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High-precision CO2 emission data by sector are of great significance for formulating CO2 emission reduction plans. This study decomposes low-precision energy consumption data from China into 149 sectors according to the high-precision input–output (I–O) table for 2017. An economic I–O life cycle assessment model, incorporating sensitivity analysis, is constructed to analyze the distribution characteristics of CO2 emissions among sectors. Considering production, the electricity/heat production and supply sector contributed the most (51.20%) to the total direct CO2 emissions. The top 10 sectors with the highest direct CO2 emissions accounted for >80% of the total CO2 emissions. From a demand-based perspective, the top 13 sectors with the highest CO2 emissions emitted 5171.14 Mt CO2 (59.78% of the total), primarily as indirect emissions; in particular, the housing construction sector contributed 23.97% of the total. Based on these results, promoting decarbonization of the power industry and improving energy and raw material utilization efficiencies of other production sectors are the primary emission reduction measures. Compared with low-precision models, our model can improve the precision and accuracy of analysis results and more effectively guide the formulation of emission reduction policies.
Fan He; Yang Yang; Xin Liu; Dong Wang; Junping Ji; Zhibin Yi. Input–Output Analysis of China’s CO2 Emissions in 2017 Based on Data of 149 Sectors. Sustainability 2021, 13, 4172 .
AMA StyleFan He, Yang Yang, Xin Liu, Dong Wang, Junping Ji, Zhibin Yi. Input–Output Analysis of China’s CO2 Emissions in 2017 Based on Data of 149 Sectors. Sustainability. 2021; 13 (8):4172.
Chicago/Turabian StyleFan He; Yang Yang; Xin Liu; Dong Wang; Junping Ji; Zhibin Yi. 2021. "Input–Output Analysis of China’s CO2 Emissions in 2017 Based on Data of 149 Sectors." Sustainability 13, no. 8: 4172.
To combat climate change, the Chinese government has announced that the country will reach its national carbon emission peak within 2030. Various scenario studies suggest that technological advances in energy, such as energy efficiency and renewables, would be the leading determining factors for the peak in China's carbon emissions. However, most of these studies have failed to reflect the fact that China is shifting its economy from energy-intensive industries to non-energy-intensive industries, which may play a vital role in mitigating carbon emissions. To assess how economic structural changes may contribute to carbon emissions, an input–output optimization model was constructed and scenario analyses were performed. This model introduced the input-output model integrated with an optimization model to ensure the balance of economic structure in an optimal result. The results show that in 2030, China could peak its carbon emissions at 12.41 Gt CO2eq (parts per giga ton; carbon dioxide equivalent) by adjusting its energy-intensive economic structure of which the key sectors are coke refined petroleum and nuclear fuel (C8), chemicals and chemical products (C9), other nonmetallic minerals (C11), basic and fabricated metals (C12), and electricity gas and water supply (C17). The continuous increase in the added value of the tertiary industry could maintain a high GDP growth rate of 5.6% when the secondary industry is restricted to reduce carbon emissions. Accelerating the pace of China's economic transformation will be very conducive to an earlier realization of peaking CO2 emissions because the inhibition effect of structural change on carbon emissions presents an increasing marginal trend. From a policy perspective, the analytical techniques in this study could provide valuable information for decision-makers to regulate sector capital investment and formulate practical industrial policies with implications for CO2 emissions.
Yuqi Su; Xin Liu; Junping Ji; XiaoMing Ma. Role of economic structural change in the peaking of China's CO2 emissions: An input–output optimization model. Science of The Total Environment 2020, 761, 143306 .
AMA StyleYuqi Su, Xin Liu, Junping Ji, XiaoMing Ma. Role of economic structural change in the peaking of China's CO2 emissions: An input–output optimization model. Science of The Total Environment. 2020; 761 ():143306.
Chicago/Turabian StyleYuqi Su; Xin Liu; Junping Ji; XiaoMing Ma. 2020. "Role of economic structural change in the peaking of China's CO2 emissions: An input–output optimization model." Science of The Total Environment 761, no. : 143306.
