{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T16:02:05Z","timestamp":1772208125787,"version":"3.50.1"},"reference-count":83,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2023,10,10]],"date-time":"2023-10-10T00:00:00Z","timestamp":1696896000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research and Development Plan","award":["2021YFB3901000"],"award-info":[{"award-number":["2021YFB3901000"]}]},{"name":"National Key Research and Development Plan","award":["YSBR-037"],"award-info":[{"award-number":["YSBR-037"]}]},{"name":"CAS Project for Young Scientists in Basic Research","award":["2021YFB3901000"],"award-info":[{"award-number":["2021YFB3901000"]}]},{"name":"CAS Project for Young Scientists in Basic Research","award":["YSBR-037"],"award-info":[{"award-number":["YSBR-037"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>TanSat-2, the next-generation Chinese greenhouse gas monitoring satellite for measuring carbon dioxide (CO2), has a new city-scale observing mode. We assess the theoretical capability of TanSat-2 to quantify integrated urban CO2 emissions over the cities of Beijing, Jinan, Los Angeles, and Paris. A high-resolution emission inventory and a column-averaged CO2 (XCO2) transport model are used to build an urban CO2 inversion system. We design a series of numerical experiments describing this observing system to evaluate the impacts of sampling patterns and XCO2 measurement errors on inferring urban CO2 emissions. We find that the correction in systematic and random flux errors is correlated with the signal-to-noise ratio of satellite measurements. The reduction in systematic flux errors for the four cities are sizable, but are subject to unbiased satellite sampling and favorable meteorological conditions (i.e., less cloud cover and lower wind speed). The corresponding correction to the random flux error is 19\u201328%. Even though clear-sky satellite data from TanSat-2 have the potential to reduce flux errors for cities with high CO2 emissions, quantifying urban emissions by satellite-based measurements is subject to additional limitations and uncertainties.<\/jats:p>","DOI":"10.3390\/rs15204904","type":"journal-article","created":{"date-parts":[[2023,10,10]],"date-time":"2023-10-10T10:23:42Z","timestamp":1696933422000},"page":"4904","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Evaluating the Ability of the Pre-Launch TanSat-2 Satellite to Quantify Urban CO2 Emissions"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2054-4278","authenticated-orcid":false,"given":"Kai","family":"Wu","sequence":"first","affiliation":[{"name":"Carbon Neutrality Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China"}]},{"given":"Dongxu","family":"Yang","sequence":"additional","affiliation":[{"name":"Carbon Neutrality Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China"},{"name":"Key Laboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China"}]},{"given":"Yi","family":"Liu","sequence":"additional","affiliation":[{"name":"Carbon Neutrality Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China"},{"name":"Key Laboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Zhaonan","family":"Cai","sequence":"additional","affiliation":[{"name":"Carbon Neutrality Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China"},{"name":"Key Laboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3427-5873","authenticated-orcid":false,"given":"Minqiang","family":"Zhou","sequence":"additional","affiliation":[{"name":"Carbon Neutrality Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China"},{"name":"Key Laboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China"}]},{"given":"Liang","family":"Feng","sequence":"additional","affiliation":[{"name":"School of GeoSciences, University of Edinburgh, Edinburgh EH9 3FF, UK"},{"name":"National Centre for Earth Observation, University of Edinburgh, Edinburgh EH9 3FF, UK"}]},{"given":"Paul I.","family":"Palmer","sequence":"additional","affiliation":[{"name":"School of GeoSciences, University of Edinburgh, Edinburgh EH9 3FF, UK"},{"name":"National Centre for Earth Observation, University of Edinburgh, Edinburgh EH9 3FF, UK"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,10]]},"reference":[{"key":"ref_1","unstructured":"Butler, J.H., and Montzka, S.A. (2016). The NOAA annual greenhouse gas index (AGGI). NOAA Earth Syst. Res. Lab., 58, Available online: http:\/\/www.esrl.noaa.gov\/gmd\/aggi\/aggi.html."},{"key":"ref_2","unstructured":"Masson-Delmotte, V., Zhai, P., P\u00f6rtner, H.O., Roberts, D., Skea, J., Shukla, P.R., Pirani, A., Moufouma-Okia, W., P\u00e9an, C., and Pidcock, R. (2022). Global Warming of 1.5 \u00b0C: IPCC Special Report on Impacts of Global Warming of 1.5 \u00b0C above Pre-Industrial Levels in Context of Strengthening Response to Climate Change, Sustainable Development, and Efforts to Eradicate Poverty, Cambridge University Press."