Digitally-enabled, person-centred care (PCC) in allergen immunotherapy: An ARIA-EAACI Position Paper

In rhinitis and asthma, several mHealth apps have been developed but only a few have been validated. However, these apps have a high potential for improving person-centred care (PCC), especially in allergen immunotherapy (AIT). They can provide support in AIT initiation by selecting the appropriate patient and allergen shared decision-making. They can also help in (i) the evaluation of (early) efficacy, (ii) early and late stopping rules and (iii) the evaluation of (carried-over) efficacy after cessation of the treatment course. Future perspectives have been formulated in the first report of a joint task force (TF)-Allergic Rhinitis and Its Impact on Asthma (ARIA) and the European Academy of Allergy and Clinical Immunology (EAACI)-on digital biomarkers. The TF on AIT now aims to (i) outline the potential of the clinical applications of mHealth solutions, (ii) express their current limitations, (iii) make proposals regarding further developments for both clinical practice and scientific purpose and (iv) suggest which of the tools might best comply with the purpose of digitally-enabled PCC in AIT.

Influence of meteorological variables and air pollutants on measurements from automatic pollen sampling devices

This study examines the influence of meteorological factors and air pollutants on the performance of automatic pollen monitoring devices, as part of the EUMETNET Autopollen COST ADOPT-intercomparison campaign held in Munich, Germany, during the 2021 pollen season. The campaign offered a unique opportunity to compare all automatic monitors available at the time, a Plair Rapid-E, a Hund-Wetzlar BAA500, an OPC Alphasense, a KH-3000 Yamatronics, three Swisens Polenos, a PollenSense APS, a FLIR IBAC2, a DMT WIBS-5, an Aerotape Sextant, to the average of four manual Hirst traps, under the same environmental conditions. The investigation aimed to elucidate how meteorological factors and air pollution impact particle capture and identification efficiency. The analysis showed coherent results for most devices regarding the correlation between environmental conditions and pollen concentrations. This reflects on one hand, a significant correlation between weather and airborne pollen concentration, and on the other hand the capability of devices to provide meaningful data under the conditions under which measurements were taken. However, correlation strength varied among devices, reflecting differences in design, algorithms, or sensors used. Additionally, it was observed that different algorithms applied to the same dataset resulted in different concentration outputs, highlighting the role of algorithm design in these systems (monitor + algorithm). Notably, no significant influence from air pollutants on the pollen concentrations was observed, suggesting that any potential difference in effect on the systems might require higher air pollution concentrations or more complex interactions. However, results from some monitors were affected to a minor degree by specific weather variables. Our findings suggest that the application of real-time devices in urban environments should focus on the associated algorithm that classifies pollen taxa. The impact of air pollution, although not to be excluded, is of secondary concern as long as the pollution levels are similar to a large European city like Munich.

Prenatal and early life exposure to air pollution and the risk of severe lower respiratory tract infections during early childhood: the Espoo Cohort Study

BACKGROUND

There is inconsistent evidence of the effects of exposure to ambient air pollution on the occurrence of lower respiratory tract infections (LRTIs) in early childhood. We assessed the effects of individual-level prenatal and early life exposure to air pollutants on the risk of LRTIs in early life.

METHODS

We studied 2568 members of the population-based Espoo Cohort Study born between 1984 and 1990 and living in 1991 in the City of Espoo, Finland. Exposure assessment was based on dispersion modelling and land-use regression for lifetime residential addresses. The outcome was a LRTI based on data from hospital registers. We applied Poisson regression to estimate the incidence rate ratio (IRR) of LTRIs, contrasting incidence rates in the exposure quartiles to the incidence rates in the first quartile. We used weighted quantile sum (WQS) regression to estimate the joint effect of the studied air pollutants.

RESULTS

The risk of LRTIs during the first 2 years of life was significantly related to exposure to individual and multiple air pollutants, measured with the Multipollutant Index (MPI), including primarily sulphur dioxide (SO2), particulate matter with a dry diameter of up to 2.5 µm (PM2.5) and nitrogen dioxide (NO2) exposures in the first year of life, with an adjusted IRR of 1.72 per unit increase in MPI (95% CI 1.20 to 2.47). LRTIs were not related to prenatal exposure.

CONCLUSIONS

We provide evidence that ambient air pollution exposure during the first year of life increases the risk of LRTIs during the first 2 years of life. SO2, PM2.5 and NO2 were found to contribute the highest weights on health effects.

Fires as a source of annual ambient PM2.5 exposure and chronic health impacts in Europe

Chronic exposure to ambient PM2.5 is the largest environmental health risk in Europe. We used a chemical transport model and recent exposure response functions to simulate ambient PM2.5, contribution from fires and related health impacts over Europe from 1990 to 2019. Our estimation indicates that the excess death burden from exposure to ambient PM2.5 declined across Europe at a rate of 10,000 deaths per year, from 0.57 million (95 % confidence intervals: 0.44-0.75 million) in 1990 to 0.28 million (0.19-0.42 million) in the specified period. Among these excess deaths, approximately 99 % were among adults, while only around 1 % occurred among children. Our findings reveal a steady increase in fire mortality fractions (excess deaths from fires per 1000 deaths from ambient PM2.5) from 2 in 1990 to 13 in 2019. Notably, countries in Eastern Europe exhibited significantly higher fire mortality fractions and experienced more pronounced increases compared to those in Western and Central Europe. We performed sensitivity analyses by considering fire PM2.5 to be more toxic as compared to other sources, as indicated by recent studies. By considering fire PM2.5 to be more toxic than other PM2.5 sources results in an increased relative contribution of fires to excess deaths, reaching 2.5-13 % in 2019. Our results indicate the requirement of larger mitigation and adaptation efforts and more sustainable forest management policies to avert the rising health burden from fires.

From MASK-air and SILAM to CATALYSE (Climate Action To Advance HeaLthY Societies in Europe)

Plant species vary under different climatic conditions and the distribution of pollen in the air. Trends in pollen distribution can be used to assess the impact of climate change on public health. In 2015, the Mobile Airways Sentinel networK for rhinitis and asthma (MASK-air®) was launched as a project of the European Innovation Partnership on Active and Healthy Ageing (EIP-on-AHA, DG Santé and DG CONNECT). This project aimed to develop a warning system to inform patients about the onset of the pollen season, namely, the System for Integrated modeLling of Atmospheric coMposition (SILAM). A global-to-meso-scale dispersion model was developed by the Finnish Meteorological Institute (FMI). It provides quantitative information on atmospheric pollution of anthropogenic and natural origins, particularly on allergenic pollens. Impact of Air Pollution on Asthma and Rhinitis (POLLAR, EIT Health) has combined MASK-air clinical data with SILAM forecasts. A new Horizon Europe grant (Climate Action to Advance HeaLthY Societies in Europe [CATALYSE]; grant agreement number 101057131), which came into force in September 2022, aims to improve our understanding of climate change and help us find ways to counteractit. One objective of this project is to develop early warning systems and predictive models to improve the effectiveness of strategies for adapting to climate change. One of the warning systems is focused on allergic rhinitis (CATALYSE Task 3.2), with a collaboration between the FMI (Finland), Porto University (Portugal), MASK-air SAS (France), ISGlobal (Spain), Hertie School (Germany), and the University of Zurich (Switzerland). It is to be implemented with the support of the European Academy of Allergy and Clinical Immunology. This paper reports the planning of CATALYSE Task 3.2.

