Hybrid approach for site selection using impact assessment and principal component analysis

Ugandhar Reddy Kondamadugula, University of Texas at El Paso


Principle component analysis (PCA) is used to analyze week data of emission of particulate material from the Residential community. In this Thesis we selected five sites maps where sensors are arranged to collect particulate materials PM0.25, PM 10. Impact Assessment on the site areas are done in the first case, the results Impact Assessment on the site shows that the Global warming potential is really high at the site when the analysis is run for hundred years the Global warming potential has a very high impact on Environment leading to various health hazards. Secondly Principal Component Analysis is used to find out if there is any correlation among the emission of particulate materials collected at different locations or not. PC loading Indicates there is significant correlation between the site maps while collecting the data for area 1 area4 and area3and area2 has correlation in case of PM 10 and in case PM 0.25 area3, areae4 and area1, area2 and area5 area correlated respectively. As there is correlation among the site data we can suggest them that they chose different site maps for collecting the data or we can suggest them to avoid the any one of the site which is having strong correlation with another site.^

Subject Area

Engineering, Industrial

Recommended Citation

Kondamadugula, Ugandhar Reddy, "Hybrid approach for site selection using impact assessment and principal component analysis" (2009). ETD Collection for University of Texas, El Paso. AAI1473873.