To benefit allergy patients and the medical practitioners, pollen information should be available in both a reliable and timely manner; the latter is only recently possible due to automatic monitoring. To evaluate the performance of all currently available automatic instruments, an international intercomparison campaign was jointly organised by the EUMETNET AutoPollen Programme and the ADOPT COST Action in Munich, Germany (March-July 2021). The automatic systems (hardware plus identification algorithms) were compared with manual Hirst-type traps. Measurements were aggregated into 3-hourly or daily values to allow comparison across all devices. We report results for total pollen as well as for Betula, Fraxinus, Poaceae, and Quercus, for all instruments that provided these data. The results for daily averages compared better with Hirst observations than the 3-hourly values. For total pollen, there was a considerable spread among systems, with some reaching R² > 0.6 (3 h) and R² > 0.75 (daily) compared with Hirst-type traps, whilst other systems were not suitable to sample total pollen efficiently (R² < 0.3). For individual pollen types, results similar to the Hirst were frequently shown by a small group of systems. For Betula, almost all systems performed well (R² > 0.75 for 9 systems for 3-hourly data). Results for Fraxinus and Quercus were not as good for most systems, while for Poaceae (with some exceptions), the performance was weakest. For all pollen types and for most measurement systems, false positive classifications were observed outside of the main pollen season. Different algorithms applied to the same device also showed different results, highlighting the importance of this aspect of the measurement system. Overall, given the 30 % error on daily concentrations that is currently accepted for Hirst-type traps, several automatic systems are currently capable of being used operationally to provide real-time observations at high temporal resolutions. They provide distinct advantages compared to the manual Hirst-type measurements.

Aerobiological databases are constantly increasing. Many of them contain long and extensive time series of data which are very difficult and tedious to manage. The development of new real‐time automatic sampling devices also requires new tools to reduce time of calculations and data management. In this sense, the AeRobiology r package has been implemented to accelerate and facilitate these tasks. This package was structured in three sections based on (a) the checking of the database, (b) calculation of the main aerobiological indexes and (c) visualization of the results. The AeRobiology package contains numerous functions which, in conjunction, solve the main general tasks that scientists must assume for the analysis of the biological data. The package is freely distributed under GNU General Public License and can directly be installed from CRAN (http://cran.r-project.org/). The reference manual is available at https://cran.r-project.org/web/packages/AeRobiology. Contact: aerobiology.package@gmail.com.