Responsible consumption and production in the European Union. A partial order analysis of Eurostat SDG 12 data

Lars Carlsen; Lars Carlsen

doi:10.3934/GF.2021003

Green Finance

2021, Volume 3, Issue 1: 28-45. doi: 10.3934/GF.2021003

Previous Article Next Article

Research article Special Issues

Responsible consumption and production in the European Union. A partial order analysis of Eurostat SDG 12 data

Lars Carlsen ^,

Awareness Center, Linkøpingvej 35, Trekroner, DK-4000 Roskilde, Denmark

Received: 17 December 2020 Accepted: 20 February 2021 Published: 23 February 2021
JEL Codes: C3, C6, C8

The UN Sustainable Development Goal 12, responsible consumption and production, is a key element in a sustainable development of our planet as it is closely linked to the exploitation of renewable and non-renewable resources. The present study focuses on five main indicators selected by Eurostat as key factors for the development of the SDG 12, i.e., 1: resource productivity, 2: average CO₂ emissions from new passenger cars, 3: circular material use rate, 4: generation of waste excluding major mineral wastes and 5: consumption of toxic chemicals for the 27 member states of the European Union, the data being analyzed applying partial ordering methodology that constitutes an advantageous decision support tool. Based on the first 4 indicators the 27 EU member states have been mutually ranked finding France, Italy, and Malta as the best and Bulgaria and Estonia as the worst among the 27 countries in complying with the SDG 12 targets. Studying the temporal development, a slightly positive tendency was observed. The most important indicator, looking at the whole EU appears to be the generation of waste, whereas, e.g., the CO₂ emission apparently is the key issue for France and Bulgaria, whereas the circular material use rate is the most important in the case of Greece. The temporal development of the consumption of toxic chemicals was separately analyzed disclosing that the amount of non-toxic waste has increased whereas a decrease in chemicals hazardous to human health and to the environment was noted. The results constitute important for authorities and regulator in their effort to select actions in order better to comply with the SDG 12 targets.
- sustainability,
- SDG 12,
- consumption,
- production,
- EU,
- partial ordering,
- ranking,
- indicator importance
Citation: Lars Carlsen. Responsible consumption and production in the European Union. A partial order analysis of Eurostat SDG 12 data[J]. Green Finance, 2021, 3(1): 28-45. doi: 10.3934/GF.2021003

Related Papers:

Abstract

The UN Sustainable Development Goal 12, responsible consumption and production, is a key element in a sustainable development of our planet as it is closely linked to the exploitation of renewable and non-renewable resources. The present study focuses on five main indicators selected by Eurostat as key factors for the development of the SDG 12, i.e., 1: resource productivity, 2: average CO₂ emissions from new passenger cars, 3: circular material use rate, 4: generation of waste excluding major mineral wastes and 5: consumption of toxic chemicals for the 27 member states of the European Union, the data being analyzed applying partial ordering methodology that constitutes an advantageous decision support tool. Based on the first 4 indicators the 27 EU member states have been mutually ranked finding France, Italy, and Malta as the best and Bulgaria and Estonia as the worst among the 27 countries in complying with the SDG 12 targets. Studying the temporal development, a slightly positive tendency was observed. The most important indicator, looking at the whole EU appears to be the generation of waste, whereas, e.g., the CO₂ emission apparently is the key issue for France and Bulgaria, whereas the circular material use rate is the most important in the case of Greece. The temporal development of the consumption of toxic chemicals was separately analyzed disclosing that the amount of non-toxic waste has increased whereas a decrease in chemicals hazardous to human health and to the environment was noted. The results constitute important for authorities and regulator in their effort to select actions in order better to comply with the SDG 12 targets.

