Pilvi Siljamo

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.

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.

Long distance pollen transport cause problems for determining the timing of birch pollen season in Fennoscandia by using phenological observations

The male flowering and leaf bud burst of birch take place almost simultaneously, suggesting that the observations of leaf bud burst could be used to determine the timing of birch pollen release. However, long‐distance transport of birch pollen before the onset of local flowering may complicate the utilization of phenological observations in pollen forecasting. We compared the timing of leaf bud burst of silver birch with the timing of the stages of birch pollen season during an eight year period (1997–2004) at five sites in Finland. The stages of the birch pollen season were defined using four different thresholds: 1) the first date of the earliest three‐day period with airborne birch pollen counts exceeding 10 grains m−3 air; and the dates when the accumulated pollen sum reaches 2) 5%; 3) 50% and 4) 95% of the annual total. Atmospheric modelling was used to determine the source areas for the observed long‐distance transported pollen, and the exploitability of phenological observations in pollen forecasting was evaluated. Pair‐wise comparisons of means indicate that the timing of leaf bud burst fell closest to the date when the accumulated pollen sum reached 5% of the annual total, and did not differ significantly from it at any site (p<0.05; Student‐Newman‐Keuls test). It was found that the timing of leaf bud burst of silver birch overlaps with the first half of the main birch pollen season. However, phenological observations alone do not suffice to determine the timing of the main birch pollen season because of long‐distance transport of birch pollen.

Pest insect immigration warning by an atmospheric dispersion model, weather radars and traps

In an experimental set‐up in and around Helsinki, Finland (60°N, 25°E), we have detected pest insect immigration using weather radars and insect traps in the field. This study was part of a project to develop a system to give warning of a possible arrival of long‐range migrant insect pests. Bird‐cherry aphid, Rhopalosiphum padi, and diamondback moth, Plutella xylostella, were found on the ground following migrations in warm airstreams at the end of May 2007. This migration episode was successfully forecast by the meteorologists in the project team. For the summer 2008, we developed a pest insect immigration alarm system based on SILAM, a Finnish Meteorological Institute atmospheric dispersion model. The first important pest insect immigration occurred in late June, bringing bird‐cherry aphids. Our alarm system correctly produced a warning of this immigration. We studied the migration path in the observed events in 2007 and 2008 with the help of the atmospheric dispersion model. Weather radars frequently showed rain echo over the area, but there was also a lot of echoes originating from the migrating insects. Using the polarimetric weather radar in Helsinki, we could differentiate insects from other sources of echoes. Insects were common in layers below 1 km, and were observed up to height of about 2.5 km. Using Doppler weather radars we were able to observe the speed and direction of the migration. The experiment showed that an atmospheric dispersion model is an effective tool for predicting the movement of airborne migrants. The alarm system would work still better, if the sources of the immigrants were known in more detail. In addition, the very simple modelling of airborne migration should be refined. Weather radars, and especially polarimetric systems, are able to detect insect migrations and reveal details of the phenomenon not obtainable by other means.

Airborne Pollen Transport

This chapter reviews the present knowledge and previous developments concerning the pollen transport in the atmosphere. Numerous studies are classified according to the spatial scales of the applications, key processes considered, and the methodology involved. Space-wise, local, regional and long-range scales are distinguished. An attempt of systematization is made towards the key processes responsible for the observed patterns: initial dispersion of pollen grains in the nearest vicinity of the sources at micro-scale, transport with the wind, mixing inside the atmospheric boundary layer and dry and wet removal at the regional scale, and the long-range dispersion with synoptic-scale wind, exchange between the boundary layer and free troposphere, roles of dry and wet removal, interactions with chemicals and solar radiation at the large scales.

An Approach to Simulation of Long-Range Atmospheric Transport of Natural Allergens: An Example of Birch Pollen

Diseases of the respiratory system due to aeroallergens, such as rhinitis and asthma, are major causes of a demand for healthcare, loss of productivity and an increased rate of morbidity. The overall prevalence of seasonal allergic rhinitis (allergic reactions in the upper respiratory system) in Europe is approximately 15 %; the asthma rates vary from 2.5% 10 %; etc. Pollenosis accounts for 12 45 % of all allergy cases. The sensitisation to pollen allergens is increasing in most European regions. The adverse health effects of allergens can be reduced by pre-emptive medical measures. However, their planning requires reliable forecasts of start time of high pollen concentrations in air, as well their levels and durations (Rantio-Lehtimaki, 1994; RantioLehtimaki and Matikainen, 2002). The currently available forecasts are based solely on local observations and do not consider the pollen transport from other regions or countries (Frosig and Rasmussen, 2003). However, there is a convincing evidence that long-range transport of pollen can significantly modify pollinating seasons (first of all, the start time and duration of high atmospheric pollen concentrations) in many European regions (Corden et al., 2002; Malgorzata et al., 2002; Hjelmroos, 1992). This transport causes unforeseen and sudden increases of concentrations of pollen that can occur up to a month before the start of the local pollen season. The long-range transport can substantially increase the concentrations of allergenic pollen also during the local flowering season. This is an important problem for Northern Europe and especially for Finland, where the flowering takes place later in spring. The most important pollinating species in respect to long-range transport are the birch ones, and Finland is neighbored by the Baltic

