Chinese carbon dioxide observation satellite (TanSat) launched in 22 Dec 2016, after on-broad test and calibration, the TanSat starts to record the back-scattered sunlight spectrum from scientific earth observation and produced first XCO₂ data from February to July in 2017.

The optimal estimation theory was involved in TanSat XCO₂ retrieval algorithm in a full physics way with simulation of the radiance transfer in atmosphere. Gas absorption, aerosol and cirrus scattering and surface reflectance associate with wavelength dispersion have been considered in inversion for better correction the interference errors to XCO₂. In this presentation, I will show the preliminary results of XCO₂ retrieved from TanSat measurements, and inter-compared with OCO-2 results in an overlap footprint measurement over north Australia. Validation study with TCCON measurements indicate a better than 4 ppm with 8 stations. The first global XCO₂ map has represented a milestone in Chinese GHGs satellite. TanSat will release level 2 and higher level products to support carbon emission estimations and climate change studies.

Satellites have the power to provide new insights into the regional sources and sinks of the major greenhouse gases (GHG) CO₂ and CH₄ thanks to their high data density and coverage. Satellite observations play an important role in diagnosing regions where carbon is taken up and released and how these fluxes respond to climate extremes such as droughts. Recently, the focus has further expanded with the aim of separating natural from anthropogenic emission sources.

Since the launch of the first dedicated GHG sensor GOSAT almost a decade ago, a series of new sensors have been launched (NASA OCO-2, TanSat, S5P…) with further sensors expected to be launched in the coming years (GOSAT-2, MicroCarb, OCO-3…). As a consequence, we are now presented with the opportunity of an emerging ad-hoc constellation of GHG satellites providing us with an opportunity to intercompare and eventually combine observations from multiple satellites to increase data coverage and density. However, one concern is potential biases between the datasets and careful validation against ground-based datasets is essential.

China is a key region for the global carbon and methane cycle with significant emission sources. However, the frequent occurrence of high aerosol loads over China combined with insufficient ground-based validation opportunities leaves satellite observations uncertain. In this presentation, we will focus on an evaluation of satellite observations of CO2 and CH4 over China. We will intercompare GOSAT, OCO2 and TanSat datasets and assess them against model calculations that are constrained with surface in-situ data. Finally, we will discuss the use of space-based data to identify and highlight main emission areas of GHGs.

We discuss the recent recearch activities that have taken place at the Finnish Meteorological Institute related to satellite observations of greenhouse gases with links to the DRAGON project “Monitoring greenhouse gases from space: Cal/Val and applications with focus in China and high latitudes“.

The FTIR instrument in Finnish Meteorological Institute’s premise in Sodankylä is one of the sites participating in the Total Carbon Column Observing Network (TCCON). The retrievals include column-averaged, dry-air mole fractions of carbon dioxide (XCO2) and methane (XCH4). Since 2013, series of AirCore balloon launches have been performed to obtain accurate in-situ profiles of methane, carbon dioxide and carbon monoxide from troposphere to lower stratosphere. As a high latitude site, Sodankylä contributes to the validation of satellite observations of greenhouse gases in boreal and arctic regions. The recent and on-going validation activities and campaigns that have taken place in Sodankylä are also discussed.

In addition, we have studied the spatiotemporal distribution of greenhouse gases by analysing spatially and temporally OCO-2 and GOSAT data. The developed methods and results are applicable also to TanSat data.

Anthropogenic CO₂ emissions from fossil fuel combustion have large impacts on climate. In order to monitor the increasing CO₂ concentrations in the atmosphere, accurate spaceborne observations—as available from the Orbiting Carbon Observatory-2 (OCO-2)—are needed. In our recent work [Hakkarainen et al., 2016] we provided a new approach to study anthropogenic CO₂ emission areas by deseasonalizing and detrending OCO-2 XCO₂ observations for deriving XCO₂ anomalies. The spatial distribution of the XCO₂ anomaly matches the features observed in the maps of the Ozone Monitoring Instrument NO₂ tropospheric columns, used as an indicator of atmospheric pollution, as well as the features observed in the ODIAC emission dataset. In addition, the results of a cluster analysis confirmed the correlation between CO₂ and NO₂ spatial patterns.

