Measurement report: Characterization of the vertical distribution of airborne <i>Pinus</i> pollen in the atmosphere with lidar-derived profiles – a modeling case study in the region of Barcelona, NE Spain

This paper investigates the mechanisms involved in the dispersion, structure, and mixing in the vertical column of atmospheric pollen. The methodology used employs observations of pollen concentration obtained from Hirst samplers (we will refer to this as surface pollen) and vertical distribution (polarization-sensitive lidar), as well as nested numerical simulations with an atmospheric transport model and a simplified pollen module developed especially for this study. The study focuses on the predominant pollen type, Pinus, of the intense pollination event which occurred in the region of Barcelona, Catalonia, NE Spain, during 27–31 March 2015. First, conversion formulas are expressed to convert lidar-derived total backscatter coefficient and model-derived mass concentration into pollen grains concentration, the magnitude measured at the surface by means of aerobiological methods, and, for the first time ever, a relationship between optical and mass properties of atmospheric pollen through the estimation of the so-called specific extinction cross section is quantified in ambient conditions. Second, the model horizontal representativeness is assessed through a comparison between nested pollen simulations at 9, 3, and 1 km horizontal resolution and observed meteorological and aerobiological variables at seven sites around Catalonia. Finally, hourly observations of surface and column concentration in Barcelona are analyzed with the different numerical simulations at increasing horizontal resolution and varying sedimentation/deposition parameters. We find that the 9 or 3 km simulations are less sensitive to the meteorology errors; hence, they should be preferred for specific forecasting applications. The largest discrepancies between measured surface (Hirst) and column (lidar) concentrations occur during nighttime, where only residual pollen is detected in the column, whereas it is also present at the surface. The main reason is related to the lidar characteristics which have the lowest useful range bin at ∼ 225 m, above the usually very thin nocturnal stable boundary layer. At the hour of the day of maximum insolation, the pollen layer does not extend up to the top of the planetary boundary layer, according to the observations (lidar), probably because of gravity effects; however, the model simulates the pollen plume up to the top of the planetary boundary layer, resulting in an overestimation of the pollen load. Besides the large size and weight of Pinus grains, sedimentation/deposition processes have only a limited impact on the model vertical concentration in contrast to the emission processes. For further modeling research, emphasis is put on the accurate knowledge of plant/tree spatial distribution, density, and type, as well as on the establishment of reliable phenology functions.

Pollen observations at four EARLINET stations during the ACTRIS-COVID-19 campaign

Lidar observations were analysed to characterize atmospheric pollen at four EARLINET (European Aerosol Research Lidar Network) stations (Hohenpeißenberg, Germany; Kuopio, Finland, Leipzig, Germany; and Warsaw, Poland) during the ACTRIS-COVID-19 campaign in May 2020. The re-analysis lidar data products, after the centralized and automatic data processing with the Single Calculus Chain (SCC), were used in this study, focusing on particle backscatter coefficients at 355 nm and 532 nm, and particle linear depolarization ratios (PDRs) at 532 nm. A novel method for the characterization of the pure pollen depolarization ratio was presented, based on the non-linear least square regression fitting using lidar-derived backscatter-related Ångström exponents (BAEs) and PDRs. Under the assumption that the BAE between 355 and 532 nm should be zero (± 0.5) for pure pollen, the pollen depolarization ratios were estimated: for Kuopio and Warsaw stations, the pollen depolarization ratios at 532 nm were of 0.24 (0.19–0.28) during the birch dominant pollen periods; whereas for Hohenpeiβenberg and Leipzig stations, the pollen depolarization ratios of 0.21 (0.15–0.27) and 0.20 (0.15–0.25) were observed for periods of mixture of birch and grass pollen. The method was also applied for the aerosol classification, using two case examples from the campaign periods: the different pollen types (or pollen mixtures) were identified at Warsaw station, and dust and pollen were classified at Hohenpeißenberg station.

Laboratory evaluation of the scattering matrix of ragweed, ash, birch and pine pollens towards pollen classification

Pollens are nowadays recognized as one of the main atmospheric particles affecting public human health as well as the Earth's climate. In this context, an important issue concerns our ability to detect and differentiate among the existing pollen taxa. In this paper, the potential differences that may exist in light scattering by four of the most common pollen taxa, namely ragweed, birch, pine and ash, are analysed in the framework of the scattering matrix formalism at two wavelengths simultaneously (532 and 1064 nm). Interestingly, our laboratory experimental error bars are precise enough to show that these four pollens, when embedded in ambient air, exhibit different spectral and polarimetric light scattering characteristics, in the form of ten scattering matrix elements (five per wavelength), which allow identifying each separately. To end with, a simpler light scattering criterion is proposed for classifying among the four considered pollens by performing a principal component (PC) analysis, that still accounts for more than 99 % of the observed variance. We thus believe this work may open new insights for future atmospheric pollen detection.

