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
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
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.
Background Allergies to grass pollen are the number one cause of outdoor hay fever. The human immune system reacts with symptoms to allergen from pollen. Objective We investigated the natural ...variability in release of the major group 5 allergen from grass pollen across Europe. Methods Airborne pollen and allergens were simultaneously collected daily with a volumetric spore trap and a high-volume cascade impactor at 10 sites across Europe for 3 consecutive years. Group 5 allergen levels were determined with a Phl p 5–specific ELISA in 2 fractions of ambient air: particulate matter of greater than 10 μm in diameter and particulate matter greater than 2.5 μm and less than 10 μm in diameter. Mediator release by ambient air was determined in FcεRI-humanized basophils. The origin of pollen was modeled and condensed to pollen potency maps. Results On average, grass pollen released 2.3 pg of Phl p 5 per pollen. Allergen release per pollen (potency) varied substantially, ranging from less than 1 to 9 pg of Phl p 5 per pollen (5% to 95% percentile). The main variation was locally day to day. Average potency maps across Europe varied between years. Mediator release from basophilic granulocytes correlated better with allergen levels per cubic meter ( r 2 = 0.80, P < .001) than with pollen grains per cubic meter ( r 2 = 0.61, P < .001). In addition, pollen released different amounts of allergen in the non–pollen-bearing fraction of ambient air, depending on humidity. Conclusion Across Europe, the same amount of pollen released substantially different amounts of group 5 grass pollen allergen. This variation in allergen release is in addition to variations in pollen counts. Molecular aerobiology (ie, determining allergen in ambient air) might be a valuable addition to pollen counting.
Operational pollen monitoring networks have developed across Europe, and the world more generally, in response to the increasing prevalence of pollen allergy and asthma. Routine pollen observations ...are in large part currently still based on time-intensive manual techniques developed in the 1950s. These methods suffer from low temporal resolution and long delays in data availability. Recent technological developments are revolutionising the field making real-time high-temporal resolution measurements possible. This paper describes the rationale behind the EUMETNET AutoPollen programme, which aims to develop a prototype automatic pollen monitoring network across Europe. We provide a brief description of the current state-of-the-art, then an overview of new technologies, and finally the main tasks of the AutoPollen programme.
Automatically operating particle detection devices generate valuable data, but their use in routine aerobiology needs to be harmonized. The growing network of researchers using automatic pollen ...detectors has the challenge to develop new data processing systems, best suited for identification of pollen or spore from bioaerosol data obtained near-real-time. It is challenging to recognise all the particles in the atmospheric bioaerosol due to their diversity. In this study, we aimed to find the natural groupings of pollen data by using cluster analysis, with the intent to use these groupings for further interpretation of real-time bioaerosol measurements. The scattering and fluorescence data belonging to 29 types of pollen and spores were first acquired in the laboratory using Rapid-E automatic particle detector. Neural networks were used for primary data processing, and the resulting feature vectors were clustered for scattering and fluorescence modality. Scattering clusters results showed that pollen of the same plant taxa associates with the different clusters corresponding to particle shape and size properties. According to fluorescence clusters, pollen grouping highlighted the possibility to differentiate Dactylis and Secale genera in the Poaceae family. Fluorescent clusters played a more important role than scattering for separating unidentified fluorescent particles from tested pollen. The proposed clustering method aids in reducing the number of false-positive errors.
•Local-scale pollen forecasting statistical model is formulated and evaluated in Riga.•Transformation of input data is included for achieving linearity and stationarity.•Predictors are projected to ...pollen data and selected via multistep linear regression.•Model was applied for Riga in several data sets and compared with other approaches.
A statistical model for predicting daily mean pollen concentrations during the flowering season is constructed and its parameterization and application to birch pollen in Riga (Latvia) are discussed. The model involves several steps of transformations of both meteorological data and pollen observations, aiming at a normally distributed homogeneous stationary dataset with linearized dependencies between the transformed meteorological predictors and pollen concentrations. The data transformation includes normalization of daily mean birch pollen concentrations, a switch of the independent axis from time to heat sum, a projection of governing parameters to pollen concentrations, and a reduction of non-stationarity via removal of the mean pollen season curve. These transformations resulted in a substantial improvement of statistical features of the data and, consequently, a higher efficiency of statistical procedures and better scores of the model. The transformed datasets are used for the model construction via multi-linear regression. For the application in Riga, the model coefficients were calculated using 9 years of birch pollen observations. The model was evaluated using years withheld from the training dataset. The evaluation showed robust model performance with the overall Model Accuracy exceeding 80% and Odds Ratio=30.
