Advertisement

Environment, Development and Sustainability

, Volume 16, Issue 4, pp 925–956 | Cite as

Integrating energy and land-use planning: socio-metabolic profiles along the rural–urban continuum in Catalonia (Spain)

  • Pere Ariza-Montobbio
  • Katharine N. Farrell
  • Gonzalo Gamboa
  • Jesus Ramos-Martin
Article
First Online:
Received:
Accepted:

Abstract

Abandoning fossil fuels and increasingly relying on low-density, land-intensive renewable energy will increase demand for land, affecting current global and regional rural–urban relationships. Over the past two decades, rural–urban relationships all over the world have witnessed unprecedented changes that have rendered their boundaries blurred and have lead to the emergence of “new ruralities.” In this paper, we analyze the current profiles of electricity generation and consumption in relation to sociodemographic variables related to the use of time and land across the territory of Catalonia, Spain. Through a clustering procedure based on multivariate statistical analysis, we found that electricity consumption is related to functional specialization in the roles undertaken by different types of municipalities in the urban system. Municipality types have distinctive metabolic profiles in different sectors depending on their industrial, services or residential role. Villages’ metabolism is influenced by urban sprawl and industrial specialization, reflecting current “new ruralities.” Segregation between work activity and residence increases both overall electricity consumption and its rate (per hour) and density (per hectare) of dissipation. A sustainable spatial organization of societal activities without the use of fossil fuels or nuclear energy would require huge structural and sociodemographic changes to reduce energy demand and adapt it to regionally available renewable energy.

Keywords

Energy metabolism Electricity MuSIASEM Distributed energy generation Functional urban specialization Renewable energy Socio-metabolic profiles 
This is a preview of subscription content, log in to check access.

Notes

Acknowledgments

We would like to thank Joan Esteve, Albert Casanovas, Meritxell Baraut and Mercé García from the Catalan Institute of Energy (ICAEN), Dolors Olivares, Marta Masats and Maite Caramazana from the Catalan Institute of Statistics (IDESCAT) for their kind delivery of the data we requested. We also thank the anonymous reviewers for their careful reading. Their insights helped to improve substantially the text. We would like also thank Joan Martinez-Alier for his intellectual support. We also would like to thank Arnim Scheidel, Violeta Cabello and Alevgul Sorman who provided helpful comments and insights to previous versions of this paper. We thank Marta Borrós who helped in GIS techniques and maps elaboration and Sara Mingorría who helped in statistical analysis. The fourth author acknowledges support from (i) the Consolidated Research Group on “Economic Institutions, Quality of Life and the Environment,” SGR2009–00962; and (ii) the Spanish Ministry for Science and Innovation project HAR-2010-20684-C02-01. The first author acknowledges support from the Spanish Government funded research project Metabolismo Social y Conflictos Ambientales (CSO2010 21979).