Associations between landscape fires and child morbidity in southern Mozambique: a time-series study

BACKGROUND

Epidemiological evidence linking exposure to landscape fires to child health remains scarce. We assessed the association between daily landscape fire smoke and child hospital visits and admissions in the Manhiça district, Mozambique, an area characterised by frequent forest and cropland fires.

METHODS

In this time-series analysis (2012-20), our primary metric for exposure to landscape fires was fire-originated PM2·5 from smoke dispersion hindcasts. We also assessed total and upwind fire exposure using daily satellite-derived fire density data. Daily numbers of hospital visits and admissions were extracted from an ongoing paediatric morbidity surveillance system (children aged ≤15 years). We applied quasi-Poisson regression models controlling for season, long-term trend, day of the week, temperature, and rainfall, and offsetting by annual population-time at risk to examine lag-specific association of fires on morbidity.

FINDINGS

A 10 μg/m3 increase in fire-originated PM2·5 was associated with a 6·12% (95% CI 0·37-12·21) increase in all-cause and a 12·43% (5·07-20·31) increase in respiratory-linked hospital visits on the following day. Positive associations were also observed for lag 0 and the cumulative lag of 0-1 days. Null associations were observed for hospital admissions. Landscape fires mostly occurred in forested areas; however, associations with child morbidity were stronger for cropland than for forest fires.

INTERPRETATION

Landscape fire smoke was associated with all-cause and respiratory-linked morbidity in children. Improved exposure assessment is needed to better quantify the contribution of landscape fire smoke to child health in regions with scarce air pollution monitoring.

FUNDING

H2020 project EXHAUSTION, Academy of Finland, Spanish Ministry of Science and Innovation, Generalitat de Catalunya, and Government of Mozambique and Spanish Agency for International Cooperation and Development.

African dust transport and deposition modelling verified through a citizen science campaign in Finland

African desert dust is emitted and long-range transported with multiple effects on climate, air quality, cryosphere, and ecosystems. On 21-23 February 2021, dust from a sand and dust storm in northern Africa was transported to Finland, north of 60°N. The episode was predicted 5 days in advance by the global operational SILAM forecast, and its key features were confirmed and detailed by a retrospective analysis. The scavenging of dust by snowfall and freezing rain in Finland resulted in a rare case of substantial mineral dust contamination of snow surfaces over a large area in the southern part of the country. A citizen science campaign was set up to collect contaminated snow samples prepared according to the scientists' instructions. The campaign gained wide national interest in television, radio, newspapers and social media, and dust samples were received from 525 locations in Finland, up to 64.3°N. The samples were utilised in investigating the ability of an atmospheric dispersion model to simulate the dust episode. The analysis confirmed that dust came from a wide Sahara and Sahel area from 5000 km away. Our results reveal the features of this rare event and demonstrate how deposition samples can be used to evaluate the skills and limitations of current atmospheric models in simulating transport of African dust towards northern Europe.

Designing an automatic pollen monitoring network for direct usage of observations to reconstruct the concentration fields

We consider several approaches to a design of a regional-to-continent-scale automatic pollen monitoring network in Europe. Practical challenges related to the arrangement of such a network limit the range of possible solutions. A hierarchical network is discussed, highlighting the necessity of a few reference sites that follow an extended observations protocol and have corresponding capabilities. Several theoretically rigorous approaches to a network design have been developed so far. However, before starting the process, a network purpose, a criterion of its performance, and a concept of the data usage should be formalized. For atmospheric composition monitoring, developments follow one of the two concepts: a network for direct representation of concentration fields and a network for model-based data assimilation, inverse problem solution, and forecasting. The current paper demonstrates the first approach, whereas the inverse problems are considered in a follow-up paper. We discuss the approaches for the network design from theoretical and practical standpoints, formulate criteria for the network optimality, and consider practical constraints for an automatic pollen network. An application of the methodology is demonstrated for a prominent example of Germany's pollen monitoring network. The multi-step method includes (i) the network representativeness and (ii) redundancy evaluation followed by (iii) fidelity evaluation and improvement using synthetic data.

Patient-centred digital biomarkers for allergic respiratory diseases and asthma: the ARIA-EAACI approach

Biomarkers for the diagnosis, treatment and follow-up of patients with rhinitis and/or asthma are urgently needed. Although some biologic biomarkers exist in specialist care for asthma, they cannot be largely used in primary care. There are no validated biomarkers in rhinitis or allergen immunotherapy (AIT) that can be used in clinical practice. The digital transformation of health and health care (including mHealth) places the patient at the centre of the health system and is likely to optimise the practice of allergy. ARIA (Allergic Rhinitis and its Impact on Asthma) and EAACI (European Academy of Allergy and Clinical Immunology) developed a Task Force aimed at proposing patient-reported outcome measures (PROMs) as digital biomarkers that can be easily used for different purposes in rhinitis and asthma. It first defined control digital biomarkers that should make a bridge between clinical practice, randomised controlled trials, observational real-life studies and allergen challenges. Using the MASK-air app as a model, a daily electronic combined symptom-medication score for allergic diseases (CSMS) or for asthma (e-DASTHMA), combined with a monthly control questionnaire, were embedded in a strategy similar to the diabetes approach for disease control. To mimic real-life, it secondly proposed quality-of-life digital biomarkers including daily EQ-5D visual analogue scales and the bi-weekly RhinAsthma Patient Perspective (RAAP). The potential implications for the management of allergic respiratory diseases were proposed.

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.

Climate change, airborne allergens, and three translational mitigation approaches

One of the important adverse impacts of climate change on human health is increases in allergic respiratory diseases such as allergic rhinitis and asthma. This impact is via the effects of increases in atmospheric carbon dioxide concentration and air temperature on sources of airborne allergens such as pollen and fungal spores. This review describes these effects and then explores three translational mitigation approaches that may lead to improved health outcomes, with recent examples and developments highlighted. Impacts have already been observed on the seasonality, production and atmospheric concentration, allergenicity, and geographic distribution of airborne allergens, and these are projected to continue into the future. A technological revolution is underway that has the potential to advance patient management by better avoiding associated increased exposures, including automated real-time airborne allergen monitoring, airborne allergen forecasting and modelling, and smartphone apps for mitigating the health impacts of airborne allergens.

