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Car-Free Day on a University Campus
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Intensive car use is associated with serious damage to the environment, human health and the economy. It has a great impact on climate change as passenger cars account for nearly half of the worldwide carbon dioxide emissions from the transport sector. Locally, it is a major source of air pollution—mainly from nitrogen oxides, volatile organic compounds and particulate matter emissions, which causes hundreds of thousands premature deaths every year. Moreover, the growing number of cars in urban areas increases congestion and traffic accidents, decreases citizens’ quality of life and brings about considerable economic losses. Although recent research has indicated that car use has reached its peak and has begun a downward trajectory, there are still major concerns about other issues such as improvements in fuel consumption, the pace of electric vehicle adoption and the increasing demand for heavier and more polluting vehicles. More recently, with the onset of the COVID-19 pandemic, tight circulation restrictions significantly reduced the average distance traveled by car. However, post-pandemic trends in car use are uncertain as the combined result of widespread disruptions in public transit, increased substitution of traveling by teleactivities and the rise of active transport remains unclear.

Car-Free Day university campus mobility soft transport policy
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Subjects: Transportation
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Update Date: 06 Apr 2022
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    1. Behavioral Foundations

    Explaining pro-environmental behavior is a challenging task. Many behavioral theories underpin this theoretical endeavor such as the Prospect Theory, the Norm Activation Theory, the Value-Belief-Norm Theory, the Theory of Planned Behavior and the Self-Regulation Theory [1]. Referring specifically to car use, Bamberg et al. [2] state that the most successful approaches are the Theory of Planned Behavior (TPB) and the Norm-Activation Theory (NAT).
    TPB evolved from the Attitude Theory [3][4] and postulates that the individual’s intention to perform a behavior can be predicted from the attitude toward this behavior (opinion/appraisal), subjective norms (social pressure) and his/her perceived behavioral control. The latter can be interpreted as the recognition of the difficulty to perform an action, which is contingent upon many situational constraints such as the place of residence, workplace and other restrictions on how the trip can be made. Additionally, TPB scholars claim that these three factors are caused by a set of salient beliefs derived from information stimuli the individuals receive throughout their lives.
    On a different note, NAT was developed to explain altruistic behavior [5] and was later refined into the Value-Belief-Norm Theory [6] to specifically account for pro-environmental behavior. The rationale behind NAT is that individuals seek to adjust their actions to meet personal norms that are grounded on a set of values and beliefs. The psychological process encompasses the recognition of adverse consequences induced by these actions, the perception of the ability to reduce the resulting threat and the following motivation to implement the behavioral change. It is important to distinguish between subjective and personal norms from TPB and NAT, respectively. The former refers to the expected social pressure of performing (or not performing) certain types of behaviors, whereas the latter is related to the felt obligation of changing the behavior considering the individual’s own moral standards. The significance of the theorized relationships between the constructs claimed by both approaches has been widely demonstrated in many studies [7][8][9].
    More recently, theories considering the inertial effects of habits on travel behavior expanded the explanatory power of travel choice models [10][11][12]. Admittedly, the repetitive nature of travel choices and the cost of searching and evaluating travel alternatives enhance the likelihood of the automaticity of behavior. Empirical studies found that—in relatively stable circumstances—habits moderate the relationship between the antecedents of behavior theorized in TPB and behavior itself [13][14][15]. An important framework that reconciles TPB and the effects of habits is the Theory of Interpersonal Behavior (TIB), first introduced by [16]. This theory agrees with TPB that intention precedes behavior, but only under new or unfamiliar circumstances [12][17], which requires deliberation to form a conscious decision. However, if this decision setting is regularly faced by an individual, the automaticity of behavior will be increasingly more likely to occur.

