How does energy transition improve energy utilization efficiency? A case study of China's coal‐to‐gas program

Low-carbon economy has become a topic of great concern to the international community. Sea level rise caused by climate change, flood disasters, biodiversity reduction, global famine, and other issues have begun to threaten the normal survival of human beings, and the climate problem needs to be solved urgently. While ensuring rapid economic development, in order to better control the total amount of greenhouse gas emissions, this paper, based on the theory of low-carbon economy, takes control of total carbon emissions for low-carbon economic development, as a perspective, and selects the optimization for the development of low-carbon economy. From the aspects of structural emission reduction technology and emission reduction, a carbon emission control optimization index system for low-carbon economic development based on total carbon emission control is constructed. Under the framework of the index system, construct an optimization model for the total amount of carbon emissions in a low-carbon economy and use the BP neural network model to seek the balance point between economic development, energy consumption, and carbon emissions so as to promote the rational and scientific development of the low-carbon economy. Planning and development. First of all, on the premise of maintaining the same economic growth rate, the optimization plan will reduce carbon emissions. Secondly, on the premise of keeping the cost of energy consumption unchanged, it is more reasonable to adjust the energy consumption structure. Taking the optimization plan as the suggestion for the development direction of the low-carbon economy, it provides scientific and feasible technical support for achieving the emission reduction target of reducing the unit greenhouse gas emission to 40%.

With the ratification of the Paris Agreement at the Paris Climate Conference, reducing carbon emissions has become a global interest. Coal is one of the main industries causing carbon emissions; thus, quantifying carbon emissions from coal mining is an important step in reducing these emissions. Firstly, based on the life cycle idea, in this paper, we define the Carbon Emission Boundary of the fully mechanized coal mining method. Secondly, the carbon emission accounting model (B-R model) of fully mechanized coal mining is established, which includes the total amount of carbon emissions and the carbon emissions of each mining link during the mining process. The Fifth-II mining area of the Jinda Coal Mine in Tengzhou City is taken as an example. We collect the relevant data on carbon emissions in the mining process of the Jinda Coal Mine, and the B-R model is used to obtain the carbon emissions in the mining process of this mining area. Finally, the feasibility of the B-R model is further verified according to the international authoritative carbon emission IPCC calculation method and the China Coal Production Enterprises Greenhouse Gas Emissions Accounting Methodology and Reporting Guide. The results show that the B-R model in this paper is feasible and that the greatest amount of carbon emissions arises from the coal breaking link and coal transportation, which provides a basis for other coal mines to calculate carbon emissions. The B-R model lays a foundation for coal mines to formulate a carbon emission reduction system.

Impact of energy structure on carbon emission and economy of China in the scenario of carbon taxation

LCA inventory data based on input-output tables was used to analyze the effects of the self-sufficiency rate of food and the food consumption pattern on the CO2 emission in Japan. For the food item i with the total consumption Ci [M¥] and self-sufficiency rate xi, the total amount of carbon emission consists of (1) domestic production of i, (2) production of industrial product j to be exported for the import of i, and (3) transportation to export j and import i. According to this model, an effective carbon emission coefficient, σeff, i was calculated for each food item i to calculate the total amount of carbon emission. Because of the low self-sufficiency rate of food (∼40%) and the rapid change in the food consumption pattern from the traditional to the western style, the total amount of carbon emission was proved to have substantially increased for the consumption of food in Japan. The difference between the present C-emission and that by assuming 100% food self-sufficiency or that assuming the self-sufficiency rate (∼60%) and the food consumption pattern at 1970 was almost comparable with the COP3 goal to reduce CO2 emission. This means that an increase in food self-sufficiency rate and/or a change in food consumption pattern, resulting in the industrial structure change, can be an effective option to reduce CO2 emission in Japan.