Substantial amounts of greenhouse gas (GHG) emissions generated at urban wastewater treatment plants (WWTP) are gaining increasing appreciation. Improving upon the commonly used Process-Based Life-Cycle Analysis (PLCA) and Environmentally-Extended Life-Cycle Analysis (EIO-LCA) models, we construct a Hybrid Life Cycle Analysis (HLCA) model and quantify both direct and indirect GHG emissions at the operational stage of WWTPs in Shenzhen, one of the fastest urbanizing cities in the world. Data are collected from 26 wastewater treatment plants in Shenzhen, out of all 32, covering 5 commonly used wastewater treatment technologies in China, i.e. Sequencing Batch Reactor, Oxidation Ditch, Biological Filter, AAO-MBR and AAO. The results show that WWTPs using AAO-MBR technology have the highest GHG emission intensity, averaging 0.79 tons per m3, primarily due to its large electricity intensity required. WWTPs using other technologies emit 0.27 to 0.39 tons of GHGs per m3 of wastewater treated. GHG emissions associated with electricity use occupy the largest share, ranging from 65 to 75%. Therefore, transforming the energy structure of the electric power sector to low-carbon sources can reduce WWTPs operational GHG emissions. In total, GHG emissions from Shenzhen's urban wastewater sector have increased from below 0.5 million tons in 2012 to over 0.6 million tons in 2017. Inter-model comparison shows that EIO-LCA substantially underestimates the urban wastewater sector's GHG emissions using the water sector's average parameters while PLCA also results in minor underestimations due the omission of indirect emissions in the production stage of chemicals and other material inputs.
Xiawei Liao; Yujia Tian; Yiwei Gan; Junping Ji. Quantifying urban wastewater treatment sector's greenhouse gas emissions using a hybrid life cycle analysis method – An application on Shenzhen city in China. Science of The Total Environment 2020, 745, 141176 .
AMA StyleXiawei Liao, Yujia Tian, Yiwei Gan, Junping Ji. Quantifying urban wastewater treatment sector's greenhouse gas emissions using a hybrid life cycle analysis method – An application on Shenzhen city in China. Science of The Total Environment. 2020; 745 ():141176.
Chicago/Turabian StyleXiawei Liao; Yujia Tian; Yiwei Gan; Junping Ji. 2020. "Quantifying urban wastewater treatment sector's greenhouse gas emissions using a hybrid life cycle analysis method – An application on Shenzhen city in China." Science of The Total Environment 745, no. : 141176.
Mengnan Li; Haiyi Ye; Xiawei Liao; Junping Ji; XiaoMing Ma. How Shenzhen, China pioneered the widespread adoption of electric vehicles in a major city: Implications for global implementation. Wiley Interdisciplinary Reviews: Energy and Environment 2020, 9, 1 .
AMA StyleMengnan Li, Haiyi Ye, Xiawei Liao, Junping Ji, XiaoMing Ma. How Shenzhen, China pioneered the widespread adoption of electric vehicles in a major city: Implications for global implementation. Wiley Interdisciplinary Reviews: Energy and Environment. 2020; 9 (4):1.
Chicago/Turabian StyleMengnan Li; Haiyi Ye; Xiawei Liao; Junping Ji; XiaoMing Ma. 2020. "How Shenzhen, China pioneered the widespread adoption of electric vehicles in a major city: Implications for global implementation." Wiley Interdisciplinary Reviews: Energy and Environment 9, no. 4: 1.
The environmental threats posed by spent lithium-ion batteries (LIBs) and the future supply risks of battery components for electric vehicles can be simultaneously addressed by remanufacturing spent electric vehicle LIBs. To figure out the feasibility of battery remanufacturing, this paper quantifies the environmental impacts and costs of the remanufacturing of lithium-nickel-manganese-cobalt oxide battery cells and compares the results with the production of batteries from virgin materials. Based on the EverBatt model, a China-specific database of hydrometallurgical remanufacturing process is established. The results indicate that the reductions in energy consumption and greenhouse gas emissions by battery remanufacturing are 8.55% and 6.62%, respectively. From the economic standpoint, the potential cost-saving from battery remanufacturing is approximately $1.87 kg−1 cell produced. Through a sensitivity analysis, LIB remanufacturing is found to be economically viable until the purchase price of spent batteries rises to $2.87 kg−1. Furthermore, the impact of battery type variability is prominent, whereas the influence of recovery efficiency is limited.