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1016\/j.envsci.2019.03.011","article-title":"What can we learn about effectiveness of carbon reduction policies from interannual variability of fossil fuel CO2 emissions in East Asia?","volume":"96","author":"Labzovskii","year":"2019","journal-title":"Environ. Sci. Policy"},{"key":"ref_4","unstructured":"Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S.L., P\u00e9an, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., and Gomis, M.I. (2021). Climate Change 2021: The Physical Science Basis, Cambridge University Press. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"118093","DOI":"10.1016\/j.envpol.2021.118093","article-title":"Fossil fuels consumption and carbon dioxide emissions in G7 countries: Empirical evidence from ARDL bounds testing approach","volume":"291","author":"Martins","year":"2021","journal-title":"Environ. Pollut."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1038\/s41558-021-01001-0","article-title":"Fossil CO2 emissions in the post-COVID-19 era","volume":"11","author":"Peters","year":"2021","journal-title":"Nat. Clim. Change"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"59","DOI":"10.5194\/amt-10-59-2017","article-title":"The on-orbit performance of the Orbiting Carbon Observatory-2 (OCO-2) instrument and its radiometrically calibrated products","volume":"10","author":"Crisp","year":"2017","journal-title":"Atmos. Meas. Tech."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"7343","DOI":"10.5194\/acp-13-7343-2013","article-title":"CO, NOx and 13CO2 as tracers for fossil fuel CO2: Results from a pilot study in Paris during winter 2010","volume":"13","author":"Lopez","year":"2013","journal-title":"Atmos. Chem. Phys."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1707","DOI":"10.5194\/acp-15-1707-2015","article-title":"An attempt at estimating Paris area CO2 emissions from atmospheric concentration measurements","volume":"15","author":"Broquet","year":"2015","journal-title":"Atmos. Chem. Phys."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"13465","DOI":"10.5194\/acp-16-13465-2016","article-title":"Network design for quantifying urban CO2 emissions: Assessing trade-offs between precision and network density","volume":"16","author":"Turner","year":"2016","journal-title":"Atmos. Chem. Phys."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"10543","DOI":"10.5194\/acp-16-10543-2016","article-title":"Spatial and temporal variability of urban fluxes of methane, carbon monoxide and carbon dioxide above London, UK","volume":"16","author":"Helfter","year":"2016","journal-title":"Atmos. Chem. Phys."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"5213","DOI":"10.1002\/2015JD024473","article-title":"High-resolution atmospheric inversion of urban CO2 emissions during the dormant season of the Indianapolis Flux Experiment (INFLUX)","volume":"121","author":"Lauvaux","year":"2016","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1525\/elementa.188","article-title":"The Indianapolis Flux Experiment (INFLUX): A test-bed for developing urban greenhouse gas emission measurements","volume":"5","author":"Davis","year":"2017","journal-title":"Elem. Sci. Anth."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"8313","DOI":"10.5194\/acp-17-8313-2017","article-title":"Carbon dioxide and methane measurements from the Los Angeles Megacity Carbon Project\u2013Part 1: Calibration, urban enhancements, and uncertainty estimates","volume":"17","author":"Verhulst","year":"2017","journal-title":"Atmos. Chem. Phys."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"7491","DOI":"10.1073\/pnas.1803715115","article-title":"Anthropogenic and biogenic CO2 fluxes in the Boston urban region","volume":"115","author":"Sargent","year":"2018","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1525\/elementa.375","article-title":"Bayesian inverse estimation of urban CO2 emissions: Results from a synthetic data simulation over Salt Lake City, UT","volume":"7","author":"Kunik","year":"2019","journal-title":"Elem. Sci. Anth."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"13300","DOI":"10.1073\/pnas.1919032117","article-title":"Estimating US fossil fuel CO2 emissions from measurements of 14C in atmospheric CO2","volume":"117","author":"Basu","year":"2020","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"160","DOI":"10.2151\/sola.2009-041","article-title":"Global concentrations of CO2 and CH4 retrieved from GOSAT: First preliminary results","volume":"5","author":"Yokota","year":"2009","journal-title":"Sola"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1061","DOI":"10.5194\/amt-4-1061-2011","article-title":"Preliminary validation of column-averaged volume mixing ratios of carbon dioxide and methane retrieved from GOSAT short-wavelength infrared spectra","volume":"4","author":"Morino","year":"2011","journal-title":"Atmos. Meas. Tech."