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Special Issue "Selected Papers from 6th Annual Conference of Energy Economics and Management"

A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: closed (30 January 2016)

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Guest Editor
Prof. Dr. Bing Wang

Director of Personnel Services; Head of Department of Economics; School of Economics, Jinan University, No. 601, West of Huangpu Avenue, Tianhe District, Guangzhou 510632, China
Website | E-Mail
Phone: +86-20-8522-0173
Fax: +86-20-8522-0173
Interests: sustainable development; development economics
Guest Editor
Prof. Dr. Ning Zhang

1 School of Economics, Jinan University, No. 601, West of Huangpu Avenue, Tianhe District, Guangzhou 510632, China
2 Institute of Poyang Lake Eco-economics, Jiangxi University of Finance and Economics, Nanchang 330013, China
3 Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
Website | E-Mail
Phone: +86-791-8381-0553
Fax: +86-791-8381-0892
Interests: environmental economics; energy economics

Special Issue Information

Dear Colleagues,

This Special Issue will consist of selected papers from the “6th annual conference of Energy Economics and Management”, a large conference held in Guangzhou, China, 11–13 November 2015. The topic of this conference will be “Toward a sustainable low carbon China: New global carbon reduction agreement and Energy Policy”. This conference is co-hosted by the National Natural Science Foundation of China (NSFC), the Project Management Research Committee China, and Jinan University (Guangzhou).

This conference is one of the leading conferences in China for presenting novel and fundamental advances in energy economics and management for policy decision making. The purpose of this conference is for scientists, scholars, engineers, and graduate students from universities/research institutes to present ongoing research activities in order to exchange research ideas in the area of energy economics and management. This conference provides opportunities for delegates to exchange new working papers and application experiences, face-to-face, in order to establish research or collaboration relations. The scope of this Special Issue encompasses topics related to energy economics and management, at both the macro- and micro-levels.

Prof. Dr. Bing Wang
Prof. Dr. Ning Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Low carbon and sustainable development
  • Climate change economics and policy
  • Carbon emissions trading market and carbon finance
  • Resources and sustainability management
  • Energy economics and finance
  • Energy security and energy poverty
  • Renewable and sustainable energy
  • Energy and environmental modeling

Published Papers (18 papers)

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Editorial

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Open AccessEditorial Toward a Sustainable Low-Carbon China: A Review of the Special Issue of “Energy Economics and Management”
Sustainability 2016, 8(8), 823; doi:10.3390/su8080823
Received: 14 August 2016 / Accepted: 17 August 2016 / Published: 22 August 2016
Cited by 4 | PDF Full-text (176 KB) | HTML Full-text | XML Full-text
Abstract
Severe environmental quality deterioration, along with predatory exploitation of energy resources, are generally associated with economic growth, especially in China. Against this background, the 6th Annual Conference of Energy Economics and Management provides a platform for examining outperforming governance factors and mechanisms of
[...] Read more.
Severe environmental quality deterioration, along with predatory exploitation of energy resources, are generally associated with economic growth, especially in China. Against this background, the 6th Annual Conference of Energy Economics and Management provides a platform for examining outperforming governance factors and mechanisms of energy economics and policy. Thanks to Sustainability for providing this special issue. This editorial highlights the contents and methodologies of the special issue for this conference, presenting diverse issues in energy economics and management. We also suggest guidelines for future study in energy economics and management. Full article

