328 citations as recorded by crossref.

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2. Balancing aggregation and smoothing errors in inverse models A. Turner & D. Jacob https://doi.org/10.5194/acp-15-7039-2015
3. Fire emissions and regional air quality impacts from fires in oil palm, timber, and logging concessions in Indonesia M. Marlier et al. https://doi.org/10.1088/1748-9326/10/8/085005
4. Environmental Insights: Democratizing access to ambient air pollution data and predictive analytics with an open-source Python package L. Berrisford & R. Menezes https://doi.org/10.1016/j.envsoft.2024.106131
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6. Remote‐Sensing Derived Trends in Gross Primary Production Explain Increases in the CO2 Seasonal Cycle Amplitude L. He et al. https://doi.org/10.1029/2021GB007220
7. Development of the tangent linear and adjoint models of the global online chemical transport model MPAS-CO2 v7.3 T. Zheng et al. https://doi.org/10.5194/gmd-17-1543-2024
8. A High-Performance Convolutional Neural Network for Ground-Level Ozone Estimation in Eastern China S. Wang et al. https://doi.org/10.3390/rs14071640
9. A method for independent validation of surface fluxes from atmospheric inversion: Application to CO2 J. Liu & K. Bowman https://doi.org/10.1002/2016GL067828
10. Impact of the Volkswagen emissions control defeat device on US public health S. Barrett et al. https://doi.org/10.1088/1748-9326/10/11/114005
11. Fires, Smoke Exposure, and Public Health: An Integrative Framework to Maximize Health Benefits From Peatland Restoration M. Marlier et al. https://doi.org/10.1029/2019GH000191
12. An intercomparison of inverse models for estimating sources and sinks of CO2 using GOSAT measurements S. Houweling et al. https://doi.org/10.1002/2014JD022962
13. The cascade of global trade to large climate forcing over the Tibetan Plateau glaciers K. Yi et al. https://doi.org/10.1038/s41467-019-10876-9
14. Spatiotemporally Detailed Quantification of Air Quality Benefits of Emissions Reductions–Part I: Benefit-per-Ton Estimates for Canada and the U.S. S. Zhao et al. https://doi.org/10.1021/acsestair.4c00127
15. Differences Between Magnitudes and Health Impacts of BC Emissions Across the United States Using 12 km Scale Seasonal Source Apportionment M. Turner et al. https://doi.org/10.1021/es505968b
16. Optimal Ozone Reduction Policy Design Using Adjoint-Based NOx Marginal Damage Information S. Mesbah et al. https://doi.org/10.1021/es402531n
17. PM2.5 source attribution for Seoul in May from 2009 to 2013 using GEOS-Chem and its adjoint model H. Lee et al. https://doi.org/10.1016/j.envpol.2016.11.088
18. Development of four-dimensional variational assimilation system based on the GRAPES–CUACE adjoint model (GRAPES–CUACE-4D-Var V1.0) and its application in emission inversion C. Wang et al. https://doi.org/10.5194/gmd-14-337-2021
19. Determination of the source regions for surface to stratosphere transport: An Eulerian backtracking approach P. Haines & J. Esler https://doi.org/10.1002/2013GL058757
20. Integrated assessment of global climate, air pollution, and dietary, malnutrition and obesity health impacts of food production and consumption between 2014 and 2018 C. Malley et al. https://doi.org/10.1088/2515-7620/ac0af9
21. Synthesizing Scientific Progress: Outcomes from U.S. EPA’s Carbonaceous Aerosols and Source Apportionment STAR Grants K. Wagstrom et al. https://doi.org/10.1021/es500782k
22. Construction of non-diagonal background error covariance matrices for global chemical data assimilation K. Singh et al. https://doi.org/10.5194/gmd-4-299-2011
23. Constraining global aerosol emissions using POLDER/PARASOL satellite remote sensing observations C. Chen et al. https://doi.org/10.5194/acp-19-14585-2019
24. Quantification of regional net CO2 flux errors in the Orbiting Carbon Observatory-2 (OCO-2) v10 model intercomparison project (MIP) ensemble using airborne measurements J. Yun et al. https://doi.org/10.5194/acp-25-1725-2025
25. Global dry deposition of nitrogen dioxide and sulfur dioxide inferred from space‐based measurements C. Nowlan et al. https://doi.org/10.1002/2014GB004805
