Open AccessThe growth of energy efficiency of the Baikal region is the basis for its sustainable development
Author(s) -
Svetlana Muzychuk,
Roman Muzychuk
Publication year - 2019
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/272/3/032234
Subject(s) - energy intensity , energy balance , sustainable development , efficient energy use , energy (signal processing) , regression analysis , research object , gross domestic product , environmental economics , environmental science , computer science , econometrics , economics , mathematics , geography , statistics , macroeconomics , regional science , engineering , ecology , biology , electrical engineering , machine learning
The Baikal region has a special status of economic activity, as an object of world heritage. In Lake Baikal there are about 20% of the world’s reserves of fresh fresh water. The urgency of energy efficiency growth is determined by the industry specialization of the economy and the requirements for preserving the Baikal nature. The purpose of the research: to identify the significant factors affecting the energy efficiency of the economy and to propose mechanisms for their implementation. A methodical approach is developed based on methods of economic-mathematical modeling, system analysis, statistical analysis, balance and indicative methods. An information and computing complex has been developed that includes: a system of models and databases for analyzing and forecasting the development of the fuel and energy complex of the eastern regions of Russia; economic-mathematical models of fuel and energy balances; methods for assessing the energy efficiency of the economy; methods of statistical analysis to identify factors that affect energy efficiency. Significant factors of reducing the energy intensity of the gross regional product of the Baikal region have been identified, and multiple regression equations have been developed to predict the energy intensity.