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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 1g€¯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 3g€¯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 g1/4g€¯225g€¯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. ; The authors thankfully acknowledge the computer resources at MareNostrum 4 and the technical support provided by BSC (grant nos. RES-AECT-2019-3-0001 and RES-AECT-2020-1-0007). The lidar data analysis has been supported by funding from the H2020 program from the European Union (grant nos. 654109, 778349, and 871115), the Spanish Ministry of Economy, Industry and Competitiveness (grant no. CGL2017-90884-REDT), the Spanish Ministry of Science and Innovation (grant no. PID2019-103886RB-I00), and the Unity of Excellence "María de Maeztu" financed by the Spanish Agencia Estatal de Investigación (grant no. MDM-2016-0600). Modeling activities have been supported by funding from the Ministerio de Ciencia, Innovación y Universidades, as part of the BROWNING project (grant no. RTI2018-099894-BI00) and ACTRIS-España (grant no. CGL2017-90884-REDT). Airborne pollen data sampling and analyzing have been supported by funding from sponsors of the Catalan Aerobiological Network (LETI Pharma, Diputació de Tarragona, Servei Meteorològic de Catalunya, Diputació de Lleida, Sociedad Española de Alergología e Inmunología Clínica (SEAIC), Societat Catalana d'Al⋅lèrgia i Immunologia Clínica (SCAIC), and J Uriach y Compañía, S.A.), and from the Spanish Ministry of Economy, Industry, and Competitiveness (grant nos. CGL2012-39523-C02-01, CTM2017-89565-C2-1-P, and CTM2017-89565-C2-2-P). This work is contributing to the ICTA "Unit of Excellence" (MinECo; grant no. MDM2015-0552).

Pollen allergenicity plays an important role on human health and wellness. It is thus of large public interest to increase our knowledge of pollen grain behavior in the atmosphere (source, emission, processes involved during their transport, etc.) at fine temporal and spatial scales. First simulations with the Barcelona Supercomputing Center NMMB/BSC-CTM model of Platanus and Pinus dispersion in the atmosphere were performed during a 5-day pollination event observed in Barcelona, Spain, between 27 – 31 March, 2015. The simulations are compared to vertical profiles measured with the continuous Barcelona Micro Pulse Lidar system. First results show that the vertical distribution is well reproduced by the model in shape, but not in intensity, the model largely underestimating in the afternoon. Guidelines are proposed to improve the dispersion of airborne pollen by numerical prediction models. ; Lidar data analysis were supported by the ACTRIS (Aerosols, Clouds, and Trace Gases Research Infrastructure Network) Research Infrastructure Project funded by the European Union's Horizon 2020 research and innovation programme under grant agreement n. 654169; by the Spanish Ministry of Economy and Competitivity (project TEC2015-63832-P) and of Science and Innovation (project UNPC10-4E-442) and EFRD (European Fund for Regional Development); by the Department of Economy and Knowledge of the Catalan autonomous government (grant 2014 SGR 583). This work is contributing to the ICTA 'Unit of Excellence' (Spanish Ministry of Economy and Competitivity, project MDM2015-0552). ; Postprint (published version)

Pollen allergenicity plays an important role on human health and wellness. It is thus of large public interest to increase our knowledge of pollen grain behavior in the atmosphere (source, emission, processes involved during their transport, etc.) at fine temporal and spatial scales. First simulations with the Barcelona Supercomputing Center NMMB/BSC-CTM model of Platanus and Pinus dispersion in the atmosphere were performed during a 5-day pollination event observed in Barcelona, Spain, between 27 – 31 March, 2015. The simulations are compared to vertical profiles measured with the continuous Barcelona Micro Pulse Lidar system. First results show that the vertical distribution is well reproduced by the model in shape, but not in intensity, the model largely underestimating in the afternoon. Guidelines are proposed to improve the dispersion of airborne pollen by numerical prediction models. ; Lidar data analysis were supported by the ACTRIS (Aerosols, Clouds, and Trace Gases Research Infrastructure Network) Research Infrastructure Project funded by the European Union's Horizon 2020 research and innovation programme under grant agreement n. 654169; by the Spanish Ministry of Economy and Competitivity (project TEC2015-63832-P) and of Science and Innovation (project UNPC10-4E-442) and EFRD (European Fund for Regional Development); by the Department of Economy and Knowledge of the Catalan autonomous government (grant 2014 SGR 583). This work is contributing to the ICTA 'Unit of Excellence' (Spanish Ministry of Economy and Competitivity, project MDM2015-0552). ; Postprint (published version)