    2. The Car-Free Day Initiative

    The first initiatives resembling the current Car-Free Day campaigns were held in Switzerland from January to February 1974 as a reaction to the oil crisis [18]. However, it took two decades for these events to reappear with the kind of motivation they are currently acknowledged. Given the growing concern with the adverse effects of car dependency on the environment, public health and the economy, the municipal government of Reykjavik (Iceland) carried out their first Car-Free Day in June 1996 [19]. From 1997 to 1999, similar campaigns were launched in the United Kingdom, France, the Netherlands and Italy. These events were later centralized and articulated in the context of the European Mobility Week, taking place every 3rd week of September from 2000 onwards. Replicates emerged outside Europe shortly after that such as the Car-Free Days in: Bogotá, Colombia (2000); Chengdu, China (2000); Fremantle, Australia (2000); and Toronto, Canada (2001) [20]. Since then, 22 September has become the official celebration date of World Car-Free Day.
    Although two decades of Car-Free Day experiences have passed, research investigating the outcomes of this practice are somewhat limited. Among the existing work, studies concerning the environmental impacts measured on the day of the campaign predominate. By comparing the concentration of pollutants on the day of the event to control periods of time, researchers evaluate whether these differences are statistically significant [21][22][23]. Overall, expressive reductions in pollutants were observed when the measurements were performed at the site of the event. However, when these emissions were surveyed on a city scale, the counterintuitive result of increased pollution was sometimes noted. Farda and Balijepalli [24] argue that by restricting the circulation of cars on the streets within the event site, persistent drivers will detour from original routes, thereby increasing the average distance traveled; consequently, this additional traffic will likely result in increased pollution outside the event area (sometimes outweighing the reduction in the restricted region).
    Beyond these immediate and local effects, more relevant goals of Car-Free Days are to give rise to new habits and promote long-term sustainable behaviors. Considering the rationale from TPB, NAT and TIB frameworks, these campaigns can impact early and middle stages of the decision process (i.e., values, beliefs, norms and attitudes) that activate intentions toward a sustainable behavior. Nonetheless, this kind of investigation is even scarcer in the Car-Free Day literature. It is worth mentioning the work of [25], who found evidence that greater car dependency, measured by frequency of use, implies less acceptability of Car-Free Day initiatives. Similarly, Ref. [26] obtained analogous results by measuring car dependency with the vehicle miles traveled (VMT) indicator. Moreover, both studies observed that the initiative acceptance was higher on weekends than on weekdays.
    It is also important to consider the academic context under which the Car-Free Day event under analysis was undertaken. College campuses are often self-contained communities, where people from different backgrounds, incomes and lifestyles interact [27]. Their infrastructure usually comprises classrooms, offices, shopping places, sports facilities, apartments, open spaces and streets, which can be located in a city center, a suburb or a rural area. Due to the proactive behavior of its members, university communities are considered relevant places to test the implementation of sustainable ways of living [27][28]. In fact, after considerable efforts to investigate mobility patterns and gaps within such contexts [29][30], several guidelines for developing sustainable mobility plans in university campuses have been proposed and discussed in the literature [31][32][33].
    For campuses inside urban areas, mobility issues are mainly related to aspects of walking, cycling, parking management and public transport [30]. Regarding the active travel modes, the most salient problems are: safety at intersections (e.g., lack of speed limitation zones, absence of signage and road marks), personal security (e.g., increased vulnerability to crime) and insufficient pedestrian and cycling networks (e.g., poor infrastructure, lack of street connectivity and proximity) [27][30][34][35][36][37][38][39][40].

    References

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    3. Fishbein, M.; Ajzen, I. Attitudes towards objects as predictors of single and multiple behavioral criteria. Psychol. Rev. 1974, 81, 59–74.
    4. Ajzen, I.; Fishbein, M. Attitude-behavior relations: A theoretical analysis and review of empirical research. Psychol. Bull. 1977, 84, 888–918.
