Public engagement on urban air pollution: an exploratory study of two interventions
- 470 Downloads
The use of portable sensors to measure air quality is a promising approach for the management of urban air quality given its potential to improve public participation in environmental issues and to promote healthy behaviors. However, not all the projects that use air quality mobile sensors consider the potential effects of their use on the attitudes and behaviors of non-expert individuals. This study explores the experiences, perceptions, attitudes, and behavioral intentions of 12 participants who used a real-time NO2 sensor over a period of 7 days in the metropolitan area of Barcelona and compares them with 16 participants who did not have access to the device but rather to documentary information. The study design is based on recombined focus groups who met at the beginning and end of a 7-day activity. The results suggest that the experience with the sensors, in comparison with the traditional information, generates greater motivation among participants. Also, that the use of the sensor seems to support a more specific awareness of the problem of air pollution. In relation to risk perception, the textual and visual information seems to generate stronger beliefs of severity among participants. In both groups, beliefs of low controllability and self-efficacy are observed. Neither using the sensor nor reading the documentary information seems to contribute positively in this sense. The results of the study aim to contribute to the design of public involvement strategies in urban air pollution.
KeywordsAir pollution Portable sensors Public engagement Attitudes Focus groups
- Aoki, P. M., Honicky, R. J., Mainwaring, A., Myers, C., Paulos, E., Subramanian, S., & Woodruff, A. (2008). Common sense: mobile environmental sensing platforms to support community action and citizen science. [http://www.communitysensing.org/pdf/AokiUbiComp2008CommonSenseDemo.pdf].
- Bales, E., Nikzad, N., Quick, N., Ziftci, C., Patrick, K., & Griswold, W. (2012). Citisense: mobile air quality sensing for individuals and communities. Design and deployment of the Citisense mobile air-quality system. Proceedings of the 6th International Conference on Pervasive Computing Technologies for Healthcare, 3–6. Doi: 10.4108/icst.pervasivehealth.2012.248724
- Boyatzis, R. E. (1998). Transforming qualitative information: thematic analysis and code development. Londres: Sage.Google Scholar
- Crowston, K., & Wiggins, A. (2011). Supporting citizen involvement in scientific research. HICSS 2011 SCI Workshop. Retrieved from http://conway.isri.cmu.edu/hicss2011-sci-workshop/crowston-hicss-supporting.pdf.
- European Environment Agency (2013). Air quality in Europe—2013 report. Denmark: Luxembourg: Publications Office of the European Union.Google Scholar
- Fereday, J., & Muir-Cochrane, E. (2006). Demonstrating rigor using thematic analysis: a hybrid approach of inductive and deductive coding and theme development. Int. J. Qual. Methods, 5, 1–11.Google Scholar
- Gardner, G. T., & Stern, P. C. (2002). Environmental problems and human behavior. Boston: Pearson Custom Publishing.Google Scholar
- Goldman J., Shilton K., Burke J. A., Estrin D., Hansen M., Ramanathan N., Reddy S, Samanta V., Srivastava M. and West R. (2009). Participatory sensing: a citizen-powered approach to illuminating the patterns that shape our world. Woodrow Wilson International Center for Scholars. Washington, D.C., USA. http://scholarworks.umass.edu/esence/362/
- Irwin, A. (1995). Citizen science: a study of people, expertise and sustainable development. London: Routledge.Google Scholar
- Jordan, R. C., Gray, S. A., Howe, D. V., Brooks, W. R., & Ehrenfeld, J. G. (2011). Knowledge gain and behavioral change in citizen-science programs. Conservation Biology, 25(6), 1148–1154.Google Scholar
- Kanhere, Salil, S 2013. “Participatory sensing: crowdsourcing data from mobile smartphones in urban spaces.” International Conference on Distributed Computing and Internet Technology. Springer Berlin Heidelberg.Google Scholar
- Krueger, R. A., & Casey, M. A. (2000). Focus groups: a practical guide for applied research. Thousand Oaks: Sage Publication.Google Scholar
- Kuznetsov, S., & Paulos, E. (2010). Participatory sensing in public spaces: activating urban surfaces with sensor probes. In Proceedings of the 8th ACM Conference on Designing Interactive Systems (pp. 21–30). ACM.Google Scholar
- Louv, R., & Fitzpatrick, J. W. (2012). Citizen science: public participation in environmental research. In J. L. Dickinson & R. Bonney (Eds.), Cornell University Press.Google Scholar
- McKenzie-Mohr, D., & Smith, W. (1999). Fostering sustainable development. An introduction to community-based social marketing. Ontario: New Society Publishers 160 pp.Google Scholar
- Neidell, Matthew(2006). “Public information and avoidance behavior: do people respond to smog alerts?.” Center for Integrating Statistical and Environmental Science Technical Report 24.Google Scholar
- Noonan, D. S. (2011). Smoggy with a chance of altruism: using air quality forecasts to drive behavioral change. AEI Outlook Series. American Enterprise Institute. AEI Working Paper, 8, 14.Google Scholar
- Paulos E., Honicky R. J. and Hooker B. (2009). Citizen science: enabling participatory urbanism. In: M. Foth (Ed.), Handbook of research on urban informatics: the practice and promise of the real-time city. Hershey, Pennsylvania, USA, pp. 414–436. Goldman et al. 2009: 3.Google Scholar
- Stieb, D. M., Paola, J., & Neuman, K. (1995). Do smog advisories work? Results of an evaluation of the Canadian Smog Advisory Program. Canadian Journal of Public Health. Revue Canadienne de Sante Publique, 87(3), 166–169.Google Scholar
- WHO. (2013). Health effects of particulate matter. Policy implications for countries in Eastern Europe, Caucasus and central Asia. World Health Organization [online]. http://www.euro.who.int/__data/assets/pdf_file/0006/189051/Health-effects-of-particulatematter-final-Eng.pdf.