Siqin Xiong; Junping Ji; XiaoMing Ma. Environmental and economic evaluation of remanufacturing lithium-ion batteries from electric vehicles. Waste Management 2019, 102, 579 -586.
AMA StyleSiqin Xiong, Junping Ji, XiaoMing Ma. Environmental and economic evaluation of remanufacturing lithium-ion batteries from electric vehicles. Waste Management. 2019; 102 ():579-586.
Chicago/Turabian StyleSiqin Xiong; Junping Ji; XiaoMing Ma. 2019. "Environmental and economic evaluation of remanufacturing lithium-ion batteries from electric vehicles." Waste Management 102, no. : 579-586.
Green bonds have both “bond” and “green” attributes and are one of the important financing tools for green financial markets. The green bond risk premium directly reflects the financing cost of bond issuers and the capital gains of investors. A reasonable risk premium is the key to the successful issuance and trading of green bonds. Therefore, this paper studies the factors affecting the risk premium of China’s green bond issuance, aiming to provide a basis for determining a more reasonable risk premium. Based on the primary issuance market of green bonds, this paper takes into account the macro- and microscopic cross-sectional data of green bond issuance and comprehensively considers the main factors affecting the green bond risk premium from macro-influence factors, micro-influence factors, and green attribute factors. An empirical study of the factors affecting the risk premium of China’s green bond issuance was conducted using multivariate statistical regression analysis. The study found that the green attribute factor affecting the risk premium of green bonds is third-party green assessment certification. The bond factors affecting the risk premium of green bond issuance mainly include debt credit rating, issue period, and issue size, all of which affect the risk of green bond issuance. The issuer factors affecting the risk premium of green bonds include debt principal, nature of property rights, and return on net assets. The macro factor affecting the risk premium of green bonds is the current market interest rate.
Qinghua Wang; Yaning Zhou; Li Luo; Junping Ji. Research on the Factors Affecting the Risk Premium of China’s Green Bond Issuance. Sustainability 2019, 11, 6394 .
AMA StyleQinghua Wang, Yaning Zhou, Li Luo, Junping Ji. Research on the Factors Affecting the Risk Premium of China’s Green Bond Issuance. Sustainability. 2019; 11 (22):6394.
Chicago/Turabian StyleQinghua Wang; Yaning Zhou; Li Luo; Junping Ji. 2019. "Research on the Factors Affecting the Risk Premium of China’s Green Bond Issuance." Sustainability 11, no. 22: 6394.
Junping Ji; Hua Tang; Peng Jin. Economic potential to develop concentrating solar power in China: A provincial assessment. Renewable and Sustainable Energy Reviews 2019, 114, 1 .
AMA StyleJunping Ji, Hua Tang, Peng Jin. Economic potential to develop concentrating solar power in China: A provincial assessment. Renewable and Sustainable Energy Reviews. 2019; 114 ():1.
Chicago/Turabian StyleJunping Ji; Hua Tang; Peng Jin. 2019. "Economic potential to develop concentrating solar power in China: A provincial assessment." Renewable and Sustainable Energy Reviews 114, no. : 1.
This paper builds an input-output model to analyze the energy and economic impacts of the 4.7 trillion-CNY investment projects of the “Three-Year Action Plan for Major Construction Projects of Transportation Infrastructure”, which was launched by the Chinese government in 2016. The results show that, from 2016 to 2018, the investment plan could increase China's GDP by 2.39%, 1.30%, and 1.24% and the energy consumption by 5.23%, 3.23%, and 1.10%, respectively. The top five production sectors contribute 55% of the GDP growth induced by the plan, and the top three sectors contribute 72% of the energy consumption growth, indicating the impact of the investment plan is mainly centralized on a limited number of sectors. From the view of supply chains, the 20 paths with the largest GDP contribution cover about 47% of the GDP growth induced by the plan, and the 20 paths that consume the most energy cover around 60% of the energy consumption growth. In these paths, the construction industry is the dominant demand sector, while the industry of nonmetallic mineral products and the industry of smelting and pressing of metals are the primary supply sectors. In the future, the Chinese government should pay more attention to indirect energy consumption related to the construction industry, while policymakers also need to set up more effective energy conservation policies for the upstream sectors of the construction industry, such as sectors providing cement, glass, and steel.
