**1. Introduction**

Our poor representation of aerosol and cloud interactions in the climate models have led to the largest uncertainty in predicting climate change. Studies have shown that CN can influence climate by changing the properties of clouds. Aerosol particles that act as CN can be broadly classified based on their source into two categories: natural and anthropogenic aerosol. The global source strength of natural aerosol is higher than anthropogenic aerosol; however, certain specific anthropogenic constituents can amplify the aerosol effect on clouds. In addition, the atmospheric trace amounts of soluble gases and organic substances can alter the aerosol properties from both of the sources.

Recent studies have shown that various aerosol properties (size, surface chemistry [hygroscopicity and wettability] and active sites) as a function of temperature and humidity can determine the CN efficiency of aerosol. Atmospheric scientists are working towards finding a relationship between these properties to parameterize the observations in the climate models. But without an adequate knowledge of CN properties this representation cannot be improved further.

The technique of CN separation from the interstitial aerosol has the advantage that by measuring the specific properties of CN, simplifies the model representation task. For example, laboratory and *in-situ* techniques can be used to differentiate the CN in CCN and/or IN measurements and their properties can be measured. Therefore, the modelers can narrow down the physicochemical properties of CN to be incorporated into the representation task. Further, the information of the aerosol chemistry helps to determine aerosol source: natural versus anthropogenic.

© 2012 Kulkarni, licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2012 Kulkarni, licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
