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Recent trend of industrial emissions in developing countries
Applied Energy 166 (2016) 187–190
Contents lists available at ScienceDirect
Applied Energy journal homepage: www.elsevier.com/locate/apenergy
Editorial
Recent trend of industrial emissions in developing countries a r t i c l e
i n f o
Keywords: GHG emissions, industrial emissions Developing countries Emission accounting Policy implications
a b s t r a c t Greenhouse gas (GHG) emissions from industrial sectors are increasing, particularly in the developing world where pursuing industrialization has been highly addressed. This calls for further studies to learn and share experiences for developing countries. In order to fill in such a research gap, this special issue focuses on examining the recent trend of industrial emissions in developing countries. Among the manuscripts submitted to the Special Issue, twelve papers have been accepted after review, covering assessment indicators, tools and methods, and policies. Key industrial sectors, including cement, lime, aluminum, coal, mining, glass, soda ash, etc, have been investigated. Valuable policy insights have been raised, including wide scale upgrading, replacement and deployment of best available technologies, integrated information platforms, cross-cutting technologies and measures, a shift to low carbon electricity, radical product innovations, carbon dioxide capture and storage (CCS), demand on new and replacement products, systematic approaches and collaboration among different industries. These useful suggestions could be shared or learned by industrial policy makers or managers in the developing world so that the overall GHG emissions from their industrial sectors can be mitigated by considering the local realities. Ó 2016 Published by Elsevier Ltd.
1. Introduction Greenhouse gas (GHG) emissions from industry are rapidly increasing and higher than those from other end-use sectors. According to IPCC AR5 [1], total emissions from the industrial sector reached 14.86 GtCO2e in 2010, representing 30% of total global GHG emissions. Particularly, from a global perspective, with both urbanization and industrialization, GHG emissions from industrial sectors in developing countries experienced a rapid growth, while such emissions in developed countries are declining. Under such a circumstance, it is necessary to pursue an absolute reduction in emissions from the industrial sector. In order to achieve such a target, a broad set of mitigation options should be considered, including energy efficiency, material use efficiency, recycling and reuse of materials and products, industrial symbiosis, product service efficiency, demand reductions. These measures have been widely applied in developed countries. However, there are few studies from developing world. As a response to such an issue, we organize this special issue in Applied Energy, a leading journal in the field. The objective of the special issue (SI) is to address both global and local issues (such as energy security, carbon emissions, air pollution and public health) from industrial sectors while contributing to development needs. It focuses on integrating climate change concerns with industrial development objectives by encouraging industrial decision-makers to encompass low-emission and/or climate-resilient economic growth in their industrial development strategies. The editorial presents an overview of the twelve selected articles of this SI, which not only detail the innovative indicators, methods, cases and tools for promoting low carbon http://dx.doi.org/10.1016/j.apenergy.2016.02.060 0306-2619/Ó 2016 Published by Elsevier Ltd.
industrial development in the developing world, but also provide valuable policy insights to policy-makers and industrial managers from developing countries. We expect that new ideas and perspectives on how positive changes can be attained as well as an understanding on how different regions can generate solutions that have large, short and long-term positive benefits and how innovative industrial emission mitigation measures can be effectively embedded into local policy settings to contribute to low carbon industrial development at the local and regional levels. Most of the papers in the SI are focused on China. This is rational since China is the largest industrial emission country in the world and its industrial production scale is more profound. Nevertheless, we presume that valuable lessons can be learned or shared from these studies in China so as to promote win-win situations in resource efficiency, climate change prevention and adaptation from industrial sector in the developing world. 2. Evaluations Appropriate evaluation methods are valuable for managing sectorial emissions and for providing guidelines on low carbon development of industrial sectors. Various performance assessment methods and indicators for different industrial sectors have been developed, based on well-known assessment methods, such as: energy consumption, IPCC methods, on-site emissions, carbon footprints, and input-output analysis. Each method has its advantages and disadvantages and can address some specific parameters of low carbon industrial development. The selection of different methods is based upon the needs and available data. For instance,
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Editorial / Applied Energy 166 (2016) 187–190
Cai et al. [2] targeted to evaluate the overall CO2 emissions from China’s cement industry based on the detailed information of China’s total 1574 cement enterprises in 2013. It reflects the aspect that cement industry triggered by intensive construction activities in the country has become one of the key industrial emission sectors in China. Due to different factors process and energy emission intensities vary significantly between different enterprises. The average CO2 emissions performance of China’s cement enterprises (806 kg CO2/ton clinker) is approx. 4% lower than the global average level in 2013. This commendable result is very much based on the performance of the best production facilities as the CO2 emissions intensity of the best 20th clinker production, is even lower than the IEA’s 2020 target. That’s why the authors propose that those enterprises could be the entry threshold for future new enterprises and top runner benchmark for the existing enterprises. Also, CO2 emissions related to cement production differ from regions to regions. In China the Yangtze River Delta region is the most important hotspot of the cement CO2 emissions. Wuhu & Tongling are the hottest emission centres, with an average of 8,288 ton of CO2 emissions per square kilometers. As emissions factors differ widely, amongst others ownership of cement enterprises should be carefully considered in designing appropriate policy instruments. Favorable policies could focus on medium sized facilities, and initially focus on specific areas (e.g. along the Silk Road Economic Belt) and technologies. Zhou et al. [3] proposed a Malmquist energy conservation and emission reduction performance index (MECERPI) for assessing the performance changes in energy use and pollutant emissions over time. Their index is built upon the non-radial directional distance function and can be derived by solving data envelopment analysis. 