    5. Schwartz, S.H. Normative influences on altruism. Adv. Exp. Soc. Psychol. 1977, 10, 221–279.
    6. Stern, P.C. Toward a coherent theory of environmentally significant behavior. J. Soc. Issues 2000, 56, 407–424.
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    8. Bamberg, S.; Möser, G. Twenty years after Hines, Hungerford, and Tomera: A new meta-analysis of psycho-social determinants of pro-environmental behaviour. J. Environ. Psychol. 2007, 27, 14–25.
    9. Gardner, B.; Abraham, C. Psychological correlates of car use: A meta-analysis. Transp. Res. Part F Traffic Psychol. Behav. 2008, 11, 300–311.
    10. Verplanken, B.A.S. Habit, information acquisition, and the process of making travel mode choices. Eur. J. Soc. Psychol. 1997, 27, 539–560.
    11. Gärling, T.; Axhausen, K.W. Introduction: Habitual travel choice. Transportation 2003, 30, 1–11.
    12. Gardner, B. Modelling motivation and habit in stable travel mode contexts. Transp. Res. Part F Psychol. Behav. 2009, 12, 68–76.
    13. Verplanken, B.; Aarts, H.; Van Knippenberg, A.; Moonen, A. Habit versus planned behaviour: A field experiment. Br. J. Soc. Psychol. 1998, 37, 111–128.
    14. Klöckner, C.A.; Matthies, E. How habits interfere with norm-directed behaviour: A normative decision-making model for travel mode choice. J. Environ. Psychol. 2004, 24, 319–327.
    15. Bamberg, S.; Ajzen, I.; Schmidt, P. Choice of Travel Mode in the Theory of Planned Behavior: The Roles of Past Behavior, Habit, and Reasoned Action. Basic Appl. Soc. Psych. 2003, 25, 175–187.
    16. Triandis, H.C. Interpersonal Behavior; Brooks: Monterey, KY, USA; Cole Pub. Co.: Hawthorne, CA, USA, 1977; ISBN 9780818501883.
    17. Daramy-Williams, E.; Anable, J.; Grant-Muller, S. Car use: Intentional, habitual, or both? Insights from anscombe and the mobility biography literature. Sustainability 2019, 11, 7122.
    18. McKibbin, D. Car Free Days: A Literature Review. Available online: http://nia1.me/2cf (accessed on 20 January 2022).
    19. Badiozamani, G. Car-free days: A shift in the planning paradigm? Nat. Resour. Forum 2003, 27, 300–303.
    20. WCFN World Car-Free Day (WCD). Available online: https://www.worldcarfree.net/wcfd/ (accessed on 23 March 2021).
    21. Gharsheen, S.Z.U.; Haron, Z.; Yahya, K.; Darus, N.; Hezmi, M.A.; Mazlan, A.N. Impact of car free day on foyer building environment. MATEC Web Conf. 2018, 250, 06008.
    22. Nagy, G.; Merényi, A.; Domokos, E.; Rédey, Á.; Yuzhakova, T. Monitoring of air pollution spread on the car-free day in the city of Veszprém. Int. J. Energy Environ. 2014, 5, 679–684.
    23. Rachman, H.O.; Barus, L.S. Impact of Car-Free Day on air pollution and its multifarious advantages in Sudirman-Thamrin Street, Jakarta. Int. J. GEOMATE 2019, 17, 167–172.
    24. Farda, M.; Balijepalli, C. Exploring the effectiveness of demand management policy in reducing traffic congestion and environmental pollution: Car-free day and odd-even plate measures for Bandung city in Indonesia. Case Stud. Transp. Policy 2018, 6, 577–590.
    25. Politis, I.; Gavanas, N.; Pitsiava–Latinopoulou, M.; Papaioannou, P.; Basbas, S. Measuring the Level of Acceptance for Sustainable Mobility in Universities. Procedia-Soc. Behav. Sci. 2012, 48, 2768–2777.