Digitally-enabled, patient-centred care in rhinitis and asthma multimorbidity: The ARIA-MASK-air® approach

MASK-air^® , a validated mHealth app (Medical Device regulation Class IIa) has enabled large observational implementation studies in over 58,000 people with allergic rhinitis and/or asthma. It can help to address unmet patient needs in rhinitis and asthma care. MASK-air^® is a Good Practice of DG Santé on digitally-enabled, patient-centred care. It is also a candidate Good Practice of OECD (Organisation for Economic Co-operation and Development). MASK-air^® data has enabled novel phenotype discovery and characterisation, as well as novel insights into the management of allergic rhinitis. MASK-air^® data show that most rhinitis patients (i) are not adherent and do not follow guidelines, (ii) use as-needed treatment, (iii) do not take medication when they are well, (iv) increase their treatment based on symptoms and (v) do not use the recommended treatment. The data also show that control (symptoms, work productivity, educational performance) is not always improved by medications. A combined symptom-medication score (ARIA-EAACI-CSMS) has been validated for clinical practice and trials. The implications of the novel MASK-air^® results should lead to change management in rhinitis and asthma.

Evaluation of 137Cs, 133Xe and 3H activity concentrations monitored in the Arctic atmosphere

This paper provides a brief introduction to the Arctic atmospheric radioactivity monitoring network. A decade of monitoring results have shown the ¹³⁷Cs background levels in Arctic air range from 0.05 to 1.50 μBq/m³. The monitoring stations have sufficient sensitivity to detect ¹³⁷Cs brought to the atmosphere due to resuspension in local soil and reemissions from biomass burning in a daily temporal resolution. These observations can be used as tracers for atmospheric processes. The ¹³³Xe measurements obtained at Yellowknife, Resolute and Spitsbergen could support other research into how air pollution problems arise across intercontinental distances. It will help develop and improve models capable of predicting the long-distance transport and deposition of trace gases in the Arctic. Rainwater monitoring data collected in Finnish Lapland since the 1960's indicate that ³H radioactivity concentrations reached natural background levels in early 2000s, typically around 1-2 Bq/L monthly, with an annual seasonal variation cycle consistent with the observed of other cosmogenic radionuclides.

Bioaerosols in the atmosphere at two sites in Northern Europe in spring 2021: Outline of an experimental campaign

A coordinated observational and modelling campaign targeting biogenic aerosols in the air was performed during spring 2021 at two locations in Northern Europe: Helsinki (Finland) and Siauliai (Lithuania), approximately 500 km from each other in north-south direction. The campaign started on March 1, 2021 in Siauliai (12 March in Helsinki) and continued till mid-May in Siauliai (end of May in Helsinki), thus recording the transition of the atmospheric biogenic aerosols profile from winter to summer. The observations included a variety of samplers working on different principles. The core of the program was based on 2- and 2.4--hourly sampling in Helsinki and Siauliai, respectively, with sticky slides (Hirst 24-h trap in Helsinki, Rapid-E slides in Siauliai). The slides were subsequently processed extracting the DNA from the collected aerosols, which was further sequenced using the 3-rd generation sequencing technology. The core sampling was accompanied with daily and daytime sampling using standard filter collectors. The hourly aerosol concentrations at the Helsinki monitoring site were obtained with a Poleno flow cytometer, which could recognize some of the aerosol types. The sampling campaign was supported by numerical modelling. For every sample, SILAM model was applied to calculate its footprint and to predict anthropogenic and natural aerosol concentrations, at both observation sites. The first results confirmed the feasibility of the DNA collection by the applied techniques: all but one delivered sufficient amount of DNA for the following analysis, in over 40% of the cases sufficient for direct DNA sequencing without the PCR step. A substantial variability of the DNA yield has been noticed, generally not following the diurnal variations of the total-aerosol concentrations, which themselves showed variability not related to daytime. An expected upward trend of the biological material amount towards summer was observed but the day-to-day variability was large. The campaign DNA analysis produced the first high-resolution dataset of bioaerosol composition in the North-European spring. It also highlighted the deficiency of generic DNA databases in applications to atmospheric biota: about 40% of samples were not identified with standard bioinformatic methods.

Introduction to the AQ-WATCH Project and the AQ-WATCH Toolkit to fight air pollution

Background

WHO states that 9 out of 10 persons in the world do not breath clean air and 8 million people die prematurely from air pollution each year. The problem is well understood, but actions to mitigate it are lacking. The purpose of the EU-funded AQ-WATCH Project is precisely to develop effective tools based on the most advanced science technologies to help decision-makers in government and the private sector to address air pollution issues in regions of the world where they operate.

Objectives

AQ-WATCH aims to develops a supply chain to generate innovative downstream products for improving air quality forecasts and attribution based on existing space/in-situ observations to improve public health and to optimize renewable energy in regions of the world. The project consortium includes research and business-oriented partners, who brings together the required expertise to define the optimal functionalities of these products to bring them to the market.

Results

The AQ-WATCH products are organized into 5 modules: (1) Air quality atlas, (2) Air quality attribution & mitigation, (3) Dust and fire forecast, (4) Fracking analysis, and (5) Air quality forecast. They are developed for 3 target regions (Beijing, Colorado and Santiago de Chile) and are integrated into a unified user-interface, the AQ-WATCH Toolkit. Product developers and prime users in the target regions are constantly interacting, and the user feedback is collected, analyzed and included during the product development.

Conclusions

Collaborative work done in AQ-WATCH shows strategic interaction between our research and business-oriented partners. Contributions from local parties are proven to be valuable for regional adaption of the products. A throughout dissemination including regional workshops is essential to ensure proper knowledge uptake by the target audience. Constant exchange with the private sector is required for a smooth transfer from scientific results to commercialized marketable products.

Key messages

• The AQ-WATCH Project follows EU’s initiative to utilize its space observations with added values to develop easily-accessible tools to fight air pollution applicable to regions of the world.

• The AQ-WATCH Toolkit is developed with iterative feedback exchanges between product developers and local users to address air pollution issues, and will be eventually exploited to the market.

Higher airborne pollen concentrations correlated with increased SARS-CoV-2 infection rates, as evidenced from 31 countries across the globe

Pollen exposure weakens the immunity against certain seasonal respiratory viruses by diminishing the antiviral interferon response. Here we investigate whether the same applies to the pandemic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is sensitive to antiviral interferons, if infection waves coincide with high airborne pollen concentrations. Our original hypothesis was that more airborne pollen would lead to increases in infection rates. To examine this, we performed a cross-sectional and longitudinal data analysis on SARS-CoV-2 infection, airborne pollen, and meteorological factors. Our dataset is the most comprehensive, largest possible worldwide from 130 stations, across 31 countries and five continents. To explicitly investigate the effects of social contact, we additionally considered population density of each study area, as well as lockdown effects, in all possible combinations: without any lockdown, with mixed lockdown-no lockdown regime, and under complete lockdown. We found that airborne pollen, sometimes in synergy with humidity and temperature, explained, on average, 44% of the infection rate variability. Infection rates increased after higher pollen concentrations most frequently during the four previous days. Without lockdown, an increase of pollen abundance by 100 pollen/m3 resulted in a 4% average increase of infection rates. Lockdown halved infection rates under similar pollen concentrations. As there can be no preventive measures against airborne pollen exposure, we suggest wide dissemination of pollen-virus coexposure dire effect information to encourage high-risk individuals to wear particle filter masks during high springtime pollen concentrations.

