Impact of land use, travel behavior, and socio-economic characteristics on carbon emissions in cool-climate cities, USA.

US cities of cool-climate zone such as Chicago and Boston are witnessing a reduction in carbon emissions potentially due to promoting public transportation and alternative energy resources. It is difficult to validate or deny optimal integration between land-use practices and transportation policies in mitigating carbon emissions due to the lack of urban comparative studies among metropolitan areas. Therefore, this research aims to examine the relationship between land use, travel behavior, and socio-economic characteristics related to carbon dioxide emissions at the zip code level. The research tends to investigate the carbon emissions in four metropolitan regions in cool climatic zone 5 compared to the carbon emissions in all US zip codes, to generate benchmarking predictive models. To this end, nine regression models were developed in this research. These include the US data model, zone 5 model, zone 5 cities model, zone 5 metropolitan areas model, zone 5 micropolitan areas model, Boston model, Chicago model, Columbus model, and Detroit model considering 14 independent variables. The nine models were calibrated and evaluated to include the statistically significant variables having the expected logical sign and acceptable values for t-statistic and multicollinearity. The adjusted R values vary between 0.62 and 0.91, where Boston, Chicago, Columbus, and Detroit models are statistically better than other models. The results indicate that the policies that can be adopted to reduce carbon emissions vary among the models.