This work deals with the analysis of different filter sampling methods to obtain INP concentration spectra using the GRAnada Ice Nuclei Spectrometer (GRAINS), a droplet freezing array based on the design of the Colorado State University Ice Spectrometer (CSU-IS) but with droplet volumes of 100 & micro;L. GRAINS was first validated with NX Illite, showing spectra consistent with literature, and also compared with FrESH (Freezing Experiment Setup Helsinki), INSEKT (Ice Nucleation Spectrometer of the Karlsruhe Institute of Technology), and PINE (Portable Ice Nucleation Experiment) for aerosol standards as well as ambient samples, with results generally within confidence intervals or a factor of 5. To assess the filter sampling methods, we simultaneously sampled ambient aerosol on polycarbonate filters (commonly used for INP analysis) and microfiber quartz filters (used for chemical analysis) over three months, with 27 filters of each type. Three analysis approaches were tested: washing the polycarbonate filters (Polycarbonate method), randomly punching the quartz filters (Quartz 96-punch method), and washing a larger punch of the quartz filter (Quartz punch washed method). Our results showed a good performance of the three methods, obtaining similar results for the INP concentrations, with approximately 89 % of the data within a factor of 5. Differences between methods become more evident at lower temperatures, with higher INP concentrations detected with both Quartz methods compared to the Polycarbonate method, which could be related to the particle extraction efficiency of this method. Differences between the three methods varied depending on the sample, with general good agreement for polluted and background conditions and different levels of agreement for dust particles. Still, there is a clear correlation between the three methods, with Spearman's coefficients of around 0.9 (p<0.05). The Quartz punch washed method allows to perform sample dilutions similar to the Polycarbonate method, making it a potential alternative to the Quartz 96-punch method for analyzing INP concentrations using quartz filters.

During the first half of the year 2020 because of the appearance of coronavirus SARS-CoV-2 and its associate illness “coronavirus disease 2019” (COVID-19) lockdown measures were adopted in Spain producing an exceptional situation in air pollutant emission scenarios due to a sharp decrease in road traffic and industrial activity. The main atmospheric effect related to the lockdown measures analyzed in this research, with the help of the GAME code, is the aerosol direct radiative forcing. The analysis presented in this study is based on the estimation of aerosol radiative forcing before and during the lockdown in Spain, using data from 6 stations scattered across the Iberian Peninsula that belong to the ICENET network and present very different climatic characteristics. As preliminary results, some statistically significant variations have been found between the radiative forcing before and during the lockdown both in the SW and in the LW components.

This work investigates scattering matrix elements during different Saharan dust outbreaks over Granada (southeast Spain) in 2022 using a polarized imaging nephelometer (PI-Neph) capable of measuring continuously the phase function (F-11) and the polarized phase function () at three different wavelengths (405, 515 and 660 nm) in the range 5-175 degrees. The focus is on two extreme dust events (PM10 > 1000 mu g m(-3)) in March 2022. During the peaks of these events F-11 and show the classical patterns observed for dust samples in laboratory measurements available in the Granada-Amsterdam Light Scattering Database at all wavelengths. However, for the moments prior to and after the peaks the results reveal important sensitivity in at 405 nm. For the other wavelengths, however, this difference in is not evident. Moreover, no remarkable changes are found in F-11, which is always characterized by strong predominance of forward scattering. The analyses of more frequent and moderate events recorded in summer 2022 (PM10 between 50 and 100 mu g m(-3)) revealed F-11 and patterns like those observed prior to and after the extreme events. The combination of PI-Neph measurements with additional in situ instrumentation allowed a typing classification that revealed the peaks in the extreme dust events as pure dust, while for the rest of cases it remarked a mixture of dust with urban background pollution. In addition, simulations with the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) code explain the different patterns in , with changes in the refractive indexes and with the different contributions of the fine and coarse mode.

