Monitoring fossil fuel CO<sub>2</sub> emissions from co-emitted NO<sub>2</sub> observed from space: progress, challenges, and future perspectives

doi:10.1007/s11783-025-1922-x

2025, Vol. 19

Issue (1) : 2 https://doi.org/10.1007/s11783-025-1922-x

Monitoring fossil fuel CO₂ emissions from co-emitted NO₂ observed from space: progress, challenges, and future perspectives

Hui Li^1,², Jiaxin Qiu^1,², Kexin Zhang^1,², Bo Zheng^1,²(

)

¹. Shenzhen Key Laboratory of Ecological Remediation and Carbon Sequestration, Institute of Environment and Ecology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
². State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China

Download: PDF(5056 KB) HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

Abstract

Developing an anthropogenic carbon dioxides (CO₂) 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 CO₂ emissions, primarily from fossil fuel (FFCO₂), as a viable emission dataset. Despite substantial progress in directly inferring FFCO₂ emissions from CO₂ observations, substantial challenges remain, particularly in distinguishing local CO₂ enhancements from the high background due to the long atmospheric lifetime. Alternatively, using short-lived and co-emitted nitrogen dioxide (NO₂) as a proxy in FFCO₂ 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, NO₂ observations act as locators, constraints, and validators for deciphering CO₂ plumes downwind of sources, typically at point source and city scales. The ERs-based inversion approach typically consists of two steps: inferring NO₂-based nitrogen oxides (NO_x) emissions and converting NO_x to CO₂ emissions using CO₂-to-NO_x ERs. While integrating NO₂ observations into FFCO₂ emission inversion offers advantages over the direct CO₂-based methods, uncertainties persist, including both structural and data-related uncertainties. Addressing these uncertainties is a primary focus for future research, which includes deploying next-generation satellites and developing advanced inversion systems. Besides, data caveats are necessary when releasing data to users to prevent potential misuse. Advancing NO₂-based CO₂ emission inversion requires interdisciplinary collaboration across multiple communities of remote sensing, emission inventory, transport model improvement, and atmospheric inversion algorithm development.

Keywords Fossil fuel CO₂ emissions CO₂ satellites NO₂ satellites Emission inversion methods Uncertainty management Future perspectives

Corresponding Author(s): Bo Zheng

Just Accepted Date: 29 August 2024 Issue Date: 29 October 2024

Cite this article:

Hui Li,Jiaxin Qiu,Kexin Zhang, et al. Monitoring fossil fuel CO₂ emissions from co-emitted NO₂ observed from space: progress, challenges, and future perspectives[J]. Front. Environ. Sci. Eng., 2025, 19(1): 2.

URL:

https://academic.hep.com.cn/fese/EN/10.1007/s11783-025-1922-x
https://academic.hep.com.cn/fese/EN/Y2025/V19/I1/2

Tab.1 Summary of major CO₂ monitoring satellites since 2000

Category	Method	Main formula/Model	Parameter/Input	Case study
Data-driven	Gaussian plume method (GP)	$V (x, y) = Q 2 π σ (x) e − y 2 2 σ 2 (x)$	$V (x, y) :$ Vertical columnx: Distance parallel to the wind directiony: Distance perpendicular to the wind directionQ: Emission flux $σ (x) :$ Standard deviation	Nassar et al. (2017)
	Cross-sectional flux method (CSF)	$E = U ∝ a b Δ Ω (x, y) d y$	E: Emission rate $Δ Ω$ : XCO₂ enhancements relative to backgroundU: Wind speed	Reuter et al. (2019)
	Integrated mass enhancement method (IME)	$E = U e f f × I M E L$	E: Emission rateIME: Integrated mass enhancement above the background $U e f f$ : Effective wind speedL: Radial plume length	Cusworth et al. (2023)
	Divergence method (Div)	$E = ∇ F + S$	E: Emission rate $∇$ F: Divergence of fluxS: Sinks	Hakkarainen et al, (2022)
Model-driven	Eulerian models	WRF-Chem/WRF-GHG	Reanalysis of wind fields/Prior emissions	Pillai et al. (2016)
Model-driven	Lagrangian models	STILT/XSTILT/ FLEXPART/HYSPLIT	Reanalysis of wind fields/Prior emissions	Wu et al. (2020)

Tab.2 Overview of commonly used CO₂ emission inversion methods

Tab.3 Summary of major NO₂ monitoring satellites over the past three decades

Fig.1 Overview of NO_x emission inversion methods.

Fig.2 Co-emission characteristics of CO₂ and NO_x during fossil fuel combustion. Note that the sectoral CO₂-to-NO_x emission ratios (ERs) are for China in 2019 derived from the Multi-resolution Emission Inventory for China (MEIC).

Fig.3 Two categories of NO₂-based CO₂ emission estimate methods.

Fig.4 Uncertainties in NO₂-based CO₂ emission inversion (black labels in the inner ring) and possible solutions (white labels in the outer ring).

Fig.5 Future perspectives of NO₂-based CO₂ emission inversion method.

