Smart industrial fan monitoring system for the implementation of sustainable development goals

Energy consumption is the major source of industrial carbon emissions. Energy consumption carbon emission factor method and LMDI (Logarithmic Mean Divisia Index) method was used to analyze the carbon emission evolution of industrial economy energy consumption in Jiangsu Province with collected data on industrial energy consumption in 1995-2012. Results showed that Jiangsu province economic industrial carbon emissions keep increasing in 1995-2012 years. The results of carbon emission increase analysis of energy consumption structure effects, industrial energy consumption intensity effects and output scale effects in 1999-2012 showed that energy consumption intensity effect has the maximum contribution to carbon emissions in industrial carbon emissions Jiangsu Province. Therefore, the main way to control carbon emissions of industrial energy consumption in Jiangsu Province is reasonably control the growth of energy consumption.

Transportation is an important part of social and economic development and is also a typical high-energy and high-emissions industry. Achieving low-carbon development in the transportation industry is a much-needed requirement and the only way to achieve high-quality development. Therefore, based on the relevant data of 30 provinces in China from 2010 to 2018, this research uses the static panel model, panel threshold model and spatial Durbin model to conduct an empirical study on the impact and mechanism of digital innovation on carbon emissions in the transportation industry, and draws the following conclusions. (1) Carbon emissions in the transportation industry have dynamic and continuous adjustment characteristics. (2) There is a significant inverted U-shape non-linear relationship between the level of digital innovation and carbon emissions in the industry. In regions with a low level of digital innovation, the application of digital technology increases carbon emissions in this industry, but as the level of digital innovation continues to increase its application suppresses carbon emissions, showing an effect of carbon emission reduction. (3) The impact of digital innovation on carbon emissions in the transportation industry has a spatial spillover effect, and its level in one province significantly impacts carbon emissions in other provinces’ transportation industry through the spatial spillover effect. Therefore, it is recommended to further strengthen the exchange and cooperation of digital innovation in the transportation industry between regions, improve the scale of digitalization in this industry, and accelerate its green transformation through digital innovation, thus promoting the green, low-carbon, and sustainable development of China’s economy.

To respond to national policy requirements, reduce carbon emissions in the construction industry, and achieve the goal of "carbon peaking and carbon neutrality" as soon as possible. In this paper, a system dynamics model is proposed to predict and analyze carbon emissions in the construction industry in Liaoning Province. First, the influencing factors of carbon emissions in the construction industry in Liaoning Province are sorted out by searching relevant literature. Secondly, combined with the relevant data of the construction industry in Liaoning Province from 2009 to 2019 and the "14th Five-Year Plan" policy, set different simulation scenarios and use Vensim software to reasonably predict the carbon emissions of the construction industry from 2020 to 2030, and find out the impact of carbon emissions. The internal logical relationship of the main factors provides a theoretical basis and emission reduction path for reducing the energy consumption of the construction industry, reducing the total carbon emissions, and realizing the green and sustainable development of buildings.

Energy consumption and carbon emissions forecasting for industrial processes: Status, challenges and perspectives

