Open Access
ARTICLE
The Challenge of the Paris Agreement to Contain Climate Change
E. Grigoroudis, F. Kanellos, V. S. Kouikoglou, Y. A. Phillis
School of Production Engineering and Management, Technical University of Crete, Chania, Greece
* Corresponding Author: Y. A. Phillis,
Intelligent Automation & Soft Computing 2018, 24(2), 319-330. https://doi.org/10.1080/10798587.2017.1292716
Abstract
Climate change due to anthropogenic CO2 and other greenhouse gas emissions has had and will
continue to have widespread negative impacts on human society and natural ecosystems. Drastic
and concerted actions should be undertaken immediately if such impacts are to be prevented. The
Paris Agreement on climate change aims to limit global mean temperature below 2 °C compared to
the pre-industrial level. Using simulation and optimization tools and the most recent data, this paper
investigates optimal emissions policies satisfying certain temperature constraints. The results show
that only if we consider negative emissions coupled with drastic emissions reductions, temperature
could be stabilized at about 2.5 °C, otherwise higher temperatures could possibly occur. To this end,
two scenarios are developed based on the national emissions reduction plan of China and the USA.
According to the simulation results, the objective of keeping temperature rise under 2 °C cannot be
met. Clearly, negative emissions are needed if the Paris targets are to be given a chance for success.
However, the feasibility of negative emissions mainly depends on technologies not yet developed.
Reliance on future technological breakthroughs could very well prove unfounded and provide excuses
for continued carbon releases with possible severe and irreversible climate repercussions. Thus, the
Paris Agreement needs immediate amendments that will lead to stronger mitigation and adaptation
commitments if it is to stay close to its goals.
Keywords
Cite This Article
E. Grigoroudis, F. Kanellos, V. S. Kouikoglou and Y. A. Phillis, "The challenge of the paris agreement to contain climate change,"
Intelligent Automation & Soft Computing, vol. 24, no.2, pp. 319–330, 2018. https://doi.org/10.1080/10798587.2017.1292716