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"L17806","DOI":"10.1029\/2012GL052738","article-title":"Space-based observations of megacity carbon dioxide","volume":"39","author":"Kort","year":"2012","journal-title":"Geophys. Res. Lett."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"3486","DOI":"10.1002\/2016GL067843","article-title":"Comparing GOSAT observations of localized CO2 enhancements by large emitters with inventory-based estimates","volume":"43","author":"Janardanan","year":"2016","journal-title":"Geophys. Res. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1002\/2016GL070885","article-title":"Direct space-based observations of anthropogenic CO2 emission areas from OCO-2","volume":"43","author":"Hakkarainen","year":"2016","journal-title":"Geophys. Res. Lett."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"eaam5782","DOI":"10.1126\/science.aam5782","article-title":"Spaceborne detection of localized carbon dioxide sources","volume":"358","author":"Schwandner","year":"2017","journal-title":"Science"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"eaam5745","DOI":"10.1126\/science.aam5745","article-title":"The Orbiting Carbon Observatory-2 early science investigations of regional carbon dioxide fluxes","volume":"358","author":"Eldering","year":"2017","journal-title":"Science"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"e2021GL097540","DOI":"10.1029\/2021GL097540","article-title":"Large CO2 emitters as seen from satellite: Comparison to a gridded global emission inventory","volume":"49","author":"Chevallier","year":"2022","journal-title":"Geophys. Res. Lett."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"e2019JD030528","DOI":"10.1029\/2019JD030528","article-title":"Constraining fossil fuel CO2 emissions from urban area using OCO-2 observations of total column CO2","volume":"125","author":"Ye","year":"2020","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"8501","DOI":"10.5194\/acp-20-8501-2020","article-title":"Observing carbon dioxide emissions over China\u2019s cities and industrial areas with the Orbiting Carbon Observatory-2","volume":"20","author":"Zheng","year":"2020","journal-title":"Atmos. Chem. Phys."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"112625","DOI":"10.1016\/j.rse.2021.112625","article-title":"Fossil fuel CO2 emissions over metropolitan areas from space: A multi-model analysis of OCO-2 data over Lahore, Pakistan","volume":"264","author":"Lei","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"792","DOI":"10.1038\/ngeo2257","article-title":"Decreasing emissions of NOx relative to CO2 in East Asia inferred from satellite observations","volume":"7","author":"Reuter","year":"2014","journal-title":"Nat. Geosci."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"13509","DOI":"10.5194\/acp-16-13509-2016","article-title":"Estimation of fossil-fuel CO2 emissions using satellite measurements of \u201cproxy\u201d species","volume":"16","author":"Konovalov","year":"2016","journal-title":"Atmos. Chem. Phys."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"133805","DOI":"10.1016\/j.scitotenv.2019.133805","article-title":"Exploiting OMI NO2 satellite observations to infer fossil-fuel CO2 emissions from US megacities","volume":"695","author":"Goldberg","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"9371","DOI":"10.5194\/acp-19-9371-2019","article-title":"Towards monitoring localized CO2 emissions from space: Co-located regional CO2 and NO2 enhancements observed by the OCO-2 and S5P satellites","volume":"19","author":"Reuter","year":"2019","journal-title":"Atmos. Chem. Phys."},{"key":"ref_33","first-page":"100110","article-title":"Analyzing nitrogen oxides to carbon dioxide emission ratios from space: A case study of Matimba Power Station in South Africa","volume":"10","author":"Hakkarainen","year":"2021","journal-title":"Atmos. Environ. X"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"112246","DOI":"10.1016\/j.rse.2020.112246","article-title":"An assessment of emission characteristics of Northern Hemisphere cities using spaceborne observations of CO2, CO, and NO2","volume":"254","author":"Park","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"721","DOI":"10.5194\/amt-15-721-2022","article-title":"Automated detection of atmospheric NO2 plumes from satellite data: A tool to help infer anthropogenic combustion emissions","volume":"15","author":"Finch","year":"2022","journal-title":"Atmos. Meas. Tech."