Search Results (25)

As the fundamental physical carrier for human production and socio-economic endeavors, enhancing urban land green use efficiency (ULGUE) is crucial for realizing sustainable development. To effectively enhance urban land green use efficiency, this study systematically examines the intrinsic relationship between industrial policies and ULGUE based on panel data from 286 Chinese cities (2010–2022), employing an integrated methodology that combines the Difference-in-Differences (DID) model, Super-Efficiency Slacks-Based Measure Data Envelopment Analysis model, and ArcGIS spatial analysis techniques. The findings clearly demonstrate that the establishment of the “Made in China 2025” pilot policy significantly improves urban land green use efficiency in pilot cities, a conclusion that endures following a succession of stringent evaluations. Moreover, studying its mechanisms suggests that the pilot policy primarily enhances urban land green use efficiency by promoting industrial upgrading, accelerating technological innovation, and strengthening environmental regulations. Heterogeneity analysis further indicates that the policy effects are more significant in urban areas characterized by high manufacturing agglomeration, non-provincial capital/non-municipal status, high industrial intelligence levels, and less sophisticated industrial structure. This research not only provides valuable policy insights for China to enhance urban land green use efficiency and promote high-quality regional sustainable development but also offers meaningful references for global efforts toward advancing urban sustainability. Full article

Power systems hold huge potential for emission reduction, which has made the modeling and pathway simulations of their decarbonizing development a subject of widespread interest. However, current studies have not yet provided a useful modeling method that can deliver analytical probabilistic information about future system behaviors by considering various uncertainty factors. Therefore, this paper proposes a stochastic process-based approach that can provide analytical solutions for the uncertainty ranges, as well as their changing momentum, accumulation, and probabilistic distributions. Quantitative probabilities of certain incidents in power systems can be deduced accordingly, without massive Monte Carlo simulations. A case study on China’s long-term coal-fired power phaseout was conducted to demonstrate the practical use of the proposed approach. By modeling the coal-fired power system at the unit level based on stochastic processes, phaseout pathways are probabilistically simulated with consideration of national power security. Simulations span from 2025 to 2060, presenting results and accumulated uncertainties for annual power amounts, full-process emissions, and carbon efficiencies. Through this modeling and simulation, the probabilities of China’s coal-fired power system achieving carbon peaking by 2030 and carbon neutrality by 2060 are 91.15% and 42.13%, respectively. It is expected that there will remain 442 GW of capacity with 0.18 Gt of carbon emissions in 2060. Full article

Characterized by frequent earthquakes and a dense population, Yunnan Province, China, faces significant seismic hazards and is a hot place for earthquake forecasting research. In a previous study, we evaluated the performance of the b value for 5-year seismic forecasting during 2000–2019 and made a forward prediction of M ≥ 5.0 earthquakes in 2020–2024. In this study, with the forecast period having passed, we first revisit the results and assess the forward prediction performance. Then, the background seismicity rate, which may also offer valuable long-term forecasting information, is incorporated into earthquake prediction for Yunnan Province. To assess the effectiveness of the prediction, the Molchan Error Diagram (MED), Probability Gain (PG), and Probability Difference (PD) are employed. Using a 25-year catalog, the spatial b value and background seismicity rate across five temporal windows are calculated, and 86 M ≥ 5.0 earthquakes as prediction samples are examined. The predictive performance of the background seismicity rate and b value is comprehensively tested and shown to be useful for 5-year forecasting in Yunnan. The performance of the b value exhibits a positive correlation with the predicted earthquake magnitude. The synergistic effect of combining these two predictors is also revealed. Finally, using the threshold corresponding to the maximum PD, we integrate the forecast information of background seismicity rates and the b value. A forward prediction is derived for the period from January 2025 to December 2029. This study can be helpful for disaster preparedness and risk management in Yunnan Province, China. Full article

