494 citations as recorded by crossref.

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44. Optimizing 4 years of CO2 biospheric fluxes from OCO-2 and in situ data in TM5: fire emissions from GFED and inferred from MOPITT CO data H. Peiro et al. https://doi.org/10.5194/acp-22-15817-2022
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49. Consistent regional fluxes of CH4 and CO2 inferred from GOSAT proxy XCH4 : XCO2 retrievals, 2010–2014 L. Feng et al. https://doi.org/10.5194/acp-17-4781-2017
50. Regional divergence in the urban form-carbon emission nexus: a comparative analysis of linear and non-linear spatial modeling approaches for 286 Chinese cities S. He et al. https://doi.org/10.3389/fenvs.2025.1658538
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53. Inverse Modeling of CO₂ Fluxes Using GOSAT Data and Multi-Year Ground-Based Observations T. Saeki et al. https://doi.org/10.2151/sola.2013-011
54. Top-down estimate of regional carbon sinks over East Asia for 2010–2019 using satellite observations M. Kim et al. https://doi.org/10.5194/acp-26-6869-2026
55. Toward Accurate, Policy-Relevant Fossil Fuel CO2 Emission Landscapes K. Gurney et al. https://doi.org/10.1021/acs.est.0c01175
56. A Novel Approach for Predicting Anthropogenic CO2 Emissions Using Machine Learning Based on Clustering of the CO2 Concentration Z. Ji et al. https://doi.org/10.3390/atmos15030323
57. Theoretical assessment of the ability of the MicroCarb satellite city-scan observing mode to estimate urban CO2 emissions K. Wu et al. https://doi.org/10.5194/amt-16-581-2023
58. Integrating remote sensing with OpenStreetMap data for comprehensive scene understanding through multi-modal self-supervised learning L. Bai et al. https://doi.org/10.1016/j.rse.2024.114573
59. The Impact of Foreign Direct Investment on Green Technology Innovation: Evidence from the Threshold Effect of Absorptive Capacity L. Ge et al. https://doi.org/10.1080/10630732.2024.2385116
60. Measuring the synergy of air pollution and CO2 emission in Chinese urban agglomerations: an evaluation from the aggregate impact and correlation perspectives Y. Guan et al. https://doi.org/10.1007/s00477-024-02705-3
61. Spatiotemporal Variations and Uncertainty in Crop Residue Burning Emissions over North China Plain: Implication for Atmospheric CO2 Simulation Y. Fu et al. https://doi.org/10.3390/rs13193880
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68. Comparative analysis of anthropogenic CO2 emissions in Thailand using the ODIAC and CAMS datasets S. Sooktawee et al. https://doi.org/10.1016/j.indic.2026.101258
69. Simultaneous shipborne measurements of CO2, CH4 and CO and their application to improving greenhouse-gas flux estimates in Australia B. Bukosa et al. https://doi.org/10.5194/acp-19-7055-2019
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71. Paths to low-carbon development in China: The role of government environmental target constraints T. Bai et al. https://doi.org/10.24136/oc.2023.034
72. Are ICT and CO2 emissions always a win-win situation? Evidence from universal telecommunication service in China X. Zhang et al. https://doi.org/10.1016/j.jclepro.2023.139262
73. Spatial-Temporal Patterns and Driving Factors of Logistics Carbon Emissions: Case Study of Yangtze River Delta in China E. Zhu et al. https://doi.org/10.1177/03611981241242068
74. Direct CO2 emissions and uptake at neighbourhood-scale across the urban area of Beijing Y. Zheng et al. https://doi.org/10.1016/j.cacint.2025.100252
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78. Geostationary Emission Explorer for Europe (G3E): mission concept and initial performance assessment A. Butz et al. https://doi.org/10.5194/amt-8-4719-2015
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134. CDIAC-FF: global and national CO2 emissions from fossil fuel combustion and cement manufacture: 1751–2017 D. Gilfillan & G. Marland https://doi.org/10.5194/essd-13-1667-2021
135. Evaluating China's fossil-fuel CO2 emissions from a comprehensive dataset of nine inventories P. Han et al. https://doi.org/10.5194/acp-20-11371-2020
136. Satellite-Based Estimation of Urban CO2 Emissions in Shandong Province, China, Using TROPOMI NO2 Observations and Differential Evolution Algorithm Y. Xie et al. https://doi.org/10.3390/rs18101470
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