Research on the Impact of China’s Foreign Trade Technology Spillover on Green Total Factor Productivity of Countries Along the“Belt and Road”:Based on the Institutional Quality Threshold Effect

China’s growing trade with countries along the“Belt and Road”Initiative is accompanied by a focus on green development.Based on the panel data from 2007 to 2018,this paper establishes a threshold regression model to empirically analyze the institutional quality threshold effect of China’s foreign trade technology spillover on the GTFP of countries along the“Belt and Road.”The results show that China’s foreign trade technology spillover has a significant institutional quality double threshold effect on the green total factor productivity of the countries along the“Belt and Road.”As the institutional quality of the countries along the“Belt and Road”crosses a specific threshold value,the impact of China’s foreign trade technology spillover on the green total factor productivity of the countries along the“Belt and Road”has a significant positive promoting effect,and corresponding suggestions are put forward.

Does innovative city pilot policy promote urban green growth in China?An analysis of green total factor productivity,2005-2020

The innovative city pilot policy(ICPP)is an essential manifestation of China’s construction of an innovative and green-driven development country.We incorporated urban green total factor productivity(GTFP)growth into the evaluation of ICPP.Based on the panel data of 223 cities in China from 2005 to 2020,we used the difference-in-differences model to empirically assess the influence and mechanism of the ICPP on urban GTFP growth.The main results show that(i)The ICPP has maintained an effectively fluctuating promotion on urban GTFP growth,mainly manifested in the urban green technological progress improvement.(ii)The ICPP has urban heterogeneity in promoting GTFP growth in pilot cities,mainly affecting key cities such as provincial capitals.(iii)The interaction between the agglomeration of producer services and the ICPP inhibits GTFP growth in pilot cities.

Empirical Analysis of the Impact of Green Finance and Technological Progress on Total Factor Productivity in China’s Industrial Sector

The enhancement of industrial green total factor productivity is pivotal for achieving high-quality and sustainable economic development.This study assesses China’s performance using the SBM-GML model,employing province-level panel data spanning from 2004 to 2020.Furthermore,we examine the influence of green finance and technological progress on industrial green total factor productivity using a spatial econometric model.The findings uncover that the relationship between the level of green financial development and industrial green total factor productivity follows a U-shaped curve.Initially,low levels of green financial development exert a suppressive effect on industrial green total factor productivity,proving ineffective in the short term.However,with the progression of green finance development,a positive and significant long-term impact on industrial green total factor productivity emerges.Moreover,technological progress demonstrates a noteworthy promotional effect on industrial green total factor productivity.The analysis delves deeper into revealing that industrial structure and environmental regulation intensity exhibit a significant negative relationship with industrial green total factor productivity.In contrast,both energy structure and education level showcase a substantial positive relationship with industrial green total factor productivity.

Establishment of Regional Green Innovation Value Chains:A Case Study on Tackling the Impeded Diffusion of Green Products

The green innovation value chain is a key step in transforming green,innovative scientific,and technological achievements into productive forces.The establishment of green innovation value chains based on value distribution rather than technical conditions can effectively overcome the common bottleneck faced by different nations during their green innovation endeavors,namely,the substitution of conventional products with green alternatives.This study investigates the impeded diffusion of green products and their underlying causes,analyzes the internal structure and mechanism of the green innovation value chain,and explores the establishment of regional green innovation value chains and the models available for value chain upgrading.

Dynamic changes and convergence of China's regional green productivity:A dynamic spatial econometric analysis

Low-carbon economic development is at the heart of the post-pandemic green recovery scheme worldwide.It requires economic recovery without compromising on the environment,implying a critical role that green productivity plays in achieving the carbon neutrality goal.Green productivity measures the quality of economic growth with consideration for energy consumption and environmental pollution.This study employs the slacks-based measure directional distance function(SBM-DDF)approach and the Malmquist-Luenberger(ML)index to calculate green productivity and its components of 30 provinces in China between 2001 and 2018.Using a spatial panel data model,we empirically analyzed the conditionalβ-convergence of China's green productivity.We found that overall,since 2001,China's green productivity has demonstrated a continuous upward trend.When taking into account spatial factors,China's green productivity demonstrates a significant conditionalβ-convergence.In terms of regional effects,the results indicate that the green productivity of the eastern and western regions demonstrates club convergence,implying a more balanced green economic development.Moreover,the convergence rate of China's green productivity increases with the addition of environmental regulation variable,and so the corresponding convergence time decreases.It indicates that environmental regulations help to facilitate the convergence of China's green productivity,narrowing the gap between the regional green economic development.The findings provide guideline for achieving a low-carbon development and carbon neutrality from a regional green productivity perspective.

How do green product exports affect carbon emissions?Evidence from China

Green development has become an increasingly important global initiative.Therefore,this study focuses on the impact of green product exports on carbon emissions in China.Firm-level datasets are used to estimate provincial green product exports between 2001-2016.This study estimates the impact of green exports on carbon emissions using the system generalized method of moments methodology.In addition,heterogeneity and asymmetry of the nexus are explored.The following findings are highlighted:(1)China’s green product exports show a significant upward trend during the study period;(2)increased green product exports,especially those of high-technology manufacturers,can effectively mitigate CO_(2) emissions;(3)the influence of green product exports on carbon emissions is regional heterogeneous but consistent across quantiles;and(4)technique and scale effects are significant mediators,whereas the composition effect is not.These findings provide new evidence supporting methods to mitigate China’s CO_(2) emissions by adjusting green product export structures.

