Abstract
The role of towns and their inhabitants in fighting climate change is becoming increasingly important (Shi et al. in Nat Clim Change 6(2):131–137, 2016). In this context, the aim of this paper is to apply a multi-regional input-output model to study the evolution of the carbon footprint for Spanish households as determined by the different type of settlement. This study analyses the household carbon footprint as a function of the municipality’s population size, whether it is located in a rural or urban environment, and its relation to population density. By using a multi-regional model we are able to calculate the share of that carbon footprint that is generated within the settlement and the share that is produced around the world along global value chains. This methodology has been widely applied to study carbon footprints for households in terms of different characteristics: income levels (Duarte et al. in Energy Policy 44:441–450, 2012), age (Shigetomi et al. in Environ Sci Technol 48(11):6069–6080, 2014), consumption of agriculture products (López et al. in J Clean Prod 103:423–436, 2015), or tourism consumption (Cadarso et al. in J Clean Prod 111(Part B):529–537, 2016). The structure of household consumption as a function of the type of settlement will be used to analyse whether socio-economic features are the greatest influence in the level of carbon footprint, or by the contrary, structural, institutional or geographical factors of the settlement are more relevant. Previous literature has addressed this link in other countries, for instance Fan et al. (J Clean Prod 33:50–59, 2012), Minx et al. (Environ Res Lett 8(3):035039, 2013), Baiocchi et al. (Global Environ Change 34:13–21, 2015) or Ahmad et al. (Environ Sci Technol 49(19):11312–11320, 2015), but not for the Spanish case. Regarding data sources, we propose combining the World Input-Output Database (WIOD) and the Household Budget Survey for the Spanish economy, in order to analyse the carbon footprint from household consumption for 2015.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
The size of the consumption unit represented by the household-dwelling unit is indicated as the sum of the weights of its members. In accordance with international recommendations, as a standard measure, the value of each member of a household-dwelling unit is determined as follows: First adult aged 18 and over = 1.0; Subsequent adults aged 18 and over = 0.7; Each person aged under 18 = 0.5; If all persons in the household-dwelling unit are aged under 18, the weight of the first member is 1.0 and that of subsequent members 0.5.
References
AEAT. (2016). Informes anuales de Recaudación Tributaria.
Ahmad, S., Baiocchi, G., & Creutzig, F. (2015). CO2 emissions from direct energy use of urban households in India. Environmental Science and Technology, 49(19), 11312–11320. doi:10.1021/es505814g
Arce, G., López, L. A., & Guan, D. (2016). Carbon emissions embodied in international trade: The post-China era. Applied Energy. doi:10.1016/j.apenergy.2016.05.084
Baiocchi, G., Creutzig, F., Minx, J., & Pichler, P. P. (2015). A spatial typology of human settlements and their CO2 emissions in England. Global Environmental Change, 34, 13–21. doi:10.1016/j.gloenvcha.2015.06.001
Cadarso, M. Á., Gómez, N., López, L. A., & Tobarra, M. Á. (2016). Calculating tourism’s carbon footprint: Measuring the impact of investments. Journal of Cleaner Production, 111(Part B), 529–537. doi:http://dx.doi.org/10.1016/j.jclepro.2014.09.019
Davis, S. J., Peters, G. P., & Caldeira, K. (2011). The supply chain of CO2 emissions. PNAS, 108(45), 18554–18559.
Dejuán, Ó., López, L. A., Tobarra, M. Á., & Zafrilla, J. (2013). A post-Keynesian age model to forecast energy demand in Spain. Economic Systems Research, 25(3), 321–340. doi:10.1080/09535314.2013.806294
Duarte, R., Mainar, A., & Sánchez-Chóliz, J. (2012). Social groups and CO2 emissions in Spanish households. Energy Policy, 44, 441–450. doi:10.1016/j.enpol.2012.02.020
Fan, J., Guo, X., Marinova, D., Wu, Y., & Zhao, D. (2012). Embedded carbon footprint of Chinese urban households: Structure and changes. Journal of Cleaner Production, 33, 50–59. doi:10.1016/j.jclepro.2012.05.018
Gouldson, A., Colenbrander, S., Sudmant, A., Papargyropoulou, E., Kerr, N., McAnulla, F., et al. (2016). Cities and climate change mitigation: Economic opportunities and governance challenges in Asia. Cities, 54, 11–19. doi:10.1016/j.cities.2015.10.010
Hubacek, K., Feng, K., Minx, J. C., Pfister, S., & Zhou, N. (2014). Teleconnecting consumption to environmental impacts at multiple spatial scales. Journal of Industrial Ecology, 18(1), 7–9. doi:10.1111/jiec.12082
INE. (2016a). Encuesta de Presupuestos Familiares (Household Budget Survey). Spanish National Institute of Statistics. http://www.ine.es/dyngs/INEbase/es/operacion.htm?c=Estadistica_C&cid=1254736176806&menu=resultados&idp=1254735976608
INE. (2016b). Índice de Precios al Consumo (Consumer price index). Spanish National Institute of Statistics.