This work deals with the set up and optimization of a commercial multiwavelength polarized imaging nephelometer (PI-Neph, Airphoton PIN100) designed to measure F-11 (phase function) and-F-12/F-11 (polarized phase function) from ambient aerosol samples. Such measurements are critical for the success of upcoming satellite missions based on polarimetry measurements because they will support and validate retrieval techniques. The main novelty of the instrument with respect to previous versions consists of using only one beam instead of a mirror system to fold it, avoiding internal reflections of light and loss of energy within the laser beam. The instrument also includes the automatization of the imaging technique that makes possible continuous measurements in near real time of the aerosol phase functions at different states of linear polarization directly from ambient air. Laser emits at three different wavelengths (405, 515 and 660 nm) and the beam goes through a wire grid polarizer for linearly polarizing the light, followed by two liquid crystal retarders that control the state of linear polarization. The detector is a CMOS camera perpendicular to the beam which allows to obtain final phase functions in the range 5-175 (losses of some angles by physical limitations and stray light). The calibration of the instrument is discussed and includes geometric calibration (to account for different light paths to the camera) plus absolute calibration (to obtain physical units). Temporal stability of calibrations is observed, and different data quality tests are presented in order to obtain reliable values of F-11 and -F-12/F-11. For an automatic operation of the instrument that permits real time phase matrix measurements, a data quality check algorithm that avoids non-physical measurements and filters outliers has been developed. Validation of the scattering matrix elements based on monodisperse aerosol measurements is also done with polystyrene latex spheres (PSL), showing good agreement with Mie theory. Finally, first results of the instrument operating at the University of Granada (UGR) station from the Andalusian Global ObseRvatory of the Atmosphere (AGORA) since April 2022 are presented. Very good agreements of the integrated scattering coefficients with an integrating nephelometer (TSI, model 3563) were obtained with high correlation coefficients for the three wavelengths (R-2 > 0.81). The calculated root -mean-square error (RMSE) reveals that the performance of the PI-Neph in the measurement of the scattering coefficient is better in the 660 nm and 515 nm wavelengths than in the 405 nm one, although differences between datasets are still low. The observed differences in phase functions and especially polarized phase functions (both in shape and spectral differences) under changing atmospheric scenarios (Saharan dust, pollution and background aerosol conditions) indicated that these variables are sensitive and reliable to classify the type of ambient aerosol. Particularly, the combined measurements of F-11 and-F-12/F-11 shows a unique potential of the PI-Neph for aerosol typology.

Remote sensing techniques are essential to monitor and characterise atmospheric aerosol. On the one hand, ceilometers have been proved to be an effective tool for detection and monitoring not only clouds, but also aerosol particle. In recent years, the developments of automatic lidars and ceilometers with profiling capabilities as well as advances in the calibration techniques related to such devices offer the capacity of characterizing optical properties such as aerosol backscatter coefficient. On the other hand, sun-photometers are a commonly employed instrument to monitor integrated products. GRASPpac is a new retrieval algorithm which is gaining relevance in recent years using the synergy between both instruments to obtain aerosol vertical profiling and microphysical properties (Román et al., 2018).This study presents the comparison of vertical aerosol backscattering coefficient (βaer) profiles obtained by GRASPpac retrieval from the synergy between the CHM15K (Lufft, Germany) ceilometer and the sun-photometer CE318-T (Cimel, France). In this way a comparison with Klett inversion (backward and forward) method using CHM15K ceilometer data is carried out. Forward retrieval is based on E-PROFILE calibration (Weigner and Geiß, 2012). A total of 48 βaer profiles measured during daytime at the aeroogical station of MeteoSwiss at Payerne (Switzerland) between 2017 and 2019 were used for this comparison.GRASPpac profiles are provided in a logarithmic vertical scale. The Klett ceilometer profiles were interpolated. The same GRASPpac height grid to enable a valid comparison. Moreover, the ceilometer signal was averaged in 30-minute bins to match GRASPpac time resolution. After all the corrections were applied, a statistical analysis was conducted to validate the profiles. This work was supported by Grant PID2021- 128008OB-I00 funded by MCIN/AEI/10.13039/501100011033/ FEDER "A way of making Europe", and the project AEROMOST (ProExcel_00204) by the Junta de Andalucía. Francisco Navas-Guzmán received funding from the Ramón y Cajal program (ref. RYC2019-027519-I) of the Spanish Ministry of Science and Innovation.Román, R., et al. (2018): Retrieval of aerosol profiles combining sunphotometer and ceilometer measurements in GRASP code, Atmos. Res., 204, 161-177.Wiegner, M. and Geiß, A. (2012): Aerosol profiling with the Jenoptik ceilometer CHM15kx, Atmos. Meas. Tech., 5, 1953–1964.

