3.3.2. Discussion

The results align with previous studies in that centrally located, pedestrian-friendly areas with mixed land use have lower levels of private car use, travel shorter distances, and thus generate less GHG emissions from local travel [7,12,72,73]. Residential location in travel-related zones was connected both to non-zero emissions and their amount, which suggests that it contributes to multiple aspects of local travel, such as car ownership, travel mode choice, and distances. PEAs, in turn, only contributed to participation in emissions: Respondents with a higher concern for the environment were more likely to rely solely on walking or cycling (Table 6). This is largely in line with previous research that suggests that PEAs are significantly related to car ownership and use [74–76]. Similarly, as in previous studies [14,21] higher incomes were related to higher GHG emissions from local travel, and the likelihood of non-zero emissions, in particular (Table 6). It likely results from differences in car-ownership, which strongly correlated with income in our sample (rs = 0.441, *p* < 0.001, n = 846).

The differences in international travel emissions depending on residential location are also in line with previous studies, with residents of centrally-located dense urban areas generating higher emissions than those living farther away from the centers (Table 8) [15,56,72,77–79]. With regard to PEAs, our results are similar to those presented in a recent paper by Alcock et al. [44], where correlations were found between climate concern and PEBs, but not between environmental concern and actively refraining from air travel. Our results also reinforce the well-known link between income level and international travel [77]. The statistically significant relationship between high education and emissions from international travel, when income is controlled for, has also been previously observed [9,72]. Interestingly, in our results, higher income increased the likelihood of international travel and university education increased the amount of emissions. This suggests that income is an enabling factor, while education level contributes to traveled distances among those who can afford it, for instance, through higher cultural capital and more extensive social networks among the educated [14].

Previous studies suggest that the amount of domestic travel decreases with increasing population density and settlement size [80,81]. These studies, however, primarily compare settlements of different sizes (e.g., large cities with small towns) and not areas within one urban region. Looking at within-city differences in three Nordic cities, a previous study [82] found that distance traveled on weekends increases with distance from the city center, which is in line with the existence of clusters of high

emissions from domestic travel in city outskirts in our results (Figure 6b). However, our regression shows no significant influence of urban zones on the emissions from domestic travel (Table 7). Higher income was positively associated with more domestic travel in our results, as well as in previous research [82], but we found no relationship with education level or gender, which is present elsewhere.

#### **4. Limitations of the Study**

The generalizability of the study is limited due to the single case study research design. Case studies are said to be objective due to the insights and knowledge of the researcher conducting it [83], but their generalizability is low until enough studies have been conducted [84].

The age range for the target group, 25 to 40 years, was relatively narrow. The reason this range was chosen was to minimize the effect of life course variables and generational differences, as people in this age group are usually employed, are independent from their parents, and have grown up in a globalized world, with good access to information and communication technologies [15]. The accuracy of behavior variables not related to travel might be compromised by their reliance on the respondent's perception of their behavior rather than direct observation (see Appendix A, Table A1 for the survey). An example is that instead of having access to information on the actual household energy used, respondents answered questions on how often they try to limit their use of household energy with various actions. The scope of the study is limited by the omission of business travel. This choice was made on an assumption that business trips are often involuntary and driven by different variables than leisure trips. Additionally, they constituted a very small share of the international travel emissions in our sample [15].
