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Socio-metabolic profiles of electricity consumption along the rural–urban continuum of Ecuador: Whose energy sovereignty?

Abstract

Integrating energy and land use planning for sustainable and resilient human settlements requires a Post-Normal science perspective where actors’ views are an essential part of the quality of energy policies assessments. Through qualitative content analysis of interviews to diverse actors in Ecuador, we found two broad contrasting narratives on Energy Sovereignty: a “Hard” and a “Soft” path. By using multivariate statistical analysis of socio-demographic, land use and electricity consumption variables, we derived a typology of parishes with distinct socio-metabolic profiles along the “rural–urban” continuum of Ecuador. Four different types and eight subtypes of parishes spatially organize by processes of suburbanization, functional urban specialization and “new ruralities” or “rural multifunctionality”. Urban centers tend to specialize in service and industrial sectors while suburban and intermediate cities, remote rural areas, and dynamic towns tend to be residential and agrarian. Suburban and intermediate cities and periurban dynamic towns are mosaics of land uses and activities where the “rural” and “urban” intertwine. Looking at these results from the two narratives found, we see how centralized grids and large-scale hydropower through the “Hard” path can sustain uneven patterns of electricity consumption. Contrastingly, under the “Soft” path, distributed energy generation could provide opportunities for multiple small-scale projects of diverse renewable sources. This could help facing the heterogeneity of socio-metabolic profiles and provide enabling conditions for a small-scale and spatially distributed industrialization, instead of centralized traditional ways that reproduce uneven development.

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Fig. 1

Source: Own elaboration

Fig. 2

Source: Own elaboration

Fig. 3

Source: Own elaboration

Fig. 4

Source: Own elaboration

Fig. 5

Source: Own elaboration based on CONELEC (2014, 2017), INEC (2011), MAGAP-MAE (2012) and https://hub.arcgis.com/

Fig. 6

Source: Own elaboration based on CONELEC (2014, 2017), INEC (2011) and MAGAP-MAE (2012)

Fig. 7

Source: Own elaboration based on INEC (2011)

Fig. 8

Source: Own elaboration based on CONELEC (2014, 2017), INEC (2011), MAGAP-MAE (2012) and Jiang (2013) method of head/tail breaks for interval representation of heavy-tailed distribution data

Fig. 9

Source: Own elaboration based on (CONELEC (2014, 2017) INEC (2011), MAGAP-MAE (2012) and Jiang (2013) method of head/tail breaks for interval representation of heavy-tailed distribution data

Notes

  1. The argumentative approach considers discourse as constitutive of the realities of environmental politics. The environmental conflict is not only about which actions to be taken, but about the meaning of social-ecological problems (Hajer 1995).

  2. “Narratives on social reality through which elements from many different domains are combined and that provide actors with a set of symbolic references that suggest a common understanding” (Hajer 1995: 62).

  3. The story-lines are often feed or promoted even by actors which don’t defend certain ideas, but through mentioning or even negation, consciously or not, help to consolidate different story-lines, even the rival ones. In this view, discourse coalitions differ from advocacy coalitions (Sabatier 1987). Actors rather than purely holding certain belief systems (individualist ontology) learn and change positioning through language and discourse and have different practices and discourses in different contexts (relational ontology). Language is not a mean, is part of the reality. Policy discussion goes beyond scientific “objective” discussions about “facts” to engage also with political discussions about “values”.

  4. We adopt the “Hard” and “Soft” path labels from previous work (Ariza-Montobbio 2013; Szarka 2007) and from the inspiration of Lovins (1977) who was one of the first authors to propose different development and transition pathways to renewable energies.

  5. Along the text, we use italics to highlight the names of types and subtypes of parishes as an emergent concept derived of our results to distinguish them from a general use of the same words.

  6. Lack of disaggregated electricity consumption and land use data at census tract limited the possibility of using census tract as the unit of analysis for the research. Analysis at finer scales could have revealed urban inequalities within parishes.

  7. The definition of rural and urban areas is a controversial one. However, the “Instituto Nacional de Estadísticas y Censos” (INEC), defines an “urban” area as “the urban settlements which are province capitals and cabeceras cantonales (main cities of a municipality, a group of parishes)” and “rural” area as “parish capitals and dispersed and peripheral population areas” (SIISE 2018).

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Acknowledgements

Thanks to all persons interviewed during the long process of collecting and processing data. Especially, thanks to all people who helped from so diverse spaces, from rural villages affected by hydroelectric powerplants to public offices of the Agencia de Regulación y Control de la Electricidad (ARCONEL, now CONECEL) and Instituto Nacional de Estadística y Censos (INEC). Thanks to Paul Lorca, Rosalía Soley, Patricia González, Gabriela Albuja, Carolina Sinchiguano, Gloria Salazar, Jessica Solorzano, José María Burgaleta, Luis Miguel Ponce, Francisco Venes, Alberto Acosta and Teodoro Bustamante who were part of the research team at Facultad Latinoamericana de Ciencias Sociales (FLACSO) and helped either in doing, transcribing or analyzing interviews, processing and creating statistical and GIS databases or in administrative or fund raising tasks. Thanks to Grupo de investigación en Biodiversidad, Medio Ambiente y Salud (BIOMAS) and Centro de Investigaciones Económicas both from Universidad de las Américas (UDLA) who funded part of the data processing, analyzing and writing phase. Especial thanks to Alexandra Villa and Rafaela Berenice for their key support on data processing and Tannya Lozada, Blanca Ríos-Touma, Laura Guerrero-Latorre, Rasa Zalakeviciute and Yves Rybarcyk, for their help and support. Thanks to Maria Cristina Cruz and Giannina Zamora for their support on GIS data analysis and representation. Thanks to the anonymous reviewers for their valuable comments to earlier versions of the article. The final version reminds only of our own responsibility.

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Ariza-Montobbio, P., Herrero Olarte, S. Socio-metabolic profiles of electricity consumption along the rural–urban continuum of Ecuador: Whose energy sovereignty?. Environ Dev Sustain 23, 7961–7995 (2021). https://doi.org/10.1007/s10668-020-00957-x

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Keywords

  • Socio-metabolic profiles
  • Distributed energy generation
  • Functional urban specialization
  • Suburbanization
  • Energy sovereingty