As the development of technologies that can reduce carbon emissions and the conversion of energy production methods have not produced particularly meaningful effects, major countries have high expectations for the effect of regulating the total amount of carbon emissions through the carbon emission market. Since Korea is a country that emits a lot of greenhouse gases, it operates a carbon emission market with a large transaction volume. For this market to show the expected effect, the movement of the emission permit price must be efficient. So this study analyzed whether the carbon emission market in Korea is efficient, comparing it with the European emission market. To this end, the time-varying Hurst exponent was measured using daily data of Korea's KAU and Europe's EUA Futures markets. The main results are summarized as follows. First, the degree of informational efficiency of the price movement of carbon emission market is time-varying. Second, in both the Korean and European carbon markets, transaction prices did not move randomly at many times, and there were many inefficient periods in both markets. Third, the long memory characteristics were stronger and the inefficiency was more severe in the KAU market than in the EUA market. Fourth, although the informational efficiency of KAU market has generally improved since 2022, it has not yet reached the level of efficiency implied by the efficient market hypothesis. These results mean that despite the government's efforts so far, the emission trading market is not functioning sufficiently. Therefore, it is necessary to continuously improve the emission trading system in a way that can reduce carbon emissions through the market function.

With the development of international trade, intermodal operations have become more and more important in goods transportation, in order to show the effect of carbon emission tax on a marine-land intermodal supply chain, this paper use dynamic game theory to get a sub-game Nash equilibrium, and the result of this paper show that the carbon emission tax will lead to sea transport and land transport to reduce the carbon emission of every goods, But the carbon tax is not necessarily guaranteed to reduce the total amount of carbon emissions. meanwhile, one part’s reduction of carbon emission may incentive the other part to reduce carbon emission.

As an important province in China with a large population, agriculture, industry, and energy consumption, Henan Province is in a period of attack and opportunity for low-carbon transformation of its economy and optimization of its energy structure, and carrying out a study on the assessment of carbon budget and carbon compensation at the county level, to promote the coordinated development of a low-carbon economy in central China and to realize China's vision of carbon neutrality by 2060, is important. The study selected 123 county-level units in Henan Province as the research object, based on the land use data of Henan Province from 2000 to 2020, constructed the carbon balance estimation model and measured the horizontal compensation standard with the help of the modified carbon compensation model, studied the spatio-temporal pattern of carbon balance and carbon compensation zoning of Henan Province under the perspective of the main functional area, and put forward the regional development strategy guided by the development of low-carbon economy. The research results demonstrated that： ① From 2000 to 2020, the total amount of carbon emissions from land use in Henan Province first increased and then decreased, with the peak in 2015, and the construction land was the major source of carbon. The amount of carbon absorption continued to grow steadily, and arable land and forest land were the major carriers of carbon sinks. The carbon budget showed significant spatial and temporal characteristics； carbon absorption showed a spatial pattern of "high in the west and low in the east, high in the south and low in the north；" and carbon emissions were spatially characterized by "a concentration of high values in the center and the north and a scattering of low values towards the outside." ② Henan Province exhibited similar spatial patterns in carbon intensity and net emissions, with high values in the central and northern regions tapering off outwards. From 2000 to 2020, carbon emission intensity ranked as follows： national key development zones （1.09） > provincial key areas （0.93） > agricultural areas （0.83） > provincial ecological zones （0.70） > national ecological zones （0.47）. For net carbon emissions, the order was （×104 t）： national key zones （165.94） > provincial key areas （52.55） > agricultural areas （-35.52） > provincial ecological zones （-47.11） > national ecological zones （-60.93）. Conversely, carbon compensation rates（%） were highest in provincial ecological zones （821）, followed by those in national ecological zones （773）, agricultural areas （412）, provincial key areas （198）, and lowest in national key zones （11）. ③ Carbon compensation varied significantly across 123 counties in Henan Province, with a total carbon payment of 9 207.09×104 yuan and offset of 4 819.29×104 yuan in 2020. A total of 45 payment zones and 78 compensation zones were identified, including 20 heavy payment zones and 30 heavy compensation zones. ④ Henan Province was divided into seven carbon intensity control areas, 33 total carbon control areas, 12 carbon balance areas, 12 low-carbon optimization areas, and 59 green carbon sink areas based on main functional areas. A regional optimization strategy was proposed to foster low-carbon economy development in Henan Province. The study offers insights for 123 counties in Henan Province to establish localized carbon compensation mechanisms, supporting the coordinated low-carbon economic development in central China and the pursuit of carbon neutrality.

