Vertical aerosol flux in urban ecosystem: how far can we push Doppler lidar aerosol observations?

Abstract. This work presents analysis of Doppler lidar-derived vertical aerosol fluxes in urban ecosystems. Based on long-term multi-seasonal measurements, we characterized the dependence of aerosol flux occurrence frequency, direction of the transport and velocity regime on seasons, diurnal cycle and altitude. To synthesize the results, we introduced the term aerosol flux intensity factor and applied it based on the aerosol flux parameters described above. This constitutes the first data analysis and characterization of vertical aerosol fluxes for an urban environment, based on multi-year (2022–2024) Doppler lidar data in Warsaw, Poland. For additional data filtering, we used data products from co-located microwave radiometer and disdrometer. The measurements were conducted within the routine observations of the Cloud Observations Network (Cloudnet-ACTRIS) at the Warsaw Observatory Station (WOS), an ACTRIS National Facility operated by the University of Warsaw, located on the roof platform of the Institute of Geophysics, Faculty of Physics, University of Warsaw (IGF UW). We observed that aerosol fluxes are most intense during Spring (MAM), particularly at the lowest altitudes during the midday Well-Mixed Layer presence. Summer and autumn (JJA and SON) represent transition periods between spring and winter (DJF), while in winter the aerosol flux intensity is generally low. Our findings suggest that the seasonal distribution of aerosol flux intensity is strongly asymmetric. After DJF, abrupt changes in vertical transport lead to a rapid intensification of aerosol fluxes over a single seasonal transition, while after spring the intensity decreases gradually. This work contributes to the multi-seasonal characterisation of aerosol flux intensity, providing a priori knowledge for aerosol vertical transport in the urban environment, and enhancing atmospheric aerosol optical property assessments, particularly in calculations based on temporal averages. The proposed methodology provides the basis for performing similar analysis at other ecosystems or measurement sites.