A graphical dual objective approach for minimizing energy consumption and carbon emission in production planning

Does new energy consumption conducive to controlling fossil energy consumption and carbon emissions?-Evidence from China

This work aims to analyze the impact of population aging on the relationship between economic growth and carbon emissions, and the relationship between energy consumption and carbon emissions. To this end, based on the panel data of 36 OECD countries from 1996 to 2016, the panel threshold regression model was developed. In the model, per capita carbon emissions are the explained variables, economic development (per capita GDP) and per capita energy consumption are the core explanatory variables of the two models respectively, population aging is the threshold variable, population size, technological innovation level, the degree of urbanization, industrial structure and energy intensity are control variables. The empirical results show that there is a population aging threshold effect between per capita GDP and per capita carbon emissions, and between per capita energy consumption and per capita carbon emissions. This means that population aging is an important factor that affects the relationship between economic growth and carbon emissions, as well as energy consumption and carbon emissions. Although economic growth and carbon emissions, energy consumption and carbon emissions were coupled, the coupling state decline when the population aging crosses the threshold value. This indicates that the population aging contributes to the decoupling of the economic growth and carbon emissions, and the decoupling of energy consumption and carbon emissions. Finally, on the basis of the proposed model, a robust analysis of the variable of trade openness was conducted to prove the validity of this research.

Are energy consumption and carbon emission caused by Bitcoin? A novel time-varying technique

The complex structure and large number of energy-consuming components in a machine tool provide a constant challenge to the researchers to characterize and model the energy consumption during a machining process. Recently, Therblig-based energy model in conjunction with value stream mapping has been used to identify and reduce the energy waste in a turning process. However, this model does not depict the information of energy consumption and carbon emissions throughout the process. Hence, it is difficult to estimate how much energy consumption and carbon emissions are caused by each activity. This paper presents an improved micro analysis of the energy and carbon emissions for each activity of a machining process on a value stream map. A case study of milling process is provided to illustrate the proposed methodology. The case study shows the improvement in energy efficiency, time efficiency, and carbon emissions. The energy and carbon emissions of each activity provide better transparency of energy flow and carbon emissions information throughout the machining process. The proposed methodology can not only be used to reduce the peak load at the factory level but also help to develop potential energy and carbon emission reduction strategies during the process planning stage.

This study delves into the complex interplay of climate change, natural disasters, energy consumption, and carbon emissions across 111 countries from 1990 to 2019. A structural shift in 2004 signifies altered global dynamics in CO2 emissions, closely linked to the escalation of meteorological and hydrological disasters driven by climate change. Globally, we illuminate the significant impact of climate-induced natural disasters, especially storms and extreme temperatures, on energy consumption and carbon emissions, albeit with variations. Regionally, we establish a notable positive association between extreme temperature-related disasters and both energy consumption and carbon emissions in Europe. Examining the aftermath of catastrophic events reveals an intensified influence of these disasters on carbon emissions and energy consumption in Africa, Latin America, and Europe. Developed economies experience significant impacts on carbon emissions and energy consumption from storms and extreme temperatures, while flood severity predominantly affects carbon emissions in developing countries. Additionally, we explore the potential of green patents in mitigating energy consumption and emissions triggered by disasters. While not conclusively proven, the statistically significant impact of green patents on energy conservation holds profound policy implications for advancing climate understanding, transforming energy landscapes, and addressing future sustainability concerns.

Compared to general public and residential buildings, large public buildings are often difficult to construct and have a long construction period, creating greater construction energy consumption and carbon emissions on the one hand, while generating a large amount and many types of difficult-to-track process data on the other. As such, it is difficult to measure carbon emissions and analyze various influencing factors. By realizing the simple calculation of energy consumption and carbon emissions, as well as discerning the degree of influence of various factors based on the results of influencing factors research, it is of considerable practical significance to propose energy savings and emission reductions in a targeted manner. In view of the above, this work aimed to establish a more practical calculation method to measure energy consumption and carbon emissions in the construction of large public buildings, as well as to identify the multiple influencing factors related to energy consumption and carbon emissions during the construction process. To demonstrate the practicality of our approach, quantitative calculations are carried out for a new terminal building in a certain place and from the perspective of sustainable urban construction; thus, the driving factors of the traditional STIRPAT model are extended to seven. Based on the calculation results, a modified STIRPAT model is used to analyze the comparative study of impact factors, such as population and construction machinery performance, on energy consumption and carbon emission intensity. The results show the following: (1) The energy consumption value per square meter of this terminal building is 3.43 kgce/m2, and the average carbon emission per square meter is about 13.88 kgCO2/m2, which is much larger than the national average of 6.96 kgCO2/m2, and (2) the type of energy used in the construction process has the greatest degree of influence on energy consumption and carbon emission, and the local GDP, population factor, construction machinery performance specifications, and shift usage also show a positive correlation with the growth of total energy consumption and carbon emissions. Moreover, while the government’s continuous investment in energy conservation and environmental protection has reduced the total energy consumption and carbon emissions in construction, there is still considerable room for improvement. Finally, according to the results, we provide theoretical references and constructive suggestions for the low-carbon construction of large public buildings in the construction stage. Thus, the results of our study will allow policy makers to formulate appropriate policies.