The south-central interior of Andalusia experiences intricate precipitation patterns as a result of its semi-arid Mediterranean climate and the impact of Saharan dust and human-made pollutants. The primary aim of this study is to monitor the inter-relations between various factors, such as aerosols, clouds, and meteorological variables, and precipitation systems in Granada using ground-based remote sensing and in situ instruments including a microwave radiometer, ceilometer, cloud radar, nephelometer, and weather station. Over an 11-year period, we detected rain events using a physical retrieval method that employed microwave radiometer measurements. A composite analysis was applied to them to construct a climatology of the temporal evolution of precipitation. It was found that convective rain is the dominant precipitation type in Granada, accounting for 68 % of the rain events. The height of the cloud base is mainly distributed at an altitude of 2 to 7 km. Integrated water vapor (IWV) and integrated cloud liquid water (ILW) increase rapidly before the onset of rain. Aerosol scattering at the surface level and hence the aerosol concentration are reduced during rain, and the predominant mean size distribution of aerosol particles before, during, and after rain is almost the same. A meteorological environment favorable for virga formation is observed in Granada. The surface weather station detected rainfall later than the microwave radiometer, indicating virga according to ceilometer and cloud radar data. We used 889 rain-day events identified by weather station data to determine precipitation intensity classes and found that light rain is the main precipitation intensity class in Granada, accounting for 72 % of the rain-day events. This can be a result of the high tropospheric temperature induced by the Andalusian climate and the reduction of cloud droplet size by the high availability of aerosol particles in the urban atmosphere. This study provides evidence that aerosols, clouds, and meteorological variables have a combined impact on precipitation which can be considered for water resource management and improving rain forecasting accuracy.

This work introduces CAECENET, a new system capable of automatically retrieving columnar and vertically-resolved aerosol properties running the GRASP (Generalized Retrieval of Atmosphere and Surface Properties) algorithm using sun-sky photometer (aerosol optical depth, AOD; and sky radiance measurements) and ceilometer (range corrected signal; RCS) data as input. This method, so called GRASPpac, is implemented in CAECENET, which assimilates sun-sky photometers data from CÆLIS database and ceilometer data from ICENET database (Iberian Ceilometer Network). CAECENET allows for continuous and near-real-time monitoring of both vertical and columnar aerosol properties. The main characteristics and workflow of CAECENET are explained in detail. This work also explores the potential of CAECENET to monitor and analyze the evolution of transported aerosol events on a regional scale by means of the distribution of CAECENET stations across the Iberian Peninsula. As an example, this paper analyzes, using the CAECENET products, the case of a Saharan dust outbreak that occurred between the 3rd and 5th of October 2022. This was an intense event, with AOD at 440 nm values around 0.5 in Madrid and Valladolid, and reaching 1.55 in Granada. Transport from the Canadian wildfires at the end of June 2023 is also studied. Despite the long-range transport of the smoke particles in this event, measured volume concentrations reached and surpassed 80 μm3/cm3 in some stations. The results obtained point to the utility of this CAECENET tool for analyzing changes in the height and speed of the event propagation, in the aerosol concentration, and how this affects the optical properties.

High-altitude remote sites are unique places to study aerosol–cloud interactions, since they are located at the altitude where clouds may form. At these remote sites, organic aerosols (OAs) are the main constituents of the overall aerosol population, playing a crucial role in defining aerosol hygroscopicity (κ). To estimate the cloud condensation nuclei (CCN) budget at OA-dominated sites, it is crucial to accurately characterize OA hygroscopicity (κOA) and how its temporal variability affects the CCN activity of the aerosol population, since κOA is not well established due to the complex nature of ambient OA. In this study, we performed CCN closures at a high-altitude remote site during summer to investigate the role of κOA in predicting CCN concentrations under different atmospheric conditions. In addition, we performed an OA source apportionment using positive matrix factorization (PMF). Three OA factors were identified from the PMF analysis: hydrocarbon-like OA (HOA), less-oxidized oxygenated OA (LO-OOA), and more-oxidized oxygenated OA (MO-OOA), with average contributions of 5 %, 36 %, and 59 % of the total OA, respectively. This result highlights the predominance of secondary organic aerosol (SOA) with a high degree of oxidation at this high-altitude site. To understand the impact of each OA factor on the overall OA hygroscopicity, we defined three κOA schemes that assume different hygroscopicity values for each OA factor. Our results show that the different κOA schemes lead to similar CCN closure results between observations and predictions (slope and correlation ranging between 1.08–1.40 and 0.89–0.94, respectively). However, the predictions were not equally accurate across the day. During the night, CCN predictions underestimated observations by 6 %–16 %, while, during morning and midday hours, when the aerosol was influenced by vertical transport of particles and/or new particle formation events, CCN concentrations were overestimated by 0 %–20 %. To further evaluate the role of κOA in CCN predictions, we established a new OA scheme that uses the OA oxidation level (parameterized by the f44 factor) to calculate κOA and predict CCN. This method also shows a large bias, especially during midday hours (up to 40 %), indicating that diurnal information about the oxygenation degree does not improve CCN predictions. Finally, we used a neural network model with four inputs to predict CCN: N80 (number concentration of particles with diameter > 80 nm), OA fraction, f44, and solar global irradiance. This model matched the observations better than the previous approaches, with a bias within ± 10 % and with no daily variation, reproducing the CCN variability throughout the day. Therefore, neural network models seem to be an appropriate tool to estimate CCN concentrations using ancillary parameters accordingly.

