Reduction Path Research Articles

Impact of intelligence on the carbon emissions of energy consumption in the mining industry based on the expanded STIRPAT model

The intelligent construction of the mining industry has become an emerging trend in its future development plans. As a traditional high energy consumption industry, its energy conservation and emissions reduction have become particularly urgent concerns. Therefore, it is of great significance to study the impact of intelligence on the carbon emissions from energy consumption in the mining industry. This paper first uses dynamic indirect energy emissions factors to build an accounting model for carbon emissions from energy consumption in the mining industry and calculates the related carbon emissions from 2001 to 2020 by sector. Then, an expandable stochastic environmental impact assessment (STIRPAT) model is established to analyze the impact of intellectualization on the carbon emissions intensity of China’s mining industry. At the same time, many other important factors are included in the model, and the model is fitted using ridge regression. The results show that the order of influence, from large to small, is as follows: energy intensity, industrial output value, per capita output value, the proportion of output value of large and medium-sized enterprises, per capita stock of fixed assets, average enterprise output value, R&D intensity and proportion of indirect energy. Each 1% increase in the above factors will increase the corresponding carbon emissions intensity by 0.2005%, −0.1271%, −0.1207%, 0.7467%, −0.0595%, −0.09813%, 0.1143% and −0.1419%, respectively. Then, the prediction values of the independent variables are obtained by using the scenario analysis method and grey prediction model, and 12 scenarios are set up to predict the carbon emissions intensity of the mining industry energy consumption from 2021 to 2035 by using the expanded STIRPAT model. By analyzing the prediction results, we conclude that Scenario 8, Scenario 9, Scenario 10, Scenario 11 and Scenario 12 can achieve the emissions reduction goals of the mining industry in 2025 and 2030; the optimal path of emissions reduction is given for various scenarios. Finally, a development strategy for emissions reduction in China’s mining industry is proposed.

Main Pathways of Carbon Reduction in Cities under the Target of Carbon Peaking: A Case Study of Nanjing, China

As a designated national low-carbon pilot city, Nanjing faces the challenge of reducing energy consumption and carbon emissions while experiencing rapid economic growth. This study developed a localized Long-range Energy Alternatives Planning System (LEAP) model specifically for Nanjing and constructed four different development scenarios. By utilizing the Log Mean Divisia Index (LMDI) decomposition, the Tapio decoupling elasticity coefficient, and comparing the emission reduction effects of individual measures and their cross-elasticity of carbon reduction, this study investigated the key factors and their carbon reduction path characteristics in Nanjing toward its carbon peak target by 2030. The results indicate that: (i) Nanjing could reach its peak carbon target of about 3.48 million tons by 2025 if carbon reduction measures are strengthened; (ii) The main elements influencing Nanjing’s carbon peak include controlling industrial energy consumption, restructuring the industry, promoting the construction of a new power system, and developing green transportation; (iii) Controlling industrial energy consumption and changing industrial structure have a greater impact on reducing carbon emissions than other measures, and both have a synergistic effect. Therefore, Nanjing should prioritize these two strategies as the most effective methods to reduce carbon emissions. Additionally, to slow down the growth of urban carbon emissions, policies aimed at reducing the energy intensity and carbon intensity of energy consumption should be formulated. For instance, the integration and innovation of green industries within the city region, such as new energy vehicles, new energy materials, and big data, should be accelerated, and the proportion of clean energy consumption in urban areas should be increased. The LEAP (Nanjing) model has successfully explored Nanjing’s low-carbon pathway and provided policy guidance for the optimal transformation of industrial cities and early carbon peaking.