As the main driving force of the new technological revolution, intelligent development is the key to promoting high-quality economic development. This paper empirically examines the nonlinear influence of intelligent development on green economy efficiency and its action paths using provincial panel data of China from 2009 to 2021. The result provides significant evidence of a U-shaped relationship between intelligent development and green economy efficiency, indicating that intelligent development initially leads to green economy efficiency decreases before ultimately increasing. Additional analysis confirms that environmental regulation, green finance, and industrial agglomeration positively moderate the impact of intelligent development on green economy efficiency. Furthermore, heterogeneous tests reveal that in the eastern region and after the release of “Made in China 2025” in 2015, the nonlinear effect of intelligent development on green economy efficiency is more pronounced. The findings of this paper provide a beneficial reference for how to leverage intelligent technology to release new kinetic energy for green economic growth under the new development concept. Full article

This study focused on the land use (LU) structure and carbon emissions (CEs) in the Jiangsu, Zhejiang, Anhui, and Shanghai provinces of the Yangtze River Delta (YRD) in China from 2000 to 2020, using the STIRPAT model and scenario analysis (SA). We conducted an analysis of the influence exerted by relevant factors on land use carbon emissions (LUCEs) and made forecasts regarding the diverse development scenarios of CE trends, aiming to provide methodological guidance for validating the effectiveness of existing policies in reducing CEs and offer direction for achieving the peak CO₂ emissions target as soon as possible. It also constitutes a significant reference for the early realization of the peak CO₂ emissions target. The results indicated the following: (1) Between 2000 and 2020, CEs resulting from LU in the YRD rose from 2.70 × 10⁸ t to 9.10 × 10⁸ t, marking an increase of 243.77%. In 2020, the built-up area was the predominant contributor to CEs, representing 99.15% of the overall carbon sources, whereas forests served as the main carbon sink, comprising 92.37% of the total carbon sinks (CSs) for that year. (2) For each percent increase in the parameters considered in this study, the corresponding increases in LU CO₂ emissions were estimated to be: 1.932% (population), 0.241% (GDP per capita), −0.141% (energy intensity), 0.043% (consumption structure), 1.045% (industrial structure), and 0.975% (urbanization). (3) According to the existing policy framework and development plans, the YRD is expected to achieve peaking carbon dioxide emissions by 2030. If energy conservation and carbon reduction strategies are implemented, this peak could be achieved as early as 2025. However, if economic growth continues to depend primarily on fossil fuel consumption, the region may not hit its carbon peak until 2035. (4) The low-carbon scenario, which considers the needs of social progress alongside the intensity of carbon emission reductions, represents the most effective development strategy for reaching a carbon peak in LU within the YRD. Effectively managing population size and facilitating the upgrading of industrial structures are key strategies to hasten the achievement of peaking carbon dioxide emissions in the region. Full article

With the rapid development of novel energy vehicles, power generation, photovoltaics, and other industries, power electronic devices have gained considerable attention. Insulated-gate bipolar transistors (IGBTs) have been widely used in those fields. With the emergence of intelligent manufacturing concepts such as Germany’s “Industry 4.0” and China’s “Made in China 2025”, conventional manufacturing which needs to be upgraded with higher efficiency and yield is rapidly pivoting toward digitalization and intelligence. The digital twin methodology has been extensively used in various industries for constructing virtual models of physical entities, facilitating real-time data interconnection to reduce costs and improve efficiency. This study proposes a modular intelligent IGBT production line based on the digital twin. Real-time data are transmitted from a physical line to a digital line for storage and analysis. The digital line is visualized, and an intelligent management platform containing multiple functions is developed. Additionally, a process simulation database is established to obtain the optimal process parameters. Numerous quality issues that can arise during each process of IGBT packaging are addressed using a problem-solving approach based on the digital twin methodology. Consequently, this digital-twin-based IGBT intelligent production line effectively enhances yield rates and efficiency. IGBT modules with various packaging forms such as ACF, ACE, and ACD are manufactured. Full article