1	D Abel, T Holloway, R M Kladar, P Meier, D Ahl, M Harkey, J Patz. (2017). Response of power plant emissions to ambient temperature in the Eastern United States. Environmental Science & Technology, 51(10): 5838–5846 https://doi.org/10.1021/acs.est.6b06201
2	L Ammoura, I Xueref-Remy, V Gros, A Baudic, B Bonsang, J E Petit, O Perrussel, N Bonnaire, J Sciare, F Chevallier. (2014). Atmospheric measurements of ratios between CO2 and co-emitted species from traffic: a tunnel study in the Paris megacity. Atmospheric Chemistry and Physics, 14(23): 12871–12882 https://doi.org/10.5194/acp-14-12871-2014
3	K Attermeyer, J P Casas-Ruiz, T Fuss, A Pastor, S Cauvy-Fraunié, D Sheath, A C Nydahl, A Doretto, A P Portela, B C Doyle. et al.. (2021). Carbon dioxide fluxes increase from day to night across European streams. Communications Earth & Environment, 2(1): 118 https://doi.org/10.1038/s43247-021-00192-w
4	R Bares, J C Lin, S W Hoch, M Baasandorj, D L Mendoza, B Fasoli, L Mitchell, D Catharine, B B Stephens. (2018). The wintertime covariation of CO2 and criteria pollutants in an urban valley of the Western United States. Journal of Geophysical Research. Atmospheres, 123(5): 2684–2703 https://doi.org/10.1002/2017JD027917
5	S Beirle, K F Boersma, U Platt, M G Lawrence, T Wagner. (2011). Megacity emissions and lifetimes of nitrogen oxides probed from space. Science, 333(6050): 1737–1739 https://doi.org/10.1126/science.1207824
6	S Beirle, C Borger, S Dörner, A Li, Z Hu, F Liu, Y Wang, T Wagner. (2019). Pinpointing nitrogen oxide emissions from space. Science Advances, 5(11): eaax9800 https://doi.org/10.1126/sciadv.aax9800
7	S Beirle, C Borger, A Jost, T Wagner. (2023). Improved catalog of NOx point source emissions (version 2). Earth System Science Data, 15(7): 3051–3073 https://doi.org/10.5194/essd-15-3051-2023
8	E V Berezin, I B Konovalov, P Ciais, A Richter, S Tao, G Janssens-Maenhout, M Beekmann, E D Schulze. (2013). Multiannual changes of CO2 emissions in China: indirect estimates derived from satellite measurements of tropospheric NO2 columns. Atmospheric Chemistry and Physics, 13(18): 9415–9438 https://doi.org/10.5194/acp-13-9415-2013
9	S Bernd, B Z Jean-Loup, L S Armin, M Yasjka (2019). The European CO2 monitoring mission: observing anthropogenic greenhouse gas emissions from space. Proc. SPIE 11180, International Conference on Space Optics—ICSO 2018, 111800M (12 July 2019, Chania, Greece)
10	S Bernd, F Valerie, J L Bézy, Y Meijer, Y Durand, G B Courrèges-Lacoste, C Pachot, A Löscher, H Nett, K Minoglou, et al. (2021). The Copernicus CO2M mission for monitoring anthropogenic carbon dioxide emissions from space. Proc. SPIE 11852, International Conference on Space Optics — ICSO 2020, 118523M (11 June 2021, Online Only)
11	K F Boersma, D J Jacob, M Trainic, Y Rudich, I Desmedt, R Dirksen, H J Eskes. (2009). Validation of urban NO2 concentrations and their diurnal and seasonal variations observed from the SCIAMACHY and OMI sensors using in situ surface measurements in Israeli cities. Atmospheric Chemistry and Physics, 9(12): 3867–3879 https://doi.org/10.5194/acp-9-3867-2009
12	H Bovensmann, M Buchwitz, J P Burrows, M Reuter, T Krings, K Gerilowski, O Schneising, J Heymann, A Tretner, J Erzinger. (2010). A remote sensing technique for global monitoring of power plant CO2 emissions from space and related applications. Atmospheric Measurement Techniques, 3(4): 781–811 https://doi.org/10.5194/amt-3-781-2010
13	H Bovensmann, J P Burrows, M Buchwitz, J Frerick, S Noël, V V Rozanov, K V Chance, A P H Goede. (1999). SCIAMACHY: mission objectives and measurement modes. Journal of the Atmospheric Sciences, 56(2): 127–150 https://doi.org/10.1175/1520-0469(1999)056<0127:SMOAMM>2.0.CO;2
14	G Broquet, F M Bréon, E Renault, M Buchwitz, M Reuter, H Bovensmann, F Chevallier, L Wu, P Ciais. (2018). The potential of satellite spectro-imagery for monitoring CO2 emissions from large cities. Atmospheric Measurement Techniques, 11(2): 681–708 https://doi.org/10.5194/amt-11-681-2018
15	M Buchwitz, M Reuter, S Noël, K Bramstedt, O Schneising, M Hilker, Andrade B Fuentes, H Bovensmann, J P Burrows, Noia A Di. et al.. (2021). Can a regional-scale reduction of atmospheric CO2 during the COVID-19 pandemic be detected from space? A case study for East China using satellite XCO2 retrievals. Atmospheric Measurement Techniques, 14(3): 2141–2166 https://doi.org/10.5194/amt-14-2141-2021
16	J P Burrows, E Hölzle, A P H Goede, H Visser, W Fricke. (1995). SCIAMACHY: scanning imaging absorption spectrometer for atmospheric chartography. Acta Astronautica, 35(7): 445–451 https://doi.org/10.1016/0094-5765(94)00278-T
17	J P Burrows, M Weber, M Buchwitz, V Rozanov, A Ladstätter-Weißenmayer, A Richter, R Debeek, R Hoogen, K Bramstedt, K U Eichmann. et al.. (1999). The global ozone monitoring experiment (GOME): mission concept and first scientific results. Journal of the Atmospheric Sciences, 56(2): 151–175 https://doi.org/10.1175/1520-0469(1999)056<0151:TGOMEG>2.0.CO;2
18	B Byrne, D F Baker, S Basu, M Bertolacci, K W Bowman, D Carroll, A Chatterjee, F Chevallier, P Ciais, N Cressie. et al.. (2023). National CO2 budgets (2015–2020) inferred from atmospheric CO2 observations in support of the global stocktake. Earth System Science Data, 15(2): 963–1004 https://doi.org/10.5194/essd-15-963-2023
19	A Chatterjee, M M Gierach, A J Sutton, R A Feely, D Crisp, A Eldering, M R Gunson, C W O’Dell, B B Stephens, D S Schimel. (2017). Influence of El Niño on atmospheric CO2 over the tropical Pacific Ocean: findings from NASA’s OCO-2 mission. Science, 358(6360): eaam5776 https://doi.org/10.1126/science.aam5776
20	F Chevallier, G Broquet, B Zheng, P Ciais, A Eldering. (2022). Large CO2 emitters as seen from satellite: comparison to a gridded global emission inventory. Geophysical Research Letters, 49(5): e2021GL097540 https://doi.org/10.1029/2021GL097540
21	F Chevallier, B Zheng, G Broquet, P Ciais, Z Liu, S J Davis, Z Deng, Y Wang, F-M Bréon, C W O’Dell. (2020). Local anomalies in the column-averaged dry air mole fractions of carbon dioxide across the globe during the first months of the coronavirus recession. Geophysical Research Letters, 47(22): e2020GL090244 https://doi.org/10.1029/2020GL090244
22	M Choulga, G Janssens-Maenhout, I Super, E Solazzo, A Agusti-Panareda, G Balsamo, N Bousserez, M Crippa, Van Der Gon H Denier, R Engelen. et al.. (2021). Global anthropogenic CO2 emissions and uncertainties as a prior for Earth system modelling and data assimilation. Earth System Science Data, 13(11): 5311–5335 https://doi.org/10.5194/essd-13-5311-2021
23	P Ciais, A J Dolman, A Bombelli, R Duren, A Peregon, P J Rayner, C Miller, N Gobron, G Kinderman, G Marland. et al.. (2014). Current systematic carbon-cycle observations and the need for implementing a policy-relevant carbon observing system. Biogeosciences, 11(13): 3547–3602 https://doi.org/10.5194/bg-11-3547-2014
24	M Cooper, R V Martin, A Padmanabhan, D K Henze. (2017). Comparing mass balance and adjoint methods for inverse modeling of nitrogen dioxide columns for global nitrogen oxide emissions. Journal of Geophysical Research. Atmospheres, 122(8): 4718–4734 https://doi.org/10.1002/2016JD025985
