367 citations as recorded by crossref.

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3. An Interpolation Method to Reduce the Computational Time in the Stochastic Lagrangian Particle Dispersion Modeling of Spatially Dense XCO2 Retrievals D. Roten et al. 10.1029/2020EA001343
4. EDGAR v4.3.2 Global Atlas of the three major greenhouse gas emissions for the period 1970–2012 G. Janssens-Maenhout et al. 10.5194/essd-11-959-2019
5. Experimental Estimates of Integral Anthropogenic CO2 Emissions in the City of St. Petersburg Y. Timofeyev et al. 10.1134/S0001433822030100
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9. Comparison of the data‐driven top‐down and bottom‐up global terrestrial CO2 exchanges: GOSAT CO2 inversion and empirical eddy flux upscaling M. Kondo et al. 10.1002/2014JG002866
10. A synthesis of carbon dioxide emissions from fossil-fuel combustion R. Andres et al. 10.5194/bg-9-1845-2012
11. Simulation of contribution of continental anthropogenic sources to variations in the CO2 concentration during winter period on Hateruma Island A. Ganshin et al. 10.1134/S1024856013010089
12. Evaluating the Ability of the Pre-Launch TanSat-2 Satellite to Quantify Urban CO2 Emissions K. Wu et al. 10.3390/rs15204904
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15. Spatiotemporal Variations of City-Level Carbon Emissions in China during 2000–2017 Using Nighttime Light Data Y. Sun et al. 10.3390/rs12182916
16. Sensitivity of the simulated CO2 concentration to inter-annual variations of its sources and sinks over East Asia Y. Fu et al. 10.1016/j.accre.2020.03.001
17. The OCO-3 mission: measurement objectives and expected performance based on 1 year of simulated data A. Eldering et al. 10.5194/amt-12-2341-2019
18. A Thermodynamic Geography: Night-Time Satellite Imagery as a Proxy Measure of Emergy L. Coscieme et al. 10.1007/s13280-013-0468-5
19. Neighborhood Emission Mapping Operation (NEMO): A 1-km anthropogenic emission dataset in the United States S. Ma & D. Tong 10.1038/s41597-022-01790-9
20. Study of the footprints of short-term variation in XCO<sub>2</sub> observed by TCCON sites using NIES and FLEXPART atmospheric transport models D. Belikov et al. 10.5194/acp-17-143-2017
21. EU Net-Zero Policy Achievement Assessment in Selected Members through Automated Forecasting Algorithms C. Tudor & R. Sova 10.3390/ijgi11040232
22. Anthropogenic Heat Release: Estimation of Global Distribution and Possible Climate Effect B. CHEN et al. 10.2151/jmsj.2014-A10
23. Constraining Urban CO2 Emissions Using Mobile Observations from a Light Rail Public Transit Platform D. Mallia et al. 10.1021/acs.est.0c04388
24. Assessment of the NOх integral emission from the St.Petersburg megacity by means of mobile DOAS measurements combined with dispersion modelling D. Ionov et al. 10.1016/j.apr.2022.101598
25. Research on the emission reduction effects of carbon trading mechanism on power industry: plant-level evidence from China Y. Han et al. 10.1108/IJCCSM-06-2022-0074
26. Monitoring spatiotemporal characteristics of land-use carbon emissions and their driving mechanisms in the Yellow River Delta: A grid-scale analysis Y. Yang & H. Li 10.1016/j.envres.2022.114151
27. How to accurately assess the spatial distribution of energy CO2 emissions? Based on POI and NPP-VIIRS comparison X. Zhang et al. 10.1016/j.jclepro.2023.136656
28. A simple method based on the thermal anomaly index to detect industrial heat sources H. Xia et al. 10.1016/j.jag.2018.08.003
29. Mapping high-resolution energy consumption CO2 emissions in China by integrating nighttime lights and point source locations M. Wang et al. 10.1016/j.scitotenv.2023.165829
30. Spatiotemporal evolution and multi-scale coupling effects of land-use carbon emissions and ecological environmental quality X. Zhang et al. 10.1016/j.scitotenv.2024.171149
31. 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 A. Schuh et al. 10.1016/j.rse.2021.112473