The climate and ecological problems caused by excessive carbon dioxide emissions are attracting more and more attention, and the need for carbon reduction has reached a consensus. Carbon peak and carbon neutrality is a solemn commitment made by China to the world and a strategic arrangement to achieve economic and social transformation. This study focused on Shanxi Province, a base of power source and heavy chemical industry in China. Based on energy consumption data, carbon emission data set at the county level, land use data and socioeconomic data, we built a carbon ecological pressure index in order to analyze the spatiotemporal evolution characteristics of the carbon footprint, carbon carrying capacity and carbon ecological security status of each county in Shanxi Province from 2000 to 2020. The results showed that: (1) the total carbon footprint of Shanxi Province increased, and the number of high carbon emission counties showed an increasing trend. The largest part of carbon footprint was coal. (2) The vegetation carbon-carrying capacity showed an increasing trend in general, and forest land was the main contributor to the carbon-carrying capacity. (3) The carbon deficit of Shanxi Province was greater than 0 and behaved as a carbon source. The carbon ecological security decreased from a relatively safe level to a general safe level. (4) The carbon ecological pressure index gradually increased. It was predicted that the carbon ecological security level of each county will remain basically unchanged by 2025 and some will still be at a carbon ecological insecurity level. In general, the carbon ecological pressure index of some counties was still large. It is necessary to strengthen the use of clean energy, optimize the industrial structure and increase the carbon sink of forest land in order to reduce carbon emissions and increase the carbon sink, so as to ensure carbon ecological security and realize the goal of a low-carbon economy. Full article

China is the largest producer and exporter of coke globally, which means that it is very important to understand the characteristics of air pollutants and carbon emissions from China’s independent coking industry. This study was the first to establish a bottom-up inventory of the air pollutants and carbon emissions of China’s independent coking industry during 2001–2018 based on continuous emission monitoring system online monitoring data and unit-based corporate information. Based on the developed emission inventory, four scenarios were established to analyze potential emissions reduction of air pollutants and carbon dioxide (CO₂) in future. The emissions of particulate matter (PM₁₀ and PM_2.5), sulfur dioxide (SO₂), black carbon (BC) and organic carbon (OC) decreased by 62.11%, 63.41%, 72.85%, 63.41% and 63.41%, respectively. CO₂, carbon monoxide (CO), volatile organic compounds (VOCs) and nitrogen oxides (NO_X) emissions increased by 355.51%, 355.51%, 355.51% and 99.74%, respectively. In 2018, PM₁₀, PM_2.5, SO₂, NOx, BC, OC, CO, VOCs and CO₂ emissions were, respectively. 45.20, 16.91, 63.84, 117.71, 5.07, 5.92, 554.91, 1026.58 Gg, and 176.88 Tg. Shanxi province made the greatest contributions to the total emissions of air pollutants and CO₂ from this industry by 25.01%. The emission source that contributed most to PM_2.5 (SO₂ and NO_X) emissions was coke pushing (quenching and the coke oven chimney respectively) in 2018. Under the ULE scenario (2018–2035), PM_2.5 and SO₂ emissions will reduce by more than 30%. Under the PCP scenario, PM_2.5 and SO₂ emissions will reduce by more than 55%. Under the CBP scenario, CO₂ emissions will peak at 197.99 Tg in 2025 and decrease to 70% of the peak in 2035. The results showed the emission characteristics of air pollutants and CO₂, future emission with several scenarios and cooperative reduction potential in China’s independent coking industry, which provides scientific support for the development of pollution control strategies. Full article

China aims to achieve a 50% rate of mechanization for aquaculture by 2025. Aerators are crucial mechanical equipment in aquaculture for increasing yield, but their manufacturing has an environmental impact. Improving the yield and controlling the environmental impacts of aerators in China is an important issue have to be considered, as is comparing the environmental impact of manufacturing innovative and conventional aerators. Herein, life cycle assessment (LCA) as a quantitative analysis method was used, and six models of three widely used aerators (impeller, paddle wheel, and wave) were selected as an example to compare the environmental impacts of conventional and innovative aerators from large-scale aerator manufacturing enterprises in Taizhou, China. The results showed that the conventional paddle wheel aerator (SC-1.5) had the largest environmental impact, while the innovative paddle wheel aerator (GSC-1.5) had the lowest environmental impact, reduced by 30%. In addition, the environmental impact of the innovative impeller aerator (SYL-1.5) and wave aerator (GYL-1.5) was less than that of the conventional impeller aerator (YL-1.5) wave aerator (SW-1.5), but only by 0.21% and 0.02%, respectively. Human toxic potential (HTP) made the largest contribution, and the manufacturing of copper wire was critical; the environmental impact was from 96.50% to 98.21% for all material inputs. The contributions of iron and stainless steel were 1.05–1.28% and 0.74–1.04%, respectively. Therefore, conductive materials with excellent environmental performance, such as carbon nanomaterials and nano copper wire, should replace copper wire in aerator manufacturing. The results expand aquaculture life cycle knowledge and could reduce the environmental impacts of aerator manufacturing in China. Full article

