Cap-and-trade and emissions clustering: A spatial-temporal analysis of the European Union Emissions Trading Scheme. (1st November 2019)

• Record Type: Journal Article
• Authors: Stuhlmacher, Michelle; Patnaik, Sanjay; Streletskiy, Dmitry; Taylor, Kelsey
• Is Part Of: Journal of environmental management. Volume 249(2019)
• Publication Date: 2019-11-01
• Subjects: Climate change -- Cap-and-Trade -- Environmental policy -- Greenhouse gas emissions; Environmental policy -- Periodicals; Environmental management -- Periodicals; Environment -- Periodicals; Ecology -- Periodicals; 363.705
• DOI: 10.1016/j.jenvman.2019.109352
• Languages: English
• ISSNs: 0301-4797

Abstract

Abstract: One of the most popular policy mechanisms for greenhouse gas emissions regulation is cap-and-trade which is a market-based approach that has come to dominate partially because of its flexibility. With flexibility, however, comes the potential for the clustering of greenhouse gas emissions. To understand whether emissions trading leads to localized clustering of emissions changes, we perform a systematic, spatio-economic assessment of the European Union Emissions Trading Scheme (EU ETS). We analyze the spatial pattern of emissions changes from individual plants across the EU as well as how the pattern changes during the first two phases of the ETS implementation. Our findings indicate that there was clustering of emissions changes at the EU and country level which peaked at the start of the second phase but declined as the EU ETS matured. We also found that iron and steel, coke ovens, and refining have greater clustering and volatility compared to other industries. Based on the air quality implications of these clustered emissions, certain countries and industry types might need additional attention during the ETS design or redesign process. This study makes a novel contribution by systematically evaluating the spatio-temporal and equity implications of emissions distribution in cap-and-trade systems. Highlights: First systematic spatio-temporal assessment of EU ETS emissions changes. Iron & steel, coke ovens, and refining have greater clustering and volatility. Emissions changes were spatially concentrated, peaking at the start of phase II. Emissions clustering should be considered in the design of trading schemes.