Development Of Green Technologies Research Articles

Robust reactive oxygen species production in interfacial reaction between organic acids and biochar: The combined effect of electron acceptance and electron conduction

Interfacial electron transport and reactive oxygen species (ROS) generation in the redox action between biochar (BC) and low-molecular-weight organic acids (LMWOAs) have been overlooked during the utilization of BC in soil amelioration/remediation. Herein, BC and N-doped BC (NBC) with various physicochemical properties were prepared at pyrolysis temperatures of 350, 550 and 750 °C (namely BC/NBC350, 550 and 750) and their interactions with LMWOAs were systematically investigated. Results of ROS quenching and electrochemical cell experiments revealed that BC/NBC could strongly interact with LMWOAs, especially ascorbic acid (AA), and acted as an electron shuttle to mediate one electron transfer from AA to oxygen to generate O2•−, followed by the robust generation of H2O2 and •OH. Interestingly, the generation rates of •OH and H2O2 in the NBC-AA system were significantly higher than that in the BC-AA system, of which the NBC550-AA system exhibited the best performance, enabling its superior ability in bisphenol A degradation. Different from conventional wisdom, the electron shuttle capacity depended on a combined aromatization degree and electron-accepting capacity of BC/NBC. These findings complement the interfacial electron transfer mechanism during the natural BC-LMWOAs interaction and provide new inspiration for the development of green and efficient organic pollutant removal technologies.

Sustainable Aspects of Startups among Generation Z—Motivations and Uncertainties among Students in Higher Educations

While technology is developing rapidly, natural resources are being exploited with more and more factories. Global environmental problems draw attention to the issue of sustainability as a warning sign. In this situation, encouraging the development of green innovative technologies and supporting green startups has become particularly important. Sustainable development is an important goal for every country, and it means a global competitive advantage if the given country supports the spread of green technologies. It is therefore the responsibility of leading politicians to create an enabling economic environment to encourage young people to become conscious, green-minded entrepreneurs. In this study, we delve into the driving factors compelling young individuals to venture into entrepreneurship. This exploration combines both quantitative and qualitative research methods. A cohort of 280 Hungarian university students participated in an online questionnaire survey as part of the quantitative segment, while the qualitative research component involved scrutinizing young people’s perspectives on enterprises and startups through focus group discussions. The research aims to unveil the motivations and primary concerns of Z-generation university students when contemplating entrepreneurship, as well as their perspectives on the significance of sustainability in this context. The outcomes of this study could serve as a catalyst for the establishment of more environmentally-conscious and sustainable businesses and startups.

Progress in Green and Low-carbon Technologies development of Building Ceramics Industry

As global and domestic concerns about climate change intensify, the development and adoption of green and low-carbon manufacturing technologies to effectively reduce resource consumption, energy usage, and greenhouse gas emissions have emerged as primary trends in the evolution of the building ceramics industry under the backdrop of the “dual carbon” strategy. This article systematically reviews the commercially applied and research-stage green and low-carbon technologies within the current building ceramics industry. It conducts a carbon emission reduction potential analysis for various technologies, identifies constraints in the technology promotion process, and highlights the substantial carbon reduction potential of clean energy substitution technologies and manufacturing process optimization technologies. Technologies such as raw material substitution, high-quality service, and waste ceramic tile recycling and regeneration contribute significantly to economic and environmental benefits, but are still in developmental stages. The article also discusses the application of methods such as life cycle assessment and carbon footprint analysis in the evaluation of green and low-carbon technologies in the field of building ceramics. It discusses the trends and limiting factors of different green and low-carbon technologies, offering suggestions and support for the building ceramics industry’s transition towards a low-carbon and environmentally friendly direction.