Emission reduction path for coal-based enterprises via carbon capture, geological utilization, and storage: China energy group

Emission reduction path for coal-based enterprises via carbon capture, geological utilization, and storage: China energy group

Research on the Optimal Energy Saving and Emission Reduction Path for Promoting High-Quality Industrial Development in Hubei Province

In December 2019, a novel coronavirus broke out in Wuhan City, Hubei Province, and, as the center of the coronavirus disease 2019 (COVID-19) epidemic, the economy and production throughout Hubei Province suffered huge temporary impacts. Based on the input–output and industrial pollution emissions data of 33 industrial industries in Hubei from 2010 to 2019, this article uses the non-parametric frontier analysis method to calculate the potential production losses and compliance costs caused by environmental regulations in Hubei’s industrial sector by year and industry. Research has found that the environmental technology efficiency of the industrial sector in Hubei is showing a trend of increasing year-on-year, but the overall efficiency level is still not high, and there is great room for improvement. The calculation results with and without environmental regulatory constraints indicate that, generally, production losses and compliance costs may be encountered in the industrial sector in Hubei, and there are significant differences by industry. The potential production losses and compliance costs in pollution-intensive industries are higher than those in clean production industries. On this basis, we propose relevant policy recommendations to improve the technological efficiency of Hubei’s industrial environment, in order to promote the high-quality development of Hubei’s industry in the post-epidemic era.

A Meta-analysis of Mindfulness and Sleep Quality

Mindfulness-based Therapies are an umbrella terminology for a group of interventions that is significantly efficient and effective in treating sleep disorders. To find out further research path of mindfulness-based stress reduction and mindfulness-based therapy for insomnia, a meta-analysis is conducted. Ten articles were included. The standardized mean difference is used as a measure to calculate this meta-analysis. Data in the analysis were processed using the random-effects model. The models effect size hedges g = -0.98 (95% CI: -1.69 to -0.27). Thus, significant difference from zero (z = -2.70, p = 0.007) was found in the average outcome. After subgroup analysis, when language served as moderator did the Q test results appeared to be homogeneous (Q (8) = 43.08, p < 0.001, tau= 0.30, I= 86.20%). This study guides a) Chinese researchers to dig more into the applications as well as mechanisms and differences between Chinese and western participants, especially more creatively and innovatively, b) Researching in online MBSR and MBT-I might lead another path towards refined and enhanced application in the future and c) more detailed control information or factors should be reported or controlled.

Dual-Defective Two-Dimensional/Two-Dimensional Z-Scheme Heterojunctions for CO2 Reduction

The target of photocatalytic CO2 reduction is to achieve high selectivity, efficiency, and stability for a single chemical/fuel production. The construction of conventional Z-scheme heterojunctions is beneficial to improve the interfacial charge separation and redox capacities. However, the random dimensions of junction component(s) undermine the charge-to-surface transport for catalytic reactions, and the limited chemical structures of catalysts restrict surface activity/selectivity tailoring. In this work, we successfully overcome these issues by stacking/constructing an ultrathin dual-defective two-dimensional (2D)/2D Z-scheme heterojunction with growing functional anionic vacancies onto both reductive and oxidative components of the Z-scheme. The O-vacancy-rich BiOCl/N-vacancy-rich g-C3N4-based 2D Z-scheme exhibits excellent photoactivity in CO2 reduction. The rate of CO2 photoreduction to CO is around 45.33 μmol g–1 h–1, which is 11.7- and 12.2-fold those of untreated bulk g-C3N4 and pristine BiOCl, respectively. Among them, N-vacancy-rich g-C3N4 exhibits active and selective photoreduction ability, accompanied with oxidation reactions from O-vacancy-rich BiOCl. Such ultrathin defective Z-schemes not only retain their original features, i.e., enhanced charge separation and redox capacities, but also extend to lower energy photon absorption and ameliorate charge-to-surface transport in two redox components. Besides, density functional theory calculations unveiled the thermodynamically favored CO2-to-CO reduction path and energy barrier’s stepwise reduction at the COOH-to-CO rate-limiting step from defective g-C3N4 to the single redox component defective junction and further to the defective junction with both redox components. This work provides an effective adaptable dual-defect engineering on 2D/2D heterojunctions to enhance CO2 photoreduction.