<sec><title>Objective</title> The world is still in a phase of rapid industrialization and urbanization. Excessive carbon emissions has become the primary root cause of various urban or even global environmental problems, further impacting human physiological and psychological health. Cities are the largest sources of carbon emissions and are crucial regions for achieving carbon neutrality goals. Urban blue-green infrastructure (UBGI), comprising natural, semi-natural, or artificial green and blue spaces within cities, is considered as the most important carbon sink space in urban areas and has increasingly attracted widespread attention from researchers. However, there are still many unresolved issues regarding the effectiveness of UBGI in carbon sink enhancement and emission reduction: 1) How is the energy efficiency of carbon sink enhancement and emission reduction measured, and what factors influence it? 2) What are the mechanisms and pathways through which UBGI enhances carbon sink and reduces carbon emission? 3) How can UBGI be regulated to better enhance its effectiveness in carbon sink enhancement and emission reduction? 4) What are the limitations and potential directions for future research? This research aims to address these issues and propose scientifically sound planning strategies for UBGI construction to achieve urban carbon neutrality goals. </sec><sec><title>Methods</title> Through literature synthesis and deduction, this research organizes and analyzes the multi-scale measurement methods for UBGI’s efficiency in carbon sink enhancement and emission reduction, identifies corresponding influencing factors at each scale, and constructs multi-scale planning strategies for UBGI based on the logical framework of “measurement methods–influencing factors – planning strategies”. </sec><sec><title>Results</title> The research proposes UBGI planning strategies across three spatial scales (site, community and urban area), covering three key aspects: Carbon sequestration and sink enhancement, carbon reduction based on temperature reduction (or preservation), and travel-related carbon reduction. Based on current research gaps and planning needs, five major research topics are further identified. This research provides a detailed analysis of the measurement methods and influencing factors of UBGI’s efficiency in carbon sink enhancement and emission reduction from three perspectives: Carbon sequestration and sink enhancement, carbon reduction based on temperature reduction (or preservation), and travel-related carbon reduction. The research finds significant differences in the measurement methods for UBGI’s efficiency in carbon sink enhancement and emission reduction efficiency across different scales. Contradictory results may occur at different scales, and large-scale research often lacks characterization of internal features, leading to unclear mechanisms of influencing factors and obstructing practical planning. Based on the interpretation of UBGI’s mechanisms for carbon sink enhancement and emission reduction at different scales, this research formulates UBGI planning strategies across three spatial scales (site, community, and urban area). These strategies include: 1) At the site scale, for carbon sequestration and sink enhancement – carbon sink at the source, land balance, and ecological design; for emission reduction – symbiosis with buildings and integration into daily life. 2) At the community scale, for carbon sequestration – overall balance of revenue and expenditure, precise positioning, and proper interconnection of the carbon chain; for emission reduction – incorporation of cool islands and co-construction. 3) At the urban area scale, for carbon sequestration – enhancement of ecological space management and establishment of a carbon-safe pattern; for emission reduction – demand-based layout and organic dispersion. Finally, the research proposes five major research topics for the planning of UBGI’s carbon sink enhancement and emission reduction: How to construct unified measurement methods for UBGI’s efficiency in carbon sink enhancement and emission reduction across scales? How to measure UBGI’s efficiency in carbon reduction based on temperature reduction (or preservation) at the site scale? How to integrate the pathways of carbon sink enhancement and emission reduction for a life cycle assessment of UBGI? How to balance UBGI’s carbon sink enhancement and emission reduction with other functions to achieve the optimal layout for comprehensive benefits? How to achieve urban “carbon justice” through UBGI? </sec><sec><title>Conclusion</title> The carbon sink pathway of the strategy framework requires “carbon sink at the source – precise positioning – safe pattern”, and the emission reduction pathway requires “symbiotic integration – co-construction and sharing – organic dispersion”. The key trade-offs between these two pathways at three spatial scales may provide theoretical support and practical guidance for UBGI construction and management. The five major research topics mentioned above may offer valuable assistance for UBGI construction and future research. </sec>

Energy consumption carbon emission factor method was used to analyze the carbon emission evolution of industrial energy consumption in Hunan Province with collected data on industrial energy consumption in 2000-2012. Results had shown that Hunan province industry’s carbon emission keep increasing in 2000-2012. There is a highly correlation between the total coal consumption and carbon emission of industrial energy carbon emission. Industrial energy consumption structure plays a decisive role in carbon emission. Industrial economic growth at the expense of high energy consumption in 2000-2005 has changed. Industrial carbon intensity has a fluctuated downward trend from 2005 to 2012. From the perspective of carbon emission per industrial output and industrial energy consumption structure, there is a large potential for carbon emission control in Hunan industrial energy consumption. Therefore, the main way to control carbon emission of industrial energy consumption in Hunan Province is to optimize the energy structure, reasonable adjustment of industry structure, improve energy technical level, proper control the growth of energy consumption.

Refined assessment and decomposition analysis of carbon emissions in high-energy intensive industrial sectors in China

The development of China's manufacturing industry is constrained by factors such as energy and resources, and low-carbon development is arduous. Digitalization is an important method to transform and upgrade traditional industries. Based on the panel data of 13 manufacturing industries in China from 2007 to 2019, a regression model and a threshold model were used to empirically test the impact of digitalization and electricity consumption on carbon emissions. The research results were as follows: (1) The digitalization level of China's manufacturing industry was steadily increasing; (2) The proportion of electricity consumption in China's manufacturing industries in the total electricity consumption hardly changed from 2007 to 2019, basically maintaining at about 6.8%. The total power consumption increased by about 2.1 times. (3) From 2007 to 2019, the total carbon emissions of China's manufacturing industry increased, but the carbon emissions of some manufacturing industries decreased. (4) There was an inverted U-shaped relationship between digitalization and carbon emissions, the higher the level of digitalization input, the greater the carbon emissions of the manufacturing industry. However, when digitalization develops to a certain extent, it will also suppress carbon emissions to a certain extent. (5) There was a significant positive correlation between electricity consumption and carbon emissions in the manufacturing industry. (6) There were double energy thresholds for the impact of labor-intensive and technology-intensive manufacturing digitalization on carbon emissions, but only a single economic threshold and scale threshold. There was a single scale threshold for capital-intensive manufacturing, and the value was -0.5352. This research provides possible countermeasures and policy recommendations for digitalization to empower the low-carbon development of China's manufacturing industry.

