A range of commercially-available automatic pollen monitors were run in parallel and evaluated for the first time during the 2019 spring season; this includes the Droplet Measurement Technologies WIBS-NEO, Helmut-Hund BAA-500, the Plair Rapid-E, two Swisens Poleno, and two Yamatronics KH-3000 devices. The instruments were run from 19 April to 31 May 2019 and located in Payerne, Switzerland, representative of a semi-rural site on the Swiss plateau. The devices were validated against Hirst-type traps in terms of total pollen counts for daily and sub-daily averages. While the manual measurements cannot be considered a "gold standard" in terms of absolute values, they provide an established reference against which the automatic instruments can be evaluated. Overall, there was considerable spread between instruments compared to the manual observations. The devices showed better performance when daily averages were considered, with three of the seven showing non-significantly different values from the manual measurements. However, when six-hourly averages were considered, only one of the instruments was not significantly different from the Hirst trap average. The largest differences between instruments were evident at low pollen concentrations (< 20 pollen grains/m 3 ), no matter the temporal resolution considered. This is in part, however, to be expected since it is at such low concentrations that the Hirst measurements are most uncertain. It is also important to note that in 2019 many of the instruments tested had only recently been developed. Differences may also have arisen due to their varying abilities to identify specific pollen taxa or because the classification algorithms applied were developed for different pollen taxa and not total pollen, the variable considered in this study Keywords pollen • automatic monitoring • validation • real-time • Hirst 1. Introduction Airborne pollen form just a small fraction of the atmospheric bioaerosol loading ([36]; [18]; [39]), but despite their low number concentrations these particles are of significant importance because of their impact on human health ([38]; [47]; [14]), agriculture and sylviculture ([6]; [20]), as well as on climate through their role in the hydrological cycle ([35]; [10]). Pollen monitoring networks exist in most countries, providing information to a range of end-users from allergy sufferers and their doctors through to researchers. The current standard that is used across these networks is based on manual technology developed in the early 1950s ([17]; [13]; [2]) that is both time-consuming and laborious. Furthermore, this measurement technique suffers from several shortcomings, including the fact that data are delivered at low temporal resolution (usually daily averages) with a delay of between 3-9 days from the time of observation. New technologies developed over the past few years have made it possible to automatically measure pollen at high temporal resolutions and in real-time ([41],[33], [40]). The provision of such observations is dramatically ...