Abstract

Countries must act urgently to achieve the SDGs and make significant progress for the planet and people by 2030. But there are some key challenges that the world must address. Climate change is one of the most significant challenges of our time, and its impacts can undermine the ability of all countries to achieve sustainable development. However, countries committed to limiting global warming to 1.5°C above pre- industrial levels in the Paris Agreement. Member nations pledge to take urgent action on climate change to save the planet from global warming.

Using data analysis techniques and methodologies, such as CRISP-DM, and visualization tools like R and Tableau, we aim to accomplish several things; First, identify the contribution of each country and sector to global CO2 emissions. Second, identify the major sectors contributing to CO2 emissions and create machine learning models (time series models) for predicting CO2 emissions for the selected countries to determine if they will peak in n 2025 and fall by 43% by 2030 to meet the Paris Agreement and limit global warming to 1.5°C as stated by the IPCC AR6 report. Third, identify the decarbonization indicators most correlated with CO2 emissions at the sector level. Fourth, determine whether some selected countries meet their commitments in their NDCs, or NetZero policies based on the three trajectories (business as usual based on historical data, NetZero pathways -minimum policy and maximum policy CO2 emissions). Fifth, investigate and promote the social cost of carbon for the UAE for the first time in the region, as this is currently a lively debate among policymakers.

As RIT students, we would like to contribute to the efforts of the UAE and the world to find solutions to climate change and raise awareness to accelerate the transition to clean energy. However, there are some limitations -Some countries need mechanisms to collect the CO2/GHG emissions or transparency reporting them, or they need an official CO2 /GHG emissions inventory. Therefore, the dataset for our project only includes annual data and does not include CO2 emissions from all countries in the world; the time was another limitation; we tried in our project to have a holistic perspective and to study all sectors, then we decided to focus more on the energy sector (Electricity and the Oil & Gas sectors) since they are the most CO2 emissions contributors among all other sectors.

Publication Date

5-2023

Document Type

Master's Project

Student Type

Graduate

Degree Name

Professional Studies (MS)

Department, Program, or Center

Graduate Programs & Research (Dubai)

Advisor

Sanjay Modak

Advisor/Committee Member

Ioannis Karamitsos

Campus

RIT Dubai

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