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357 KiB

Open AccessArticle

Net Energy, CO₂ Emission and Land-Based Cost-Benefit Analyses of Jatropha Biodiesel: A Case Study of the Panzhihua Region of Sichuan Province in China

by Xiangzheng Deng, Jianzhi Han and Fang Yin

Energies 2012, 5(7), 2150-2164; https://doi.org/10.3390/en5072150 - 28 Jun 2012

Cited by 52 | Viewed by 8234

Abstract

Bioenergy is currently regarded as a renewable energy source with a high growth potential. Forest-based biodiesel, with the significant advantage of not competing with grain production on cultivated land, has been considered as a promising substitute for diesel fuel by many countries, including [...] Read more.

Bioenergy is currently regarded as a renewable energy source with a high growth potential. Forest-based biodiesel, with the significant advantage of not competing with grain production on cultivated land, has been considered as a promising substitute for diesel fuel by many countries, including China. Consequently, extracting biodiesel from Jatropha curcas has become a growing industry. However, many key issues related to the development of this industry are still not fully resolved and the prospects for this industry are complicated. The aim of this paper is to evaluate the net energy, CO₂ emission, and cost efficiency of Jatropha biodiesel as a substitute fuel in China to help resolve some of the key issues by studying data from this region of China that is well suited to growing Jatropha. Our results show that: (1) Jatropha biodiesel is preferable for global warming mitigation over diesel fuel in terms of the carbon sink during Jatropha tree growth. (2) The net energy yield of Jatropha biodiesel is much lower than that of fossil fuel, induced by the high energy consumption during Jatropha plantation establishment and the conversion from seed oil to diesel fuel step. Therefore, the energy efficiencies of the production of Jatropha and its conversion to biodiesel need to be improved. (3) Due to current low profit and high risk in the study area, farmers have little incentive to continue or increase Jatropha production. (4) It is necessary to provide more subsidies and preferential policies for Jatropha plantations if this industry is to grow. It is also necessary for local government to set realistic objectives and make rational plans to choose proper sites for Jatropha biodiesel development and the work reported here should assist that effort. Future research focused on breading high-yield varieties, development of efficient field management systems, and detailed studies lifecycle environmental impacts analysis is required to promote biologically and economically sustainable development of Jatropha biodiesel and to assist government agencies in setting realistic objectives and appropriate and advantageous policies for the regions and the country. Full article

(This article belongs to the Special Issue Low Carbon Transitions Worldwide)

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472 KiB

Open AccessArticle

An Optimization Model of Carbon Sinks in CDM Forestry Projects Based on Interval Linear Programming

by Dufeng Li, Yang Zhang, Xianen Wang, Yu Li and Wenjin Zhao

Energies 2012, 5(6), 1766-1781; https://doi.org/10.3390/en5061766 - 13 Jun 2012

Cited by 2 | Viewed by 6002

Abstract

This study describes the first general optimization model for complex systems with uncertain parameters and decision variables represented as intervals in CDM forestry projects. We work through a specific example of the optimization method developed for a Clean Development Mechanism (CDM) forestry project [...] Read more.

This study describes the first general optimization model for complex systems with uncertain parameters and decision variables represented as intervals in CDM forestry projects. We work through a specific example of the optimization method developed for a Clean Development Mechanism (CDM) forestry project in Inner Mongolia, China. This model is designed to optimize the carbon sink capacity of the new forests, and can deal with uncertainties in the carbon sink capacity, average annual rainfall, ecological parameters, and biological characteristics of tree species. The uncertain inputs are presented in the form of intervals, as are several of the optimized output variables. Compared with the project’s originally recommended scheme, the optimized model will absorb and fix between 1,142 and 885,762 tonnes of extra carbon dioxide. Moreover, the ecological and environmental benefits of the project are also raised to various extents. Full article

(This article belongs to the Special Issue Low Carbon Transitions Worldwide)

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1256 KiB

Open AccessArticle

Decomposition Analysis of the Mechanism Behind the Spatial and Temporal Patterns of Changes in Carbon Bio-Sequestration in China

by Jinyan Zhan, Haiming Yan, Bin Chen, Jiao Luo and Nana Shi

Energies 2012, 5(2), 386-398; https://doi.org/10.3390/en5020386 - 22 Feb 2012

Cited by 16 | Viewed by 7255

Abstract

Great attention has been paid to carbon bio-sequestration due to increasing concerns over global warming. Understanding the relationship between carbon bio-sequestration and its influencing factors is of great significance for formulating appropriate management measures for global warming mitigation. Since change in carbon bio-sequestration [...] Read more.