Research

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Open AccessArticle Economic Impacts of Power Shortage
Sustainability 2016, 8(7), 687; doi:10.3390/su8070687
Received: 13 March 2016 / Revised: 11 July 2016 / Accepted: 13 July 2016 / Published: 21 July 2016
Cited by 1 | PDF Full-text (1029 KB) | HTML Full-text | XML Full-text
Abstract
The electricity industry is a basic industry of the national economy. It has experienced several large-scale power shortages, hard power shortage and soft power shortage, which have brought a great threat to China’s sustainable economic development. To solve this problem better, it is
[...] Read more.
The electricity industry is a basic industry of the national economy. It has experienced several large-scale power shortages, hard power shortage and soft power shortage, which have brought a great threat to China’s sustainable economic development. To solve this problem better, it is necessary to make a quantitative assessment of the economic impacts of power shortage. The CGE model is commonly used for simulating economic shocks and policy effects. It describes supply, demand and equilibrium in different markets by simulating the economic mechanism through a set of equations. Once changed, the exogenous variables will affect a certain part of the system and then the whole system, leading to changes in quantities and prices. The equilibrium state will also change from one to another. A static CGE model is built in this paper, and the Social Accounting Matrix (SAM) of eight sectors of China in 2007 is compiled, in order to simulate the economic impacts of hard power shortage and soft power shortage. Simulation results show that the negative effects of power shortage on economic development are very significant, and the effects vary in different sectors. Especially, under the background of hard power shortage, the industrial sector suffers most. The economic cost of power shortage is considerable, and the main reason for it is the specific administrative pricing system in China. The low electricity price in the long term will lead to insufficient construction and hard power shortage; moreover, that in the short run would result in soft power shortage. In order to solve the problem of power shortage completely, power system reform is inevitable. Full article
Open AccessArticle How Much CO2 Emissions Can Be Reduced in China’s Heating Industry
Sustainability 2016, 8(7), 642; doi:10.3390/su8070642
Received: 9 March 2016 / Revised: 14 June 2016 / Accepted: 4 July 2016 / Published: 8 July 2016
Cited by 2 | PDF Full-text (2987 KB) | HTML Full-text | XML Full-text
Abstract
China’s heating industry is a coal-fired industry with serious environmental issues. CO2 emissions from the heating industry accounted for an average 6.1% of China’s carbon emissions during 1985–2010. The potential for reducing emissions in China’s heating industry is evaluated by co-integration analysis
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China’s heating industry is a coal-fired industry with serious environmental issues. CO2 emissions from the heating industry accounted for an average 6.1% of China’s carbon emissions during 1985–2010. The potential for reducing emissions in China’s heating industry is evaluated by co-integration analysis and scenario analysis. The results demonstrate that there is a long-run equilibrium relationship among CO2 emissions and the influencing factors, including energy intensity, industrial scale, labor productivity, and energy productivity. Monte Carlo technique is adopted for risk analysis. It is found that the CO2 emissions reduction potential of the heating industry will be 26.7 million tons of coal equivalent (Mtce) in 2020 and 64.8 Mtce in 2025 under the moderate scenario, compared with 50.6 Mtce in 2020 and 122.1 Mtce in 2025 under the advanced scenario. Policy suggestions are provided accordingly. Full article
Open AccessArticle Are Consumers Willing to Pay More for Sustainable Products? A Study of Eco-Labeled Tuna Steak
Sustainability 2016, 8(5), 494; doi:10.3390/su8050494
Received: 29 January 2016 / Revised: 14 May 2016 / Accepted: 16 May 2016 / Published: 23 May 2016
Cited by 4 | PDF Full-text (1400 KB) | HTML Full-text | XML Full-text
Abstract
A high demand for seafood leads to overfishing, harms the long-term health of seafood stocks, and threatens environmental sustainability in oceans. Sustainability certification is one of the major sustainability movements and is known as eco-labeling. For instance, in the tuna industry, leading tuna
[...] Read more.
A high demand for seafood leads to overfishing, harms the long-term health of seafood stocks, and threatens environmental sustainability in oceans. Sustainability certification is one of the major sustainability movements and is known as eco-labeling. For instance, in the tuna industry, leading tuna brands have committed to protecting sea turtles by allowing the tracing of the source of their tuna “from catch to can.” This paper relies on an Internet survey on consumers from Kentucky conducted in July 2010. The survey investigates household-level tuna steak (sashimi grade) consumption and examines consumer preferences for eco-labeling (“Certified Turtle Safe” (CTS) in this study) while mimicking individuals’ seafood procurement processes. A random parameter logit model is utilized, and willingness-to-pay measures are calculated based on model estimation results. It was found that respondents on average preferred turtle-safe-labeled tuna steak and were likely to pay more for it; however, they were less likely to purchase wild-caught species, and insignificant results were found for pre-frozen. Moreover, significant heterogeneities were found across individuals regarding tuna steak purchases. The findings indicate evidence of public support for environmental friendliness, particularly with regard to eco-labeling. Full article
Open AccessArticle Research on Factors Affecting the Optimal Exploitation of Natural Gas Resources in China
Sustainability 2016, 8(5), 435; doi:10.3390/su8050435