15 MECERPIs were applied in order to empirically investigate the industrial performance of energy conservation and emission reduction in over two hundred cities in China as well as its influential factors. Their empirical results show that due to the combined effects of technological progress and efficiency improvement, the energy conservation and emission reduction performance of Chinese industry has improved at an average annual rate of 16%. The catch-up effect and convergence exist throughout the country, including the eastern, central, western and northeastern regions. The best performers, which act as the benchmark for industrial energy conservation and emission reduction, are the coastal cities in eastern China. Such findings implicate that the future cooperation between different regions should be enhanced so that advanced technologies and management measures can be transferred from the east to the central and west China. Long et al. [4] measured the industrial carbon productivity of 30 provinces in China from 2005 to 2012 and examined the spacetime characteristics and the main factors of China’s industrial carbon productivity by using Moran’s I index and spatial panel data models. Their empirical results indicate that there is significant positive spatial dependence and clustering characteristics in China’s province-level industrial carbon productivity. The spatial dependence may create biased estimated parameters in an ordinary least squares framework. According to the analysis of their spatial panel models, industrial energy efficiency, the opening degree, technological progress, and the industrial scale structure have significantly positive effects on industrial carbon productivity, while per-capita GDP, the industrial energy consumption structure, and the industrial ownership structure exert a negative effect on industrial carbon productivity. Such findings implicate that governmental organizations should encourage the exchange and sharing of information, technology, talents, and other resources across different provinces so that interprovincial cooperation on energy conservation and emissions reduction can be initiated, while industrial CO2 abatement should depend on technology updates, including the alternative energy, energy saving, and carbon-
sequestration technologies. In addition, due to the remarkable regional disparity, some sustainable industries in the southeast coastal provinces may better move to the mid-west inland provinces so that advanced technologies and management experiences can be shared by these backward regions. 3. Tools and methods Innovative tools and methods are essential to the success of low carbon industrial development since they can help researchers and policy maker to identify new industrial mitigation opportunities and measures. For instance, Shao et al. [5] selected mining sector to investigate the key driving factors on inducing corresponding carbon emissions since mining sector is the foundation of the whole industrial production as well as a carbon intensive sector. By employing a novel index decomposition method, namely, Generalized Divisia Index Method, they decomposed the energyrelated carbon emission changes of China’s mining industry and its sub-sectors over the period of 1999–2013 into some absolute value indices and relative value indices, including output scale, energy use, carbon intensity, emission coefficient, and energy intensity. In addition, a scenario analysis approach was applied to seek the feasible mitigation pathways on China’s mining sector and its five sub-sectors. Their results indicate that output scale effect is the primary contributor of the increase in the carbon emissions of both mining sector and its five sub-sectors and energy use effect also plays a promotion role, while carbon intensity effect contributes most to the decrease in carbon emissions. Another finding is that all sub-sectors have achieved the target of 45% carbon intensity reduction except the extraction industry of petroleum and natural gas. Even though, more efforts should be made for the whole mining sector in order to achieve the 2030 peak target of carbon scale. In another regard, industrial process emissions are increasing in the developing countries due to their fast industrialization. However, few studies have been reported on carbon emissions from the production of industrial materials, such as mineral products (e.g., lime, soda ash, asphalt roofing), chemical products (e.g., ammonia, nitric acid) and metal products (e.g., iron, steel and aluminum). It is also difficult to find effective data on carbon emissions from the production processes of these industrial products (in addition to cement production) from current international carbon emission datasets. Under such a circumstance, Liu [6] estimated the carbon emissions resulting from the manufacturing of 5 major industrial products in China. Based on an investigation of China’s specific production processes, he applied the Tier 1 approach depicted in IPCC, which is an output-based approach that estimates emissions based on the production volume and the default emission factors. The results indicate that China’s total carbon emission from the production of alumina, plate glass, soda ash, ammonia and calcium carbide was 233 million tons in 2013, equivalent to the total CO2 emissions of Spain in 2013. The cumulative emission from the manufacturing of these 5 products during the period of 1990–2013 was approximately 2.5 Gt CO2, more than the annual total CO2 emissions of India. Such a result indicates that quantifying the emissions from industrial processes is critical for understanding the global carbon budget and to develop suitable mitigation technologies and policies for these processes are crucial. In addition, Shan et al. [7] further examined the emissions from lime production, the second largest source of carbon emissions from industrial processes after cement production. Their study analyzes CO2 emissions from China’s lime production for the period of 2001–2012 and estimated the process emissions (scope 1 direct emissions caused by the process), fossil fuel combustion emissions (scope 1 direct emissions caused by fossil fuel combustion), and scope 2 indirect emissions (CO2 emissions caused by
Editorial / Applied Energy 166 (2016) 187–190