Junping Ji; Zijian Zou; Yushen Tian. Energy and economic impacts of China's 2016 economic investment plan for transport infrastructure construction: An input-output path analysis. Journal of Cleaner Production 2019, 238, 117761 .
AMA StyleJunping Ji, Zijian Zou, Yushen Tian. Energy and economic impacts of China's 2016 economic investment plan for transport infrastructure construction: An input-output path analysis. Journal of Cleaner Production. 2019; 238 ():117761.
Chicago/Turabian StyleJunping Ji; Zijian Zou; Yushen Tian. 2019. "Energy and economic impacts of China's 2016 economic investment plan for transport infrastructure construction: An input-output path analysis." Journal of Cleaner Production 238, no. : 117761.
Interprovincial electricity transmissions have been utilised in China to overcome the country's imbalanced social-economic development and resource endowments. A bottom-up technology-based model is adopted to estimate water uses in electricity-exporting provinces to produce the transmitted electricity as well as opportunistic water savings in the receiving provinces. The results highlight that, in 2014, on a national scale, electricity transmissions generated co-benefit of saving 20.10 billion m³ of water nationally due to the electric power sector's water productivity differences in the exporting and importing provinces. Taking regional water stresses into account, 10.98 billion m³ of national scarce water saving is realized through electricity transmissions. Moreover, electricity transmissions by China's proposed 12 future transmission lines are expected to use additional 3.22 billion m³ of water in the electricity-exporting provinces. As more water-intensive technologies, e.g. open-loop cooling, are more commonly utilised in the electricity-receiving provinces, a total amount of 16.97 billion m³ of water use will be avoided nationally. Water-use efficiency for power production should be improved in all regions. Transmitted power imports should still be encouraged in water-scarce regions to alleviate their water stresses while power exports should be shifted away from water-stressed regions to water-abundant ones. Energy transformation by utilising gas-fired capacity and hydropower in water-abundant Southern China could be advanced.
Xiawei Liao; Li Chai; Yu Jiang; Junping Ji; Xu Zhao. Inter-provincial electricity transmissions’ co-benefit of national water savings in China. Journal of Cleaner Production 2019, 229, 350 -357.
AMA StyleXiawei Liao, Li Chai, Yu Jiang, Junping Ji, Xu Zhao. Inter-provincial electricity transmissions’ co-benefit of national water savings in China. Journal of Cleaner Production. 2019; 229 ():350-357.
Chicago/Turabian StyleXiawei Liao; Li Chai; Yu Jiang; Junping Ji; Xu Zhao. 2019. "Inter-provincial electricity transmissions’ co-benefit of national water savings in China." Journal of Cleaner Production 229, no. : 350-357.
With a Multi-Regional Input-Output analysis, this study for the first time quantifies China's final electricity demands' life-cycle impacts on water quality using the indicator Grey Water Footprint (GWF). China's Grey Water Footprint for Final Power Demands (GWFP) amounts to 37.54 billion m³ in 2010, which is the highest in the north, east and central regions. Regarding the upstream sectoral contributions on a national scale, Coal Mining and Dressing, whose GWF is decided mainly by Chemical Oxygen Demand (COD) and petroleum, and Agriculture sector, whose GWF is decided by total nitrogen discharged, contribute the largest shares of 32.40% and 23.24%, respectively. 22.28 billion m³ of GWFP is transferred across provincial boundaries as virtual grey water embodied in electricity transmissions and trades of the power sector's upstream supplies. Electric power demands in coastal provinces induce water pollution in inland provinces. For example, 1.38, 1.07 and 1.06 billion m³ of GWF in Shanxi, Inner Mongolia, and Henan, respectively, are generated to fulfill final power demands in Shandong, Jilin and Shandong. Findings in this study are significant in helping policymakers recognize and mitigate final power demands' life-cycle adverse impacts on water quality. Moreover, insights of the inter-provincial virtual grey water transfers induced by power demands enable further discussions on burden sharing and compensation in terms of power demand management and water pollution controls.