Wind-dispersed pollen grains emitted from vegetation are directly injected into the atmosphere being an important source of natural aerosols globally. These coarse particles of pollen can rupture into smaller particles, known as subpollen particles (SPPs), that may act as cloud condensation nuclei (CCN) and affect the climate. In this study, we characterize and investigate the ability of SPPs of 10 Mediterranean-climate pollen types to activate as CCN. A continuous flow CCN counter (CCNC) was used to measure the activation of size-selected (80, 100 and 200 nm dry mobility diameter) particles at different supersaturations (SS). Hygroscopicity parameter (x) for each SPP type and size has been calculated using x-Ko & BULL;hler theory. Organic chemical speciation and protein content has been determined to further characterize pollen solutions. Furthermore, the surface activity of SPPs has also been investigated by using pendant drop tensiometry. All studied SPP samples show critical supersaturation (SSCrit) values that are atmospherically relevant SS conditions. Hygroscopicity x values are in the range characteristic of organic compounds (0.1-0.3). We found that organic speciation and protein content vary substantially among pollen types, with saccharides and fatty acids being the only organic compounds found in all pollen types. A clear relationship between SPP activation and its organic composition was not observed. This study also reveals that all SPPs investigated reduce the surface tension of water at high concentrations but at diluted concentrations (such as those of activation in the CCNC), the water surface tension value is a good

High-altitude mountain areas are sentinel ecosystems for global environmental changes such as anthropogenic pollution. In this study, we report a source apportionment of particulate material with an aerodynamic diameter smaller than 10 μm (PM10) in a high-altitude site in southern Europe (Sierra Nevada Station; SNS (2500 m a.s.l.)) during summer 2021. The emission sources and atmospheric secondary processes that determine the composition of aerosol particles in Sierra Nevada National Park (Spain) are identified from the concentrations of organic carbon (OC), elemental carbon (EC), 12 major inorganic compounds, 18 trace elements and 44 organic molecular tracer compounds in PM10 filter samples collected during day- and nighttime. The multivariate analysis of the joint dataset resolved five main PM10 sources: 1) Saharan dust, 2) advection from the urbanized valley, 3) local combustion, 4) smoke from a fire-event, and 5) aerosol from regional recirculation with high contribution of particles from secondary inorganic and organic aerosol formation processes. PM sources were clearly associated with synoptic meteorological conditions, and day- and nighttime circulation patterns typical of mountainous areas. Although a local pollution source was identified, the contribution of this source to PM10, OC and EC was small. Our results evidence the strong influence of middle- and long-range transport of aerosols, mainly from anthropogenic origin, on the aerosol chemical composition at this remote site.