A Systematic Design Framework for Zero Carbon Campuses: Investigating the Shanghai Jiao Tong University Fahua Campus Case

Since the global zero carbon goal was proposed, most higher education institutions around the world are still in the process of transitioning towards carbon neutrality. However, there is still a research gap in the systematic design strategy for a zero carbon campus. This study adopts a qualitative literature analysis approach to establish a theoretical framework for a zero carbon campus design. The framework hierarchically outlines the One Top-Down vision of carbon neutrality, two complementary paths of carbon emission reduction and carbon sink, specific implementation strategies based on the coupling of the social, technological, and ecological dimensions, as well as the establishment of a carbon-neutral smart services platform. Subsequently, a case study was conducted at the Fahua campus of Shanghai Jiao Tong University, guided by this theoretical framework. This study not only completed the modeling and visualization of the carbon-neutral systematic design of the campus but also attempted to conceive of people-centered services under the zero carbon commitment and emphasized the critical role of university campus culture and historical connotations in the carbon-upgrading process. The results showed that the establishment of this theoretical framework can inspire innovative localized carbon-neutral solutions for campus, empower the replicability of advanced zero carbon campuses, and more effectively promote the carbon neutrality development of communities and cities.

Monetary values of increasing life expectancy: Sensitivity to shifts of the survival curve.

Individuals' monetary values of decreases in mortality risk depend on the magnitude and timing of the risk reduction. We elicited stated preferences among three time paths of risk reduction yielding the same increase in life expectancy (decreasing risk for the next decade, subtracting a constant from or multiplying risk by a constant in all future years) and willingness to pay (WTP) for risk reductions differing in timing and life-expectancy gain. Respondents exhibited heterogeneous preferences over the alternative time paths, with almost 90 percent reporting transitive orderings. WTP is statistically significantly associated with life-expectancy gain (between about 7 and 28 days) and with respondents' stated preferences over the alternative time paths. Estimated value per statistical life year (VSLY) can differ by time path and averages about $500,000, roughly consistent with conventional estimates obtained by dividing estimated value per statistical life by discounted life expectancy.

Long-Term Air Pollution Characteristics and Multi-scale Meteorological Factor Variability Analysis of Mega-mountain Cities in the Chengdu-Chongqing Economic Circle.

The online version contains supplementary material available at 10.1007/s11270-023-06279-8.

Autonomous Path Planning With Muscle Force Optimization for Robot-Assisted Pelvic Fracture Closed Reduction

The development of pelvic fracture closed reduction surgical robots is in its infancy, and the path planning of such robots lacks consideration of muscle force. This studys objective is to develop an intelligent path-planning algorithm to reduce muscle resistance and improve surgical safety. First, an orientation planning strategy (OPS) is introduced to adjust the orientation of fracture fragments. Then, the OPS is coupled to the 3D A* algorithm to obtain the 3D-OPS A* algorithm, which initially lowers the muscle resistance. In addition, a musculoskeletal model of a fractured pelvis is constructed based on the OpenSim platform, and the models validity is verified using data comparison and in vitro experiments. Finally, the OpenSim API is combined with the 3D-OPS A* algorithm to obtain 3D-OPSF A*, which is used to search for the reduction path with the least muscle resistance. Results show that the OPS-based path planning algorithm lowers muscle resistance by 49.4% on average compared to traditional and 3D A* planning. Compared to 3D-OPS A*, 3D-OPSF A* achieves 12.8% lower muscle resistance. The path planned by the 3D-OPSF A* algorithm significantly lowers muscle resistance, optimizes the robot payload intensity, and enhances the safety of the surgery. This study will be of great reference value for future research on intelligent path planning for pelvic fracture closed reduction surgical robots.