electricity consumption) from China’s lime industry. Their results show that the process emissions from lime sector increased rapidly from 88.79 million tons to 141.72 million tons during 2001–2012. Particularly, the scope 1 emissions from fossil fuel combustion were 56.55 million tons in 2012, whereas the scope 2 indirect emissions were 4.42 million tons. Moreover, the uncertainty of such estimations was analyzed, showing that the relative uncertainty of the emission factors and activities data falls between 2.83% and 3.34%. Also, with the rapid growth of aluminum production, reducing greenhouse gas (GHG) emissions in aluminum sector is a significant challenge. Liu et al. [8] analyzed the energy-related GHG emission trajectories, features and driving forces of China’s aluminum industry (CAI) from the perspective of life cycle analysis (LCA) for the period of 2004–2013. Their results indicate that CAI experienced a rapid growth of energy-related GHG emissions with an average annual growth of 28.5 million tons CO2e from 2004 to 2013. By applying the Log-Mean Divisia Index (LMDI) approach, a major index decomposition analysis (IDA) method, they found that energy-scale effect is the main driving force for energy-related GHG emissions increase in CAI, while emission-factor effect of secondary aluminum production plays a marginal effect. Construction and transportation-related activities account for the bulk of the embodied emissions, accounting for more than 40% of the total embodied emissions from CAI. Policy implications for GHG mitigation within the CAI, such as developing secondary aluminum industry (such as recycling used aluminum products), improving energy mix and optimizing resource efficiency of production, are raised. Similarly, due to the energy intensive nature of aluminum sector, Hao et al. [9] also studied the GHG emissions from China’s aluminum sector. They accounted that total GHG emissions from China’s primary aluminum production were 421 mt CO2e in 2013, approximately accounting for 4% of China’s total GHG emissions. Particularly, aluminum production process consumes huge amounts of electricity. Thus, power generation has substantial impact on overall GHG emissions. Under such a circumstance, the authors explored the impact of regional disparity of China’s power generation system on GHG emissions for the sector of primary aluminum production. Their analysis revealed that the national GHG emissions factor (GEF) of China’s primary aluminum production was 16.5 t CO2e/t Al ingot in 2013. In the different provinces GEFs ranged from 8.2 to 21.7 t CO2e/t Al ingot. They also found that provinces with high aluminum productions are also those with high GEFs. Future scenario analysis indicates that until 2020 GEF could be reduced by 13.2% in comparison to 2013 level, but total GHG emissions will increase to 551 million t CO2e triggered by an increasing product demand in the same time span. Based on their analysis, the authors recommended that the government should further promote energy efficiency improvement, facilitate aluminum industry redistribution with low-carbon consideration, promote secondary aluminum production, and improve aluminum industry data reporting and disclosure. Moreover, as the most abundant fossil fuel on the planet, coal provided around 29.0% of the global primary energy need and generated about 40.4% of the world’s electricity in 2012 [10]. Therefore, it is necessary to seek an appropriate pathway to allocate the limited coal resources among a set of pollutant treatment projects from an investment perspective so that the total losses can be minimized, including penal loss and vacancy loss. In order to solve such a problem, Yu et al. [11] proposed a discrete dynamic programming procedure to provide an effective solution for decision-making in treatment project investment. Furthermore, a case study involving the Laojuntang coal mine of Zhengzhou Coal Industry (Group) of China on the treatment project investment problem was implemented using the proposed model. The results
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demonstrated that the proposed model is effective and applicable for environmental investment decision-making at a typical coal mine in terms of minimizing the total losses. Finally, it is important for each developing country to disaggregate their national reduction targets into targets for various geographical parts of the country. In this regard, Wu et al. [12] proposed a DEA-based approach to allocate China’s national CO2 emissions and energy intensity reduction targets over Chinese provincial industrial sectors. They first evaluated the energy and environmental efficiency of Chinese industry. Then, considering the necessity of mitigating greenhouse gas (GHG) emission and energy consumption, they developed a context-dependent DEA technique which can better characterize the changeable production with reductions of CO2 emission and energy intensity, to help allocate the national reduction targets over provincial industrial sectors. Their empirical study of 30 Chinese regions for the period of 2005–2010 shows that Chinese industry had poor energy and environmental efficiency. Considering three major geographical areas, eastern China’s industrial sector had the highest efficiency scores while central and western China were similar to each other at a lower level. Their study shows that the most effective allocation of the national reduction target requires most of the 30 regional industrial to reduce CO2 emission and energy intensity, while a few can increase or maintain their 2010 emission levels. 4. Innovative policies Innovative policies can help governmental institutions and industrial managers achieve successful low carbon industrial development. They are instrumental in identifying industrial mitigation opportunities and creating enabling conditions. However, inappropriate policies may impede the real implementation or even discourage the enthusiasm of relevant stakeholders. Therefore, policy studies are critical so that appropriate policy options can be identified. In this regard, Liu et al. [13] reviewed the joint air control policy in the Jing-Jin-Ji region of north China. The Jing-Jin-Ji region is the most serious region in China for facing notorious air pollution. In order to respond to such a challenge, this region has now established ambitious targets for tackling air pollution within a rather complicated multi-level institutional architecture. Besides the intended improvements in air quality, these measures will have strong impacts in the industrial, power and transport sectors, raising questions about the larger economic, socio-political and environmental effects in the region and elsewhere. The purpose of this policy study is to gain a deeper understanding as to what extent the air quality can be improved and identifying potential problems of the policy implementation. By constructing a Competition & Cooperation framework of the local governments based on historical document analysis, their results show that for historical reasons, administrative decentralization and fiscal decentralization strengthen the phenomenon of governmental fragmentation; which led to both economic growth promotion and obstacle formation to the collaborative reduction of regional air pollution. This study provides valuable policy insights to those decision-makers so that different governmental organizations can coordinate and jointly prepare appropriate dust-haze management policies in the Jing-Jin-Ji region. Renewable energy has a critical role in limiting the GHG emissions. Mittal et al. [14] assessed the implication of aligning renewable energy deployment target with national emission reduction target for mitigation cost for the two largest developing countries, namely China and India. Their assessment method used Asia– Pacific Integrated Assessment/computable general equilibrium (AIM/CGE) model to determine the mitigation cost in terms of GDP and welfare loss under alternative renewable targets in