25	M J Cooper, R V Martin, M S Hammer, P F Levelt, P Veefkind, L N Lamsal, N A Krotkov, J R Brook, C A Mclinden. (2022). Global fine-scale changes in ambient NO2 during COVID-19 lockdowns. Nature, 601(7893): 380–387 https://doi.org/10.1038/s41586-021-04229-0
26	S M Correa. (1993). A Review of NOx Formation Under Gas-Turbine Combustion Conditions. Combustion Science and Technology, 87(1−6): 329–362 https://doi.org/10.1080/00102209208947221
27	D Crisp, H R Pollock, R Rosenberg, L Chapsky, R A M Lee, F A Oyafuso, C Frankenberg, C W O’Dell, C J Bruegge, G B Doran. et al.. (2017). The on-orbit performance of the Orbiting Carbon Observatory-2 (OCO-2) instrument and its radiometrically calibrated products. Atmospheric Measurement Techniques, 10(1): 59–81 https://doi.org/10.5194/amt-10-59-2017
28	D H Cusworth, A K Thorpe, C E Miller, A K Ayasse, R Jiorle, R M Duren, R Nassar, J P Mastrogiacomo, R R Nelson. (2023). Two years of satellite-based carbon dioxide emission quantification at the world’s largest coal-fired power plants. Atmospheric Chemistry and Physics, 23(22): 14577–14591 https://doi.org/10.5194/acp-23-14577-2023
29	B de Foy, J J Schauer. (2022). An improved understanding of NOx emissions in South Asian megacities using TROPOMI NO2 retrievals. Environmental Research Letters, 17(2): 024006 https://doi.org/10.1088/1748-9326/ac48b4
30	I del Portillo, B G Cameron, E F Crawley. (2019). A technical comparison of three low earth orbit satellite constellation systems to provide global broadband. Acta Astronautica, 159: 123–135 https://doi.org/10.1016/j.actaastro.2019.03.040
31	J Dumont Le Brazidec, P Vanderbecken, A Farchi, M Bocquet, J Lian, G Broquet, G Kuhlmann, A Danjou, T Lauvaux. (2023). Segmentation of XCO2 images with deep learning: application to synthetic plumes from cities and power plants. Geoscientific Model Development, 16(13): 3997–4016 https://doi.org/10.5194/gmd-16-3997-2023
32	J Dumont Le Brazidec, P Vanderbecken, A Farchi, G Broquet, G Kuhlmann, M Bocquet. (2024). Deep learning applied to CO2 power plant emissions quantification using simulated satellite images. Geoscientific Model Development, 17(5): 1995–2014 https://doi.org/10.5194/gmd-17-1995-2024
33	M Eby, K Zickfeld, A Montenegro, D Archer, K J Meissner, A J Weaver. (2009). Lifetime of anthropogenic climate change: millennial time scales of potential CO2 and surface temperature perturbations. Journal of Climate, 22(10): 2501–2511 https://doi.org/10.1175/2008JCLI2554.1
34	Editorial. (2023). Global stocktake and beyond. Nature Climate Change, 13(10): 999 https://doi.org/10.1038/s41558-023-01845-8
35	S G Eduardo Calvo Buendia, Limmeechokchai B, Pipatti R, Rojas Y, Sturgiss R, Tanabe K, Wirth T, Romano D J W, Garg A, Weitz M M, et al. (2019). 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories_Overview. Genève: The Intergovernmental Panel on Climate Change
36	A Eldering, T E Taylor, C W O’Dell, R Pavlick. (2019). The OCO-3 mission: measurement objectives and expected performance based on 1 year of simulated data. Atmospheric Measurement Techniques, 12(4): 2341–2370 https://doi.org/10.5194/amt-12-2341-2019
37	A Eldering, P O Wennberg, D Crisp, D S Schimel, M R Gunson, A Chatterjee, J Liu, F M Schwandner, Y Sun, C W O’Dell. et al.. (2017). The Orbiting Carbon Observatory-2 early science investigations of regional carbon dioxide fluxes. Science, 358(6360): eaam5745 https://doi.org/10.1126/science.aam5745
38	C European, Ciais P, Palmer P, Scholze M, Kentarchos A, Brunhes T, Dolman H, Husband R, Holmlund K, Engelen R, et al. (2017). An Operational Anthropogenic CO2 Emissions Monitoring & Verification System: Baseline Requirements, Model Components and Functional Architecture. Brussels: Publications Office of the European Union
39	S Feng, F Jiang, H Wang, Y Liu, W He, H Wang, Y Shen, L Zhang, M Jia, W Ju, J M Chen. (2024). China’s fossil fuel CO2 emissions estimated using surface observations of coemitted NO2. Environmental Science & Technology, 58(19): 8299–8312 https://doi.org/10.1021/acs.est.3c07756
40	D P Finch, P I Palmer, T Zhang. (2022). Automated detection of atmospheric NO2 plumes from satellite data: a tool to help infer anthropogenic combustion emissions. Atmospheric Measurement Techniques, 15(3): 721–733 https://doi.org/10.5194/amt-15-721-2022
41	P Friedlingstein, M O’sullivan, M W Jones, R M Andrew, D C E Bakker, J Hauck, P Landschützer, Quéré C Le, I T Luijkx, G P Peters. et al.. (2023). Global Carbon Budget 2023. Earth System Science Data, 15(12): 5301–5369 https://doi.org/10.5194/essd-15-5301-2023
42	Y Fu, W Sun, D Fan, Z Zhang, Y Hao. (2022). An assessment of China’s industrial emission characteristics using satellite observations of XCO2, SO2, and NO2. Atmospheric Pollution Research, 13(8): 101486 https://doi.org/10.1016/j.apr.2022.101486
43	B Fuentes Andrade, M Buchwitz, M Reuter, H Bovensmann, A Richter, H Boesch, J P Burrows. (2024). A method for estimating localized CO2 emissions from co-located satellite XCO2 and NO2 images. Atmospheric Measurement Techniques, 17(3): 1145–1173 https://doi.org/10.5194/amt-17-1145-2024
44	T Fujinawa, A Kuze, H Suto, K Shiomi, Y Kanaya, T Kawashima, F Kataoka, S Mori, H Eskes, H Tanimoto. (2021). First concurrent observations of NO2 and CO2 from power plant plumes by airborne remote sensing. Geophysical Research Letters, 48(14): e2021GL092685 https://doi.org/10.1029/2021GL092685
45	D L Goldberg, M Harkey, B de Foy, L Judd, J Johnson, G Yarwood, T Holloway. (2022). Evaluating NOx emissions and their effect on O3 production in Texas using TROPOMI NO2 and HCHO. Atmospheric Chemistry and Physics, 22(16): 10875–10900 https://doi.org/10.5194/acp-22-10875-2022
46	D L Goldberg, Z Lu, T Oda, L N Lamsal, F Liu, D Griffin, C A Mclinden, N A Krotkov, B N Duncan, D G Streets. (2019a). Exploiting OMI NO2 satellite observations to infer fossil-fuel CO2 emissions from U.S. megacities. Science of the Total Environment, 695: 133805 https://doi.org/10.1016/j.scitotenv.2019.133805
47	D L Goldberg, Z Lu, D G Streets, B de Foy, D Griffin, C A Mclinden, L N Lamsal, N A Krotkov, H Eskes. (2019b). Enhanced capabilities of TROPOMI NO2: estimating NOx from North American cities and power plants. Environmental Science & Technology, 53(21): 12594–12601 https://doi.org/10.1021/acs.est.9b04488
48	S K Grange, N J Farren, A R Vaughan, R A Rose, D C Carslaw. (2019). Strong temperature dependence for light-duty diesel vehicle NOx emissions. Environmental Science & Technology, 53(11): 6587–6596 https://doi.org/10.1021/acs.est.9b01024
49	H D Graven, B B Stephens, T P Guilderson, T L Campos, D S Schimel, J E Campbell, R F Keeling. (2009). Vertical profiles of biospheric and fossil fuel-derived CO2 and fossil fuel CO2: CO ratios from airborne measurements of Δ14C, CO2 and CO above Colorado, USA. Tellus B: Chemical and Physical Meteorology, 61: 536–546 https://doi.org/10.1111/j.1600-0889.2009.00421.x