Xiawei Liao; Li Chai; Xiaofan Xu; Qiong Lu; Junping Ji. Grey water footprint and interprovincial virtual grey water transfers for China's final electricity demands. Journal of Cleaner Production 2019, 227, 111 -118.
AMA StyleXiawei Liao, Li Chai, Xiaofan Xu, Qiong Lu, Junping Ji. Grey water footprint and interprovincial virtual grey water transfers for China's final electricity demands. Journal of Cleaner Production. 2019; 227 ():111-118.
Chicago/Turabian StyleXiawei Liao; Li Chai; Xiaofan Xu; Qiong Lu; Junping Ji. 2019. "Grey water footprint and interprovincial virtual grey water transfers for China's final electricity demands." Journal of Cleaner Production 227, no. : 111-118.
Battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs) are seen as the most promising alternatives to internal combustion vehicles, as a means to reduce the energy consumption and greenhouse gas (GHG) emissions in the transportation sector. To provide the basis for preferable decisions among these vehicle technologies, an environmental benefit evaluation should be conducted. Lithium iron phosphate (LFP) and lithium nickel manganese cobalt oxide (NMC) are two most often applied batteries to power these vehicles. Given this context, this study aims to compare life cycle energy consumption and GHG emissions of BEVs and PHEVs, both of which are powered by LFP and NMC batteries. Furthermore, sensitivity analyses are conducted, concerning electricity generation mix, lifetime mileage, utility factor, and battery recycling. BEVs are found to be less emission-intensive than PHEVs given the existing and near-future electricity generation mix in China, and the energy consumption and GHG emissions of a BEV are about 3.04% (NMC) to 9.57% (LFP) and 15.95% (NMC) to 26.32% (LFP) lower, respectively, than those of a PHEV.
Siqin Xiong; Junping Ji; XiaoMing Ma. Comparative Life Cycle Energy and GHG Emission Analysis for BEVs and PhEVs: A Case Study in China. Energies 2019, 12, 834 .
AMA StyleSiqin Xiong, Junping Ji, XiaoMing Ma. Comparative Life Cycle Energy and GHG Emission Analysis for BEVs and PhEVs: A Case Study in China. Energies. 2019; 12 (5):834.
Chicago/Turabian StyleSiqin Xiong; Junping Ji; XiaoMing Ma. 2019. "Comparative Life Cycle Energy and GHG Emission Analysis for BEVs and PhEVs: A Case Study in China." Energies 12, no. 5: 834.
Cities consume more than 67% of global primary energy, the production of which results in approximately three-quarters of global CO2 emissions, exacerbating the global warming trend and related extreme weather events and natural disasters. Therefore, it is critical for cities to use existing and new sources of energy efficiently and effectively. This paper introduces a methodology that can combine sustainable energy planning with economic analysis, proposing a form of sustainable urban energy planning that could reduce energy consumption with the minimum economic cost. Taking a postindustrial city (Shenzhen, China) as an example, this paper defines four scenarios by which to analyze future projections of energy generation and consumption from 2015 to 2030 based on the Long-range Energy Alternatives Planning System model. Also developed are Sankey maps for the energy flow from the energy supply to demand sectors for different scenarios. The results show that energy efficiency improvement and energy structure upgrade policies implemented in Shenzhen would have a significant impact on its energy system. Energy consumption is projected to increase steadily up to 2030 under each scenario except for the Peak Scenario, but with different growth rates. Electricity generation in all scenarios is supposed to expand by 2030 and sustainable electricity (such as distributed photovoltaic power, waste-to-energy power, and Combined Cooling, Heating, and Power) will play an important role in the Energy structure upgrade and Peak scenarios.
Guangxiao Hu; XiaoMing Ma; Junping Ji. Scenarios and policies for sustainable urban energy development based on LEAP model – A case study of a postindustrial city: Shenzhen China. Applied Energy 2019, 238, 876 -886.
AMA StyleGuangxiao Hu, XiaoMing Ma, Junping Ji. Scenarios and policies for sustainable urban energy development based on LEAP model – A case study of a postindustrial city: Shenzhen China. Applied Energy. 2019; 238 ():876-886.
