Identifying key environmental factors to model Alt a 1 airborne allergen presence and variation.

Fungal spores, commonly found in the atmosphere, can trigger important respiratory disorders. The glycoprotein Alt a 1 is the major allergen present in conidia of the genus Alternaria and has a high clinical relevance for people sensitized to fungi. Exposure to this allergen has been traditionally assessed by aerobiological spore counts, although this does not always offer an accurate estimate of airborne allergen load. This study aims to pinpoint the key factors that explain the presence and variation of Alt a 1 concentration in the atmosphere in order to establish exposure risk periods and improve forecasting models. Alternaria spores were sampled using a Hirst-type volumetric sampler over a five-year period. The allergenic fraction from the bioaerosol was collected using a low-volume cyclone sampler and Alt a 1 quantified by Enzyme-Linked ImmunoSorbent Assay. A cluster analysis was executed in order to group days with similar environmental features and then analyze days with the presence of the allergen in each of them. Subsequently, a quadratic discriminant analysis was performed to evaluate if the selected variables can predict days with high Alt a 1 load. The results indicate that higher temperatures and absolute humidity favor the presence of Alt a 1 in the atmosphere, while time of precipitation is related to days without allergen. Moreover, using the selected parameters, the quadratic discriminant analysis to predict days with allergen showed an accuracy rate between 67 % and 85 %. The mismatch between daily airborne concentration of Alternaria spores and allergen load can be explained by the greater contribution of medium-to-long distance transport of the allergen from the major emission sources as compared with spores. Results highlight the importance of conducting aeroallergen quantification studies together with spore counts to improve the forecasting models of allergy risk, especially for fungal spores.

Indoor PM from residential coal combustion: Levels, chemical composition, and toxicity.

Indoor air quality is crucial for human health due to the significant time people spend at home, and it is mainly affected by internal sources such as solid fuel combustion for heating. This study investigated the indoor air quality and health implications associated with residential coal burning covering gaseous pollutants (CO, CO2 and total volatile organic compounds), particulate matter, and toxicity. The PM10 chemical composition was obtained by ICP-MS/OES (elements), ion chromatography (water-soluble ions) and thermal-optical analysis (organic and elemental carbon). During coal combustion, PM10 levels were higher (up to 8.8 times) than background levels and the indoor-to-outdoor ratios were, on average, greater than unity, confirming the existence of a significant indoor source. The chemical characterisation of PM10 revealed increased concentrations of organic carbon and elemental carbon during coal combustion as well as arsenic, cadmium and lead. Carcinogenic risks associated with exposure to arsenic exceeded safety thresholds. Indoor air quality fluctuated during the study, with varying toxicity levels assessed using the Aliivibrio fischeri bioluminescence inhibition assay. These findings underscore the importance of mitigating indoor air pollution associated with coal burning and highlight the potential health risks from long-term exposure. Effective interventions are needed to improve indoor air quality and reduce health risks in coal-burning households.

Connection between Weather Types and Air Pollution Levels: A 19-Year Study in Nine EMEP Stations in Spain.

This study focuses on the analysis of the distribution, both spatial and temporal, of the PM10 (particulate matter with a diameter of 10 µm or less) concentrations recorded in nine EMEP (European Monitoring and Evaluation Programme) background stations distributed throughout mainland Spain between 2001 and 2019. A study of hierarchical clusters was used to classify the stations into three main groups with similarities in yearly concentrations: GC (coastal location), GNC (north-central location), and GSE (southeastern location). The highest PM10 concentrations were registered in summer. Annual evolution showed statistically significant decreasing trends in PM10 concentration in all the stations covering a range from -0.21 to -0.50 µg m-3/year for Barcarrota and Víznar, respectively. Through the Lamb classification, the weather types were defined during the study period, and those associated with high levels of pollution were identified. Finally, the values exceeding the limits established by the legislation were analyzed for every station assessed in the study.