Separation Performance of Lithium and Calcium from Synthetic Geothermal Brine Using Electric Field-assisted Membrane

Green low-carbon technology development has spurred an increased demand for lithium. Brine, including geothermal brine, is the world’s largest source of lithium. However, the low lithium content and the presence of other ions pose challenges in concentrating lithium. An electric field-assisted membrane is a separation approach combining nanofiltration membranes with an electric field as an additional driving force, effectively separating lithium from magnesium and strontium. This study was conducted to separate lithium and calcium from synthetic geothermal brine using an electric field-assisted membrane. The separation process is conducted for lithium (50 ppm) and calcium (300, 800, and 2,000 ppm) with variations in electrical voltage (0V, 2V, and 3V). The decrease in lithium rejection reaches up to 50% at an electrical voltage of 2V. Conversely, the increase in electrical voltage does not significantly impact calcium rejection (calcium rejection remains at 89% with an electrical voltage of 3V) and the permeate flux for lithium and calcium. The increasing calcium concentration affects permeate flux significantly but does not notably affect calcium rejection, with the rejection remaining above 85%. The findings suggest the feasibility of concentrating lithium through electric field application without compromising calcium rejection within a single salt solution system.

Power allocation strategy for fuel cell distributed drive electric tractor based on adaptive multi-resolution analysis theory

Fuel cell distributed drive electric tractor (FCDET) provided a novel pathway for the development of green agricultural machinery technology. However, FCDET faced problems such as low traction efficiency, short endurance, and high hydrogen consumption. Relevant studies have shown that reasonable and effective power allocation strategy can improve the efficiency and reduce the energy consumption of fuel cell systems. In this paper, a drive power allocation strategy based on adaptive multi-resolution analysis theory (AMRA) was proposed. The strategy could realize effective decoupling between various energy sources, reduce the problems of frequent start-stop and large power fluctuation for fuel cells. We started with an equivalent circuit model of the fuel cell system, a total efficiency solution model, an energy dissipation model, and a drive motor response model. The first-time reconstruction strategy was based on Tunable Q-factor Wavelet Transform (TQWT) to obtain a subsequence that responds to the oscillatory characteristics of the power signal. The second-time reconstruction strategy took the low-frequency subsequence through Variational Mode Decomposition (VMD) into a number of discrete sub-signals with special sparse properties. Meanwhile, the Sparrow Search Algorithm (SSA) was used to obtain the optimal combined values of the modal decomposition layers and the quadratic penalty factor in the VMD on real time. Finally, the second-time decomposed subsequences and sub-signals were reconstructed according to the frequency characteristics, and the reconstructed power signals were redistributed among the individual energy sources. In order to validate the proposed power allocation strategy, we used the ET504-H prototype as a research object. The power information of plowing and transportation operating conditions was collected in Mengjin test base of China YTO Group. The MATLAB/Simulink-PXI joint simulation platform was set up and the driving motor bench test was carried out in the New Energy Key Laboratory of Henan Province. The results show that the AMRA-based FCDET drive power allocation strategy can effectively improve the energy utilization of the fuel cell system and the economy of the whole tractor operating unit. Compared to the power-following strategy under plowing and transportation conditions, the average efficiency of the fuel cell system was improved by 8.3 % and 3.3 %, the equivalent hydrogen consumption was reduced by 35.6 % and 43.89 %, respectively. The average efficiency of the drive motor was improved by 2.06 % and 2.08 %, the total energy consumption was reduced by 3.73 % and 2.6 %, respectively. This study can provide a theoretical foundation and a novel technical approach for the development of FCDET control system.

Dechlorination of wastewater from shell-based glucosamine processing by mangrove wetland-derived fungi.

Wastewater from processing crustacean shell features ultrahigh chloride content. Bioremediation of the wastewater is challenging due to the high chloride ion content, making it inhospitable for most microorganisms to survive and growth. In this study, mangrove wetland-derived fungi were first tested for their salt tolerance, and the highly tolerant isolates were cultured in shrimp processing wastewater and the chloride concentration was monitored. Notably, the filamentous fungal species Aspergillus piperis could remove over 70% of the chloride in the wastewater within 3 days, with the fastest biomass increase (2.01 times heavier) and chloride removal occurring between day one and two. The chloride ions were sequestered into the fungal cells. The genome of this fungal species contained Cl- conversion enzymes, which may have contributed to the ion removal. The fungal strain was found to be of low virulence in larval models and could serve as a starting point for further considerations in bioremediation of shell processing wastewater, promoting the development of green technology in the shell processing industry.

