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The reduction of carbon emissions in the power industry will play a vital role in global decarbonization. The power industry has three main strategies to achieve this reduction in emissions: to implement lean marketing strategies that effectively target users of power and encourage them to adopt decarbonizing technologies and services; to optimize the efficiency of these users of power; and to improve the efficiency of renewable energy sources. This paper establishes a comprehensive evaluation system of indexed data from power industry customers for the development of lean marketing strategies. This system evaluates indexes derived from customer data on renewable energy sources, carbon emissions, energy efficiency, and customer credit. It adopts the DEMATEL–CRITIC combination weight assignment and VIKOR method for system evaluation and conducts simulation experiments on customer data in a region of Northeastern China to give an example of how this method could be applied in practice to lean marketing. The results show that the evaluation system proposed in this paper can govern the lean marketing decision-making of power sales enterprises. [ABSTRACT FROM AUTHOR]

As a developing country, extensive carbon and sulfur emissions are associated with China’s rapid social and economic development. Chief among them are the emissions from coal and oil consumption. This paper focuses on the demand side, attempting to regulate the range of relative price of oil to coal at the consumption level. Through the adjustment of the relative price, the goal of reducing the emissions of carbon and sulfur could be achieved in the market of energy consumption. Data regression is applied to investigate the functional relationship between emissions and energy prices. The results indicate that when the coal price is less than 300, the higher relative price leads to less carbon and sulfur emissions; when the coal price is more than 300 and less than 500, there exists an optimal relative price which has the least carbon emissions, and this value is not more than 11.5; when the coal price is more than 500, the smaller relative price is beneficial to decline carbon and sulfur emissions. The changed trend of relative price-sulfur emissions is very similar to relative price-carbon emissions. Compared to the present energy situation in China, the relative price of oil to coal still need to be reduced especially when coal price is more than 500. [ABSTRACT FROM AUTHOR]

The power industry is the industry with the most direct uses of fossil fuels in China and is one of China's main carbon industries. A comprehensive and accurate analysis of the impacts of carbon emissions by the power industry can reveal the potential for carbon emissions reductions in the power industry to achieve China's emissions reduction targets. The main contribution of this paper is the use of a Generalized Divisia Index Model for the first time to factorize the change of carbon emissions in China's power industry from 2000 to 2015, and gives full consideration to the influence of the economy, population, and energy consumption on the carbon emissions. At the same time, the Monte Carlo method is first used to predict the carbon emissions of the power industry from 2017 to 2030 under three different scenarios. The results show that the output scale is the most important factor leading to an increase in carbon emissions in China's power industry from 2000 to 2015, followed by the energy consumption scale and population size. Energy intensity levels have always promoted carbon emissions reduction in the power industry, where energy intensity and carbon intensity effects of energy consumption have great potential to mitigate carbon levels. By setting the main factors affecting carbon emissions in the future three scenarios, this paper predicts the carbon emissions of China's power industry from 2017 to 2030. Under the baseline scenario, the maximum probability range of the potential annual growth rate of carbon emissions by the power industry in China from 2017 to 2030 is 1.9–2.2%. Under the low carbon scenario and technological breakthrough scenario, carbon emissions in China's power industry continue to decline from 2017 to 2030. The maximum probability range of the potential annual drop rate are measured at 1.6–2.1% and 1.9–2.4%, respectively. The results of this study show that China's power industry still has great potential to reduce carbon emissions. In the future, the development of carbon emissions reduction in the power industry should focus on the innovation and development of energy saving and emissions reduction technology on the premise of further optimizing the energy structure and adhering to the low-carbon road. [ABSTRACT FROM AUTHOR]

China's emissions continue to rise rapidly in line with its mounting energy consumption, which puts considerable pressure on China to meet its emission reduction commitments. This paper assesses the impacts of CO2 mitigation measures in China during the period from 2010 to 2050 by using a computable general equilibrium method, called AIM/CGE. Results show that renewable energy makes a critical difference in abating emissions during the period from 2010 to 2020. The scenarios with emission trading would drive more emission reductions, whereby the emission-cutting commitment for 2020 would be achieved and emission reductions in 2050 would be more than 57.90%. Meanwhile, the share of non-fossil energy increases significantly and would be more than doubled in 2050 compared with the BAU scenario. A carbon tax would result in a significant decline in emissions in the short term, but would have an adverse effect on economic growth and energy structure improvements. It is also observed that the integrated measures would not only substantially decrease the total emissions, but also improve the energy structure. [ABSTRACT FROM AUTHOR]