Great attention has been paid to carbon bio-sequestration due to increasing concerns over global warming. Understanding the relationship between carbon bio-sequestration and its influencing factors is of great significance for formulating appropriate management measures for global warming mitigation. Since change in carbon bio-sequestration is a complex process, it is difficult to take into account all of its influencing factors, while the panel data model may provide an effective way to measure their subtle effects. In this paper, decomposition analysis is applied to further analyze these influencing factors. The results indicate that climatic, demographic and geographical variables play important roles in explaining the spatial heterogeneity of carbon bio-sequestration in China, which is consistent with previous researches. Meanwhile, the irrigation rate is found to be the most critical factor influencing carbon bio-sequestration changes, followed by climatic and economic factors. These results may provide decision makers in China with important scientific reference information for formulating regional carbon bio-sequestration management policies, which are of great significance to alleviating and adapting to global warming. Full article

(This article belongs to the Special Issue Low Carbon Transitions Worldwide)

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594 KiB

Open AccessArticle

A Novel Multiscale Ensemble Carbon Price Prediction Model Integrating Empirical Mode Decomposition, Genetic Algorithm and Artificial Neural Network

by Bangzhu Zhu

Energies 2012, 5(2), 355-370; https://doi.org/10.3390/en5020355 - 17 Feb 2012

Cited by 85 | Viewed by 8438

Abstract

Due to the movement and complexity of the carbon market, traditional monoscale forecasting approaches often fail to capture its nonstationary and nonlinear properties and accurately describe its moving tendencies. In this study, a multiscale ensemble forecasting model integrating empirical mode decomposition (EMD), genetic [...] Read more.

Due to the movement and complexity of the carbon market, traditional monoscale forecasting approaches often fail to capture its nonstationary and nonlinear properties and accurately describe its moving tendencies. In this study, a multiscale ensemble forecasting model integrating empirical mode decomposition (EMD), genetic algorithm (GA) and artificial neural network (ANN) is proposed to forecast carbon price. Firstly, the proposed model uses EMD to decompose carbon price data into several intrinsic mode functions (IMFs) and one residue. Then, the IMFs and residue are composed into a high frequency component, a low frequency component and a trend component which have similar frequency characteristics, simple components and strong regularity using the fine-to-coarse reconstruction algorithm. Finally, those three components are predicted using an ANN trained by GA, i.e., a GAANN model, and the final forecasting results can be obtained by the sum of these three forecasting results. For verification and testing, two main carbon future prices with different maturity in the European Climate Exchange (ECX) are used to test the effectiveness of the proposed multiscale ensemble forecasting model. Empirical results obtained demonstrate that the proposed multiscale ensemble forecasting model can outperform the single random walk (RW), ARIMA, ANN and GAANN models without EMD preprocessing and the ensemble ARIMA model with EMD preprocessing. Full article

(This article belongs to the Special Issue Low Carbon Transitions Worldwide)

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977 KiB

Open AccessArticle

Low-Carbon Development Patterns: Observations of Typical Chinese Cities

by Meirong Su, Chen Liang, Bin Chen, Shaoqing Chen and Zhifeng Yang

Energies 2012, 5(2), 291-304; https://doi.org/10.3390/en5020291 - 13 Feb 2012

Cited by 50 | Viewed by 9165

Abstract

Threatened by the huge pressure caused by climate change, low-carbon cities have become an inevitable part of urban evolution. It is essential to evaluate urban low-carbon development levels to smoothly promote the construction of low-carbon cities. This paper proposes an evaluation index system [...] Read more.