Has the Development of The Digital Economy Reduced the Growth Rate of Carbon Emissions?

Against the backdrop of the "30 · 60" dual carbon target, low-carbon development and the progress of the digital economy are the focus of attention at home and abroad. The digital economy has become an important driving force for high-quality economic development in China. This article studies panel data at the provincial level in China from 2011 to 2018, empirically testing the negative correlation between the development of the digital economy and the growth rate of carbon emissions, and verifying the mechanism effect of green technology innovation, Finally, the situation in the eastern, central, and western regions was discussed through sample analysis and robustness testing was conducted. Based on the above research conclusions, the following insights can be drawn: firstly, improve the speed and quality of digital economy development; Secondly, focus on the development of green innovative technologies.

Green hydrogen: A pathway to a sustainable energy future

The development of sustainable energy sources has become a major challenge for society. Green hydrogen, produced through the electrolysis of water using renewable energy sources, offers a potential solution to reducing our dependence on fossil fuels. The paper examines the integration of green hydrogen into various sectors, such as transportation, industry, power generation, and heating, highlighting its potential to decarbonize traditionally carbon-intensive areas. Furthermore, it analyses the strategies and policies employed by the European Union, Australia, Japan, the United States, and Canada to drive the development and adoption of green hydrogen technologies. The challenges and barriers that need to be addressed to fully realize the potential of green hydrogen, such as technological limitations, infrastructure development, costs and economic feasibility, regulatory and policy frameworks, and public perception and acceptance, have been investigated. Recommendations for overcoming these challenges and accelerating the adoption of green hydrogen technologies are provided, and the importance of research and development in this sector is emphasized.

Tracking and predicting technological knowledge interactions between artificial intelligence and wind power: Multimethod patent analysis

To track the dynamics of AI and wind power technology knowledge interaction and predict future interaction directions, this study proposes a multiview and multilayer patent analysis framework based on three data-driven methods: DMC co-occurrence networks, LDA, and link prediction. The framework is applied to collate and analyse patents related to wind power technologies using artificial intelligence from 2010 to 2021. We find that the number of AI and wind power technology knowledge interactions increases significantly over time, but the network is sparse overall and still has much room for improvement. Second, the AI and wind power technology knowledge interaction patterns show a shift from machine learning models (generation-side wind power technology) to deep learning models (generation-side and transmission- and distribution-side wind power technology) to hybrid AI models (generation, transmission, distribution, and power consumption in the whole process of wind power technology). Finally, possible future directions of interaction between AI and wind power are predicted. The proposed framework is expected to yield a new empirical perspective on green energy technology development. Additionally, the obtained results provide a comprehensive understanding of AI application research in wind power generation.

Analysis of the advantages and disadvantages of BIPV technology

As environmental problems such as the greenhouse effect and glacier melting become more and more serious, the society's awareness of environmental protection is becoming stronger and stronger, which makes the development of green buildings extremely important, and the development of many green building materials and environmental protection technologies is also increasing. more attention. In this article, BIPV (Building Integrated Photovoltaic) will be researched and its development discussed. BIPV is to reduce energy consumption through the effective use of solar energy. It is green, environmentally friendly and non-polluting. However, China started late in photovoltaics and lack of research in this area, which makes the application of BIPV technology in China still have high costs and lack of relevant building specification standards. This paper discusses the suggestions for the future development of BIPV technology, hoping to provide meager strength for the development of green buildings in China and provide direction for the future development of BIPV.