Dynamic Prediction and Driving Factors of Carbon Emission in Beijing, China, under Carbon Neutrality Targets

China has made remarkable achievements in reducing carbon emissions in recent years. However, there is still much reduction room before achieving carbon neutrality. In Beijing, the capital of China, it is a strategic choice to respond to global climate change by promoting green and low-carbon development. This paper calculates the carbon dioxide emissions of key industries in Beijing and analyzes the temporal evolution trend of carbon emissions. Carbon dioxide emissions in Beijing before 2030 are predicted based on the grey prediction GM (1,1) and BP neural network model. The effects of factors of carbon dioxide emissions are discussed using the threshold regression model under different economic conditions. The results show that energy consumption intensity, GDP per capita, and the ownership of civil cars have a positive impact on carbon dioxide emissions, while the number of permanent residents and urban green space areas have a negative impact on carbon dioxide emissions. These findings of carbon emission prediction and influencing factors contribute to carbon reduction path design. Related policy implications on carbon emission reduction are put forward from the aspects of promoting industrial upgrading, accelerating the construction of advanced economic structures, optimizing transportation structures, and strengthening green building development.

Understanding Carbon Emissions Reduction in China: Perspectives of Political Mobility

Climate change is one of the largest challenges facing mankind, and the question of how to reduce carbon emissions has raised extensive concern all over the world. However, due to the lack of mechanisms to explain the impact of political factors on environmental regulatory tools, the evaluation of carbon emissions reduction is insufficient in the majority of previous studies. How to better explore the path of carbon emissions reduction has become the key for China to achieve carbon neutralization as soon as possible. Based on a quasi-natural experiment regarding China’s carbon emission trading policy, this paper adopts a difference-in-differences model to address the impact of political mobility on China’s carbon emissions trading policy, and the selected pilot and non-pilot provinces of this policy in China enabled the model to be matched. Using a panel database with 30 provincial administrative units as the observation objects, the results show that China’s carbon emissions trading policy and the horizontal mobility experience of the provincial governors exert a significant positive effect on carbon emission reduction. Additionally, this study identifies a latent factor previously ignored by the existing literature: the correlation between political factors and carbon emissions. This verifies our theoretical hypothesis that officials transferred from the provincial level tend to have higher performance regarding carbon emission reduction. This paper also provides suggestions for the central government to further plan and implement carbon emission reduction policies and mobilize the incentives of local officials in environmental governance.

Low-carbon city planning based on collaborative analysis of supply and demand scenarios

With the proposal of carbon reduction goals of countries around the world, "green and low-carbon" has become a new key to urban development and construction. However, in the existing urban planning system, the energy planning mapped by carbon emissions has received less attention, and the main goal is often to ensure safe supply. There is less research on carbon emissions. Therefore, it is necessary to take the energy planning in urban planning as the breakthrough point to carry out research on green and low-carbon development and construction at the urban level in the " Carbon Reduction " era. First, a city in China was taken as the research object to evaluate the resource endowment and development potential of the target city. Then, the carbon reduction paths of target cities in the three fields of construction, transportation and industry were studied, and the carbon reduction potential in different scenarios was quantified. After that, the influence of electric power carbon emission coefficient on different carbon saving scenarios was studied through sensitivity analysis. Finally, the government's low-carbon urban planning and decision-making suggestions were given. The results show that the relatively effective way is to carry out large-scale promotion of ultra-low energy consumption buildings and electric vehicles on the demand side, and to build distributed photovoltaic and heat pump systems on the supply side. On this basis, with the introduction of additional 30% of foreign green power, the per capita carbon emissions of cities would be reduced to 1.5tCO2 in 2035. In this way, the target city can achieve the goal of carbon neutrality in advance. Therefore, the results of this study have certain theoretical reference value for the study of low-carbon urban planning.

Identifying impacts of industrial co-agglomeration on carbon emissions: Evidence from China.