Threatened by the huge pressure caused by climate change, low-carbon cities have become an inevitable part of urban evolution. It is essential to evaluate urban low-carbon development levels to smoothly promote the construction of low-carbon cities. This paper proposes an evaluation index system for urban low-carbon development from the points of view of economic development and social progress, energy structure and usage efficiency, living consumption, and development surroundings. A weighted sum model was also established. Selecting 12 typical Chinese cities as cases studies, an integrated evaluation was conducted based on the index system and the assessment model. The development speed and limiting factors of different cities were also analyzed. The 12 cities were ultimately classified into three groups in terms of their low-carbon development patterns by integrating all of the analysis results. Furthermore, suitable regulation and management for different patterns were suggested. This study both aids in assessing the executive effect of low-carbon city construction and helps to determine existing problems and suggest effective solutions. Full article

(This article belongs to the Special Issue Low Carbon Transitions Worldwide)

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277 KiB

Open AccessArticle

Changing Lifestyles Towards a Low Carbon Economy: An IPAT Analysis for China

by Klaus Hubacek, Kuishuang Feng and Bin Chen

Energies 2012, 5(1), 22-31; https://doi.org/10.3390/en5010022 - 27 Dec 2011

Cited by 76 | Viewed by 10051

Abstract

China has achieved notable success in developing its economy with approximate 10 percent average annual GDP growth over the last two decades. At the same time, energy consumption and CO₂ emissions almost doubled every five years, which led China to be the [...] Read more.

China has achieved notable success in developing its economy with approximate 10 percent average annual GDP growth over the last two decades. At the same time, energy consumption and CO₂ emissions almost doubled every five years, which led China to be the world top emitter in 2007. In response, China’s government has put forward a carbon mitigation target of 40%–45% reduction of CO₂ emission intensity by 2020. To better understand the potential for success or failure of such a policy, it is essential to assess different driving forces such as population, lifestyle and technology and their associated CO₂ emissions. This study confirms that increase of affluence has been the main driving force for China’s CO₂ emissions since the late 1970s, which outweighs reductions achieved through technical progress. Meanwhile, the contribution of population growth to CO₂ emissions was relatively small. We also found a huge disparity between urban and rural households in terms of changes of lifestyle and consumption patterns. Lifestyles in urban China are beginning to resemble Western lifestyles, and approaching their level of CO₂ emissions. Therefore, in addition to the apparent inefficiencies in terms of production technologies there is also a lot of room for improvement on the consumption side especially in interaction of current infrastructure investments and future consumption. Full article

(This article belongs to the Special Issue Low Carbon Transitions Worldwide)

247 KiB

Open AccessArticle

Alternative Scenarios for the Development of a Low-Carbon City: A Case Study of Beijing, China

by Lixiao Zhang, Yueyi Feng and Bin Chen

Energies 2011, 4(12), 2295-2310; https://doi.org/10.3390/en4122295 - 20 Dec 2011

Cited by 73 | Viewed by 10303

Abstract

The establishment of low-carbon cities has been suggested all over the World, since cities are key drivers of energy usage and the associated carbon emissions. This paper presents a scenario analysis of future energy consumption and carbon emissions for the city of Beijing. [...] Read more.

The establishment of low-carbon cities has been suggested all over the World, since cities are key drivers of energy usage and the associated carbon emissions. This paper presents a scenario analysis of future energy consumption and carbon emissions for the city of Beijing. The Long-range Energy Alternatives Planning (LEAP) model is used to simulate a range of pathways and to analyze how these would change energy consumption and carbon emissions from 2007 to 2030. Three scenarios have been designed to describe future energy strategies in relation to the development of Beijing city, namely a reference scenario (RS), control scenario (CS), and integrated scenario (IS). The results show that under the IS the total energy demand in Beijing is expected to reach 88.61 million tonnes coal equivalent (Mtce) by 2030 (59.32 Mtce in 2007), 55.82% and 32.72% lower than the values under the RS and the CS, respectively. The total carbon emissions in 2030 under the IS, although higher than the 2007 level, will be 62.22% and 40.27% lower than under the RS and the CS, respectively, with emissions peaking in 2026 and declining afterwards. In terms of the potential for reduction of energy consumption and carbon emissions, the industrial sector will continue to act as the largest contributor under the IS and CS compared with the RS, while the building and transport sectors are identified as promising fields for achieving effective control of energy consumption and carbon emissions over the next two decades. The calculation results show that an integrated package of measures is the most effective in terms of energy savings and carbon emissions mitigation, although it also faces the largest challenge to achieve the related targets. Full article

