Characteristics of Grass Pollen Seasons in Areas of Southern Spain and the United Kingdom

Spatial and temporal variations in daily grass pollen counts and weather variables are described for two regions with different bio-geographical and climatic regimes, southern Spain and the United Kingdom. Daily average grass pollen counts are considered from six pollen-monitoring sites, three in southern Spain (Ciudad Real, Córdoba and Priego) and three in the United Kingdom (Edinburgh, Worcester and Cambridge). Analysis shows that rainfall and maximum temperatures are important factors controlling the magnitude of the grass pollen season in both southern Spain and the United Kingdom, and that the strength and direction of the influence exerted by these variables varies with geographical location and time.

Factors that Determine the Severity of Betula spp. Pollen Seasons in Poland (Poznań and Krakow) and the United Kingdom (Worcester and London)

The aim of this paper is to analyse variations in the severity of Betula pollen seasons, particularly in relation to meteorological parameters at four sites, Poznań and Krakow in Poland and Worcester and London in the United Kingdom. Results show that there is a significant relationship between Betula pollen season severity and weather conditions in the year before pollination as well as conditions in the same year that pollen is released from the plant. Furthermore, it is likely that the magnitude of birch pollen seasons in Poznań, Worcester and London is linked in some way to different phases of the North Atlantic Oscillation (NAO). Significant positive relationships exist between birch pollen counts at Poznań and temperatures, rainfall and averages of the NAO in the year before pollination. An opposite relationship is evident at the two sites studied in the British Isles. There were significant positive correlations between the severity of birch pollen seasons recorded at Worcester and London and temperatures and averages of the NAO during the year of pollination, and negative correlations with similar variables from the previous year. In addition, Betula pollen seasons in Krakow do not appear to be influenced by the NAO, which is probably the result of Krakow having a more continental climate.

Counselling Psychology in the United Kingdom

Counselling psychology within the UK has grown over the last three decades, adapting to many changes in the field of applied psychology, whilst remaining true to its core values and humanistic origins. The identity of counselling psychology is strongly rooted in a relational stance and applied psychology, where attention to psychological formulation is given to improve psychological functioning and well-being. This article outlines a brief history of counselling psychology in the UK, the training process, credentialing and looks at some important challenges and future directions for counselling psychology in the UK. A proportion of the members from the British Psychological Society’s division of counselling psychology (DCoP, N = 148) took part in the study. Participants provided demographic, training, employment, workplace and career pathway information obtained through an online questionnaire distributed to all DCoP members. On the whole, DCoP members are working in a variety of areas within the UK and the findings of this article contribute to the international study comparing counselling psychology across the globe.

Changes in the Pollen Seasons of the Early Flowering Trees Alnus spp. and Corylus spp. in Worcester United Kingdom 1996-2005

Previous work on Betula spp. (birch) in the UK and at five sites in Europe has shown that pollen seasons for this taxon have tended to become earlier by about 5–10 days per decade in most regions investigated over the last 30 years. This pattern has been linked to the trend to warmer winters and springs in recent years. However, little work has been done to investigate the changes in the pollen seasons for the early flowering trees. Several of these, such as Alnus spp. and Corylus spp., have allergens, which cross-react with those of Betula spp., and so have a priming effect on allergic people. This paper investigates pollen seasons for Alnus spp. and Corylus spp. for the years 1996–2005 at Worcester, in the West Midlands, United Kingdom. Pollen data for daily average counts were collected using a Burkard volumetric trap sited on the exposed roof of a three-storey building. The climate is western maritime. Meteorological data for daily temperatures (maximum and minimum) and rainfall were obtained from the local monitoring sites. The local area up to approximately 10 km surrounding the site is mostly level terrain with some undulating hills and valleys. The local vegetation is mixed farmland and deciduous woodland. The pollen seasons for the two taxa investigated are typically late December or early January to late March. Various ways of defining the start and end of the pollen seasons were considered for these taxa, but the most useful was the 1% method whereby the season is deemed to have started when 1% of the total catch is achieved and to have ended when 99% is reached. The cumulative catches (in grains/m3) for Alnus spp. varied from 698 (2001) to 3,467 (2004). For Corylus spp., they varied from 65 (2001) to 4,933 (2004). The start dates for Alnus spp. showed 39 days difference in the 10 years (earliest 2000 day 21, latest 1996 day 60). The end dates differed by 26 days and the length of season differed by 15 days. The last 4 years in the set had notably higher cumulative counts than the first 2, but there was no trend towards earlier starts. For Corylus spp. start days also differed by 39 days (earliest 1999 day 5, latest 1996 day 44). The end date differed by 35 days and length of season by 26 days. Cumulative counts and lengths of season showed a distinct pattern of alternative high (long) and low (short) years. There is some evidence of a synchronous pattern for Alnus spp.. These patterns show some significant correlations with temperature and rainfall through the autumn, winter and early spring, and some relationships with growth degree 4s and chill units, but the series is too short to discern trends. The analysis has provided insight to the variation in the seasons for these early flowering trees and will form a basis for future work on building predictive models for these taxa.