Higher airborne pollen concentrations correlated with increased SARS-CoV-2 infection rates, as evidenced from 31 countries across the globe

Pollen exposure weakens the immunity against certain seasonal respiratory viruses by diminishing the antiviral interferon response. Here we investigate whether the same applies to the pandemic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is sensitive to antiviral interferons, if infection waves coincide with high airborne pollen concentrations. Our original hypothesis was that more airborne pollen would lead to increases in infection rates. To examine this, we performed a cross-sectional and longitudinal data analysis on SARS-CoV-2 infection, airborne pollen, and meteorological factors. Our dataset is the most comprehensive, largest possible worldwide from 130 stations, across 31 countries and five continents. To explicitly investigate the effects of social contact, we additionally considered population density of each study area, as well as lockdown effects, in all possible combinations: without any lockdown, with mixed lockdown-no lockdown regime, and under complete lockdown. We found that airborne pollen, sometimes in synergy with humidity and temperature, explained, on average, 44% of the infection rate variability. Infection rates increased after higher pollen concentrations most frequently during the four previous days. Without lockdown, an increase of pollen abundance by 100 pollen/m³ resulted in a 4% average increase of infection rates. Lockdown halved infection rates under similar pollen concentrations. As there can be no preventive measures against airborne pollen exposure, we suggest wide dissemination of pollen-virus coexposure dire effect information to encourage high-risk individuals to wear particle filter masks during high springtime pollen concentrations.

Modelling grass pollen levels in Belgium

Biogenic aerosols such as airborne grass pollen affect the public health badly by putting additional distress on people already suffering from cardiovascular and respiratory diseases. In Belgium, daily airborne pollen concentrations are monitored offline at a few sites only, hampering the timely coverage of the country and short-term forecasts. Here we apply the Chemistry Transport Model SILAM to the Belgian territory to model the spatio-temporal airborne grass pollen levels near the surface based on bottom-up inventories of grass pollen emissions updated with the Copernicus land monitoring Service grassland map of 2015. Transport of aerosols in SILAM is driven by ECMWF ERA5 meteorological data. The emitted grass pollen amounts in SILAM are computed by the multiplication of the grass pollen source map with the release rate determined by the seasonal shape production curve during the grass flowering period. The onset and offset of this period follow a location-dependent prescribed calendar days. Here we optimize the grass pollen seasonal start and end in SILAM by comparing a 2008-2018 time series of daily airborne grass pollen concentrations from the Belgian aerobiological surveillance network with the simulations. The effect of the spatial distribution of grass pollen sources is quantified by constructing pollen source-receptor relations using model simulations with varying grass pollen emissions in five areas of the model domain as input. Up to 33% of the airborne grass pollen in one area was transport from others areas inside Belgium. Adjusting the start and end of the grass pollen season improved the model performance substantially by almost doubling the correlation with local observations. By introducing the temporal scaling of the inter-seasonal pollen amounts in the model, an additional R² increase up to 22% was obtained. Further improvements can be made by including more detailed grass pollen sources and more dynamic start and end dates of the pollen season.

Treatment of allergic rhinitis during and outside the pollen season using mobile technology. A MASK study

Background

The analysis of mobile health (mHealth) data has generated innovative insights into improving allergic rhinitis control, but additive information is needed. A cross-sectional real-world observational study was undertaken in 17 European countries during and outside the estimated pollen season. The aim was to collect novel information including the phenotypic characteristics of the users.

Methods

The Allergy Diary–MASK-air–mobile phone app, freely available via Google Play and App, was used to collect the data of daily visual analogue scales (VASs) for overall allergic symptoms and medication use. Fluticasone Furoate (FF), Mometasone Furoate (MF), Azelastine Fluticasone Proprionate combination (MPAzeFlu) and eight oral H1-antihistamines were studied. Phenotypic characteristics were recorded at entry. The ARIA severity score was derived from entry data. This was an a priori planned analysis.

Results

9037 users filled in 70,286 days of VAS in 2016, 2017 and 2018. The ARIA severity score was lower outside than during the pollen season. Severity was similar for all treatment groups during the pollen season, and lower in the MPAzeFlu group outside the pollen season. Days with MPAzeFlu had lower VAS levels and a higher frequency of monotherapy than the other treatments during the season. Outside the season, days with MPAzeFlu also had a higher frequency of monotherapy. The number of reported days was significantly higher with MPAzeFlu during and outside the season than with MF, FF or oral H1-antihistamines.

Conclusions

This study shows that the overall efficacy of treatments is similar during and outside the pollen season and indicates that medications are similarly effective during the year.

ARIA digital anamorphosis: Digital transformation of health and care in airway diseases from research to practice

Digital anamorphosis is used to define a distorted image of health and care that may be viewed correctly using digital tools and strategies. MASK digital anamorphosis represents the process used by MASK to develop the digital transformation of health and care in rhinitis. It strengthens the ARIA change management strategy in the prevention and management of airway disease. The MASK strategy is based on validated digital tools. Using the MASK digital tool and the CARAT online enhanced clinical framework, solutions for practical steps of digital enhancement of care are proposed.

A demonstration project of Global Alliance against Chronic Respiratory Diseases: Prediction of interactions between air pollution and allergen exposure-the Mobile Airways Sentinel NetworK-Impact of air POLLution on Asthma and Rhinitis approach

This review analyzes the state and recent progress in the field of information support for pollen allergy sufferers. For decades, information available for the patients and allergologists consisted of pollen counts, which are vital but insufficient. New technology paves the way to substantial increase in amount and diversity of the data. This paper reviews old and newly suggested methods to predict pollen and air pollutant concentrations in the air and proposes an allergy risk concept, which combines the pollen and pollution information and transforms it into a qualitative risk index. This new index is available in an app (Mobile Airways Sentinel NetworK-air) that was developed in the frame of the European Union grant Impact of Air POLLution on sleep, Asthma and Rhinitis (a project of European Institute of Innovation and Technology-Health). On-going transformation of the pollen allergy information support is based on new technological solutions for pollen and air quality monitoring and predictions. The new information-technology and artificial-intelligence-based solutions help to convert this information into easy-to-use services for both medical practitioners and allergy sufferers.