(This article belongs to the Special Issue Low Carbon Transitions Worldwide)

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265 KiB

Open AccessArticle

Embodiment Analysis for Greenhouse Gas Emissions by Chinese Economy Based on Global Thermodynamic Potentials

by Bo Zhang, Suping Peng, Xiangyang Xu and Lijie Wang

Energies 2011, 4(11), 1897-1915; https://doi.org/10.3390/en4111897 - 4 Nov 2011

Cited by 23 | Viewed by 7995

Abstract

This paper considers the Global Thermodynamic Potential (GTP) indicator to perform a unified assessment of greenhouse gas (GHG) emissions, and to systematically reveal the emission embodiment in the production, consumption, and international trade of the Chinese economy in 2007 as the most recent [...] Read more.

This paper considers the Global Thermodynamic Potential (GTP) indicator to perform a unified assessment of greenhouse gas (GHG) emissions, and to systematically reveal the emission embodiment in the production, consumption, and international trade of the Chinese economy in 2007 as the most recent year available with input-output table and updated inventory data. The results show that the estimated total direct GHG emissions by the Chinese economy in 2007 amount to 10,657.5 Mt CO₂-eq by the GTPs with 40.6% from CH₄ emissions in magnitude of the same importance as CO₂ emissions. The five sectors of Electric Power/Steam and Hot Water Production and Supply, Smelting and Pressing of Ferrous and Nonferrous Metals, Nonmetal Mineral Products, Agriculture, and Coal Mining and Dressing, are responsible for 83.3% of the total GHG emissions with different emission structures. The demands of coal and coal-electricity determine the structure of emission embodiment to an essential extent. The Construction sector holds the top GHG emissions embodied in both domestic production and domestic consumption. The GHG emission embodied in gross capital formation is more than those in other components of final demand characterized by extensive investment and limited household consumption. China is a net exporter of embodied GHG emissions, with a remarkable share of direct emission induced by international trade, such as textile products, industrial raw materials, and primary machinery and equipment products exports. The fractions of CH₄ in the component of embodied GHG emissions in the final demand are much greater than those fractions calculated by the Global Warming Potentials, which highlight the importance of CH₄ emissions for the case of China and indicate the essential effect of CH₄ emissions on global climate change. To understand the full context to achieve GHG emission mitigation, this study provides a new insight to address China’s GHG emissions status and hidden emission information induced by the final demand to the related policy-makers. Full article

(This article belongs to the Special Issue Low Carbon Transitions Worldwide)

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509 KiB

Open AccessArticle

An Inexact Mix-Integer Two-Stage Linear Programming Model for Supporting the Management of a Low-Carbon Energy System in China

by Ye Liu, Guohe Huang, Yanpeng Cai and Cong Dong

Energies 2011, 4(10), 1657-1686; https://doi.org/10.3390/en4101657 - 21 Oct 2011

Cited by 21 | Viewed by 7234

Abstract

In view of the great contribution of coal-fired units to CO₂ emissions, the coupled coal and power system with consideration of CO₂ mitigation is a typical sub-system of the highly emitting Chinese energy system for low-carbon studies. In this study, an [...] Read more.

In view of the great contribution of coal-fired units to CO₂ emissions, the coupled coal and power system with consideration of CO₂ mitigation is a typical sub-system of the highly emitting Chinese energy system for low-carbon studies. In this study, an inexact mix-integer two-stage programming (IMITSP) model for the management of low-carbon energy systems was developed based on the integration of multiple inexact programming techniques. Uncertainties and complexities related to the carbon mitigation issues in the coupled coal and power system can be effectively reflected and dealt with in this model. An optimal CO₂ mitigation strategy associated with stochastic power-generation demand under specific CO₂ mitigation targets could be obtained. Dynamic analysis of capacity expansion, facility improvement, coal selection, as well as coal blending within a multi-period and multi-option context could be facilitated. The developed IMITSP model was applied to a semi-hypothetical case of long-term coupled management of coal and power within a low-carbon energy system in north China. The generated decision alternatives could help decision makers identify desired strategies related to coal production and allocation, CO₂ emission mitigation, as well as facility capacity upgrade and expansion under various social-economic, ecological, environmental and system-reliability constraints. It could also provide interval solutions with a minimized system cost, a maximized system reliability and a maximized power-generation demand security. Moreover, the developed model could provide an in-depth insight into various CO₂ mitigation technologies and the associated environmental and economic implications under a given reduction target. Tradeoffs among system costs, energy security and CO₂ emission reduction could be analyzed. Full article