32. Exploring dynamics relationship between carbon emissions and eco-environmental quality in Samarinda Metropolitan Area: A spatiotemporal approach A. Hasanah & J. Wu 10.1016/j.scitotenv.2024.172188
33. Origin, realization path and key scientific issues of carbon neutrality: Climate change and sustainable urbanization M. CHEN et al. 10.31497/zrzyxb.20220509
34. Predicting European cities’ climate mitigation performance using machine learning A. Hsu et al. 10.1038/s41467-022-35108-5
35. North American CO<sub>2</sub> exchange: inter-comparison of modeled estimates with results from a fine-scale atmospheric inversion S. Gourdji et al. 10.5194/bg-9-457-2012
36. Brightness of Nighttime Lights as a Proxy for Freight Traffic: A Case Study of China J. Tian et al. 10.1109/JSTARS.2013.2258892
37. Optimization of a prognostic biosphere model for terrestrial biomass and atmospheric CO<sub>2</sub> variability M. Saito et al. 10.5194/gmd-7-1829-2014
38. Effects of urban forms on CO2 emissions in China from a multi-perspective analysis K. Shi et al. 10.1016/j.jenvman.2020.110300
39. A global carbon assimilation system using a modified ensemble Kalman filter S. Zhang et al. 10.5194/gmd-8-805-2015
40. High-resolution spatial distribution of greenhouse gas emissions in the residential sector O. Danylo et al. 10.1007/s11027-019-9846-z
41. A Coupled CH4, CO and CO2 Simulation for Improved Chemical Source Modeling B. Bukosa et al. 10.3390/atmos14050764
42. Evidence of Carbon Uptake Associated with Vegetation Greening Trends in Eastern China Z. He et al. 10.3390/rs12040718
43. Impact of COVID-19 on the Spatio-temporal Distribution of CO2 Emission Y. Han et al. 10.1051/e3sconf/202339302006
44. Near-real-time global gridded daily CO2 emissions X. Dou et al. 10.1016/j.xinn.2021.100182
45. Recent research quantifying anthropogenic CO2emissions at the street scale within the urban domain K. Gurney 10.1080/17583004.2014.986849
46. Spatial distributions of <i>X</i><sub>CO<sub>2</sub></sub> seasonal cycle amplitude and phase over northern high-latitude regions N. Jacobs et al. 10.5194/acp-21-16661-2021
47. A comparison of estimates of global carbon dioxide emissions from fossil carbon sources R. Andrew 10.5194/essd-12-1437-2020
48. Quantification of Fossil Fuel CO2 Emissions on the Building/Street Scale for a Large U.S. City K. Gurney et al. 10.1021/es3011282
49. Spatio-temporal pattern evolution of carbon emissions at the city-county-town scale in Fujian Province based on DMSP/OLS and NPP/VIIRS nighttime light data Y. Zheng et al. 10.1016/j.jclepro.2024.140958
50. 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. 10.5194/acp-22-15817-2022
51. VIIRS night-time lights C. Elvidge et al. 10.1080/01431161.2017.1342050
52. Direct space‐based observations of anthropogenic CO2 emission areas from OCO‐2 J. Hakkarainen et al. 10.1002/2016GL070885
53. A decadal inversion of CO₂ using the Global Eulerian–Lagrangian Coupled Atmospheric model (GELCA): sensitivity to the ground-based observation network T. Shirai et al. 10.1080/16000889.2017.1291158
54. A new space-borne perspective of crop productivity variations over the US Corn Belt P. Somkuti et al. 10.1016/j.agrformet.2019.107826
55. Assumptions about prior fossil fuel inventories impact our ability to estimate posterior net CO2 fluxes that are needed for verifying national inventories T. Oda et al. 10.1088/1748-9326/ad059b
56. Consistent regional fluxes of CH<sub>4</sub> and CO<sub>2</sub> inferred from GOSAT proxy XCH<sub>4</sub> : XCO<sub>2</sub> retrievals, 2010–2014 L. Feng et al. 10.5194/acp-17-4781-2017
57. Short-term reduction of regional enhancement of atmospheric CO2 in China during the first COVID-19 pandemic period S. Sim et al. 10.1088/1748-9326/ac507d
58. Can Mixed Land Use Reduce CO2 Emissions? A Case Study of 268 Chinese Cities Q. Li et al. 10.3390/su142215117
59. Global carbon emission spatial pattern in 2030 under INDCs: using a gridding approach based on population and urbanization L. Tao et al. 10.1108/IJCCSM-04-2021-0038
60. Examining partial-column density retrieval of lower-tropospheric CO2 from GOSAT target observations over global megacities A. Kuze et al. 10.1016/j.rse.2022.112966