Pollen season is reflected on symptom load for grass and birch pollen-induced allergic rhinitis in different geographic areas-An EAACI Task Force Report

BACKGROUND

The effectiveness of allergen immunotherapy (AIT) in seasonal and perennial allergic rhinitis (AR) depends on the definition of pollen exposure intensity or time period. We recently evaluated pollen and symptom data from Germany to examine the new definitions of the European Academy of Allergy and Clinical Immunology (EAACI) on pollen season and peak pollen period start and end. Now, we aim to confirm the feasibility of these definitions to properly mirror symptom loads for grass and birch pollen-induced allergic rhinitis in other European geographical areas such as Austria, Finland and France, and therefore their suitability for AIT and clinical practice support.

METHODS

Data from twenty-three pollen monitoring stations from three countries in Europe and for 3 years (2014-2016) were used to investigate the correlation between birch and grass pollen concentrations during the birch and grass pollen season defined via the EAACI criteria, and total nasal symptom and medication scores as reported with the aid of the patient's hay-fever diary (PHD). In addition, we conducted a statistical analysis, together with a graphical investigation, to reveal correlations and dependencies between the studied parameters.

RESULTS

The analysis demonstrated that the definitions of pollen season as well as peak pollen period start and end as proposed by the EAACI are correlated to pollen-induced symptom loads reported by PHD users during birch and grass pollen season. A statistically significant correlation (slightly higher for birch) has been found between the Total Nasal Symptom and Medication Score (TNSMS) and the pollen concentration levels. Moreover, the maximum symptom levels occurred mostly within the peak pollen periods (PPP) following the EAACI criteria.

CONCLUSIONS

Based on our analyses, we confirm the validity of the EAACI definitions on pollen season for both birch and grass and for a variety of geographical locations for the four European countries (including Germany from a previous publication) analyzed so far. On this basis, the use of the EAACI definitions is supported in future clinical trials on AIT as well as in daily routine for optimal patient care. Further evaluation of the EAACI criteria in other European regions is recommended.

Estimated health impacts from maritime transport in the Mediterranean region and benefits from the use of cleaner fuels

Ship traffic emissions degrade air quality in coastal areas and contribute to climate impacts globally. The estimated health burden of exposure to shipping emissions in coastal areas may inform policy makers as they seek to reduce exposure and associated potential health impacts. This work estimates the PM2.5-attributable impacts in the form of premature mortality and cardiovascular and respiratory hospital admissions, from long-term exposure to shipping emissions. Health impact assessment (HIA) was performed in 8 Mediterranean coastal cities, using a baseline conditions from the literature and a policy case accounting for the MARPOL Annex VI rules requiring cleaner fuels in 2020. Input data were (a) shipping contributions to ambient PM2.5 concentrations based on receptor modelling studies found in the literature, (b) population and health incidence data from national statistical registries, and (c) geographically-relevant concentration-response functions from the literature. Long-term exposure to ship-sourced PM2.5 accounted for 430 (95% CI: 220-650) premature deaths per year, in the 8 cities, distributed between groups of cities: Barcelona and Athens, with >100 premature deaths/year, and Nicosia, Brindisi, Genoa, Venice, Msida and Melilla, with tens of premature deaths/year. The more stringent standards in 2020 would reduce the number of PM2.5-attributable premature deaths by 15% on average. HIA provided a comparative assessment of the health burden of shipping emissions across Mediterranean coastal cities, which may provide decision support for urban planning with a special focus on harbour areas, and in view of the reduction in sulphur content of marine fuels due to MARPOL Annex VI in 2020.

Short-term prenatal exposure to ambient air pollution and risk of preterm birth - A population-based cohort study in Finland

BACKGROUND

Previous studies have provided evidence that prenatal exposure to low-level air pollution increases the risk of preterm birth (PTB), but the findings of the effects of short-term exposure have been inconclusive. Moreover, there is little knowledge on potential synergistic effects of different combinations of air pollutants.

OBJECTIVES

To assess independent and joint effects of prenatal exposure to air pollutants during the week prior to the delivery on the risk of PTB.

METHODS

The study population included 2568 members of the Espoo Cohort Study, living in the City of Espoo, Finland, born between 1984 and 1990. We assessed individual-level prenatal exposure to ambient air pollutants of interest based on maternal residential addresses, while taking into account their residential mobility. We used both regional-to-city-scale dispersion modelling and land-use regression-based method to estimates the pollutant concentrations. We contrasted the risk of PTB in the highest quartile (Q₄) of exposure to the lower exposure quartiles (Q₁-Q₃) during the specific periods of pregnancy. We applied Poisson regression analysis to estimate the adjusted risk ratios (RRs) with their 95% confidence intervals (CI), adjusting for season of birth, maternal age, sex of the baby, family's socioeconomic status, maternal smoking, and exposure to environmental tobacco smoke during pregnancy, single parenthood, and exposure to other air pollutants (this in multi-pollutant models).

RESULTS

The risk of PTB was related to exposures to PM_2.5, PM₁₀ and NO₂ during the week prior to the delivery with adjusted RRs of 1.67 (95%CI: 1.14, 2.46), 1.60 (95% CI: 1.09, 2.34) and 1.65 (95% CI: 1.14, 2.37), from three-pollutant models respectively. There were no significant joint effects for these different air pollutants (during the week prior to the delivery).

CONCLUSION

Our results provide evidence that exposure to fairly low-level air pollution may trigger PTB, but synergistic effects of different pollutants are not likely.

Interactions Between Air Pollution and Pollen Season for Rhinitis Using Mobile Technology: A MASK-POLLAR Study

BACKGROUND

Several studies have suggested an interaction between air pollution and pollen exposure with an impact on allergy symptoms. However, large studies with real-life data are not available.

OBJECTIVE

To investigate associations between major air pollutants (ozone and particulate matter with a diameter of <2.5 μm) and allergic rhinitis (AR) control during grass and birch pollen seasons as well as outside the pollen season.

METHODS

The daily impact of allergic symptoms was recorded by the Allergy Diary (Mobile Airways Sentinel NetworK [MASK-air]) app (a validated mHealth tool for rhinitis management) using visual analog scales (VASs) in Northern and Central Europe users in 2017 and 2018. Uncontrolled AR was defined using symptoms and medications. Pollutant levels were assessed using the System for Integrated modeLing of Atmospheric coMposition database. Pollen seasons were assessed by regions using Google Trends. Generalized estimating equation models were used to account for repeated measures per user, adjusting for sex, age, treatment, and country. Analyses were stratified by pollen seasons to investigate interactions between air pollutants and pollen exposure.

RESULTS

A total of 3323 geolocated individuals (36,440 VAS-days) were studied. Associations between uncontrolled rhinitis and pollutants were stronger during the grass pollen season. Days with uncontrolled AR increased by 25% for an interquartile range increase in ozone levels during the grass pollen season (odds ratio of 1.25 [95% CI, 1.11-1.41] in 2017 and of 1.14 [95% CI, 1.04-1.25] in 2018). A similar trend was found for particulate matter with a diameter of less than 2.5 μm, especially in 2017.

