Search

Abstract: The pulp and paper industry is one of the most energy-intensive industries worldwide. In 2007, it accounted for 5% of total global industrial energy consumption and 2% of direct industrial carbon dioxide (CO2) emissions. An energy audit is a primary step toward improving energy efficiency at the facility level. This paper describes a plant-wide energy audit aimed at identifying energy conservation and CO2 mitigation opportunities at a paper mill in Guangdong province, China. We describe the energy audit methods, relevant Chinese standards, methods of calculating energy and carbon indicators, baseline energy consumption and CO2 emissions of the audited paper mill, and nine energy-efficiency improvement opportunities identified by the audit. For each of the nine options, we evaluate the energy conservation and associated CO2 mitigation potential. The total technical energy conservation potential for these nine opportunities is 967.8terajoules (TJ), and the total CO2 mitigation potential is equal to 93,453tonnes CO2 annually, representing 14.4% and 14.7%, respectively, of the mill’s total energy consumption and CO2 emissions during the audit period. [Copyright &y& Elsevier]

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]

Coal mining not only produces, but also consumes a large amount of energy. Coal production has an extremely high energy efficiency potential, and benchmarking is critical to discover this potential. To address problems such as ambiguity of coal production (e.g. underground mining), benchmarking range and absence of both indicators and standards for energy efficiency benchmarking, this paper makes use of product-based and process-based benchmarking. These two techniques are used to construct a benchmarking system for coal production with high energy efficiency, and improve the standards used at the eight coal mines owned by the Yankuang Group. Comparison and analysis of benchmarking in enterprises indicates that energy use during raw coal production could be reduced by 22.77%. Across China energy savings from coal production could reach 15.98–32.98 Mtce, with an equivalent 42–87 Mt of CO 2 emissions saved. Lastly, this paper provides measures to improve coal production energy efficiency. [ABSTRACT FROM AUTHOR]

Highlights • The input–output model and ecological network analysis (ENA) are integrated. • The control and dependence conditions of economic sectors in China are analyzed. • The key regions and sectors for carbon mitigation of China are identified. Abstract In this paper, multi-regional input–output analysis (MRIO) and ecological network analysis (ENA) are combined to assess carbon flows within China and identify key regions and sectors in the context of spatial heterogeneity for effective carbon mitigation. An interregional carbon network model is established by articulating the directions and magnitudes of carbon flows based on MRIO. ENA is then used to unveil indirect carbon flows and mutual relationships among regions. The results show that the northwest is the largest controller for most regions in China. Most carbon emissions in the rest of China are induced by the east’s final demand and substantial consumption. In addition, at sectoral level, the control and dependence abilities vary by region in China. This study provides an integrated framework to investigate interregional carbon emission structure, identify efficient pathways for coordinated emission mitigation, and reduce global carbon inequality across regions. [ABSTRACT FROM AUTHOR]

This paper explores the optimization scheme of carbon trading in China based on a novel energy-saving and emission-reduction (ESER) system with carbon price constraints. With the aid of nonlinear dynamics theory, the dynamics behavior of the novel system is discussed. Genetic algorithm and back propagation neural network is used to identify the quantitative coefficients according to the statistical data of the second period in European Union (EU). Taking the actual situation in EU for instance, the variables which are sensitive to carbon trading are detailedly researched. Enlightened by the EU’s experience, an optimal road of China ’ s carbon trading is put forward. The results show that carbon emissions could be controlled by carbon trading. The investment to carbon trading hampers economic growth in the near future, and ESER technical progress is negatively correlated with carbon trading in the long run. Demand and supply relationship is closely related to carbon price, both are the important issues in carbon trading system. Excessive government control and extortionate carbon price will deliver the opposite effect and even fatal influence on carbon trading system. [ABSTRACT FROM AUTHOR]