Climate change calls for worldwide public concern and effort to cut down carbon dioxide (CO2) emissions and globally realize sustainable development. As one of the largest energy consumers, the construction industry plays a crucial role in achieving the national carbon emission reduction goal. This paper, by employing an improved Kaya model, explored the relationships and trends among carbon emission, energy consumption, and GDP growth rate and carbon emission intensity of the Chinese construction industry. Results showed that the carbon emission of the construction industry is mainly affected by GDP growth of construction scale. The energy consumption was the main driver to the increase of carbon emissions. The carbon emissions of unit area and carbon intensity showed a decreased trend with the development of economy and the increase of construction scale. The dependence of construction activities on the fossil fuel remained despite noticeable decrease. Energy intensity helps to reduce construction carbon emissions. Low carbon economy development of construction industry calls for technological innovation, alternative energy and new technical support for further breakthrough. These findings provide scientific evidence of carbon emissions in the Chinese construction industry and useful inputs for industry-specific emission regulations.

This paper investigates the relationship between technological progress in the energy sector and carbon emissions based on the Environment Kuznets Curve (EKC) and data from China during the period of 1995–2012. Our study confirms that the situation in China conforms to the EKC hypothesis and presents the inverted U-curve relationship between per capita income and carbon emissions. Furthermore, the inflection point will be reached in at least five years. Then, we use research and development (R & D) investment in the energy industry as the quantitative indicator of its technological progress to test its impact on carbon emissions. Our results show that technological progress in the energy sector contributes to a reduction in carbon emissions with hysteresis. Furthermore, our results show that energy efficiency improvements are also helpful in reducing carbon emissions. However, climate policy and change in industrial structure increase carbon emissions to some extent. Our conclusion demonstrates that currently, China is not achieving economic growth and pollution reduction simultaneously. To further achieve the goal of carbon reduction, the government should increase investment in the energy industry research and improve energy efficiency.

With the convened of Copenhagen conference, the national is vigorously respond to the low-carbon economic development. In such a situation, Tianjin is also actively engaged in. As an important aspect of the development of Tianjin, energy, also need to make reforms. As the foundation of the national economy, Energy is playing a very important role in ensuring the sustained, rapid and healthy development of the national economy and improving people's lives. How to develop low carbon energy, and reduce carbon emissions, is an important part of constructing the low-carbon economy society. This passage is mainly analyzes the relationship between the industrial structure and the carbon emissions, which is base on the unit of GDP of the scale-above industry in Tianjin and carbon emissions.

PurposeThis study aims to analyse the scientific relationship between technological innovation and carbon emissions. Taking the Chinese electric power industry as the empirical research object, this study examined the effect of power technological innovation on carbon emissions and proposed policy recommendations for the development of technological innovation in China.Design/methodology/approachThis study first calculated the energy consumption and carbon emission level of the Chinese electric power industry from 2005 to 2018. Secondly, this study built an evaluation index system for technological innovation of electric power with six indicators: average utilisation hours of power generation equipment; power consumption rate of power plant; line loss rate; standard coal consumption for power generation; standard coal consumption for power supply; and number of patent applications granted for generation, conversion or distribution of electric power in China. Finally, from a practical point of view, the relationship between technological innovation and carbon emissions of the Chinese electric power industry from 2005 to 2018 is evaluated and analysed.FindingsPower technology innovation has been found to have a long-term and relatively large effect on carbon emissions, and carbon emissions have a short-term and insignificant impact on power technology innovation.Research limitations/implicationsThis study puts forward relevant suggestions for developing technological innovation and technology transfer, which is essential to establishing a low-carbon or zero-carbon power system in China.Practical implicationsThis study provides empirical evidence for clarifying the relationship between technological innovation and carbon emissions in the power industry and further develops research theories on technological innovation and carbon emissions.Social implicationsRelevant authorities will adopt measures to promote technological innovation and development in the power sector to reduce carbon emissions.Originality/valueThis study built an evaluation index system with six indicators for technological innovation of electric power. The evaluation method was used to measure the technological innovation level of the Chinese electric power industry. The causal link between technological innovation and carbon emissions in China was analysed.

The rapid development of High-Performance Computing (HPC) has driven technological advancements but also brought environmental challenges such as high energy consumption, carbon emissions, and electronic waste. This paper develops three core models to systematically analyze these issues and proposes sustainable solutions. Firstly, the paper analyzes the total energy consumption of global HPC centers, dividing it into computing-related energy and non-computing energy (e.g., cooling systems). In 2024, the estimated total energy consumption of the HPC industry was 205 terawatt-hours, which could reach 287 to 328 terawatt-hours under full load conditions. Secondly, by calculating the carbon emissions per kilowatt-hour of electricity, the paper estimates the global carbon emissions of the HPC industry in 2024 to be 7.24 million tons. The third model assesses the environmental impact of electronic waste generated by HPC systems, projecting that by 2030, HPC-related electronic waste will produce 112.8 million tons of carbon emissions, with disposal costs reaching 715 million USD and landfill costs of 6 million USD. Additionally, the study predicts the trends of energy consumption, carbon emissions, and electronic waste in the HPC industry by 2030. The research indicates that by adopting energy-saving technologies, accelerating the transition to renewable energy, and optimizing electronic waste management, the HPC industry can mitigate environmental hazards while leveraging its innovative potential and, based on this, proposes technical design recommendations such as energy-efficient hardware and software, reducing electronic waste, adopting cloud storage, and considering environmental impacts in technical design.