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different climate-constrained scenarios. A range of country-specific emission constraints was taken to address the uncertainties related to global emission pathways and emission entitlement schemes. Their comparative results show that China needs to significantly increase its share of non-fossil fuel in the primary energy mix to achieve the stringent emission reduction target compared to India. The modeling results show that it would be beneficial for the emerging economies to have harmonization between their renewable energy and emission reduction targets, significantly in the primary energy mix to achieve the stringent emission reduction target compared to India. Also, there is a shift toward the renewables and Carbon Capture and Storage (CCS) technologies with the increase in the stringency level of mitigation target. Finally, economic losses can be reduced by increasing the installed renewable energy capacity to fulfill the same mitigation target, implying that coordinated national climate and renewable energy policies help to achieve the GHG emission reduction target in an efficient and cost-effective manner. 5. Conclusions Industrial-related GHG emissions have continued to increase and are higher than GHG emissions from other end-use sectors. With the rapid industrialization in the developing countries, such a trend is even clear, especially in the Asian region where many emergent economies have chosen industrialization as their main development strategies. This special issue reports CO2 emissions from different industrial sectors, covering related assessment indicators, innovative tools and methods, and appropriate policies, so that a wide array of expertise, experiences and lessons can be shared. The detailed research outcomes from these studies can be shared or learned by industrial policy-makers and managers from developing world. However, the real application of these innovative efforts depends on the wills to use them in different regions. It is not easy to simply transfer the experiences from one to another. Especially, demand for environmentally superior technologies is still weak and both technical and financial resources are still inadequate in developing countries. Consequently, it is rational for industrial sectors in developing world to seek more environmentally and financially beneficial pathways on industrial development so that relevant research outcomes can be successfully transferred and applied in developing countries. Valuable policy insights from these studies include wide scale upgrading, replacement and deployment of best available technologies, integrated information platforms, cross-cutting technologies and measures (such as efficient motors, industrial process optimizations, energy saving and emission reduction efforts), a shift to low carbon electricity, radical product innovations (such as alternatives to cement), carbon dioxide capture and storage (CCS), demand on new and replacement products, systematic approaches and collaboration among different industries (share of infrastructure, waste management and information, energy cascading, industrial symbiosis, co-benefits efforts, etc.). Acknowledgement This special issue was financially supported by National Natural Science Foundation of China (71325006, 71461137008, 71573021).
References [1] IPCC. Climate change 2014: mitigation of climate change. IPCC assessment report 5, Geneva; 2014. [2] Cai B, Wang J, He J, Geng Y. Evaluating CO2 emission performance in China’s cement industry: an enterprise perspective. Appl Energy 2016;166:191–200. http://dx.doi.org/10.1016/j.apenergy.2015.11.006. [3] Zhou DQ, Wang Q, Su B, Zhou P, Yao LX. Industrial energy conservation and emission reduction performance in China: A city-level nonparametric analysis. Appl Energy 2016;166:201–9. http://dx.doi.org/10.1016/j.apenergy.2015. 09.081. [4] Long R, Shao T, Chen H. Spacial econometric analysis of China’s province-level industrial carbon productivity and its influencing factors. Appl Energy 2016;166:210–9. http://dx.doi.org/10.1016/j.apenergy.2015.09.100. [5] Shao S, Liu J, Geng Y, Miao Z, Yang Y. Uncovering driving factors of carbon emissions from China’s mining sector. Appl Energy 2016;166:220–238. [6] Liu Z. National carbon emissions from the industry process: production of glass, soda ash, ammonia, calcium carbide and alumina. Appl Energy 2016;166:239–44. http://dx.doi.org/10.1016/j.apenergy.2015.11.005. [7] Shan Y, Liu Z, Guan D. CO2 emissions from China’s lime industry. Appl Energy 2016;166:245–52. http://dx.doi.org/10.1016/j.apenergy.2015.04.091. [8] Liu Z, Adams M, Geng Y, Tian X. Uncovering driving forces on greenhouse gas emissions in China’ aluminum industry from the perspective of life cycle analysis. Appl Energy 2016;166:253–63. http://dx.doi.org/10.1016/j. apenergy.2015.11.075. [9] Hao H, Geng Y, Hang W. GHG emissions from primary aluminum production in China: regional disparity and policy implications. Appl Energy 2016;166:264–72. http://dx.doi.org/10.1016/j.apenergy.2015.05.056. [10] IEA. Key world energy statistics. Paris, France: International Energy Agency; 2014. [11] Yu S, Gao S, Sun H. A dynamic programming model for environmental investment decision-making in coal mining. Appl Energy 2016;166:273–81. http://dx.doi.org/10.1016/j.apenergy.2015.09.099. [12] Wu J, Zhu Q, Liang L. CO2 emissions and energy intensity reduction allocation over provincial industrial sectors in China. Appl Energy 2016;166:282–91. http://dx.doi.org/10.1016/j.apenergy.2016.01.008. [13] Liu G, Yang Z, Chen B, Zhang Y, Su M, Ulgiati S. Prevention and control policy analysis for energy-related regional pollution management in China. Appl Energy 2016;166:292–300. http://dx.doi.org/10.1016/j.apenergy.2015.06.032. [14] Mittal S, Dai H, Fujimori S, Masui T. Bridging greenhouse gas emissions and renewable energy deployment target: comparative assessment of China and India. Appl Energy 2016;166:301–13. http://dx.doi.org/10.1016/j.apenergy. 2015.12.124.
