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Traditional energy planning methods are mostly related to newly-built area. However, in most already-built regions, the existing district energy systems (DESs) need to be ameliorated due to insufficient capacity and low efficiency. This paper investigates the methodology of expansion planning, which can offer planners a viable way to expand existing DESs. The term “expansion” aims to increase the supply capacity of the energy forms, e.g., steam, hot water and electricity, which cannot be accessed from national or urban energy supply network, and meanwhile increase energy utilization efficiency and cut CO 2 emission. Three parts of the methodology, including problem analysis in current DESs, demand side analysis and the existing DES expansion, are introduced in this paper. New concepts of load structure and evaluation system of the whole district are proposed in this methodology. A case analysis of Ningbo Hi-Tech District, China is conducted to shed light on the application of this method. [ABSTRACT FROM AUTHOR]

The surge in energy consumption and CO 2 (carbon dioxide) emissions is exacerbating global warming. The Chinese government has promised to reduce CO 2 emission by 60%–65% per unit of GDP over the 2005 level by around 2030. Analyzing the factors influencing CO 2 emissions is one of the key aspects involved in effectively reducing greenhouse gas emissions. In this paper, we add climatic factors based on socio-economic factors, and adopt the extended STIRPAT model to investigate the mechanism driving emissions by the co-action of natural and socio-economic factors. The results show that the 1995–2014 emissions in China's Zhejiang province had an upward trend with growth rates varying between intermediate periods. The order of the factors' elasticity coefficients is urbanization rate (0.181) > GDP per capita (0.180) > population (0.177) > energy intensity (0.170) > trade openness (0.170) > cooling degree days (0.127) > mean temperature anomaly (0.116). Economic development and urbanization were the main factors promoting CO 2 emissions in 1996–1999, while economic development and foreign trade were the main factors in 2000–2014. Policy makers should pay more attention to keeping a healthy pace of economic development, introducing more low energy consumption and low pollution enterprises and encouraging technological innovation. Improving the quality of urbanization, guiding a sustainable lifestyle, adjusting the structure of foreign trade and curbing energy intensity are also expected to reduce emissions. [ABSTRACT FROM AUTHOR]

Rapid urbanization has exerted substantial pressure on China’s energy system and contributed to climate change. To find the key drivers of urban residential energy consumption and CO 2 emissions, this paper uses an extended Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model that employs city-level data to examine the influences of population scale, income level, population compactness and price on house-based residential energy consumption, energy-related CO 2 emissions and private vehicle ownership. The empirical results indicate that factors such as population scale, affluence, and population compactness can lead to increases in residential energy consumption and CO 2 emissions. In terms of transportation, income and population scale positively drive the growth of private vehicle ownership, while the fuel price negatively influences private vehicle ownership. Moreover, population scale is the most important factor in residential energy consumption and CO 2 emissions. Finally, policy recommendations are suggested for China’s urban development strategy and urban design and to encourage technology innovations that reduce residential energy consumption and CO 2 emissions. [ABSTRACT FROM AUTHOR]

Since the combustion of fossil fuel became the largest contributing factor of greenhouse gas emissions in China, the growth of energy consumption caused by urbanization has led to significant increase in carbon emissions. Applying both the carbon-emissions-coefficient and the sector-energy-consumption method, we predicted the energy consumption and carbon emissions, explored the characteristics of energy consumption and carbon emissions in different urbanization stages, and analyzed the energy crisis in Shandong which is a typical province in China. The results indicate that in 2015 and 2020, the total primary energy consumption will be 1.57 times and 1.85 times higher than that of in 2009, and the carbon emissions are estimated to be 1.48 times and 1.67 times respectively. The urbanization has distinct positive effects on energy consumption and carbon emissions, and the influence is more obvious in the intermediate-stage than in the early-stage. From a policy perspective, this paper could provide valuable information for planners and decision makers to formulate feasible and practical polices with a view to optimize energy structure and mitigate carbon emissions. [ABSTRACT FROM AUTHOR]

China is experiencing a stage of rapid urban development. The energy consumption and related carbon dioxide emissions of households continue to increase. This paper calculates direct and indirect carbon dioxide emissions of households based on the input–output method in China from 1996 to 2012. The results reveal that there were more total carbon dioxide emissions from urban households than from rural households, far more indirect emissions from urban households than from rural households, slightly more direct emissions from urban households than from rural households, and differences in direct carbon dioxide emissions from various fuels and in indirect emissions from various sectors between urban and rural households. To examine the causal relationship between urbanization and the carbon dioxide emissions of households, cointegration and Granger causality tests are applied. A unidirectional causal relation was found running from urbanization to both direct and indirect household carbon dioxide emissions, and the direct and indirect carbon dioxide emissions of households would increase 2.9% and 1.1%, respectively, for every increase of one percent in urbanization. We discuss the reasons of why the development of urbanization will lead to more household direct and indirect carbon dioxide emissions, and suggest certain policy implications for urbanization and carbon dioxide emissions based on the results of this study. [ABSTRACT FROM AUTHOR]

Based on analysis of input–output energy and household expenditure data (IO-EA-expenditure), this paper calculates China’s indirect carbon emissions from residential consumption in 2002 and 2007, by region. Then a new Structural Decomposition Analysis (SDA) model is proposed to investigate the regional variations of impacts of urbanization, consumption ratio and consumption structure on residential indirect CO 2 emissions in China during 2002–2007. As the results suggest, expansion of urbanization and upgrade of consumption structure play important roles in the growth of residential indirect emissions. Transformation of consumption ratio, contributing the most to emissions in the eastern region, reduces indirect emissions in all regions to a certain extent. The persistent decline of carbon emission intensity still contributes significantly to the decrease in emissions and the rise of per capita consumption plays a dominant role in the growth of residential indirect emissions. Based on empirical results, this article provides policy suggestions which can help reduce China’s residential indirect CO 2 emissions. [ABSTRACT FROM AUTHOR]

Abstract: To find the key impact factors of CO2 emissions to realize the carbon intensity target, this paper examined the impact factors of population, economic level, technology level, urbanization level, industrialization level, service level, energy consumption structure and foreign trade degree on the energy-related CO2 emissions in Guangdong Province, China from 1980 to 2010 using an extended STIRPAT model. We employed ridge regression to fit the extended STIRPAT model. Empirical results indicate that factors such as population, urbanization level, GDP per capita, industrialization level and service level, can cause an increase in CO2 emissions. However, technology level, energy consumption structure and foreign trade degree can lead to a decrease in CO2 emissions. The estimated elastic coefficients suggest that population is the most important impact factor of CO2 emissions. Industrialization level, urbanization level, energy consumption structure, service level and GDP per capita are also significant impact factors, but the other factors such as technology level and foreign trade degree are less important impact factors. Some policy recommendations are also given on how to mitigate the growth of CO2 emissions. [Copyright &y& Elsevier]