Combustion of fossil fuels are the main source of man-made Greenhouse Gas (GHG) emissions. Weather it is in power generation or manufacturing industries; weather in ground transportation or aviation, wherever fossil fuels are burnt to produce energy, GHGs (particularly CO2) are emitted to the atmosphere. Petroleum products are one of the main such fuels whose market events can hugely influence the emission control strategies of the industries. In this paper, we provide an extensive model to investigate the effects of oil market variations on the volumes of the carbon emissions.
Based on the system dynamics methodology, we perform a detailed literature survey on the factors involved in carbon emissions. In particular, we find the main variables involved in the decision making process of the power generation, manufacturing, and transportation industries. We build a causal model that describes the relations between these variables and utilize the related historic data, such as for volumes of emissions by sector and resources, emission allowance price (in an Emission Trading System (ETS)), global oil price, demand and supply, and economic growth. The relations between the variables are derived using time-series analysis wherever possible and look-up tables, otherwise. The overall model is reduced to a system of ordinary differential equations that is solved using numerical Euler methods.
Our oil market model is used to simulate several possible events in the oil market that can drastically affect either demand or supply. Moreover, stochastic events are also introduced where the occurrence of changes in the main market variables and the amount of such changes follow a random walk process. Based on our analysis in the carbon emissions, it is noted that the industries can change their short, mid and long term strategies on the portfolio of the natural resources that are utilized. However, the amount of reactions indicate different elasticities based on the type of industries. For instance, power sector as the main source of carbon emissions in the EU can plan for their mid-term portfolio based on the price changes, whereas in the long-term the effect of the EU regulations and goals in terms of the carbon emission (enforced by the ETS) play a more significant role. Our simulation results confirm these findings. Moreover, a detailed case study of related oil market events in 2016 is provided whose effects are simulated in the model to show the carbon emissions changes.
A system dynamics model that combines the oil market and carbon emission model is provided and the effect of stochastic events in the oil market (that result in the oil price changes) are investigated. A case study of 2016 events are provided and possible future events are simulated to investigate the changes in volumes of carbon emissions.