Application of Lagrange Interpolation Algorithm in Beijing Carbon Emissions Prediction

Industry is the main aero of the city's energy saving and emission reduction. Currently, the industrial energy consumption and carbon emission has a high proportion of the whole energy consumption and carbon emission in Beijing. It will have great practical significances to research the characteristics and major factors of Beijing's industrial energy consumption and carbon emissions. Basing on the statistical data collected, the existing problems and deficiencies of industrial energy consumption in Beijing were analyzed. Then the energy consumption and carbon dioxide emissions in next decade were predicted using GM (1.1) model and the exponential model. Based on this, the policy recommendations of the industries low-carbon development which in line with the functional orientation in capital. KEYWORD: Beijing; Industrial energy consumption; Carbon emissions; Low-carbon development

In recent years, China's economic development has attracted worldwide attention, but economic growth has been at the expense of the excessive consumption of energy.Per unit of GDP's energy consumption in China is not only much higher than the United States, Japan and other developed countries that are far higher than the world average.On basis of simple analysis on the cause of excessive energy consumption in our country, this paper uses the econometrics method to study the various factors in the economic growth and how they affect the level of the energy consumption.Finally, this paper puts forward the proposal of optimize the industrial structure in our country, as well as development of new energy and so on.Only in this way can we at the same time in the guarantee of our country's economic growth and reduce energy consumption, which improve the effect of energy efficiency achieved particularly remarkable.

This paper studies the causal relationship between energy consumption and economic growth in Beijing by using econometric method from 1980 to 2012, and then establishes the model between the energy consumption of three industries and economic growth to study the influence of the secondary industry and tertiary industry energy consumption on economic growth in Beijing. Finally, we put forward counter measures and suggestions on sustainable development of Beijing's economy and energy industry.

This paper does empirical analysis for the relationship between the energy consumption and export trade of Beijing based on the data about the total energy consumption and total export trade volume of Beijing during the period from 1980 to 2009 and by making use of a cointegration theory and a Granger causality test and establishing an error correction model (ECM). According to the analysis result, the energy consumption and export trade of Beijing had a cointegration relationship, namely a long-term equilibrium relationship and the changes of energy consumption of Beijing were the causes of the changes of the export trade scale of Beijing, which suggests that the energy consumption of Beijing had a certain promoting impact on the export trade of Beijing. It is therefore necessary for Beijing to ensure a equilibrium relationship between its energy consumption and export trade on the basis of sound and fast development of its economy so that its export trade can develop in a healthy way while its energy safety is guaranteed.

This study investigates the asymmetric cointegration and causal relationships between economic growth, carbon emissions, and energy consumption in the next eleven (11) countries over the period 1972–2013. The nonlinear autoregressive distributed lag (NARDL) bounds testing approach and nonpragmatic Granger causality tests are employed. This research’s empirical results have entrenched vital relationships that have significant policy implications. We affirm nonlinear cointegration among the variables in Bangladesh, Iran, Turkey, and Vietnam. The long-run asymmetric effect outcomes indicate a definite boom in economic growth, significantly increases carbon emission in Turkey, and a decline in Vietnam. Additionally, a positive shock to energy consumption significantly increases the carbon emission in Bangladesh, Iran, and Turkey, but a decrease in emissions in Vietnam. Findings from the Wald test reveal a long-run asymmetric effect between carbon emission and economic growth in Bangladesh, Iran, and Vietnam, and for Iran, an asymmetric short-run impact. Long-run and short-run asymmetric effects between carbon emission and energy consumption in Bangladesh and Iran. In terms of asymmetric causality results, bidirectional causality between carbon emission and economic growth was noted in Bangladesh and Turkey, and a unidirectional causality from economic growth to carbon emission in Egypt and South Korea. Energy consumption causes carbon emission in Bangladesh, Egypt, Pakistan, South Korea, and not vice versa. We determined a bidirectional asymmetric causality relationship between carbon emission and energy consumption in Vietnam and a unidirectional causality link from carbon emissions to Turkey’s energy consumption.

Excessive carbon emissions from energy consumption seriously restrict China's sustainable development and eco-environmental protection. Although the carbon emissions from the construction industry are less than that of the power, transportation, and manufacturing sectors, the carbon emissions released by the construction industry cannot be ignored due to its extensive development trend of high energy consumption and low efficiency. Based on this, this paper studies energy-related carbon emissions and emissions reduction of China's construction industry from 2007 to 2017 by adopting the input-output analysis method, energy consumption method, and structural decomposition model. The results show that within the sample range: (1) The optimization of the construction industry energy consumption structure has a significant reduction effect on the growth of energy carbon emissions from the construction industry in China, and the reduction effect has shown an increasing trend over time. However, it should be noted that in this sample range, the optimization of energy consumption structure in the construction industry is mainly reflected in the decrease of the proportion of high-carbon energy consumption such as raw coal, while low-carbon energy such as natural gas has not played a significant role. Therefore, the future energy optimization space of China's construction industry is still huge. (2) Energy intensity effect and input structure effect have a positive inhibitory effect on carbon emission growth of the construction industry, and the inhibitory effect of energy intensity effect is stronger than that of input structure effect. It shows that in the sample range, the generalized technological progress and energy efficiency of the construction industry have been better optimized and improved. (3) Except for 2015-2017, the final demand effect in other intervals has a positive effect on the growth of carbon emissions in the construction industry, and the secondary and tertiary industries play a major role in the final demand effect. It shows that the total demand for the construction industry in various industries still maintains a growth trend. This paper provides a theoretical analysis basis and practical guidance for China's construction industry to carry out more accurate and efficient emission reduction from the supply-side energy varieties and demand-side industry level, and further enriches the existing research on carbon emissions of the construction industry from the perspective of input-output analysis.

