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Guangdong is China's largest province in terms of energy consumption. The energy-related carbon emissions in Guangdong province are calculated, and two extended and improved decomposition models for energy-related carbon emissions are established with the Logarithmic Mean Divisia Index method based on the basic principle of Kaya identity. Main results are as follows: (1) the energy-related carbon emissions from the three strata of industry, except the primary industry, and household energy consumption in Guangdong province show increasing trend from 1995 to 2009; (2) the main driving and inhibiting factors which influence energy-related carbon emissions are economic output and energy intensity, respectively, while the contributions of energy mix, industrial structures, population size and living standards are not significant during the period of interest. It is concluded that optimizing the energy mix by exploiting new energy sources and cutting down energy intensity by developing low-carbon technologies are the two most effective approaches to reduce carbon emissions for Guangdong province in the future. The results and proposals in this paper provided reference for relevant administrative departments in the Government of Guangdong province to develop policies for energy conservation and emission reduction as well as to promote development of low-carbon economy. [ABSTRACT FROM AUTHOR]

Abstract: Making new coal-fired power plants carbon capture ready (Carbon Capture Ready) in China has been recognised as a crucial by a number of stakeholders academics, energy companies and regional government, based on a study in EU-UK-China NZEC project. A number of publications have investigated the definition, engineering requirements, economic and finance of CCR for China. However there remain a number of questions regarding the extent to which a plant’s physical location might constrain the feasibility of CCS retrofit. To address this issue, a Geographical Information System (GIS) has been used as a tool for mapping current and planned large carbon dioxide sources in Guangdong, also illustrating potential storage sites and calculating possible carbon dioxide transportation route. This paper investigates the location factors that should be considered when locating new build CCR power plants and demonstrates the methodology of using GIS software with spatial analysis in planning new build power plant in Guangdong. A preliminary study has identified over 30 large power plants within the region, with plant locations and historical emission data collected and presented in ArcGIS. Factors such as distance to potential storage site, route of CO2 pipeline, extra space on site and potential development plan etc. were investigated in the modelling and calculated the potential source and sink solution. The study then moves on to suggest possible new build plant locations which can be easily fitted in to the current network, based on economic optimisation. The scope for future coal plant development combined with a possible nuclear plant siting plan is discussed towards the end of the paper. Guangdong province, which owns the third largest coal-fired power installed capacity out of 31 provinces, generated over 8% of China’s total electricity every year for the past 15 years. CO2 storage opportunities could be found in the surrounding South China Sea, where Guangdong has a total of 4,300 km of coastline and some small scale oil fields on shore within the region. It is also among the first places to start the national open and reform policy in China. The province is one of the richest in China, with the highest GDP among all other provinces since 1989, and the foreign trade accounts for more than a quarter of China’s total amount. It also contributes around 12 of the total national economic output. Currently, the provincial government is proposing a low carbon roadmap, which is the first of its kind in China. The work has created a totally new thinking on capture ready power plant planning. This differs from existing studies (e.g., which aim to investigate the existing carbon dioxide emission sources at specified location and provide source and sink matching analysis. Instead the study focuses on policy implementation for new build capture ready power plants. Three clusters within Guangdong province are identified as potential temporary CO2 storage hubs before transporting the gas to a long term storage site. When officials are planning new power plant locations from a capture ready perspective, the plants should not necessarily be close to storage sites in straight line, but rather should be within a reasonable distance of a cluster. Transport of the captured CO2 will not be limited to pipelines, but could be extended to road and rail tankers. Power plant parameters and storage site data were collected for this research. Public transportation, utilities, landscapes, river, land used and population data were referenced from various sources; therefore, some of the data could be out of date. Nevertheless, it should still provide enough information when deciding the location of the transport cluster. Any future work could build on the existing model with updated data. Moreover, it could fit in with the national natural gas transportation network and utility planning network to provide long term integrated energy system analysis. The paper could provide policy makers, investors and urban planning officials with a view on how conventional thermal power plant investment and planning could be optimised, using Carbon Capture Ready designs, to keep the CCS retrofitting option open. [Copyright &y& Elsevier]

