44 citations as recorded by crossref.

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3. Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE): emissions of particulate matter and sulfur dioxide from vehicles and brick kilns and their impacts on air quality in the Kathmandu Valley, Nepal M. Zhong et al. https://doi.org/10.5194/acp-19-8209-2019
4. Potential role of local contributions to record-breaking high-temperature event in Xiamen, China F. Wang & Y. Wang https://doi.org/10.1016/j.wace.2021.100338
5. Comparison of CO2 Content in the Atmosphere of St. Petersburg According to Numerical Modeling and Observations G. Nerobelov et al. https://doi.org/10.1134/S0001433823020056
6. Revisiting black carbon emission estimates in the Third Pole: a hierarchical Bayesian synthesis inversion perspective C. Roychoudhury et al. https://doi.org/10.1088/2515-7620/ae4858
7. Insights of Boundary Layer Turbulence Over the Complex Terrain of Central Himalaya from GVAX Field Campaign A. Rajput et al. https://doi.org/10.1007/s13143-023-00341-5
8. Air quality trends of the Kathmandu Valley: A satellite, observation and modeling perspective P. Mahapatra et al. https://doi.org/10.1016/j.atmosenv.2018.12.043
9. Effects of spatial resolution on WRF v3.8.1 simulated meteorology over the central Himalaya J. Singh et al. https://doi.org/10.5194/gmd-14-1427-2021
10. Pre-monsoon submicron aerosol composition and source contribution in the Kathmandu Valley, Nepal B. Werden et al. https://doi.org/10.1039/D2EA00008C
11. Assessment of the impact of atmospheric aerosols and meteorological data assimilation on simulation of the weather over India during summer 2015 S. Devaliya et al. https://doi.org/10.1016/j.atmosenv.2023.119586
12. Variations in surface ozone and carbon monoxide in the Kathmandu Valley and surrounding broader regions during SusKat-ABC field campaign: role of local and regional sources P. Bhardwaj et al. https://doi.org/10.5194/acp-18-11949-2018
13. Investigating dust storm dynamics and lightning interactions using Weather Research Forecasting-Chemistry (WRF-CHEM) model over India V. Swathi et al. https://doi.org/10.1016/j.scitotenv.2025.180083
14. Molecular characterization of organic aerosols in the Kathmandu Valley, Nepal: insights into primary and secondary sources X. Wan et al. https://doi.org/10.5194/acp-19-2725-2019
15. South and Southeast Asia controls black carbon characteristics of Meili Snow Mountains in southeast Tibetan Plateau P. Chen et al. https://doi.org/10.1016/j.scitotenv.2024.172262
16. High Resolution Chemistry Transport Modeling with the On-Line CHIMERE-WRF Model over the French Alps—Analysis of a Feedback of Surface Particulate Matter Concentrations on Mountain Meteorology B. Bessagnet et al. https://doi.org/10.3390/atmos11060565
17. Complex Validation of Weather Research and Forecasting—Chemistry Modelling of Atmospheric CO2 in the Coastal Cities of the Gulf of Finland G. Nerobelov et al. https://doi.org/10.3390/rs15245757
18. Anomalous transport in the planetary boundary layer: A three-dimensional time-fractional advection–diffusion model S. Pariyar et al. https://doi.org/10.1016/j.physa.2026.132017
19. Long-Term Trends in Black Carbon and Aerosol Optical Depth Over the Central Himalayas: Potential Causes and Implications H. Joshi et al. https://doi.org/10.3389/feart.2022.851444
20. Characterizing Emissions from Agricultural Diesel Pumps in the Terai Region of Nepal S. Adhikari et al. https://doi.org/10.3390/atmos10020056
21. Top-down vehicle emission inventory for spatial distribution and dispersion modeling of particulate matter W. Andreão et al. https://doi.org/10.1007/s11356-020-08476-y
22. A Comparative Study of Stack Emissions from Straight-Line and Zigzag Brick Kilns in Nepal S. Nepal et al. https://doi.org/10.3390/atmos10030107
23. Wintertime Boundary Layer Evolution and Air Pollution Potential Over the Kathmandu Valley, Nepal R. Regmi et al. https://doi.org/10.1029/2018JD030198
