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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]

Whether renewable energy consumption is beneficial to reducing CO 2 emission intensity and carbon emissions in the context of the goal of "carbon peak and carbon neutrality" in China. To prove this conjecture, considering the spatial spillover effect of carbon dioxide, this paper adopts the spatial Dubin model for empirical analysis based on the panel data of China's 30 provinces over the period 2002–2019. This study explores the CO 2 intensity mitigation effect of China's renewable energy consumption and further investigates the mediation role of technological innovation, industrial structure upgrading and optimization, and energy efficiency in the nexus between renewable energy consumption and carbon intensity. The main findings present that: (1) China's carbon emission intensity is characterized by significant spatial correlation; (2) Renewable energy consumption can significantly reduce carbon intensity and per capita carbon emissions; (3) The mediation effect of renewable energy consumption in reducing carbon emission intensity is to promote technological innovation and industrial structure upgrading, as well as improve energy efficiency. Based on the conclusions, this paper offers several policy implications for governments to reduce CO 2 emission intensity. • The impact of renewable energy consumption on CO 2 emission intensity is explored. • Renewable energy consumption can reduce carbon emission intensity and per capita carbon emissions. • Renewable energy consumption reduces CO 2 intensity through the spatial mediation effect. [ABSTRACT FROM AUTHOR]

The metallurgy industry plays a very important role in China's economic growth. Due to its energy concentration, the energy consumption of the industry accounts for a large proportion of China's total energy consumption, and thus contributes to carbon emissions. Whether the metallurgy industry can successfully reduce emissions is related to the future of China's carbon emissions targets. In this paper, the logarithmic mean Divisia index model is used to analyze the change in China's carbon dioxide emissions from 1991 to 2014. The empirical results show that there are three main factors affecting the carbon dioxide emissions of China's metallurgy industry. The three factors are labor productivity, energy intensity and industry size. In addition, we further analyzed the deep motivation of carbon dioxide emissions in the industry, and calculated the future emission reduction potentials. Lastly, according to the empirical results, the paper proposes policy recommendations for the future emission reduction of China's metallurgy industry. [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 transportation sector is one of the major driving forces of carbon emissions. Identifying the factors that affect CO 2 emissions from the transportation sector is important to build a low-carbon city. Most existing research focuses on the total effect of factors on CO 2 emissions while the indirect influence is also the driving force of CO 2 emissions. Additionally, identifying the causal relationship between variables is helpful to study the mutual acting mechanism. Therefore, this paper uses the path analysis model to estimate the direct, indirect and total influences of driving factors on transportation CO 2 emissions in Beijing and investigate the causality relationships between variables. The results show that reducing energy intensity and transportation intensity are the key factors in controlling the increase of transportation-related CO 2 emissions. Population has the greatest positive impact on CO 2 emissions because an increasing population is leading to growth in energy consumption and the number of motor vehicles. However, population could indirectly affect the energy intensity and transportation intensity to reduce carbon emissions. Moreover, motor vehicles increase CO 2 emissions due to the growth in private car population and its low energy efficiency. And, the change in the economic growth pattern somewhat inhibits the growth rate of CO 2 emissions by reducing the energy intensity and transportation intensity indirectly. To further suppress the growth of transportation carbon emissions, the following steps should be taken: appropriately improve the quality of population, control the scale of motor vehicles, develop and promote clean energy, and reduce traffic energy intensity and transportation intensity. [ABSTRACT FROM AUTHOR]

Since the combustion of fossil fuel became the largest contributing factor of greenhouse gas emissions in China, the growth of energy consumption caused by urbanization has led to significant increase in carbon emissions. Applying both the carbon-emissions-coefficient and the sector-energy-consumption method, we predicted the energy consumption and carbon emissions, explored the characteristics of energy consumption and carbon emissions in different urbanization stages, and analyzed the energy crisis in Shandong which is a typical province in China. The results indicate that in 2015 and 2020, the total primary energy consumption will be 1.57 times and 1.85 times higher than that of in 2009, and the carbon emissions are estimated to be 1.48 times and 1.67 times respectively. The urbanization has distinct positive effects on energy consumption and carbon emissions, and the influence is more obvious in the intermediate-stage than in the early-stage. From a policy perspective, this paper could provide valuable information for planners and decision makers to formulate feasible and practical polices with a view to optimize energy structure and mitigate carbon emissions. [ABSTRACT FROM AUTHOR]

The increasing energy and material consumption associated with global economic growth has resulted in the need for more severe efforts at mitigating global climate change. The iron and steel industry consumes 8% of energy and emits 7% of total CO 2 globally. China's iron and steel industry contributes to 15% of that country's total CO 2 emissions. Therefore, there is an urgent need to explore the possibility of net zero emissions in the iron and steel industry in China to meet China's goal of carbon neutrality before 2060. In the study presented in this paper, the MESSAGEix–China iron and steel model was developed by integrating the process-based technology of the sector into the IIASA's MESSAGEix framework to explore zero CO 2 emission pathways and their associated impacts on resources, energy, and water in China's iron and steel industry up to 2100. We found that there are multiple pathways to achieving zero CO 2 emissions in the Chinese iron and steel industry by the end of the 21st century. More specifically, in all the pathways developed in this study, CO 2 emissions decreased significantly between 2030 and 2060 due to the rapid application of 100% scrap-based Electric Arc Furnaces (EAFs) and hydrogen-based Direct Reduced Iron (DRI)-EAFs steel-making technologies. However, by 2060, there will still be 70–360 Mt of CO 2 emissions from China's iron and steel industry; consequently, carbon sink or negative emission technologies are required to offset this and achieve the country's carbon neutrality goal. Furthermore, technologies for achieving zero emissions differ widely in terms of their impacts on the consumption of materials and energy. Compared to the electric (ELE) scenarios, 25–40% of extra iron ore is consumed in the current and new national policy (NPS) scenarios and the DRI scenarios, but 25–220% of scrap is required. At the same time, 20–150% more energy will be saved in the ELE scenarios than in the NPS and DRI scenarios. Finally, we recommend that policy makers design a cross-cutting strategy to achieve zero CO 2 emissions and enhance efforts for material recycling and the provision of clean energy and water. • There are multiple pathways to achieving net zero emissions in China's iron and steel industry. • Steel outputs are essential for reducing CO 2 emissions and conserving materials, energy, and water. • Hydrogen-based DRI and 100% scrap-EAFs technologies are key to achieving zero emissions. • CO 2 mitigation measures have limited impacts on water consumption. [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]