This paper investigates the effects of population, investment, urbanization, industrial structure, policy instrument, and enterprise size on energy intensity in Guangdong, China. A dynamic optimal theoretical framework is utilized and empirical results are reported using panel data from 2006 to 2015. The fixed effects models and spatial fixed effects models both show that population, investment, urbanization, and enterprise size decrease energy intensity, but industrial structure and policy instrument drive it up; population, investment, urbanization, and enterprise size increase the energy consumption and economic output, but industrial structure and policy instrument decrease them, China; the energy intensity has significant spatial spillover effect that should be considered in Guangdong, China. Recommendations for Resource Managers•Population, investment, urbanization, and enterprise size decrease energy intensity, but industrial structure and policy instrument drive it up.•Population, investment, urbanization, and enterprise size increase the energy consumption and economic output, but industrial structure and policy instrument decrease them, China.•The energy intensity has significant spatial spillover effect that should be considered in Guangdong, China. [ABSTRACT FROM AUTHOR]

• The new power supply structure resulting from the new policy has been considered. • The new models project the inefficient points onto a more realistic efficient frontier. • The new models have the power to allocate the shared resources. • Results show that the power production stage is allocated less shared resources. • The power sale stage's efficiency is lower than the one of power production stage. To relieve the problems of energy shortage and environmental pollution, many countries have implemented a variety of policies to improve the energy efficiency of the power industry. To understand the impacts of such policies on energy efficiency, this paper constructs novel network data envelopment analysis models to recognize the policy-induced structural changes in the power system. Compared with previous studies, the new models project the inefficient points onto a more realistic efficient production frontier, considering how the distribution proportion of shared resources will change when the power system, modeled as a power generation stage and a power sale stage, is led by the latter stage. Our empirical study on China's power system shows that the province of Guangdong and the eastern region of China perform best, and all power production stages perform better than the corresponding power sale stages. The development of the two power subsystems in the four regions is unbalanced. More than half of the power supply systems choose to allocate more proportion of the shared resources to the sale stage rather than use a more balanced distribution between the two stages. [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]

Abstract: This paper uses two methods LMDI and Laspeyres to analysis the influences the industrial structure has on energy consumption,including how much the three industries have contribution to energy intensity .The results we conclude are:1) Economy has a strong stimulating effect on energy consumption;2)The effect of improving energy efficiency by using science and technology is significant in Guangdong province, especially in the secondary industry; 3) The secondary industry plays a positive role in reducing energy intensity, and the advantages of the tertiary industry isn’t displayed. [Copyright &y& Elsevier]

Because of irreversibility on building construction, building energy efficiency design is more depended on simulation technology. Ministry of Housing and Urban-Rural Development of China also stated that China's building energy consumption accounted for 27.5% of the total energy consumption in 2012. Energy consumption is simulated based on the heat transfer principle of building wall, windows, roof and ventilation. Improved measurements are proposed for simulation cases. The heating, ventilation, and air conditioning energy consumption of benchmark and energy efficiency building are simulated based on EnergyPlus software. The most effective energy-saving measurements of energy efficiency building are improving air-conditioning system performance and thermal properties of wall and window. The results show that the energy efficiency ratio of refrigeration system should be more than three and energy-saving ratio is about 30%. Heat transfer coefficient of wall and window should be less than 1.0 W/m2k- and 2.0, W/m2k- the energy-saving ratio is more than 16% and 10%, respectively. The sum energy-saving ratios of refrigeration system, wall and window are about 56%. The energy efficiency ratios of roof and air exchanges number are not very obvious. Some energy-saving technologies with high cost are put forward based on simulation results which provide effective ways for building energy efficiency in Guangdong province, China. [ABSTRACT FROM AUTHOR]