Environmental perception in 33 European countries: an analysis based on partial order
The environmental perception in 33 European countries is based on eight indicators: ‘Air Pollution,’ ‘Drinking Water Pollution and Inaccessibility,’ ‘Dissatisfaction with Garbage Disposal,’ ‘Dirty and Untidy,’ ‘Noise and Light Pollution,’ ‘Water Pollution,’ ‘Dissatisfaction to Spend Time in the City’ and ‘Dissatisfaction with Green and Parks in the City.’ This system of indicators characterizes a set of objects, here 33 countries, with respect to a complex ranking aim, which may be formulated as attitude toward quality in urban life. Usually such system of indicators is analyzed by methods of multicriteria decision aids, such as the well-known PROMETHEE. Here our focus is on what insights bring the indicators if they are not numerically combined to get a ranking index, like that proposed by Numbeo. In the study performed here, we divide the indicator set into two subsets, the first, the so-called pressure set includes indicators of pollution; the other set, denoted as “quality of life in urban areas” (briefly “urban quality”), includes indicators describing the attitude toward urban services. We show the different roles of pressure and urban quality indicators, and thus the role of conflicts among the indicators. We perform a similarity study and apply methods to find the intrinsic importance of indicators. Further we disclose the combined effect of both indicator systems and the role of each indicator for the ranking. The most important factors for the overall environmental perception were found to be ‘Noise and Light Pollution’ and ‘Dissatisfaction with Green and Parks in the City,’ whereas ‘Water Pollution,’ ‘Dissatisfaction with Garbage Disposal’ and ‘Air Pollution’ apparently play a less dominant role.
KeywordsEnvironmental perception Partial ordering Indicator importance
- Borg, I., & Shye, S. (1995). Facet theory: Form and content (advanced quantitative techniques in the social sciences). Thousand Oaks: Sage, Publications, Inc. https://www.goodreads.com/book/show/4190655-facet-theory.
- Bruggemann, R., & Carlsen, L. (2006b). Introduction to partial order theory exemplified by the evaluation of sampling sites. In: R. Bruggemann & L. Carlsen (Eds.), Partial order in environmental sciences and chemistry (pp. 61–110). Berlin: Springer. https://doi.org/10.1007/3-540-33970-1_4.
- Bruggemann, R., & Carlsen, L. (2011). An improved estimation of averaged ranks of partial orders. MATCH Communications in Mathematical and in Computer Chemistry, 65, 383–414. http://match.pmf.kg.ac.rs/electronic_versions/Match65/n2/match65n2_383-414.pdf. Accessed Feb 2018.
- Bruggemann, R., & Carlsen, L. (2012). Multi-criteria decision analyses. Viewing MCDA in terms of both process and aggregation methods: Some thoughts, motivated by the paper of Huang,Keisler and Linkov. Science of the total environment, 425, 293–295. https://doi.org/10.1016/j.scitotenv.2012.02.062.CrossRefGoogle Scholar
- Bruggemann, R., Carlsen, L., Voigt, K. & Wieland, R. (2014). PyHasse software for partial order analysis, In: R. Bruggemann, L. Carlsen, & J. Wittmann (Eds.), Multi-indicator systems and modelling in partial order (pp. 389–423). New York: Springer. https://doi.org/10.1007/978-1-4614-8223-9_19.Google Scholar
- Brüggemann, R., Halfon, E., Welzl, G., Voigt, K., & Steinberg, C. (2001). Applying the concept of partially ordered sets on the ranking of near-shore sediments by a battery of tests. Journal of Chemical Information and Computer Sciences, 41, 918–925. https://doi.org/10.1021/ci000055k.CrossRefGoogle Scholar
- Bruggemann, R., Scherb, H., Schramm, K. W., Cok, I., & Voigt, K. (2014b). CombiSimilarity, an innovative method to compare environmental and health data sets with different attribute sizes example: Eighteen organochlorine pesticides in soil and human breast milk samples. Ecotoxicology and Environmental Safety, 105, 29–35. https://doi.org/10.1016/j.ecoenv.2014.03.031.CrossRefGoogle Scholar
- Bruggemann, R., & Voigt, K. (2012). Antichains in partial order, example: pollution in a German region by Lead, Cadmium, Zinc and Sulfur in the herb layer. MATCH Communications in Mathematical and in Computer Chemistry, 67, 731–744, http://match.pmf.kg.ac.rs/electronic_versions/Match67/n3/match67n3_731-744.pdf.
