Recent developments in monitoring and modelling airborne pollen,a review

Abstract

Public awareness of the rising importance of allergies and other respiratory diseases has led to increased scientific effort to accurately and rapidly monitor and predict pollen, fungal spores and other bioaerosols in our atmosphere. An important driving force for the increased social and scientific concern is the realisation that climate change will increasingly have an impact on worldwide bioaerosol distributions and subsequent human health. In this review we examine new developments in monitoring of atmospheric pollen as well as observation and source-orientated modelling techniques. The results of a Scopus® search for scientific publications conducted with the terms ‘Pollen allergy’ and ‘Pollen forecast’ included in the title, abstract or keywords show that the number of such articles published has increased year on year. The 12 most important allergenic pollen taxa in Europe as defined by COST Action ES0603 were ranked in terms of the most ‘popular’ for model-based forecasting and for forecasting method used. Betula, Poaceae and Ambrosia are the most forecast taxa. Traditional regression and phenological models (including temperature sum and chilling models) are the most used modelling methods, but it is notable that there are a large number of new modelling techniques being explored. In particular, it appears that Machine Learning techniques have become more popular and led to better results than more traditional observation-orientated models such as regression and time-series analyses.     

Regional variations in the pollen season of Betula in Burgundy: two models for predicting the start of the pollination

Today, 10% of the French people suffer frompollen allergy, a world-wide rising ailmentsince the end of the last century.To prevent the appearance of the symptoms, physicians need precise and early information on the pollination date of the main allergenic species. This wascarried out in Burgundy on birch (Betula), which is responsible for frequent pollinoses inMarch–April. Two of the tested methods were both successful and complementary: the sum oftemperatures and the multiple regression. The first one is very precise but only allows forecastingfive days in advance: this is enough for people suffering from rhinitis or conjunctivitis, who muststart a preventive treatment one or two days before pollination is effective. But for asthmaticpatients, the treatment must one or two weeks in advance; the second method, although alittle less precise, is interesting becauseforecasting can be done at least two weeks inadvance. The results, from 1995 to 1998, were used prospectively in 1999.     

宁南山区小麦条锈病发生规律预测预报研究

宁南山区小麦条锈病发生规律预测预报研究谢成君（宁夏西吉县农业技术推广中心，７５６２００）ＳｔｕｄｙｏｆＦｏｒｅｃａｓｔｉｎｇｏｆＯｃｃｕｒｒｅｎｃｅＲｅｇｕｌａｒｉｔｙｏｆＰｕｃｉｎｉａＳｔｒｉｆｏｒｍｉｓＷｅｓｔｉｎＭｏｕｎｔａｉｎＡｒｅａｓｏｆＳ...     

Information Technology and U.S. Energy Consumption: Energy Hog,Productivity Tool,or Both?

A significant debate has emerged with respect to the energy requirements of the Internet. The popular literature has echoed a misleading study that incorrectly suggests the growth of the information economy will require huge amounts of new energy resources. Even correcting the misleading assumptions in that study, discussion on this topic tends to result in a highly limited and unsatisfactory review of many larger issues. Although the evidence suggests a relatively small amount of energy is required to power today's information needs—;about 3% of total electricity consumption in the United States—;the complexity and connectivity of the Internet, and, more generally, the information economy, yield a deep uncertainty about the eventual long-term impact on energy consumption. Although we may not yet be able to generalize about the future long-term energy needs associated with the information economy, the evidence points to continuing technical changes and the growing substitution of knowledge for material resources. These interrelated trends will likely generate small decreases in energy intensity and reduce subsequent environmental impacts relative to many baseline projections. Despite these trends, a number of questions need to be addressed before any solid long-term conclusions might be forthcoming. The article reviews some of the dimensions of these possible changes and suggests further directions for research that may help answer these important questions.     

Detection of chaos: New approach to atmospheric pollen time-series analysis

Pollen and spores are biological particles that are ubiquitous to the atmosphere and are pathologically significant, causing plant diseases and inhalant allergies. One of the main objectives of aerobiological surveys is forecasting. Prediction models are required in order to apply aerobiological knowledge to medical or agricultural practice; a necessary condition of these models is not to be chaotic. The existence of chaos is detected through the analysis of a time series. The time series comprises hourly counts of atmospheric pollen grains obtained using a Burkard spore trap from 1987 to 1989 at Mar del Plata. Abraham's method to obtain the correlation dimension was applied. A low and fractal dimension shows chaotic dynamics. The predictability of models for atomspheric pollen forecasting is discussed.     

Products and Ecological Models: A Population Ecology Perspective

Industrial ecology has used the systems ecology model, with its emphasis on the flows of energy and nutrients, as a tool to find ways to minimize the adverse environmental effects of industrial activity. A second ecosystem model, the population ecology model, emphasizes intra-and inter-specific interactions of many types. When applied to industrial systems, it suggests an increased focus on products. It therefore can provide a useful complement to the systems ecology approach. If industrial processes that are less harmful to the environment are to be successfully implemented, they will have to produce products that can successfully penetrate the marketplace. A number of historical examples are used to illustrate the many product interactions discussed.     

Forecasting of peak population density of the rose grain aphid Metopolophium dirhodum on wheat

Suction trap catches for the period 1969 to 1984 were used to develop a forecasting system for M. dirhodum. This was achieved by using the strong relationships that exist between: a) suction trap catches of Metopolophium dirhodum at Broom's Barn and populations of the aphid in fields near Norwich, and b) winter and spring temperatures and the time when the crop became unsuitable for this aphid. This forecasting system was tested in 1985, 1986, 1987 and 1988 and successfully forecast early in the season that it would not be necessary to apply aphicides in 1987 and 1988. The use of this forecasting system would have correctly indicated that aphicide application against this aphid was unnecessary in 9 out of the 16 seasons from 1969 to 1984.     

A review on temperature and humidity effects on Drosophila suzukii population dynamics

1. Drosophila suzukii is an invasive polyphagous pest of wild and cultivated soft‐skinned fruits, which can cause widespread economic damage in orchards and vineyards.
2. The simulation and prediction of D. suzukii's population dynamics would be helpful for guiding pest management. Therefore, we reviewed and summarized the current knowledge on effects of air temperature and relative humidity on different life cycle parameters of D. suzukii.
3. The literature summary presented shows that high oviposition rates can occur between 18 and 30 °C. Temperatures between 16 and 25 °C resulted in fast and high egg‐to‐adult development success of more than 80%. Oviposition and adult life span were positively affected by high relative humidity; however, the factor humidity is so far rarely investigated.
4. We assume that this is one reason why relative humidity usually is not considered in modelling approaches, which are summarized herein. The high number of recently published research articles on D. suzukii's life cycle suggests that there is already a lot of knowledge available on its biology. However, there are still considerable research gaps mentioned in the literature, which are also summarized herein.
5. Nevertheless, we conclude that sufficient temperature data in the literature are suitable to understand and predict population dynamics of D. suzukii, in order to assist pest management in the field.