Future research directions and data requirements for developing ambient ozone guidelines or standards for agroecosystems

The ambient air quality in Central Europe appears to have the potential to adversely affect the productivity of the agroecosystems in that geographic area. Therefore, there is a need to develop, validate, and apply air pollutant exposure-plant response models to explain the relationships between the stochastic chemical climate and ecosystem responses. Such models will have to include numerical terms for the effective air pollutant exposure regime to account for the fluxes of matter, energy and information within the ecosystem and its components. The structure and function of the ecosystem which are influenced by the air pollutant flux can be described by a combination of empirical and mechanistic models. A discussion of such an approach is presented in this paper.     

Air pollution and diseases of the respiratory tracts in pre-school children: A transfer function model

The purpose of the present statistical analysis was the assessment of the relation between time series of environmental factors and of frequencies of diseases of the respiratory system in pre-school children. During about one year, daily measurements of air pollutants and climatic variables were taken. During the same period of time two series of medical data were collected: (i) The daily relative number of pre-school children, exhibiting diseases of the respiratory tracts who either came to the outpatients' clinic of the children's hospital or were reported by paediatricians in Basle (ENTRIES). (ii) The daily relative frequency of symptoms of the respiratory tracts observed in a group of randomly selected pre-school children (SYMPTOMS).By means of transfer function models the relation between the two target variables and the explaining variables was analysed. Several practical problems did arise: Choice of the appropriate transformation of the different series, interpretation of the crosscorrelation function using different methods of prewhitening, time splitting and nonstationarity of the crosscorrelation structure. In particular, it was found that after prewhitening the crosscorrelation function between the explanatory series SO₂ and the response series SYMPTOMS changes with time. While during the winter period an instantaneous relation between these two series (and to a lesser extent between NO₂ and SYMPTOMS) was identified, no such relation was found for the other seasons.