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"7064","DOI":"10.1002\/2016JD026111","article-title":"Observational evidence of 3-D cloud effects in OCO-2 CO2 retrievals","volume":"122","author":"Massie","year":"2017","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"6539","DOI":"10.5194\/amt-11-6539-2018","article-title":"Improved retrievals of carbon dioxide from Orbiting Carbon Observatory-2 with the version 8 ACOS algorithm","volume":"11","author":"Eldering","year":"2018","journal-title":"Atmos. Meas. Tech."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"2013","DOI":"10.5194\/amt-14-2013-2021","article-title":"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","volume":"14","author":"Suto","year":"2021","journal-title":"Atmos. Meas. Tech."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1919","DOI":"10.1007\/s11430-013-4707-1","article-title":"Analysis of XCO 2 retrieval sensitivity using simulated Chinese Carbon Satellite (TanSat) measurements","volume":"57","author":"Cai","year":"2014","journal-title":"Sci. China Earth Sci."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1200","DOI":"10.1016\/j.scib.2018.08.004","article-title":"The TanSat mission: Preliminary global observations","volume":"63","author":"Liu","year":"2018","journal-title":"Sci. Bull."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1007\/s00376-018-7312-6","article-title":"First global carbon dioxide maps produced from TanSat measurements","volume":"35","author":"Yang","year":"2018","journal-title":"Adv. Atmos. Sci."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"e2020JD032794","DOI":"10.1029\/2020JD032794","article-title":"Toward high precision XCO 2 retrievals from TanSat observations: Retrieval improvement and validation against TCCON measurements","volume":"125","author":"Yang","year":"2020","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"3329","DOI":"10.5194\/amt-13-3329-2020","article-title":"The use of the 1.27 \u03bcm O2 absorption band for greenhouse gas monitoring from space and application to MicroCarb","volume":"13","author":"Bertaux","year":"2020","journal-title":"Atmos. Meas. Tech."},{"key":"ref_44","unstructured":"Jouglet, D., Landiech, P., Breon, F.M., and The MicroCarb Team (2021, January 14\u201317). MicroCarb, first European program for CO2 monitoring: Nearing development conclusion before launch. Proceedings of the IWGGMS-17 Conference, Online."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"581","DOI":"10.5194\/amt-16-581-2023","article-title":"Theoretical assessment of the ability of the MicroCarb satellite city-scan observing mode to estimate urban CO2 emissions","volume":"16","author":"Wu","year":"2023","journal-title":"Atmos. Meas. Tech."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"6733","DOI":"10.5194\/amt-13-6733-2020","article-title":"Quantifying CO2 emissions of a city with the Copernicus Anthropogenic CO2 Monitoring satellite mission","volume":"13","author":"Kuhlmann","year":"2020","journal-title":"Atmos. Meas. Tech."},{"key":"ref_47","first-page":"118523M","article-title":"The Copernicus CO2M mission for monitoring anthropogenic carbon dioxide emissions from space","volume":"Volume 11852","author":"Cugny","year":"2021","journal-title":"Proceedings of the International Conference on Space Optics\u2014ICSO 2020"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"112314","DOI":"10.1016\/j.rse.2021.112314","article-title":"Urban-focused satellite CO2 observations from the Orbiting Carbon Observatory-3: A first look at the Los Angeles megacity","volume":"258","author":"Kiel","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"2341","DOI":"10.5194\/amt-12-2341-2019","article-title":"The OCO-3 mission: Measurement objectives and expected performance based on 1 year of simulated data","volume":"12","author":"Eldering","year":"2019","journal-title":"Atmos. Meas. Tech."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"112032","DOI":"10.1016\/j.rse.2020.112032","article-title":"OCO-3 early mission operations and initial (vEarly) XCO 2 and SIF retrievals","volume":"251","author":"Taylor","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"035004","DOI":"10.1088\/1748-9326\/ab68eb","article-title":"Space-based quantification of per capita CO2 emissions from cities","volume":"15","author":"Wu","year":"2020","journal-title":"Environ. Res. Lett."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"e2019JD031922","DOI":"10.1029\/2019JD031922","article-title":"Using space-based observations and Lagrangian modeling to evaluate urban carbon dioxide emissions in the Middle East","volume":"125","author":"Yang","year":"2020","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"2087","DOI":"10.1098\/rsta.2010.0240","article-title":"The total carbon column observing network","volume":"369","author":"Wunch","year":"2011","journal-title":"Philos. Trans. R. Soc. A Math. Phys. Eng. Sci."