50	D Gu, Y Wang, C Smeltzer, K F Boersma. (2014). Anthropogenic emissions of NOx over China: reconciling the difference of inverse modeling results using GOME-2 and OMI measurements. Journal of Geophysical Research, D, Atmospheres, 119(12): 7732–7740 https://doi.org/10.1002/2014JD021644
51	J Hakkarainen, I Ialongo, E Koene, M E Szeląg, J Tamminen, G Kuhlmann, D Brunner (2022). Analyzing local carbon dioxide and nitrogen oxide emissions from space using the divergence method: an application to the synthetic SMARTCARB dataset. Frontiers in Remote Sensing, 3
52	J Hakkarainen, I Ialongo, T Oda, M E Szeląg, C W O’Dell, A Eldering, D Crisp. (2023). Building a bridge: characterizing major anthropogenic point sources in the South African Highveld region using OCO-3 carbon dioxide snapshot area maps and Sentinel-5P/TROPOMI nitrogen dioxide columns. Environmental Research Letters, 18(3): 035003 https://doi.org/10.1088/1748-9326/acb837
53	J Hakkarainen, I Ialongo, J Tamminen. (2016). Direct space-based observations of anthropogenic CO2 emission areas from OCO-2. Geophysical Research Letters, 43(21): 11400–11406
54	M Hao, J Zhang, R Niu, C Deng, H Liang. (2018). Application of BeiDou navigation satellite system in emergency rescue of natural hazards: a case study for field geological survey of Qinghai−Tibet plateau. Geo-Spatial Information Science, 21(4): 294–301 https://doi.org/10.1080/10095020.2018.1522085
55	S Hassinen, D Balis, H Bauer, M Begoin, A Delcloo, K Eleftheratos, Garcia S Gimeno, J Granville, M Grossi, N Hao. et al.. (2016). Overview of the O3M SAF GOME-2 operational atmospheric composition and UV radiation data products and data availability. Atmospheric Measurement Techniques, 9(2): 383–407 https://doi.org/10.5194/amt-9-383-2016
56	C He, X Lu, Y Zhang, Z Liu, F Jiang, Y Sun, M Gao, Y Liu, H Lin, J Yang, X Lin, Y Wang, C Hu, S Fan. (2024a). Revisiting the quantification of power plant CO2 emissions in the United States and China from satellite: a comparative study using three top-down approaches. Remote Sensing of Environment, 308: 114192 https://doi.org/10.1016/j.rse.2024.114192
57	Z He, L Gao, M Liang, Z C Zeng. (2024b). A survey of methane point source emissions from coal mines in Shanxi province of China using AHSI on board Gaofen-5B. Atmospheric Measurement Techniques, 17(9): 2937–2956 https://doi.org/10.5194/amt-17-2937-2024
58	H Hersbach, B Bell, P Berrisford, S Hirahara, A Horányi, J Muñoz-Sabater, J Nicolas, C Peubey, R Radu, D Schepers. et al.. (2020). The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146(730): 1999–2049 https://doi.org/10.1002/qj.3803
59	J Heymann, M Reuter, M Buchwitz, O Schneising, H Bovensmann, J P Burrows, S Massart, J W Kaiser, D Crisp. (2017). CO2 emission of Indonesian fires in 2015 estimated from satellite-derived atmospheric CO2 concentrations. Geophysical Research Letters, 44(3): 1537–1544 https://doi.org/10.1002/2016GL072042
60	X Hong, C Zhang, Y Tian, Y Zhu, Y Hao, C Liu. (2024). First TanSat CO2 retrieval over land and ocean using both nadir and glint spectroscopy. Remote Sensing of Environment, 304: 114053 https://doi.org/10.1016/j.rse.2024.114053
61	X Hong, P Zhang, Y Bi, C Liu, Y Sun, W Wang, Z Chen, H Yin, C Zhang, Y Tian, J Liu. (2022). Retrieval of Global carbon dioxide from tansat satellite and comprehensive validation with TCCON measurements and satellite observations. IEEE Transactions on Geoscience and Remote Sensing, 60: 1–16 https://doi.org/10.1109/TGRS.2021.3066623
62	P Ingmann, B Veihelmann, J Langen, D Lamarre, H Stark, G B Courrèges-Lacoste. (2012). Requirements for the GMES Atmosphere Service and ESA’s implementation concept: sentinels-4/-5 and −5p. Remote Sensing of Environment, 120: 58–69 https://doi.org/10.1016/j.rse.2012.01.023
63	IPCC(2006). 2006 IPCC Guidelines for National Greenhouse Gas Inventories: Volume 1 General Guidance and Reporting. Genève: The Intergovernmental Panel on Climate Change
64	D Jervis, J Mckeever, B O A Durak, J J Sloan, D Gains, D J Varon, A Ramier, M Strupler, E Tarrant. (2021). The GHGSat-D imaging spectrometer. Atmospheric Measurement Techniques, 14(3): 2127–2140 https://doi.org/10.5194/amt-14-2127-2021
65	M W Jones, G P Peters, T Gasser, R M Andrew, C Schwingshackl, J Gütschow, R A Houghton, P Friedlingstein, J Pongratz, Quéré C Le. (2023). National contributions to climate change due to historical emissions of carbon dioxide, methane, and nitrous oxide since 1850. Scientific Data, 10(1): 155 https://doi.org/10.1038/s41597-023-02041-1
66	P Joyce, Villena C Ruiz, Y Huang, A Webb, M Gloor, F H Wagner, M P Chipperfield, Guilló R Barrio, C Wilson, H Boesch. (2023). Using a deep neural network to detect methane point sources and quantify emissions from PRISMA hyperspectral satellite images. Atmospheric Measurement Techniques, 16(10): 2627–2640 https://doi.org/10.5194/amt-16-2627-2023
67	M Kiel, A Eldering, D D Roten, J C Lin, S Feng, R Lei, T Lauvaux, T Oda, C M Roehl, J F Blavier. et al.. (2021). Urban-focused satellite CO2 observations from the Orbiting Carbon Observatory-3: a first look at the Los Angeles megacity. Remote Sensing of Environment, 258: 112314 https://doi.org/10.1016/j.rse.2021.112314
68	H C Kim, T Chai, A Stein, S Kondragunta. (2020a). Inverse modeling of fire emissions constrained by smoke plume transport using HYSPLIT dispersion model and geostationary satellite observations. Atmospheric Chemistry and Physics, 20(17): 10259–10277 https://doi.org/10.5194/acp-20-10259-2020
69	J Kim, U Jeong, M H Ahn, J H Kim, R J Park, H Lee, C H Song, Y S Choi, K H Lee, J M Yoo. et al.. (2020b). New era of air quality monitoring from space: geostationary environment monitoring spectrometer (GEMS). Bulletin of the American Meteorological Society, 101(1): E1–E22 https://doi.org/10.1175/BAMS-D-18-0013.1
70	H Kong, J Lin, R Zhang, M Liu, H Weng, R Ni, L Chen, J Wang, Y Yan, Q Zhang. (2019). High-resolution (0.05° × 0.05°) NOx emissions in the Yangtze River Delta inferred from OMI. Atmospheric Chemistry and Physics, 19(20): 12835–12856 https://doi.org/10.5194/acp-19-12835-2019
71	I B Konovalov, E V Berezin, P Ciais, G Broquet, R V Zhuravlev, G Janssens-Maenhout. (2016). Estimation of fossil-fuel CO2 emissions using satellite measurements of “proxy” species. Atmospheric Chemistry and Physics, 16(21): 13509–13540 https://doi.org/10.5194/acp-16-13509-2016
72	E A Kort, C Frankenberg, C E Miller, T Oda. (2012). Space-based observations of megacity carbon dioxide. Geophysical Research Letters, 39(17): 2012GL052738 https://doi.org/10.1029/2012GL052738
73	G Kuhlmann, S Henne, Y Meijer, D Brunner (2021). Quantifying CO2 emissions of power plants with CO2 and NO2 imaging satellites. Frontiers in Remote Sensing, 2
74	S Kurchaba, A Sokolovsky, J Van Vliet, F J Verbeek, C J Veenman. (2024). Sensitivity analysis for the detection of NO2 plumes from seagoing ships using TROPOMI data. Remote Sensing of Environment, 304: 304 https://doi.org/10.1016/j.rse.2024.114041
75	A Kuze, H Suto, M Nakajima, T Hamazaki. (2009). Thermal and near infrared sensor for carbon observation Fourier-transform spectrometer on the Greenhouse Gases Observing Satellite for greenhouse gases monitoring. Applied Optics, 48(35): 6716–6733 https://doi.org/10.1364/AO.48.006716