61. Impact of spatial proxies on the representation of bottom-up emission inventories: A satellite-based analysis G. Geng et al. 10.5194/acp-17-4131-2017
62. Removing traffic emissions from CO2 time series measured at a tall tower using mobile measurements and transport modeling A. Schmidt et al. 10.1016/j.atmosenv.2014.08.006
63. Forecasting China’s GDP at the pixel level using nighttime lights time series and population images N. Zhao et al. 10.1080/15481603.2016.1276705
64. A geographically weighted random forest approach for evaluate forest change drivers in the Northern Ecuadorian Amazon F. Santos et al. 10.1371/journal.pone.0226224
65. Assessing the Effectiveness of an Urban CO2 Monitoring Network over the Paris Region through the COVID-19 Lockdown Natural Experiment J. Lian et al. 10.1021/acs.est.1c04973
66. Inverse Modeling of CO₂ Fluxes Using GOSAT Data and Multi-Year Ground-Based Observations T. Saeki et al. 10.2151/sola.2013-011
67. Explore the spatial pattern of carbon emissions in urban functional zones: a case study of Pudong, Shanghai, China E. Zhu et al. 10.1007/s11356-023-31149-5
68. Toward Accurate, Policy-Relevant Fossil Fuel CO2 Emission Landscapes K. Gurney et al. 10.1021/acs.est.0c01175
69. A Novel Approach for Predicting Anthropogenic CO2 Emissions Using Machine Learning Based on Clustering of the CO2 Concentration Z. Ji et al. 10.3390/atmos15030323
70. Top‐Down Constraints on Anthropogenic CO2 Emissions Within an Agricultural‐Urban Landscape C. Hu et al. 10.1029/2017JD027881
71. Theoretical assessment of the ability of the MicroCarb satellite city-scan observing mode to estimate urban CO2 emissions K. Wu et al. 10.5194/amt-16-581-2023
72. Towards space based verification of CO<sub>2</sub> emissions from strong localized sources: fossil fuel power plant emissions as seen by a CarbonSat constellation V. Velazco et al. 10.5194/amt-4-2809-2011
73. Evaluating national and subnational CO2 mitigation goals in China’s thirteenth five-year plan from satellite observations G. Pan et al. 10.1016/j.envint.2021.106771
74. Spatialization of Chinese R-410A emissions from the room air-conditioning sector P. Wu et al. 10.1007/s10668-022-02264-z
75. 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. 10.1007/s00477-024-02705-3
76. Spatiotemporal Variations and Uncertainty in Crop Residue Burning Emissions over North China Plain: Implication for Atmospheric CO2 Simulation Y. Fu et al. 10.3390/rs13193880
77. Spatial variation in household consumption-based carbon emission inventories for 1200 Japanese cities K. Kanemoto et al. 10.1088/1748-9326/abc045
78. Carbon saving potential of urban parks due to heat mitigation in Yangtze River Economic Belt M. Chen et al. 10.1016/j.jclepro.2022.135713
79. Diurnal, weekly, seasonal, and spatial variabilities in carbon dioxide flux in different urban landscapes in Sakai, Japan M. Ueyama & T. Ando 10.5194/acp-16-14727-2016
80. How does urbanization affect CO2 emissions of central heating systems in China? An assessment of natural gas transition policy based on nighttime light data W. Zhang et al. 10.1016/j.jclepro.2020.123188
81. Particulate matter-attributable mortality and relationships with carbon dioxide in 250 urban areas worldwide S. Anenberg et al. 10.1038/s41598-019-48057-9
82. Analysis of CO<sub>2</sub>, CH<sub>4</sub>, and CO surface and column concentrations observed at Réunion Island by assessing WRF-Chem simulations S. Callewaert et al. 10.5194/acp-22-7763-2022
83. Optimizing the Spatial Resolution for Urban CO2 Flux Studies Using the Shannon Entropy J. Liang et al. 10.3390/atmos8050090
84. Constraining emission estimates of carbon monoxide using a perturbed emissions ensemble with observations: a focus on Beijing L. Yuan et al. 10.1007/s11869-021-01041-7
85. CO2 annual and semiannual cycles from multiple satellite retrievals and models X. Jiang et al. 10.1002/2014EA000045