- Carlsen, L., & Bruggemann, R. (2013). An analysis of the ‘failed states index’ by partial order methodology. Journal of Social Structure, 14(3), 1–32. https://www.cmu.edu/joss/content/articles/volume14/CarlsenBruggemann.pdf. Accessed Feb 2018.
- Colorni, A., Paruccini, M., & Roy, B. (2001). A-MCD-A, Aide multi critere a la decision, multiple criteria decision aiding. JRC European Commission, Ispra; ISBN: 92-8940994-0, EUR Report 19808EN.Google Scholar
- EC (2008). Attitudes of European citizens towards the environment, Special Eurobarometer 295/Wave 68.2—TNS Opinion & Social., European Commission. http://ec.europa.eu/commfrontoffice/publicopinion/archives/ebs/ebs_295_en.pdf. Accessed Feb 2018.
- EEA (2015). The European environment—state and outlook 2015: synthesis report, European Environment Agency, Copenhagen, 2015. https://www.kowi.de/Portaldata/2/Resources/horizon2020/coop/SOER-Synthesis-2015-EN.pdf. Accessed Feb 2018.
- Eurostat (2010). Environmental statistics and accounts in Europe, Eurostat, European Union. https://doi.org/10.2785/48676.
- FDES (2013). Framework for the development of environmental statistics (FDES 2013). https://unstats.un.org/unsd/environment/fdes/FDES-2015-supporting-tools/FDES.pdf. Assessed Feb 2018.
- Fishburn, P.C. (1970). Utility theory for decision making. New York: Wiley. https://link.springer.com/chapter/10.1007/978-1-349-20568-4_40.
- Numbeo (2017). Pollution. https://www.numbeo.com/pollution/ Accessed Sep 2017; see also https://www.numbeo.com/common/motivation_and_methodology.jsp. Accessed Feb 2018.
- Roy, B. (1972). Electre III: Un algorithme de classements fonde sur une representation floue des preferences en presence de criteres multiples. Cahiers du Centre d’Etudes de Recherche Operationelle, 20, 32–43. http://www.lgi.ecp.fr/Biblio/PDF/BR-Cahiers-CERO1978.pdf. Accessed Feb 2018.
- Roy, B., & Vanderpooten, D. (1996). The European school of MCDA: Emergence, basic features and current works. Journal of Multi-Criteria Decision Analysis, 5, 22–38. https://doi.org/10.1002/(SICI)1099-1360(199603)5:1%3c22:AID-MCDA93%3e3.0.CO;2-F.CrossRefGoogle Scholar
- Sachs, J.D. (2015). The age of sustainable development. New York: Columbia University Press. https://cup.columbia.edu/book/the-age-of-sustainable-development/9780231173155.
- Shye, S. (1994). Facet theory. In: T. Husen & T. N. Postlethwaite (Eds.), International encyclopedia of education (pp. 2213–2219). Oxford: Pergamon Press. https://searchworks.stanford.edu/view/2832030. Accessed Feb 2018.
- Voigt, K., Bruggemann, R., Kirchner, M., & Schramm, K. W. (2010). Influence of altitude concerning the contamination of humus soils in the German Alps: a data evaluation approach using PyHasse. Environmental Science and Pollution Research, 17, 429–440. https://doi.org/10.1007/s11356-009-0244-z.CrossRefGoogle Scholar
- Woodstock (2017). 229 Very low-cost cities around the world: Data sources. https://raywoodcockslatest.wordpress.com/2017/06/06/123-low-cost-cities/. Accessed Feb 2018.