Abstract
An aspect of global change currently not well understood is how processes operating on spatial scales finer than those used in recent global circulation models (GCMs) contribute to changes in atmospheric composition and the subsequent changes in climate. We use the ‘IPAT’ formulation as a framework to test relationships among social driving forces and user group greenhouse gas (GHG) emissions in northwestern North Carolina. Using regression, correlation, and bivariate mapping to examine relationships between a suite of socioeconomic variables and GHG emissions for the residential, commercial/industrial, and agricultural end-user categories, we find that various measures of population and affluence serve equally well as explanatory variables.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