Economic development leads to the widespread use of energy, which results in carbon emissions. In order to determine the correlation between different urban carbon emissions and fiscal growth, a coupling and coordination model of urban carbon emissions and economic growth based on discrete Fourier transform (DFT) is constructed. According to the coupling and coordinated development characteristics of economic growth and carbon emissions, the evaluation index system of the regional economy and carbon emissions is constructed. This paper examines the proportion of primary energy consumption and the influencing factors of carbon emission in a city and constructs the economic growth computational intelligence model and urban carbon emission model. The coupling degree among economic growth, carbon emission, and energy consumption is studied; the coupling standard between economic growth and energy consumption carbon emission is determined; and the carbon emission factor under the method of DFT is introduced. The coupling coordination model between economic growth and carbon emission is constructed, and the interaction mechanism between carbon emission, economic development, and environmental protection is determined. The experimental findings demonstrate that when energy consumption intensity and carbon emission are relatively low, the model’s change in the trend of coupling coordination index is comparable with the real/actual condition and the model is more reliable.

In 2021, the Chinese government announced the goal and vision of carbon peak and carbon neutralization. The proposal of "double carbon strategy" has an important impact on China’s economic development. In this context, in order to accelerate the green development of Liaoning economy and realize the decoupling between economic growth and carbon emission. Taking Liaoning Province as the research object, this paper uses Granger causality test to analyze the relationship between energy consumption, carbon emission and economic growth, and uses Tapio decoupling analysis method to study the change of decoupling state between carbon emission and economic growth from 2010 to 2019. It is found that there is a two-way Granger causality between carbon emission, energy consumption and economic growth. At the same time, the decoupling analysis shows that the decoupling of carbon emission in Liaoning Province is more significant, and the carbon emission intensity of economy has decreased. Finally, it puts forward countermeasures and suggestions that Liaoning Province should optimize the industrial structure and speed up the application of clean energy.

Economic development usually leads to increased energy consumption, which in turn will result in an increase in carbon emissions. To break the relationship between economic development and carbon emissions, scholars have turned their attention to the phenomenon of decoupling. In this paper, we studied the decoupling relationship between carbon emissions and economic growth of the equipment manufacturing industry in China from 2000 to 2014. We adapted the LMDI decomposition method, and we used the Tapio decoupling evaluation model to analyze our data. We found that the decoupling relationship between carbon emissions and economic growth of China’s equipment manufacturing industry is weak, which indicates the industry is experiencing faster economic growth than carbon emission growth. We found the economic output is the factor that has the strongest influence on the industry’s carbon emission, and energy consumption intensity has the strongest relationship with the decoupling of economic growth and carbon emission. The indicators of the industry’s decoupling-effort are all less than 1.0, which indicates that the industry is in the state of weak decoupling, and we also observed an annual decreasing trend in the industry’s indicators. Toward the end of this paper, we used the Grey forecasting model to predict the decoupling relationship between carbon emission and economic growth for 2015–2024, and we discussed the implications of our research.

The study aims to examine the survey of earlier literature that deals with economic growth, energy consumption and carbon emission, both single country studies as well as multi-county studies that covers the period till 2019. The main focus of this survey is on the coverage of countries, modeling methodologies, periods as well as empirical conclusions. The literature survey in this research paper is based on the causality’s direction between (i) economic growth and carbon emission; (ii) economic growth and energy consumption; (iii) energy consumption and carbon emissions. From reviewing these studies, general remark can be assumed that the literature which has been produced is paradoxical. Firstly, most of the earlier studies have reported that economic growth and energy consumption are significant sources of carbon emission, however, the role of economic growth in carbon emission is highly reported in highly developing countries. On contrary, in case of developed countries, carbon emission is not linked with economic development. Secondly, in case of developing countries, higher energy consumption leads to increase the economic growth. For developed countries, there are less evidence of dependence between energy consumption and economic growth. Lastly, in both developing and developed countries, higher energy consumption has reported the main culprit for carbon emission Focusing on the implications, the governments and industries have to replace the non-renewable energy sources with renewable sources to generate electricity, run the industrial operations and for transportation purposes etc. Comprehending the literature survey has provided the basis to address the designing as well as implementing effective environmental as well as energy policies.