The Role of Green Energy Technologies Development, Carbon Finance, Carbon Tax and Economic Growth on Environmental Conditions in ASEAN Countries

Green technology and carbon finance have the potential to greatly add significance towards traditional financing practices related to carbon emissions because of information based nature, Thus, exploration of green technologies and carbon finance assist economies in the formulation of effective policies. By employing the panel data of ASEAN economies from 2011-2019, the study used CUP-FM and CUP-BC methods to empirically analyze the said relationship. The outcomes of the study revealed that green technologies, carbon finance, carbon taxes, economic growth decrease GHG emissions. It implies that the synergetic effect of green technologies, carbon finance, carbon tax and economic growth play an essential role in improving environmental conditions. Consequently, ASEAN region can reshape the policies by integrating green technologies and carbon finance and also looks into country’s local condition to improve the urban environmental efficiency, hence, achieving carbon neutralization goal.

Digitization, perception of policy uncertainty, and corporate green innovation: A study from China

A green economic transformation requires innovation in related technologies. The impact of digitalization on corporate green innovation must be investigated in the context of increasing policy uncertainty; therefore, this study uses data from listed manufacturing enterprises in China from 2011 to 2020, constructs a digitization and policy uncertainty perception index based on text analysis, and investigates corporate green technology innovation in light of digitization and policy uncertainty perception. The results indicate that digitization substantially and positively affects corporate green technology innovation, which raises its performance. An array of robustness tests, including instrumental variable methods, supports the conclusion that digitization enables green innovation. A Heterogeneity analysis also indicates that digitization has a pronounced impact on green technology innovation in large, capital-intensive, and state-owned enterprises. Frequent policy adjustment engenders an upsurge in policy uncertainty, which impedes corporate green technology innovation; however, digitization can play a vital role in alleviating the negative impacts of economic policy uncertainty, thereby accelerating the development of corporate green technologies. This article provides empirical evidence on achieving green and sustainable development in the digital era, making a valuable contribution to the existing literature.

Sustainable construction projects management in the AEC industry: analysis and visualization

Within the last decade, sustainable construction projects (SCPs) management has become a hot topic in the architecture, engineering, and construction (AEC) industry covering from building materials to the construction process. This study aims to systematically analyze literature concerning SCPs management between 2000 and October 2022 to improve the researchers’ overall understanding of SCPs management. From an objective analysis of co-occurrence keywords obtained by scientometric analysis, this study visualizes and conducts a detailed discussion about active studies and research trends. After discussing environmental, economic, and social sustainability indicators and their integration, the methods for improving SCPs management are summarized by a theoretical model. These methods include waste management, energy management, construction materials management, low-carbon management, green rating system, sustainable design, lean construction, knowledge management, capability building, value management, and implementation of new technology. Finally, future research directions are proposed, such as the social sustainability of different phases, the improvement of green rating systems, the development of green technologies, the collaboration of normative guidelines from different countries, and so on. This scientometric review explains the state-of-the-art research of SCPs management and encourages more interdisciplinary research involving relevant sustainability areas.

Ammonium Sulfite Slurry from Ammonia-Based Desulfurization Activates Water-Soluble Humic Substances from Lignite: Performance, Application, and Mechanism.

Both ammonium sulfite slurry (ASS) from ammonia-based desulfurization and lignite are waste materials with low value. In this work, an innovative method was developed by applying ASS in lignite activation to produce water-soluble humic substances (WHSs) with a high bioactivity and economic value. The optimal activation method was to mix lignite and ASS at a 4:1-liquid-solid ratio by vortex blender and then oscillate it for 30 min at 25 °C. Compared with that of the unactivated lignite (UAL), the yield of WHSs from activated lignite (AL) increased by 42.72%. WHSs from AL consisted of a large number of aliphatic carbons with low molecular weight and functional groups such as amides, amines, sulfonic acid groups, C-O, and so forth. Moreover, WHSs from AL at lower concentrations (2 mg/L) has a more obvious root-elongation-promoting effect than WHSs from UAL (10 mg/L). Activation experiment with the lignite-related model compounds revealed that ASS caused the breakage of Caliph-O, Caliph-Caliph, and Carom-Caliph linkages between aromatic rings. These findings provide a theoretical basis for the development of green and sustainable technologies for the beneficial reuse of ASS and lignite in agriculture.