The key distinction between production-based and consumption-based accounting lies in the way in which trade-embodied emissions are allocated between producer and consumer regions. Yet, these two regions are not necessarily directly connected to each other in supply chains, due to spatial production fragmentation. To better understand the link from the production-based to the consumption-based regional carbon inventories, this paper defines the economic length of carbon transfer (ELCT) as the number of administrative border-crossing involved in the influence process of a region’s final demand on the carbon emissions of another region. Using a multi-regional input-output analysis framework for China, we propose an approach to calculating the ELCT related to a region’s production or demand for domestic consumption or international export. We find that the average ELCT in 2010 is 1.34 and that more than a quarter of interregional carbon transfer crosses provincial borders twice or more. The provincial and sectoral analysis of ELCT reveals that spatial production fragmentation is an important challenge to be conquered for successful implementation of consumption-based climate regulations. [ABSTRACT FROM AUTHOR]

Accurately understanding the real situation of China’s carbon emissions at the provincial level is not only crucial for realizing carbon mitigation in China, but also of great importance for tackling climate change on a global scale. This paper uses detailed energy consumption data subdivided within each fuel type and sector-specific emission factors, to calculate both direct and indirect energy-related CO 2 emissions for China’s provinces, and offers provincially-targeted policy proposals on emission reductions. The results uncover large divergences in calculation of provincial CO 2 emissions between production-based and consumption-based accounting approaches. Considering the large amount of interprovincial CO 2 emission transfers embodied in secondary energy deployment, the consumption-based accounting performs better in reflecting the actual features and responsibilities of carbon emissions in the provinces of China. From the consumption perspective, Shandong, Hebei, Jiangsu, Inner Mongolia, Guangdong, Henan, Liaoning and Shanxi contributed to the majority of China’s carbon emission growth during the period of 1996–2013, while Xinjiang, Sichuan, Anhui, Tianjin and Hunan were playing an increasingly important role. These two groups of provinces should be regarded as the key regions for national emissions abatement. Meanwhile, the energy industry was the top sectoral contributor to CO 2 emissions growth in most provinces, while service and household sectors made increasingly significant impacts on driving up provincial emissions. Together with ongoing efforts in the energy sector, the mitigation of CO 2 emissions in service and household sectors deserves much more attention, especially in the transportation and urban household sectors. Furthermore, the temporal trends of carbon emissions in various provinces, as well as their factor and sectoral driving forces, varied greatly with each other. Therefore, each of the provinces should formulate emission reduction policies according to their own situation, and target the key driving factors and sectors of carbon emissions at the current stage or in the near future. [ABSTRACT FROM AUTHOR]

The use of data envelopment analysis (DEA) in China’s regional energy efficiency and carbon emission efficiency (EE&CE) assessment has received increasing attention in recent years. This paper conducted a comprehensive survey of empirical studies published in 2006–2015 on China’s regional EE&CE assessment using DEA-type models. The main features used in previous studies were identified, and then the methodological framework for deriving the EE&CE indicators as well as six widely used DEA models were introduced. These DEA models were compared and applied to measure China’s regional EE&CE in 30 provinces/regions between 1995 and 2012. The empirical study indicates that China’s regional EE&CE remained stable in the 9th Five Year Plan (1996–2000), then decreased in the 10th Five Year Plan (2000–2005), and increased a bit in the 11th Five Year Plan (2006–2010). The east region of China had the highest EE&CE while the central area had the lowest. By way of conclusion, some useful points relating to model selection are summarized from both methodological and empirical aspects. [ABSTRACT FROM AUTHOR]

The rapid growth of energy consumption in China has led to increased emissions of CO 2 . As a response, the Chinese government has proposed a series of carbon mitigation strategies, such as switching the production structure and implementing energy-saving and emission–reduction technologies in energy-intensive sectors. In this paper, an integrated assessment approach was developed by combining the Stock-based model, the China-TIMES model and the co-benefits analysis model. The approach was applied to China’s steel sector to simulate the trends of energy consumption and air emissions (CO 2 , SO 2 , NO x , and PM 10 ) during 2010–2050, under a reference scenario and three alternative carbon mitigation scenarios. The model quantified the air emission reductions, water conservation, and associated co-benefits during the study period. The modeling results show that by switching the production structure and implementing energy-saving and emission–reduction technologies, China’s steel sector can achieve significant co-benefits of carbon mitigation, water conservation, averted mortality and averted morbidity. Despite certain limitations and uncertainties associated with the elements of the integrated assessment approach, the results demonstrate that substantial social benefits and health effects could be realized through carbon mitigation strategies in China’s steel sector. [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]

