A statistical model of background air pollution frequency distributions.
This paper describes an approach for identifying statistically stable central tendencies in the frequency distributions of time series of observations of background atmospheric pollutants. The data were collected as daily mean values of concentrations of sulfur dioxide and suspended particulate matter at five monitoring stations-three in the USSR, one in Norway, and one in Sweden.The approach uses statistical techniques and methods for constructing multimodal distributions. The problem is subdivided into two parts: first, a decomposition of the observations in order to obtain a description of each season separately and second, an investigation of this description in order to derive statistically stable characteristics of the entire data set. The main hypothesis of the investigation is that dispersion processes interact in such a way that in the zone of influence of one process (near its mode) the 'tails' of the other process are not observed. This permits illumination of interrelations between the physics and the chemistry of the atmosphere.
International Institute for Applied Systems Analysis, Laxenburg, Australia.
M Y
MY
Antonovsky
V M
VM
Buchstaber
E A
EA
Zelenuk