3.3.1. Results

Participation in and amount of emissions from all travel categories increased with increased income, and the most notable difference in participation in international travel was found between respondents with very low and very high income (Figure 5). Single people had the lowest participation rates and mean annual emissions from all travel categories. Families had the highest participation rates and mean annual local travel emissions, and couples had the highest participation rates and mean annual emissions from national travel. Mean emissions from international and national travel increased with education level while local travel emissions decreased. Very little difference was found in participation in local travel between education levels. Respondents with a medium level of education had the highest participation scores, closely followed by the high education category. Women had slightly higher participation percentages than men throughout all travel categories. They had higher mean annual emissions in the national and international travel categories, while men had slightly higher emissions from local travel.

**Figure 5.** Mean annual local, national, and international per capita travel emissions (kg CO2 eq) and participation (%) in emissions by gender, household type, income, education, and zone categories.

Respondents from car-oriented zones had the highest participation rates (93%) and mean annual emissions from local travel, while respondents from pedestrian-oriented zones had the lowest participation rates (70%) and mean annual emissions from local travel. On the other hand, residents of pedestrian-oriented zones had the highest participation rates and annual emissions in international travel. Participation rates and annual emissions in national travel were similar throughout the zones. Spatial clustering was the strongest in the case of emissions from local travel (Moran's I = 0.22, *p* < 0.001), and not significant in the case of domestic or international travel (Table 5), although there were significant local clusters of high emissions (Figure 6b, Figure 7).


**Table 5.** Results of spatial analyses of local, domestic, and international travel emissions.

**Figure 6.** (**a**) Hot spot (Getis-Ord Gi\*) map of GHG emissions from local travel (n = 831). Areas highlighted in red have values higher than expected, and areas highlighted in blue have values lower than expected.; (**b**) hot spot (Getis-Ord Gi\*) map of GHG emissions from domestic leisure travel (n = 831). Areas highlighted in red have values higher than expected, and areas highlighted in blue have values lower than expected.

**Figure 7.** Hot spot (Getis-Ord Gi\*) map of GHG emissions from international leisure travel (n = 831). Areas highlighted in red have values higher than the regional average, and areas highlighted in blue have values lower than the regional average.

Education level and household type did not have a statistically significant relationship to local travel, neither on the participation rates nor the amount of emissions (Table 6). High income, being a woman, and living in car-oriented zones were all positively associated with participation in local travel emissions. The largest odds ratio was found with participants of a very high income, who were more likely to participate in local travel emissions than the lowest income group.

**Table 6.** Binary logistic regression on participation in local travel emissions (1) and multiple linear regression on the amount of local travel emissions (1a) of local per capita annual emissions (CO2 eq) of those participating.


Notes. \**p* < 0.05. \*\**p* < 0.01. \*\*\**p* < 0.001. <sup>1</sup> Model 1: Binary logistic regression on participation in emissions from local travel. Education level, household type, income category, gender, zones, and PEAs are independent variables. Model 1a: Multiple linear regression on the natural logarithm of the amount of yearly emissions from local travel. Education level, household type, income category, gender, zone, and PEAs are independent variables. <sup>2</sup> Hosmer-Lemeshow test of goodness-of-fit.

The only significant contributor to the amount of local emissions was residential location. Residents of the car-oriented zones were most likely to participate in local travel and had the highest emissions from local travel. PEAs had a negative effect on participation in emissions from local travel, but did not have a statistically significant effect on the amount of emissions.

Binary logistic regressions performed with the data split by residential zones showed that although residents with high PEA scores of all three zones were less likely to participate in local travel emissions, only the coefficients from the pedestrian-oriented zone data were statistically significant (see Table A3 in Appendix C). This suggests that those with high PEA scores living in the central pedestrian zone are able to adopt sustainable urban mobility. No statistical significance was found between PEA and international or national travel when data was split by zones (see Tables A4 and A5 in Appendix C).

Neither PEA factor scores nor residential zones had a significant relationship to domestic travel emission participation or the amount of emissions (Table 7). Single people generated significantly more emissions from travel within the country than couples and families did. Wealthier respondents were significantly more likely to participate in travel and generated more emissions. Although the amount of emissions generated by women was not significantly different to men, they were more likely to participate in national travel. Education level had no significant effect on emissions from domestic travel.



Notes. \**p* < 0.05. \*\**p* < 0.01. \*\*\**p* < 0.001. <sup>1</sup> Model 2: Binary logistic regression on participation in emissions from domestic travel. Education level, household type, income category, gender, zones, and PEAs are independent variables. Model 2a: Multiple linear regression on the natural logarithm of the amount of yearly emissions from domestic travel. Education level, household type, income category, gender, zones, and PEAs are independent variables. <sup>2</sup> Hosmer-Lemeshow test of goodness-of-fit.

Respondents with high income and living in pedestrian-oriented zones were more likely to participate in international travel emissions, but for those participating the amount of emissions were not significantly different from other zones or income categories (Table 8). Families had a significantly negative relationship with international travel emissions and the highly educated had a significantly positive relationship with emissions.

**Table 8.** Binary logistic regression on participation in international travel emissions (3) and multiple linear regression on the amount of travel emissions (3a) of international per capita annual emissions (CO2 eq) of those participating.



**Table 8.** *Cont.*

Notes. \**p* < 0.05. \*\**p* < 0.01. \*\*\**p* < 0.001. <sup>1</sup> Model 3: Binary logistic regression on participation in emissions from international travel. Education level, household type, income category, gender, zones, and PEAs are independent variables. Model 3a: Multiple linear regression on the natural logarithm of the amount of yearly emissions from international travel. Education level, household type, income category, gender, zones, and PEAs are independent variables. <sup>2</sup> Hosmer-Lemeshow test of goodness-of-fit.

Spatial autocorrelation and residual analysis was performed on travel models 1a, 2a, and 3a (see Appendix D, Table A6). No spatial autocorrelation was found, using global Moran's I with a threshold of *p* < 0.05, and the residuals showed no signs of heteroskedasticity; they were symmetrically distributed, showed no signs of patterns, and were clustered towards the middle of the plots.