Three volcanic plumes were detected during the Tajogaite volcano eruptive activity (Canary Islands, Spain, September-December 2021) over the Iberian Peninsula. The spatiotemporal evolution of these events is char-acterised by combining passive satellite remote sensing and ground-based lidar and sun-photometer systems. The inversion algorithm GRASP is used with a suite of ground-based remote sensing instruments such as lidar/ ceilometer and sun-photometer from eight sites at different locations throughout the Iberian Peninsula. Satellite observations showed that the volcanic ash plumes remained nearby the Canary Islands covering a mean area of 120 & PLUSMN; 202 km2 during the whole period of eruptive activity and that sulphur dioxide plumes reached the Iberian Peninsula. Remote sensing observations showed that the three events were mainly composed of sulphates, which were transported from the volcano into the free troposphere. The high backscatter-related & ANGS;ngstro & BULL;m exponents for wavelengths 532-1064 nm (1.17 & PLUSMN; 0.20 to 1.40 & PLUSMN; 0.24) and low particle depolarization ratios (0.08 & PLUSMN; 0.02 to 0.09 & PLUSMN; 0.02), measured by the multi-wavelength Raman lidar, hinted at the presence of spherical small particles. The layer aerosol optical depth at 532 nm (AODL532) obtained from lidar measurements contributed between 49% and 82% to the AERONET total column AOD at 532 nm in event II (11-13 October). According to the GRASP retrievals, the layer aerosol optical depth at 440 nm (AODL440) was higher in all sites during event II with values between 0.097 (Badajoz) and 0.233 (Guadiana-UGR) and lower in event III (19-21 October) varying between 0.003 (Granada) and 0.026 (& PRIME;Evora). Compared with the GRASP retrievals of total column AOD at 440 nm, the AODL440 had contributions between 21% and 52% during event II. In the event I (25-28 September), the mean volume concentrations (VC) varied between 5 & PLUSMN; 4 & mu;m3cm  3 (El-Arenosillo/Huelva) and 17 & PLUSMN; 10 & mu;m3cm  3 (Guadiana-UGR), while in event II this variation was from 11 & PLUSMN; 7 & mu;m3cm- 3 (Badajoz) to 27 & PLUSMN; 10 & mu;m3cm- 3 (Guadiana-UGR). Due to the impact of volcanic events on atmospheric and economic fields, such as radiative forcing and airspace security, a proper characterization is required. This work undertakes it using advanced instrumentation and methods.

The aerosol radiative effect (ARE) is one of the atmospheric components still affected by large uncertainty. One of the causes is related to the fact that the longwave (LW) component is usually neglected, even though it is necessary for an accurate quantification of the ARE together with the shortwave component (SW). In this study we have developed a methodology based on the GAME (Global Atmospheric Model) radiative transfer model (RTM) that allows to obtain the radiative effect of the atmospheric aerosol for both spectral ranges in an automated way. The microphysical and optical properties necessary to feed the RTM have been obtained through the GRASP (Generalized Retrieval of Aerosol and Surface Properties) algorithm, with the combination of ceilometer and sun-sky photometer data. Data measured in Granada (Spain) during 2017 have been used for the evaluation and implementation of this methodology. According to the results, the ARE in the SW spectral range (ARE SW ) varies between 0 and -50 Wm -2 for most of the data, whereas the ARE in the LW range (ARE LW ) varies between 0 and 5 Wm -2 , at heights near the surface. In general, the obtained results agree with those found in the literature, with negative values in the SW range (cooling effect) and positive values in the LW (heating effect). The seasonal analysis shows that, for both components, the ARE is more important during the spring and summer seasons, when the aerosol load is greater, as expected. The analysis of the heating rate (HR) shows positive values in the SW and negative values in the LW range. The majority of the HR SW data varies between 0 and 1 Kd -1 during the year whereas the HR LW does it between 0 and -0.15 Kd -1 . The seasonal analysis of the HR shows that the greater monthly average values are found during spring, however there is not much variability along the year, with the exception of February, under the effects of an extreme dust intrusion. The mineral dust particles in this event cause an ARE SW of -130 Wm -2 and an ARE LW of 23 Wm -2 (ARE LW /ARE SW = 17%), thus pointing out that the LW component should not be neglected for large particles. Additionally, it is observed that the vertical distribution of the aerosol layers strongly influences the ARE and the HR obtained profiles, affecting the way the atmospheric cooling/heating occurs in the vertical coordinate.

