Forecasting of CO2 Emission According to data analysis

Abstract

The effects of global warming are being felt more and more today. One of the most important factors affecting global warming is carbon emission. Global warming and climate change are the problems of the world and humanity that concern sectors such as industry, commerce, and agriculture. The increasing amount of carbon in the world is due to many reasons. Carbon emissions are also called greenhouse gas emissions. Since most of these gases are based on carbon molecules, they are called carbon emissions. The purpose of this article is to find important factors that affect carbon emissions and make predictions for the future. Many reasons such as increasing population, increasing use of fossil fuel vehicles, increasing industrialization in the world after the industrial revolution, waste materials and urbanization affect carbon emissions. Carbon emission estimation is important to raise awareness between states and the public and to learn about measures to be taken. Carbon emission measurements can be made with sensors and devices with Internet of Things (IoT) systems. Regions, where carbon emissions are high, can be determined by IoT. Real-time monitoring of carbon dioxide emissions can be done with IoT systems. Each of the factors affecting carbon emission was estimated to estimate. Factor estimates were used in the regression equation. In addition, we aim to clarify the measures that can be taken for the factors used in the regression equation. In the regression equation, forest areas, waste, the number of incoming tourists, the use of renewable energy sources and the number of vehicles used have an important effect. In this article, Moving Average, Single and Double Exponential Smoothing and Winter Method are the prediction methods. As a result, the amount of carbon emission will increase in the future. The results obtained to prove this diagnosis. Measures need to be taken for CO2 emissions. Although global warming cannot be eliminated, slowing down can be achieved with IoT based systems and applications.