A stochastic, three-parameter, Weibull frequency distribution, probability generator was
tested by using theoretical data. Subsequently, it was applied to replace missing values of …

This paper explores the spatio-temporal patterns of particulate matter (PM) in Taiwan based
on a series of methods. Using fuzzy c-means clustering first, the spatial heterogeneity (six …

In the environmental exposure community numerical models are now widely available for a
number of air pollutants. These models provide output exposures at various spatial and …

The vast territories that have been radioactively contaminated during the 1986 Chernobyl
accident provide a substantial data set of radioactive monitoring data, which can be used for …

The incorporation of various sources of physical knowledge is an important aspect of
spatiotemporal analysis and mapping. There exist two major knowledge bases: general …

The past two decades have seen significant advances in mesoscale meteorological
modeling research and applications, such as the development of sophisticated and now …

Health impact studies of air pollution often require estimates of pollutant concentrations at
locations where monitoring data are not available, using the concentrations observed at …

When dealing with spatial data or modelling in a geographical context, identifying an
appropriate scale for analysis is a critical precursor; however, it is difficult to determine due …

Recent interest in near-road exposure to air pollutants and related health and environmental
justice issues has highlighted the importance of improving the accuracy of intraurban …

Several multivariate data analysis methods have been applied to a combination of particle
size and composition measurements made at the Baltimore Supersite. Partial least squares …