Rainfall prediction is one of the most challenging and uncertain tasks in weather forecasting, which has a significant impact on human society. Detection of heavy rainfall trends may be masked or amplified by natural variability, and numerical weather prediction (NWP) models have difficulty to predict them accurately. Therefore, understanding of rainfall effects with the evolution of atmospheric parameters and seeking atmospheric precursors of rainfall for nowcasting or prediction become an urgent need.To date, most related studies have analyzed only a limited number of rain events or lacked long-term observations. This is likely to have a weak robustness. A multi-instrument and multi-parameter atmospheric monitoring system to detect precipitation precursors can improve the existing nowcasting system. AGORA (Andalusian Global ObseRvatory of the Atmosphere) is an ACTRIS facility located in the southeast of the Iberian Peninsula which offers unique infrastructure for the study of aerosol, clouds and precipitation. AGORA consists of two stations, an urban station located in the city of Granada (680 m asl) and a high-mountain station located in the National Park of Sierra Nevada (2580 m asl), separated by a horizontal distance of 20 km only. This infrastructure comprises state-of-the-art instrumentation covering active and passive remote sensing and in-situ techniques, including lidars, cloud radars, microwave radiometer, and weather stations. These instruments can obtain multiple atmospheric parameters (atmospheric water, aerosol, temperature, wind, etc.), including their vertical profiles.In this study, we investigate the potential of different atmospheric parameters from ground-based microwave radiometer, ceilometer, nephelometer, absorption photometer and weather stations for the nowcasting of rainfall. We use 694 rain events identified by microwave radiometer in the southeast of Iberian Peninsula to identify conditions favorable to trigger rainfall over 10 years, and to analyze how they are related to observed changes in water vapor and aerosol load and properties. The composite analysis is carried out in a long time interval of 8 hours before and 16 hours after rain, with the onset of rain serving as the time marker for this method. The aim of our study is to show the typical behavior of rainfall, to reveal the interaction of rainfall with atmospheric parameters, and to explore the precursors of rainfall.

This study proposes a new methodology to estimate the Atmospheric Boundary Layer Height (ABLH), discriminating between Convective Boundary Layer and Stable Boundary Layer heights, based on the machine learning algorithm known as Gradient Boosting Regression Tree. The algorithm proposed here uses a first estimation of the ABLH derived applying the gradient method to a ceilometer signal and several meteorological variables to obtain ABLH values comparable to those derived from a microwave radiometer. A deep analysis of the model configuration and its inputs has been performed in order to avoid the model overfitting and ensure its applicability. The hourly and seasonal values and variability of the ABLH values obtained with the new algorithm have been analyzed and compared with the initial estimations obtained using only the ceilometer signal. Mean Relative Errors (MRE) between the ABLH estimated with the new algorithm and microwave radiometer show a daily pattern with their highest values during the night-time (stable situations) and their lowest values along the day-time (convective situations). This pattern has been observed for all the seasons with MRE ranging between −5% and 35%. This result notably improves those ABLH values derived by applying the gradient method to ceilometer data during convective situations and enables the Stable Boundary Layer height detection at night and early morning, instead of only Residual Layer top height. Finally, the model performance has been directly validated in three particular cases: clear-sky day, presence of low-clouds and dust outbreak event. In these three particular situations, ABLH values obtained with the new algorithm follow the pattern obtained with the microwave radiometer presenting very similar values, thus confirming the good model performance. In this way it is feasible by the combination of the proposed method with gradient method, to estimate Convective, Stable and Residual Boundary Layer height from ceilometer data and surface meteorological data in extended network that include ceilometer profiling.

The presence of very high pollen levels in the atmosphere is associated with a strong impact on health and a worsening of symptoms in people who already have a respiratory disease. However, there is no specification on the aerobiological, environmental and meteorological factors that allow for characterizing a pollen event as of great magnitude due to the significant impact it can cause on the population and the environment. This work proposes criteria to typify the levels of atmospheric pollen as an extreme pollen event (EPE), and aims to determine the meteorological variables that can affect the presence and permanence of high pollen concentrations over a period of time. To address this goal, the quasi-climatological pollen dataset recorded in Granada (Southeastern Spain) during the period 1992-2019, has been used. On the daily accumulated pollen concentrations, the 95th, 97th and 99th percentiles were calculated. Spearman's correlation between the pollen con-centration exceeding the proposed thresholds (C (> P95), C (> P97), C (> P99)) and surface meteorological variables recorded during up to five days before the event were established in order to identify the meteorological conditions that might affect the EPEs. As for the number of days with values higher than the established percentiles, it has been seen that in the case of total pollen and Olea, Cupressaceae and Pinus, there is a robust monotonically ascending trend throughout the study period. Regarding meteorological variables, relative humidity and 24-h accumulated precipitation are shown as the two most influential variables up to three days before the event, although temperatures, visibility and wind direction also show a correlation with some pollen types. The criteria proposed in this work allow us for classifying high levels of pollen as an EPE, and lay the foundations of these extreme events in a context of climate change in which they will become more frequent.