To reduce carbon emissions effectively in Shandong province in New Normal economy, this paper presents a new way to reflect the situation of carbon emissions accurately from both time-perspective and spatial perspective. The characteristics of carbon emissions in Shandong province are presented during 2005–2014, and this paper explores the spatial autocorrelation of carbon emissions branches in 17 cities. The results show that the total amount of carbon emissions in Shandong province presented a steady growth, whereas the growth rate was low, and the proportion of coal consumption in energy structure was significantly higher than the national average. In addition, the spatial pattern of the carbon emissions in 17 cities presented obvious regionally distinction. Furthermore, the affecting factors governing carbon emissions are decomposed based on the Kaya identity. The results reveal that economic scale was the key factor to increase the carbon emissions, whereas energy efficiency was the main factor of carbon emissions reduction. Therefore, this paper draws government should promote carbon emissions reduction given priority to some regions virtually, while encouraging emission reduction in others.

This study takes Kunming City, Yunnan Province, China as the research area, to provide reference basis for revealing the change law of land use structure and energy consumption and carbon emissions in Kunming, optimizing land use structure and realizing the development of low-carbon city. Based on the data of land use structure and energy consumption in Kunming from 1997 to 2017, based on the estimation of total energy consumption carbon emissions, carbon intensity and per capita carbon emissions, the correlation between land use structure and energy consumption carbon emissions in Kunming has been calculated and analyzed in the past 20 years. Results: 1) The total amount of carbon emissions in Kunming has increased significantly in the past 20 years. It increased from 34.46 × 105 t to 95.09 × 105 t, an increase of about 2.8 times. 2) The types of land use with the highest correlation between land use structure and total carbon emissions of energy consumption, carbon emission intensity and per capita carbon emissions are urban and village and industrial and mining land (0.8258), cultivated land (0.8733) and garden land (0.7971) respectively. 3) The correlation between construction land and total carbon emissions is greater than that of agricultural land. Conclusion: There is a close correlation between land use structure and carbon emissions from energy consumption in Kunming.

In this paper, we consider the effect of carbon emission regulations on the vehicles assignment optimization problem. We propose a mathematical model, in which the choice of vehicles (between the traditional and new environmental-friendly ones) and the proper assignments to customers are the decision variables. We introduce a new measure, called the over-emission intensity (OEI) factor, with which the government can control the amount of carbon emission of companies. Based on this proposal, we establish a new mechanism, known as the cap-and-trade program with OEI, and incorporate it into the optimization model. This novel model is then validated and used to study the impacts of OEI, carbon emission quota, emission price, and budget, on the operational performance and optimal decision of the company. We demonstrate the usefulness of the model by illustrating the effect of market regulation and government’s macrocontrol on the reduction of carbon emission. We also show how the OEI affects the company’s total cost, total amount of carbon emission, and the optimal vehicles assignment scheme. Finally, we argue that integrating the government macrocontrol scheme with the market mechanism is an effective measure.

As the current carbon measurement method makes it difficult to reflect the time-space variability of carbon emission factors, it leads to the inability to clarify the carbon emission responsibility of grid-side losses. In this paper, starting from the internal power system, based on the power system carbon emission flow analysis theory and knowledge graph technology, a trend-tracking analytical algorithm based on the node conductivity matrix operation is proposed to solve the complex power allocation relationship between each generating unit and each node load, and between each generating unit and the line network loss. On the basis of this algorithm, the carbon flow tracking model of the whole power system is established according to the conversion relationship between the current and the carbon flow, and the analytical expressions of the carbon emission distribution among the power generation side, the load side and the line loss are obtained by combining with matrix operation, so as to measure the carbon emission measurement results of the whole power system and to provide data references for the responsibility sharing of carbon emission. Finally, simulation verification is carried out based on the actual system operation and load data for C city. The total amount of carbon emissions from electricity consumption is 98.8 million tCO2 when C city is used as the minimum spatial scale, while the total amount of carbon emissions from electricity consumption is 67.9 million tCO2, 14.0 million tCO2, 16.9 million tCO2, and the total amount of the three regions is 98.8 million tCO2, which is consistent with that calculated when C city is used as the minimum spatial scale. The calculation results are consistent in real-time. The carbon measurement method proposed in this paper can obtain higher spatial resolution carbon measurement results for electricity consumption.