26. Intercomparison of Magnitudes and Trends in Anthropogenic Surface Emissions From Bottom‐Up Inventories, Top‐Down Estimates, and Emission Scenarios N. Elguindi et al. https://doi.org/10.1029/2020EF001520
27. Understanding factors influencing the detection of mercury policies in modelled Laurentian Great Lakes wet deposition A. Giang et al. https://doi.org/10.1039/C8EM00268A
28. Technical Note: Adjoint formulation of the TOMCAT atmospheric transport scheme in the Eulerian backtracking framework (RETRO-TOM) P. Haines et al. https://doi.org/10.5194/acp-14-5477-2014
29. Sources and Processes Affecting Fine Particulate Matter Pollution over North China: An Adjoint Analysis of the Beijing APEC Period L. Zhang et al. https://doi.org/10.1021/acs.est.6b03010
30. Parameterization and sensitivity analysis of a process‐based terrestrial ecosystem model using adjoint method Q. Zhu & Q. Zhuang https://doi.org/10.1002/2013MS000241
31. Duration of tangent-linear regime in sectional multi-component aerosol dynamics T. Viskari et al. https://doi.org/10.1016/j.jaerosci.2008.04.002
32. Assessing remote polarimetric measurement sensitivities to aerosol emissions using the geos-chem adjoint model B. Meland et al. https://doi.org/10.5194/amt-6-3441-2013
33. Estimates of black carbon emissions in the western United States using the GEOS-Chem adjoint model Y. Mao et al. https://doi.org/10.5194/acp-15-7685-2015
34. Terrestrial ecosystem carbon flux estimated using GOSAT and OCO-2 XCO2 retrievals H. Wang et al. https://doi.org/10.5194/acp-19-12067-2019
35. A new method for inferring city emissions and lifetimes of nitrogen oxides from high-resolution nitrogen dioxide observations: a model study F. Liu et al. https://doi.org/10.5194/acp-22-1333-2022
36. An Inversion Framework for Optimizing Non‐Methane VOC Emissions Using Remote Sensing and Airborne Observations in Northeast Asia During the KORUS‐AQ Field Campaign J. Choi et al. https://doi.org/10.1029/2021JD035844
37. Retrieval of aerosol components directly from satellite and ground-based measurements L. Li et al. https://doi.org/10.5194/acp-19-13409-2019
38. Description and evaluation of a detailed gas-phase chemistry scheme in the TM5-MP global chemistry transport model (r112) S. Myriokefalitakis et al. https://doi.org/10.5194/gmd-13-5507-2020
39. Fundamentals of data assimilation applied to biogeochemistry P. Rayner et al. https://doi.org/10.5194/acp-19-13911-2019
40. Simulating out-of-sample atmospheric transport to enable flux inversions N. Dadheech & A. Turner https://doi.org/10.5194/acp-26-427-2026
41. Contributions to local- and regional-scale formaldehyde concentrations L. Bastien et al. https://doi.org/10.5194/acp-19-8363-2019
42. On what scales can GOSAT flux inversions constrain anomalies in terrestrial ecosystems? B. Byrne et al. https://doi.org/10.5194/acp-19-13017-2019
43. Sector‐Based Top‐Down Estimates of NOx, SO2, and CO Emissions in East Asia Z. Qu et al. https://doi.org/10.1029/2021GL096009
44. Premature Deaths in Brazil Associated With Long‐Term Exposure to PM2.5 From Amazon Fires Between 2016 and 2019 M. Nawaz & D. Henze https://doi.org/10.1029/2020GH000268
45. Development of the adjoint of the unified tropospheric–stratospheric chemistry extension (UCX) in GEOS-Chem adjoint v36 I. Dedoussi et al. https://doi.org/10.5194/gmd-17-5689-2024
46. ISORROPIA‐MCX: Enabling Sensitivity Analysis With Multicomplex Variables in the Aerosol Thermodynamic Model, ISORROPIA B. Berman et al. https://doi.org/10.1029/2022EA002729
47. Sensitivity analysis of the potential impact of discrepancies in stratosphere–troposphere exchange on inferred sources and sinks of CO2 F. Deng et al. https://doi.org/10.5194/acp-15-11773-2015
48. A multiphase CMAQ version 5.0 adjoint S. Zhao et al. https://doi.org/10.5194/gmd-13-2925-2020
49. OCO‐2 Satellite‐Imposed Constraints on Terrestrial Biospheric CO2 Fluxes Over South Asia S. Philip et al. https://doi.org/10.1029/2021JD035035
50. Revealing the sulfur dioxide emission reductions in China by assimilating surface observations in WRF-Chem T. Dai et al. https://doi.org/10.5194/acp-21-4357-2021