86. Analyzing the impact of three-dimensional building structure on CO2 emissions based on random forest regression J. Lin et al. 10.1016/j.energy.2021.121502
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88. Urban-focused satellite CO2 observations from the Orbiting Carbon Observatory-3: A first look at the Los Angeles megacity M. Kiel et al. 10.1016/j.rse.2021.112314
89. Shedding Light on Agricultural Transitions, Dragon Fruit Cultivation, and Electrification in Southern Vietnam Using Mixed Methods L. Krauser et al. 10.1080/24694452.2021.1940825
90. On the Ability of Space‐Based Passive and Active Remote Sensing Observations of CO2 to Detect Flux Perturbations to the Carbon Cycle S. Crowell et al. 10.1002/2017JD027836
91. Global enhanced vegetation photosynthesis in urban environment and its drivers revealed by satellite solar-induced chlorophyll fluorescence data S. Wang et al. 10.1016/j.agrformet.2023.109622
92. Simultaneous shipborne measurements of CO<sub>2</sub>, CH<sub>4</sub> and CO and their application to improving greenhouse-gas flux estimates in Australia B. Bukosa et al. 10.5194/acp-19-7055-2019
93. Enhanced regional terrestrial carbon uptake over Korea revealed by atmospheric CO2 measurements from 1999 to 2017 J. Yun et al. 10.1111/gcb.15061
94. Errors and uncertainties in a gridded carbon dioxide emissions inventory T. Oda et al. 10.1007/s11027-019-09877-2
95. Large Chinese land carbon sink estimated from atmospheric carbon dioxide data J. Wang et al. 10.1038/s41586-020-2849-9
96. Development of a high-resolution spatial inventory of greenhouse gas emissions for Poland from stationary and mobile sources R. Bun et al. 10.1007/s11027-018-9791-2
97. Investigating sources of variability and error in simulations of carbon dioxide in an urban region C. Martin et al. 10.1016/j.atmosenv.2018.11.013
98. Paths to low-carbon development in China: The role of government environmental target constraints T. Bai et al. 10.24136/oc.2023.034
99. Are ICT and CO2 emissions always a win-win situation? Evidence from universal telecommunication service in China X. Zhang et al. 10.1016/j.jclepro.2023.139262
100. Tweets or nighttime lights: Comparison for preeminence in estimating socioeconomic factors N. Zhao et al. 10.1016/j.isprsjprs.2018.08.018
101. Constraint of satellite CO2 retrieval on the global carbon cycle from a Chinese atmospheric inversion system Z. Jin et al. 10.1007/s11430-022-1036-7
102. Comparison of Global Downscaled Versus Bottom‐Up Fossil Fuel CO2 Emissions at the Urban Scale in Four U.S. Urban Areas K. Gurney et al. 10.1029/2018JD028859
103. Assessing China's Scope 2 CO2 emissions and mitigation pace from space G. Pan & Y. Xu 10.1016/j.atmosenv.2023.119906
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107. Geostationary Emission Explorer for Europe (G3E): mission concept and initial performance assessment A. Butz et al. 10.5194/amt-8-4719-2015
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115. Identifying industrial heat sources using time-series of the VIIRS Nightfire product with an object-oriented approach Y. Liu et al. 10.1016/j.rse.2017.10.019
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118. Impacts of different biomass burning emission inventories: Simulations of atmospheric CO2 concentrations based on GEOS-Chem M. Su et al. 10.1016/j.scitotenv.2023.162825
119. Future Scenarios of Urban Nighttime Lights: A Method for Global Cities and Its Application to Urban Expansion and Carbon Emission Estimation M. Kii et al. 10.3390/rs16061018
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135. Net CO<sub>2</sub> fossil fuel emissions of Tokyo estimated directly from measurements of the Tsukuba TCCON site and radiosondes A. Babenhauserheide et al. 10.5194/amt-13-2697-2020
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155. Consistent weekly cycles of atmospheric NO2, CO, and CO2 in a North American megacity from ground-based, mountaintop, and satellite measurements H. Wang et al. 10.1016/j.atmosenv.2021.118809
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