24 citations as recorded by crossref.

1. Development of an AI Model to Measure Traffic Air Pollution from Multisensor and Weather Data H. Ly et al.
2. Influences of planetary boundary layer mixing parameterization on summertime surface ozone concentration and dry deposition over North China Y. Zhao et al.
3. Google Earth Engine-based mapping of land use and land cover for weather forecast models using Landsat 8 imagery M. Ganjirad & H. Bagheri
4. High-Resolution Modeling of Air Quality in Abidjan (Côte d’Ivoire) Using a New Urban-Scale Inventory S. Gnamien et al.
5. Assessing the COVID‐19 Impact on Air Quality: A Machine Learning Approach Y. Rybarczyk & R. Zalakeviciute
6. Ozone air quality simulations with WRF-Chem (v3.5.1) over Europe: model evaluation and chemical mechanism comparison K. Mar et al.
7. Uso do Modelo WRF-CHEM para a Simulação da Dispersão de Gases no Centro de Lançamento de Alcântara. P. Iriart & G. Fisch
8. Evaluation of air quality forecasting system FORAIR-IT over Europe and Italy at high resolution for year 2017 M. Adani et al.
9. The influence of dry deposition on surface ozone simulations under different planetary boundary layer schemes over eastern China D. Li et al.
10. Setting-up a Real-Time Air Quality Forecasting system for Serbia: a WRF-Chem feasibility study with different horizontal resolutions and emission inventories Z. Podrascanin
11. High-resolution multi-scale air pollution system: Evaluation of modelling performance and emission control strategies D. Lopes et al.
12. Data imbalance causes underestimation of high ozone pollution in machine learning models: A weighted support vector regression solution L. Zhen et al.
13. Evaluation of the offline-coupled GFSv15–FV3–CMAQv5.0.2 in support of the next-generation National Air Quality Forecast Capability over the contiguous United States X. Chen et al.
14. Optimized neural network for daily-scale ozone prediction based on transfer learning W. Ma et al.
15. Selection of the data time interval for the prediction of maximum ozone concentrations J. Kocijan et al.
16. Improving of local ozone forecasting by integrated models D. Gradišar et al.
17. Improving air quality assessment using physics-inspired deep graph learning L. Li et al.
18. A Hybrid Neural Network Model for Predicting Air Quality under the Coupling of Ground Atmosphere Z. Li et al.
19. Quantifying the sensitivity of aerosol optical properties to the parameterizations of physico-chemical processes during the 2010 Russian wildfires and heatwave L. Palacios-Peña et al.
20. Source attribution of carbon monoxide over Northern India during crop residue burning period over Punjab A. Sharma et al.
21. The 1-way on-line coupled model system MECO(n) – Part 4: Chemical evaluation (based on MESSy v2.52) M. Mertens et al.
22. Combined Effect of High-Resolution Land Cover and Grid Resolution on Surface NO2 Concentrations C. Silveira et al.
23. PM2.5 and O3 concentration estimation based on interpretable machine learning S. Wang et al.
24. Evaluation of real-time PM2.5 forecasts with the WRF-CMAQ modeling system and weather-pattern-dependent bias-adjusted PM2.5 forecasts in Taiwan F. Cheng et al.