In this work, we study this idea further and provide the global XCO₂ anomaly maps for three full years 2015, 2016 and 2017. The patterns observed in these maps are compared with inventory-based estimates given by the Lagrangian particle dispersion model FLEXPART driven by the high-resolution ODIAC emission dataset. We also analyze the changes observed in XCO₂ anomaly maps and compare these changes to the inventory-based estimates, as well as to the changes observed in other trace gases (NO₂ and SO₂).

References

Hakkarainen, J., I. Ialongo, and J. Tamminen (2016), Direct space-based observations of anthropogenic CO2 emission areas from OCO-2, Geophys. Res. Lett., 43, 11,400–11,406, doi:10.1002/2016GL070885.

CO₂ anthropogenic emissions contribute 37 Gt CO₂ to the global carbon budget. The emissions of carbon dioxide arise from different anthropogenic activities with the dominant contribution from burning of fossil fuel especially for power generation and the industry and transport sectors. The quickly growing economy of China has, in recent years, become the largest emitter of CO₂ generating about 30% of all emissions. Cities and urban areas, where the human activities are very intense, are responsible for over 70% of all CO₂ emissions highlighted the need for a better understanding of emissions form these urban areas.

New satellite observations of CO₂, in particular from NASA’s OCO-2 launched in 2014 and the Chinese TanSat launched in 2016 provide the opportunity to monitor CO₂ concentration over polluted areas in the scale of big cities and individual point sources due to the small size of its footprint of ~ 4 km².

The goal of this study is to investigate if and how well we can observe anthropogenic enhancement of total column dry air CO₂ mole fraction (XCO₂) from space over densely populated areas as well as for individual large cities. We will focus on Eastern China as well as selected megacities globally.

We will show an evaluation of current model calculations such as Copernicus Atmosphere Monitoring Service (CAMS) against space-based data and present first result based on a high-resolution modelling approach that allows interpretation of individual soundings/orbits.

In recent years, the continuous rise in the concentrations of greenhouse gases has drawn a great attention of the international community, especially for carbon dioxide (CO₂) and methane (CH₄). The sources and sinks of CO₂ and CH₄ in the atmosphere are distributed unevenly and subjected to a variety of transport. The high-precision observation of CO₂ and CH₄ provides a foundation for the assessment of carbon emissions and a basis for the study of carbon cycle Much effort has been done by the government and research groups to monitor and quantify the magnitude and distribution of greenhouse gases, including both domestic and international.

High-accuracy continuous measurements of CO₂ and CH₄ at Xinglong (40°24'N, 117°30'E, 940 m a.s.l.) located at ~150km northeast of Beijing from May 2016 to December 2017 were made based on cavity ring down spectroscopy (CRDS) analyzer. The calibration data, seasonal and diurnal variations, influence of local wind and regional transport have been discussed. To understand different regional background in China, the seasonal cycles of CO₂ and CH₄ at Xinglong have been compared the results from Mt.Waliguan and Shangdianzi.

The calibration result shows that the accuracies of measurements of the instrument meet the compatibility goals of WMO/GAW. CO₂ concentration is high in winter and low in summer while CH₄ concentration is high in summer as well as in middle autumn and low in spring. The seasonal variation for CO₂ is mainly due to the combination influence of photosynthesis and respiration of plants. The regional transportation is another important factor. The air mass from southwest-south-southeast of the station such as Beijing, Hebei and Jinan may contribute to the relative high concentrations, especially in summer and autumn. The higher CH₄ concentration occurs in summer and middle autumn due to the gradual degradation of anaerobic microorganisms emitting large quantities of CH₄ in local area and fossil combustion emissions from Beijing-Tianjin-Hebei in summer and autumn. What’s more, Mongolia is another potential source area for both CO₂ and CH₄ in autumn and winter.

The diurnal patterns of CO₂ and CH₄ both show relatively low value in the noon. For CO₂ it is because the strong sunshine in the noon which is conductive to the stronger mixing of near-surface air with lower CO₂ concentrations aloft. While for CH₄ it is the increasing OH radicals in the atmosphere after sunrise that leads to the decrease of CH₄.The stable boundary in the afternoon and at night helps the accumulations of CO₂ and CH₄ in the afternoon.

The seasonal variations of CO₂ comparisons between Xinglong, Shangdianzi and Mt.Waliguan show that the patterns are the similar in the 3 sites for CO₂,high in summer and low in other seasons. The pattern for CH₄ at Xinglong is high in summer, middle autumn and winter while low in spring. However, the variation of atmospheric CH₄ in Mt.Waliguan and Shangdianzi is only high in summer and smaller than other 2 stations.