‘Pollen potency’: the relationship between atmospheric pollen counts and allergen exposure

Pollen allergies are responsible for a considerable global public health burden, and understanding exposure is critical to addressing the health impacts. Atmospheric pollen counts are routinely used as a predictor of risk; however, immune responses are triggered by specific proteins known as allergens, which occur both within and on the surface of the pollen grain. The ratio between atmospheric pollen counts and allergen concentrations (‘pollen potency’) has been shown to be inconsistent, with potentially important implications for pollen monitoring practice. Despite this, there has been no previous synthesis of the literature and our understanding of the factors that influence pollen potency remains poor. We conducted a scoping review with the aim of deriving a current understanding of: (a) the factors that influence pollen potency; (b) its variation through time, between taxa and by location; and (c) the implications for pollen monitoring practice. Our synthesis found that pollen potency is highly variable within and between seasons, and between locations; however, much of this variability remains unexplained and has not been deeply investigated. We found no predictable pollen potency patterns relating to taxon, geography or time, and inconclusive evidence regarding possible driving factors. With respect to human health, the studies in our synthesis generally reported larger associations between atmospheric allergen loads and allergy symptoms than whole pollen counts. This suggests that pollen potency influences public health risk; however, the evidence base remains limited. Further research is needed to better understand both pollen potency variability and its implications for health.

Characterization of atmospheric pollen with active remote sensing

Atmospheric pollen is a well-known health threat causing allergy-related diseases. As a biogenic aerosol, pollen also affects the climate by directly absorbing and scattering solar radiation and by acting as cloud condensation or ice nuclei. A good understanding of pollen distribution and transport mechanisms is needed to evaluate the environmental and health impacts of pollen. However, pollen observations are usually performed close to ground and vertical information, which could be used to evaluate and improve pollen transport models, is widely missing. In this thesis, the applicability of lidar measurements to detect pollen in the atmosphere is investigated. For this purpose, measurements of the multiwavelength Raman polarization lidar PollyXT at the rural forest site in Vehmasmäki (Kuopio), Eastern Finland have been utilized. The depolarization ratio was identified to be the most valuable optical property for the detection of atmospheric pollen, as nonspherical pollen like pine and spruce pollen causes high depolarization ratios. However, detected depolarization ratios coincide with typical values for dusty mixtures and additional information such as backward trajectories need to be considered to ensure the absence of other depolarizing aerosols like dust. To separate pollen from background aerosol, a method to estimate the optical properties of pure pollen using lidar measurements was developed. Under the assumption that the Ångström exponent of pure pollen is zero, the depolarization ratio of pure pollen can be estimated. Depolarization ratios for birch and pine pollen at 355 and 532 nm were determined and suggested a wavelength dependence of the depolarization ratio. To further investigate this wavelength dependence, the possibility to use depolarization measurements of Halo Doppler lidars (1565 nm) was explored. In the lower troposphere, Halo Doppler lidars can provide reasonable depolarization values with comparable quality to PollyXT measurements. Finally, measurements of PollyXT and a Halo StreamLine Doppler lidar were used to determine the depolarization ratio at three wavelengths. A wavelength dependence of the particle depolarization ratio with maximum depolarization at 532 nm was found. This could be a characteristic feature of non-spherical pollen and the key to distinguish pollen from other depolarizing aerosol types.

Measurement report: Characterization of the vertical distribution of airborne Pinus pollen in the atmosphere with lidar-derived profiles: a modelling case study in the region of Barcelona, NE Spain