References

[1]	Annoni P, Bruggemann R, Carlsen L (2015) A multidimensional view on poverty in the European Union by partial order theory. J Appl Stat 42: 535–554. doi: 10.1080/02664763.2014.978269
[2]	Bruggemann R, Annoni P (2014) Average heights in partially ordered sets. MATCH Commun Math Comput Chem 71: 117–142.
[3]	Bruggemann R, Carlsen L (2006a) Partial Order in Environmental Sciences and Chemistry, Springer, Berlin. Available from: https://www.springer.com/gp/book/9783540339687.
[4]	Bruggemann R, Carlsen L (2006b) Introduction to partial order theory exemplified by the evaluation of sampling sites, In: Bruggemann R and Carlsen L (Eds.), Partial Order in Environmental Sciences and Chemistry, Springer, Berlin, 61–110.
[5]	Bruggemann R, Carlsen L (2011) An improved estimation of averaged ranks of partial orders. MATCH Commun Math Comput Chem 65: 383–414.
[6]	Bruggemann R, Carlsen L (2021) Attempt to test impact values for multi-indicator systems—exemplified by gender equality. Qual Quant.
[7]	Bruggemann R, Münzer B (1993) A Graph-Theoretical Tool for Priority Setting of Chemicals. Chemosphere 27: 1729–1736. doi: 10.1016/0045-6535(93)90153-V
[8]	Bruggemann R, Patil GP (2011) Ranking and Prioritization for Multi-indicator Systems—Introduction to Partial Order Applications, Springer, New York.
[9]	Bruggemann R, Voigt K (1995) An Evaluation of Online Databases by Methods of Lattice Theory. Chemosphere 31: 3585–3594. doi: 10.1016/0045-6535(95)00207-O
[10]	Bruggemann R, Voigt K (2008) Basic Principles of Hasse Diagram Technique in Chemistry. Comb Chem High Throughput Screen 11: 756–769. doi: 10.2174/138620708786306005
[11]	Bruggemann R, Carlsen L, Voigt K, et al. (2014) PyHasse Software for Partial Order Analysis: Scientific Background and Description of Selected Modules, In: Bruggemann R, Carlsen L, and Wittmann J (Eds), Multi-indicator Systems and Modelling in Partial Order, Springer, New York, 389–423.
[12]	Bruggemann R, Halfon E, Welzl G, et al. (2001) Applying the Concept of Partially Ordered Sets on the Ranking of Near-Shore Sediments by a Battery of Tests. J Chem Inf Comp Sci 41: 918–925. doi: 10.1021/ci000055k
[13]	Bubley R, Dyer RM (1999) Faster random generation of linear extensions. Discr Math 201: 81–88. doi: 10.1016/S0012-365X(98)00333-1
[14]	Carlsen L (2018) Happiness as a sustainability factor. The World Happiness Index. A Posetic Based Data Analysis. Sustain Sci 13: 549–571.
[15]	Carlsen L, Bruggemann R (2013) Partial order methodology a valuable tool in chemometrics. J Chemometrics 28: 226–234. doi: 10.1002/cem.2569
[16]	Carlsen L, Bruggemann R (2014) The "Failed State Index" Offers More than Just a Simple Ranking. Soc Indic Res 115: 525–530. doi: 10.1007/s11205-012-9999-6
[17]	Carlsen L, Bruggemann R (2018) Environmental perception in 33 European countries an analysis based on partial order. Environ Dev Sustain 22: 1873–1896. doi: 10.1007/s10668-018-0267-z
[18]	Eurostat (2020a) Sustainable development in the European Union. Monitoring report on progress towards the SDGs in an EU context, 2020 Edition. Available from: https://ec.europa.eu/eurostat/statistics−explained/index.php/Sustainable_development_in_the_European_Union.
[19]	Eurostat (2020b) Consumption of toxic chemicals. Available from: https://ec.europa.eu/eurostat/tgm/table.do?tab=table&init=1&language=en&pcode=sdg_12_10&plugin=1.
[20]	Eurostat (2020c) Resource productivity and domestic material consumption (DMC). Available from: https://ec.europa.eu/eurostat/tgm/table.do?tab=table&init=1&language=en&pcode=sdg_12_20&plugin=1.
[21]	Eurostat (2020d) Average CO₂ emissions from new passenger cars. Available from: https://ec.europa.eu/eurostat/tgm/table.do?tab=table&init=1&language=en&pcode=sdg_12_30&plugin=1.
[22]	Eurostat (2020e) Circular material use rate. Available from: https://ec.europa.eu/eurostat/tgm/table.do?tab=table&init=1&language=en&pcode=sdg_12_41&plugin=1.
[23]	Eurostat (2020f) Generation of waste excluding major mineral wastes. Available from: https://ec.europa.eu/eurostat/tgm/table.do?tab=table&init=1&language=en&pcode=sdg_12_50&plugin=1.
[24]	Eurostat (2020g) Gross value added in environmental goods and services sector. Available from: https://ec.europa.eu/eurostat/tgm/table.do?tab=table&init=1&language=en&pcode=sdg_12_61&plugin=1.
[25]	Munda G (2008) Social Multi-Criteria Evaluation for a Sustainable Economy. Springer-Verlag, Berlin. Available from: https://www.springer.com/la/book/9783540737025 (Accessed Dec. 2020).
[26]	Newlin J, Patil GP (2010) Application of partial order to stream channel assessment at bridge infrastructure for mitigation management. Environ Ecol Stat 17: 437–454. doi: 10.1007/s10651-010-0162-8
[27]	SDG (2017) Sustainable Development Goals. Available from: https://sdgs.un.org/goals (Accessed Dec. 2020).
[28]	Sørensen PB, Mogensen BB, Carlsen L, et al. (2000) The influence of partial order ranking from input parameter uncertainty. Definition of a robustness parameter Chemosphere 41: 595–601.
[29]	Tseng ML, Wu KJ, Hu J, et al. (2018) Decision-making model for sustainable supply chain finance under uncertainties Int J Product Econ 205: 30–36.
[30]	Tseng ML, Lim KM, Wu KJ (2019) Improving the benefits and costs on sustainable supply chain finance under uncertainty. Int J Product Econ 218: 308–321. doi: 10.1016/j.ijpe.2019.06.017
[31]	UNDP (2020) Goal 12 Targets. Available from: https://www.undp.org/content/undp/en/home/sustainable-development-goals/goal-12-responsible-consumption-and-production/targets.html (Accessed Dec. 2020).
[32]	Voigt K, Bruggemann R, Scherb H, et al. (2013) Organochlorine Pesticides in the Environment and Humans Necessity for Comparative Data Evaluation, In: Wittmann J. and Müller M (Eds), Simulation in Umwelt−und Geowissenschaften, Workshop Leipzig 2013, Shaker-Verlag, Aachen, 9–22.

Reader Comments

Your name:*

Email:*
© 2021 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)