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Yong Geng School of Environmental Science and Technology, Shanghai Jiaotong University, Shanghai, China ⇑ Corresponding author. Yi-Ming Wei Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, China Manfred Fischedick Wuppertal Institute for Climate, Energy and Environment, Germany Anthony Chiu Department of Industrial Engineering, De La Salle University, Philippines Bin Chen School of Environment, Beijing Normal University, China Jinyue Yan Royal Institute of Technology (KTH), Sweden Malardalen University (MDU), Sweden
Contents lists available at ScienceDirect
Applied Energy journal homepage: www.elsevier.com/locate/apenergy
Editorial
Recent trend of industrial emissions in developing countries a r t i c l e
i n f o
Keywords: GHG emissions, industrial emissions Developing countries Emission accounting Policy implications
a b s t r a c t Greenhouse gas (GHG) emissions from industrial sectors are increasing, particularly in the developing world where pursuing industrialization has been highly addressed. This calls for further studies to learn and share experiences for developing countries. In order to fill in such a research gap, this special issue focuses on examining the recent trend of industrial emissions in developing countries. Among the manuscripts submitted to the Special Issue, twelve papers have been accepted after review, covering assessment indicators, tools and methods, and policies. Key industrial sectors, including cement, lime, aluminum, coal, mining, glass, soda ash, etc, have been investigated. Valuable policy insights have been raised, including wide scale upgrading, replacement and deployment of best available technologies, integrated information platforms, cross-cutting technologies and measures, a shift to low carbon electricity, radical product innovations, carbon dioxide capture and storage (CCS), demand on new and replacement products, systematic approaches and collaboration among different industries. These useful suggestions could be shared or learned by industrial policy makers or managers in the developing world so that the overall GHG emissions from their industrial sectors can be mitigated by considering the local realities. Ó 2016 Published by Elsevier Ltd.
1. Introduction Greenhouse gas (GHG) emissions from industry are rapidly increasing and higher than those from other end-use sectors. According to IPCC AR5 [1], total emissions from the industrial sector reached 14.86 GtCO2e in 2010, representing 30% of total global GHG emissions. Particularly, from a global perspective, with both urbanization and industrialization, GHG emissions from industrial sectors in developing countries experienced a rapid growth, while such emissions in developed countries are declining. Under such a circumstance, it is necessary to pursue an absolute reduction in emissions from the industrial sector. In order to achieve such a target, a broad set of mitigation options should be considered, including energy efficiency, material use efficiency, recycling and reuse of materials and products, industrial symbiosis, product service efficiency, demand reductions. These measures have been widely applied in developed countries. However, there are few studies from developing world. As a response to such an issue, we organize this special issue in Applied Energy, a leading journal in the field. The objective of the special issue (SI) is to address both global and local issues (such as energy security, carbon emissions, air pollution and public health) from industrial sectors while contributing to development needs. It focuses on integrating climate change concerns with industrial development objectives by encouraging industrial decision-makers to encompass low-emission and/or climate-resilient economic growth in their industrial development strategies. The editorial presents an overview of the twelve selected articles of this SI, which not only detail the innovative indicators, methods, cases and tools for promoting low carbon http://dx.doi.org/10.1016/j.apenergy.2016.02.060 0306-2619/Ó 2016 Published by Elsevier Ltd.