Forward and Inverse Simulations with Finnish Emergency Model Silam

An evolution of the term “emergency modeling” to a large extent reflects the evolution of the other term: “public safety”. The starting point was the Chernobyl catastrophe, when comparably safe plant suddenly turned to be one of the biggest threat to public health and life around European continent. Since then, it has become evident that the list of potentially dangerous installations can be extended further and further. The new threats of terrorists applying supposedly well-controlled agents like biological weapon or “non-standard” arms like dirty bomb, are forcing the scientists and decision- making authorities to review the methods and instruments used for the information support of the decision-making. In particular, it may appear that the source of the dangerous agent is not linked to any existing installation or simply unknown. Second, the net of potential sources is so dense that there can be no time to run the model to estimate the area of risk — it has to be known “in advance”. Current paper presents some of possible responses to these challenges implemented in the modeling framework SILAM.

Development and Applications of Biogenic Emission Term as a Basis of Long-Range Transport of Allergenic Pollen

This study presents a birch pollen long-range transport forecasting system, which is developed at Finnish Meteorological Institute together with the Aerobiology Unit of the University of Turku, and the Department of Forest Ecology of the University of Helsinki. The forecasting system consists of several submodels. It is based on a numerical weather prediction (NWP) model. The use of good-quality NWP model is essential for the forecasting system, as the sub-models for the pollen emission, that is a dispersion model, a pollen release model and a phenological model for the starting date of flowering, are all sensitive to the quality of the weather data. Numerical forecasts of birch pollen concentration in springs have been done at FMI since 2005 and the model has been developed throughout these years. The latest version of the forecasting system gives realistic result, despite a tendency to underestimate pollen concentrations. Especially the timing of long-range transport episodes is well predicted.

Chapter 7.4 On influence of long-range transport of pollen grains onto pollinating seasons

Abstract Pollen grains can be transported over hundreds and even thousands of kilometres and significantly affect pollen concentration in many regions making it less dependent upon the local conditions. In this study we have used the Finnish operational dispersion model SILAM to delineate birch pollen source areas as well as to forward simulations for pollen long-range transport. We have considered an episode of very high birch pollen concentration in Finland in April 1999 both in forward and inverse point of view. As a representative of easterly located areas, we considered also Moscow region. Source delineation for early pollen peaks is done for years 1999, 2002 and 2004.

Air Quality Forecasting During Summer 2006: Forest Fires as One of Major Pollution Sources in Europe

This paper considers an influence of wild-land fires on air quality in Europe during spring and summer seasons of 2006 and discusses the experience of its forecasting by the SILAM modelling system that considers anthropogenic, natural and fire-related emission sources. The emission of anthropogenic pollutants was based on the EMEP database, while the fire emission was deducted from the near-real-time MODIS satellite retrievals, which were assimilated daily by the emission pre-processor. The system also included allergenic birch pollen as described by Siljamo et al. (this volume). We analysed several episodes and compared an impact of fires with contribution from anthropogenic sources. For example, exceptionally high concentrations of nearly all pollutants were detected in Central, Eastern and Northern Europe in April and May of 2006. Simulations showed that this episode was formed by contributions of all three main sources: major wild-land fires in Russia, substantial amounts of anthropogenic air pollutants accumulated for a few days over Eastern Europe, and intensive birch flowering in Russia. A synchronization role was played by meteorology. Specific weather conditions promoted formation of the multi-component pollution cloud, which was then transported across most of Central and Northern Europe causing widespread allergic symptoms and other illnesses associated to poor air quality. Several other episodes were more localised. Thus, August of 2006 was particularly difficult in Portugal and Spain, but also in Finland. The model predictions were compared with available information from ground-based monitoring sites and satellites retrievals. The agreement was fairly good, especially for timing of rise and fall of concentrations, while the absolute levels were usually under-estimated by the model. That pointed to necessity to extend the list of sources of, in particular, atmospheric aerosols to include wind-blown dust, sea salt, nitrates, SOA, etc, and also to refine the parameterization of emission from biomass burning.