A 30-Day-Ahead Forecast Model for Grass Pollen in North London, United Kingdom

A 30-day ahead forecast method has been developed for grass pollen at north London. The total period of the grass pollen season is covered by eight multiple regression models, each covering a 10-day period running consecutively from 21st May to 8th August. This means that three models were used for each 30-day forecast. The forecast models were produced using grass pollen and environmental data from 1961-1999 and tested on data from 2000 and 2002. Model accuracy was judged in two ways: the number of times the forecast model was able to successfully predict the severity (relative to the 1961-1999 dataset as a whole) of grass pollen counts in each of the eight forecast periods on a scale of one to four; and the number of times the forecast model was able to predict whether grass pollen counts were higher or lower than the mean. The models achieved 62.5% accuracy in both assessment years when predicting the relative severity of grass pollen counts on a scale of one to four, which equates to six of the eight 10-day periods being forecast correctly. The models attained 87.5% and 100% accuracy in 2000 and 2002 respectively when predicting whether grass pollen counts would be higher or lower than the mean. Attempting to predict pollen counts during distinct 10-day periods throughout the grass pollen season is a novel approach. The models also employed original methodology in the use of winter averages of the North Atlantic Oscillation to forecast 10-day means of allergenic pollen counts.

Constructing a 7-day Ahead Forecast Model for Grass Pollen at North London, United Kingdom

A number of media outlets now issue medium-range (~7 day) weather forecasts on a regular basis. It is therefore logical that aerobiologists should attempt to produce medium-range forecasts for allergenic pollen that cover the same time period as the weather forecasts. The objective of this study is to construct a medium-range (< 7 day) forecast model for grass pollen at north London. The forecast models were produced using regression analysis based on grass pollen and meteorological data from 1990-1999 and tested on data from 2000 and 2002. The modelling process was improved by dividing the grass pollen season into three periods; the pre-peak, peak and post peak periods of grass pollen release. The forecast consisted of five regression models. Two simple linear regression models predicting the start and end date of the peak period, and three multiple regression models forecasting daily average grass pollen counts in the pre-peak, peak and post-peak periods. Overall the forecast models achieved 62% accuracy in 2000 and 47% in 2002, reflecting the fact that the 2002 grass pollen season was of a higher magnitude than any of the other seasons included in the analysis. This study has the potential to make a notable contribution to the field of aerobiology. Winter averages of the North Atlantic Oscillation were used to predict certain characteristics of the grass pollen season, which presents an important advance in aerobiological work. The ability to predict allergenic pollen counts for a period between five and seven days will benefit allergy sufferers. Furthermore, medium-range forecasts for allergenic pollen will be of assistance to the medical profession, including allergists planning treatment and physicians scheduling clinical trials.

Examining High Magnitude Grass Pollen Episodes at Worcester, United Kingdom, Using Back-Trajectory Analysis

Trajectory analysis is a valuable tool that has been used before in aerobiological studies, to investigate the movement of airborne pollen. This study has employed back-trajectories to examine the four highest grass pollen episodes at Worcester, during the 2001 grass pollen season. The results have shown that the highest grass pollen counts of the 2001 season were reached when air masses arrived from a westerly direction. Back-trajectory analysis has a limited value to forecasters because the method is retrospective and cannot be employed directly for forecasting. However, when used in conjunction with meteorological data this technique can be used to examine high magnitude events in order to identify conditions that lead to high pollen counts.