76	L N Lamsal, N A Krotkov, A Vasilkov, S Marchenko, W Qin, E S Yang, Z Fasnacht, J Joiner, S Choi, D Haffner. et al.. (2021). Ozone Monitoring Instrument (OMI) Aura nitrogen dioxide standard product version 4.0 with improved surface and cloud treatments. Atmospheric Measurement Techniques, 14(1): 455–479 https://doi.org/10.5194/amt-14-455-2021
77	K Lange, A Richter, J P Burrows. (2022). Variability of nitrogen oxide emission fluxes and lifetimes estimated from Sentinel-5P TROPOMI observations. Atmospheric Chemistry and Physics, 22(4): 2745–2767 https://doi.org/10.5194/acp-22-2745-2022
78	R Lei, S Feng, A Danjou, G Broquet, D Wu, J C Lin, C W O’Dell, T Lauvaux. (2021). Fossil fuel CO2 emissions over metropolitan areas from space: a multi-model analysis of OCO-2 data over Lahore, Pakistan. Remote Sensing of Environment, 264: 112625 https://doi.org/10.1016/j.rse.2021.112625
79	R Lei, S Feng, Y Xu, S Tran, M Ramonet, M Grutter, A Garcia, M Campos-Pineda, T Lauvaux. (2022). Reconciliation of asynchronous satellite-based NO2 and XCO2 enhancements with mesoscale modeling over two urban landscapes. Remote Sensing of Environment, 281: 113241 https://doi.org/10.1016/j.rse.2022.113241
80	T Lei, D Wang, X Yu, S Ma, W Zhao, C Cui, J Meng, S Tao, D Guan (2023). Global iron and steel plant CO2 emissions and carbon-neutrality pathways. Nature, 622, 514–520
81	F Lespinas, Y Wang, G Broquet, F-M Bréon, M Buchwitz, M Reuter, Y Meijer, A Loescher, G Janssens-Maenhout, B Zheng. et al.. (2020). The potential of a constellation of low earth orbit satellite imagers to monitor worldwide fossil fuel CO2 emissions from large cities and point sources. Carbon Balance and Management, 15(1): 18 https://doi.org/10.1186/s13021-020-00153-4
82	P F Levelt, den Oord G H J van, M R Dobber, A Mälkki, H Visser, Vries J de, P Stammes, J Lundell, H. Saari. (2006). The ozone monitoring instrument. IEEE Transactions on Geoscience and Remote Sensing, 44(5): 1093–1101 https://doi.org/10.1109/TGRS.2006.872333
83	C Li, R V Martin, M W Shephard, K Cady-Pereira, M J Cooper, J Kaiser, C J Lee, L Zhang, D K Henze. (2019). Assessing the iterative finite difference mass balance and 4D-var methods to derive ammonia emissions over North America using synthetic observations. Journal of Geophysical Research. Atmospheres, 124(7): 4222–4236 https://doi.org/10.1029/2018JD030183
84	H Li, B Zheng. (2023a). TROPOMI NO2 shows a fast recovery of China’s economy in the first quarter of 2023. Environmental Science & Technology Letters, 10(8): 635–641
85	H Li, B Zheng, P Ciais, K F Boersma, T C V W Riess, R V Martin, G Broquet, Der A R Van, H Li, C Hong. et al.. (2023b). Satellite reveals a steep decline in China’s CO2 emissions in early 2022. Science Advances, 9(29): eadg7429 https://doi.org/10.1126/sciadv.adg7429
86	J Li, Y Wang, R Zhang, C Smeltzer, A Weinheimer, J Herman, K F Boersma, E A Celarier, R W Long, J J Szykman. et al.. (2021). Comprehensive evaluations of diurnal NO2 measurements during DISCOVER-AQ 2011: effects of resolution-dependent representation of NOx emissions. Atmospheric Chemistry and Physics, 21(14): 11133–11160 https://doi.org/10.5194/acp-21-11133-2021
87	S Li, S Wang, Q Wu, Y Zhang, D Ouyang, H Zheng, L Han, X Qiu, Y Wen, M Liu. et al.. (2023c). Emission trends of air pollutants and CO2 in China from 2005 to 2021. Earth System Science Data, 15(6): 2279–2294 https://doi.org/10.5194/essd-15-2279-2023
88	J T Lin, R V Martin, K F Boersma, M Sneep, P Stammes, R Spurr, P Wang, Roozendael M Van, K Clémer, H Irie. (2014). Retrieving tropospheric nitrogen dioxide from the Ozone Monitoring Instrument: effects of aerosols, surface reflectance anisotropy, and vertical profile of nitrogen dioxide. Atmospheric Chemistry and Physics, 14(3): 1441–1461 https://doi.org/10.5194/acp-14-1441-2014
89	X Lin, der A R van, Laat J de, H Eskes, F Chevallier, P Ciais, Z Deng, Y Geng, X Song, X Ni. et al.. (2023). Monitoring and quantifying CO2 emissions of isolated power plants from space. Atmospheric Chemistry and Physics, 23(11): 6599–6611 https://doi.org/10.5194/acp-23-6599-2023
90	R Lindenmaier, M K Dubey, B G Henderson, Z T Butterfield, J R Herman, T Rahn, S H Lee. (2014). Multiscale observations of CO2, 13CO2, and pollutants at four corners for emission verification and attribution. Proceedings of the National Academy of Sciences of the United States of America, 111(23): 8386–8391 https://doi.org/10.1073/pnas.1321883111
91	F Liu, S Beirle, Q Zhang, S Dörner, K He, T Wagner. (2016). NOx lifetimes and emissions of cities and power plants in polluted background estimated by satellite observations. Atmospheric Chemistry and Physics, 16(8): 5283–5298 https://doi.org/10.5194/acp-16-5283-2016
92	F Liu, B N Duncan, N A Krotkov, L N Lamsal, S Beirle, D Griffin, C A Mclinden, D L Goldberg, Z Lu. (2020). A methodology to constrain carbon dioxide emissions from coal-fired power plants using satellite observations of co-emitted nitrogen dioxide. Atmospheric Chemistry and Physics, 20(1): 99–116 https://doi.org/10.5194/acp-20-99-2020
93	J Liu, K W Bowman, D S Schimel, N C Parazoo, Z Jiang, M Lee, A A Bloom, D Wunch, C Frankenberg, Y Sun. et al.. (2017). Contrasting carbon cycle responses of the tropical continents to the 2015–2016 El Niño. Science, 358(6360): eaam5690 https://doi.org/10.1126/science.aam5690
94	S Liu, P Valks, G Curci, Y Chen, L Shu, J Jin, S Sun, D Pu, X Li, J Li. et al.. (2024). Satellite NO2 retrieval complicated by aerosol composition over global urban agglomerations: seasonal variations and long-term trends (2001–2018). Environmental Science & Technology, 58(18): 7891–7903
95	Y Liu, J Wang, L Yao, X Chen, Z Cai, D Yang, Z Yin, S Gu, L Tian, N Lu. et al.. (2018). The TanSat mission: preliminary global observations. Science Bulletin, 63(18): 1200–1207 https://doi.org/10.1016/j.scib.2018.08.004
96	Z Liu, Z Deng, S Davis, P Ciais. (2023). Monitoring global carbon emissions in 2022. Nature Reviews. Earth & Environment, 4(4): 205–206 https://doi.org/10.1038/s43017-023-00406-z
97	Z Liu, Z Deng, B Zhu, P Ciais, S J Davis, J Tan, R M Andrew, O Boucher, S B Arous, J G Canadell. et al.. (2022). Global patterns of daily CO2 emissions reductions in the first year of COVID-19. Nature Geoscience, 15(8): 615–620 https://doi.org/10.1038/s41561-022-00965-8
98	X Lu, X Ye, M Zhou, Y Zhao, H Weng, H Kong, K Li, M Gao, B Zheng, J Lin. et al.. (2021). The underappreciated role of agricultural soil nitrogen oxide emissions in ozone pollution regulation in North China. Nature Communications, 12(1): 5021 https://doi.org/10.1038/s41467-021-25147-9
99	G Luderer, S Madeddu, L Merfort, F Ueckerdt, M Pehl, R Pietzcker, M Rottoli, F Schreyer, N Bauer, L Baumstark. et al.. (2022). Impact of declining renewable energy costs on electrification in low-emission scenarios. Nature Energy, 7(1): 32–42 https://doi.org/10.1038/s41560-021-00937-z
100	C G MacDonald, J P Mastrogiacomo, J L Laughner, J K Hedelius, R Nassar, D Wunch. (2023). Estimating enhancement ratios of nitrogen dioxide, carbon monoxide and carbon dioxide using satellite observations. Atmospheric Chemistry and Physics, 23(6): 3493–3516 https://doi.org/10.5194/acp-23-3493-2023
