Fungal spores make up a significant portion of Primary Biological Aerosol Particles (PBAPs) with large quantities of such particles noted in the air. Fungal particles are of interest because of their potential to affect the health of both plants and humans. They are omnipresent in the atmosphere year-round, with concentrations varying due to meteorological parameters and location. Equally, differences between indoor and outdoor fungal spore concentrations and dispersal play an important role in occupational health. This review attempts to summarise the different spore sampling methods, identify the most important spore types in terms of negative effects on crops and the public, the factors affecting their growth/dispersal, and different methods of predicting fungal spore concentrations currently in use.

Non-Road Mobile Machinery (NRMM) incorporate a wide range of machinery, with or without bodywork and wheels, and are installed with a combustion engine and not intended for carrying passengers or goods on the road. These are used in many different sectors including construction, agriculture, forestry, mining, local authorities, airport and port ground operations, railways, inland waterways and within the household and gardening sector. This article presents a review of the state of knowledge with regard to non-road mobile machinery, particularly focusing on their regulation and the atmospheric emissions associated with them. This was undertaken as there is currently a lack of this information available in the literature, which is an oversight due to the potential for Non-Road Mobile Machinery to form a greater part of atmospheric emissions in the future, as other areas of emissions are tackled by regulations, as is outlined in the article. Emissions such as particulate matter (PM), carbon oxide (CO), carbon dioxide (CO₂), hydrocarbons (HC), nitrogen oxides (NO_x) and sulphur oxides (SO_x) from NRMM contribute considerably to total emissions released into the air. NRMM are diverse in application, engine type and fuel use, and are therefore difficult to categorise. This leads to numerous issues when it comes to the control and regulation of their emissions. The most recent European and international regulations are outlined in this article. Due to the divergent nature of NRMM, their emissions profiles are highly varied, and in-use emissions monitoring is challenging. This has led to a lack of data and inaccuracies in the estimation of total emissions and emission inventories. It was assumed in the past that emissions from non-road sources did not contribute as significantly to total emissions as those from on-road sources. This assumption was partly due to the difficulty in gathering relevant data, and it was disproven in the 1990s by studies in The Netherlands, Finland and Sweden. It is now understood that NRMM will eventually surpass on-road vehicles as the leading source of mobile pollution due to the continuing efforts to reduce emissions from other sources. Many states worldwide gather emissions data from NRMM, and EU member states are required to report their emissions. As of January 2017, a new European regulation establishing limits for gaseous and particulate pollutants from NRMM applies, and this regulation also defines administrative and technical requirements for EU approval. The exact number of NRMM and the total amount of fuel they use is currently not known. In Ireland, for example, their fuel use has been reported under stationary boilers and engines. However, this results in the underestimation of emissions of some pollutants (NO_x in particular) because emissions of air pollutants tend to be higher in mobile than in stationary machinery.

Public awareness of the rising importance of allergies and other respiratory diseases has led to increased scientific effort to accurately and rapidly monitor and predict pollen, fungal spores and other bioaerosols in our atmosphere. An important driving force for the increased social and scientific concern is the realisation that climate change will increasingly have an impact on worldwide bioaerosol distributions and subsequent human health. In this review we examine new developments in monitoring of atmospheric pollen as well as observation and source-orientated modelling techniques. The results of a Scopus® search for scientific publications conducted with the terms ‘Pollen allergy’ and ‘Pollen forecast’ included in the title, abstract or keywords show that the number of such articles published has increased year on year. The 12 most important allergenic pollen taxa in Europe as defined by COST Action ES0603 were ranked in terms of the most ‘popular’ for model-based forecasting and for forecasting method used. Betula, Poaceae and Ambrosia are the most forecast taxa. Traditional regression and phenological models (including temperature sum and chilling models) are the most used modelling methods, but it is notable that there are a large number of new modelling techniques being explored. In particular, it appears that Machine Learning techniques have become more popular and led to better results than more traditional observation-orientated models such as regression and time-series analyses.

The real-time monitoring of primary biological aerosol particles (PBAP) such as pollen and fungal spores has received much attention in recent years as a result of their health and climatic effects. In this study, the Wideband Integrated Bioaerosol Sensor (WIBS) 4+ model was evaluated for its ability to sample and detect ambient fungal spore and pollen concentrations, compared to the traditional Hirst volumetric method. Although the determination of total pollen and fungal spore ambient concentrations are of interest, the selective detection of individual pollen/fungal spore types are often of greater allergenic/agricultural concern. To aid in this endeavour, modifications were made to the WIBS-4 instrument to target chlorophyll fluorescence. Two additional fluorescence channels (FL4 and FL5 channels) were combined with the standard WIBS channels (FL1, FL2, FL3). The purpose of this modification is to help discriminate between grass and herb pollen from other pollen. The WIBS-4+ was able to successfully detect and differentiate between different bioaerosol classes. The addition of the FL4 and FL5 channels also allowed for the improved differentiation between tree (R² = 0.8), herbaceous (R² = 0.6) and grass (R² = 0.4) pollen and fungal spores (R² = 0.8). Both grass and herbaceous pollen types showed a high correlation with D type particles, showing strong fluorescence in the FL4 channel. The additional fluorescent data that were introduced also improved clustering attempts, making k-means clustering a comparable solution for this high-resolution data.

Respiratory allergies triggered by pollen allergens represent a significant health concern to the Irish public. Up to now, Ireland has largely refrained from participating in long-term aerobiological studies. Recently, pollen monitoring has commenced in several sampling locations around Ireland. The first results of the pollen monitoring campaigns for Dublin (urban) and Carlow (rural) concerning the period 2017–2019 and 2018–2019, respectively, are presented herein. Additional unpublished pollen data from 1978–1980 and, 2010–2011 were also incorporated in creating the first pollen calendar for Dublin. During the monitoring period over 60 pollen types were identified with an average Annual Pollen Integral (APIn) of 32,217 Pollen × day/m³ for Dublin and 78,411 Pollen × day/m³ for Carlow. The most prevalent pollen types in Dublin were: Poaceae (32%), Urticaceae (29%), Cupressaceae/Taxaceae (11%), Betula (10%), Quercus (4%), Pinus (3%), Fraxinus (2%), Alnus (2%) and Platanus (1%). The predominant pollen types in Carlow were identified as Poaceae (70%), Urticaceae (12%), Betula (10%), Quercus (2%), Fraxinus (1%) and Pinus (1%). These prevalent pollen types increased in annual pollen concentration in both locations from 2018 to 2019 except for Fraxinus. Although higher pollen concentrations were observed for the Carlow (rural) site a greater variety of pollen types were identified for the Dublin (urban) site. The general annual trend in the pollen season began with the release of tree pollen in early spring, followed by the release of grass and herbaceous pollen which dominated the summer months with the annual pollen season coming to an end in October. This behaviour was illustrated for 21 different pollen types in the Dublin pollen calendar. The correlation between ambient pollen concentration and meteorological parameters was also examined and differed greatly depending on the location and study year. A striking feature was a substantial fraction of the recorded pollen sampled in Dublin did not correlate with the prevailing wind directions. However, using non-parametric wind regression, specific source regions could be determined such as Alnus originating from the Southeast, Betula originating from the East and Poaceae originating from the Southwest.