Received: 16 January 2016 / Revised: 22 April 2016 / Accepted: 26 April 2016 / Published: 2 May 2016
Cited by 1 | PDF Full-text (3747 KB) | HTML Full-text | XML Full-text
Abstract
This paper develops an optimizing model for the long-term exploitation of limited natural gas reserves in China. In addition to describing the life cycle characteristics of natural gas production and introducing the inter-temporal allocation theory, this paper builds the optimal exploitation model of
[...] Read more.
This paper develops an optimizing model for the long-term exploitation of limited natural gas reserves in China. In addition to describing the life cycle characteristics of natural gas production and introducing the inter-temporal allocation theory, this paper builds the optimal exploitation model of natural gas resources within a gas field in the Ordos Basin as an example to analyze its exploitation scale and how influence factors, such as recovery rate, discount rate and the gas well exhausting cycle, affect the optimal exploration path of this gas field. We determine that an increase in the discount rate stimulates investors to invest more aggressively in natural gas exploitation in the early period due to the lower discounted value, thereby increasing the pace of the exploitation of natural gas and the exhaustion of gas fields. A higher recoverable factor implies more recoverable reserves and greater potential of increasing the output of gas fields. The exhaustion rate of gas wells affects the capability of converting capacity to output. When exhaustion occurs quickly in gas wells, the output will likely increase in the output rising period, and the output will likely decrease at a faster rate in the output reduction period. Price reform affects the economic recoverable reserves of gas fields. Full article
Open AccessArticle Analysis of the Relationship between China’s IPPU CO2 Emissions and the Industrial Economic Growth
Sustainability 2016, 8(5), 426; doi:10.3390/su8050426
Received: 28 January 2016 / Revised: 18 April 2016 / Accepted: 26 April 2016 / Published: 29 April 2016
Cited by 3 | PDF Full-text (1572 KB) | HTML Full-text | XML Full-text
Abstract
According to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC 2006) and based on the production technology and products, this paper has calculated CO2 emissions from industrial processes and product use (IPPU), which involves the individual and the summation of
[...] Read more.
According to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC 2006) and based on the production technology and products, this paper has calculated CO2 emissions from industrial processes and product use (IPPU), which involves the individual and the summation of five major IPUU CO2 emissions industrial departments. As there is a classic environmental Kuznets curve between IPPU CO2 emissions and the economy, this paper discusses the relationship based on the calculation results and the actual situation. The results show that the overall emission level is indeed rising yearly, and that steel and iron alloy manufacturing and nonmetal manufacturing occupy about 80% of the total emissions. The IPPU CO2 emissions and the corresponding gross industrial output value do not present a classic Kuznets curve in most industrial sectors due to the increasing industrial employed population. The year 2002 appears to be the boundary instead, where prior to 2002, there is a relatively stable function-type growth curve and after 2002, gross industrial output value (GIOV) per employed person remained within a certain interval while IPPU CO2 emissions per employed dipped slightly then increased again. Some, but not all, industrial departments and the combined emissions of per employed person reached maximum values in 2012. Full article
Open AccessArticle Assessment and Decomposition of Total Factor Energy Efficiency: An Evidence Based on Energy Shadow Price in China
Sustainability 2016, 8(5), 408; doi:10.3390/su8050408
Received: 25 January 2016 / Revised: 17 April 2016 / Accepted: 19 April 2016 / Published: 26 April 2016
Cited by 2 | PDF Full-text (1681 KB) | HTML Full-text | XML Full-text
Abstract
By adopting an energy-input based directional distance function, we calculated the shadow price of four types of energy (i.e., coal, oil, gas and electricity) among 30 areas in China from 1998 to 2012. Moreover, a macro-energy efficiency index in China was
[...] Read more.
By adopting an energy-input based directional distance function, we calculated the shadow price of four types of energy (i.e., coal, oil, gas and electricity) among 30 areas in China from 1998 to 2012. Moreover, a macro-energy efficiency index in China was estimated and divided into intra-provincial technical efficiency, allocation efficiency of energy input structure and inter-provincial energy allocation efficiency. It shows that total energy efficiency has decreased in recent years, where intra-provincial energy technical efficiency drops markedly and extensive mode of energy consumption rises. However, energy structure and allocation improves slowly. Meanwhile, lacking an integrated energy market leads to the loss of energy efficiency. Further improvement of market allocation and structure adjustment play a pivotal role in the increase of energy efficiency. Full article
Open AccessArticle Multivariate EMD-Based Modeling and Forecasting of Crude Oil Price
Sustainability 2016, 8(4), 387; doi:10.3390/su8040387
Received: 23 February 2016 / Accepted: 8 April 2016 / Published: 21 April 2016
Cited by 3 | PDF Full-text (226 KB) | HTML Full-text | XML Full-text
Abstract
Recent empirical studies reveal evidence of the co-existence of heterogeneous data characteristics distinguishable by time scale in the movement crude oil prices. In this paper we propose a new multivariate Empirical Mode Decomposition (EMD)-based model to take advantage of these heterogeneous characteristics of