Jones, C., & Kammen, D. M. (2014). Spatial distribution of U.S. household carbon footprints reveals suburbanization undermines greenhouse gas benefits of urban population density. Environmental Science and Technology, 48(2), 895–902. doi:10.1021/es4034364
Kanemoto, K., Lenzen, M., Peters, G. P., Moran, D. D., & Geschke, A. (2012). Frameworks for comparing emissions associated with production, consumption and international trade. Envionmental Science and Technology, 46, 172–179.
Larsen, H. N., & Hertwich, E. G. (2010). Implementing carbon-footprint-based calculation tools in municipal greenhouse gas inventories. Journal of Industrial Ecology, 14(6), 965–977. doi:10.1111/j.1530-9290.2010.00295.x
Liu, L. C., Wu, G., Wang, J. N., & Wei, Y. M. (2011). China’s carbon emissions from urban and rural households during 1992–2007. Journal of Cleaner Production, 19(15), 1754–1762. doi:10.1016/j.jclepro.2011.06.011
López, L. A., Arce, G., Morenate, M., & Monsalve, F. (2016). Assessing the inequality of Spanish households through the carbon footprint: The 21st century great recession effect. Journal of Industrial Ecology, 20(3):571–581. doi:10.1111/jiec.12466
López, L. A., Cadarso, M. A., Gómez, N., & Tobarra, M. Á. (2015). Food miles, carbon footprint and global value chains for Spanish agriculture: Assessing the impact of a carbon border tax. Journal of Cleaner Production, 103, 423–436. doi:10.1016/j.jclepro.2015.01.039
Mi, Z., Zhang, Y., Guan, D., Shan, Y., Liu, Z., Cong, R., . . . Wei, Y. -M. (2016). Consumption-based emission accounting for Chinese cities. Applied Energy, 184, 1073–1081. doi:http://dx.doi.org/10.1016/j.apenergy.2016.06.094
Miller, R. E., & Blair, P. D. (2009). Input-output analysis: foundations and extensions (2nd ed.). Cambridge: Cambridge University Press.
Minx, J., Giovanni, B., Thomas, W., John, B., Felix, C., Kuishuang, F., . . . Klaus, H. (2013). Carbon footprints of cities and other human settlements in the UK. Environmental Research Letters, 8(3), 035039.
Minx, J. C., Wiedmann, T., Wood, R., Peters, G. P., Lenzen, M., Owen, A., . . . Ackerman, F. (2009). Input-output analysis and carbon footprinting: An overview of applications. Economic Systems Research, 21(3), 187–216. doi:10.1080/09535310903541298
Peters, G. P., Davis, S. J., & Andrew, R. M. (2012). A synthesis of carbon in international trade. Biogeosciences Discuss, 9(3), 3949–4023.
Rosenzweig, C., Solecki, W., Hammer, S. A., & Mehrotra, S. (2010). Cities lead the way in climate-change action. Nature, 467(7318), 909–911.
Sanz, T., Yniguez, R., & Rueda-Cantuche, J. (2016). The relevance of multi-country input-output tables in measuring emissions trade balance of countries: The case of Spain. Sort, 1(1), 3–30.
Shi, L., Chu, E., Anguelovski, I., Aylett, A., Debats, J., Goh, K., . . . VanDeveer, S. D. (2016). Roadmap towards justice in urban climate adaptation research. Nature Climate Change, 6(2), 131–137. doi:10.1038/nclimate2841
Shigetomi, Y., Nansai, K., Kagawa, S., & Tohno, S. (2014). Changes in the carbon footprint of Japanese households in an aging society. Environmental Science and Technology, 48(11), 6069–6080. doi:10.1021/es404939d
Timmer, M. P., Dietzenbacher, E., Los, B., Stehrer, R., & de Vries, G. J. (2015). An illustrated user guide to the world input-output database: The case of global automotive production. Review of International Economics, 23(3), 575–605. doi:10.1111/roie.12178
Yu, Y., Hubacek, K., Feng, K., & Guan, D. (2010). Assessing regional and global water footprints for the UK. Ecological Economics, 69(5), 1140–1147. doi:10.1016/j.ecolecon.2009.12.008
Zafrilla, J. E. (2014). The mining industry under the thumb of politicians: The environmental consequences of the Spanish coal decree. Journal of Cleaner Production, 84, 715–722. doi:10.1016/j.jclepro.2014.02.031
Zafrilla, J. E., López, L. A., Cadarso, M. Á., & Dejuán, Ó. (2012). Fulfilling the Kyoto protocol in Spain: A matter of economic crisis or environmental policies? Energy Policy, 51, 708–719. doi:10.1016/j.enpol.2012.09.011
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this chapter
Cite this chapter
Arce, G., Zafrilla, J.E., López, LA., Tobarra, M.Á. (2017). Carbon Footprint of Human Settlements in Spain. In: Álvarez Fernández, R., Zubelzu, S., Martínez, R. (eds) Carbon Footprint and the Industrial Life Cycle. Green Energy and Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-54984-2_14
Download citation
DOI: https://doi.org/10.1007/978-3-319-54984-2_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-54983-5
Online ISBN: 978-3-319-54984-2
eBook Packages: EnergyEnergy (R0)