51. Sensitivity analysis and precursor emission sources reduction strategies of O3 for different pollution weather types based on the GRAPES-CUACE adjoint model C. Wang et al. https://doi.org/10.1016/j.atmosenv.2024.120632
52. Adjoint of the global Eulerian–Lagrangian coupled atmospheric transport model (A-GELCA v1.0): development and validation D. Belikov et al. https://doi.org/10.5194/gmd-9-749-2016
53. Global spatiotemporal completion of daily high-resolution TCCO from TROPOMI over land using a swath-based local ensemble learning method Y. Wang et al. https://doi.org/10.1016/j.isprsjprs.2022.10.012
54. Variational regional inverse modeling of reactive species emissions with PYVAR-CHIMERE-v2019 A. Fortems-Cheiney et al. https://doi.org/10.5194/gmd-14-2939-2021
55. Sensitivity of inorganic aerosol radiative effects to U.S. emissions J. Holt et al. https://doi.org/10.1002/2016JD025890
56. Technical note: A comparative study of chemistry schemes for volcanic sulfur dioxide in Lagrangian transport simulations – a case study of the 2019 Raikoke eruption M. Liu et al. https://doi.org/10.5194/acp-25-4403-2025
57. Adjoint inversion of Chinese non-methane volatile organic compound emissions using space-based observations of formaldehyde and glyoxal H. Cao et al. https://doi.org/10.5194/acp-18-15017-2018
58. Sources of PM2.5‐Associated Health Risks in Europe and Corresponding Emission‐Induced Changes During 2005–2015 Y. Gu et al. https://doi.org/10.1029/2022GH000767
59. 4D‐Var Inversion of European NH3 Emissions Using CrIS NH3 Measurements and GEOS‐Chem Adjoint With Bi‐Directional and Uni‐Directional Flux Schemes H. Cao et al. https://doi.org/10.1029/2021JD035687
60. Evaluation of a multi-model, multi-constituent assimilation framework for tropospheric chemical reanalysis K. Miyazaki et al. https://doi.org/10.5194/acp-20-931-2020
61. The zonal structure of tropical O3 and CO as observed by the Tropospheric Emission Spectrometer in November 2004 – Part 2: Impact of surface emissions on O3 and its precursors K. Bowman et al. https://doi.org/10.5194/acp-9-3563-2009
62. Evaluation of Lagrangian Particle Dispersion Models with Measurements from Controlled Tracer Releases J. Hegarty et al. https://doi.org/10.1175/JAMC-D-13-0125.1
63. Constraints on aerosol sources using GEOS‐Chem adjoint and MODIS radiances, and evaluation with multisensor (OMI, MISR) data X. Xu et al. https://doi.org/10.1002/jgrd.50515
64. Improving PM2. 5 forecast over China by the joint adjustment of initial conditions and source emissions with an ensemble Kalman filter Z. Peng et al. https://doi.org/10.5194/acp-17-4837-2017
65. Inverse modeling of SO2 and NOx emissions over China using multisensor satellite data – Part 2: Downscaling techniques for air quality analysis and forecasts Y. Wang et al. https://doi.org/10.5194/acp-20-6651-2020
66. Estimating global and North American methane emissions with high spatial resolution using GOSAT satellite data A. Turner et al. https://doi.org/10.5194/acp-15-7049-2015
67. Temporal and spatial variability in the aviation NO x -related O 3 impact C. Gilmore et al. https://doi.org/10.1088/1748-9326/8/3/034027
68. Chemical Data Assimilation—An Overview A. Sandu & T. Chai https://doi.org/10.3390/atmos2030426
69. Black carbon emissions in Jordan: national inventory, climate and health implications (2022–2050) A. Al-Shurafat et al. https://doi.org/10.1088/2515-7620/ae1660
70. Profiling tropospheric CO2 using Aura TES and TCCON instruments L. Kuai et al. https://doi.org/10.5194/amt-6-63-2013
71. Inverse modeling of pan-Arctic methane emissions at high spatial resolution: what can we learn from assimilating satellite retrievals and using different process-based wetland and lake biogeochemical models? Z. Tan et al. https://doi.org/10.5194/acp-16-12649-2016
72. Comparing mass balance and adjoint methods for inverse modeling of nitrogen dioxide columns for global nitrogen oxide emissions M. Cooper et al. https://doi.org/10.1002/2016JD025985
73. The 2015–2016 carbon cycle as seen from OCO-2 and the global in situ network S. Crowell et al. https://doi.org/10.5194/acp-19-9797-2019