Energy poverty and climate change are global challenges. While the Belt and Road Initiative (BRI) has fostered energy cooperation and alleviated energy poverty in BRI countries, its impact on climate change requires careful examination. This study investigates the impact of energy poverty alleviation on carbon emissions in BRI countries and analyzes the underlying mechanisms. In particular, this study constructs an integrated energy poverty assessment framework that includes three dimensions of energy accessibility, cleanliness, and affordability and utilizes the entropy-TOPSIS method to assess the status of energy poverty in 70 BRI countries. Subsequently, an empirical analysis using the Gini index as an instrumental variable was conducted to explore the impact of energy poverty alleviation on carbon emissions and the specific mechanisms. It is found that alleviating energy poverty in BRI countries will lead to an increase in per capita carbon emissions. However, improving energy cleanliness is effective in reducing per capita carbon emissions, while improving energy affordability has no significant impact on carbon emissions. This study shows that energy poverty alleviation and carbon emission reduction are two non-conflicting sustainable development goals. BRI countries can synergize energy poverty alleviation and carbon emissions reduction by focusing on clean energy development and providing energy subsidies.

Using energy consumption and land use data of each region of China in 2007, this paper established carbon emission and carbon footprint model based on energy consumption, and estimated the carbon emission amount of fossil energy and rural biomass energy of different regions of China in 2007. Through matching the energy consumption items with industrial spaces, this paper divided industrial spaces into five types: agricultural space, living & industrial-commercial space, transportation industrial space, fishery and water conservancy space, and other industrial space. Then the author analyzed the carbon emission intensity and carbon footprint of each industrial space. Finally, advices of decreasing industrial carbon footprint and optimizing industrial space pattern were put forward. The main conclusions are as following: (1) Total amount of carbon emission from energy consumption of China in 2007 was about 1.65 GtC, in which the proportion of carbon emission from fossil energy was 89%. (2) Carbon emission intensity of industrial space of China in 2007 was 1.98 t/hm2, in which, carbon emission intensity of living & industrial-commercial space and of transportation industrial space was 55.16 t/hm2 and 49.65 t/hm2 respectively, they were high-carbon-emission industrial spaces among others. (3) Carbon footprint caused by industrial activities of China in 2007 was 522.34×106 hm2, which brought about ecological deficit of 28.69×106 hm2, which means that the productive lands were not sufficient to compensate for carbon footprint of industrial activities, and the compensating rate was 94.5%. As to the regional carbon footprint, several regions have ecological profit while others have not. In general, the present ecological deficit caused by industrial activities was small in 2007. (4) Per unit area carbon footprint of industrial space in China was about 0.63 hm2/hm2 in 2007, in which that of living & industrial-commercial space was the highest (17.5 hm2/hm2). The per unit area carbon footprint of different industrial spaces all presented a declining trend from east to west of China.

This paper considers a carbon emission cap and trade market, where the carbon emission cap for each entity (either government or firm) is allocated first and then the carbon trading price is decided interdependently in the carbon trading market among the non-cooperative entities which make their production decision. We assume that there are n entities emitting carbon during the production process. After allocating the carbon (emission) cap for each participating entity in the carbon cap and trade market, each participant makes a production decision using the Newsvendor model given carbon trading price determined in the carbon trading market and trades some amount of its carbon emission, if its carbon emission is below or above its own carbon cap. Here, the carbon trading price depends on how carbon caps over the entities are allocated, since the carbon trading price is determined through the carbon (emission) trading market, which considers total amount of carbon emission being equal to total carbon caps over entities and some fraction of total carbon emission should be from each entity participating in the carbon cap and trade market. Thus, we can see the interdependency among the production decision, carbon cap and carbon trading price. We model this as a non-cooperative Stackelberg game in which carbon cap for each entity is allocated in the first stage and each entity’s production quantity is decided in the second stage considering the carbon trading price determined in the carbon trading market. First, we show the monotonic property of the carbon trading price and each entity’s production over the carbon cap allocation. In addition, we show that there exists an optimality condition for the carbon cap allocation. Using this optimality condition, we provide various results for carbon cap and trade market.

Spatial decomposition of city-level CO2 emission changes in Beijing-Tianjin-Hebei