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Recent empirical studies reveal evidence of the co-existence of heterogeneous data characteristics distinguishable by time scale in the movement crude oil prices. In this paper we propose a new multivariate Empirical Mode Decomposition (EMD)-based model to take advantage of these heterogeneous characteristics of the price movement and model them in the crude oil markets. Empirical studies in benchmark crude oil markets confirm that more diverse heterogeneous data characteristics can be revealed and modeled in the projected time delayed domain. The proposed model demonstrates the superior performance compared to the benchmark models. Full article
Open AccessArticle Estimating the Contribution of Industry Structure Adjustment to the Carbon Intensity Target: A Case of Guangdong
Sustainability 2016, 8(4), 355; doi:10.3390/su8040355
Received: 26 January 2016 / Revised: 17 March 2016 / Accepted: 6 April 2016 / Published: 12 April 2016
Cited by 2 | PDF Full-text (629 KB) | HTML Full-text | XML Full-text
Abstract
Industry structure adjustment is an effective measure to achieve the carbon intensity target of Guangdong Province. Accurately evaluating the contribution of industry structure adjustment to the carbon intensity target is helpful for the government to implement more flexible and effective policies and measures
[...] Read more.
Industry structure adjustment is an effective measure to achieve the carbon intensity target of Guangdong Province. Accurately evaluating the contribution of industry structure adjustment to the carbon intensity target is helpful for the government to implement more flexible and effective policies and measures for CO2 emissions reduction. In this paper, we attempt to evaluate the contribution of industry structure adjustment to the carbon intensity target. Firstly, we predict the gross domestic product (GDP) with scenario forecasting, industry structure with the Markov chain model, CO2 emissions with a novel correlation mode based on least squares support vector machine, and then we assess the contribution of industry structure adjustment to the carbon intensity target of Guangdong during the period of 2011–2015 under nine scenarios. The obtained results show, in the ideal scenario, that the economy will grow at a high speed and the industry structure will be significantly adjusted, and thus the carbon intensity in 2015 will decrease by 25.53% compared to that in 2010, which will make a 130.94% contribution to the carbon intensity target. Meanwhile, in the conservative scenario, the economy will grow at a low speed and the industry structure will be slightly adjusted, and thus the carbon intensity in 2015 will decrease by 23.89% compared to that in 2010, which will make a 122.50% contribution to the carbon intensity target. Full article
Open AccessArticle Measuring the Total-Factor Carbon Emission Performance of Industrial Land Use in China Based on the Global Directional Distance Function and Non-Radial Luenberger Productivity Index
Sustainability 2016, 8(4), 336; doi:10.3390/su8040336
Received: 7 January 2016 / Revised: 20 March 2016 / Accepted: 20 March 2016 / Published: 6 April 2016
Cited by 10 | PDF Full-text (640 KB) | HTML Full-text | XML Full-text
Abstract
Industry is a major contributor to carbon emissions in China, and industrial land is an important input to industrial production. Therefore, a detailed analysis of the carbon emission performance of industrial land use is necessary for making reasonable carbon reduction policies that promote
[...] Read more.
Industry is a major contributor to carbon emissions in China, and industrial land is an important input to industrial production. Therefore, a detailed analysis of the carbon emission performance of industrial land use is necessary for making reasonable carbon reduction policies that promote the sustainable use of industrial land. This paper aims to analyze the dynamic changes in the total-factor carbon emission performance of industrial land use (TCPIL) in China by applying a global directional distance function (DDF) and non-radial Luenberger productivity index. The empirical results show that the eastern region enjoys better TCPIL than the central and western regions, but the regional gaps in TCPIL are narrowing. The growth in NLCPILs (non-radial Luenberger carbon emission performance of industrial land use) in the eastern and central regions is mainly driven by technological progress, whereas efficiency improvements contribute more to the growth of NLCPIL in the western region. The provinces in the eastern region have the most innovative and environmentally-friendly production technologies. The results of the analysis of the influencing factors show implications for improving the NLCPIL, including more investment in industrial research and development (R&D), the implementation of carbon emission reduction policies, reduction in the use of fossil energy, especially coal, in the process of industrial production, actively learning about foreign advanced technology, properly solving the problem of surplus labor in industry and the expansion of industrial development. Full article
Open AccessArticle Analysis of the Threshold Effect of Financial Development on China’s Carbon Intensity
Sustainability 2016, 8(3), 271; doi:10.3390/su8030271
Received: 31 December 2015 / Revised: 6 March 2016 / Accepted: 10 March 2016 / Published: 15 March 2016
Cited by 3 | PDF Full-text (410 KB) | HTML Full-text | XML Full-text
Abstract
Using panel data on 30 provinces in China from 2005 to 2012, this paper conducts an empirical test on the threshold effect of the relationship between financial development and carbon emission intensity from the perspectives of financial scale and financial efficiency. The results
[...] Read more.