Synergizing Machine Learning and the Aviation Sector in Lithium-Ion Battery Applications: A Review

Lithium-ion batteries, as a typical energy storage device, have broad application prospects. However, developing lithium-ion batteries with high energy density, high power density, long lifespan, and safety and reliability remains a huge challenge. Machine learning, as an emerging artificial intelligence technology, has successfully solved many problems in academic research on business, financial management, and high-dimensional complex problems. It has great potential for mining and revealing valuable information from experimental and theoretical datasets. Therefore, quantitative “structure function” correlations can be established to predict battery health status. Machine learning also shows significant advantages in strategy optimization such as energy optimization management strategy. For lithium-ion batteries, their performance and safety are closely related to the material structure, battery health, fault analysis, and diagnosis. This article reviews the application of machine learning in lithium-ion battery material research, battery health estimation, fault analysis, and diagnosis, and analyzes its application in aviation batteries in conjunction with the development of green aviation technology. By exploring the practical applications of machine learning algorithms and the advantages and disadvantages of different applications, this article summarizes and prospects the application of machine learning in lithium batteries, which is conducive to further understanding and development in this direction.

Financial performance-based assessment of companies’ competitiveness: Evidence from the Norwegian Shipbuilding Industry

The Norwegian maritime industry is at the forefront of green technology development, with shipyards playing a crucial role in testing, verification, and development. However, the industry faces challenges such as high personal costs, increasing competition from abroad, and cyclical market trends. This study aims to assess financial performance as indicator of firm-level competitiveness based on a set of 12 financial measures and test the hypothesis of the positive impact of portfolio diversification on shipyards’ competitiveness.The analysis utilizes data from four large construction yards and four medium-sized construction, repair, and maintenance yards in the Møre region. The methodology involves constructing a Shipyard Competitiveness Index with sub-indices for liquidity, profitability, solvency, and efficiency. Regression analysis is conducted to investigate the impact of ship variety, as a diversification parameter, on the competitiveness level.The obtained results reveal that during the analyzed period (2009–2020), companies in the group of large shipyards had better financial performance until 2017, while on the contrary, the second group of shipyards in the same period showed an increase in their competitiveness index. Moreover, the findings proved the presence of the positive relationship between diversification of portfolio and competitiveness index.This study contributes valuable insights for the Norwegian shipbuilding industry, highlighting the importance of financial performance assessment in measuring competitiveness. The study provides a foundation for future discussions on fostering sustainable growth and innovation within the maritime sector.

Green innovation and political embeddedness in China's heavily polluted industry: role of environmental disclosure, gender diversity, and enterprise growth.

Innovation in green technology is an efficient approach to reducing carbon emissions and achieving energy conservation, which is essential for fostering sustainable and green economic development. Even though the development of eco-friendly technologies is accelerating, the grasp of how political ties affect firms' adoption of green technologies remains hazy. This paper examines the effect of a firm's total political embeddedness (government ownership and political connections) along with the influencing mechanisms by employing a panel fixed effect regression approach on a dataset of Chinese A-share enterprises operating in pollution-intensive industries spanning 2012 to 2021. The findings offer conclusive evidence that political embeddedness encourages the enterprises' development of green technologies and boosts their output of innovation. In addition, mechanism analysis reveals that companies' political embedding influences their green innovation behavior through environmental disclosure. Moreover, board gender diversity and company growth rate are found to reinforce the impact of political embeddedness on green innovation. Besides expanding the current research on green innovation and corporate political involvement, the findings also provide important policy recommendations for the sustainable development of companies in emerging markets.