References

  1. Abdi, H., & Williams, L. J. (2010). Principal component analysis. Wiley Interdisciplinary Reviews Computational Statistics, 2(4), 433–459.CrossRefGoogle Scholar
  2. Abramsky, K. (Ed.). (2010). Sparking a worldwide energy revolution. Social struggles in the transition to a post-petrol world. Oakland, Edinburgh, Baltimore: AK Press.Google Scholar
  3. Ackermann, T., Andersson, G., & Söder, L. (2001). Distributed generation: A definition. Electric Power Systems Research, 57(3), 195–204.CrossRefGoogle Scholar
  4. Alanne, K., & Saari, A. (2006). Distributed energy generation and sustainable development. Renewable and Sustainable Energy Reviews, 10(6), 539–558.CrossRefGoogle Scholar
  5. Alcántara, V., & Duarte, R. (2004). Comparison of energy intensities in European Union countries. Results of a structural decomposition analysis. Energy Policy, 32(2), 177–189.CrossRefGoogle Scholar
  6. Alcántara, V., & Padilla, E. (2003). “Key” sectors in final energy consumption: An input-output application to the Spanish case. Energy Policy, 31(15), 1673–1678.CrossRefGoogle Scholar
  7. Brereton, F., Bullock, C., Clinch, J. P., & Scott, M. (2011). Rural change and individual well-being: The case of Ireland and rural quality of life. European Urban and Regional Studies, 18(2), 203–227. doi: 10.1177/0969776411399346.CrossRefGoogle Scholar
  8. Brounen, D., Kok, N., & Quigley, J. M. (2012). Residential energy use and conservation: Economics and demographics. European Economic Review, 56(5), 931–945.CrossRefGoogle Scholar
  9. Camarero, L. A. (Ed.). (2009). The rural population in Spain. From disequilibrium to social sustainability. Barcelona: La Caixa Foundation.Google Scholar
  10. Catalán, B., Saurí, D., & Serra, P. (2008). Urban sprawl in the Mediterranean? Patterns of growth and change in the Barcelona Metropolitan Region 1993–2000. Landscape and Urban Planning, 85(3–4), 174–184.CrossRefGoogle Scholar
  11. Cussó, X., Garrabou, R., & Tello, E. (2006). Social metabolism in an agrarian region of Catalonia (Spain) in 1860–1870: Flows, energy balance and land use. Ecological Economics, 58(1), 49–65.CrossRefGoogle Scholar
  12. D’Alisa, G., & Cattaneo, C. (2012). Household work and energy consumption: A de growth perspective. Catalonia’s case study. Journal of Cleaner Production, 38, 71–79.CrossRefGoogle Scholar
  13. Domingue, J., Galis, A., Gavras, A., Zahariadis, T., Lambert, D., Cleary, F., et al. (2011). Smart cities and the future internet: Towards cooperation frameworks for open innovation. In The future internet (Vol. 6656, pp. 431–446, Lecture Notes in Computer Science): Springer, Berlin, Heidelberg.Google Scholar
  14. Duranton, G., & Puga, D. (2005). From sectoral to functional urban specialisation. Journal of Urban Economics, 57(2), 343–370.CrossRefGoogle Scholar
  15. Eisenmenger, N., Ramos-Martín, J., & Schandl, H. (2007). Análisis del metabolismo energético y de materiales de Brasil, Chile y Venezuela. Revista Iberoamericana de Economía Ecológica, 6, 17–39.Google Scholar
  16. Entrena-Durán, F. (1998). Cambios en la construcción social de lo rural: De la autarquía a la globalización. Madrid: Tecnos.Google Scholar
  17. Ewing, R., & Rong, F. (2008). The impact of urban form on U.S. residential energy use. Housing Policy Debate, 19(1), 1–30.CrossRefGoogle Scholar
  18. Falconí-Benítez, F. (2001). Integrated assessment of the recent economic history of Ecuador. Population and Environment, 22(3), 257–280.CrossRefGoogle Scholar
  19. Farhangi, H. (2010). The path of the smart grid. IEEE power & energy magazine. January/February 2010.Google Scholar
  20. FMR (2009). Atles de la nova ruralitat (Atlas of the new rurality). Fundació del Món Rural (FMR). http://www.fmr.cat/atles/.
  21. Freire, J. (2011). Eficiència Energètica i Efecte Rebot Desenvolupaments Metodològics i Evidència Empírica. Barcelona: Facultat de Ciències Econòmiques i Empresarials Universitat Autònoma de Barcelona.Google Scholar