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"2209","DOI":"10.5194\/amt-10-2209-2017","article-title":"Comparisons of the orbiting carbon observatory-2 (OCO-2) X CO2 measurements with TCCON","volume":"10","author":"Wunch","year":"2017","journal-title":"Atmos. Meas. Tech."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Zhou, M., Ni, Q., Cai, Z., Langerock, B., Nan, W., Yang, Y., Che, K., Yang, D., Wang, T., and Liu, Y. (2022). CO2 in Beijing and Xianghe Observed by Ground-Based FTIR Column Measurements and Validation to OCO-2\/3 Satellite Observations. Remote Sens., 14.","DOI":"10.3390\/rs14153769"},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Cai, Z., Sun, K., Yang, D., Liu, Y., Yao, L., Lin, C., and Liu, X. (2022). On-Orbit Characterization of TanSat Instrument Line Shape Using Observed Solar Spectra. Remote Sens., 14.","DOI":"10.3390\/rs14143334"},{"key":"ref_57","unstructured":"Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Hor\u00e1nyi, A., Mu\u00f1oz Sabater, J., Nicolas, J., Peubey, C., Radu, R., and Rozum, I. (2018). ERA5 hourly data on single levels from 1979 to present. Copernic. Clim. Change Serv. Clim. Data Store, 10."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"543","DOI":"10.5194\/acp-11-543-2011","article-title":"A very high-resolution (1 km \u00d7 1 km) global fossil fuel CO2 emission inventory derived using a point source database and satellite observations of nighttime lights","volume":"11","author":"Oda","year":"2011","journal-title":"Atmos. Chem. Phys."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"87","DOI":"10.5194\/essd-10-87-2018","article-title":"The Open-source Data Inventory for Anthropogenic CO2, version 2016 (ODIAC2016): A global monthly fossil fuel CO2 gridded emissions data product for tracer transport simulations and surface flux inversions","volume":"10","author":"Oda","year":"2018","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"4843","DOI":"10.5194\/gmd-11-4843-2018","article-title":"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 (\u201cX-STILT v1\u201d)","volume":"11","author":"Wu","year":"2018","journal-title":"Geosci. Model Dev."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"2813","DOI":"10.5194\/gmd-11-2813-2018","article-title":"Simulating atmospheric tracer concentrations for spatially distributed receptors: Updates to the Stochastic Time-Inverted Lagrangian Transport model\u2019s R interface (STILT-R version 2)","volume":"11","author":"Fasoli","year":"2018","journal-title":"Geosci. Model Dev."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"4493","DOI":"10.1029\/2002JD003161","article-title":"A near-field tool for simulating the upstream influence of atmospheric observations: The Stochastic Time-Inverted Lagrangian Transport (STILT) model","volume":"108","author":"Lin","year":"2003","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_63","unstructured":"NCEP (2015). 0.25 Degree Global Forecast Grids Historical Archive (Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory, National Centers for Environmental Prediction\/National Weather Service\/NOAA\/US Department of Commerce."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1525\/elementa.133","article-title":"Toward reduced transport errors in a high resolution urban CO2 inversion system","volume":"5","author":"Deng","year":"2017","journal-title":"Elem. Sci. Anth."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"12007","DOI":"10.5194\/acp-19-12007-2019","article-title":"Diagnosing spatial error structures in CO2 mole fractions and XCO2 column mole fractions from atmospheric transport","volume":"19","author":"Lauvaux","year":"2019","journal-title":"Atmos. Chem. Phys."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"1007","DOI":"10.1007\/s11027-019-09877-2","article-title":"Errors and uncertainties in a gridded carbon dioxide emissions inventory","volume":"24","author":"Oda","year":"2019","journal-title":"Mitig. Adapt. Strateg. Glob. Change"},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Wu, K., Lauvaux, T., Davis, K.J., Deng, A., Coto, I.L., Gurney, K.R., and Patarasuk, R. (2018). Joint inverse estimation of fossil fuel and biogenic CO2 fluxes in an urban environment: An observing system simulation experiment to assess the impact of multiple uncertainties. Elem. Sci. Anth., 6.","DOI":"10.1525\/elementa.138"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1111\/j.1600-0889.2011.00529.x","article-title":"Constraining surface emissions of air pollutants using inverse modelling: Method intercomparison and a new two-step two-scale regularization approach","volume":"63","author":"Saide","year":"2011","journal-title":"Tellus