China’s goal of reaching peak carbon by 2030 and carbon neutrality by 2060 has been a popular research topic in recent years. Carbon peaking and carbon neutrality goals are solemn commitments made by the Chinese government to the international community. As a national ecological civilization demonstration area, Fujian province has incorporated peak carbon and carbon neutrality into its overall ecological construction plans. This paper uses the scalable stochastic environmental impact assessment model STIRPAT to quantitatively analyze the relationship between carbon emission intensity and economy, population, energy intensity, energy structure, and industrial structure in Fujian Province from 2001 to 2020, and it uses a Markov transition matrix to predict the ratio of energy structure in the next four years. On the basis of the above-mentioned research, combined with the provincial ecological planning outlined in the 14th Five-Year Plan of Fujian Province, three development modes (i.e., the general mode, the energy-saving mode, and the energy consumption mode) are proposed. Finally, according to the model, this paper predicts that the carbon intensity goal of 2025 can be achieved under the general and energy saving modes, while the carbon intensity goal cannot be reached under the energy consumption mode. Full article

The optimization of the ecological network structure in Nanping can provide a scientific reference for guaranteeing ecological safety in Southeast China. This study estimated ecosystem services in Nanping with the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model based on land-use data from 2020 to 2025 simulated with the CLUE-S model under the natural development scenario and ecological protection scenario and then explored their trade-offs and synergies. The ecological network structure was, thereafter, optimized in terms of the eco-matrix, eco-corridors and nodes based on simulated land use and ecosystem services. The results suggested that the average habitat quality and total soil retention increased, while the average degradation index and total water yield decreased under the ecological protection scenario, indicating that the ecological environment quality tended to be improved. In addition, soil retention had significant synergies with habitat quality and water yield, and habitat quality had significant trade-offs with ecological degradation and water yield on the regional scale under two scenarios, while ecological degradation also showed significant trade-offs with soil retention and water yield. In addition, the results suggested that 11 additional ecological sources could be added, and the number of eco-corridors increased from 15 to 136; a total of 1019 ecological break points were restored, and 1481 stepping stone patches were deployed, which jointly made network circuitry, edge/node ratio and network connectivity reach 0.45, 1.86 and 0.64, respectively, indicating that optimization could effectively improve the structure and connectivity of the ecological network. These findings can provide a theoretical basis for improving the ecological network structure and ecological service functions in Nanping and other regions. Full article

The Chinese government has made great efforts to combat air pollution through the reductions in SO₂, NOx and VOCs emissions, as part of its socioeconomic Five-Year Plans (FYPs). China aims to further reduce the emissions of VOCs and NOx by 10% in its upcoming 14th FYP (2021–2025). Here, we used a regional chemical transport model (e.g., WRF/CMAQ) to examine the responses of PM_2.5 and O₃ to emission control policies of the 14th FYP in the Yangtze River Delta (YRD) region. The simulation results under the 4 emission control scenarios in the 2 winter months in 2025 indicate that the average concentrations of city mean PM_2.5 in 41 cities in the YRD were predicted to only decrease by 10% under both S1 and S1_E scenarios, whereas the enhanced emission control scenarios (i.e., S2_E and S3_E) could reduce PM_2.5 in each city by more than 20%. The model simulation results for O₃ in the 3 summer months in 2025 show that the O₃ responses to the emission controls under the S1 and S1_E scenarios show different control effects on O₃ concentrations in the YRD with the increase and decrease effects, respectively. The study found that both enhanced emission control scenarios (S2_E and S3_E) could decrease O₃ in each city by more than 20% with more reductions in O₃ under the S3_E emission control scenario because of its higher control strengths for both NOx and VOCs emissions. It was found that emission reduction policies for controlling high emission sectors of NO_x and VOCs such as S2_E and S3_E were more effective for decreasing both PM_2.5 and O₃ in the YRD. This study shows that O₃ controls will benefit from well-designed air pollution control strategies for reasonable control ratios of NOx and VOCs emissions. Full article