CONCLUSIONS

These results suggest that the relationship between uncontrolled AR and air pollution is modified by the presence of grass pollens. This study confirms the impact of pollutants in the grass pollen season but not in the birch pollen season.

Building an automatic pollen monitoring network (ePIN): Selection of optimal sites by clustering pollen stations

Airborne pollen is a recognized biological indicator and its monitoring has multiple uses such as providing a tool for allergy diagnosis and prevention. There is a knowledge gap related to the distribution of pollen traps needed to achieve representative biomonitoring in a region. The aim of this manuscript is to suggest a method for setting up a pollen network (monitoring method, monitoring conditions, number and location of samplers etc.). As a case study, we describe the distribution of pollen across Bavaria and the design of the Bavarian pollen monitoring network (ePIN), the first operational automatic pollen network worldwide. We established and ran a dense pollen monitoring network of 27 manual Hirst-type pollen traps across Bavaria, Germany, during 2015. Hierarchical cluster analysis of the data was then performed to select the locations for the sites of the final pollen monitoring network. According to our method, Bavaria can be clustered into three large pollen regions with eight zones. Within each zone, pollen diversity and distribution among different locations does not vary significantly. Based on the pollen zones, we opted to place one automatic monitoring station per zone resulting in the ePIN network, serving 13 million inhabitants. The described method defines stations representative for a homogeneous aeropalynologically region, which reduces redundancy within the network and subsequent costs (in the study case from 27 to 8 locations). Following this method, resources in pollen monitoring networks can be optimized and allergic citizens can then be informed in a timely and effective way, even in larger geographical areas.

Synergistic effects of prenatal exposure to fine particulate matter (PM2.5) and ozone (O3) on the risk of preterm birth: A population-based cohort study

BACKGROUND

There is some evidence that prenatal exposure to low-level air pollution increases the risk of preterm birth (PTB), but little is known about synergistic effects of different pollutants.

OBJECTIVES

We assessed the independent and joint effects of prenatal exposure to air pollution during the entire duration of pregnancy.

METHODS

The study population consisted of the 2568 members of the Espoo Cohort Study, born between 1984 and 1990, and living in the City of Espoo, Finland. We assessed individual-level prenatal exposure to ambient air pollutants of interest at all the residential addresses from conception to birth. The pollutant concentrations were estimated both by using regional-to-city-scale dispersion modelling and land-use regression-based method. We applied Poisson regression analysis to estimate the adjusted risk ratios (RRs) with their 95% confidence intervals (CI) by comparing the risk of PTB among babies with the highest quartile (Q₄) of exposure during the entire duration of pregnancy with those with the lower exposure quartiles (Q₁-Q₃). We adjusted for season of birth, maternal age, sex of the baby, family's socioeconomic status, maternal smoking during pregnancy, maternal exposure to environmental tobacco smoke during pregnancy, single parenthood, and exposure to other air pollutants (only in multi-pollutant models) in the analysis.

RESULTS

In a multi-pollutant model estimating the effects of exposure during entire pregnancy, the adjusted RR was 1.37 (95% CI: 0.85, 2.23) for PM_2.5 and 1.64 (95% CI: 1.15, 2.35) for O₃. The joint effect of PM_2.5 and O₃ was substantially higher, an adjusted RR of 3.63 (95% CI: 2.16, 6.10), than what would have been expected from their independent effects (0.99 for PM_2.5 and 1.34 for O₃). The relative risk due to interaction (RERI) was 2.30 (95% CI: 0.95, 4.57).

DISCUSSION

Our results strengthen the evidence that exposure to fairly low-level air pollution during pregnancy increases the risk of PTB. We provide novel observations indicating that individual air pollutants such as PM_2.5 and O₃ may act synergistically potentiating each other's adverse effects.

Current state of the global operational aerosol multi-model ensemble: An update from the International Cooperative for Aerosol Prediction (ICAP)

Since the first International Cooperative for Aerosol Prediction (ICAP) multi-model ensemble (MME) study, the number of ICAP global operational aerosol models has increased from five to nine. An update of the current ICAP status is provided, along with an evaluation of the performance of ICAP-MME over 2012-2017, with a focus on June 2016-May 2017. Evaluated with ground-based Aerosol Robotic Network (AERONET) aerosol optical depth (AOD) and data assimilation quality MODerate-resolution Imaging Spectroradiometer (MODIS) retrieval products, the ICAP-MME AOD consensus remains the overall top-scoring and most consistent performer among all models in terms of root-mean-square error (RMSE), bias and correlation for total, fine- and coarse-mode AODs as well as dust AOD; this is similar to the first ICAP-MME study. Further, over the years, the performance of ICAP-MME is relatively stable and reliable compared to more variability in the individual models. The extent to which the AOD forecast error of ICAP-MME can be predicted is also examined. Leading predictors are found to be the consensus mean and spread. Regression models of absolute forecast errors were built for AOD forecasts of different lengths for potential applications. ICAP-MME performance in terms of modal AOD RMSEs of the 21 regionally representative sites over 2012-2017 suggests a general tendency for model improvements in fine-mode AOD, especially over Asia. No significant improvement in coarse-mode AOD is found overall for this time period.

Health Impacts of Ambient Air Pollution in Finland

Air pollution has been estimated to be one of the leading environmental health risks in Finland. National health impact estimates existing to date have focused on particles (PM) and ozone (O₃). In this work, we quantify the impacts of particles, ozone, and nitrogen dioxide (NO₂) in 2015, and analyze the related uncertainties. The exposures were estimated with a high spatial resolution chemical transport model, and adjusted to observed concentrations. We calculated the health impacts according to Word Health Organization (WHO) working group recommendations. According to our results, ambient air pollution caused a burden of 34,800 disability-adjusted life years (DALY). Fine particles were the main contributor (74%) to the disease burden, which is in line with the earlier studies. The attributable burden was dominated by mortality (32,900 years of life lost (YLL); 95%). Impacts differed between population age groups. The burden was clearly higher in the adult population over 30 years (98%), due to the dominant role of mortality impacts. Uncertainties due to the concentration-response functions were larger than those related to exposures.

A statistical model for predicting the inter-annual variability of birch pollen abundance in Northern and North-Eastern Europe

The paper suggests a methodology for predicting next-year seasonal pollen index (SPI, a sum of daily-mean pollen concentrations) over large regions and demonstrates its performance for birch in Northern and North-Eastern Europe. A statistical model is constructed using meteorological, geophysical and biological characteristics of the previous year). A cluster analysis of multi-annual data of European Aeroallergen Network (EAN) revealed several large regions in Europe, where the observed SPI exhibits similar patterns of the multi-annual variability. We built the model for the northern cluster of stations, which covers Finland, Sweden, Baltic States, part of Belarus, and, probably, Russia and Norway, where the lack of data did not allow for conclusive analysis. The constructed model was capable of predicting the SPI with correlation coefficient reaching up to 0.9 for some stations, odds ratio is infinitely high for 50% of sites inside the region and the fraction of prediction falling within factor of 2 from observations, stays within 40-70%. In particular, model successfully reproduced both the bi-annual cycle of the SPI and years when this cycle breaks down.