B"},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Wu, L., Bocquet, M., Lauvaux, T., Chevallier, F., Rayner, P., and Davis, K. (2011). Optimal representation of source-sink fluxes for mesoscale carbon dioxide inversion with synthetic data. J. Geophys. Res. Atmos., 116.","DOI":"10.1029\/2011JD016198"},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Enting, I.G. (2002). Inverse Problems in Atmospheric Constituent Transport, Cambridge University Press.","DOI":"10.1017\/CBO9780511535741"},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Tarantola, A. (2004). Inverse Problem Theory and Methods for Model Parameter Estimation, SIAM.","DOI":"10.1137\/1.9780898717921"},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"2619","DOI":"10.5194\/acp-9-2619-2009","article-title":"Estimating surface CO2 fluxes from space-borne CO2 dry air mole fraction observations using an ensemble Kalman Filter","volume":"9","author":"Feng","year":"2009","journal-title":"Atmos. Chem. Phys."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"17513","DOI":"10.1029\/2000JD900151","article-title":"A nonlinear optimal estimation inverse method for radio occultation measurements of temperature, humidity, and surface pressure","volume":"105","author":"Palmer","year":"2000","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"7200","DOI":"10.1002\/2017JD026455","article-title":"Emissions and topographic effects on column CO2 (XCO2) variations, with a focus on the Southern California Megacity","volume":"122","author":"Hedelius","year":"2017","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"16271","DOI":"10.5194\/acp-18-16271-2018","article-title":"Southern California megacity CO2, CH4, and CO flux estimates using ground-and space-based remote sensing and a Lagrangian model","volume":"18","author":"Hedelius","year":"2018","journal-title":"Atmos. Chem. Phys."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"681","DOI":"10.5194\/amt-11-681-2018","article-title":"The potential of satellite spectro-imagery for monitoring CO2 emissions from large cities","volume":"11","author":"Broquet","year":"2018","journal-title":"Atmos. Meas. Tech."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"112473","DOI":"10.1016\/j.rse.2021.112473","article-title":"Far-field biogenic and anthropogenic emissions as a dominant source of variability in local urban carbon budgets: A global high-resolution model study with implications for satellite remote sensing","volume":"262","author":"Schuh","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"7789","DOI":"10.5194\/acp-19-7789-2019","article-title":"An atmospheric inversion over the city of Cape Town: Sensitivity analyses","volume":"19","author":"Nickless","year":"2019","journal-title":"Atmos. Chem. Phys."},{"key":"ref_79","doi-asserted-by":"crossref","unstructured":"Hakkarainen, J., Ialongo, I., Maksyutov, S., and Crisp, D. (2019). Analysis of four years of global XCO2 anomalies as seen by orbiting carbon observatory-2. Remote Sens., 11.","DOI":"10.3390\/rs11070850"},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"012045","DOI":"10.1088\/1755-1315\/386\/1\/012045","article-title":"High-resolution simulation of particle transport in the urban atmospheric boundary layer","volume":"386","author":"Varentsov","year":"2019","journal-title":"IOP Conf. Ser. Earth Environ. Sci."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"292","DOI":"10.1002\/2014JD022555","article-title":"Toward quantification and source sector identification of fossil fuel CO2 emissions from an urban area: Results from the INFLUX experiment","volume":"120","author":"Turnbull","year":"2015","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"26681","DOI":"10.1073\/pnas.2005253117","article-title":"Large and seasonally varying biospheric CO2 fluxes in the Los Angeles megacity revealed by atmospheric radiocarbon","volume":"117","author":"Miller","year":"2020","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"074035","DOI":"10.1088\/1748-9326\/ac7c29","article-title":"Source decomposition of eddy-covariance CO2 flux measurements for evaluating a high-resolution urban CO2 emissions inventory","volume":"17","author":"Wu","year":"2022","journal-title":"Environ. Res. Lett."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/20\/4904\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:04:26Z","timestamp":1760130266000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/20\/4904"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,10]]},"references-count":83,"journal-issue":{"issue":"20","published-online":{"date-parts":[[2023,10]]}},"alternative-id":["rs15204904"],"URL":"https:\/\/doi.org\/10.3390\/rs15204904","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,10,10]]}}}