Chicago/Turabian StyleGuangxiao Hu; XiaoMing Ma; Junping Ji. 2019. "Scenarios and policies for sustainable urban energy development based on LEAP model – A case study of a postindustrial city: Shenzhen China." Applied Energy 238, no. : 876-886.
Regional disparity in terms of industrial energy efficiency is noticeable in China due to the unbalanced economic progress in past decades. Analyzing the provincial industrial energy efficiency and its influencing factors is of great significance to formulate differentiated policies. To date, the influence of many social-economic factors on the industrial energy efficiency have been examined but the impact of the inter-industry structure has almost been ignored. In this paper, the slacks-based measure model incorporating undesirable output is applied to evaluate the industrial energy efficiency both at the provincial level and the sectoral level in China for the period 2010 to 2016. Then, industrial structure efficiency is introduced, which reflects the inter-industry structure and takes the sectoral-level energy efficiency into consideration. And the impact of the industrial structure efficiency on provincial industrial energy efficiency is tested by Tobit regression model. The results show that huge discrepancies of provincial industrial energy efficiency exist and the industrial structure efficiency is confirmed to be a determinative factor to the provincial industrial energy efficiency, with the coefficient of 0.525. Policy recommendations are provided for adjusting the provincial inter-industry structure and improving the industrial energy efficiency.
Siqin Xiong; XiaoMing Ma; Junping Ji. The impact of industrial structure efficiency on provincial industrial energy efficiency in China. Journal of Cleaner Production 2019, 215, 952 -962.
AMA StyleSiqin Xiong, XiaoMing Ma, Junping Ji. The impact of industrial structure efficiency on provincial industrial energy efficiency in China. Journal of Cleaner Production. 2019; 215 ():952-962.
Chicago/Turabian StyleSiqin Xiong; XiaoMing Ma; Junping Ji. 2019. "The impact of industrial structure efficiency on provincial industrial energy efficiency in China." Journal of Cleaner Production 215, no. : 952-962.
China's household energy demands' life-cycle water uses from 2002 to 2015 are quantified with an Input-Output analysis disaggregating rural and urban impacts. 9.73 and 1.60 km3 of water was withdrawn and consumed respectively in the life cycle of Chinese household energy demands in 2015, which was dominated by power and heat uses. An average urbanite's household energy uses, including coal, gas, petroleum products, power and heat, require about four times of life-cycle water uses than its rural counterpart. Among all upstream sectors, while agricultural sectors accounted for the largest shares for all energy uses, oil and gas extraction made significant contributions to petroleum products and gas consumption. A Structural Decomposition Analysis is conducted to disentangle the impacts of four driving factors, i.e. population, demand, economic structure and technology. Population change reduced energy consumption's life-cycle water use for rural households but increased that for urban households. Each economic sector's water intensity decreases, which represent technology advancement, played the dominant role curbing household energy consumption's life-cycle water uses. While power and heat dominates the household energy use profile, urbanization is accompanied by household consumption shifting from coal to gas and petroleum products. In order to reduce household energy consumption's impacts and reliance on water resources, it is imperative to reduce energy production's water use by adopting water-saving technologies, such as air cooling, as well as to reduce upstream sectors' water intensities, such as by promoting drip irrigation.
Xiawei Liao; Li Chai; Junping Ji; Zhifu Mi; Dabo Guan; Xu Zhao. Life-cycle water uses for energy consumption of Chinese households from 2002 to 2015. Journal of Environmental Management 2018, 231, 989 -995.
AMA StyleXiawei Liao, Li Chai, Junping Ji, Zhifu Mi, Dabo Guan, Xu Zhao. Life-cycle water uses for energy consumption of Chinese households from 2002 to 2015. Journal of Environmental Management. 2018; 231 ():989-995.
Chicago/Turabian StyleXiawei Liao; Li Chai; Junping Ji; Zhifu Mi; Dabo Guan; Xu Zhao. 2018. "Life-cycle water uses for energy consumption of Chinese households from 2002 to 2015." Journal of Environmental Management 231, no. : 989-995.
