11 citations as recorded by crossref.

1. Estimating long-term PM10-2.5 concentrations in six US cities using satellite-based aerosol optical depth data M. Pedde et al. https://doi.org/10.1016/j.atmosenv.2022.118945
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3. Exploring the formation mechanism of fine particles in an ex-heavily polluted Northwestern city, China Z. Liu et al. https://doi.org/10.1016/j.scitotenv.2022.161333
4. Effects of COVID-19 lockdowns on fine particulate matter concentrations M. Hammer et al. https://doi.org/10.1126/sciadv.abg7670
5. Urban inland wintertime N2O5 and ClNO2 influenced by snow-covered ground, air turbulence, and precipitation K. Kulju et al. https://doi.org/10.5194/acp-22-2553-2022
6. Evaluating the Impacts of Cloud Processing on Resuspended Aerosol Particles After Cloud Evaporation Using a Particle‐Resolved Model Y. Yao et al. https://doi.org/10.1029/2021JD034992
7. Ambient Aerosol Is Physically Larger on Cloudy Days in Bondville, Illinois M. Flesch et al. https://doi.org/10.1021/acsearthspacechem.2c00207
8. High-resolution sampling and chemical characterisation of wet deposition using the low-cost R-WASH system A. Stein Santos et al. https://doi.org/10.1080/09593330.2025.2556348
9. Factors influencing ambient particulate matter in Delhi, India: Insights from machine learning K. Patel et al. https://doi.org/10.1080/02786826.2023.2193237
10. Machine learning-guided integration of fixed and mobile sensors for high resolution urban PM2.5 mapping T. Li et al. https://doi.org/10.1038/s41612-025-00984-3
11. Evaluation and source apportionment of persistent decadal air pollution disparities in Kansas City, Missouri S. Ojha et al. https://doi.org/10.1080/10962247.2025.2572810