101	G Maral, J J De Ridder, B G Evans, M Richharia. (1991). Low earth orbit satellite systems for communications. International Journal of Satellite Communications, 9(4): 209–225 https://doi.org/10.1002/sat.4600090403
102	R V Martin, D J Jacob, K Chance, T P Kurosu, P I Palmer, M J Evans. (2003). Global inventory of nitrogen oxide emissions constrained by space-based observations of NO2 columns. Journal of Geophysical Research, 108(D17): 2003JD003453 https://doi.org/10.1029/2003JD003453
103	W J Massman. (1998). A review of the molecular diffusivities of H2O, CO2, CH4, CO, O3, SO2, NH3, N2O, NO, and NO2 in air, O2 and N2 near STP. Atmospheric Environment, 32(6): 1111–1127 https://doi.org/10.1016/S1352-2310(97)00391-9
104	M Meinshausen, J Lewis, C Mcglade, J Gutschow, Z Nicholls, R Burdon, L Cozzi, B Hackmann. (2022). Realization of Paris Agreement pledges may limit warming just below 2 °C. Nature, 604(7905): 304–309 https://doi.org/10.1038/s41586-022-04553-z
105	K Miyazaki, K Bowman. (2023). Predictability of fossil fuel CO2 from air quality emissions. Nature Communications, 14(1): 1604 https://doi.org/10.1038/s41467-023-37264-8
106	K Miyazaki, H Eskes, K Sudo, K F Boersma, K Bowman, Y Kanaya. (2017). Decadal changes in global surface NOx emissions from multi-constituent satellite data assimilation. Atmospheric Chemistry and Physics, 17(2): 807–837 https://doi.org/10.5194/acp-17-807-2017
107	J Moon, Y Choi, W Jeon, H C Kim, A Pouyaei, J Jung, S Pan, S Kim, C H Kim, J Bak. et al.. (2024). Hybrid IFDMB/4D-Var inverse modeling to constrain the spatiotemporal distribution of CO and NO2 emissions using the CMAQ adjoint model. Atmospheric Environment, 327: 120490 https://doi.org/10.1016/j.atmosenv.2024.120490
108	R Nassar, T G Hill, C A Mclinden, D Wunch, D B A Jones, D Crisp. (2017). Quantifying CO2 Emissions from Individual Power Plants From Space. Geophysical Research Letters, 44(19): 10045–10053
109	R Nassar, J P Mastrogiacomo, W Bateman-Hemphill, C Mccracken, C G Macdonald, T Hill, C W O’Dell, M Kiel, D Crisp. (2021). Advances in quantifying power plant CO2 emissions with OCO-2. Remote Sensing of Environment, 264: 112579 https://doi.org/10.1016/j.rse.2021.112579
110	R Nassar, O Moeini, JP Mastrogiacomo, C W O’Dell, R R Nelson, M Kiel, A Chatterjee, A Eldering, D Crisp (2022). Tracking CO2 emission reductions from space: a case study at Europe’s largest fossil fuel power plant. Frontiers in Remote Sensing, 3
111	R Nassar, L Napier-Linton, K R Gurney, R J Andres, T Oda, F R Vogel, F Deng. (2013). Improving the temporal and spatial distribution of CO2 emissions from global fossil fuel emission data sets. Journal of Geophysical Research. Atmospheres, 118(2): 917–933 https://doi.org/10.1029/2012JD018196
112	T Nehrkorn, J Eluszkiewicz, S C Wofsy, J C Lin, C Gerbig, M Longo, S Freitas. (2010). Coupled weather research and forecasting-stochastic time-inverted lagrangian transport (WRF–STILT) model. Meteorology and Atmospheric Physics, 107(1): 51–64 https://doi.org/10.1007/s00703-010-0068-x
113	R Newman, I Noy. (2023). The global costs of extreme weather that are attributable to climate change. Nature Communications, 14(1): 6103 https://doi.org/10.1038/s41467-023-41888-1
114	S C Olsen, J T Randerson. (2004). Differences between surface and column atmospheric CO2 and implications for carbon cycle research. Journal of Geophysical Research, 109(D2): 2003JD003968 https://doi.org/10.1029/2003JD003968
115	M Ombadi, M D Risser, A M Rhoades, C Varadharajan. (2023). A warming-induced reduction in snow fraction amplifies rainfall extremes. Nature, 619(7969): 305–310 https://doi.org/10.1038/s41586-023-06092-7
116	P I Palmer, D J Jacob, A M Fiore, R V Martin, K Chance, T P Kurosu. (2003). Mapping isoprene emissions over North America using formaldehyde column observations from space. Journal of Geophysical Research, 108(D6): 2002JD002153 https://doi.org/10.1029/2002JD002153
117	H Park, S Jeong, H Park, L D Labzovskii, K W Bowman. (2021). An assessment of emission characteristics of Northern Hemisphere cities using spaceborne observations of CO2, CO, and NO2. Remote Sensing of Environment, 254: 112246 https://doi.org/10.1016/j.rse.2020.112246
118	S S Park, K Kozawa, S Fruin, S Mara, Y K Hsu, C Jakober, A Winer, J Herner. (2011). Emission Factors for high-emitting vehicles based on on-road measurements of individual vehicle exhaust with a mobile measurement platform. Journal of the Air & Waste Management Association, 61(10): 1046–1056 https://doi.org/10.1080/10473289.2011.595981
119	E Penn, T Holloway. (2020). Evaluating current satellite capability to observe diurnal change in nitrogen oxides in preparation for geostationary satellite missions. Environmental Research Letters, 15(3): 034038 https://doi.org/10.1088/1748-9326/ab6b36
120	D Pillai, M Buchwitz, C Gerbig, T Koch, M Reuter, H Bovensmann, J Marshall, J P Burrows. (2016). Tracking city CO2 emissions from space using a high-resolution inverse modelling approach: a case study for Berlin, Germany. Atmospheric Chemistry and Physics, 16(15): 9591–9610 https://doi.org/10.5194/acp-16-9591-2016
121	Z Qu, D K Henze, H M Worden, Z Jiang, B Gaubert, N Theys, W Wang. (2022). Sector-based top-down estimates of NOx, SO2, and CO emissions in East Asia. Geophysical Research Letters, 49(2): e2021GL096009 https://doi.org/10.1029/2021GL096009
122	M Reuter, M Buchwitz, A Hilboll, A Richter, O Schneising, M Hilker, J Heymann, H Bovensmann, J P Burrows. (2014). Decreasing emissions of NOx relative to CO2 in East Asia inferred from satellite observations. Nature Geoscience, 7(11): 792–795 https://doi.org/10.1038/ngeo2257
123	M Reuter, M Buchwitz, O Schneising, S Krautwurst, C W O’Dell, A Richter, H Bovensmann, J P Burrows. (2019). Towards monitoring localized CO2 emissions from space: co-located regional CO2 and NO2 enhancements observed by the OCO-2 and S5P satellites. Atmospheric Chemistry and Physics, 19(14): 9371–9383 https://doi.org/10.5194/acp-19-9371-2019
124	F Röser, O Widerberg, N Höhne, T Day. (2020). Ambition in the making: analysing the preparation and implementation process of the Nationally Determined Contributions under the Paris Agreement. Climate Policy, 20(4): 415–429 https://doi.org/10.1080/14693062.2019.1708697
125	D Santaren, G Broquet, F M Bréon, F Chevallier, D Siméoni, B Zheng, P Ciais. (2021). A local- to national-scale inverse modeling system to assess the potential of spaceborne CO2 measurements for the monitoring of anthropogenic emissions. Atmospheric Measurement Techniques, 14(1): 403–433 https://doi.org/10.5194/amt-14-403-2021
126	O Schneising, M Buchwitz, M Reuter, J Heymann, H Bovensmann, J P Burrows. (2011). Long-term analysis of carbon dioxide and methane column-averaged mole fractions retrieved from SCIAMACHY. Atmospheric Chemistry and Physics, 11(6): 2863–2880 https://doi.org/10.5194/acp-11-2863-2011
127	B J Schuit, J D Maasakkers, P Bijl, G Mahapatra, Den Berg A W Van, S Pandey, A Lorente, T Borsdorff, S Houweling, D J Varon. et al.. (2023). Automated detection and monitoring of methane super-emitters using satellite data. Atmospheric Chemistry and Physics, 23(16): 9071–9098 https://doi.org/10.5194/acp-23-9071-2023