industrial development in the developing world, but also provide valuable policy insights to policy-makers and industrial managers from developing countries. We expect that new ideas and perspectives on how positive changes can be attained as well as an understanding on how different regions can generate solutions that have large, short and long-term positive benefits and how innovative industrial emission mitigation measures can be effectively embedded into local policy settings to contribute to low carbon industrial development at the local and regional levels. Most of the papers in the SI are focused on China. This is rational since China is the largest industrial emission country in the world and its industrial production scale is more profound. Nevertheless, we presume that valuable lessons can be learned or shared from these studies in China so as to promote win-win situations in resource efficiency, climate change prevention and adaptation from industrial sector in the developing world. 2. Evaluations Appropriate evaluation methods are valuable for managing sectorial emissions and for providing guidelines on low carbon development of industrial sectors. Various performance assessment methods and indicators for different industrial sectors have been developed, based on well-known assessment methods, such as: energy consumption, IPCC methods, on-site emissions, carbon footprints, and input-output analysis. Each method has its advantages and disadvantages and can address some specific parameters of low carbon industrial development. The selection of different methods is based upon the needs and available data. For instance,
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Editorial / Applied Energy 166 (2016) 187–190
Cai et al. [2] targeted to evaluate the overall CO2 emissions from China’s cement industry based on the detailed information of China’s total 1574 cement enterprises in 2013. It reflects the aspect that cement industry triggered by intensive construction activities in the country has become one of the key industrial emission sectors in China. Due to different factors process and energy emission intensities vary significantly between different enterprises. The average CO2 emissions performance of China’s cement enterprises (806 kg CO2/ton clinker) is approx. 4% lower than the global average level in 2013. This commendable result is very much based on the performance of the best production facilities as the CO2 emissions intensity of the best 20th clinker production, is even lower than the IEA’s 2020 target. That’s why the authors propose that those enterprises could be the entry threshold for future new enterprises and top runner benchmark for the existing enterprises. Also, CO2 emissions related to cement production differ from regions to regions. In China the Yangtze River Delta region is the most important hotspot of the cement CO2 emissions. Wuhu & Tongling are the hottest emission centres, with an average of 8,288 ton of CO2 emissions per square kilometers. As emissions factors differ widely, amongst others ownership of cement enterprises should be carefully considered in designing appropriate policy instruments. Favorable policies could focus on medium sized facilities, and initially focus on specific areas (e.g. along the Silk Road Economic Belt) and technologies. Zhou et al. [3] proposed a Malmquist energy conservation and emission reduction performance index (MECERPI) for assessing the performance changes in energy use and pollutant emissions over time. Their index is built upon the non-radial directional distance function and can be derived by solving data envelopment analysis. 15 MECERPIs were applied in order to empirically investigate the industrial performance of energy conservation and emission reduction in over two hundred cities in China as well as its influential factors. Their empirical results show that due to the combined effects of technological progress and efficiency improvement, the energy conservation and emission reduction performance of Chinese industry has improved at an average annual rate of 16%. The catch-up effect and convergence exist throughout the country, including the eastern, central, western and northeastern regions. The best performers, which act as the benchmark for industrial energy conservation and emission reduction, are the coastal cities in eastern China. Such findings implicate that the future cooperation between different regions should be enhanced so that advanced technologies and management measures can be transferred from the east to the central and west China. Long et al. [4] measured the industrial carbon productivity of 30 provinces in China from 2005 to 2012 and examined the spacetime characteristics and the main factors of China’s industrial carbon productivity by using Moran’s I index and spatial panel data models. Their empirical results indicate that there is significant positive spatial dependence and clustering characteristics in China’s province-level industrial carbon productivity. The spatial dependence may create biased estimated parameters in an ordinary least squares framework. According to the analysis of their spatial panel models, industrial energy efficiency, the opening degree, technological progress, and the industrial scale structure have significantly positive effects on industrial carbon productivity, while per-capita GDP, the industrial energy consumption structure, and the industrial ownership structure exert a negative effect on industrial carbon productivity. Such findings implicate that governmental organizations should encourage the exchange and sharing of information, technology, talents, and other resources across different provinces so that interprovincial cooperation on energy conservation and emissions reduction can be initiated, while industrial CO2 abatement should depend on technology updates, including the alternative energy, energy saving, and carbon-
sequestration technologies. In addition, due to the remarkable regional disparity, some sustainable industries in the southeast coastal provinces may better move to the mid-west inland provinces so that advanced technologies and management experiences can be shared by these backward regions. 