Using panel data on 30 provinces in China from 2005 to 2012, this paper conducts an empirical test on the threshold effect of the relationship between financial development and carbon emission intensity from the perspectives of financial scale and financial efficiency. The results show that at a low level of per capita GDP, the expansion of the financial scale and the enhancement of financial efficiency will increase carbon intensity. When the per capita GDP is greater than the threshold value (RMB 37,410), the expansion of the financial scale will also increase carbon intensity, but the potency of this effect will be weaker. At the same time, the improvement of financial efficiency will help reduce carbon intensity. Most provinces with per capita GDP greater than the threshold value (RMB 37,410) are located in the eastern coastal areas of China, whereas most provinces with per capita GDP less than the threshold value are located in the central and western areas of China. Both raising the level of openness and improving the industrial structure will have significantly positive effects on carbon intensity. Full article
Open AccessArticle Analysis on Impact Factors of Water Utilization Structure in Tianjin, China
Sustainability 2016, 8(3), 241; doi:10.3390/su8030241
Received: 1 January 2016 / Revised: 27 February 2016 / Accepted: 1 March 2016 / Published: 7 March 2016
Cited by 3 | PDF Full-text (1258 KB) | HTML Full-text | XML Full-text
Abstract
Water is an essential foundation for socio-economic development and environmental protection. As such, it is very critical for a city’s sustainable development. This study analyzed the changes in water utilization structure and its impact factors using water consumption data for agricultural, industrial, domestic
[...] Read more.
Water is an essential foundation for socio-economic development and environmental protection. As such, it is very critical for a city’s sustainable development. This study analyzed the changes in water utilization structure and its impact factors using water consumption data for agricultural, industrial, domestic and ecological areas in the city of Tianjin, China from 2004 to 2013. On this base, the evolution law and impact factors of water utilization structure were depicted by information entropy and grey correlation respectively. These analyses lead to three main results. First, the total amount of water consumption in Tianjin increased slightly from 2004 to 2013. Second, the information entropy and equilibrium degree peaked in 2010. From 2004 to 2010, the water utilization structure tended to be more disordered and balanced. Third, the economic and social factors seemed to influence the water utilization structure, while the main impact factors were industrial structure, per capita green area, cultivated area, effective irrigation area, rural electricity consumption, animal husbandry output, resident population, per capita domestic water etc. Full article
Open AccessArticle Green Development Performance in China: A Metafrontier Non-Radial Approach
Sustainability 2016, 8(3), 219; doi:10.3390/su8030219
Received: 4 December 2015 / Revised: 23 February 2016 / Accepted: 24 February 2016 / Published: 1 March 2016
Cited by 6 | PDF Full-text (1893 KB) | HTML Full-text | XML Full-text
Abstract
This paper proposes a green development growth index (GDGI) for measuring the changes in sustainable development over time. This index considers a wide range of pollutants, and allows for the incorporation of group heterogeneity and non-radial slack in the conventional green development index.
[...] Read more.
This paper proposes a green development growth index (GDGI) for measuring the changes in sustainable development over time. This index considers a wide range of pollutants, and allows for the incorporation of group heterogeneity and non-radial slack in the conventional green development index. The GDGI is calculated based on a non-radial directional distance function derived by several data envelopment analysis (DEA) models, and was decomposed into an efficiency change (EC) index, a best-practice gap change (BPC) index and a technology gap change (TGC) index. The proposed indices are employed to measure green development performance in 30 provinces in China from 2000 to 2012. The empirical results show that China has a low level of green development, with a 2.58% increase per year driven by an innovation effect. China’s green development is mainly led by the eastern region, and the technology gaps between the eastern region and the other two regions (the central and western regions) have become wider over the years. The group innovative provinces have set a target for resource utilization of non-innovative provinces in order to catch-up with the corresponding groups, while the metafrontier innovative provinces provide targets for the technology levels of other provinces to improve their green development performance. Full article
Open AccessArticle Industrial Carbon Emissions of China’s Regions: A Spatial Econometric Analysis
Sustainability 2016, 8(3), 210; doi:10.3390/su8030210
Received: 22 December 2015 / Revised: 31 January 2016 / Accepted: 18 February 2016 / Published: 29 February 2016
Cited by 10 | PDF Full-text (234 KB) | HTML Full-text | XML Full-text
Abstract
This paper proposes an extended Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model to investigate the factors driving industrial carbon emissions in China. In the first stage, a spatial Durbin model is applied to investigate the determinants of regional industrial
[...] Read more.
This paper proposes an extended Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model to investigate the factors driving industrial carbon emissions in China. In the first stage, a spatial Durbin model is applied to investigate the determinants of regional industrial carbon emissions. In the second stage, a geographically and temporally weighted regression is applied to investigate temporal and spatial variations in the impacts of these driving factors on the scale and intensity of regional industrial carbon emissions. The empirical results suggest that the provinces with low carbon emissions act as exemplars for those with high carbon emissions and that driving factors impact carbon emission both directly and indirectly. All of the factors were investigated, except energy intensity, energy price, and openness, significantly impact carbon emissions. Overall, the results suggest that spatial correlation, heterogeneity, and spillover effects should be taken into account when formulating policies aiming at reducing industrial carbon emissions. The paper concludes with relevant policy recommendations taking full account of the regional industrial carbon emissions, heterogeneity and spillover. Full article