Towards a model of wet deposition of bioaerosols: The raindrop size role.

Bioaerosols play a major role in the plant life of ecosystems. In addition, they have a profound impact on human health, since they may cause lung diseases or allergies. The key objective of this study is to assess the below cloud scavenging effect of rainfall on pollen concentration. The analysis is based on a sampling carried out in León, Spain, between 2015 and 2018. The rainfall variables and the pollen concentrations have been obtained with a disdrometer and a volumetric Hirst type spore-trap, respectively. In order to evaluate the scavenging, three parameters have been calculated: scavenging efficiency (through the concentration-weighted average (%ΔC)), the scavenging coefficient (λ) and the percentage of events with a decrease in pollen concentration (%ES) also called events with effective scavenging. 71% of rain events presented an effective scavenging that affected all types of pollen. The %ΔC mean value of total pollen was 24 ± 18% (positive values indicate an effective scavenging) and the types of pollen with the highest values were Castanea and Cupressaceae (71 and 40%, respectively). A linear model (R2 = 0.94) to estimate the pollen concentration after rain was built with variables such as pollen concentration before rain and other variables from a weather station and a disdrometer. Furthermore, we have shown the possibility of knowing in real time the probable Cupressaceae pollen concentration, from the initial pollen concentration and the physical parameters of rain (such as raindrop size, rain intensity or volume swept by raindrops in their falling path).

Towards a model for aerosol removal by rain scavenging: The role of physical-chemical characteristics of raindrops.

A one-year study was carried out in León, Spain, in order to characterize physically and chemically the precipitation. With the aim of studying the scavenging process of atmospheric pollutants, scavenging ratio and removal coefficients were calculated through physical parameters of raindrops (obtained by disdrometer data) and through chemical properties of aerosols. Finally, linear models for the prediction of the chemical composition of rainwater and the efficiency of the removal effect were established. In general, the rainwater was dominated by NH4+ > SO42- > NO3- in all seasons. Higher ion concentrations and conductivity and lowest pH were observed in summer, due to the low volume of rain. In winter, the high values of Na+ and Cl- in the rainwater showed the contribution from marine sources, while in summer the high concentrations of Ca2+, Mg2+, SO42-, NH4+ and NO3- reflected the contribution from both crustal and anthropogenic sources. The linear models revealed that the amount of dissolved organic carbon and of the water-soluble ions in rain samples, Ca2+, SO42-, NO3-, increases with the volume swept by the falling drops. Insoluble carbon fraction has a negative dependence with the volume swept and positive with the diameter of the raindrop. Removal coefficients are affected by the concentration in the air of each species before precipitation, the duration of the event and the time elapsed between two precipitation events.

Characterization of aerosol sources in León (Spain) using Positive Matrix Factorization and weather types.

A one-year aerosol sampling campaign, between 2016 and 2017, was conducted in a suburban area of León city, Spain. An association between the Positive Matrix Factorization (PMF) results and air masses through circulation weather types was carried out, through the construction of linear models from the PM10 concentrations and its chemical composition. The aerosol sources, identified by PMF six-factor solution, were: traffic (29%), aged sea salt (26%), secondary aerosols (16%), dust (13%), marine aerosol (7%) and biomass burning (3%). Traffic and secondary factors showed the highest PM10 contribution in the hybrid cyclonic types with wind component from the first and second quadrant. Anticyclonic types with wind component from the first quadrant exhibited high values of secondary, aged sea salt and dust factors. The highest contributions of the dust factor were also associated with northerly types. The linear models built for estimating the source apportionment of PM10, from aerosol chemical composition and geostrophic flow, showed positive coefficients for: westerly flows (WF) in marine factor, southerly flows (SF) in secondary and traffic factors, and shear southerly vorticities (ZS) in dust factor. Negative dependences were observed for ZS in aged sea salt factor and for SF in dust factor. The PM10 mass concentration calculated by the linear models and by the PMF model were strongly correlated. This can be very useful to determine the contribution of a specific source to PM10 in León, only by knowing some meteorological and chemical variables.