The authors wish to thank to different projects and entities for financing this study: COST ES0603 EUPOL; Laboratorios LETI S.A.; Proyecto EOLO-PAT; European Commission for «ENV4-CT98-0755»; Spanish Ministry of Science and Technology I+D+I for «AMB97-0457-CO7-021», «REN2001-10659-CO3-01», «BOS2002-03474», «CGL2004-21166-E», «CGL2005-07543/CLI», «CGL2009-11205» and CONSOLIDER CSD2007_00067 GRACCIE; Andalusian Government for «RNM-5058»; and Catalan Government AGAUR for «2002SGR00059», «2005SGR00519» and «2009SGR1102».

The use of Land use and Land cover (LULC) data is gradually becoming more widely spread in studies relating the environment to human health. However, little research has acknowledged the compositional nature of these data. The goal of the present study is to explore, for the first time, the independent effect of eight LULC categories (agricultural land, bare land, coniferous forest, broad-leaved forest, sclerophyll forest, grassland and shrubs urban areas, and waterbodies) on three selected common health conditions: type 2 diabetes mellitus (T2DM), asthma and anxiety, using a compositional methodological approach and leveraging observational health data of Catalonia (Spain) at area level. We fixed the risk exposure scenario using three covariates (socioeconomic status, age group, and sex). Then, we assessed the independent effect of the eight LULC categories on each health condition. Our results show that each LULC category has a distinctive effect on the three health conditions and that the three covariates clearly modify this effect. ; Quim Zaldo-Aubanell was supported by AGAUR FI fellowship (DOGC num. 7720, of 5.10.2018). Isabel Serra acknowledges support from FIS2015-71851-P and PGC-FIS2018-099629-B-I00 from Spanish MINECO and MICINN, and was partially funded by the grant RTI2018- 096072-B-I00 from the Spanish Ministry of Science, Innovation and Universities. Jordina Belmonte was supported by the Spanish Ministry of Science and Technology through the project CTM2017-86565-C2-1-O and by the Catalan Government AGAUR through 2017SGR1692. Pepus Daunis-i-Estadella acknowledges support from the project RTI2018- 095518-B-C21 Methods for Compositional analysis of Data (CODAMET), Ministerio de Ciencia, Innovación y Universidades, Spain.

The use of Land use and Land cover (LULC) data is gradually becoming more widely spread in studies relating the environment to human health. However, little research has acknowledged the compositional nature of these data. The goal of the present study is to explore, for the first time, the independent effect of eight LULC categories (agricultural land, bare land, coniferous forest, broad-leaved forest, sclerophyll forest, grassland and shrubs, urban areas, and waterbodies) on three selected common health conditions: type 2 diabetes mellitus (T2DM), asthma and anxiety, using a compositional methodological approach and leveraging observational health data of Catalonia (Spain) at area level. We fixed the risk exposure scenario using three covariates (socioeconomic status, age group, and sex). Then, we assessed the independent effect of the eight LULC categories on each health condition. Our results show that each LULC category has a distinctive effect on the three health conditions and that the three covariates clearly modify this effect. This compositional approach has yielded plausible results supported by the existing literature, highlighting the relevance of environmental heterogeneity in health studies. In this sense, we argue that different types of environment possess exclusive biotic and abiotic elements affecting distinctively on human health. We believe our contribution might help researchers approach the environment in a more multidimensional manner integrating environmental heterogeneity in the analysis. ; Quim Zaldo-Aubanell was supported by AGAUR FI fellowship (DOGC num. 7720, of 5.10.2018). Isabel Serra acknowledges support from FIS2015-71851-P and PGC-FIS2018-099629-B-I00 from Spanish MINECO and MICINN, and was partially funded by the grant RTI2018-096072-B-I00 from the Spanish Ministry of Science, Innovation and Universities. Jordina Belmonte was supported by the Spanish Ministry of Science and Technology through the project CTM2017-86565-C2-1-O and by the Catalan Government AGAUR through 2017SGR1692. Pepus Daunis-i-Estadella acknowledges support from the project RTI2018-095518-B-C21 Methods for Compositional analysis of Data (CODAMET), Ministerio de Ciencia, Innovación y Universidades, Spain. The funding sources did not participate in the design or conduct of the study, the collection, management, analysis, or interpretation of the data, or the preparation, review, or approval of the manuscript. We want to thank Marcel Bach-Pagès for his insights in the manuscript. ; Peer Reviewed ; Postprint (published version)