The rapid development of urbanization, population growth, and unreasonable use of land resources have made the contradiction between human beings and land increasingly prominent, and the carrying capacity of land resources has become an important factor affecting the sustainable development of a city or even a country. Based on the carrying capacity of agricultural land, construction land, and ecological land in 31 provinces of China, this paper analyzed the spatiotemporal characteristics of the carrying capacity of land resources in 31 provinces of China from 2008 to 2016 by using single-factor carrying capacity evaluation and comprehensive carrying capacity evaluation methods. The evaluation results were divided into six levels (No pressure, Lower pressure, Low pressure, Medium pressure, High pressure, Higher pressure), and the ArcGIS10.2 software was used for visualization, and the carrying capacity prediction model was constructed to predict the development trend of the comprehensive carrying capacity of land resources in 2020 and 2025. The results showed that China’s land carrying capacity is extremely unbalanced. Whether from the evaluation results of single-factor carrying capacity or comprehensive carrying capacity, we showed the characteristics of high pressure in the east and low pressure in the west, and that the regional land resources have a deteriorating trend. Through the prediction of the future land resource carrying capacity index, it was found that the comprehensive carrying capacity index of land resources in 31 provinces of China will still show an upward trend in the future. Full article

Digitalization is rushing throughout the world, namely, in industrial and societal infrastructures. Hence, digital transformation becomes a pillar of industrial policy, known in Europe as “Industry 4.0,” in China as “made in China 2025,” in Asia as “Smart Cities,” in Japan as “Society 5.0,” and in North America as “Industrial Internet.” These transformations will change the industrial landscape, toward Quality 4.0 and therefore, our lives. The presented research was conducted on quality management employees in Portugal and it aims to analyze if such employees have the perception of the impact of Industry 4.0 in the quality management profession and the required and needed skills. After analyzing the answered questionnaires, 90 results were considered valid. This is the sample of our study. Simultaneously, the goal of this research is also to review and analyze the main topics in progress related to quality management for the fourth industrial revolution and how quality emerges of this change. The professionals that work on quality management must have creative thinking, be leaders, know how to communicate and work as a team, as well as, to have knowledge and understanding of ICT (Information and Communications Technology), and main pillars of Industry 4.0. These are the main findings. Besides that, they must know how to motivate their work teams, be open to change, know how to use Big Data to make decisions and above all, they must know how to manage conflicts. In addition, quality professionals must promote the design and production of first class products, be the defenders of their customers within the organization, and finally, they must create value for the stakeholders. Full article

Predicting and allocating water resources have become important tasks in water resource management. System dynamics and optimal planning models are widely applied to solve individual problems, but are seldom combined in studies. In this work, we developed a framework involving a system dynamics-multiple objective optimization (SD-MOO) model, which integrated the functions of simulation, policy control, and water allocation, and applied it to a case study of water management in Jiaxing, China to demonstrate the modeling. The predicted results of the case study showed that water shortage would not occur at a high-inflow level during 2018–2035 but would appear at mid- and low-inflow levels in 2025 and 2022, respectively. After we made dynamic adjustments to water use efficiency, economic growth, population growth, and water resource utilization, the predicted water shortage rates decreased by approximately 69–70% at the mid- and low-inflow levels in 2025 and 2035 compared to the scenarios without any adjustment strategies. Water allocation schemes obtained from the “prediction + dynamic regulation + optimization” framework were competitive in terms of social, economic and environmental benefits and flexibly satisfied the water demands. The case study demonstrated that the SD-MOO model framework could be an effective tool in achieving sustainable water resource management. Full article