(This article belongs to the Special Issue Low Carbon Transitions Worldwide)

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337 KiB

Open AccessArticle

Emergy-Based Adjustment of the Agricultural Structure in a Low-Carbon Economy in Manas County of China

by Xiaobin Dong, Yufang Zhang, Weijia Cui, Bin Xun, Baohua Yu, Sergio Ulgiati and Xinshi Zhang

Energies 2011, 4(9), 1428-1442; https://doi.org/10.3390/en4091428 - 21 Sep 2011

Cited by 16 | Viewed by 7227

Abstract

The emergy concept, integrated with a multi-objective linear programming method, was used to model the agricultural structure of Xinjiang Uygur Autonomous Region under the consideration of the need to develop a low-carbon economy. The emergy indices before and after the structural optimization were [...] Read more.

The emergy concept, integrated with a multi-objective linear programming method, was used to model the agricultural structure of Xinjiang Uygur Autonomous Region under the consideration of the need to develop a low-carbon economy. The emergy indices before and after the structural optimization were evaluated. In the reconstructed model, the proportions of agriculture, forestry and artificial grassland should be adjusted from 19:2:1 to 5.2:1:2.5; the Emergy Yield Ratio (1.48) was higher than the average local (0.49) and national levels (0.27); and the Emergy Investment Ratio (11.1) was higher than the current structure (4.93) and that obtained from the 2003 data (0.055) in Xinjiang Uygur Autonomous Region, the Water Emergy Cost (0.055) should be reduced compared to that before the adjustment (0.088). The measurement of all the parameters validated the positive impact of the modeled agricultural structure. The self-sufficiency ratio of the system increased from the original level of 0.106 to 0.432, which indicated a better coupling effect among the subsystems within the whole system. The comparative advantage index between the two systems before and after optimization was approximately 2:1. When the mountain ecosystem service value was considered, excessive animal husbandry led to a 1.41 × 10¹⁰ RMB·a⁻¹ indirect economic loss, which was 4.15 times the GDP during the same time period. The functional improvement of the modeled structure supports the plan to “construct a central oasis and protect the surrounding mountains and deserts” to develop a sustainable agricultural system. Conserved natural grassland can make a large contribution to the carbon storage; and therefore, it is wise alternative that promote a low-carbon economic development strategy. Full article

(This article belongs to the Special Issue Low Carbon Transitions Worldwide)

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1599 KiB

Open AccessArticle

Improved Methods for Production Manufacturing Processes in Environmentally Benign Manufacturing

by Xian-Chun Tan, Yan-Yan Wang, Bai-He Gu, Ze-Kun Mu and Can Yang

Energies 2011, 4(9), 1391-1409; https://doi.org/10.3390/en4091391 - 14 Sep 2011

Cited by 14 | Viewed by 8356

Abstract

How to design a production process with low carbon emissions and low environmental impact as well as high manufacturing performance is a key factor in the success of low-carbon production. It is important to address concerns about climate change for the large carbon [...] Read more.

How to design a production process with low carbon emissions and low environmental impact as well as high manufacturing performance is a key factor in the success of low-carbon production. It is important to address concerns about climate change for the large carbon emission source manufacturing industries because of their high energy consumption and environmental impact during the manufacturing stage of the production life cycle. In this paper, methodology for determining a production process is developed. This methodology integrates process determination from three different levels: new production processing, selected production processing and batch production processing. This approach is taken within a manufacturing enterprise based on prior research. The methodology is aimed at providing decision support for implementing Environmentally Benign Manufacturing (EBM) and low-carbon production to improve the environmental performance of the manufacturing industry. At the first level, a decision-making model for new production processes based on the Genetic Simulated Annealing Algorithm (GSAA) is presented. The decision-making model considers not only the traditional factors, such as time, quality and cost, but also energy and resource consumption and environmental impact, which are different from the traditional methods. At the second level, a methodology is developed based on an IPO (Input-Process-Output) model that integrates assessments of resource consumption and environmental impact in terms of a materials balance principle for batch production processes. At the third level, based on the above two levels, a method for determining production processes that focus on low-carbon production is developed based on case-based reasoning, expert systems and feature technology for designing the process flow of a new component. Through the above three levels, a method for determining the production process to identify, quantify, assess, and optimize the production process with the goal of reducing and ultimately minimizing the environmental impact while maximizing the resource efficiency is effectively presented. The feasibility of the method is verified by a case study of a whole production process design at the above three levels. Full article

