Lidar estimates of birch pollen number, mass, and CCN-related concentrations

The accurate representation of microphysical properties of atmospheric aerosol particles - such as the number, mass, and cloud condensation nuclei (CCN) concentration - is key to constraining climate forcing estimations and improving weather and air quality forecasts. Lidars capable of vertically resolving aerosol optical properties have been increasingly utilized to study aerosol-cloud interactions, allowing for estimations of cloud-relevant microphysical properties. Recently, lidars have been employed to identify and monitor pollen particles in the atmosphere, an understudied aerosol particle with health and possibly climate implications. Lidar remote sensing of pollen is an emerging research field, and in this study, we present for the first time retrievals of particle number, mass, CCN, giant CCN (GCCN), and ultragiant CCN (UGCCN) concentration estimations of birch pollen derived from polarization lidar observations and specifically from a PollyXT lidar and a Vaisala CL61 ceilometer at 532 and 910 nm, respectively.