3. Tools and methods Innovative tools and methods are essential to the success of low carbon industrial development since they can help researchers and policy maker to identify new industrial mitigation opportunities and measures. For instance, Shao et al. [5] selected mining sector to investigate the key driving factors on inducing corresponding carbon emissions since mining sector is the foundation of the whole industrial production as well as a carbon intensive sector. By employing a novel index decomposition method, namely, Generalized Divisia Index Method, they decomposed the energyrelated carbon emission changes of China’s mining industry and its sub-sectors over the period of 1999–2013 into some absolute value indices and relative value indices, including output scale, energy use, carbon intensity, emission coefficient, and energy intensity. In addition, a scenario analysis approach was applied to seek the feasible mitigation pathways on China’s mining sector and its five sub-sectors. Their results indicate that output scale effect is the primary contributor of the increase in the carbon emissions of both mining sector and its five sub-sectors and energy use effect also plays a promotion role, while carbon intensity effect contributes most to the decrease in carbon emissions. Another finding is that all sub-sectors have achieved the target of 45% carbon intensity reduction except the extraction industry of petroleum and natural gas. Even though, more efforts should be made for the whole mining sector in order to achieve the 2030 peak target of carbon scale. In another regard, industrial process emissions are increasing in the developing countries due to their fast industrialization. However, few studies have been reported on carbon emissions from the production of industrial materials, such as mineral products (e.g., lime, soda ash, asphalt roofing), chemical products (e.g., ammonia, nitric acid) and metal products (e.g., iron, steel and aluminum). It is also difficult to find effective data on carbon emissions from the production processes of these industrial products (in addition to cement production) from current international carbon emission datasets. Under such a circumstance, Liu [6] estimated the carbon emissions resulting from the manufacturing of 5 major industrial products in China. Based on an investigation of China’s specific production processes, he applied the Tier 1 approach depicted in IPCC, which is an output-based approach that estimates emissions based on the production volume and the default emission factors. The results indicate that China’s total carbon emission from the production of alumina, plate glass, soda ash, ammonia and calcium carbide was 233 million tons in 2013, equivalent to the total CO2 emissions of Spain in 2013. The cumulative emission from the manufacturing of these 5 products during the period of 1990–2013 was approximately 2.5 Gt CO2, more than the annual total CO2 emissions of India. Such a result indicates that quantifying the emissions from industrial processes is critical for understanding the global carbon budget and to develop suitable mitigation technologies and policies for these processes are crucial. In addition, Shan et al. [7] further examined the emissions from lime production, the second largest source of carbon emissions from industrial processes after cement production. Their study analyzes CO2 emissions from China’s lime production for the period of 2001–2012 and estimated the process emissions (scope 1 direct emissions caused by the process), fossil fuel combustion emissions (scope 1 direct emissions caused by fossil fuel combustion), and scope 2 indirect emissions (CO2 emissions caused by
Editorial / Applied Energy 166 (2016) 187–190
electricity consumption) from China’s lime industry. Their results show that the process emissions from lime sector increased rapidly from 88.79 million tons to 141.72 million tons during 2001–2012. Particularly, the scope 1 emissions from fossil fuel combustion were 56.55 million tons in 2012, whereas the scope 2 indirect emissions were 4.42 million tons. Moreover, the uncertainty of such estimations was analyzed, showing that the relative uncertainty of the emission factors and activities data falls between 2.83% and 3.34%. Also, with the rapid growth of aluminum production, reducing greenhouse gas (GHG) emissions in aluminum sector is a significant challenge. Liu et al. [8] analyzed the energy-related GHG emission trajectories, features and driving forces of China’s aluminum industry (CAI) from the perspective of life cycle analysis (LCA) for the period of 2004–2013. Their results indicate that CAI experienced a rapid growth of energy-related GHG emissions with an average annual growth of 28.5 million tons CO2e from 2004 to 2013. By applying the Log-Mean Divisia Index (LMDI) approach, a major index decomposition analysis (IDA) method, they found that energy-scale effect is the main driving force for energy-related GHG emissions increase in CAI, while emission-factor effect of secondary aluminum production plays a marginal effect. Construction and transportation-related activities account for the bulk of the embodied emissions, accounting for more than 40% of the total embodied emissions from CAI. Policy implications for GHG mitigation within the CAI, such as developing secondary aluminum industry (such as recycling used aluminum products), improving energy mix and optimizing resource efficiency of production, are raised. Similarly, due to the energy intensive nature of aluminum sector, Hao et al. [9] also studied the GHG emissions from China’s aluminum sector. They accounted that total GHG emissions from China’s primary aluminum production were 421 mt CO2e in 2013, approximately accounting for 4% of China’s total GHG emissions. Particularly, aluminum production process consumes huge amounts of electricity. Thus, power generation has substantial impact on overall GHG emissions. Under such a circumstance, the authors explored the impact of regional disparity of China’s power generation system on GHG emissions for the sector of primary aluminum production. Their analysis revealed that the national GHG emissions factor (GEF) of China’s primary aluminum production was 16.5 t CO2e/t Al ingot in 2013. In the different provinces GEFs ranged from 8.2 to 21.7 t CO2e/t Al ingot. They also found that provinces with high aluminum productions are also those with high GEFs. Future scenario analysis indicates that until 2020 GEF could be reduced by 13.2% in comparison to 2013 level, but total GHG emissions will increase to 551 million t CO2e triggered by an increasing product demand in the same time span. Based on their analysis, the authors recommended that the government should further promote energy efficiency improvement, facilitate aluminum industry redistribution with low-carbon consideration, promote secondary aluminum production, and improve aluminum industry data reporting and disclosure. Moreover, as the most abundant fossil fuel on the planet, coal provided around 29.0% of the global primary energy need and generated about 40.4% of the world’s electricity in 2012 [10]. Therefore, it is necessary to seek an appropriate pathway to allocate the limited coal resources among a set of pollutant treatment projects from an investment perspective so that the total losses can be minimized, including penal loss and vacancy loss. In order to solve such a problem, Yu et al. [11] proposed a discrete dynamic programming procedure to provide an effective solution for decision-making in treatment project investment. Furthermore, a case study involving the Laojuntang coal mine of Zhengzhou Coal Industry (Group) of China on the treatment project investment problem was implemented using the proposed model. The results