The Global Fire Assimilation System (GFAS) assimilates fire radiative power (FRP) observations from satellite-based sensors to produce daily estimates of biomass burning emissions. It has been ...extended to include information about injection heights derived from fire observations and meteorological information from the operational weather forecasts of ECMWF. Injection heights are provided by two distinct methods: the Integrated Monitoring and Modelling System for wildland fires (IS4FIRES) parameterisation and the one-dimensional plume rise model (PRM). A global database of daily biomass burning emissions and injection heights at 0.1° resolution has been produced for 2003–2015 and is continuously extended in near-real time with the operational GFAS service of the Copernicus Atmospheric Monitoring Service (CAMS). In this study, the two injection height data sets were compared with the new MPHP2 (MISR Plume Height Project 2) satellite-based plume height retrievals. The IS4FIRES parameterisation showed a better overall agreement than the observations, while the PRM was better at capturing the variability of injection heights. The performance of both parameterisations is also dependent on the type of vegetation. Furthermore, the use of biomass burning emission heights from GFAS in atmospheric composition forecasts was assessed in two case studies: the South AMerican Biomass Burning Analysis (SAMBBA) campaign which took place in September 2012 in Brazil, and a series of large fire events in the western USA in August 2013. For these case studies, forecasts of biomass burning aerosol species by the Composition Integrated Forecasting System (C-IFS) of CAMS were found to better reproduce the observed vertical distribution when using PRM injection heights from GFAS compared to aerosols emissions being prescribed at the surface. The globally available GFAS injection heights introduced and evaluated in this study provide a comprehensive data set for future fire and atmospheric composition modelling studies.
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.
International Cooperative for Aerosol Predictions (ICAP) model 550 nm total AOD RMSE of the 72 h forecast versus corresponding mean AODs for AERONET sites listed in Table 2. Large black dots are ICAP multi‐model ensemble consensus means. Individual models are in small coloured dots. Validation of fine‐ and coarse‐modal AODs and dust AOD is also available in Figure 2.
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.
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•New model for predicting seasonal pollen index for large regions is developed.•Procedure of cluster analysis-based region selection is proposed.•A single universal equation describes the next year seasonal pollen index.•Combination biological and meteorological factors shows the best predicting capacity.•The model was tested for Russia and Belgium to identify the limits of the method.
•N deposition in 1951–2020 totaled 120–470 kg/ha, i.e., annual average 1.8–6.7 kg/ha.•Soils in pine stands were similar, except decreasing N status with the lowest deposition.•Tree ring δ15N was ...different between the lowest and highest N deposition sites.•δ15N in 1951–2020 correlated negatively with total-, ammonium- and nitrate-N depositions.•Temporal development of δ15N and N deposition coincided only on some sites.
Since nitrogen (N) is the main forest-growth limiting nutrient in the boreal region, atmospheric N deposition may be an important source of available soil N. The objective of the study was to determine whether the variation in N deposition is reflected in the stem wood N and in its isotopic signatures (variation of 15N/14N ratios relative to atmospheric N2, reported as δ15N values), as well as in current soil properties with a special focus on N cycling. The study material consisted of twelve Scots pine (Pinus sylvestris L.) stands located along the N deposition gradient from south to north in Finland, representing similar site types with relatively unfertile and N-limited soils. Tree-ring N from 5-year segments, spanning a period of 70 years (1951–2020), were examined. Based on the modelled open-place deposition amounts, annual N deposition increased until around 1990 up to 9 kg/ha/year at the southernmost site and 1 kg/ha/year in the north but decreased substantially thereafter. The deposition of N totaled 472 kg/ha at the southernmost and 123 kg/ha at the northernmost site during the 70-year period. δ15N values in tree rings varied between −5.8 and + 1.3 and were higher at the northern than at the southern sites. Tree-ring δ15N ratio correlated negatively with total N, nitrate-N and ammonium-N depositions. The negative correlation still existed when stand age was used as a controlling factor. The correlation also remained negative when the dataset was divided into periods of generally increasing (1951–1990) and decreasing (1991–2020) deposition, or over 30-year age classes, except for the oldest age class (>90-year-old stands). Humus layer pH did not vary much between the sites, but slight signs of decreasing N status existed from south to north. The temporal development of tree-ring δ15N ratio and the amount of N deposition coincided only on some sites after the effect of stand age was controlled. In conclusion, although climate effects cannot be totally excluded, given the same tree species, mycorrhizal type (ectomycorrhiza), site and soil factors, the N isotopic ratios in tree rings distinguished the highest and the lowest N deposition levels. Within small differences in N deposition other factors affecting the ratio may dominate and tracing of the N input from the past is questionable.
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