The growth pattern and fuel life cycle analysis of the electricity consumption of Hong Kong

As the consumption of electricity increases, air pollutants from power generation increase. In metropolitans such as Hong Kong and other Asian cities, the surge of electricity consumption has been phenomenal over the past decades. This paper presents a historical review about electricity consumption, population, and change in economic structure in Hong Kong. It is hypothesized that the growth of electricity consumption and change in gross domestic product can be modeled by 4-parameter logistic functions. The accuracy of the functions was assessed by Pearson's correlation coefficient, mean absolute percent error, and root mean squared percent error. The paper also applies the life cycle approach to determine carbon dioxide, methane, nitrous oxide, sulfur dioxide, and nitrogen oxide emissions for the electricity consumption of Hong Kong. Monte Carlo simulations were applied to determine the confidence intervals of pollutant emissions. The implications of importing more nuclear power are discussed. ► We model electricity consumption and GDP using 4-parameter logistic functions. ► We apply backward life cycle approach to quantify GHG, SO2, and NOx emissions. ► Pollution reduction can be achieved by altering fuel mix, using renewable energy, and planting trees. Understanding the growth pattern and fuel life cycle analysis of electricity consumption is important for pollution prevention.