74. Ozone air quality measurement requirements for a geostationary satellite mission P. Zoogman et al. https://doi.org/10.1016/j.atmosenv.2011.05.058
75. Inverse modeling of NH3sources using CrIS remote sensing measurements H. Cao et al. https://doi.org/10.1088/1748-9326/abb5cc
76. A Method to Quantitatively Apportion Pollutants at High Spatial and Temporal Resolution: The Stochastic Lagrangian Apportionment Method (SLAM) J. Lin & D. Wen https://doi.org/10.1021/es505603v
77. Quantifying Emissions of CO and NOx Using Observations From MOPITT, OMI, TES, and OSIRIS X. Zhang et al. https://doi.org/10.1029/2018JD028670
78. GLIMPSE: A Rapid Decision Framework for Energy and Environmental Policy F. Akhtar et al. https://doi.org/10.1021/es402283j
79. Four-dimensional variational assimilation for SO2 emission and its application around the COVID-19 lockdown in the spring 2020 over China Y. Hu et al. https://doi.org/10.5194/acp-22-13183-2022
80. Validation of TES methane with HIPPO aircraft observations: implications for inverse modeling of methane sources K. Wecht et al. https://doi.org/10.5194/acp-12-1823-2012
81. Satellite observations of atmospheric methane and their value for quantifying methane emissions D. Jacob et al. https://doi.org/10.5194/acp-16-14371-2016
82. Simulation of atmospheric N2O with GEOS-Chem and its adjoint: evaluation of observational constraints K. Wells et al. https://doi.org/10.5194/gmd-8-3179-2015
83. Emissions, degradation and impact of HFO-1234ze from China PU foam industry Y. Wang et al. https://doi.org/10.1016/j.scitotenv.2021.146631
84. Global CO emissions and drivers of atmospheric CO trends constrained by MOPITT satellite measurements Z. Tang et al. https://doi.org/10.5194/acp-26-5531-2026
85. Spatial variation of modelled total, dry and wet nitrogen deposition to forests at global scale D. Schwede et al. https://doi.org/10.1016/j.envpol.2018.09.084
86. The MACC reanalysis: an 8 yr data set of atmospheric composition A. Inness et al. https://doi.org/10.5194/acp-13-4073-2013
87. Assimilating AOD retrievals from GOCI and VIIRS to forecast surface PM2.5 episodes over Eastern China J. Pang et al. https://doi.org/10.1016/j.atmosenv.2018.02.011
88. Evolution of sectoral emissions and contributions to mortality from particulate matter exposure in the Asia-Pacific region between 2010 and 2015 K. Dasadhikari et al. https://doi.org/10.1016/j.atmosenv.2019.116916
89. A Practical Method to Estimate Information Content in the Context of 4D-Var Data Assimilation K. Singh et al. https://doi.org/10.1137/120884523
90. Changes in Inorganic Fine Particulate Matter Sensitivities to Precursors Due to Large-Scale US Emissions Reductions J. Holt et al. https://doi.org/10.1021/acs.est.5b00008
91. Satellite contributions to the quantitative characterization of biomass burning for climate modeling C. Ichoku et al. https://doi.org/10.1016/j.atmosres.2012.03.007
92. Novel Method for Ozone Isopleth Construction and Diagnosis for the Ozone Control Strategy of Chinese Cities H. Shen et al. https://doi.org/10.1021/acs.est.1c01567
93. A 15-year record of CO emissions constrained by MOPITT CO observations Z. Jiang et al. https://doi.org/10.5194/acp-17-4565-2017
94. FootNet v1.0: development of a machine learning emulator of atmospheric transport T. He et al. https://doi.org/10.5194/gmd-18-1661-2025
95. A review of operational, regional-scale, chemical weather forecasting models in Europe J. Kukkonen et al. https://doi.org/10.5194/acp-12-1-2012
96. Detecting drought impact on terrestrial biosphere carbon fluxes over contiguous US with satellite observations J. Liu et al. https://doi.org/10.1088/1748-9326/aad5ef
97. Achieving Both Efficiency and Fairness in Risk-Based Cross-State Air Pollution Controls J. Heo https://doi.org/10.2139/ssrn.3460372
98. Implementation and evaluation of an array of chemical solvers in the Global Chemical Transport Model GEOS-Chem P. Eller et al. https://doi.org/10.5194/gmd-2-89-2009
99. Continuous versus discrete advection adjoints in chemical data assimilation with CMAQ T. Gou & A. Sandu https://doi.org/10.1016/j.atmosenv.2011.06.015