The article aims to develop an integrated relationship between carbon emissions, energy consumption, economic growth and trade for the top ten trading countries in the world for a period of nineteen years, 2000–2018. The results of panel data indicate a significant relationship between carbon emissions, energy consumption, economic growth and trade both in the short and long run. It is seen that a bidirectional causality between carbon emissions, trade and growth is present. Empirical results of the analysis in this article indicate that an increase in carbon emissions leads to an increase in the economic growth rate. The article also finds a positive relationship between carbon emissions and energy consumption. The findings also show that the emerging and newly industrialized countries place more emphasis on enhancing their trade positions, while developed countries tend to focus more on the overall economic growth than on trade. A major limitation of the study is that the data for energy consumption and carbon emissions is for the economy as a whole and not only for manufacturing. An incentive structure for reducing carbon emissions for the selected countries can be adopted along with the focus on adopting clean energy. The article’s findings add to the existing literature as comparatively few studies have been conducted with trade as an indicator and at the cross-country level for determining the empirical relationship between energy consumption, carbon emissions, growth and trade.

Accompanying the rapid growth of China’s population and economy, energy consumption and carbon emission increased significantly from 1978 to 2012. China is now the largest energy consumer and CO2 emitter of the world, leading to much interest in researches on the nexus between energy consumption, carbon emissions and low-carbon economy. This article presents the domestic Chinese studies on this hotpot issue, and we obtain the following findings. First, most research fields involve geography, ecology and resource economics, and research contents contained some analysis of current situation, factors decomposition, predictive analysis and the introduction of methods and models. Second, there exists an inverted “U-shaped” curve connection between carbon emission, energy consumption and economic development. Energy consumption in China will be in a low-speed growth after 2035 and it is expected to peak between 6.19–12.13 billion TCE in 2050. China’s carbon emissions are expected to peak in 2035, or during 2020 to 2045, and the optimal range of carbon emissions is between 2.4–3.3 PgC/year (1 PgC=1 billion tons C) in 2050. Third, future research should be focused on global carbon trading, regional carbon flows, reforming the current energy structure, reducing energy consumption and innovating the low-carbon economic theory, as well as establishing a comprehensive theoretical system of energy consumption, carbon emissions and low-carbon economy.

A fuzzy multi-objective model for aggregate production planning considering energy consumption, carbon emission, chemical, solid waste, and wastewater

This article analyses the relationships among carbon emissions, energy consumption, trade and economic growth in 12 Asia-Pacific economies. The results indicate the existence of four long-run equilibrium relationships among carbon emissions, energy consumption, trade and economic growth. These four variables are causally related to each other. The inverted-U environment Kuznets hypothesis is supported. The long-run elasticity of carbon emissions with respect to trade and energy consumption were 0.21 and 1.13, respectively. Furthermore, the empirical evidence from a dynamic panel error-correction model revealed two short-run unidirectional causalities: from trade to energy consumption and from energy consumption to GDP growth. The short-run results also showed two bidirectional causal relationships between energy consumption and carbon emissions and between economic growth and carbon emissions. These results suggest that Asia-Pacific economies undertake energy policy to reduce carbon emissions by increasing the energy efficiency and substantially increasing the share of renewable energy in the overall energy usage.

This article analyses the relationships among carbon emissions, energy consumption, trade and economic growth in 12 Asia-Pacific economies. The results indicate the existence of four long-run equilibrium relationships among carbon emissions, energy consumption, trade and economic growth. These four variables are causally related to each other. The inverted-U environment Kuznets hypothesis is supported. The long-run elasticity of carbon emissions with respect to trade and energy consumption were 0.21 and 1.13, respectively. Furthermore, the empirical evidence from a dynamic panel error-correction model revealed two short-run unidirectional causalities: from trade to energy consumption and from energy consumption to GDP growth. The short-run results also showed two bidirectional causal relationships between energy consumption and carbon emissions and between economic growth and carbon emissions. These results suggest that Asia-Pacific economies undertake energy policy to reduce carbon emissions by increasing the energy efficiency and substantially increasing the share of renewable energy in the overall energy usage.

