Pollen and fungal spores have detrimental effects on health [1,2,3,4,5,6,7] and it is therefore logical that these airborne allergenic particles are monitored throughout the world. Monitoring the air quality of non-biological components in ambient air is commonplace and is undertaken world-wide, mostly on the basis of legal exposure limits. The airborne components such as PM10, PM2.5, SO2, NOX and O3 that are monitored, often with standardized methods, may be different depending on the country that is carrying out the monitoring. The fact that this monitoring is carried out with public financing signifies that most of the data from these networks are available to the public at no cost and are often published with open access on the internet. Citizens can, therefore, easily assess the quality of the air that they breathe with a minimal lag time thanks to these online networks.
The situation of biological particles is, however, completely different. Only few countries like MeteoSwiss (Switzerland) and RNSA (France) have state-owned monitoring networks. Biological particles, including pollen and fungal spores (spores), were first monitored with medical purposes in 1870 by Blackley in the UK , and the oldest continuous pollen record dates back to 1943 in Cardiff, the UK, a station that has used a Hirst pollen trap since 1954 [9,10,11]. The volumetric Hirst-type pollen and spore trap is still one of the instruments most widely used for pollen and spore monitoring . Records for non-biological components are more recent: for example, the CO2 concentrations in ambient air at Mauna Loa, Hawaii, date back to 1958 . Another difference between biological and non-biological air quality monitoring is that non-biological particles are collected by law as particles of < 10 µm or smaller (PM10, PM2.5), whereas biological particles are often > 10 µm [14,15,16]. Some pollen, such as Urticamembranaceae Poir (Urticaceae) , and some fungal spores are < 10 µm in diameter (e.g. Aspergillus or Penicillium ), but none are smaller than fine particles of < 2.5 µm. Non-biological air quality parameters are, therefore, either gasses or small particles, while biological air quality parameters are predominately very large particles.
Despite the large size of pollen, the imperfect capacity of common PM10 samplers to separate particles by size  signifies that up to 15% of birch (21 µm, range approx. 15–27 µm) or grass pollen (25–45 µm) falls into the PM10 fraction (particles of between 2.5 and 10 µm) [15, 20, 21], and the situation is similar for other pollen and moulds. The reason why very large particles are found in < 10 µm fractions of air is that the instruments used to collect particulate matter from ambient air do not completely separate them. These instruments, which are mostly impactors, have less efficient separation characteristics then their names suggest: PM10 implies that particles > 10 µm are separated from the smaller particles. This is not the case, and approximately 15% of pollen, and even pollen which is larger than 20 µm, can be detected in the fraction of air that should contain only particles of < 10 µm. Pollen and fungal spores are, therefore, collected with the existing air-quality monitoring networks, but very poorly and these technical limitations consequently signify that networks monitoring non-biological components are not useful for monitoring biological particles.
About 30% of the population suffers from some type of allergy to airborne pollen , which may have extreme effects on their health, including death . However, few governments own pollen monitoring stations or run a monitoring network for pollen and/or fungal spores. Most pollen and spore networks are privately owned and the data they produce are not freely available.
For allergy sufferers, the location of pollen monitoring stations is unclear and mostly unknown: many Apps deliver pollen forecasts, but it is unclear how the data are obtained and are of little interest to the users, as they assume that sufficient data support the pollen flight prognosis. This is often not the case. For instance, Bavaria in Germany has 12 million inhabitants but only 3 non-public pollen monitoring stations are operating (www.pollenstiftung.de), despite the availability of many Apps. The quality of the pollen flight prognosis is consequently, questionable. Finding the location of pollen monitoring stations could, therefore, be useful for stakeholders. The creation of a map of pollen monitoring stations will improve access to local pollen data and will, hopefully, benefit those with allergies, the medical profession and, of course, aerobiologists. Our aim was, therefore, to a review pollen and spore monitoring stations throughout the world and to develop a practical visualisation method to disseminate their data.