  22. Gamboa, G. (2009). Application of the MuSIASEM approach to the analysis of the household sector: The supply and requirement of working hours to/from the service sector in Catalonia. Report of the Catalonia case study Deliverable 8, WP 3—Document C. http://www.smile-fp7.eu/deliverables/SMILE%20D8%20Document%20C.pdf.
  23. Gasparatos, A., El-Haram, M., & Horner, M. (2009). Assessing the sustainability of the UK society using thermodynamic concepts: Part 2. Renewable and Sustainable Energy Reviews, 13(5), 956–970.CrossRefGoogle Scholar
  26. Georgescu-Roegen, N. (1971). The enthropy law and the economic process. London, England: Harvard University Press.CrossRefGoogle Scholar
  27. Giampietro, M., Mayumi, K. (2008). The Jevons Paradox: The evolution of complex adaptive systems and the challenge for scientific analysis. In Polimeni, J. M., Mayumi, K., Giampietro, M. (eds.) The jevons paradox and the myth of resource efficiency Improvements. Earthscan. pp. 79–140. ISBN1-84407-462-5.Google Scholar
  28. Giampietro, M., Mayumi, K., & Ramos-Martin, J. (2009). Multi-scale integrated analysis of societal and ecosystem metabolism (MuSIASEM): Theoretical concepts and basic rationale. Energy, 34(3), 313–322.CrossRefGoogle Scholar
  29. Gilbert, R., Perl, A. (2010). Transportation in the post-carbon world. http://www.postcarbon.org/Reader/PCReader-Perl-Transportation.pdf. Accessed February 19, 2013.
  30. Gram-Hanssen, K., Ropke, I., & Reisch, L. A. (2004). Domestic electricity consumption-consumers and appliances. In I. Røpke & L. A. Reisch (Eds.), The ecological economics of consumption (1st ed., pp. 132–150). Cheltenham, UK: Edward Elgar.Google Scholar
  31. Härdle, W., & Simar, L. (2012). Applied multivariate statistical analysis (3rd ed.). Heidelberg: Springer.CrossRefGoogle Scholar
  32. Howard, E. (1985 [1898]). Garden cities of tomorrow: Powys: Attic books.Google Scholar
  33. ICAEN (2009). Estadístiques Energètiques de Catalunya. Dades de Producció Elèctrica. (Energy statistics of catalonia. Electricity production data). http://www15.gencat.cat/icaen_prd_elec/.
  34. ICAEN (2010). Generació d’energia elèctrica (Kwh) per tipus de central i capacitat instal·lada (Kw) a nivell municipal. Consum d’energia elèctrica per codi d’activitat econòmica (CNAE 2009 i CNAE-93) a nivell municipal. Anys 1992, 1996, 2001, 2006 i 2007. (Electricity generation (Kwh) per power plant type and installed capacity at the municipality level. Electricity consumption per economic activity code (CNAE 2009 i CNAE-93) at the municipality level. Years 1992, 1996, 2001, 2006 and 2007. Data provided under data protection and statistical confidenciality agreement by the Institut Català de la Energia (ICAEN).Google Scholar
  35. ICC(2012), Base de límits administratius 1:250.000, Institut Cartogràfic de Catalunya (ICC) (© Cartographic base property of Institut Cartogràfic de Catalunya. http://www20.gencat.cat/portal/site/territori/menuitem.2a0ef7c1d39370645f13ae92b0c0e1a0/?vgnextoid=5e8a159adcc4c310VgnVCM1000008d0c1e0aRCRD&vgnextchannel=5e8a159adcc4c310VgnVCM1000008d0c1e0aRCRD&vgnextfmt=default and http://www.icc.cat (Accessed on 8 July, 2012).
  36. IDESCAT (2001). Cens de població (2001). Population census (2001). http://www.idescat.cat/cataleg/?tc=c&idp=64&lang=en.
  37. IEA. (2012). Energy balances of OECD countries. IEA statistics. International energy agency. http://www.oecd-ilibrary.org/energy/energy-balances-of-oecd-countries-2012_energy_bal_oecd-2012-en.
  38. Iorgulescu, R. I., & Polimeni, J. M. (2009). A multi-scale integrated analysis of the energy use in Romania, Bulgaria, Poland and Hungary. WESC 2006, 6th world energy system conference, Advances in Energy Studies, 5th workshop on Advances, Innovation and Visions in Energy and Energy-related Environmental and Socio-Economic Issues, 34(3), 341–347.Google Scholar
  39. Jevons, W. S. (1866). The coal question (2nd ed.). London: Macmillan and Co.Google Scholar
  40. Jiang, B. (2012). Head/tail breaks: A new classification scheme for data with a heavy-tailed distribution, Professional Geographer, x: xx–xx. doi: 10.1080/00330124.2012.700499. http://arxiv.org/abs/1209.2801.
