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Quantifying the cost of leaving the Paris Agreement via the integration of life cycle assessment, energy systems modeling and monetization

handle: 10044/1/67500
Abstract Current energy systems models focus on cost minimization with a bound on some greenhouse gas emissions. This limited environmental scope can lead to mixes that are not consistent with our sustainable development. To circumvent this limitation, we here make use of the concept of monetization and life cycle assessment to quantify the indirect costs of electricity generation in the design of energy systems. Applying our approach to the United States, we found that the indirect costs of electricity generation could be reduced by as much as 63% by meeting the Paris Agreement. Consequently, the total opportunity cost (i.e., direct and indirect costs) of withdrawing from the Paris Agreement and continuing with the current mix would be as high as 1103 ± 206 billion USD2013 in 2030 (i.e., 6% of the United States gross domestic product in 2017). By optimizing the direct and indirect costs of electricity generation concurrently, we found an optimal ecological solution that attains total economic savings compared to the Paris Agreement mix of as much as 373 ± 164 billion USD2013 in 2030. Our work highlights the need to extend the environmental policies that regulate energy systems beyond the direct greenhouse emissions to consider other critical environmental criteria.
- Universitat Rovira i Virgili Spain
- ETH Zurich Switzerland
- Imperial College London United Kingdom
- Institute for Chemical and Bioengineering Switzerland
Consequential life cycle assessment, Energy, 330, Paris Agreement, 09 Engineering, Sustainability, Externalities, Energy systems modeling, Monetization, 14 Economics
Consequential life cycle assessment, Energy, 330, Paris Agreement, 09 Engineering, Sustainability, Externalities, Energy systems modeling, Monetization, 14 Economics
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).27 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
