Ecoregionalization is the process by which a territory is classified in similar areas according to specific environmental and climatic factors. The climate and the environment strongly influence the presence and distribution of vectors responsible for significant human and animal diseases worldwide. In this paper, we developed a map of the eco-climatic regions of Italy adopting a data-driven spatial clustering approach using recent and detailed spatial data on climatic and environmental factors. We selected seven variables, relevant for a broad set of human and animal vector-borne diseases (VBDs): standard deviation of altitude, mean daytime land surface temperature, mean amplitude and peak timing of the annual cycle of land surface temperature, mean and amplitude of the annual cycle of greenness value, and daily mean amount of rainfall. Principal Component Analysis followed by multivariate geographic clustering using the k-medoids technique were used to group the pixels with similar characteristics into different ecoregions, and at different spatial resolutions (250 m, 1 km and 2 km). We showed that the spatial structure of ecoregions is generally maintained at different spatial resolutions and we compared the resulting ecoregion maps with two datasets related to Bluetongue vectors and West Nile Disease (WND) outbreaks in Italy. The known characteristics of Culicoides imicola habitat were well captured by 2/22 specific ecoregions (at 250 m resolution). Culicoides obsoletus/scoticus occupy all sampled ecoregions, according to its known widespread distribution across the peninsula. WND outbreak locations strongly cluster in 4/22 ecoregions, dominated by human influenced landscape, with intense cultivations and complex irrigation network. This approach could be a supportive tool in case of VBDs, defining pixel-based areas that are conducive environment for VBD spread, indicating where surveillance and prevention measures could be prioritized in Italy. Also, ecoregions suitable to specific VBDs vectors could inform entomological surveillance strategies.

Abstract. The meso-scale chemistry-transport model CHIMERE is used to assess our understanding of major sources and formation processes leading to a fairly large amount of organic aerosols (OA, including primary OA (POA) and secondary OA (SOA)) observed in Mexico City during the MILAGRO field project (March 2006). Chemical analyses of submicron aerosols from aerosol mass spectrometers (AMS) indicate that organic particles found in the Mexico City basin contain a large fraction of oxygenated organic species (OOA) which have strong correspondence with SOA, and that their production actively continues downwind of the city. The SOA formation is modeled here by the one-step oxidation of anthropogenic (i.e. aromatics, alkanes), biogenic (i.e. monoterpenes and isoprene), and biomass-burning SOA precursors and their partitioning into both organic and aqueous phases. The near-surface model evaluation shows that predicted OA correlates reasonably well with measurements during the campaign, however it remains a factor of 2 lower than the measured total OA. Fairly good agreement is found between predicted and observed POA within the city suggesting that anthropogenic and biomass burning emissions are reasonably captured. Consistent with previous studies in Mexico City, large discrepancies are encountered for SOA, with a factor of 2–10 model underestimate. When only anthropogenic SOA precursors were considered, the model was able to reproduce within a factor of two the sharp increase in SOA concentrations during the late morning at both urban and near-urban locations but the discrepancy increases rapidly later in the day, consistent with previous results, and is especially obvious when the column-integrated SOA mass is considered instead of the surface concentration. The increase in the missing SOA mass in the afternoon coincides with the sharp drop in POA suggesting a tendency of the model to excessively evaporate the freshly formed SOA. Predicted SOA concentrations in our base case were extremely low when photochemistry was not active, especially overnight, as the SOA formed in the previous day was mostly quickly advected away from the basin. These nighttime discrepancies were not significantly reduced when greatly enhanced partitioning to the aerosol phase was assumed. Model sensitivity results suggest that observed nighttime SOA concentrations are strongly influenced by a regional background SOA (~1.5 μg/m3) of biogenic origin which is transported from the coastal mountain ranges into the Mexico City basin. The relative contribution of biogenic SOA to monthly mean modeled SOA levels is estimated to be more than 30% within the city and up to 65–90% at the regional scale (even in the immediate vicinity of the city) which may help explain the significant amount of modern carbon in the aerosols inside the city during low biomass burning periods. The anthropogenic emissions of isoprene and its nighttime oxidation by NO3 were also found to enhance the SOA mean concentrations within the city by an additional 15%. Our results confirm the large underestimation of the SOA production by traditional models in polluted regions (estimated as 10–20 Tons within the Mexico City metropolitan area during the daily peak), and emphasize for the first time the role of biogenic precursors in this region, indicating that they cannot be neglected in modeling studies.

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Anemophilous pollen is one of the main causes of allergy by sensitive subjects. Due to the early and prolonged pollen season due to climate change, there is a potentially increasing risk for the European population (Lake et al., 2017). In this work, pollen and meteorological data have been associated in order to identify the favourable conditions for increasing pollen concentration. We use of the classification software from the COST733 action to classify each day of the studied period (2016-2018) among nine weather regimes. The use of a Performance Index (PI) made it possible to relate the pollen concentration to the synoptic classes and thus to associate a higher pollen concentration to a high-pressure condition. In addition, by combining wind roses and a detailed land cover thematic map, we identify the location of main potential pollen sources. The results encourage further analysis of pollen dispersal in response to climate change.

The year 2015 is considered the hottest on records at the global scale, since reliable temperature measurements are available. Ambient air quality is strongly influenced by meteorological conditions, and daytime surface ozone concentrations are generally positively correlated with temperatures. We thus analysed 2015 ozone data over Italy to check if exceptional ozone values reflected the exceptional temperatures. To this end, we evaluated the ozone season in 2015 compared to the 2002-2015 trend, using data from 24 selected monitoring stations and analyzing the exceedances of limit values imposed by the European directive. We found that 2015 was one of the hottest years over Italy, and the ozone season was one of the most severe in the last ten years. In 2015, the average duration of ozone episodes (the number of consecutive days with daily maximum 8-hour-average values higher than the threshold of 120 µg•m −3) was about 4 days, similar to that of 2006 and less than that of 2003 which was about 5 days. This duration is longer than the average observed in recent years, which is less than 3 days. Furthermore, the mean maximum concentration of ozone events was the second on record together with 2006, after the notable heatwave of 2003.