# Review of Satellite Remote Sensing of Carbon Dioxide Inversion and Assimilation
## 2 CO2 Observation, Datasets, Global Related Research
### CO\({}_{2}\) Observation Database
#### 2.3.2 Anthropogenic Emissions Dataset  
Anthropogenic emission data is crucial for estimating the concentration of CO\({}_{2}\) in the atmosphere. This data encompasses emissions from a variety of human activities that contribute to the global carbon footprint. The primary sources of anthropogenic CO\({}_{2}\) emissions come from agricultural activities, industrial production, land use changes, and waste disposal, and are monitored and verified through carbon accounting, climate modeling, and emissions inventories. ODIAC, launched by JAXA in 2008, is a global high-resolution dataset for CO\({}_{2}\) emissions from fossil fuel combustion. Its primary aim is to provide foundational information on fossil fuel CO\({}_{2}\) emissions for global and regional flux inversions using GOSAT observations [38]. ODIAC estimates CO\({}_{2}\) emissions by combining spatial allocations of point source locations with nighttime lighting data from power plants around the world. The dataset \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Country** & **Satellite** & \begin{tabular}{c} **Detection** \\ **Payload** \\ \end{tabular} & \begin{tabular}{c} **Launching** \\ **Time** \\ \end{tabular} & \begin{tabular}{c} **Spatial** \\ **Resolution/km** \\ \end{tabular} & \begin{tabular}{c} **Spectral** \\ **Band/\(\mu\)m** \\ \end{tabular} & \begin{tabular}{c} **Spectral** \\ **Resolution/cm\({}^{-1}\)** \\ \end{tabular} & **Width/km** \\ \hline European Union & ENVISAT-1 & SCIAMACHY & 2002–2003 & 30 \(\times\) 60 & 0.24\(\sim\)2.4 & 4.2 & 960 \\ Japan & GOSAT & TANSO- & 2009–2001 & 10.5 & 0.76\(\sim\)14.3 & 0.6/0.27 & 640 \\  & & 3-band grating & & & & \\ United States & OCO-2 & \
\begin{tabular}{c} hyper \\ spectrometer \\ \end{tabular} & 2014–2007 & 1.29 \(\times\) 2.25 & 0.76\(\sim\)2.08 & 0.043/0.083/0.104 & 10.6 \\ China & TANSAT & ACGS/CAPI & 2016–2012 & 2 \(\times\) 2 & 0.76\(\sim\)2.08 & 0.044/0.125/0.165 & 18 \\ China & FY-3D & GAS/FTS & 2017–2011 & 10 & 0.75\(\sim\)2.38 & 0.6/0.27 & 2250 \\ China & GF-5 & GMI & 2018–2005 & 10.3 & 0.76\(\sim\)2.06 & 0.6/0.27 & 865 \\ Japan & GOSAT-2 & TANSO- & 2/CAL-2 & 2018–2010 & 9.7 & 0.76\(\sim\)14.3 & 0.6/0.27 & 632 \\ United States & OCO-3 &
\begin{tabular}{c} hyper \\ spectrometer \\ \end{tabular} & 2019–2005 & 1.6 \(\times\) 2.2 & 0.76\(\sim\)2.08 & 0.044/0.084/0.108 & 10.6 \\ China & GF-5-02 & GMI & 2021–2009 & 10.3 & 0.76\(\sim\)2.06 & 0.6/0.27 & 865 \\ France & MicroCarb & Infrared & 2025 & 4.5 \(\times\) 9 & 0.76\(\sim\)2.06 & - & 13.5 \\ United States & Carbon Mapper & Hyperspectral & & & & \\ United States & Carbon Mapper & imaging & 2024 & 0.03 & 0.4\(\sim\)2.5 & 0.05 & 18 \\ Japan & GOSAT-GW & TANSO-3 & 2024 & 10/1\(\sim\)3 & 0.45\(\sim\)1.6 & 0.05/0.02 & 911/90 \\ European Union & CO\({}_{2}\)M & CO\({}_{2}\)I/NO\({}_{2}\)I & 2025 & 2 \(\times\) 2 & 0.74\(\sim\)2.09 & 0.12/0.3/0.35 & 256 \\ China & TANSAT-2 & - & 2025 & 2 \(\times\) 2 & - & - & -- \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Summary of typical shortwave infrared satellites and sensors (by time). \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Data Name** & **Algorithm** & **Version** & **Time Range** & **Download Website** \\ \hline SCIAMACHY WFMD & WFM-DOAS & V4.0 & 10.2002–04.2012 & [27] \\ SCIAMACHY BESD & DOAS-BESD & V2.1.2 & 01.2003–03.2012 & [28] \\ GOSAT OCFP & UOL-FP & V7.0 & 04.2009–12.2015 & [29] \\ CO\({}_{2}\)EMMA & EMMA & V2.2 & 06.2009–06.2014 & [30] \\ GOSAT-2 ACOS & ACOS & V9r & 04.2009–08.2020 & [31] \\ GOSAT-2 SRFP & RemoTeC & V2.0.0 & 02.2019–08.2020 & [32] \\ GOSAT-2 NIES & NIES & V2.95 & 04.2009–08.2020 & [33] \\ Tansat OCFP & UOL-FP & V1.2 & 11.2017–12.2020 & [34] \\ OCO-2 ACOS & ACOS & V11.1r & 09.2014–08.2024 & [35] \\ OCO-2 FOCAL & FOCAL & V10 & 09.2014–05.2021 & [36] \\ OCO-3 ACOS & ACOS & V10.4r & 08.2019–08.2024 & [37] \\ \hline \hline \end{tabular}
\end{table} 
Table 3: XCO\({}_{2}\) product information for remote sensing satellites.