Outdoor airborne allergens: Characterization, behavior and monitoring in Europe

Aeroallergens or inhalant allergens, are proteins dispersed through the air and have the potential to induce allergic conditions such as rhinitis, conjunctivitis, and asthma. Outdoor aeroallergens are found predominantly in pollen grains and fungal spores, which are allergen carriers. Aeroallergens from pollen and fungi have seasonal emission patterns that correlate with plant pollination and fungal sporulation and are strongly associated with atmospheric weather conditions. They are released when allergen carriers come in contact with the respiratory system, e.g. the nasal mucosa. In addition, due to the rupture of allergen carriers, airborne allergen molecules may be released directly into the air in the form of micronic and submicronic particles (cytoplasmic debris, cell wall fragments, droplets etc.) or adhered onto other airborne particulate matter. Therefore, aeroallergen detection strategies must consider, in addition to the allergen carriers, the allergen molecules themselves. This review article aims to present the current knowledge on inhalant allergens in the outdoor environment, their structure, localization, and factors affecting their production, transformation, release or degradation. In addition, methods for collecting and quantifying aeroallergens are listed and thoroughly discussed. Finally, the knowledge gaps, challenges and implications associated with aeroallergen analysis are describe

Comparison of dust forecast (GEOS-5 and WRF-Chem), satellite observations and ground-based aerosol measurements in the Caribbean region during the 2020 Summer African dust season

North African dust reaches the Caribbean region every summer supplying mineral dust particles which play an important role in the regional weather and public health. During the African dust season of summer 2020 several events, including the "Godzilla" mega dust event, were identified over the Caribbean. Under the framework of the NASA-funded project Caribbean Air-quality Alert and Management Assistance System-Public Health (CALIMA-PH), we compare results of the dust forecast models with the ground-based and satellite observations for events that happened in parallel with large convective systems over the region during June-July 2020. The models used are the global dust forecast model Goddard Earth Observing System-5 (GEOS-5) and the regional dust forecast model Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). Satellite observations are from the Visible Infrared Imaging Radiometer Suite (VIIRS), the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). Ground-based observations (e.g., aerosol optical depth (AOD), depolarization ratio, particulate matter, scattering Angstrom exponent (SAE), dust surface concentration, height of dust layer) were performed at seven different locations (Cayenne, Martinique, Guadeloupe--French Territories, Barbados, Puerto Rico, Merida--Mexico and Miami--USA) over the Caribbean to provide a better understanding of African dust dispersal patterns over the region with a unique "Lagrangian" measurement, including the Godzilla mega dust event and tropical storms developed in the area. Results show that the dust forecast models were not always in agreement with the observations, and this was the particular case during the presence of tropical storms like Cristobal and Gonzalo. We will show the differences between the forecast provided by both models and the result of another run after ingesting the models with aerosol available data such as AOD

"Godzilla" African dust event of June 2020; impacts of air quality in the Greater Caribbean Basin, the Gulf of Mexico and the United States

On June 19, 2020, the Caribbean region started to feel the effects of an historic African (Saharan) dust plume that has been called "Godzilla" due to its large geographic extent and record amount of dust. This plume, with an area close to the size of the continental USA (8,080,464 km (super 2) ), blanketed areas in the greater Caribbean Basin, the Gulf of Mexico and the southern United States. The occurrence and progression of this "Godzilla" event was predicted by several dust forecast models, among them, the global Goddard Earth Observing System-5 (GEOS-5) and the regional dust forecast model Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). According to data from the NASA Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP Lidar), the dust plume extended from the Earth's surface up to about 5 km altitude. As part of the NASA-funded summer 2020 intensive field phase of the Caribbean Air-quality Alert and Management Assistance System-Public Health (CALIMA-PH) project, eight ground-based stations in the Greater Caribbean Basin (French Guiana, Trinidad and Tobago, Martinique, Guadeloupe, Puerto Rico, Merida-Mexico and Miami-USA) collected surface aerosol data (e.g., PM (sub 10) and PM (sub 2.5) mass concentrations, light scattering and absorption coefficients, visibility, dust concentrations) and column aerosol data (i.e., aerosol optical depth--AOD) during the event. Using these data, together with satellite observations from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Visible Infrared Imaging Radiometer Suite (VIIRS), and CALIOP, we describe the movement of the dust plume through the region and assess its impact. The event caused a decrease in visibility in the atmosphere's boundary layer of less than 3 miles in some locations, showed record values for the aerosol optical properties, and exhibited exceedances in both the US EPA air quality standard and the World Health Organization (WHO) air quality guidelines. For several days, the locations impacted by the "Godzilla" dust plume were exposed to air quality conditions ranging from "Unhealthy for sensitive groups" to "Hazardous", in cases reaching PM (sub 10) values ca. 500 mu g/m (super 3)

Sea spray aerosol as a unique source of ice nucleating particles.