Cleaner fuels for ships provide public health benefits with climate tradeoffs

We evaluate public health and climate impacts of low-sulphur fuels in global shipping. Using high-resolution emissions inventories, integrated atmospheric models, and health risk functions, we assess ship-related PM_2.5 pollution impacts in 2020 with and without the use of low-sulphur fuels. Cleaner marine fuels will reduce ship-related premature mortality and morbidity by 34 and 54%, respectively, representing a ~ 2.6% global reduction in PM_2.5 cardiovascular and lung cancer deaths and a ~3.6% global reduction in childhood asthma. Despite these reductions, low-sulphur marine fuels will still account for ~250k deaths and ~6.4 M childhood asthma cases annually, and more stringent standards beyond 2020 may provide additional health benefits. Lower sulphur fuels also reduce radiative cooling from ship aerosols by ~80%, equating to a ~3% increase in current estimates of total anthropogenic forcing. Therefore, stronger international shipping policies may need to achieve climate and health targets by jointly reducing greenhouse gases and air pollution.

Cleaner fuels for ships provide public health benefits with climate tradeoffs

We evaluate public health and climate impacts of low-sulphur fuels in global shipping. Using high-resolution emissions inventories, integrated atmospheric models, and health risk functions, we assess ship-related PM2.5 pollution impacts in 2020 with and without the use of low-sulphur fuels. Cleaner marine fuels will reduce ship-related premature mortality and morbidity by 34 and 54%, respectively, representing a ~ 2.6% global reduction in PM2.5 cardiovascular and lung cancer deaths and a ~3.6% global reduction in childhood asthma. Despite these reductions, low-sulphur marine fuels will still account for ~250k deaths and ~6.4 M childhood asthma cases annually, and more stringent standards beyond 2020 may provide additional health benefits. Lower sulphur fuels also reduce radiative cooling from ship aerosols by ~80%, equating to a ~3% increase in current estimates of total anthropogenic forcing. Therefore, stronger international shipping policies may need to achieve climate and health targets by jointly reducing greenhouse gases and air pollution.

Defining pollen exposure times for clinical trials of allergen immunotherapy for pollen-induced rhinoconjunctivitis - an EAACI position paper

BACKGROUND

Clinical efficacy of pollen allergen immunotherapy (AIT) has been broadly documented in randomized controlled trials. The underlying clinical endpoints are analysed in seasonal time periods predefined based on the background pollen concentration. However, any validated or generally accepted definition from academia or regulatory authorities for this relevant pollen exposure intensity or period of time (season) is currently not available. Therefore, this Task Force initiative of the European Academy of Allergy and Clinical Immunology (EAACI) aimed to propose definitions based on expert consensus.

METHODS

A Task Force of the Immunotherapy and Aerobiology and Pollution Interest Groups of the EAACI reviewed the literature on pollen exposure in the context of defining relevant time intervals for evaluation of efficacy in AIT trials. Underlying principles in measuring pollen exposure and associated methodological problems and limitations were considered to achieve a consensus.

RESULTS

The Task Force achieved a comprehensive position in defining pollen exposure times for different pollen types. Definitions are presented for 'pollen season', 'high pollen season' (or 'peak pollen period') and 'high pollen days'.

CONCLUSION

This EAACI position paper provides definitions of pollen exposures for different pollen types for use in AIT trials. Their validity as standards remains to be tested in future studies.

Mortality due to Vegetation Fire-Originated PM2.5 Exposure in Europe-Assessment for the Years 2005 and 2008

BACKGROUND

Vegetation fires can release substantial quantities of fine particles (PM2.5), which are harmful to health. The fire smoke may be transported over long distances and can cause adverse health effects over wide areas.

OBJECTIVE

We aimed to assess annual mortality attributable to short-term exposures to vegetation fire-originated PM2.5 in different regions of Europe.

METHODS

PM2.5 emissions from vegetation fires in Europe in 2005 and 2008 were evaluated based on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data on fire radiative power. Atmospheric transport of the emissions was modeled using the System for Integrated modeLling of Atmospheric coMposition (SILAM) chemical transport model. Mortality impacts were estimated for 27 European countries based on a) modeled daily PM2.5 concentrations and b) population data, both presented in a 50 × 50 km2 spatial grid; c) an exposure-response function for short-term PM2.5 exposure and daily nonaccidental mortality; and d) country-level data for background mortality risk.

RESULTS

In the 27 countries overall, an estimated 1,483 and 1,080 premature deaths were attributable to the vegetation fire-originated PM2.5 in 2005 and 2008, respectively. Estimated impacts were highest in southern and eastern Europe. However, all countries were affected by fire-originated PM2.5, and even the lower concentrations in western and northern Europe contributed substantially (~ 30%) to the overall estimate of attributable mortality.

CONCLUSIONS

Our assessment suggests that air pollution caused by PM2.5 released from vegetation fires is a notable risk factor for public health in Europe. Moreover, the risk can be expected to increase in the future as climate change proceeds. This factor should be taken into consideration when evaluating the overall health and socioeconomic impacts of these fires. Citation: Kollanus V, Prank M, Gens A, Soares J, Vira J, Kukkonen J, Sofiev M, Salonen RO, Lanki T. 2017. Mortality due to vegetation fire-originated PM2.5 exposure in Europe-assessment for the years 2005 and 2008. Environ Health Perspect 125:30-37; http://dx.doi.org/10.1289/EHP194.

On impact of transport conditions on variability of the seasonal pollen index

This discussion paper reveals the contribution of pollen transport conditions to the inter-annual variability of the seasonal pollen index (SPI). This contribution is quantified as a sensitivity of the pollen model predictions to meteorological variability and is shown to be a noticeable addition to the SPI variability caused by plant reproduction cycles. A specially designed SILAM model re-analysis of pollen seasons 1980-2014 was performed, resulting in the 35 years of the SPI predictions over Europe, which was used to compute the SPI inter-annual variability. The current paper presents the results for birch and grass. Throughout the re-analysis, the source term formulations and habitation maps were kept constant, which allowed attributing the obtained variability exclusively to the pollen release and transport conditions during the flowering seasons. It is shown that the effect is substantial: it amounts to 10-20% (grass) and 20-40% (birch) of the observed SPI year-to-year changes reported in the literature. The phenomenon has well-pronounced spatial- and species-specific patterns. The findings were compared with observation-based statistical models for the SPI prediction, showing that such models highlight the same processes as the analysis with the SILAM model.

