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There is growing evidence to support an increase in air temperature over recent decades, with significant effects on aeroallergens such as pollen. It is generally accepted that the trend will continue, and become even more pronounced in the future.Global climate change is already affecting, and will continue to affect, with earlier floral initiation, the timing of the production of allergenic pollen. In addition, a warmer climate might lead to a longer pollen season and more days with high pollen counts. It could also increase the allergen content of pollens, and result in extension of plant species towards the poles and higher altitudes. Finally, rising levels of atmospheric CO₂ are likely to reinforce these trends.These predictions are subject to uncertainties that may lead to outcomes that differ materially from what is expected. Understanding the magnitude and direction of the changes affecting pollinisation is critical in order to quantify the future allergic disease burden and model the impacts of different climate change scenarios.Climate change influences the production, distribution, dispersion and allergenicity of anemophilous pollen and the growth and distribution of weeds, grasses and trees that produce it. These changes in aeroallergens and subsequent human exposure could affect the prevalence and severity of allergic disorders. There is, therefore, an important public health issue that requires development and implementation of appropriate response strategies without delay.

Pollens of Poaceae are among the most allergenic pollen in Europe with pollen of birch. It is therefore useful to elaborate models to help pollen allergy sufferers. The objective of this study was to construct forecast models that could predict the first day characterized by a certain level of allergic risk called here the Starting Date of the Allergic Risk (SDAR). Models result from four forecast methods (three summing and one multiple regression analysis) used in the literature. They were applied on Nancy and Strasbourg from 1988 to 2005 and were tested on 2006. Mean Absolute Error and Actual forecast ability test are the parameters used to choose best models, assess and compare their accuracy. It was found, on the whole, that all the models presented a good forecast accuracy which was equivalent. They were all reliable and were used in order to forecast the SDAR in 2006 with contrasting results in forecasting precision.

The pollen of Ambrosia, highly allergenic, can be found in high quantities in the French regions of Burgundy, Auvergne and mostly a great part of the Rhône-Alpes region. The aim of this study was to establish some forecast models of the Starting Date of the Pollen season (SDP) of Ambrosia, in order to provide early information to allergists and allergic people. The pollen data came from the Hirst trap set up in Lyon since 1987 by the RNSA, and the meteorological data for the same period were provided by Météo-France. Two models were used, a sum of daily average temperatures and a multiple regression on all the 10-day period meteorological data. The results were quite accurate, except for 2003 with the temperature sums, probably because of very special meteorological conditions. So the models will have to be updated in this way.

The french network of aeropalynology includes traps very close together and vast areas without any trap as well. A study was launched in order to optimise this network, without the number of traps increasing too much. Five criteria are successively reviewed to rationalise the spatial cover. Equi-distance of sites has to be balanced by the number of concerned people. But the need for having long time series is incentive to delete only as a last resort the traps which are reliable for a long time. Moreover, apart from the general network, some local or regional features make indispensable a trap in such-and-such a place (health resort), or justify a higher density of traps in such-and-such an area (the Rhône-Alpes concerning ragweed, the Mediterranean South concerning cypress).

The purpose of this paper was to verify the effect of pollen peaks on blood eosinophilia in an all and sundry population, including allergic as well as non-allergic subjects, so that we can open up new horizons in the understanding and prevention of pollinosis. Daily eosinophilia counts of hospital patients were measured at the time of a blood checkup (1996-1998), and divided into six classes. Those data were compared to daily pollen counts of twelve taxa, coming from the Hirst trap of Dijon (France). An eosinophilia increase occurred when hazel, hornebeam, birch, oak, grasses, ragweed and plantain were present in high concentration. In other cases, only simultaneous presence of several taxa seemed to play a part, because of cross-reactivity or polysensitization. Lastly, Cupressaceae-Taxaceae and ragweed were seen as increasing eosinophilia in seemingly non allergic people. The analysis of eosinophilia in the general population was able to reveal potential allergic patients and potential allergic diseases.