  41. Kaza, N. (2010). Understanding the spectrum of residential energy consumption: A quantile regression approach. Energy Policy, 38(11), 6574–6585.CrossRefGoogle Scholar
  42. Köbrich, C., Rehman, T., & Khan, M. (2003). Typification of farming systems for constructing representative farm models: Two illustrations of the application of multi-variate analyses in Chile and Pakistan. Agricultural Systems, 76(1), 141–157.CrossRefGoogle Scholar
  43. Kruskal, W. H., & Wallis, W. A. (1952). Use of ranks in one-criterion variance analysis. Journal of the American Statistical Association, 47(260), 583–621.CrossRefGoogle Scholar
  44. Liu, J. D., Daily, G. C., Ehrlich, P. R., & Luck, G. W. (2003). Effects of household dynamics on resource consumption and biodiversity. Nature, 421, 530–533.CrossRefGoogle Scholar
  45. Lobo, A., Baena, M. A. (2009). A first attempt of geographically-distributed multiscale integrated analysis of societal and ecosystem metabolism (MuSIASEM): Mapping human time and energy throughput in metropolitan Barcelona, Reports on Environmental Sciences 2. http://www.recercat.net/handle/2072/16100.
  46. Marsden, T. (1999). Rural futures: The consumption countryside and its regulation. Sociologia Ruralis, 39(4), 501–526.CrossRefGoogle Scholar
  47. Marsden, T. (2009). Mobilities, vulnerabilities and sustainabilities: Exploring pathways from denial to sustainable rural development. Sociologia Ruralis, 49(2), 113–131.CrossRefGoogle Scholar
  48. Marull, J., Pino, J., Mallarach, J. M., & Cordobilla, M. J. (2007). The loss of landscape efficiency: an ecological analysis of land-use changes in Western Mediterranean agriculture (Vallès County, Catalonia, 1853–2004). Global Environmental A Journal of History and Natural and Social Sciences, 2, 112–150.Google Scholar
  49. Marull, J., Pino, J., Tello, E., & Cordobilla, M. J. (2010). Social metabolism, landscape change and land-use planning in the Barcelona Metropolitan Region. Land Use Policy, 27(2), 497–510.CrossRefGoogle Scholar
  50. Mingorría, S., Gamboa, G. (2010). Metabolismo socio-ecológico de comunidades campesinas Q’eqchi’ y la expansión de la agro-industria de caña de azúcar y palma africana: Valle del Río Polochic, Guatemala [Instituto de Ciencia y Tecnología Ambiental de la Universidad Autónoma de Barcelona (ICTA/UAB) y el Instituto de Estudios Agrarios de la Coordinación de ONGs y Cooperativas (IDEAR/CONGCOOP)]: Magnaterra Editores.Google Scholar
  51. Munda, G. (2008). Social multi-criteria evaluation for a sustainable economy. Operation research and decision theory series. Heidelberg, New York: Springer.CrossRefGoogle Scholar
  52. Nel·lo, O. (2001). Ciutat de ciutats. Barcelona: Empúries.Google Scholar
  53. Ocaña-Riola, R., & Sánchez-Cantalejo, C. (2005). Rurality index for small areas in Spain. Social Indicators Research, 73(2), 247–266.CrossRefGoogle Scholar
  54. Ortega, M., & Calaf, M. (2010). Equitat ambiental a Catalunya. Integració de les dimensions ambiental, territorial i social a la presa de decisions. (Environmental equity in Catalonia. Integration of environmental, territorial and social dimensions to decision making.). Barcelona: Departament de la Vicepresidència. Consell Assessor per al Desenvolupament Sostenible de Catalunya (CADS).Google Scholar
  55. Pepermans, G., Driesen, J., Haeseldonckx, D., Belmans, R., & D’haeseleer, W. (2005). Distributed generation: Definition, benefits and issues. Energy Policy, 33(6), 787–798.CrossRefGoogle Scholar
  56. Prieto-Lara, E., & Ocaña-Riola, R. (2010). Updating rurality index for small areas in Spain. Social Indicators Research, 95(2), 267–280.CrossRefGoogle Scholar
  57. Ramos-Martín, J. (2001). Historical analysis of energy intensity of Spain: From a “conventional view” to an “integrated assessment”. Population and Environment, 22(3), 281–313.CrossRefGoogle Scholar
  58. Ramos-Martín, J., Cañellas-Boltà, S., Giampietro, M., & Gamboa, G. (2009). Catalonia’s energy metabolism: Using the MuSIASEM approach at different scales. Energy Policy, 37(11), 4658–4671.CrossRefGoogle Scholar