As the world's largest developing country and greenhouse gas emitter, China's residential energy consumption (REC) is now responsible for over 11% of the country's total energy consumption. In this paper, we present a novel method that utilizes spatially distributed information from the Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) and human activity index (HAI) to test the hypothesis that counties with similar carbon dioxide emissions from REC are more spatially clustered than would be expected by chance. Our results revealed a high degree of county-level clustering in the distribution of emissions per capita. However, further analysis showed that high-emission counties tended to be surrounded by counties with relatively low per capita GDP levels. Therefore, our results contrasted with other evidence that REC emissions were closely related to GDP levels. Accordingly, we stress the need for the consideration of other factors in determining emission patterns, such as residential consumption patterns (e.g., consumer choices, behavior, knowledge, and information diffusion). [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: Evaluation of the energy and emissions efficiency of Chinese regions has recently attracted increasing interest. A number of previous studies have contributed to the measurement of energy efficiency using various types of data envelopment analysis (DEA) techniques. However, most of these DEA-based energy efficiency analyses were restricted to the radial expansions of outputs or radial contractions of inputs. In this paper, we utilize the multi-directional efficiency analysis (MEA) approach instead of the traditional radial DEA to investigate Chinese regional energy and emissions efficiency. Since MEA selects benchmarks such that the input contractions or output expansions are proportional to the potential improvement identified by considering the improvement potential in each input or output variable separately, not just the efficiency status but also the efficiency patterns of different Chinese regions and areas can be detected. The empirical study results indicate that, in general, the MEA efficiency of China experienced an increasing process over the study period 1997–2010; the east area overall is more MEA efficient than the central area and the west area of China during the study period; the significant higher MEA efficiency of the east area to the central area and the west area are due to both the higher energy specific efficiency and the higher emissions specific efficiency of the east area compared to the other two areas; the provinces of Hebei, Shanxi, Inner Mongolia, Shandong, Henan, and Hubei etc. have both high energy saving potentials and high emissions reduction potentials, thus they will play the most important roles in China’s effort on energy conservation and CO2 emissions mitigation. [Copyright &y& Elsevier]

Abstract: The residential sector is the second largest consumer in China with great room for energy consumption growth, as well as the related carbon emissions. Thus, how to reduce the growth rate of carbon emissions is crucial for realizing the target of energy conservation and emission mitigation in the residential sector. Based on a bottom-up framework with survey data and official statistics, this paper examines the changes of aggregate residential carbon intensity, and analyzes its driving factors from an end-use perspective over the period of 1996–2008. The Adaptive Weighting Divisia with rolling base year index specification is applied to identify the quantitative effects of driving components and their further decomposing results of end-use activities. Results show that, the residential aggregate carbon intensity has grown rapidly since 2002 in both urban and rural China. The changes in primary fuel mix for electricity and heat generation have an overall negative but insignificant effect on the residential aggregate carbon intensity, while the effect of final energy structure is positive with a rising tendency. The significant impact of changes in energy intensity shift from negative to positive over time, and contribute more to a decline than to an increase. The driving force arising from the residential end-use mode has the highest contribution to the increase of aggregate carbon intensity. Finally, some policy implications are proposed to effectively slow down the accelerated rate of the residential aggregate carbon intensity. Guiding households towards energy-saving behaviors is recommended as a wise and first policy choice. [Copyright &y& Elsevier]

Abstract: Operation mode of combined cooling heating and power (CCHP) system determines its energetic and environmental performances. This paper analyzes the energy flows of CCHP system and separated production (SP) system. The fuel energy consumptions of CCHP system following electrical demand management (EDM) and thermal demand management (TDM) are deduced respectively. Three indicators: primary energy saving, exergy efficiency and CO2 emission reduction, are employed to evaluate the performances of CCHP system for a commercial building in Beijing, China. The feasibility analysis shows that the performance of CCHP system is strictly dependent upon building energy demands. The selection of CCHP operation modes is systemically based on building loads, CCHP system and local SP system. The calculation results conclude that CCHP system in winter under EDM achieves more benefits than in summer. The sensitivity discussion indicates that the coefficient of performance for cooling and the efficiency of electricity generation are the most sensitive variables to the energetic and environmental performances of CCHP system. [Copyright &y& Elsevier]