氧化碳探测仪的光谱指标对二氧化碳柱平均混合比(XCO2)反演精度的影响,并利用GOSAT卫星观测数据进行了XCO2的反演试验.研究表明,低光谱采样频率主要影响二氧化碳弱吸收带(1.61 m)观测精度,可以造成XCO2反演误差达到1 ppm(1 ppm=1 L L 1).通过降低光谱分辨率,将光谱采样频率提高至2.0以上可以有效降低采样频率的影响,为提高中国碳卫星的观测精度奠定了理论基础.

森林生态系统碳储量及碳通量遥感监测研究进展

在全球CO_2浓度持续增加导致气候变暖的背景下,森林生态系统碳储量及碳通量遥感大尺度监测成为关注热点。文中深入分析了当前国内外卫星遥感观测技术对森林碳循环评估的2种途径:1)基于遥感手段估算森林生物量并推算森林碳储量,通过碳储量变化确定森林生态系统的CO_2通量。归纳各类森林生物量遥感估算方法的原理及优缺点,系统评述各类方法在大区域森林碳储量估算中存在的不确定性。2)基于CO_2温室气体观测卫星遥感数据,定量监测森林生态系统与大气CO_2通量,基于交换的CO_2通量推算森林碳储量变化。归纳遥感手段观测森林生态系统与大气CO_2通量的主要数据、方法及优缺点,系统评述各类数据及方法在森林CO_2通量时空变化特征监测、森林碳储量估算等方面取得的进展,重点分析专用CO_2浓度监测卫星数据,尤其是我国自主碳卫星数据在CO_2柱浓度反演算法研究以及不同数据源之间的对比、验证和同化研究等方面取得的进展,总结专用温室气体遥感观测数据在森林碳储量及碳通量监测方面的优势。提出利用遥感手段进行森林生态系统碳循环定量监测的研究展望。