100. A Review of Satellite-Based CO2 Data Reconstruction Studies: Methodologies, Challenges, and Advances K. Hu et al. https://doi.org/10.3390/rs16203818
101. Air Quality Response Modeling for Decision Support D. Cohan & S. Napelenok https://doi.org/10.3390/atmos2030407
102. Reducing the air quality and CO2 climate impacts of taxi and takeoff operations at airports A. Ashok et al. https://doi.org/10.1016/j.trd.2017.05.013
103. Mercury accumulation in soil from atmospheric deposition in temperate steppe of Inner Mongolia, China Z. Cheng et al. https://doi.org/10.1016/j.envpol.2019.113692
104. Technical note: Posterior uncertainty estimation via a Monte Carlo procedure specialized for 4D-Var data assimilation M. Stanley et al. https://doi.org/10.5194/acp-24-9419-2024
105. Impacts of the Degradation of 2,3,3,3-Tetrafluoropropene into Trifluoroacetic Acid from Its Application in Automobile Air Conditioners in China, the United States, and Europe Z. Wang et al. https://doi.org/10.1021/acs.est.7b05960
106. Real-time air quality forecasting, part II: State of the science, current research needs, and future prospects Y. Zhang et al. https://doi.org/10.1016/j.atmosenv.2012.02.041
107. Impacts of anthropogenic and natural sources on free tropospheric ozone over the Middle East Z. Jiang et al. https://doi.org/10.5194/acp-16-6537-2016
108. The SPRINTARS version 3.80/4D-Var data assimilation system: development and inversion experiments based on the observing system simulation experiment framework K. Yumimoto & T. Takemura https://doi.org/10.5194/gmd-6-2005-2013
109. Transboundary air pollution from coal-fired power generation X. Du et al. https://doi.org/10.1016/j.jenvman.2020.110862
110. Spatial sensitivities of human health risk to intercontinental and high-altitude pollution J. Koo et al. https://doi.org/10.1016/j.atmosenv.2013.01.025
111. Prescribed Burns as a Tool to Mitigate Future Wildfire Smoke Exposure: Lessons for States and Rural Environmental Justice Communities M. Kelp et al. https://doi.org/10.1029/2022EF003468
112. Global and regional radiative forcing from 20 % reductions in BC, OC and SO4 – an HTAP2 multi-model study C. Stjern et al. https://doi.org/10.5194/acp-16-13579-2016
113. Prior biosphere model impact on global terrestrial CO2 fluxes estimated from OCO-2 retrievals S. Philip et al. https://doi.org/10.5194/acp-19-13267-2019
114. A framework for scalable ambient air pollution concentration estimation L. Berrisford et al. https://doi.org/10.1017/eds.2025.9
115. Constraints on Asian ozone using Aura TES, OMI and Terra MOPITT Z. Jiang et al. https://doi.org/10.5194/acp-15-99-2015
116. National climate action can ameliorate, perpetuate, or exacerbate international air pollution inequalities M. Nawaz & D. Henze https://doi.org/10.1038/s41467-026-68827-0
117. Retrieval of desert dust and carbonaceous aerosol emissions over Africa from POLDER/PARASOL products generated by the GRASP algorithm C. Chen et al. https://doi.org/10.5194/acp-18-12551-2018
118. The global impacts of COVID-19 lockdowns on urban air pollution G. Gkatzelis et al. https://doi.org/10.1525/elementa.2021.00176
119. Geostatistical inverse modeling with very large datasets: an example from the Orbiting Carbon Observatory 2 (OCO-2) satellite S. Miller et al. https://doi.org/10.5194/gmd-13-1771-2020
120. Enhanced Integration of Health, Climate, and Air Quality Management Planning at the Urban Scale G. Kleiman et al. https://doi.org/10.3389/frsc.2022.934672
121. Effects of a priori profile shape assumptions on comparisons between satellite NO2 columns and model simulations M. Cooper et al. https://doi.org/10.5194/acp-20-7231-2020
122. Global and Brazilian Carbon Response to El Niño Modoki 2011–2010 K. Bowman et al. https://doi.org/10.1002/2016EA000204
123. An Adaptive Auto‐Reduction Solver for Speeding Up Integration of Chemical Kinetics in Atmospheric Chemistry Models: Implementation and Evaluation in the Kinetic Pre‐Processor (KPP) Version 3.0.0 H. Lin et al. https://doi.org/10.1029/2022MS003293
124. Source attribution of particulate matter pollution over North China with the adjoint method L. Zhang et al. https://doi.org/10.1088/1748-9326/10/8/084011