The fast-growing petrochemical industry is one of the largest energy consumers and emitters in China, exerting a strong impact on the national economic, energy and environmental systems. We provide a holistic picture of energy consumption and energy-related CO2 emissions from China's petrochemical industry in 2012 through an environmental input-output life-cycle assessment (EIO-LCA). We combine two perspectives: (1) direct energy consumption and emissions, and (2) the indirect energy and emissions embodied and reallocated from other sectors in the supply chain to satisfy final demand in the petrochemical industry. Results indicate that the total of its direct and indirect energy consumption and CO2 emissions accounts for approximately 32% and 18% of China's industrial total, respectively, exerting high "influence" and "induction" with regards to the rest of the economic sectors. Most of the petrochemical industry's embodied energy and CO2 emissions comes from the "Production and Supply of Electric and Heat Power". We also identified five other sectors key to China's energy conservation and CO2 mitigation efforts due to their high influence and induction effects: "Smelting and Pressing of Ferrous Metals", "Manufacture of Non-metallic Mineral Products", "Smelting and Pressing of Non-ferrous Metals", "Transport, Storage and Post", and "Mining and Washing of Coal". A systematic view of direct and indirect energy, environmental relationships, and the conveying effects among sectors is crucial for policymaking in China to achieve its energy and mitigation goals. [ABSTRACT FROM AUTHOR]

The household sector consumes a large amount of goods and services and is therefore a major source of global carbon emissions. This study aims to analyze per person household carbon emission (HCEs) patterns of urban and rural China over the period from 1995 to 2011. Annual macroeconomic data for the study were obtained from authentic Chinese government sources. Direct HCE estimates for each fossil fuel were obtained using the IPCC's reference approach, and indirect HCEs were calculated by input-output analysis. In 1995, per person HCEs from direct sources for urban and rural China were 0.50 tCO2 and 0.22 tCO2, respectively; by 2011, these values had increased to 0.60 tCO2 and 0.61 tCO2, an increase of 20% and 177.27%, respectively. Similarly, in 1995, per person HCEs from indirect sources for urban and rural China were 0.43 tCO2 and 0.16 tCO2, respectively; by 2011, these values had increased to 1.77 tCO2 and 0.53 tCO2, respectively, an increase of 306% and 235%. The reasons for these differences and the sets of policies required to rectify increasing emissions are discussed. If current trends and practices continue, with a RMB1000 increase in per capita income from 2011 levels, per person HCEs in urban and rural China will increase by 0.119 tCO2 and 0.197 tCO2, respectively. This result indicates that the sector of society which is most vulnerable will contribute most to China's increasing HCEs. Therefore, while developing energy consumption and emissions reduction policies and programs, principles of fairness and equity need to be followed. [ABSTRACT FROM AUTHOR]

With rising income and the emergence of modern shopping centers in urban China, shopping trips by private car becomes more and more common, leading to higher carbon emissions in the transport sector. Encouraging car owners to shift transport mode from private car to public transport could achieve significant emissions reductions. This study estimate carbon emissions savings by shifting from private cars to public transport for shopping trips in urban China, using Shenyang, one of the largest cities in China, as a case study. Our results show that the average carbon emissions per shopper is 426.9 g, and the carbon emissions on weekends is 13% higher than weekdays. Moreover, shoppers travelling by private car emitted five times more carbon emission than those by public transport. We also found that car ownership gradually increased as accessibility to public transport decreased, and that more car owners chose to travel by private cars than public transport in areas with limited access. This study, thus, highlights the potential for high-quality public transport to reduce the transport sector's carbon emissions in urban China. [ABSTRACT FROM AUTHOR]

China's industrial sector, which has a significant position in the world, is the main sector of China's energy consumption and waste gas emission. China's government has promulgated a Guiding Opinion, setting key regions to establish an emission reduction target of air pollutants during the 12th five year plan (2011–2015). Thus, there is a different regional treatment of industrial waste gas in China. This study considers the waste gas treatment expenditure as a new input and employs the non-radial directional distance function in the framework of the meta-frontier model to investigate the energy and emission reduction performance of China's industrial sectors. The study is aimed at finding a significant and expanded technical gap between key and non-key regions in the energy and emission reduction efficiencies. The empirical result presents an effective method to improve the performance by increasing the emission treatment expenditure to reduce emissions. [ABSTRACT FROM AUTHOR]