Assessing regional convergence of greenhouse gas emissions in Spain: insights from economic activities

Abstract

ABSTRACTIn recent decades, Spain has undergone a strong economic expansion; however, it has not made a robust response to fulfil the international greenhouse gas Paris Agreement targets. Thus, understanding the dynamics of the environmental performance of the Spanish regions is essential for policymakers. We explore the convergence process of emissions intensity at the regional level during 1990–2018, differentiating between direct and diffuse emission sector, based on the degree of energy intensity of economic activities, which is the most novel aspect of our analysis. Our results recognise several convergence clubs; predominantly, the determining factors are income level and added value breakdown, the energy mix of renewable power, as well as the temperature of the climate. In any event, the dispersion of behaviours and the existence of different factors driving the convergence process highlight the need for customised policies at the regional scale.Key Policy HighlightsCustomised environmental policies are vital for regions in Spain with varying emissions levels.National consensus is needed to reduce emissions across industries, transportation, businesses, households, and agriculture.Targeted development can mitigate environmental impact, aiding policymakers.Regions that are falling behind should prioritise renewable energy promotion.Energy conservation laws must be mandatory henceforth.KEYWORDS: Emission intensityconvergenceclubs/clusterssectorsSpain Disclosure statementNo potential conflict of interest was reported by the author(s).Data accessibility statementThe data that support the findings of this study are available from the corresponding author upon reasonable request.Notes1 The figures for the autonomous cities are not shown individually because of their low degree of representation. In this manner, our subsequent analysis always has 18 regions, the last one being the combination of Ceuta and Melilla (CYM).2 The smoothing parameter, λ, of the Hodrick-Prescott filter should be adjusted when changing the frequency of observations which can affect the results of filtering (Ravn and Uhlig Citation2002). We have defined λ= 400 as noted (Phillips and Sul Citation2009). Results do not change significantly with λ=100 for annual data.