Nitrogen oxides and ozone in Portugal: trends and ozone estimation in an urban and a rural site.

This study provides an analysis of the spatial distribution and trends of NO, NO2 and O3 concentrations in Portugal between 1995 and 2010. Furthermore, an estimation model for daily ozone concentrations was developed for an urban and a rural site. NO concentration showed a significant decreasing trend in most urban stations. A decreasing trend in NO2 is only observed in the stations with less influence from emissions of primary NO2. Several stations showed a significant upward trend in O3 as a result of the decrease in the NO/NO2 ratio. In the northern rural region, ozone showed a strong correlation with wind direction, highlighting the importance of long-range transport. In the urban site, most of the variance is explained by the NO2/NOX ratio. The results obtained by the ozone estimation model in the urban site fit 2013 observed data. In the rural site, the estimated ozone during extreme events agrees with observed concentration.

Indoor aerosol size distributions in a gymnasium.

In this study, an indoor/outdoor monitoring program was carried out in a gymnasium at the University of Leon, Spain. The main goal was a characterization of aerosol size distributions in a university gymnasium under different conditions and sports activities (with and without magnesia alba) and the study of the mass fraction deposited in each of the parts of the respiratory tract. The aerosol particles were measured in 31 discrete channels (size ranges) using a laser spectrometer probe. Aerosol size distributions were studied under different conditions: i) before sports activities, ii) activities without using magnesia alba, iii) activities using magnesia alba, iv) cleaning procedures, and v) outdoors. The aerosol refractive index and density indoors were estimated from the aerosol composition: 1.577-0.003i and 2.055 g cm(-3), respectively. Using the estimated density, the mass concentration was calculated, and the evolution of PM1, PM2.5 and PM10 for different activities was assessed. The quality of the air in the gymnasium was strongly influenced by the use of magnesia alba (MgCO3) and the number of gymnasts who were training. Due to the climbing chalk and the constant process of resuspension, average PM10 concentrations of over 440 µg m(-3) were reached. The maximum daily concentrations ranged from 500 to 900 µg m(-3). Particle size determines the place in the respiratory tract where the deposition occurs. For this reason, the inhalable, thoracic, tracheobronchial and respirable fractions were assessed for healthy adults and high risk people, according to international standards. The estimations show that, for healthy adults, up to 300 µg m(-3) can be retained by the trachea and bronchi, and 130 µg m(-3) may reach the alveolar region. The different physical activities and the attendance rates in the sports facility have a significant influence on the concentration and size distributions observed.

Particulate matter in the indoor and outdoor air of a gymnasium and a fronton.

An indoor/outdoor monitoring programme of PM10 was carried out in two sports venues (a fronton and a gymnasium). Levels always below 50 µg m(-3) were obtained in the fronton and outdoor air. Due to the climbing chalk and the constant process of resuspension, concentrations above 150 µg m(-3) were registered in the gymnasium. The chalk dust contributed to CO3 (2-) concentrations of 32 ± 9.4 µg m(-3) in this sports facility, which represented, on average, 18 % of the PM10 mass. Here, the carbonate levels were 128 times higher than those registered outdoors. Much lower concentrations, around 1 µg m(-3), were measured in the fronton. The chalk dust is also responsible for the high Mg(2+) concentrations in the gym (4.7 ± 0.89 µg m(-3)), unfolding a PM10 mass fraction of 2.7 %. Total carbon accounted for almost 30 % of PM10 in both indoor spaces. Aerosol size distributions were bimodal and revealed a clear dependence on physical activities and characteristics of the sports facilities. The use of climbing chalk in the gymnasium contributed significantly to the coarse mode. The average geometric mean diameter, geometric standard deviation and total number of coarse particles were 0.77 µm, 2.79 cm(-3) and 28 cm(-3), respectively.

