Regional variable, pollution

Among the multivariate statistical techniques that have been used as source-receptor models, factor analysis is the most widely employed. The basic objective of factor analysis is to allow the variation within a set of data to determine the number of independent causalities, i.e. sources of particles. It also permits the combination of the measured variables into new axes for the system that can be related to specific particle sources. The principles of factor analysis are reviewed and the principal components method is illustrated by the reanalysis of aerosol composition results from Charleston, West Virginia. An alternative approach to factor analysis. Target Transformation Factor Analysis, is introduced and its application to a subset of particle composition data from the Regional Air Pollution Study (RAPS) of St. Louis, Missouri is presented. 

Ahiksson A. (2001) Regional variability of Cd, Hg, Pb and C concentrations in different horizons of Swedish forest soils. Water Air Soil Pollut. Focus 1, 325-341. 

Amini M., Khademi H., Afyuni M., Abbaspour K.C. Variability of available cadmium in relation to soil properties and landuse in an arid region in central Iran. Water Air Soil Pollut 2005 162 205-218. 

The presence of water-soluble macromolecules in solution at submicel-lar concentrations has been reported to enhance the water solubility of hydro-phobic organic chemicals in several instances [19, 106, 113]. The presence of macromolecules in solution can enhance the apparent solubility of solutes by sorptive interactions in the solution phase. The processes by which macromolecules enhance the solubility of pollutants are probably variable as a function of the particular physical and chemical properties of the system. A macromolecule possessing a substantial nonpolar region can sorb a hydrophobic molecule, thereby minimizing the interfacial tension between the solute and the water. 

Water is the most common solvent used by humans. It is readily available in most parts of the world and is used for drinking, washing, cleaning, and industrially as a solvent. Water quality varies widely from region to region, from heavily polluted to purified drinking water quality. Water hardness and impurities are even more variable depending on the source of the water. 

Cripps, G. C. (1992). Baseline levels of hydrocarbons in seawater of the southern ocean natural variability and regional patterns. Marine Pollution Bulletin, 24, 109-14. 

TABLE 2 Variables and Experimental Region" for the Investigation of the Pilot Level Ti02 Photocatalyzed Oxidative Degradation of Organic Pollutants Contained in an Industrial Waste Water [12]... 

This chapter will focus on PM ambient concentrations, which are key variables for exposure models, and are generally obtained by direct measurements in air quality monitoring stations. However, depending on the location and dimension of the region to be studied, monitoring data could not be sufficient to characterise PM levels or to perform population exposure estimations. Numerical models complement and improve the information provided by measured concentration data. These models simulate the changes of pollutant concentrations in the air using a set of mathematical equations that translate the chemical and physical processes in the atmosphere. 

Attempts to measure DMS in air masses influenced by polluted continental regions have yielded quite different results, with a higher degree of variability and less well defined diurnal cycles. In the North Atlantic, Andreae et al. (12) used trajectory analysis to separate their data set into air masses of continental... 

Our observations are similar to those of Blanck et al. (2003), who studied the variability in zinc tolerance in periphyton communities sampled from 15 European river stretches using the PICT concept. Due to differences in water chemistry, (history of) metal pollution, species composition, and other biotope characteristics, the regional uncertainty factor for Zn was estimated to range from 1.7 to 4.3, and the interregional uncertainty factor from 2.4 to 8.6, when extrapolating periphyton tolerances from river to river (Blanck et al. 2003). 

It would appear that while the ambient level of S02 is quite low away from pollution sources, it can be much higher and quite variable in industrial and populated regions. 

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