In today's highly advanced industrialised and modernised world, China's economy is still growing, and its demand for energy is increasing daily. It is crucial to examine the connection between energy consumption, carbon emissions, and economic growth in order to promote economic growth based on energy conservation and emission reduction. Using Dezhou City in Shandong Province as an example, the study builds a VAR model of carbon emission, energy consumption, and economic growth in Dezhou City based on simplified macroeconomic sub-models, energy sub-models, and environmental sub-models. It then determines the correlation and influence mechanism between the three using tests like ADF unit root and Granger causality. The pertinent elements affecting Dezhou's carbon emissions were then investigated using grey correlation analysis. Finally, based on the study's findings, policy suggestions are made regarding energy use, carbon emissions, and economic expansion. It is necessary not only to restrain high-energy consumption industries and fundamentally optimize the energy consumption structure, but also to find new economic growth points and improve economic growth channels, so as to optimize the industrial structure. In this process, increasing the proportion of the tertiary industry is a key measure. In addition, the government needs to advocate the citizens to adopt a low-carbon lifestyle, and the concept of low-carbon environmental protection will be deeply rooted in the hearts of the people. This study will provide suggestions and theoretical guidance for China's energy consumption and carbon emissions, and help achieve high-quality growth of China and even the world economy.

After more than two decades of negotiation, the China–Russia gas deal represents a new era of energy cooperation between China and Russia. In total, this is a win–win deal for both sides. For China, the deal will decrease energy consumption and carbon emission but will not significantly influence air quality; for Russia, it will provide a new market for its gas resources. In this study, we calculated the energy consumption, carbon emission, and particulate matter pollution (PM2.5 and PM10) in China in 2020, 2030, 2040, and 2050 under four IPCC representative concentration pathways (RCPs 8.5, 6.0, 4.5, and 2.6). We found that energy consumption and carbon emission decreased under the gas deal in RCPs 8.5, 6.0, and 4.5, although the rate of decrease slowed over time; however, in RCP 2.6, the rate of decrease of energy consumption and emission increased over time. PM2.5 and PM10 emission showed similar trends but with increasing rate, although the gas deal would mitigate air pollution in the short term. Although China’s government hopes to reduce carbon and pollutant emission under the deal, our results suggest that additional mitigation measures will be necessary to achieve this goal. Nonetheless, the reduction in carbon emission suggests that the China–Russia gas deal provides a model that other countries can follow to slow climate change.

To understand the current situation and development trend of energy consumption and carbon emissions in the fishery industry, a Long-Range Energy Alternatives Planning System (LEAP)-fishery model for Zhoushan City was constructed, and the trends of energy consumption and carbon emissions in the Zhoushan City fishery industry were analyzed under the business-as-usual scenario, the low-carbon scenario, and the strengthened low-carbon scenario. The results show that under the business-as-usual scenario, the future energy consumption of Zhoushan City’s fisheries in general shows an increasing trend, and the composition of energy consumption in all scenarios is primarily dominated by fossil energy, with diesel and coal predominating. In terms of the structure of end-use energy consumption, fishing vessels and aquaculture consume the most energy, with energy consumption exceeding 30% of total energy consumption in all scenarios. In terms of the emission reduction contribution rate, which the promotion of clean energy generation, the improvement of energy efficiency, and the reduction of aquaculture production play key roles in the low-carbon development of the fishery industry. From an economic perspective, carbon reduction measures such as reduction of aquaculture production and increased efficiency of energy delivery would have significant economic benefits, but these measures have limitations. Finally, suggestions are made to optimize the energy structure, improve the implementation of energy intensity and total energy control, and strengthen public awareness of energy conservation to reduce carbon emissions from the fishery industry, thus making the research in this paper relevant to real-world situations.

Since the early 2010s, building energy consumption in regions in China with hot summers and cold winters has experienced an average annual growth rate of 6.5%, while building carbon emissions demonstrated an average annual growth rate of 3.7%. This underscores the pressing need to reduce building energy consumption and carbon emissions. The layout of residential clusters plays a critical role in determining the effective shading coefficient, which directly impacts solar radiation gain and subsequently affects energy consumption and carbon emissions. To explore this correlation and optimize the layout configuration of residential clusters to achieve the objective of minimizing energy consumption and carbon emissions in buildings, our study employed ECOTECT 2011 software to assess the layout attributes of different residential clusters through an analysis of the effective shading coefficient. Furthermore, using VirVil-HTB2 17_04_21 software, we simulated the solar radiation, building energy consumption, and carbon emissions for different residential cluster layouts. To examine the interplay between solar radiation, energy consumption, and carbon emissions, SPSS 27 software was used. The findings revealed that different residential cluster configurations exhibit unique effective shading coefficients, substantially influencing the solar radiation received by buildings and, consequently, their thermal performance. Our research reveals that adopting a staggered layout can lead to a reduction in average operating energy consumption by up to 2.23% and cooling energy consumption by up to 7.17%, compared to an enclosed layout. Similarly, enclosed layouts can contribute to a decrease in heating energy consumption by up to 4.06%, in contrast to courtyard layouts. Additionally, scattered layouts can effectively reduce carbon emissions by up to 0.95% when compared to courtyard layouts.