Pollen grains emitted by urban vegetation are the main primary biological airborne particles (PBAPs) which alter the biological quality of urban air and have a significant impact on human health. This work analyses the interactions which exist between pollen-type PBAPs, meteorological variables, and air pollutants in the urban atmosphere so that the complex relationships and trends in future scenarios of changing environmental conditions can be assessed. For this study, the 1992-2018 pollen data series from the city of Granada (southeast Spain) was used, in which the dynamics of the total pollen as well as the 8 main pollen types (Cupressaceae, Olea, Pinus, Platanus, Poaceae, Populus, Quercus and Urticaceae) were analysed. The trend analysis showed that all except Urticaceae trended upward throughout the series. Spearman's correlations with meteorological variables showed that, in general, the most influential variables on the pollen concentrations were the daily maximum temperature, relative humidity, water vapor pressure, global radiation, and insolation, with different effects on different pollen types. Parallel analysis by neural networks (ANN) confirmed these variables as the predominant ones, especially global radiation. The correlation with atmospheric pollutants revealed that ozone was the pollutant with the highest influence, although some pollen types also showed correlation with NO2, SO2, CO and PM10. The Generalized Linear Models (GLM) between pollen and pollutants also indicated O3 as the most prominent variable. These results highlight the active role that pollen-type PBAPs have on urban air quality by establishing their interactions with meteorological variables and pollutants, thereby providing information on the behaviour of pollen emissions under changing environmental conditions.

Aerosol particles play an important role in physical and chemical processes that occur in the atmosphere. On the one hand, these particles are able to modify atmospheric optical properties, causing a significant impact on Earth’s energy balance, and consequently their presence is fundamental on the global climate. On the other hand, aerosol particles act as cloud condensation nuclei (CCN) and ice nuclei (IN); making them an essential part of the hydrological cycle. Atmospheric aerosols can be grouped into two categories depending on their origin: natural or anthropogenic. In our study, we put the focus on atmospheric aerosols of natural origin, in particular on primary biological aerosol particles (PBAPs) such as pollen and spores. These biogenic particles are released in large quantities from terrestrial vegetation into the atmosphere, where they can be transported up to 100-1000 km. Due to their large size (between 10-100 µm pollen grains and 2-10 µm spores) their residence time in the atmosphere is short. For this reason, they are not climate relevant compared to other components in the atmosphere. However, under moist and high humidity conditions or mechanical processes these biological aerosol particles can break into smaller particles known as sub-pollen particles (SPP) and sub-spores particles (SSP). Each pollen grain can rupture releasing a large quantity of these type of sub-particles (106). Wozniak et al. (2018) estimated that, for clean background conditions, high SPPs concentrations can suppress average seasonal precipitation by 32% and shift rates from heavy to light while increasing dry days. In this study, we have investigated the ability of various pollen and spores types to break into sub-particles and be activated as CCN. To this end we used a CCN counter (CCN-100, DMT) coupled with a Scanning Mobility Particle Sizer (SMPS, TSI) to select SPPs and SSPs of 50, 100 and 200 nm. The results show that not all pollen types have the same activation properties, with critical supersaturations varying between species and particle size. Additionally, SEM images have been performed to confirm the rupture of pollen and spores particles into SPPs and SSPs, respectively. Chemical composition of the different species have been investigated as well. References: Wozniak,M. C., Solmon, F., & Steiner, A. L. (2018). Pollen rupture and its impact on precipitation in clean continental conditions. Geophysical Research Letters, 45, 7156–7164. https://doi.org/10.1029/2018GL077692 Acknowledgments: This work was supported by the Spanish Ministry of Science and Innovation through projects CGL2016-81092-R, CGL2017-90884REDT and RTI2018.101154.A.I00, by Junta de Andalucía, UGR and FEDER funds through project B-RNM-474-UGR18 and B-RNM-496-UGR18 and by University of Granada Plan Propio through Visiting Scholars program. Andrea Casans is funded by MINECO under predoctoral program FPI (PRE2019-090827). Thanks to the NOAA Global Monitoring Laboratory for providing the CCN counter.