In the US, particulate matter (PM10) is considered an important criteria air pollutant and it is
monitored throughout the country by means of a considerably dense network of stations …

Spatiotemporal Geostatistics provides an efficient mapping estimation method to interpolate
a variable of interest at unsampled spatiotemporal locations based on sparse measured …

The space/time distribution of PM10 in Thailand is modeled using the Bayesian maximum
entropy (BME) method of modern spatiotemporal geostatistics. Three kinds of BME …

Spatiotemporal maps of particulate matter (PM) concentrations contribute considerably to
the understanding of the underlying natural processes and the adequate assessment of the …

The United States Environmental Protection Agency has established a large network of
stations to monitor fine particulate matter of< 2.5 µm (PM2. 5) that is known to be harmful to …

Abstract: This paper analyzes the data on the particular matter of size of 2.5 microns or less
(PM2. 5) for the states of North Carolina, South Carolina and Georgia. The spatio-temporal …

In this paper we illustrate the application of modern functional data analysis methods to
study the spatiotemporal variability of particulate matter components across the United …

Maps of temporal and spatial values of annual averages of daily particulate matter (PM10)
concentrations were generated throughout the state of California using uncertain forms of …

Functional spatio-temporal data naturally arise in many environmental and climate
applications where data are collected in a three-dimensional space over time. The MATLAB …

Trustonlymovement. Life happens at the level of events not of words. Trust movement. A.
Adler As its title suggests, the main goal of this book is the development of advanced fu-tions …