Green technology diversification, technology vertical spillovers, and energy intensity in Chinese cities

Drawing from patent data spanning 2011-2016 in 249 Chinese prefecture-level cities and urban scale multi-region input-output (MRIO) table data, this paper empirically demonstrates that as green technological diversification levels escalate, the energy intensity of Chinese prefecture-level cities exhibits an initial increase followed by a decline. Green technological diversification indirectly influences urban energy intensity through vertical spillovers of green technology across the upstream and downstream sectors within the supply chain. Medium-sized cities, service industry-oriented cities, and those in the early stages of industrialization need to prioritize development of multiple green technologies to surpass the diversification turning point. The finding suggests a strategic transition for Chinese cities from a single green technology agglomeration model to a cluster model of collaborative development of multiple green technologies.

Research and evaluation of spatiotemporal dynamic of network green innovation efficiency in China—based on meta-Frontier theory

Green innovation has emerged as a crucial driver for advancing green and high-quality development. Exploring the evolutionary patterns of green innovation efficiency is crucial for achieving the “dual carbon” goals and realizing the benefits of both economic growth and environmental sustainability under the framework of new development concepts. This study employs the network SBM-DEA model under meta-Frontier and group-Frontier. Additionally, it considers the GML index and Moran’s I to conduct a comprehensive analysis of the evolving efficiency of green innovation in Chinese provinces from 2008 to 2020, then uses the Tobit regression model to verify the influencing indicators for green innovation efficiency. The examination covers various aspects, including the stage of green innovation, the diversity of technology accumulation, the comparability of pre- and post-development, the spillover effects in geographical space, and the diversity of influencing factors. The research findings indicate the following: 1) The group division exhibit a high level of geographical correlation, and the efficiency of green innovation in the two-stage and network displays heterogeneity across distinct frontiers. The efficiency loss in the Green Achievement Transformation stage is bigger than that in the Green Technology Research and Development stage. 2) There is an overall increase in green innovation efficiency of each type during most years, and the spatial correlation and stability of the two-stage and network green innovation efficiency have improved year by year. Provinces with higher Green Innovation Environment Composite Index have the highest concentration of “high-high” efficiency agglomeration. 3) Environmental regulation intensity, factor endowment, property rights structure, foreign direct investment and energy consumption have varying degrees of constraints on green innovation, and the regional economic development level can significantly improve the efficiency of various green innovations. Finally, this paper provides some suggestions, including stimulating innovation vitality, formulating differentiated policies, strengthening regional innovation collaboration, and mobilizing resources from various stakeholders. These recommendations aim to provide guidance and reference for promoting green innovation and achieving sustainable development in different regions.

The Impact of Green Technology Research and Development (R&D) Investment on Performance: A Case Study of Listed Energy Companies in Beijing, China

The aim of this study is to investigate the relationship between green technology R&D investment and corporate performance (ROA) of 44 Beijing-listed energy companies from 2016 to 2021 using a threshold regression model. The results show that there is an inverse W-shaped nonlinear relationship between green technology R&D investment and firm performance. This means that green technology R&D investments only have a positive effect on firm performance within an appropriate green technology R&D investment interval, and a negative effect occurs outside this interval. Additionally, the study analyses the influence of three threshold variables (firm size, capital structure and capital density) on the relationship between green technology R&D investment and firm performance. The results show that firm size has an inversely- U-shaped relationship, the capital structure has a negative nonlinear relationship and the capital density has an inversely N-shaped relationship. Optimal intervals are observed for all three threshold variables. Moreover, the study shows that the green technology R&D investment intensity has a lagged effect on firm performance. The positive influence weakens over time, and the negative influence becomes more pronounced. The findings of the study can help energy companies to develop green technology R&D innovation strategies, such as differentiating green technology R&D expenditures for companies in different development situations. It can also exploit the driving effect of green technology R&D investment on firm performance in the context of China’s energy sector restructuring.