14 citations as recorded by crossref.

1. Applications of Machine Learning and Artificial Intelligence in Tropospheric Ozone Research S. Hickman et al. https://doi.org/10.5194/gmd-18-8777-2025
2. The Capability of Deep Learning Model to Predict Ozone Across Continents in China, the United States and Europe W. Han et al. https://doi.org/10.1029/2023GL104928
3. Atmospheric CH4 plateau sustained by NOx emission rise and southward shift Y. Zhu et al. https://doi.org/10.1038/s41586-026-10983-w
4. Observation-constrained sensitivities of Arctic methane emissions to warming G. Liu et al. https://doi.org/10.1073/pnas.2523274123
5. Rapid Adaptive Optimization Model for Atmospheric Chemistry (ROMAC) v1.0 J. Li et al. https://doi.org/10.5194/gmd-16-6049-2023
6. Opinion: Challenges and needs of tropospheric chemical mechanism development B. Ervens et al. https://doi.org/10.5194/acp-24-13317-2024
7. Guaranteed Mass-Conserving Deep Learning Model for Stiff Kinetics in Atmospheric Chemistry H. Feng et al. https://doi.org/10.1021/acsearthspacechem.6c00004
8. Trends in the seasonal amplitude of atmospheric methane G. Liu et al. https://doi.org/10.1038/s41586-025-08900-8
9. 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
10. Implementation of a parallel reduction algorithm in the GENerator of reduced Organic Aerosol mechanisms (GENOA v2.0): Application to multiple monoterpene aerosol precursors Z. Wang et al. https://doi.org/10.1016/j.jaerosci.2023.106248
11. Data-Driven Surface Ozone Forecasting Using Node-Based Gated Spatiotemporal Fusion M. Lor et al. https://doi.org/10.1109/TGRS.2026.3725283
12. Improved advection, resolution, performance, and community access in the new generation (version 13) of the high-performance GEOS-Chem global atmospheric chemistry model (GCHP) R. Martin et al. https://doi.org/10.5194/gmd-15-8731-2022
13. Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP S. Fiedler et al. https://doi.org/10.5194/gmd-17-2387-2024
14. Data driven analysis on changing patterns of reactive nitrogen deposition in East and Southeast Asia J. Tan et al. https://doi.org/10.1016/j.atmosenv.2026.121962