24. Impact of local and regional emission sources on air quality in foothills of the Himalaya during spring 2016: An observation, satellite and modeling perspective M. Mehra et al. https://doi.org/10.1016/j.atmosenv.2019.116897
25. Insights to WRF-Chem sensitivity in a zone of complex terrain in the tropical Andes: Effect of boundary conditions, chemical mechanisms, nesting, and domain configuration F. Cifuentes et al. https://doi.org/10.1016/j.apr.2021.101093
26. Estimating Black Carbon Concentrations in China by Combining Machine Learning Models and Optimization of Satellite-Based Input Schemes S. Li et al. https://doi.org/10.1109/TGRS.2026.3652561
27. Quantifying the air quality and health benefits of greening freight movements L. Minet et al. https://doi.org/10.1016/j.envres.2020.109193
28. Air pollution terrain nexus: A review considering energy generation and consumption X. Wang et al. https://doi.org/10.1016/j.rser.2019.01.049
29. Comparison of СO₂ Content in the Atmosphere of St. Petersburg According to Numerical Modelling and Observations G. Nerobelov et al. https://doi.org/10.31857/S0002351523020050
30. Impacts of different boundary layer parameterization schemes on simulation of meteorology over Himalaya J. Singh et al. https://doi.org/10.1016/j.atmosres.2023.107154
31. Isotope constraints of the strong influence of biomass burning to climate-forcing Black Carbon aerosols over Southeast Asia J. Liu et al. https://doi.org/10.1016/j.scitotenv.2020.140359
32. Aerosol–precipitation elevation dependence over the central Himalayas using cloud-resolving WRF-Chem numerical modeling P. Adhikari & J. Mejia https://doi.org/10.5194/acp-23-1019-2023
33. Improving Temporal and Spatial Coverage of UK Black Carbon Measurements by Applying a Machine Learning Approach I. Wong et al. https://doi.org/10.1021/acsestair.4c00306
34. Meteorological Downscaling with WRF Model, Version 4.0, and Comparative Evaluation of Planetary Boundary Layer Schemes over a Complex Coastal Airshed C. Onwukwe & P. Jackson https://doi.org/10.1175/JAMC-D-19-0212.1
35. The effect of local pollution and transport dust on near surface aerosol properties over a semi-arid station from ground and satellite observations B. Akkiraju et al. https://doi.org/10.1007/s11869-023-01462-6
36. Evaluating and comparison of WRF-chem model configurations for wind field impact on the April 2022 dust episode in western Iran E. Hassan et al. https://doi.org/10.1016/j.atmosenv.2024.120892
37. Evaluation of WRF-Chem-simulated meteorology and aerosols over northern India during the severe pollution episode of 2016 P. Agarwal et al. https://doi.org/10.5194/acp-24-2239-2024
38. Particulate matter variability in Kathmandu based on in-situ measurements, remote sensing, and reanalysis data S. Becker et al. https://doi.org/10.1016/j.atmosres.2021.105623
39. Sulfur dioxide emissions in Portugal: Prediction, estimation and air quality regulation using machine learning V. Ribeiro https://doi.org/10.1016/j.jclepro.2021.128358
40. Long-term trends of black carbon levels, sources, and radiative effects from 2013 to 2022 in Beijing, China Y. Xie et al. https://doi.org/10.1038/s44407-025-00010-z
41. Tracing Atmospheric Anthropogenic Black Carbon and Its Potential Radiative Response Over Pan‐Third Pole Region: A Synoptic‐Scale Analysis Using WRF‐Chem M. Rai et al. https://doi.org/10.1029/2021JD035772
42. MATCHA, a novel regional hydroclimate-chemical reanalysis: System description and evaluation C. Roychoudhury et al. https://doi.org/10.5194/essd-18-5209-2026
43. Dynamics of Mixing Layer Height and Homogeneity from Ceilometer-Measured Aerosol Profiles and Correlation to Ground Level PM2.5 in New York City D. Li et al. https://doi.org/10.3390/rs14246370
44. Validation of a 10-meter wind in simulating a dust event in northwestern Iran mountains (October 28–31, 2017) E. Mobarak Hassan et al. https://doi.org/10.1016/j.aeolia.2025.101002