(This article belongs to the Special Issue Low Carbon Transitions Worldwide)

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394 KiB

Open AccessArticle

Temporal and Spatial Analysis of Integrated Energy and Environment Efficiency in China Based on a Green GDP Index

by Weibin Lin, Jin Yang and Bin Chen

Energies 2011, 4(9), 1376-1390; https://doi.org/10.3390/en4091376 - 9 Sep 2011

Cited by 28 | Viewed by 8483

Abstract

China is experiencing a high speed economic development which may exert great pressure on the environment and energy systems. To measure the environmental and energy performance during the economic development process, this paper selected 30 provinces, cities or autonomous regions as the decision [...] Read more.

China is experiencing a high speed economic development which may exert great pressure on the environment and energy systems. To measure the environmental and energy performance during the economic development process, this paper selected 30 provinces, cities or autonomous regions as the decision making unit (DMU), and proposed a Green GDP index (GGI) in view of energy intensity and pollution intensity using the generalized Data Envelopment Analysis (DEA) method, and the developing trends of integrated energy and environment efficiency of DMUs from 2006 to 2010 are also demonstrated by the Malmquist index. Results show that the integrated energy and environment efficiency varies for each DMU. GGI were both 1 in Beijing and Shanghai. GGI values for the developed cities in Eastern China, such as Guangdong, Fujian, Zhejiang, Tianjin, Jiangsu, and Hainan, ranked high, while those in the Northeast and Middle China remained relatively low. Moreover, there is a positive relationship between the GGI and per capita GDP with a correlation coefficient of 0.75. Increases in GGI are also observed in the results, representing great achievements are acquired in energy conservation and emission reduction. However, the GGIs do not converge to the green frontier across the provinces. Full article

(This article belongs to the Special Issue Low Carbon Transitions Worldwide)

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Review

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289 KiB

Open AccessReview

A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty

by Yong Zeng, Yanpeng Cai, Guohe Huang and Jing Dai

Energies 2011, 4(10), 1624-1656; https://doi.org/10.3390/en4101624 - 21 Oct 2011

Cited by 97 | Viewed by 12380

Abstract

Energy is crucial in supporting people’s daily lives and the continual quest for human development. Due to the associated complexities and uncertainties, decision makers and planners are facing increased pressure to respond more effectively to a number of energy-related issues and conflicts, as [...] Read more.

Energy is crucial in supporting people’s daily lives and the continual quest for human development. Due to the associated complexities and uncertainties, decision makers and planners are facing increased pressure to respond more effectively to a number of energy-related issues and conflicts, as well as GHG emission mitigation within the multiple scales of energy management systems (EMSs). This quandary requires a focused effort to resolve a wide range of issues related to EMSs, as well as the associated economic and environmental implications. Effective systems analysis approaches under uncertainty to successfully address interactions, complexities, uncertainties, and changing conditions associated with EMSs is desired, which require a systematic investigation of the current studies on energy systems. Systems analysis and optimization modeling for low-carbon energy systems planning with the consideration of GHG emission reduction under uncertainty is thus comprehensively reviewed in this paper. A number of related methodologies and applications related to: (a) optimization modeling of GHG emission mitigation; (b) optimization modeling of energy systems planning under uncertainty; and (c) model-based decision support tools are examined. Perspectives of effective management schemes are investigated, demonstrating many demanding areas for enhanced research efforts, which include issues of data availability and reliability, concerns in uncertainty, necessity of post-modeling analysis, and usefulness of development of simulation techniques. Full article

(This article belongs to the Special Issue Low Carbon Transitions Worldwide)

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