The first test found a regression model, CO2= 57.78+ 0.03(percentmiles) +1.46(percentpop) +0.61(faresperexpense).

The p-value for the regression model is <0.0001, which is low enough to reject the null hypothesis in favor of the alternative, which is that at least one parameter estimate is not zero. Percentmiles and faresperexpense both shared p-values that were <0.0001, and therefore those variables in the model made for statistically significant predictors of the emissions variable. Percentpop, however, had a p-value that was 0.1024, which is not low enough to reject the null hypothesis. To confirm this, the 95% confidence interval was (-0.29, 3.21). Since a 0 value falls within the interval, the variable is not a good predictor of emissions.

By applying the regression equation to the Atlanta area, it is found that increasing the percent population covered by the service area from the current 35.7% to 50%, carbon dioxide would increase by 0.0475 million metric tons per year. By increasing the percent of the city covered by the service area from 18.8% to 25%, carbon dioxide pollution would increase by 0.0236 million metric tons per year. If the ratio of fares earned to total operating cost were to decrease from 28% to 20%, the amount of carbon dioxide pollution would decrease by 0.0488 million metric tons per year.The second test performed was a one-way ANOVA, which would reveal if there was a relationship between mode of transportation and CO2 pollution. While the p-value is <0.0001, indicating a rejection of the null hypothesis, a low R2 value of 0.0092 indicates that only 0.92% of variation in carbon dioxide emissions is explained by the different modes of transportation. In the context of Atlanta, even though the mean levels of CO2 are found to be significantly different between modes, the fact that such a small percent of that variation is caused by mode suggests that changing the modes of transportation used in the city will not have a large effect on pollution.

Nikki Lyons , Advisor: Dr. Jun TuDepartment of Geography and Anthropology, Kennesaw State University

ABSTRACT

OBJECTIVE and METHOD

RESULT and DISCUSSION

CONCLUSION

Figure 4: Amount of Carbon Dioxide Pollution by Mode of Transportation

Availability of Public Transport and Its Effect of Carbon Dioxide Pollution in Atlanta

Table 1: Abbreviations of Mode of Transportation ExplainedCarbon dioxide pollution is a problem that plagues many

major cities in the United States. For this research, the goal is to discover the effect of public transportation availability in major cities on carbon dioxide pollution in that state. The data for this research came from two different sources- the American Public Transport Association and the Environmental Protection Agency. By comparing different variables related to public transport to statewide carbon dioxide emissions from transportation sources, the goal is to be able to predict the outcome of expanding public transportation services in the Atlanta metro area.The first test used a regression procedure, which created a model combining the percentarea, percentpop, and faresperexpense in order to predict carbon dioxide emissions in million metric tons per state (CO2). The null hypothesis is that the parameter estimates for each variable will all be equal to zero, meaning the variable has no effect on emissions. The alternative hypothesis is that at least one of the variables will have a nonzero parameter estimate.A second test was performed using a one-way ANOVA to analyze the differences between the mean amounts of CO2 produced by mode. The null hypothesis would be that each mode of transport would produce the same amount of carbon dioxide emissions. The alternative hypothesis would be that at least one mean differs from the rest.

It would be expected that emissions would increase with faresperexpense, because the higher the cost of riding, the more people will be likely to take their own vehicles. For the percentarea , however, a negative relationship was expected. Instead, the more urban area covered by service, the higher the CO2 emissions are. It was also surprising to see that percentpop was not a good predictor of emissions.For future research, a variable relating my current variables to total population of the urban area may be helpful, or possibly using different variables to predict emissions may provide more appropriate estimates.

CB Commuter Bus (Bus systems that connect outlying areas with a central

city.) CC Cable Car

(Streetcar attached to moving cable beneath street and powered by engines not on board vehicle)

CR Commuter Rail (An electric or diesel propelled railway for urban

passenger service operating between a central city and adjacent suburbs.)

DR Demand Response (Passenger cars, vans or small buses operating in

response to calls from passengers to transit operator.) DT Demand Response Taxi

(Demand response operated by taxicab providers.) FB Ferry Boat HR Heavy Rail

(Electric railway with the capacity for a heavy volume of traffic.)

IP Inclined Plane (A railway operating over exclusive right of way on steep grades with powerless vehicles propelled by

moving cables attached to the vehicles and powered by engines or motors at a central location not onboard the vehicle. The special tramway types of vehicles have

passenger seats that remain horizontal while the undercarriage (truck) is angled parallel to the slope.)

LR Light Rail (Electric railway with light volume of traffic compared

to heavy rail.) MB Motor Bus

(Rubber tired passenger vehicles operating on fixed routes over roadways.)

MG Monorail/ Automated Guide way RB Bus Rapid Transit (Fixed-route bus operating with its

own separate right of way, with traffic signal priority.) SR Streetcar Rail

(Rail system operating entire routes predominantly on mixed-traffic roads.)

TB Trolley Bus (Manually steered rubber tire vehicles operating on city

streets propelled by overhead wires.) VP Vanpool/ Shuttle

(Vans, small buses, and other vehicles operated as a ride sharing arrangement, transporting passengers directly

between home and a set destination.) YR Hybrid Rail

(Typically operated light rail type vehicles as diesel multiple unit trains operated separately from freight

traffic.)

The focus of this research is to be able to relate public transportation availability to levels of carbon dioxide emissions produced by transportation, with particular focus on the city of Atlanta. Certain variables related to public transportation may be used as predictors in levels of carbon dioxide emissions (in million metric tons per state), including percent of urban area covered by public transportation service (percentarea), the ratio of fares earned to total operating cost (faresperexpense), percent of the urban population living within the service area (percentpop), and the mode of transport used (mode). Using multiple regression and ANOVA tests, the data set was analyzed to find any relationships amongst the variables. It was found that the percentarea and faresperexpense were significant predictors in determining carbon dioxide emissions, while percentpop was found not to be significant. The ANOVA that was performed analyzing mean amounts of emissions by mode found that while the means for each group were significantly different, the variation among modes only accounts for 0.9% of variation in emissions.

Figure 1: City of Atlanta Transportation Maps

Figure 3: U.S. GHG Emissions from Transportation Sources, 2010 (CO2 equivalent)

Figure 2: Total U.S. Greenhouse Gas Emissionsby Economic Sector in 2012