Manufacturing is the foundation of China's economy and accounts for a large proportion of China's CO2 emissions. In this study, the structural path decomposition (SPD) methodology, based on an environmental input-output model, was used to find critical supply chain paths that drive changes in CO2 life cycle in China's manufacturing industry from 1992 to 2012. The changes in CO2 emissions were decomposed into three main factors: carbon emissions intensity, input-output structure, and final demand. In this study, the “weighted average decompositions” method of structural decomposition analysis and the non-comparable input-output table were first applied to the SPD method to obtain accurate results. The results indicate that higher-order paths, especially the paths that started from the “Smelting and Rolling of Metals” and the “Production and Supply of Electricity and Steam” sectors, led to an increase in carbon emissions. This was mainly due to the extension of the industrial chain as well as policy priorities. Moreover, CO2 emissions from the “Chemical Industry”, “Manufacture of Nonmetallic Mineral Products”, and “Smelting and Rolling of Metals” sectors were mainly induced by the increase of final export demands. Based on the results of this study, relevant policy changes have also been recommended.
Yushen Tian; Siqin Xiong; XiaoMing Ma; Junping Ji. Structural path decomposition of carbon emission: A study of China's manufacturing industry. Journal of Cleaner Production 2018, 193, 563 -574.
AMA StyleYushen Tian, Siqin Xiong, XiaoMing Ma, Junping Ji. Structural path decomposition of carbon emission: A study of China's manufacturing industry. Journal of Cleaner Production. 2018; 193 ():563-574.
Chicago/Turabian StyleYushen Tian; Siqin Xiong; XiaoMing Ma; Junping Ji. 2018. "Structural path decomposition of carbon emission: A study of China's manufacturing industry." Journal of Cleaner Production 193, no. : 563-574.
To realize the sustainable development of energy, the Chinese government has formulated a series of national goals of total energy control and energy structure optimization. Under the national constraints, how to efficiently allocate the constrained total amount of energy consumption to each province is a fundamental problem to be solved. Based on a data envelopment analysis (DEA) model and a zero-sum game theory (ZSG), this paper constructs a weighted zero-sum game data envelopment analysis (ZSG-DEA) model to allocate the energy consumption quota. Additionally, this paper compares the results with the current administrative targets, to examine the efficiency and feasibility of each allocation mechanism. Finally, this paper employs the proposed model to determine the optimal energy structure for each province in China. The results indicate that by 2020, the national goal of energy structure adjustment will be realized, and energy structure will be diversified in most regions, whereas the coal-dominated status in primary energy consumption will not change. Additionally, the weighted ZSG-DEA model focuses on allocation efficiency while the government considers more regional economic disparity. Therefore, this study suggests a mixture of the two allocation mechanisms in accordance with specific conditions.
Siqin Xiong; Yushen Tian; Junping Ji; XiaoMing Ma. Allocation of Energy Consumption among Provinces in China: A Weighted ZSG-DEA Model. Sustainability 2017, 9, 2115 .
AMA StyleSiqin Xiong, Yushen Tian, Junping Ji, XiaoMing Ma. Allocation of Energy Consumption among Provinces in China: A Weighted ZSG-DEA Model. Sustainability. 2017; 9 (11):2115.
Chicago/Turabian StyleSiqin Xiong; Yushen Tian; Junping Ji; XiaoMing Ma. 2017. "Allocation of Energy Consumption among Provinces in China: A Weighted ZSG-DEA Model." Sustainability 9, no. 11: 2115.
In order to solve problems caused by climate change, countries around the world should work together to reduce GHG (greenhouse gas) emissions, especially CO2 emissions. Power demand takes up the largest proportion of final energy demand in China, so the key to achieve its goal of energy-saving and emission reduction is to reduce the carbon emissions in the power sector. Taking Shenzhen as an example, this paper proposed a stochastic optimization model incorporating power demand uncertainty to plan the carbon mitigation path of power sector between 2015 and 2030. The results show that, in order to achieve the optimal path in Shenzhen’s power sector, the carbon mitigation technologies of existing coal and gas-fired power plants will be 100% implemented. Two-thirds and remaining one-third of coal-fired power plant capacities are going to be decommissioned in 2023 and 2028, respectively. Gas-fired power, distributed photovoltaic power, waste-to-energy power and CCHP (Combined Cooling, Heating, and Power) are going to expand their capacities gradually.