Ice nucleating particles (INPs) are vital for ice initiation in, and precipitation from, mixed-phase clouds. A source of INPs from oceans within sea spray aerosol (SSA) emissions has been suggested in previous studies but remained unconfirmed. Here, we show that INPs are emitted using real wave breaking in a laboratory flume to produce SSA. The number concentrations of INPs from laboratory-generated SSA, when normalized to typical total aerosol number concentrations in the marine boundary layer, agree well with measurements from diverse regions over the oceans. Data in the present study are also in accord with previously published INP measurements made over remote ocean regions. INP number concentrations active within liquid water droplets increase exponentially in number with a decrease in temperature below 0 °C, averaging an order of magnitude increase per 5 °C interval. The plausibility of a strong increase in SSA INP emissions in association with phytoplankton blooms is also shown in laboratory simulations. Nevertheless, INP number concentrations, or active site densities approximated using "dry" geometric SSA surface areas, are a few orders of magnitude lower than corresponding concentrations or site densities in the surface boundary layer over continental regions. These findings have important implications for cloud radiative forcing and precipitation within low-level and midlevel marine clouds unaffected by continental INP sources, such as may occur over the Southern Ocean

Towards European automatic bioaerosol monitoring:comparison of 9 automatic pollen observational instruments with classic Hirst-type traps

To benefit allergy patients and the medical practitioners, pollen information should be available in both a reliable and timely manner; the latter is only recently possible due to automatic monitoring. To evaluate the performance of all currently available automatic instruments, an international intercomparison campaign was jointly organised by the EUMETNET AutoPollen Programme and the ADOPT COST Action in Munich, Germany (March–July 2021).The automatic systems (hardware plus identification algorithms) were compared with manual Hirst-type traps. Measurements were aggregated into 3-hourly or daily values to allow comparison across all devices. We report results for total pollen as well as for Betula, Fraxinus, Poaceae, and Quercus, for all instruments that provided these data. The results for daily averages compared better with Hirst observations than the 3-hourly values. For total pollen, there was a considerable spread among systems, with some reaching R2 > 0.6 (3 h) and R2 > 0.75 (daily) compared with Hirst-type traps, whilst other systems were not suitable to sample total pollen efficiently (R2 < 0.3). For individual pollen types, results similar to the Hirst were frequently shown by a small group of systems. For Betula, almost all systems performed well (R2 > 0.75 for 9 systems for 3-hourly data). Results for Fraxinus and Quercus were not as good for most systems, while for Poaceae (with some exceptions), the performance was weakest. For all pollen types and for most measurement systems, false positive classifications were observed outside of the main pollen season. Different algorithms applied to the same device also showed different results, highlighting the importance of this aspect of the measurement system. Overall, given the 30 % error on daily concentrations that is currently accepted for Hirst-type traps, several automatic systems are currently capable of being used operationally to provide real-time observations at high temporal resolutions. They provide distinct advantages compared to the manual Hirst-type measurements

Clinical risk factors of adverse outcomes among women with COVID-19 in the pregnancy and postpartum period: a sequential, prospective meta-analysis