Green logistics is an important part of green supply chain management, and its green and low-carbon level greatly affects the level of green supply chain management. In order to achieve China's targets of carbon peaking and carbon neutrality, and to study the emission reduction path of the logistics industry under green supply chain management, this paper uses the scalable STIRPAT model and ridge regression to analyze the influencing factors of carbon emissions in the logistics industry; Taking the relevant data from 2000 to 2020 as an example, combined with the scenario analysis method, this paper conducts an empirical study on the development trend of carbon emissions in China's logistics industry in the future. The results show that: under the low-carbon and enhanced low-carbon scenarios, China's logistics industry can achieve the carbon peak target of 876.6 MtCO2 and 817.02 MtCO2 respectively. Carbon emissions can be reduced to 234.9 MtCO2 by 2060 in the Enhanced Low Carbon Scenario. There is still a certain distance between neutralization. In the meantime, according to the forecast results, this paper, from the perspective of green supply chain management, from the three directions of carbon trading, reverse logistics and emission reduction costs, gives suggestions on the emission reduction path of China's logistics industry under the carbon peaking and carbon neutrality goals: consider early Incorporate the logistics industry into the carbon trading market; increase support and accelerate the development of reverse logistics; increase scientific research investment in clean energy, and promote new energy vehicles. This paper innovatively stands in the perspective of supply chain management, and improves the analysis of influencing factors. For the single industry of logistics industry, the carbon peaking and carbon neutrality goals goal is put in a model, which can better reflect the complete trend and target Provide low-carbon directions and suggestions. In all, these findings contribute to the formulation and implementation of sound policies to help China achieve the carbon peaking and carbon neutrality goals.

Carbon emissions from bridge engineering are an important component of the carbon emissions in the construction industry. The life cycle carbon emissions (LCCE) of two commonly used simple-supported beam bridges, hollow slab bridge and T-beam bridge, are studied and compared. Firstly, in order to establish the criteria for the comparison of different bridge types, the principle of equal stiffness is proposed for the superstructures, and the principle of matching load effect with bearing capacity is proposed for the substructures. Based on the above two principles, 6 bridges of 2 types and 3 spans are designed for comparative analysis. Then, a calculation model of the LCCE of simple-supported beam bridges is established, in which four stages, production, construction, operation and demolition stages are included, and the carbon emission factors of each stage are established. Finally, the carbon emissions of 6 bridges designed above are calculated, and the main factors affecting the LCCE of simple-supported beam bridges are discussed. The calculation results show that (1) For the same span, the LCCE of T-beam bridges are about 8–10% lower than those of hollow slab bridges. The reasons for this are that T-beam bridges use 22-32% less concrete and 4.5-11.5% less reinforcement than hollow slab bridges, which reduces carbon emissions during the production and demolition stages, and that the durability of the lateral connections of T-beam bridge is better than that of hollow slab bridge, which reduces carbon emissions from the maintenance and repair of T-beam bridge in the operation stage by about 30%. (2) Carbon emissions in the production stage of simple-supported beam bridges account for 83–84% of the LCCE, 11-12.6% of the LCCE in the operation stage, 3.8–4.5% of the LCCE in the construction stage, and 1% of the LCCE in the demolition phase. Therefore, the reduction of carbon emissions is most effective in the production and operation stages of these bridges. (3) Steel and concrete are the two materials that have the greatest impact on carbon emissions of simple-supported beam bridges. 100% recycled steel can reduce the carbon emissions of bridges by 17.7 -19.2% compared with 50% recycled steel. 50% and 100% recycled coarse aggregate concrete can reduce the carbon emissions of bridges by approximately 2.9% and 5.7%, respectively. (4) The carbon emission of the superstructure of the T-beam bridge is 12.5-14.2% less than that of the hollow slab bridge in the same span, and the differences in carbon emissions of the substructures are very small due to the small differences in the loads they are subjected to. With the increase of bridge span, the carbon emission per unit area of the superstructure of simple-supported beam bridge increases, that of the substructure decreases, and that of the whole bridge decreases firstly and then increases, which makes it possible to choose appropriate bridge span to decrease the carbon emission.