Based on panel data of 285 cities in China at the prefecture level and above from 2005 to 2020, this paper aims to study the nexus between industrial co-agglomeration and carbon emissions from dual perspectives including space and time. It adopts multiple approaches including a dynamic general method of moment, panel quantile regression model, panel threshold model, and dynamic spatial Durbin model. The non-spatial empirical results support the establishment of the threshold effect and the imbalance effect. The spatial empirical results indicate that industrial co-agglomeration poses a dramatic stimulating effect on urban carbon emissions, and its spatial spillover effect and spatial heterogeneity are conditionally established. Furthermore, heterogeneous effects are supported, such as the positive spillover effects of industrial co-agglomeration are more significant in western cities, resource-oriented cities, and non-low-carbon pilot cities. The heterogeneous influence of cost factors on industrial agglomeration and carbon emissions has also been partially confirmed. In terms of the channels and mechanism of action, the negative externalities of industrial co-agglomeration occupy a dominant position in the current status of economic development. The dynamic equilibrium between government intervention and marketization is a solid foundation for the optimization of carbon emission reduction paths.

Temporal and Spatial Characteristics of Net CO2 Emissions and Decoupling Analysis in Yangtze River Economic Belt

Calculating the fossil energy consumption, revealing the temporal and spatial evolution characteristics of net CO2 emissions, and analyzing the decoupling effect between social development and net CO2 emissions in different regions of the Yangtze River Economic Belt (YREB) is crucial to support the different regions, allowing them to select their individual industrial development and carbon emission reduction path. The results showed that:① from 1999 to 2012, YREB became greener, the CO2 emission of the YREB increased by 2244.23 million tons, and the carbon sink increased by 148.07 million tons during the research period. ② From 2013 to 2018, the area of medium-high carbon sequestration (NPP>800 g·m-2, count for C) increased by 23.25%, compared with that from 1999-2012. ③ A highly decoupling effect between social development and net CO2 emissions was found in the downstream of the YREB. The highest decoupling cities in the upstream, midstream, and downstream accounted for 12%, 34%, and 54% of the highest decoupling cities in the YREB, respectively.

Direct molten-salt electro-reduction of CO2 in porous electrodes

Although the direct electro-reduction of CO2 is thermodynamically favorable, it is difficult to accomplish due to the limited solubility of CO2 in oxide-free molten salts. Thus, the electrochemical reduction of CO2 in molten carbonate should be assisted by the existing lithium and alkaline earth cations that alter the thermodynamic energy barrier of CO32−. In this study, we employ a porous metal foam electrode to realize the direct electro-reduction of CO2 in molten Na2CO3-K2CO3. The porous electrode increases the contact area between the solid electrode and CO2 gas, resulting in the direct electro-reduction of CO2 to CO and carbon through the thin electrolyte layer. The overall current efficiency reaches 90% for CO at 800 °C. The molten Na2CO3-K2CO3 makes the downstream product separation easy because Na2CO3 and K2CO3 are highly soluble in water. Overall, using the gas electrode achieves the direct electro-reduction of CO2 and the use of lithium- and alkaline-earth-metal-free molten carbonates, offering a more energy-efficient CO2 reduction path.

Carbon Emission Scenario Prediction and Peak Path Selection in China

Due to the emission of carbon dioxide and other greenhouse gases, the global climate is warming. As the world’s biggest emitter of carbon emissions, China faces a more severe challenge in reducing carbon emissions than developed countries. A reasonable prediction of the carbon peak in China will help the government to formulate effective emission reduction paths. This paper analyzes the changes in carbon emissions in China from 2004 to 2020, uses the STIRPAT model and scenario analysis method to predict carbon emissions from 2021 to 2030, and then calculates the carbon efficiency during carbon peaking to select the most effective carbon peak path for China. The results show that China’s carbon emissions increased year by year from 2004 to 2020. Under the baseline scenario, China is unlikely to reach its carbon peak before 2030. Under the regulatory scenarios, China can reach its carbon peak before 2030. The peak values from high to low are seen with the rapid development-weak carbon control scenario, rapid development-intensified carbon control scenario, slow development-weak carbon control scenario and slow development-intensified carbon control scenario, respectively. Correspondingly, China will peak its carbon emissions in 2029, 2028, 2028 and 2028, respectively, according to these scenarios. The carbon efficiency under the rapid development-weak carbon control scenario is the highest, which means that accelerating the growth rate of population, GDP and urbanization while moderately carrying out the transformation of industrial structure and energy structure is an effective way to achieve the goal of “carbon peak by 2030”.