Summary Cities, contributing more than 75% of global carbon emissions, are at the heart of climate change mitigation. Given cities' heterogeneity, they need specific low-carbon roadmaps instead of one-size-fits-all approaches. Here, we present the most detailed and up-to-date accounts of CO2 emissions for 294 cities in China and examine the extent to which their economic growth was decoupled from emissions. Results show that from 2005 to 2015, only 11% of cities exhibited strong decoupling, whereas 65.6% showed weak decoupling, and 23.4% showed no decoupling. We attribute the economic-emission decoupling in cities to several socioeconomic factors (i.e., structure and size of the economy, emission intensity, and population size) and find that the decline in emission intensity via improvement in production and carbon efficiency (e.g., decarbonizing the energy mix via building a renewable energy system) is the most important one. The experience and status quo of carbon emissions and emission-GDP (gross domestic product) decoupling in Chinese cities may have implications for other developing economies to design low-carbon development pathways.

In recent years, the global greenhouse effect caused by excessive energy-related carbon emissions has attracted more and more attention. In this paper, we studied the dynamic evolution of factors driving China's energy-related CO2 emissions growth from 2007 to 2015 by using energy consumption method and input-output analysis and used the IO-SDA model to decompose the energy carbon emissions. Within the research interval, the results showed that (1) on the energy supply-side, the high carbon energy represented by raw coal was still the main factor to promote the growth of energy-related CO2 emissions. However, the optimization of energy consumption structure is conducive to reducing emissions. Specifically, the high carbon energy represented by raw coal exhibited a downward trend in promoting the increment of energy-related CO2 emissions, while the clean energy represented by natural gas showed an upward trend in promoting the increment of CO2 emissions. It is worth noting that there is still a lot of room for optimization of China’s energy consumption structure to reduce emissions. (2) On the energy demand-side, the final demand effect is the main driving force of the growth of carbon emissions from fossil energy. Among them, the secondary industry plays a major role in the final demand effect. The "high carbonization" of the final product reflects the characteristics of China's high energy input in the process of industrialization. At the same time, since the carbon emission efficiency of the tertiary industry and the primary industry is better than that of the secondary industry, actively optimizing the industrial structure is conducive to slowing down the growth of carbon emission brought by the demand effect. (3) The input structure effect is the main restraining factor for the growth of energy carbon emissions, while the energy intensity effect has a slight driving effect on the growth of energy carbon emissions. The results show that China's "extensive" economic growth model has been effectively reversed, but the optimization of fossil energy utilization efficiency is still not obvious, and there is still a large space to curb carbon emissions by improving fossil energy utilization efficiency in the future.

This study examines the causal relationship between energy consumption, carbon emission, trade openness, and economic growth and how the first three variables affects economic growth. Using data ranged from 1966 to 2023 from Indonesia, a vector error correction model and granger causality test is used to help analyze the data. Despite the expectations from exogenous growth theory and environmental Kuznets curve theory, the results reveal limited causality. Results shows that theres a causality from carbon emission towards economic growth and a bidirectional causality from energy consumption and economic growth with a long run effect from energy consumption, carbon emission, and trade openness towards economic growth. These findings suggest that that economic activities are reactive to environmental and energy trends. Policy implications include the need for integrated energy and environmental planning while recognizing the limited short-term impact of trade openness on economic growth dynamics in Indonesia.

Under the pressure of climate change and international carbon reduction targets, long-neglected rural energy consumption needs to be given high priority. China’s rural energy consumption structure is in the transition from non-commercial to commercial sources, and rural energy has become a key determinant to slow down the carbon emission growth. This paper systematically calibrates the current situation of rural energy consumption in Beijing by using the survey data of 1866 households in 13 districts and counties in Beijing based on the trend of energy supply and demand change in China. To this end, the paper combines rural policy measures to assess the pressure on coal-burning and clean energy supply trends, puts forward the rural energy structure adjustment path, with a view to promoting the use of clean energy in rural areas and reduce the environmental consequences of coal-burning.

This study focuses on the relationship among the energy consumption, carbon emission and economic growth of Malaysia by using a time series data from 1980-2016. The study findings are shown by an econometric analysis that energy consumption, total and per capita CO2 emission and gross domestic product (GDP) has increased vastly between 1980 and 2016. The Johansen cointegration test confirms the existence of the long run relationship of energy consumption with carbon emission and economic growth. Moreover, the Granger causality test reveals the unidirectional causality of energy demand and population with carbon emission. The positive and significant relationship between GDP and carbon emission is a critical issue in Malaysia that needs to be addressed with care as economic growth is necessary but increase of carbon emission is undesirable. Therefore, this study recommends to promote green energy, green growth (GDP) that will ensure both energy security and energy sustainability in Malaysia over time.