Open AccessArticle Regional Competition, Heterogeneous Factors and Pollution Intensity in China: A Spatial Econometric Analysis
Sustainability 2016, 8(2), 171; doi:10.3390/su8020171
Received: 10 January 2016 / Revised: 29 January 2016 / Accepted: 1 February 2016 / Published: 16 February 2016
Cited by 3 | PDF Full-text (876 KB) | HTML Full-text | XML Full-text
Abstract
Regional competition may play an important role in the balance of environmental protection and economic growth. However, it is a pending issue of whether the competition among Chinese local governments leads to a race to black development or green development. This paper aims
[...] Read more.
Regional competition may play an important role in the balance of environmental protection and economic growth. However, it is a pending issue of whether the competition among Chinese local governments leads to a race to black development or green development. This paper aims to explore the strategic interactions in provincial development in terms of an environment-economic indicator, i.e., the pollution intensity in China from 2000 to 2013. We divide four predominant industrial pollutants into two groups according to whether the pollutant is regulated, and then test the strategic interactions among regions based on the spatial lag term by employing the spatial Durbin model. The results show that the heterogeneous factors, such as various pollutants and regional difference, may give rise to diversified competition strategies. We find that the “race to black development” hypothesis is not supported at the national level, and the “race to green development” hypothesis is established in the developed eastern regions only in terms of the regulated industrial pollutants. We also detect how pollution intensity is influenced by the direct and spatial spillover effects of environmental regulation and find that environmental legislation has been effective in reducing regulated pollutants’ pollution intensity, while the effects of environmental staff and investment are weak. Finally, some policy suggestions are discussed. Full article
Open AccessArticle Optimal Path for Controlling Sectoral CO2 Emissions Among China’s Regions: A Centralized DEA Approach
Sustainability 2016, 8(1), 28; doi:10.3390/su8010028
Received: 31 October 2015 / Revised: 6 December 2015 / Accepted: 22 December 2015 / Published: 29 December 2015
Cited by 6 | PDF Full-text (1627 KB) | HTML Full-text | XML Full-text
Abstract
This paper proposes a centralized data envelopment analysis (DEA) model for industrial optimization based on several different production technologies among several regions. We developed this model based on improved Kuosmanen environmental DEA technology, which avoids positive shadow price on undesirable outputs. We also
[...] Read more.
This paper proposes a centralized data envelopment analysis (DEA) model for industrial optimization based on several different production technologies among several regions. We developed this model based on improved Kuosmanen environmental DEA technology, which avoids positive shadow price on undesirable outputs. We also designed a dual model for our centralized DEA model, and used it to analyze shadow prices on CO2 emissions. We further employed the proposed model to determine the optimal path for controlling CO2 emissions at the sector level for each province in China. At sectoral level, manufacturing showed the highest potential emissions reduction, and transportation was the largest accepter of emission quotas. At regional level, western and northeastern areas faced the largest adjustments in allowable emissions, while central and eastern areas required the least amount of adjustment. Because our model represents increase or decrease in emissions bidirectionally in terms of shadow price analysis, this setting makes the shadow price on CO2 emissions lower than strong regulation (decreasing CO2 emissions along with increasing value added) used by directional distance function (DDF). Full article
Open AccessArticle Did the Establishment of Poyang Lake Eco-Economic Zone Increase Agricultural Labor Productivity in Jiangxi Province, China?
Sustainability 2016, 8(1), 8; doi:10.3390/su8010008
Received: 10 December 2015 / Revised: 18 December 2015 / Accepted: 21 December 2015 / Published: 24 December 2015
Cited by 2 | PDF Full-text (399 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we take the establishment of Poyang Lake Eco-Economic Zone in 2009 as a quasi-natural experiment, to evaluate its influence on the agricultural labor productivity in Jiangxi Province, China. The estimation results of the DID method show that the establishment of
[...] Read more.
In this paper, we take the establishment of Poyang Lake Eco-Economic Zone in 2009 as a quasi-natural experiment, to evaluate its influence on the agricultural labor productivity in Jiangxi Province, China. The estimation results of the DID method show that the establishment of the zone reduced agricultural labor productivity by 3.1%, lowering farmers’ net income by 2.5% and reducing the agricultural GDP by 3.6%. Furthermore, this negative effect has increased year after year since 2009. However, the heterogeneity analysis implies that the agricultural labor productivities of all cities in Jiangxi Province will ultimately converge. We find that the lack of agricultural R&D activities and the abuse of chemical fertilizers may be the main reasons behind the negative influence of the policy, by examining two possible transmission channels—the R&D investment and technological substitution. Corresponding policy implications are also provided. Full article

