Assessing GHG mitigation goals of INDCs (NDCs) considering socio-economic and environmental indicators of the parties

Based on the announced (Intended) Nationally Determined Contributions (INDCs), parties to the United Nations Framework Convention on Climate Change (UNFCCC) have introduced greenhouse gas emission reduction goals. These goals are based on the country-specific long-term climate policy. However, these goals do not necessarily match the countries' socio-economic statuses and environmental performances, which are the main pillars of sustainable development. This paper proposes unconditional mitigation goals for 190 countries considering their socio-economic and environmental status in such a way that the total emission reductions are equal to that of (I)NDCs. To do so, different data mining methods including k-means clustering, Decision Trees (DT), Multivariate Adaptive Regression Splines (MARS), and Generalized Regression Neural Networks (GRNNs) are employed. Different clusters of countries are described and an appropriate range as unconditional mitigation goal for each country is introduced. In addition, the sufficiency of the current targets for each country is analyzed based on the proposed ranges. The results indicate that among top emitters, (I)NDCs of India, Russia, and Japan do not match their socio-economic status. On the contrary, Indonesia, Germany, and Mexico have targeted stricter mitigation goals than the proposed ranges of this research.