125. Global Terrestrial Ecosystem Carbon Flux Inferred from TanSat XCO 2 Retrievals H. Wang et al. https://doi.org/10.34133/2022/9816536
126. Long-term observational constraints of organic aerosol dependence on inorganic species in the southeast US Y. Zheng et al. https://doi.org/10.5194/acp-20-13091-2020
127. Data fusion in air pollution exposure assessment: Methods, applications, and future directions Y. Liu et al. https://doi.org/10.1080/10962247.2026.2660605
128. Climate change mitigation in Zimbabwe and links to sustainable development D. Sithole et al. https://doi.org/10.1016/j.envdev.2023.100891
129. Characterizing model errors in chemical transport modeling of methane: impact of model resolution in versions v9-02 of GEOS-Chem and v35j of its adjoint model I. Stanevich et al. https://doi.org/10.5194/gmd-13-3839-2020
130. Atmospheric inverse modeling with known physical bounds: an example from trace gas emissions S. Miller et al. https://doi.org/10.5194/gmd-7-303-2014
131. Global evaluation of ammonia bidirectional exchange and livestock diurnal variation schemes L. Zhu et al. https://doi.org/10.5194/acp-15-12823-2015
132. Air pollution and early deaths in the United States. Part II: Attribution of PM2.5 exposure to emissions species, time, location and sector I. Dedoussi & S. Barrett https://doi.org/10.1016/j.atmosenv.2014.10.033
133. The role of NOx emission reductions in Euro 7/VII vehicle emission standards to reduce adverse health impacts in the EU27 through 2050 E. Mulholland et al. https://doi.org/10.1016/j.treng.2022.100133
134. Agricultural ammonia emissions in China: reconciling bottom-up and top-down estimates L. Zhang et al. https://doi.org/10.5194/acp-18-339-2018
135. Quantifying the impact of model errors on top-down estimates of carbon monoxide emissions using satellite observations Z. Jiang et al. https://doi.org/10.1029/2010JD015282
136. Premature mortality related to United States cross-state air pollution I. Dedoussi et al. https://doi.org/10.1038/s41586-020-1983-8
137. Improved analysis‐error covariance matrix for high‐dimensional variational inversions: application to source estimation using a 3D atmospheric transport model N. Bousserez et al. https://doi.org/10.1002/qj.2495
138. A Source Apportionment and Emission Scenario Assessment of PM2.5‐ and O3‐Related Health Impacts in G20 Countries M. Nawaz et al. https://doi.org/10.1029/2022GH000713
139. Development of the CMA-GFS-AERO 4D-Var assimilation system v1.0 – Part 1: System description and preliminary experimental results Y. Liu et al. https://doi.org/10.5194/gmd-18-4855-2025
140. Sources of black carbon during severe haze events in the Beijing–Tianjin–Hebei region using the adjoint method Y. Mao et al. https://doi.org/10.1016/j.scitotenv.2020.140149
141. Attribution of PM2.5 exposure in Beijing–Tianjin–Hebei region to emissions: implication to control strategies X. Li et al. https://doi.org/10.1016/j.scib.2017.06.005
142. Computationally efficient methods for large-scale atmospheric inverse modeling T. Cho et al. https://doi.org/10.5194/gmd-15-5547-2022
143. Comparisons of simple and complex methods for quantifying exposure to individual point source air pollution emissions L. Henneman et al. https://doi.org/10.1038/s41370-020-0219-1
144. Characterizing model errors in chemical transport modeling of methane: using GOSAT XCH4 data with weak-constraint four-dimensional variational data assimilation I. Stanevich et al. https://doi.org/10.5194/acp-21-9545-2021
145. A low-order coupled chemistry meteorology model for testing online and offline data assimilation schemes: L95-GRS (v1.0) J. Haussaire & M. Bocquet https://doi.org/10.5194/gmd-9-393-2016
146. Air pollution mitigation assessment to inform Cambodia's first clean air plan P. Sokharavuth et al. https://doi.org/10.1016/j.envres.2023.115230
147. Spatiotemporally Detailed Quantification of Air Quality Benefits of Emissions–Part II: Sensitivity to Study Parameters and Assumptions A. Hakami et al. https://doi.org/10.1021/acsestair.4c00128