128	F M Schwandner, M R Gunson, C E Miller, S A Carn, A Eldering, T Krings, K R Verhulst, D S Schimel, H M Nguyen, D Crisp. et al.. (2017). Spaceborne detection of localized carbon dioxide sources. Science, 358(6360): eaam5782 https://doi.org/10.1126/science.aam5782
129	V Shah, D J Jacob, R Dang, L N Lamsal, S A Strode, S D Steenrod, K F Boersma, S D Eastham, T M Fritz, C Thompson. et al.. (2023). Nitrogen oxides in the free troposphere: implications for tropospheric oxidants and the interpretation of satellite NO2 measurements. Atmospheric Chemistry and Physics, 23(2): 1227–1257 https://doi.org/10.5194/acp-23-1227-2023
130	L Shen, T Gao, J Zhao, L Wang, L Wang, L Liu, F Chen, J Xue. (2014). Factory-level measurements on CO2 emission factors of cement production in China. Renewable & Sustainable Energy Reviews, 34: 337–349 https://doi.org/10.1016/j.rser.2014.03.025
131	Q Shi, B Zheng, Y Zheng, D Tong, Y Liu, H Ma, C Hong, G Geng, D Guan, K He. et al.. (2022). Co-benefits of CO2 emission reduction from China’s clean air actions between 2013–2020. Nature Communications, 13(1): 5061 https://doi.org/10.1038/s41467-022-32656-8
132	S J Silva, A F Arellano. (2017). Characterizing regional-scale combustion using satellite retrievals of CO, NO2 and CO2. Remote Sensing, 9(7): 744 https://doi.org/10.3390/rs9070744
133	L A Singh, W R Whittecar, M D Diprinzio, J D Herman, M P Ferringer, P M Reed. (2020). Low cost satellite constellations for nearly continuous global coverage. Nature Communications, 11(1): 200 https://doi.org/10.1038/s41467-019-13865-0
134	E Solazzo, M Crippa, D Guizzardi, M Muntean, M Choulga, G Janssens-Maenhout. (2021). Uncertainties in the emissions database for global atmospheric research (EDGAR) emission inventory of greenhouse gases. Atmospheric Chemistry and Physics, 21(7): 5655–5683 https://doi.org/10.5194/acp-21-5655-2021
135	G L Squadrito, W A Pryor. (1998). Oxidative chemistry of nitric oxide: the roles of superoxide, peroxynitrite, and carbon dioxide. Free Radical Biology & Medicine, 25(4−5): 392–403 https://doi.org/10.1016/S0891-5849(98)00095-1
136	T Stavrakou, J F Müller, K F Boersma, Smedt I de, der A R J van. (2008). Assessing the distribution and growth rates of NOx emission sources by inverting a 10-year record of NO2 satellite columns. Geophysical Research Letters, 35(10): 2008GL033521 https://doi.org/10.1029/2008GL033521
137	Y Sun, C Frankenberg, J D Wood, D S Schimel, M Jung, L Guanter, D T Drewry, M Verma, A Porcar-Castell, T J Griffis. et al.. (2017). OCO-2 advances photosynthesis observation from space via solar-induced chlorophyll fluorescence. Science, 358(6360): eaam5747 https://doi.org/10.1126/science.aam5747
138	H Suto, F Kataoka, N Kikuchi, R O Knuteson, A Butz, M Haun, H Buijs, K Shiomi, H Imai, A Kuze. (2021). Thermal and near-infrared sensor for carbon observation Fourier transform spectrometer-2 (TANSO-FTS-2) on the Greenhouse gases Observing SATellite-2 (GOSAT-2) during its first year in orbit. Atmospheric Measurement Techniques, 14(3): 2013–2039 https://doi.org/10.5194/amt-14-2013-2021
139	D L Swain, D Singh, D Touma, N S Diffenbaugh. (2020). Attributing Extreme events to climate change: a new frontier in a warming world. One Earth, 2(6): 522–527 https://doi.org/10.1016/j.oneear.2020.05.011
140	L Tang, M Jia, J Yang, L Li, X Bo, Z Mi. (2023). Chinese industrial air pollution emissions based on the continuous emission monitoring systems network. Scientific Data, 10(1): 153 https://doi.org/10.1038/s41597-023-02054-w
141	T E Taylor, C W O’Dell, D Baker, C Bruegge, A Chang, L Chapsky, A Chatterjee, C Cheng, F Chevallier, D Crisp. et al.. (2023). Evaluating the consistency between OCO-2 and OCO-3 XCO2 estimates derived from the NASA ACOS version 10 retrieval algorithm. Atmospheric Measurement Techniques, 16(12): 3173–3209 https://doi.org/10.5194/amt-16-3173-2023
142	D Thompson, T D Brown, J M Beér. (1972). NOx formation in combustion. Combustion and Flame, 19(1): 69–79 https://doi.org/10.1016/S0010-2180(72)80087-7
143	K W Thoning, P P Tans, W D Komhyr. (1989). Atmospheric carbon dioxide at Mauna Loa Observatory: 2. Analysis of the NOAA GMCC data, 1974–1985. Journal of Geophysical Research, 94(D6): 8549–8565 https://doi.org/10.1029/JD094iD06p08549
144	K Tibrewal, P Ciais, M Saunois, A Martinez, X Lin, J Thanwerdas, Z Deng, F Chevallier, C Giron, C Albergel. et al.. (2024). Assessment of methane emissions from oil, gas and coal sectors across inventories and atmospheric inversions. Communications Earth & Environment, 5(1): 26 https://doi.org/10.1038/s43247-023-01190-w
145	A J Turner, D K Henze, R V Martin, A Hakami. (2012). The spatial extent of source influences on modeled column concentrations of short-lived species. Geophysical Research Letters, 39(12): 2012GL051832 https://doi.org/10.1029/2012GL051832
146	Y Ulybyshev. (2008). Satellite constellation design for complex coverage. Journal of Spacecraft and Rockets, 45(4): 843–849 https://doi.org/10.2514/1.35369
147	J van Geffen, K F Boersma, H Eskes, M Sneep, M Ter Linden, M Zara, J P Veefkind. (2020). S5P TROPOMI NO2 slant column retrieval: method, stability, uncertainties and comparisons with OMI. Atmospheric Measurement Techniques, 13(3): 1315–1335 https://doi.org/10.5194/amt-13-1315-2020
148	Geffen J van, H Eskes, S Compernolle, G Pinardi, T Verhoelst, J C Lambert, M Sneep, Linden M Ter, A Ludewig, K F Boersma. et al.. (2022). Sentinel-5P TROPOMI NO2 retrieval: impact of version v2.2 improvements and comparisons with OMI and ground-based data. Atmospheric Measurement Techniques, 15(7): 2037–2060 https://doi.org/10.5194/amt-15-2037-2022
149	T C Vance, T Huang, K A Butler. (2024). Big data in Earth science: emerging practice and promise. Science, 383(6688): eadh9607 https://doi.org/10.1126/science.adh9607
150	J P Veefkind, I Aben, K Mcmullan, H Förster, Vries J de, G Otter, J Claas, H J Eskes, Haan J F de, Q Kleipool. et al.. (2012). TROPOMI on the ESA Sentinel-5 Precursor: a GMES mission for global observations of the atmospheric composition for climate, air quality and ozone layer applications. Remote Sensing of Environment, 120: 70–83 https://doi.org/10.1016/j.rse.2011.09.027
151	V A Velazco, M Buchwitz, H Bovensmann, M Reuter, O Schneising, J Heymann, T Krings, K Gerilowski, J P Burrows. (2011). Towards space based verification of CO2 emissions from strong localized sources: fossil fuel power plant emissions as seen by a CarbonSat constellation. Atmospheric Measurement Techniques, 4(12): 2809–2822 https://doi.org/10.5194/amt-4-2809-2011
152	H Wang, F Jiang, J Wang, W Ju, J M Chen. (2019). Terrestrial ecosystem carbon flux estimated using GOSAT and OCO-2 XCO2 retrievals. Atmospheric Chemistry and Physics, 19(18): 12067–12082 https://doi.org/10.5194/acp-19-12067-2019
153	J Wei, S Liu, Z Li, C Liu, K Qin, X Liu, R T Pinker, R R Dickerson, J Lin, K F Boersma. et al.. (2022). Ground-Level NO2 Surveillance from space across China for high resolution using interpretable spatiotemporally weighted artificial intelligence. Environmental Science & Technology, 56(14): 9988–9998 https://doi.org/10.1021/acs.est.2c03834