Guangxiao Hu; XiaoMing Ma; Junping Ji. A Stochastic Optimization Model for Carbon Mitigation Path under Demand Uncertainty of the Power Sector in Shenzhen, China. Sustainability 2017, 9, 1942 .
AMA StyleGuangxiao Hu, XiaoMing Ma, Junping Ji. A Stochastic Optimization Model for Carbon Mitigation Path under Demand Uncertainty of the Power Sector in Shenzhen, China. Sustainability. 2017; 9 (11):1942.
Chicago/Turabian StyleGuangxiao Hu; XiaoMing Ma; Junping Ji. 2017. "A Stochastic Optimization Model for Carbon Mitigation Path under Demand Uncertainty of the Power Sector in Shenzhen, China." Sustainability 9, no. 11: 1942.
This paper studied the carbon mitigation paths of the power sector in Shenzhen, China from a supply-side perspective. We investigated the carbon mitigation potentials and investments of seventeen mitigation technologies in the power sector, and employed a linear programming method to optimize the mitigation paths. The results show that: 1) The total carbon mitigation potential is 5.95 MtCO2 in 2020 in which the adjustment of power supply structure, technical improvements of existing coal- and gas-fired power plant account for 87.5%,6.5% and 6.0%, respectively. 2) In the optimal path, the avoided carbon dioxide to meet the local government's mitigation goal in power sector is 1.26 MtCO2.The adjustment of power supply structure and technical improvement of the coal-fired power plants are the driving factors of carbon mitigation, with contributions to total carbon mitigation are 72.6% and 27.4%, respectively.
Xin Li; Guangxiao Hu; Ying Duan; Junping Ji. Optimization of carbon mitigation paths in the power sector of Shenzhen, China. IOP Conference Series: Earth and Environmental Science 2017, 81, 012168 .
AMA StyleXin Li, Guangxiao Hu, Ying Duan, Junping Ji. Optimization of carbon mitigation paths in the power sector of Shenzhen, China. IOP Conference Series: Earth and Environmental Science. 2017; 81 (1):012168.
Chicago/Turabian StyleXin Li; Guangxiao Hu; Ying Duan; Junping Ji. 2017. "Optimization of carbon mitigation paths in the power sector of Shenzhen, China." IOP Conference Series: Earth and Environmental Science 81, no. 1: 012168.
Peishi Wu; XiaoMing Ma; Junping Ji; Yunrong Ma. Review on Life Cycle Assessment of Greenhouse Gas Emission Profit of Solar Photovoltaic Systems. Energy Procedia 2017, 105, 1289 -1294.
AMA StylePeishi Wu, XiaoMing Ma, Junping Ji, Yunrong Ma. Review on Life Cycle Assessment of Greenhouse Gas Emission Profit of Solar Photovoltaic Systems. Energy Procedia. 2017; 105 ():1289-1294.
Chicago/Turabian StylePeishi Wu; XiaoMing Ma; Junping Ji; Yunrong Ma. 2017. "Review on Life Cycle Assessment of Greenhouse Gas Emission Profit of Solar Photovoltaic Systems." Energy Procedia 105, no. : 1289-1294.
Peishi Wu; XiaoMing Ma; Junping Ji; Yunrong Ma. Review on Life Cycle Assessment of Energy Payback of Solar Photovoltaic Systems and a Case Study. Energy Procedia 2017, 105, 68 -74.
AMA StylePeishi Wu, XiaoMing Ma, Junping Ji, Yunrong Ma. Review on Life Cycle Assessment of Energy Payback of Solar Photovoltaic Systems and a Case Study. Energy Procedia. 2017; 105 ():68-74.
Chicago/Turabian StylePeishi Wu; XiaoMing Ma; Junping Ji; Yunrong Ma. 2017. "Review on Life Cycle Assessment of Energy Payback of Solar Photovoltaic Systems and a Case Study." Energy Procedia 105, no. : 68-74.