148. A Review of City-Scale Methane Flux Inversion Based on Top-Down Methods X. Li et al. https://doi.org/10.3390/rs17183152
149. A high-resolution satellite-based map of global methane emissions reveals missing wetland, fossil fuel, and monsoon sources X. Yu et al. https://doi.org/10.5194/acp-23-3325-2023
150. Sources of PM2.5 exposure and health benefits of clean air actions in Shanghai Y. Gu et al. https://doi.org/10.1016/j.envint.2025.109259
151. Transboundary transport of ozone pollution to a US border region: A case study of Yuma Z. Qu et al. https://doi.org/10.1016/j.envpol.2020.116421
152. TES ammonia retrieval strategy and global observations of the spatial and seasonal variability of ammonia M. Shephard et al. https://doi.org/10.5194/acp-11-10743-2011
153. Analysis of transpacific transport of black carbon during HIPPO-3: implications for black carbon aging Z. Shen et al. https://doi.org/10.5194/acp-14-6315-2014
154. JRAero: the Japanese Reanalysis for Aerosol v1.0 K. Yumimoto et al. https://doi.org/10.5194/gmd-10-3225-2017
155. Evaluating the Impact of Emissions Regulations on the Emissions Reduction During the 2015 China Victory Day Parade With an Ensemble Square Root Filter K. Chu et al. https://doi.org/10.1002/2017JD027631
156. The impact of multi-species surface chemical observation assimilation on air quality forecasts in China Z. Peng et al. https://doi.org/10.5194/acp-18-17387-2018
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229. Origin and radiative forcing of black carbon transported to the Himalayas and Tibetan Plateau M. Kopacz et al. https://doi.org/10.5194/acp-11-2837-2011
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253. Health benefits of phasing out coal-fired power plants in Ontario, Alberta, and Canada Y. Öztaner et al. https://doi.org/10.1016/j.atmosenv.2024.120711
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263. The Adjoint of CMAQ A. Hakami et al. https://doi.org/10.1021/es070944p
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267. Responses of Photochemical Air Pollution in California’s San Joaquin Valley to Spatially and Temporally Resolved Changes in Precursor Emissions Y. Wang et al. https://doi.org/10.1021/acs.est.1c07011
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291. New constraints on biogenic emissions using satellite-based estimates of carbon monoxide fluxes H. Worden et al. https://doi.org/10.5194/acp-19-13569-2019
292. How well can inverse analyses of high-resolution satellite data resolve heterogeneous methane fluxes? Observing system simulation experiments with the GEOS-Chem adjoint model (v35) X. Yu et al. https://doi.org/10.5194/gmd-14-7775-2021
293. Top-down constraints on global N2O emissions at optimal resolution: application of a new dimension reduction technique K. Wells et al. https://doi.org/10.5194/acp-18-735-2018
294. Public health costs accounting of inorganic PM2.5 pollution in metropolitan areas of the United States using a risk-based source-receptor model J. Heo et al. https://doi.org/10.1016/j.envint.2017.06.006
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303. Intercontinental source attribution of ozone pollution at western U.S. sites using an adjoint method L. Zhang et al. https://doi.org/10.1029/2009GL037950
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308. Global health benefits of policies to reduce on-road vehicle pollution through 2040 L. Jin et al. https://doi.org/10.1088/1748-9326/adcd87
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310. Sensitivity analysis of atmospheric oxidation capacity in Beijing based on the GRAPES-CUACE adjoint model C. Wang et al. https://doi.org/10.1016/j.atmosenv.2023.119641
311. The influence of boreal biomass burning emissions on the distribution of tropospheric ozone over North America and the North Atlantic during 2010 M. Parrington et al. https://doi.org/10.5194/acp-12-2077-2012
312. Application of an adjoint neighborhood‐scale chemistry transport model to the attribution of primary formaldehyde at Lynchburg Ferry during TexAQS II E. Olaguer https://doi.org/10.1002/jgrd.50406
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