  59. Ramos-Martin, J., Giampietro, M., & Mayumi, K. (2007). On China’s exosomatic energy metabolism: An application of multi-scale integrated analysis of societal metabolism (MSIASM). Ecological Economics, 63(1), 174–191.CrossRefGoogle Scholar
  60. Ramos-Martín, J. (Coord.) (2009). Ús de l’Energia a Catalunya. Anàlisi del Metabolisme Energètic de l’Economia Catalana (AMEEC). Informes del CADS. Barcelona: Consell Assessor per al Desenvolupament Sostenible.Google Scholar
  61. Rifkin, J. (2011). The third industrial revolution: How lateral power is transforming energy the economy, and the world. Basingstoke: Palgrave Macmillan.Google Scholar
  62. Roca, J., & Alcántara, V. (2001). Energy intensity, CO2 emissions and the environmental Kuznets curve. The Spanish case. Energy Policy, 29(7), 553–556.CrossRefGoogle Scholar
  63. Saladié, s. (2011). Els conflictes territorials del sistema elèctric a Catalunya (The territorial conflicts of the electrical system of Catalonia). Treballs de la Societat Catalana de Geografia, 71–72, 201–221.Google Scholar
  64. Scheidel, A., & Sorman, A. H. (2012). Energy transitions and the global land rush: Ultimate drivers and persistent consequences. Global Environmental Change, 22(3), 588–595.CrossRefGoogle Scholar
  65. Shapiro, S. S., & Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3–4), 591–611. doi: 10.1093/biomet/52.3-4.591.CrossRefGoogle Scholar
  66. Siciliano, G. (2012). Urbanization strategies, rural development and land use changes in China: A multiple-level integrated assessment. Land Use Policy, 29(1), 165–178.CrossRefGoogle Scholar
  67. Smil, V. (2008). Energy in nature and society: General energetics of complex systems. Cambridge: The MIT Press.Google Scholar
  68. Smith, D. (2007). The changing faces of rural populations: ‘“(re) fixing” the gaze ‘or ‘eyes wide shut’’? Journal of Rural Studies, 23(3), 275–282.CrossRefGoogle Scholar
  69. Sorman, A. H., & Giampietro, M. (2011). Generating better energy indicators: Addressing the existence of multiple scales and multiple dimensions. Ecological Modelling, 223(1), 41–53.CrossRefGoogle Scholar
  70. Tacoli, C. (2003). The links between urban and rural development. Environment and Urbanization, 15(1), 3–12. doi: 10.1177/095624780301500111.CrossRefGoogle Scholar
  71. Tello, E. (2005). Changing course? Principles and tools for local sustainability. In T. Marshall (Ed.), Transforming Barcelona (pp. 110–225). London: Routledge.Google Scholar
  72. Tello, E. Pigrau, A. and García, M. (2013), Sostenibilidad y descentralización en las políticas locales de energía. In. Canal, R. (Ed). Ciudades y pueblos que puedan durar. Políticas locales para una nueva época, Ed. Icaria, Barcelona, p. 29–43.Google Scholar
  73. Usai, M. G., Casu, S., Molle, G., Decandia, M., Ligios, S., & Carta, A. (2006). Using cluster analysis to characterize the goat farming system in Sardinia. Livestock Science, 104(1–2), 63–76.CrossRefGoogle Scholar
  74. Usman, A., & Shami, S. H. (2013). Evolution of communication technologies for smart grid applications. Renewable and Sustainable Energy Reviews, 19, 191–199.CrossRefGoogle Scholar
  75. Williams, J. (2007). Innovative solutions for averting a potential resource crisis—the case of one-person households in England and Wales. Environment, Development and Sustainability, 9(3), 325–354.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Pere Ariza-Montobbio
    • 1
    • 2
  • Katharine N. Farrell
    • 2
    • 3
  • Gonzalo Gamboa
    • 2
  • Jesus Ramos-Martin
    • 2
    • 4
  1. 1.FLACSO Ecuador - La PraderaQuitoEcuador
  2. 2.Institut de Ciència i Tecnologia AmbientalsUniversitat Autònoma de BarcelonaBellaterra (Cerdanyola del Vallès), BarcelonaSpain
  3. 3.Division of Resource Economics, Department of Agricultural EconomicsHumboldt-Universität zu BerlinBerlinGermany
  4. 4.Departament d’Economia i d’Història EconòmicaUniversitat Autònoma de BarcelonaBellaterra (Cerdanyola del Vallès), BarcelonaSpain

Personalised recommendations

Cite article

Buy options