Forecasting and mitigation of global environmental carbon dioxide emission using machine learning techniques

Abstract

Carbon dioxide emission has emerged as a major concern in the 21st century. The rising global average temperature and its impact on climate change has a major impact on the socioeconomic affairs of the world. This rise, directly causes the melting of the polar ice caps which in turn, brings about many other issues including extinction of polar animals, flooding of coastal regions, exposure to ancient microbial life and bacteria frozen in the snow which pose a risk of many more global pandemics and unseen diseases. An urgent need to control this carbon emission is required. The initial step in this process is to accurately identify the threat levels and milestones. Certain thresholds need to be mapped that express the most critical levels of CO2 such as – the risk point, point of no return, etc. This is the main issue that this paper aims to address. The paper also aims to suggest some methodologies to deal with the same issue. The flow of the experiment and paper is described in the following lines. Historical data was used to make a prediction for the year in which the earth will hit a particular threshold for carbon dioxide concentration in the atmosphere. This level must not be breached and is essential in the fight against climate change. Next, analysis and data are used to calculate the reduction needed in the emission levels in order to bring back the CO2 concentrations into a safer range. The study concludes that the critical level of CO2 - 500 ppm, will be achieved by the year 2047. This level is considered a point of no return. A reduction rate of 6.37% and reversal rate of 23.38% is required to bring the emissions back to safe levels. The study also concluded that various socioeconomic factors such as population, greenhouse gasses, combustion industries contribute the most to these emissions. The authors recommend that further research be carried out on this problem to ascertain further predictions on the point of no return so that an action plan can be developed accordingly. The authors also recommend that a shift to renewable energy sources be undertaken speedily and that carbon neutrality be a crucial goal of every organization.