154	B Weir, D Crisp, C W O’Dell, S Basu, A Chatterjee, J Kolassa, T Oda, S Pawson, B Poulter, Z Zhang. et al.. (2021). Regional impacts of COVID-19 on carbon dioxide detected worldwide from space. Science Advances, 7(45): eabf9415 https://doi.org/10.1126/sciadv.abf9415
155	D M Winker, M A Vaughan, A Omar, Y Hu, K A Powell, Z Liu, W H Hunt, S A Young. (2009). Overview of the CALIPSO mission and CALIOP data processing algorithms. Journal of Atmospheric and Oceanic Technology, 26(11): 2310–2323 https://doi.org/10.1175/2009JTECHA1281.1
156	S N Wren, C A Mclinden, D Griffin, S M Li, S G Cober, A Darlington, K Hayden, C Mihele, R L Mittermeier, M J Wheeler. et al.. (2023). Aircraft and satellite observations reveal historical gap between top–down and bottom–up CO2 emissions from Canadian oil sands. PNAS Nexus, 2(5): pgad140 https://doi.org/10.1093/pnasnexus/pgad140
157	D Wu, J C Lin, B Fasoli, T Oda, X Ye, T Lauvaux, E G Yang, E A Kort. (2018). A Lagrangian approach towards extracting signals of urban CO2 emissions from satellite observations of atmospheric column CO2 (XCO2): X-Stochastic Time-Inverted Lagrangian Transport model (“X-STILT v1”). Geoscientific Model Development, 11(12): 4843–4871 https://doi.org/10.5194/gmd-11-4843-2018
158	D Wu, J C Lin, T Oda, E A Kort. (2020). Space-based quantification of per capita CO2 emissions from cities. Environmental Research Letters, 15(3): 035004 https://doi.org/10.1088/1748-9326/ab68eb
159	R Xu, D Tong, S J Davis, X Qin, J Cheng, Q Shi, Y Liu, C Chen, L Yan, X Yan. et al.. (2023). Plant-by-plant decarbonization strategies for the global steel industry. Nature Climate Change, 13(10): 1067–1074 https://doi.org/10.1038/s41558-023-01808-z
160	T Xu, C Zhang, J Xue, Q Hu, C Xing, C Liu. (2024). Estimating hourly nitrogen oxide emissions over East Asia from geostationary satellite measurements. Environmental Science & Technology Letters, 11(2): 122–129 https://doi.org/10.1021/acs.estlett.3c00467
161	D Yang, H Boesch, Y Liu, P Somkuti, Z Cai, X Chen, Noia A Di, C Lin, N Lu, D Lyu. et al.. (2020). Toward high precision XCO2 retrievals from tansat observations: retrieval improvement and validation against TCCON measurements. Journal of Geophysical Research: Atmospheres, 125(22): e2020JD032794 https://doi.org/10.1029/2020JD032794
162	D Yang, Y Liu, Z Cai, X Chen, L Yao, D Lu. (2018). First global carbon dioxide maps produced from TanSat measurements. Advances in Atmospheric Sciences, 35(6): 621–623 https://doi.org/10.1007/s00376-018-7312-6
163	E G Yang, E A Kort, L E Ott, T Oda, J C Lin. (2023). Using space-based CO2 and NO2 observations to estimate urban CO2 emissions. Journal of Geophysical Research: Atmospheres, 128(6): e2022JD037736 https://doi.org/10.1029/2022JD037736
164	J Yang, P Gong, R Fu, M Zhang, J Chen, S Liang, B Xu, J Shi, R Dickinson. (2013). The role of satellite remote sensing in climate change studies. Nature Climate Change, 3(10): 875–883 https://doi.org/10.1038/nclimate1908
165	X Ye, T Lauvaux, E A Kort, T Oda, S Feng, J C Lin, E G Yang, D Wu. (2020). Constraining fossil fuel CO2 emissions from urban area using OCO-2 observations of total column CO2. Journal of Geophysical Research: Atmospheres, 125(8): e2019JD030528 https://doi.org/10.1029/2019JD030528
166	X Yuan, Y Wang, P Ji, P Wu, J Sheffield, J A Otkin. (2023). A global transition to flash droughts under climate change. Science, 380(6641): 187–191 https://doi.org/10.1126/science.abn6301
167	C Zhang, C Liu, K L Chan, Q Hu, H Liu, B Li, C Xing, W Tan, H Zhou, F Si. et al.. (2020). First observation of tropospheric nitrogen dioxide from the environmental trace gases monitoring instrument onboard the GaoFen-5 satellite. Light, Science & Applications, 9(1): 66 https://doi.org/10.1038/s41377-020-0306-z
168	Q Zhang, K F Boersma, B Zhao, H Eskes, C Chen, H Zheng, X Zhang. (2023). Quantifying daily NOx and CO2 emissions from Wuhan using satellite observations from TROPOMI and OCO-2. Atmospheric Chemistry and Physics, 23(1): 551–563 https://doi.org/10.5194/acp-23-551-2023
169	C Zhao, Y Wang. (2009). Assimilated inversion of NOx emissions over east Asia using OMI NO2 column measurements. Geophysical Research Letters, 36(6): 2008GL037123 https://doi.org/10.1029/2008GL037123
170	H Zhao, W He, J Cheng, Y Liu, Y Zheng, H Tian, K He, Y Lei, Q Zhang. (2024). Heterogeneities in regional air pollutant emission mitigation across China during 2012–2020. Earth’s Future, 12(3): e2023EF004139 https://doi.org/10.1029/2023EF004139
171	B Zheng, F Chevallier, P Ciais, G Broquet, Y Wang, J Lian, Y Zhao. (2020a). Observing carbon dioxide emissions over China’s cities and industrial areas with the Orbiting Carbon Observatory-2. Atmospheric Chemistry and Physics, 20(14): 8501–8510 https://doi.org/10.5194/acp-20-8501-2020
172	B Zheng, P Ciais, F Chevallier, H Yang, J G Canadell, Y Chen, der Velde I R van, I Aben, E Chuvieco, S J Davis. et al.. (2023). Record-high CO2 emissions from boreal fires in 2021. Science, 379(6635): 912–917 https://doi.org/10.1126/science.ade0805
173	B Zheng, G Geng, P Ciais, S J Davis, R V Martin, J Meng, N Wu, F Chevallier, G Broquet, F Boersma. et al.. (2020b). Satellite-based estimates of decline and rebound in China’s CO2 emissions during COVID-19 pandemic. Science Advances, 6(49): eabd4998 https://doi.org/10.1126/sciadv.abd4998
174	B Zheng, D Tong, M Li, F Liu, C Hong, G Geng, H Li, X Li, L Peng, J Qi. et al.. (2018). Trends in China’s anthropogenic emissions since 2010 as the consequence of clean air actions. Atmospheric Chemistry and Physics, 18(19): 14095–14111 https://doi.org/10.5194/acp-18-14095-2018
175	B Zheng, Q Zhang, D Tong, C Chen, C Hong, M Li, G Geng, Y Lei, H Huo, K He. (2017). Resolution dependence of uncertainties in gridded emission inventories: a case study in Hebei, China. Atmospheric Chemistry and Physics, 17(2): 921–933 https://doi.org/10.5194/acp-17-921-2017
176	T Zheng, R Nassar, M Baxter. (2019). Estimating power plant CO2 emission using OCO-2 XCO2 and high resolution WRF-Chem simulations. Environmental Research Letters, 14(8): 085001 https://doi.org/10.1088/1748-9326/ab25ae
177	X Zhu, Y Gao (2017). Comparison of intelligent algorithms to design satellite constellations for enhanced coverage capability. In: Proceedings of the 10th International Symposium on Computational Intelligence and Design (ISCID), Hangzhou, China
178	P Zoogman, X Liu, R M Suleiman, W F Pennington, D E Flittner, J A Al-Saadi, B B Hilton, D K Nicks, M J Newchurch, J L Carr. et al.. (2017). Tropospheric emissions: monitoring of pollution (TEMPO). Journal of Quantitative Spectroscopy & Radiative Transfer, 186: 17–39 https://doi.org/10.1016/j.jqsrt.2016.05.008
179	W zu Castell, R Ruhnke, L M Bouwer, H Brix, P Dietrich, D Dransch, S Frickenhaus, J Greinert, A Petzold (2022). Integrating Data Science and Earth Science: Challenges and Solutions. Berlin: Springer International Publishing

[1]

FSE-24088-OF-LH_suppl_1

Download

Viewed

Full text

Abstract

Cited

Shared

Discussed