A Strong Magnetic Field Alters the Activity and Selectivity of the CO2RR by Restraining C–C Coupling

As an external field, a magnetic field can change the electrocatalytic activity of catalysts through various effects. Among them, electron spin polarization on the catalyst surface has attracted much attention. Herein, we investigate the sensitive response behavior of a Cu2O nanocubes to an in situ magnetic field. Under a 3 T strong magnetic field, the total transferred electron quantity in IT test (−1.1 VRHE) and the current density in the polarization curve increase by 28.7% and 54.7%, respectively, while the onset potential decreases significantly by 114 mV. Moreover, it was found that product selectivity was also altered by the magnetic field. The Faraday efficiency of C1 increases substantially, along with the inhibition of C2+ reaction paths and the HER. Our experimental results and DFT calculation demonstrate that a hybrid magnetic effect accelerates the CO2RR kinetic and generates spin polarization of the catalyst surface. The polarized surface changes the binding energy of *OCHO/*COOH and inhibits singlet C–C coupling, which restrains the C2+ reduction path and thus more CO2 is reduced to HCOOH.

Interim Evaluation of Germany’s Sugar Reduction Strategy for Soft Drinks: Commitments versus Actual Trends in Sugar Content and Sugar Sales from Soft Drinks

Introduction: A high intake of sugar, in particular from sugar-sweetened soft drinks, increases the risk for obesity, type 2 diabetes mellitus, and dental caries. Germany has pursued a national strategy for sugar reduction in soft drinks based on voluntary commitments by industry since 2015, but its effects are unclear. Methods: We use aggregated annual sales data from Euromonitor International to assess trends in mean sales-weighted sugar content of soft drinks and per capita sugar sales from soft drinks in Germany from 2015 to 2021. We compare these trends to the reduction path set by Germany’s national sugar reduction strategy and to data for the United Kingdom, which adopted a soft drinks tax in 2017 and which we selected as best practice comparison country based on pre-defined criteria. Results: Between 2015 and 2021, the mean sales-weighted sugar content of soft drinks sold in Germany decreased by 2% from 5.3 to 5.2 g/100 mL, falling short of an interim 9% reduction target and a 29% reduction observed in the United Kingdom over the same period. Sugar sales from soft drinks in Germany decreased from 22.4 to 21.6 g/capita/day (−4%) between 2015 and 2021 but remain high from a public health perspective. Conclusions: Reductions observed under Germany’s sugar reduction strategy fall short of stated targets and trends observed internationally under best practice conditions. Additional policy measures may be needed to support sugar reduction in soft drinks in Germany.

Structurally designable Bi2S3/P-doped ZnO S-scheme photothermal metamaterial enhanced CO2 reduction

In this study, a novel 3D Bi2S3/P-ZnO S-scheme gyroid metamaterial was prepared by 3D printing and the hydrothermal method. The unique gyroid macrostructure and nanoarray microstructure offer a large volume of active sites for the photothermal catalytic reaction, thus improving the overall utilization rate of light. ZnO obtained by sintering the precursor produces oxygen vacancies, primarily due to P doping. This enables it to have a photothermal effect. After loading Bi2S3, the photothermal effect of P-ZnO and Bi2S3 is coupled, further increasing the surface temperature of composite structure and speeding up the reaction rate. P-ZnO and Bi2S3 formed a S-scheme heterojunction, promoting the separation and transfer of photogenerated carriers. Under simulated sunlight, the CO and CH4 yield of Bi2S3/P-ZnO S-scheme gyroid metamaterials are 8.87 and 1.49 μmol h−1. These are 3.45 times and 4.65 times of P-ZnO gyroid structure, respectively. Through SEM, TEM, XPS, ESR and in-situ FTIR characterizations, the transfer paths of photogenerated carriers between heterojunctions were revealed, and the reaction paths of photothermal catalytic CO2 reduction were explored. The co-design of 3D structure and material allows for a novel concept for further improving photothermal catalytic performance.