Objective This sequential, prospective meta-analysis (sPMA) sought to identify risk factors among pregnant and postpartum women with COVID-19 for adverse outcomes related to: disease severity, maternal morbidities, neonatal mortality and morbidity, adverse birth outcomes. Data sources We prospectively invited study investigators to join the sPMA via professional research networks beginning in March 2020. Study eligibility criteria Eligible studies included those recruiting at least 25 consecutive cases of COVID-19 in pregnancy within a defined catchment area. Study appraisal and synthesis methods We included individual patient data from 21 participating studies. Data quality was assessed, and harmonized variables for risk factors and outcomes were constructed. Duplicate cases were removed. Pooled estimates for the absolute and relative risk of adverse outcomes comparing those with and without each risk factor were generated using a two-stage meta-analysis. Results We collected data from 33 countries and territories, including 21,977 cases of SARS-CoV-2 infection in pregnancy or postpartum. We found that women with comorbidities (pre-existing diabetes, hypertension, cardiovascular disease) versus those without were at higher risk for COVID-19 severity and pregnancy health outcomes (fetal death, preterm birth, low birthweight). Participants with COVID-19 and HIV were 1.74 times (95% CI: 1.12, 2.71) more likely to be admitted to the ICU. Pregnant women who were underweight before pregnancy were at higher risk of ICU admission (RR 5.53, 95% CI: 2.27, 13.44), ventilation (RR 9.36, 95% CI: 3.87, 22.63), and pregnancy-related death (RR 14.10, 95% CI: 2.83, 70.36). Pre-pregnancy obesity was also a risk factor for severe COVID-19 outcomes including ICU admission (RR 1.81, 95% CI: 1.26,2.60), ventilation (RR 2.05, 95% CI: 1.20,3.51), any critical care (RR 1.89, 95% CI: 1.28,2.77), and pneumonia (RR 1.66, 95% CI: 1.18,2.33). Anemic pregnant women with COVID-19 also had increased risk of ICU admission (RR 1.63, 95% CI: 1.25, 2.11) and death (RR 2.36, 95% CI: 1.15, 4.81). Conclusion We found that pregnant women with comorbidities including diabetes, hypertension, and cardiovascular disease were at increased risk for severe COVID-19-related outcomes, maternal morbidities, and adverse birth outcomes. We also identified several less commonly-known risk factors, including HIV infection, pre-pregnancy underweight, and anemia. Although pregnant women are already considered a high-risk population, special priority for prevention and treatment should be given to pregnant women with these additional risk factors

Clinical risk factors of adverse outcomes among women with COVID-19 in the pregnancy and postpartum period: A sequential, prospective meta-analysis

OBJECTIVE: This sequential, prospective meta-analysis (sPMA) sought to identify risk factors among pregnant and postpartum women with COVID-19 for adverse outcomes related to: disease severity, maternal morbidities, neonatal mortality and morbidity, adverse birth outcomes. DATA SOURCES: We prospectively invited study investigators to join the sPMA via professional research networks beginning in March 2020. STUDY ELIGIBILITY CRITERIA: Eligible studies included those recruiting at least 25 consecutive cases of COVID-19 in pregnancy within a defined catchment area. STUDY APPRAISAL AND SYNTHESIS METHODS: We included individual patient data from 21 participating studies. Data quality was assessed, and harmonized variables for risk factors and outcomes were constructed. Duplicate cases were removed. Pooled estimates for the absolute and relative risk of adverse outcomes comparing those with and without each risk factor were generated using a two-stage meta-analysis. RESULTS: We collected data from 33 countries and territories, including 21,977 cases of SARS-CoV-2 infection in pregnancy or postpartum. We found that women with comorbidities (pre-existing diabetes, hypertension, cardiovascular disease) versus those without were at higher risk for COVID-19 severity and pregnancy health outcomes (fetal death, preterm birth, low birthweight). Participants with COVID-19 and HIV were 1.74 times (95% CI: 1.12, 2.71) more likely to be admitted to the ICU. Pregnant women who were underweight before pregnancy were at higher risk of ICU admission (RR 5.53, 95% CI: 2.27, 13.44), ventilation (RR 9.36, 95% CI: 3.87, 22.63), and pregnancy-related death (RR 14.10, 95% CI: 2.83, 70.36). Pre-pregnancy obesity was also a risk factor for severe COVID-19 outcomes including ICU admission (RR 1.81, 95% CI: 1.26,2.60), ventilation (RR 2.05, 95% CI: 1.20,3.51), any critical care (RR 1.89, 95% CI: 1.28,2.77), and pneumonia (RR 1.66, 95% CI: 1.18,2.33). Anemic pregnant women with COVID-19 also had increased risk of ICU admission (RR 1.63, 95% CI: 1.25, 2.11) and death (RR 2.36, 95% CI: 1.15, 4.81). CONCLUSION: We found that pregnant women with comorbidities including diabetes, hypertension, and cardiovascular disease were at increased risk for severe COVID-19-related outcomes, maternal morbidities, and adverse birth outcomes. We also identified several less commonly-known risk factors, including HIV infection, pre-pregnancy underweight, and anemia. Although pregnant women are already considered a high-risk population, special priority for prevention and treatment should be given to pregnant women with these additional risk factors