This paper investigates the mechanisms involved in the dispersion, structure and mixing in the vertical column of atmospheric pollen. The methodology used employs observations of pollen concentration obtained from Hirst samplers (we will refer to as surface pollen) and vertical distribution (polarization-sensitive lidar) as well as nested numerical simulations with an atmospheric transport model and a simplified pollen module developed especially for this study. The study focuses on the predominant pollen type, Pinus, of the intense pollination event which occurred in the region of Barcelona, Catalonia, NE Spain, during 27–31 March, 2015. First, conversion formulas are expressed to convert lidar-derived total backscatter coefficient and model-derived mass concentration into pollen grains concentration, the magnitude measured at the surface by means of aerobiological methods, and for the first time ever, a relationship between optical and mass properties of atmospheric pollen, through the estimation of the so-called specific extinction cross-section, is quantified in ambient conditions. Second, the model horizontal representativeness is assessed through comparison between nested pollen simulations at 9, 3 and 1 km horizontal resolution and observed meteorological and aerobiological variables at seven sites around Catalonia. Finally, hourly observations of surface and column concentration in Barcelona are analysed with the different numerical simulations at increasing horizontal resolution and varying sedimentation/deposition parameters. We find that the 9 or 3 km simulations are less sensitive to the meteorology errors hence they should be preferred for specific forecasting applications. The largest discrepancies between measured surface (Hirst) and column (lidar) concentrations occur during nighttime: only residual pollen is detected in the column whereas it is present at the surface. The main reason is related to the lidar characteristics which has a lowest useful range bin at ~225 m, above the usually very thin nocturnal stable boundary layer. At the hour of the day of maximum insolation, the pollen layer does not extend up to the top of the planetary boundary layer according to the observations (lidar), probably because of gravity effects; however, the model simulates the pollen plume up to the top of the planetary boundary layer, resulting in an overestimation of the pollen load. Besides the large size and weight of Pinus grains, sedimentation/deposition processes have only a limited impact on the model vertical concentration in contrast to the emission processes. For further modelling research, emphasis is put on the accurate knowledge of plant/tree spatial distribution, density and type, as well as on the establishment of reliable phenology functions.

Lidar depolarization ratio of atmospheric pollen at multiple wavelengths

Lidar observations during the pollen season 2019 at the European Aerosol Research Lidar Network (EARLINET) station in Kuopio, Finland, were analyzed in order to optically characterize atmospheric pollen. Pollen concentration and type information were obtained by a Hirst-type volumetric air sampler. Previous studies showed the detectability of non-spherical pollen using depolarization ratio measurements. We present lidar depolarization ratio measurements at three wavelengths of atmospheric pollen in ambient conditions. In addition to the depolarization ratio detected with the multiwavelength Raman polarization lidar PollyXT at 355 and 532 nm, depolarization measurements of a co-located Halo Doppler lidar at 1565 nm were utilized. During a 4 d period of high birch (Betula) and spruce (Picea abies) pollen concentrations, unusually high depolarization ratios were observed within the boundary layer. Detected layers were investigated regarding the share of spruce pollen to the total pollen number concentration. Daily mean linear particle depolarization ratios of the pollen layers on the day with the highest spruce pollen share are 0.10 ± 0.02, 0.38 ± 0.23 and 0.29 ± 0.10 at 355, 532 and 1565 nm, respectively, whereas on days with lower spruce pollen share, depolarization ratios are lower with less wavelength dependence. This spectral dependence of the depolarization ratios could be indicative of big, non-spherical spruce pollen. The depolarization ratio of pollen particles was investigated by applying a newly developed method and assuming a backscatter-related Ångström exponent of zero. Depolarization ratios of 0.44 and 0.16 at 532 and 355 nm for the birch and spruce pollen mixture were determined.

Lidar Depolarization Ratio of Atmospheric Pollen at Multiple Wavelengths

Lidar observations during the pollen season 2019 at the European Aerosol Research Lidar Network (EARLINET) station in Kuopio, Finland were analyzed in order to optically characterize atmospheric pollen. Previous studies showed the detectability of non-spherical pollen using depolarization ratio measurements. We present lidar depolarization ratio measurements at three wavelengths of atmospheric pollen in ambient conditions. In addition to the depolarization ratio detected with the multiwavelength Raman polarization lidar PollyXT at 355 and 532 nm, depolarization measurements of a co-located HALO Photonics Streamline Doppler lidar at 1565 nm were utilized. During a four days period of high birch (Betula) and spruce (Picea abies) pollen concentrations, unusually high depolarization ratios were observed within the boundary layer. Detected layers were investigated regarding the share of spruce pollen to the total pollen number concentration. Daily mean particle depolarization ratios of the pollen layers on the day with the highest spruce pollen share are 0.10 ± 0.02, 0.38 ± 0.23 and 0.29 ± 0.10 at 355, 532 and 1565 nm, respectively. Whereas on days with lower spruce pollen share, depolarization ratios are lower with less wavelength dependence. This spectral dependence of the depolarization ratios could be indicative of big, non-spherical spruce pollen. The depolarization ratio of pollen particles was investigated by applying a newly developed method and assuming a backscatter-related Ångström exponent of zero. Depolarization ratios of 0.44 and 0.16 at 532 and 355 nm for the birch and spruce pollen mixture were determined.