    26. Anwar, M.; Fujiwara, A.; Silaban, T.A.; Aquitana, V. Evaluating Local People Acceptance towards Car Free Day Program Using Structural Equation Model: Study on Surabaya City of Indonesia. In Eastern Asia Society for Transportation Studies, Proceedings of the 8th International Conference of Eastern Asia Society for Transportation Studies, Surabaya, Indonesia, 16–19 November 2009; Eastern Asia Society for Transportation Studies: Tokyo, Japan, 2009; Volume 7, pp. 1–27.
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    28. Tolley, R. Green campuses: Cutting the environmental cost of commuting. J. Transp. Geogr. 1996, 4, 213–217.
    29. Papantoniou, P.; Vlahogianni, E.; Yannis, G.; Attard, M.; Valero-Mora, P.; Campos-Díaz, E.; Tormo-Lancero, M.T. Investigating mobility gaps in university campuses. Adv. Intell. Syst. Comput. 2019, 879, 378–385.
    30. Vlahogianni, E.; Papantoniou, P.; Yannis, G.; Attard, M.; Regattieri, A.; Piana, F.; Pilati, F. Analysis of mobility patterns in selected university campus areas. Adv. Intell. Syst. Comput. 2019, 879, 426–433.
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    32. Papantoniou, P.; Yannis, G.; Vlahogianni, E.; Attard, M.; Regattieri, A.; Piana, F.; Pilati, F. Developing a Sustainable Mobility Action Plan for University Campuses. Transp. Res. Procedia 2020, 48, 1908–1917.
    33. Cadena, R.P.; De Andrade, M.O.; Meira, L.H.; De Freitas Dourado, A.B. The pursuit of a sustainable and accessible mobility on university campuses. Transp. Res. Procedia 2020, 48, 1861–1880.
    34. Ramakreshnan, L.; Fong, C.S.; Sulaiman, N.M.; Aghamohammadi, N. Motivations and built environment factors associated with campus walkability in the tropical settings. Sci. Total Environ. 2020, 749, 141457.
    35. Memon, I.A.; Kalwar, S.; Sahito, N.; Qureshi, S. Average Index Modelling of Campus Safety and Walkability: The Case Study of University of Sindh. Sukkur IBA J. Comput. Math. Sci. 2020, 4, 37–44.
    36. Rybarczyk, G.; Gallagher, L. Measuring the potential for bicycling and walking at a metropolitan commuter university. J. Transp. Geogr. 2014, 39, 1–10.
    37. Stein, P.P.; Rodrigues da Silva, A.N. Barriers, motivators and strategies for sustainable mobility at the USP campus in São Carlos, Brazil. Case Stud. Transp. Policy 2018, 6, 329–335.
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    40. Capasso da Silva, D.; Rodrigues da Silva, A.N. Sustainable modes and violence: Perceived safety and exposure to crimes on trips to and from a Brazilian university campus. J. Transp. Health 2020, 16, 100817.
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      Junior, J.U.P.; Silva, A.N.R.D.; Pitombo, C.S. Car-Free Day on a University Campus. Encyclopedia. Available online: https://encyclopedia.pub/entry/21221 (accessed on 02 February 2023).
      Junior JUP, Silva ANRD, Pitombo CS. Car-Free Day on a University Campus. Encyclopedia. Available at: https://encyclopedia.pub/entry/21221. Accessed February 02, 2023.
      Junior, Jorge Ubirajara Pedreira, Antonio Nelson Rodrigues Da Silva, Cira Souza Pitombo. "Car-Free Day on a University Campus," Encyclopedia, https://encyclopedia.pub/entry/21221 (accessed February 02, 2023).
      Junior, J.U.P., Silva, A.N.R.D., & Pitombo, C.S. (2022, March 31). Car-Free Day on a University Campus. In Encyclopedia. https://encyclopedia.pub/entry/21221
      Junior, Jorge Ubirajara Pedreira, et al. ''Car-Free Day on a University Campus.'' Encyclopedia. Web. 31 March, 2022.
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