Other

Jump to: Editorial, Research

Open AccessCase Report Commercially Available Materials Selection in Sustainable Design: An Integrated Multi-Attribute Decision Making Approach
Sustainability 2016, 8(1), 79; doi:10.3390/su8010079
Received: 18 October 2015 / Revised: 11 January 2016 / Accepted: 11 January 2016 / Published: 16 January 2016
Cited by 6 | PDF Full-text (486 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents an integrated multi-attribute decision-making (MADM) approach to aid selection of commercially available materials in the context of sustainable design. The MADM couples grey relational analysis (GRA) with an analytic hierarchy process (AHP) to rank alternative materials in terms of their
[...] Read more.
This paper presents an integrated multi-attribute decision-making (MADM) approach to aid selection of commercially available materials in the context of sustainable design. The MADM couples grey relational analysis (GRA) with an analytic hierarchy process (AHP) to rank alternative materials in terms of their economic, environmental, and social performance. AHP is used to determine the corresponding weighting values for the selected indicators. In addition, a case example is used to verify the proposed MADM method and demonstrate its practical application. Three alternative polymer materials, i.e., poly(vinyl chloride) (PVC), polypropylene (PP), and polyethylene (PE), are examined to determine their sustainability for plastic pipe design. The associated MADM result and the limitations of the approach are discussed to lay the foundation for further improvement. Full article
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