Costs and benefits of low-sulphur fuel standard for Baltic Sea shipping

The maximum allowable fuel sulphur content for shipping in the Baltic Sea dropped from 1%S to 0.1%S in 1 January 2015. We provide a cost-benefit analysis of the sulphur reduction policy in the Baltic Sea Sulphur Emission Control Area (SECA). We calculated the abatement costs based on shipowners' optimal decision-making in choosing between low-sulphur fuel and a sulphur scrubber, and the benefits were modelled through a high-resolution impact pathway analysis, which took into account the formation and dispersion of the emissions, and considered the positive health impacts resulting from lowered ambient PM_2.5 concentrations. Our basic result indicates that for the Baltic Sea only, the latest sulphur regulation is not cost-effective. The expected annual cost is roughly €465 M and benefit 2200 saved Disability Adjusted Life-Years (DALYs) or monetized €105 M. Based on our sensitivity analysis, the benefits yet have a potential to exceed the costs. The analysis neither takes into account the acidifying impact of sulphur nor the impact North Sea shipping has on the cost-benefit ratio. Lastly, a similar approach is found highly recommendable to study the implications of the upcoming Tier III NO_x standard for shipping.

Fine-Scale Exposure to Allergenic Pollen in the Urban Environment: Evaluation of Land Use Regression Approach

BACKGROUND

Despite the recent developments in physically and chemically based analysis of atmospheric particles, no models exist for resolving the spatial variability of pollen concentration at urban scale.

OBJECTIVES

We developed a land use regression (LUR) approach for predicting spatial fine-scale allergenic pollen concentrations in the Helsinki metropolitan area, Finland, and evaluated the performance of the models against available empirical data.

METHODS

We used grass pollen data monitored at 16 sites in an urban area during the peak pollen season and geospatial environmental data. The main statistical method was generalized linear model (GLM).

RESULTS

GLM-based LURs explained 79% of the spatial variation in the grass pollen data based on all samples, and 47% of the variation when samples from two sites with very high concentrations were excluded. In model evaluation, prediction errors ranged from 6% to 26% of the observed range of grass pollen concentrations. Our findings support the use of geospatial data-based statistical models to predict the spatial variation of allergenic grass pollen concentrations at intra-urban scales. A remote sensing-based vegetation index was the strongest predictor of pollen concentrations for exposure assessments at local scales.

CONCLUSIONS

The LUR approach provides new opportunities to estimate the relations between environmental determinants and allergenic pollen concentration in human-modified environments at fine spatial scales. This approach could potentially be applied to estimate retrospectively pollen concentrations to be used for long-term exposure assessments.

CITATION

Hjort J, Hugg TT, Antikainen H, Rusanen J, Sofiev M, Kukkonen J, Jaakkola MS, Jaakkola JJ. 2016. Fine-scale exposure to allergenic pollen in the urban environment: evaluation of land use regression approach. Environ Health Perspect 124:619-626; http://dx.doi.org/10.1289/ehp.1509761.

First comparison of symptom data with allergen content (Bet v 1 and Phl p 5 measurements) and pollen data from four European regions during 2009-2011

BACKGROUND

The level of symptoms in pollen allergy sufferers and users of the Patient's Hayfever Diary (PHD), does not directly reflect the total amount of pollen in the air. It is necessary to explain the symptom load and thus the development of allergic symptoms and to determine which environmental factors, besides the pollen load, influence variables. It seems reasonable to suspect allergen content because the amount of allergen varies throughout seasons and regions and is not always correlated with the total pollen amount.

METHODS

Data on the allergen content of ambient air (Bet v 1 and Phl p 5) from 2009 until 2011 was used to compare the respective pollen and symptom loads for study regions in Austria, Germany, France and Finland.

RESULTS

Our findings suggest that allergen amount (Bet v 1/Phl p 5) has a strong but regionally dependent impact on the symptom load of pollen allergy sufferers. Peak symptom loads can be traced with peak allergen loads. The influence of other important aeroallergens should also be assessed during the pollen season.

CONCLUSION

Allergen concentrations have an impact on pollen allergy sufferers although not as clear as assumed previously. The pattern of pollen load and major allergen content distribution does not directly explain the symptom load pattern, although significant positive correlations were found. Thus, monitoring of symptoms via voluntary crowdsourcing should be considered for future pollen and symptom forecasts in order to support pollen allergy sufferers.

Airborne olive pollen counts are not representative of exposure to the major olive allergen Ole e 1

Pollen is routinely monitored, but it is unknown whether pollen counts represent allergen exposure. We therefore simultaneously determined olive pollen and Ole e 1 in ambient air in Córdoba, Spain, and Évora, Portugal, using Hirst-type traps for pollen and high-volume cascade impactors for allergen. Pollen from different days released 12-fold different amounts of Ole e 1 per pollen (both locations P < 0.001). Average allergen release from pollen (pollen potency) was much higher in Córdoba (3.9 pg Ole e 1/pollen) than in Évora (0.8 pg Ole e 1/pollen, P = 0.004). Indeed, yearly olive pollen counts in Córdoba were 2.4 times higher than in Évora, but Ole e 1 concentrations were 7.6 times higher. When modeling the origin of the pollen, >40% of Ole e 1 exposure in Évora was explained by high-potency pollen originating from the south of Spain. Thus, olive pollen can vary substantially in allergen release, even though they are morphologically identical.

A numerical model of birch pollen emission and dispersion in the atmosphere. Model evaluation and sensitivity analysis

An evaluation of performance of the System for Integrated modeLling of Atmospheric coMposition (SILAM) in application to birch pollen dispersion is presented. The system is described in a companion paper whereas the current study evaluates the model sensitivity to details of the pollen emission module parameterisation and to the meteorological input data. The most important parameters are highlighted. The reference year considered for the analysis is 2006. It is shown that the model is capable of predicting about two-thirds of allergenic alerts, with the odds ratio exceeding 12 for the best setup. Several other statistics corroborate with these estimations. Low-pollen concentration days are also predicted correctly in more than two-thirds of cases. The model experiences certain difficulties only with intermediate pollen concentrations. It is demonstrated that the most important input parameter is the near-surface temperature, the bias of which can easily jeopardise the results. The model sensitivity to random fluctuations of temperature is much lower. Other parameters important at various stages of pollen development, release, and dispersion are precipitation and ambient humidity, as well as wind direction.

A numerical model of birch pollen emission and dispersion in the atmosphere. Description of the emission module

A birch pollen emission model is described and its main features are discussed. The development of the model is based on a double-threshold temperature sum model that describes the propagation of the flowering season and naturally links to the thermal time models to predict the onset and duration of flowering. For the flowering season, the emission model considers ambient humidity and precipitation rate, both of which suppress the pollen release, as well as wind speed and turbulence intensity, which promote it. These dependencies are qualitatively evaluated using the aerobiological observations. Reflecting the probabilistic character of the flowering of an individual tree in a population, the model introduces relaxation functions at the start and end of the season. The physical basis of the suggested birch pollen emission model is compared with another comprehensive emission module reported in literature. The emission model has been implemented in the SILAM dispersion modelling system, the results of which are evaluated in a companion paper.