Automatic monitoring and imaging-based identification of airborne Olea pollen

Monitoring airborne pollen needs to ensure precision and data reproducibility. The classic volumetric method of Hirst-type spore trap is the gold standard proposed by the European norm. This method is time-consuming and requires highly qualified personnel. Additionally, this method produces a temporal delay of the recorded data of 5 to 10 days. Although significant work has been done, with varying degrees of success, there are still some issues with automatic pollen monitoring. We compared the pollen concentration observed using Pollen Sense APS-330 with parallel measurements taken with a Hirst-type sampler. Here, we focus on olive pollen season data during 2023 and 2024 in Córdoba (Spain). The average daily pollen concentrations recorded by the APS-330 were 2129 pollen grains/m³, and by the Hirst were 1535 pollen grains/m³. During 2023, the APS-330 recorded the maximum daily concentration of 9276 pollen grains/m³ on April 27, whereas the Hirst also recorded the peak concentration the same day, with 8228 pollen grains/m³. During 2024, both samplers showed the peak concentration on 23 April, 4798 pollen grains/m³ by APS-330 and 3500 pollen grains/m³ by Hirst. We observed a significant correlation (r = 0.93-0.94) of daily pollen concentrations provided by both samplers. Similar correlations with weather variables are shown. We observe a ratio between both samplers close to 1, meaning similar concentrations. However, the ratio increases during periods with high pollen concentration, meaning that Hirst might underestimate pollen concentrations consistently when there is a high number of particles in the air. These results are very promising and will greatly impact olive management strategies and potential applications from a public health standpoint. The mobile and real-time capabilities of APS-330 underscore its potential to monitor Olea pollen. However, this study is restricted to an urban site for Olea pollen. Continued field test data of additional monitoring sites with different degrees of urbanisation is recommended to improve accuracy and continued validation.