(36e) Minimization of the GHG Emissions At the Macroeconomic Level Via a Multi-Objective Input-Output Approach: A Case Study of the EU-25 Economy

Cortés, D., University Rovira i Virgili
Guillén-Gosálbez, G., University Rovira i Virgili
Guimerá, R., Universitat Rovira i Virgili
Sales-Pardo, M., Universitat Rovira i Virgili
Ruiz-Hernández, A., University Rovira i Virgili
Llop, M., Universitat Rovira i Virgili

Minimization of the GHG emissions at the macroeconomic level via a multi-objective input-output approach: A case study of the EU-25 economy


D. Cortés-Bordaa, A. Ruiz-Hernándeza, G. Guillén-Gosálbeza, M. Llopb, R. Guimerà, M. Sales-Pardo.

a.Departament d’Enginyeria Química, Universitat Rovira i Virgili, Av. Països Catalans, 26, Tarragona E-43007, Spain.

b.Centre de Recerca en Economia Industrial i Economia Pública (CREIP), Universitat Rovira i Virgili, Av. Universitat 1, 43204 Reus, Spain. 

Global warming has grown significantly in the recent past due to the increasing atmospheric concentration of anthropogenic greenhouse gasses (GHGs). As a result, worldwide environmental policies are placing global warming mitigation as a top priority in the nations’ environmental agendas. That is, most of the National governments are adopting policies that aim to minimize GHG emissions.

Unfortunately, in today’s globalized markets designing effective environmental policies is challenging because international trade establishes channels through which impacts are imported and exported among nations, overshadowing the main source of pollution into an intricate trading network. Therefore, the design of these policies requires robust environmental assessment methods capable of capturing the complexity of the existing international supply chains of goods/services .

Methods based on extended environmental input-output (EEIO) models are particularly suitable to address global warming at a global scale, since they can assess macroeconomic connections between productive sectors of different nations and the associated environmental impact. This information can be used to allocate the corresponding environmental responsibility. EEIO models are flexible, transparent and accurate enough to perform life cycle assessment (LCA) studies. Hence, LCA-based EEIO models translate the economic output of a given economy into a tangible environmental impact.

By using macroeconomic EEIO models, we can identify a wide range of alternatives for environmental savings, as it is possible to reduce each sector’s output (and therefore its associated GHGs emissions) to a different extent through taxation and/or economic penalties. In this context, systematic optimization tools are especially helpful to identify the most promising alternatives considering economic and environmental concerns.

We have developed in this work a systematic approach of this type for reducing the environmental impact of an economy that is based on the combined use of  EEIO models and multi-objective linear programming techniques. This tool has been applied to the European Union (EU-25) economy in order to find solutions that simultaneously maximize the total output and minimize the GHGs emissions. Hence, in our approach the problem of identifying key economic sectors that should be given higher priority is posed in mathematical terms as a bi-criteria LP problem that seeks to optimize simultaneously the total European gross domestic product and the associated life cycle GHGs simultaneously. Our study makes use of the E3IOT database, which covers 487 EU economic sectors.

Numerical results show that substantial reductions in global warming potential can be achieved by imposing taxes on sectors such as energy, mineral extraction, and meat and its derived products. By applying this wide-scope assessment, we find potential alternatives for reducing GHG emissions (that are not obvious at first sight) that can assist policy-making.