Implications of GHG emissions

Studies have shown that every mode of transport, comprising of walking, cycling, car, bus, train and taxi, each has its advantages. Active transport (walking and cycling) results in zero GHG emissions, public transport results in less GHG emissions due to a high number of passengers on buses and trains, while private transport (particularly by car) provides door to door transportation but also results in much higher GHG emissions due to more fuel consumption (Walsh et al., 2008; Pan et al., 2013; Pongthanaisawan and Sorapipatana, 2013).

The evidence base does not currently include travel GHG emissions from participants- dominated sport (running). Several studies have examined transport GHG emissions from mega sporting events such as the Commonwealth Games and Olympic games, although both participants and

Chapter 5. Participant-dominated sport: Runners GHG emissions from travel, nature relatedness and mental wellbeing

153 spectators were responsible for the GHG emissions (Roper, 2006; Shaw et al., 2007; Collins et al., 2009; Shaw et al., 2010; Sahu et al., 2011). Moreover, there is well-documented evidence that travel to marathon races by spectators; organisers, volunteers and participants contribute to GHG emissions (Bullard et al., 2007; Robbins et al., 2007; Krugell and Saayman, 2013).

This study found that car travel dominated overall emissions (84.70% of total GHG emissions), followed by train (12%), bus (2.90%) and taxi (0.40%). Participants that use active transport such as walking and cycling to running locations emitted zero GHG emissions. This research suggest that increase in active transport will not just help to reduce traffic congestion on the roads but ultimately reduce GHG emissions, a finding similar to a previous study (Simons et al., 2013).

The mean GHG emissions of participants from their travel to running location was 0.62 kgCO₂e, which was far less than the mean GHG emissions from travel from spectator dominated sports (football) of 4.74kgCO₂e in Chapter 3.The extrapolations of travel GHG emission of runners in England for 2012 included all forms of athletes: track and field, road running and other running such as recreational running alone or with a running group. This amounted to about 2 million runners per week and, with a mean GHG emission of 0.62 kgCO₂e to and from running locations for a running session, resulted in 64,480 tCO₂e. The GHG emissions from indoor running location (0.86kgCO₂e,n=174) was higher than the outdoor (0.54 kgCO₂e,n=466), a change in the way runners travel to running location such as gym could reduce their environmental impact, and the findings can be used for policy changes. Participants travel average distance of 7.4km and their running session last for averagely 6.1km. If participants had started their run from home or the office, their travel GHG emissions could have reduced because they travel more distance than their running distance.

The findings show that the behavioural choice of participants going to a gymnasium produced higher GHG emissions than to other outdoor running locations. Participants in rural environments

Chapter 5. Participant-dominated sport: Runners GHG emissions from travel, nature relatedness and mental wellbeing

produced less GHG emissions compared to suburban and urban environments, which can be compared to a previous study on residential CO2 emissions in suburban and urban China (Donglan et al., 2010). This is possibly due to less open space to engage in physical activities in suburban and urban settings, unlike the rural environment, and also the population density is higher in urban than rural environments.

The result of multiple regression analysis on the outcome variable showed that, to varying degrees, the independent variables of distance travelled and urban environment affected levels of GHG emissions and explained 70.6% of the variance, leaving just 29.4% unexplained. The outcome variable also positively correlated with the independent variable (distance travelled). These influencing factors are in line with the evidence base (Goodman et al., 2012; Rentziou et al., 2012;

Gately et al., 2013). As with the present findings, the evidence in published literature regarding GHG emissions used the carbon footprint method, comprising of recording, analysing, reporting and managing GHG emissions. More importantly, behavioural changes by people to use more environmentally friendly modes of travel are vital to reduce and manage GHG emissions (Ramaswami et al., 2011; Wright et al., 2011; Andrews et al., 2013; Cadarso et al., 2015; Li et al., 2015).

5.4.3 Mental wellbeing

The findings of this study show that taking part in running has a beneficial effect on mental wellbeing among participants of varying gender and ages; this is similar to past studies (Thompson Coon et al., 2011; Gaudlitz et al., 2015). The average (mean) WEMWBS scores of the participants was 51.19, SD=8.23; this is within the ‘average wellbeing’ range reported in chapter 4; This is similar to the average mental wellbeing found in Scottish Survey 2012 and at the study of spectator dominated sport (football) in chapter 4 of mean wellbeing score of 51.52.

In terms of how mental wellbeing trait was affected by independent variables: gender and age, had no effect on mental wellbeing measures similar to findings in chapter 4. Mental wellbeing was not

Chapter 5. Participant-dominated sport: Runners GHG emissions from travel, nature relatedness and mental wellbeing

155 affected by running location (indoor or outdoor) and running environment. However, mental wellbeing was higher in lone runners compared to group runners. However, mental wellbeing did not correlate with nature connectedness. This is contrary to findings from past studies that showed positive correlation between mental wellbeing and connection with nature (Newton, 2007; Nisbet et al., 2011; Bragg, 2014).