Scenario Analysis on Energy Consumption and CO2 Emissions Reduction Potential in Building Heating Sector at Community Level

Chuan Tian,Shuai Li,Guohui Feng,Fuqiang Xu

doi:10.3390/su11195392

Abstract

Energy consumption and carbon emissions of building heating are increasing rapidly. Taking Liaobin coastal economic zone as an example, two scenarios are built to analyze the potential of energy consumption and CO2 emissions reduction from the aspects of laws, regulations, policies and planning. The baseline scenario refers to the traditional way of energy planning and the community energy planning scenario seeks to apply community energy planning within the zone. Energy consumption and CO2 emission are forecast in two scenarios with the driving factors including GDP growth, changes in population size, energy structure adjustment, energy technology progress, and increase of energy efficiency. To improve accuracy of future GDP and population data prediction, an ARIMA (Autoregressive Integrated Moving Average model) (1,1,1) model is introduced into GDP prediction and a logistics model is introduced into population prediction. Results show that compared with the baseline scenario, energy consumption levels in the community energy planning scenario are reduced by 140% and CO2 emission levels are reduced by 45%; the short-term and long-term driving factors are analyzed. Policy implications are given for energy conservation and environmental protection.

Highlights

In recent years, owing to rapid development of science and technology in the world, many serious environmental problems have appeared, such as environmental pollution, energy shortages and global climate change [1,2,3,4]
Lin et al developed a LEAP model to analyze the future trends of energy demand and greenhouse gas (GHG) emissions in Xiamen city, and the results showed that the clean energy substitution measure was the most effective in terms of energy saving and GHG emissions mitigation, and that the industrial sector had the largest abatement potential in Xiamen in 2010 [24]
To improve accuracy of future GDP and population data prediction, an ARIMA (1,1,1) model is introduced into GDP prediction and a logistics model is introduced into population prediction

Summary

Introduction

In recent years, owing to rapid development of science and technology in the world, many serious environmental problems have appeared, such as environmental pollution, energy shortages and global climate change [1,2,3,4]. Energy-saving and carbon dioxide emission reduction have become major topics of conversation worldwide [5,6,7] It is the most populous nation in the world, China’s per capita share of resources is below the global average. In 2016, before the Paris Agreement came into effect, the Chinese government put forward the 13th Five-Year Plan of Work on Controlling Greenhouse Gas Emissions. These targets specify that China’s carbon dioxide emissions will peak around 2030 and peak as soon as possible and are incorporated into medium-term and long-term planning of national economic and social development as obligatory. Carbon dioxide emission has become an inflexible constraint in community energy planning [10]

Methods

Results

Conclusion