Human mortality seasonality in Castile-León, Spain, between 1980 and 1998: the influence of temperature, pressure and humidity.

This study was carried out in the region of Castile and Leon, Spain, from 1980 to 1998 and analyzes the relationship between the number of monthly deaths caused by cardiovascular, respiratory and digestive diseases and three meteorological variables: temperature, pressure and humidity. One of the innovations in this study is the application of principal component analysis in a way that differs from its usual application: one single series representing the whole region was constructed for each meteorological variable from the series of eight weather stations. Annual and seasonal mortality trends were also studied. Cardiovascular diseases are the leading cause of death in Castile and Leon. The mortality related to cardiovascular, respiratory and digestive systems shows a statistically significant rising trend across the study period (an annual increase of 6, 16 and 4 per thousand, respectively). The pressure at which mortality is lowest is approximately the same for all causes of death (about 915 hPa), but temperature values vary greatly (16.8-19.7 degrees C for the mean, 10.9-18.1 degrees C for the minimum, and 24.1-27.2 degrees C for the maximum temperature). The most comfortable temperatures for patients with cardiovascular diseases (16.8 degrees C) are apparently lower than those for patients with respiratory diseases (18.1 degrees C), which are, in turn, lower than in the case of diseases of the digestive system (19.7 degrees C). Finally, the optimal humidity for patients with respiratory diseases is the lowest (24%) among the diseases, and the highest (51%) corresponds to diseases of the digestive system, while the optimal relative humidity for the cardiovascular system is 45%.

Alternative statistical methods for interpreting airborne Alder (Alnus glutimosa (L.) Gaertner) pollen concentrations.

This paper reports on the behaviour of Alnus glutinosa (alder) pollen grains in the atmosphere of Ponferrada (León, NW Spain) from 1995 to 2006. The study, which sought to determine the effects of various weather-related parameters on Alnus pollen counts, was performed using a volumetric method. The main pollination period for this taxon is January-February. Alder pollen is one of the eight major airborne pollen allergens found in the study area. An analysis was made of the correlation between pollen counts and major weather-related parameters over each period. In general, the strongest positive correlation was with temperature, particularly maximum temperature. During each period, peak pollen counts occurred when the maximum temperature fell within the range 9 degrees C-14 degrees C. Finally, multivariate analysis showed that the parameter exerting the greatest influence was temperature, a finding confirmed by Spearman correlation tests. Principal components analysis suggested that periods with high pollen counts were characterised by high maximum temperature, low rainfall and an absolute humidity of around 6 g m(-3). Use of this type of analysis in conjunction with other methods is essential for obtaining an accurate record of pollen-count variations over a given period.

Urticaceae pollen concentration in the atmosphere of North Western Spain.

Plants of the Urticaceae family can develop into a pest on soils enriched with nitrogen. Urticaceae pollen is a biohazard because it elicits severe pollinosis. Pollen grains were sampled by using a Lanzoni seven-day-recording trap from February 1995-December 2000 in the atmosphere of the city of Ponferrada (Leon, North Western Spain). The Spearman test was used to analyse the statistical correlation between Urticaceae pollen and certain meteorological factors in different main pollination periods. Maximum values are reached in June and July, minimum levels are recorded in January and December. The parameters bearing the greatest positive influence on the occurrence of Urticaceae pollen grains are: temperature (maximum, minimum and mean), humidity (absolute, wet-bulb temperature, dew point and mixing ratio) and south western wind direction; negative parameters are: relative humidity, rainfall and period without wind. The highest correlation coefficients were obtained with temperature and wet-bulb. Absolute humidity and wet-bulb temperature yielded better correlation than relative humidity; hence, these two parameters must be included in this type of study. The use of one main pollination period or another in statistical analysis has an influence on the coefficient value. The behaviour of the pollen grains in the atmosphere during the year also influences the results.