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demonstrated that the proposed model is effective and applicable for environmental investment decision-making at a typical coal mine in terms of minimizing the total losses. Finally, it is important for each developing country to disaggregate their national reduction targets into targets for various geographical parts of the country. In this regard, Wu et al. [12] proposed a DEA-based approach to allocate China’s national CO2 emissions and energy intensity reduction targets over Chinese provincial industrial sectors. They first evaluated the energy and environmental efficiency of Chinese industry. Then, considering the necessity of mitigating greenhouse gas (GHG) emission and energy consumption, they developed a context-dependent DEA technique which can better characterize the changeable production with reductions of CO2 emission and energy intensity, to help allocate the national reduction targets over provincial industrial sectors. Their empirical study of 30 Chinese regions for the period of 2005–2010 shows that Chinese industry had poor energy and environmental efficiency. Considering three major geographical areas, eastern China’s industrial sector had the highest efficiency scores while central and western China were similar to each other at a lower level. Their study shows that the most effective allocation of the national reduction target requires most of the 30 regional industrial to reduce CO2 emission and energy intensity, while a few can increase or maintain their 2010 emission levels. 4. Innovative policies Innovative policies can help governmental institutions and industrial managers achieve successful low carbon industrial development. They are instrumental in identifying industrial mitigation opportunities and creating enabling conditions. However, inappropriate policies may impede the real implementation or even discourage the enthusiasm of relevant stakeholders. Therefore, policy studies are critical so that appropriate policy options can be identified. In this regard, Liu et al. [13] reviewed the joint air control policy in the Jing-Jin-Ji region of north China. The Jing-Jin-Ji region is the most serious region in China for facing notorious air pollution. In order to respond to such a challenge, this region has now established ambitious targets for tackling air pollution within a rather complicated multi-level institutional architecture. Besides the intended improvements in air quality, these measures will have strong impacts in the industrial, power and transport sectors, raising questions about the larger economic, socio-political and environmental effects in the region and elsewhere. The purpose of this policy study is to gain a deeper understanding as to what extent the air quality can be improved and identifying potential problems of the policy implementation. By constructing a Competition & Cooperation framework of the local governments based on historical document analysis, their results show that for historical reasons, administrative decentralization and fiscal decentralization strengthen the phenomenon of governmental fragmentation; which led to both economic growth promotion and obstacle formation to the collaborative reduction of regional air pollution. This study provides valuable policy insights to those decision-makers so that different governmental organizations can coordinate and jointly prepare appropriate dust-haze management policies in the Jing-Jin-Ji region. Renewable energy has a critical role in limiting the GHG emissions. Mittal et al. [14] assessed the implication of aligning renewable energy deployment target with national emission reduction target for mitigation cost for the two largest developing countries, namely China and India. Their assessment method used Asia– Pacific Integrated Assessment/computable general equilibrium (AIM/CGE) model to determine the mitigation cost in terms of GDP and welfare loss under alternative renewable targets in
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different climate-constrained scenarios. A range of country-specific emission constraints was taken to address the uncertainties related to global emission pathways and emission entitlement schemes. Their comparative results show that China needs to significantly increase its share of non-fossil fuel in the primary energy mix to achieve the stringent emission reduction target compared to India. The modeling results show that it would be beneficial for the emerging economies to have harmonization between their renewable energy and emission reduction targets, significantly in the primary energy mix to achieve the stringent emission reduction target compared to India. Also, there is a shift toward the renewables and Carbon Capture and Storage (CCS) technologies with the increase in the stringency level of mitigation target. Finally, economic losses can be reduced by increasing the installed renewable energy capacity to fulfill the same mitigation target, implying that coordinated national climate and renewable energy policies help to achieve the GHG emission reduction target in an efficient and cost-effective manner. 5. Conclusions Industrial-related GHG emissions have continued to increase and are higher than GHG emissions from other end-use sectors. With the rapid industrialization in the developing countries, such a trend is even clear, especially in the Asian region where many emergent economies have chosen industrialization as their main development strategies. This special issue reports CO2 emissions from different industrial sectors, covering related assessment indicators, innovative tools and methods, and appropriate policies, so that a wide array of expertise, experiences and lessons can be shared. The detailed research outcomes from these studies can be shared or learned by industrial policy-makers and managers from developing world. However, the real application of these innovative efforts depends on the wills to use them in different regions. It is not easy to simply transfer the experiences from one to another. Especially, demand for environmentally superior technologies is still weak and both technical and financial resources are still inadequate in developing countries. Consequently, it is rational for industrial sectors in developing world to seek more environmentally and financially beneficial pathways on industrial development so that relevant research outcomes can be successfully transferred and applied in developing countries. Valuable policy insights from these studies include wide scale upgrading, replacement and deployment of best available technologies, integrated information platforms, cross-cutting technologies and measures (such as efficient motors, industrial process optimizations, energy saving and emission reduction efforts), a shift to low carbon electricity, radical product innovations (such as alternatives to cement), carbon dioxide capture and storage (CCS), demand on new and replacement products, systematic approaches and collaboration among different industries (share of infrastructure, waste management and information, energy cascading, industrial symbiosis, co-benefits efforts, etc.). Acknowledgement This special issue was financially supported by National Natural Science Foundation of China (71325006, 71461137008, 71573021).
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Yong Geng School of Environmental Science and Technology, Shanghai Jiaotong University, Shanghai, China ⇑ Corresponding author. Yi-Ming Wei Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, China Manfred Fischedick Wuppertal Institute for Climate, Energy and Environment, Germany Anthony Chiu Department of Industrial Engineering, De La Salle University, Philippines Bin Chen School of Environment, Beijing Normal University, China Jinyue Yan Royal Institute of Technology (KTH), Sweden Malardalen University (MDU), Sweden