A Solar Energy System Design for Green Hydrogen Production in South-Western Nigeria, Lagos State, Using HOMER & ASPEN

Solar system design for green hydrogen production has become the most prominent renewable energy research area, and this has also actively fueled the desire to achieve net-zero emissions. Hydrogen is a promising energy carrier because it possesses more energy capacity than fossil fuels and the abundant nature of renewable energy systems can be utilized for green hydrogen production. However, the design of an optimized electrical energy system required for hydrogen production is crucial. Solar energy is indeed beneficial for green hydrogen production and this research designed, discussed, and provided high-level research on HOMER design for green hydrogen production and deployed the energy requirement with ASPEN Plus to optimize the energy system, while also incorporating fuzzy logic and PID control approaches. In addition, a promising technology with a high potential for renewable hydrogen energy is the proton exchange membrane (PEM) electrolyzer. Since its cathode (hydrogen electrode) may be operated over a wide range of pressure, a control process must be added to the system in order for it to work dynamically efficiently. This system can be characterized as an analogous circuit that consists of a resistor, capacitor, and reversible voltage. As a result, this research work also explores the Fuzzy-PID control of the PEM electrolysis system. Both the PID and Fuzzy Logic control systems were simulated using the control simulation program Matlab R2018a, which makes use of Matlab script files and the Simulink environment. Based on the circuit diagram, a transfer function that represents the mathematical model of the plant was created, and the PEM electrolysis control system is determined to be highly significant and applicable to the two control systems. The PI controller, however, has a 30.8% overshoot deficit, but when the fuzzy control system is compared to the PID controller, it is found that the fuzzy control system achieves stability more quickly, demonstrating its benefit over PID.

Towards high-performance and robust anion exchange membranes(AEMs)for water electrolysis:Super-acid-catalyzed synthesis of AEMs

The increasing demand for hydrogen energy to address environmental issues and achieve carbon neutrality has elevated interest in green hydrogen production,which does not rely on fossil fuels.Among various hydrogen production technologies,anion exchange membrane water electrolyzer(AEMWE)has emerged as a next-generation technology known for its high hydrogen production efficiency and its ability to use non-metal catalysts.However,this technology faces significant challenges,particularly in terms of the membrane durability and low ionic conductivity.To address these challenges,research efforts have focused on developing membranes with a new backbone structure and anion exchange groups to enhance durability and ionic conductivity.Notably,the super-acid-catalyzed condensation(SACC)synthesis method stands out due to its user convenience,the ability to create high molecular weight(MW)polymers,and the use of oxygen-tolerant organic catalysts.Although the synthesis of anion exchange membranes(AEMs)using the SACC method began in 2015,and despite growing interest in this synthesis approach,there remains a scarcity of review papers focusing on AEMs synthesized using the SACC method.The review covers the basics of SACC synthesis,presents various polymers synthesized using this method,and summarizes the development of these polymers,particularly their building blocks including aryl,ketone,and anion exchange groups.We systematically describe the effects of changes in the molecular structure of each polymer component,conducted by various research groups,on the mechanical properties,conductivity,and operational stability of the membrane.This review will provide insights into the development of AEMs with superior performance and operational stability suitable for water electrolysis applications.

Do smart city policies improve energy efficiency?Evidence from China

To address air pollution and offer a convenient and comfortable living environment,the Chinese government launched a smart city pilot(SCP)project in 2012,accompanied by a comprehensive set of environmental and energy-related laws and regulations.Although academic interest in smart cities has surged,there remains a notable gap in empirical research exploring the economic,environmental,and energy effects of such initiatives.Taking 232 prefecture-level cities from 2003 to 2017 as research subjects,this study measures energy effi‐ciency by using energy consumption per unit of GDP and adopts a difference-in-differences(DID)analysis to investigate the impact of SCPs on energy efficiency.The empirical results indicate that SCPs improved energy efficiency by promoting urban technological innovation capabilities and green total factor productivity,and this effect was more pronounced in cities that were more dependent on traditional fossil fuel energy sources and had more developed fiscal and financial levels.Studying the impact of smart city construction on energy utilization efficiency in developing countries,such as China,is not only significantly enlightening for China’s green and low-carbon transition but also provides reference opinions for constructing smart cities and the path to enhancing energy efficiency in other developing countries.The findings provide valuable insights into the global development of smart cities,urban sustainability,and high-quality economic growth.

Technological innovation paths toward green industry in China

With the environmental carrying capacity reaching its limits and the decreasing margin benefits of traditional production factors, the green transformation and green development through technological innovations has been a major direction for the future development of Chinese industries. However, the characteristics and heterogeneities of various types of industries call for different approaches regarding technological innovations. How to choose the most effective mode of technological innovation according to the characteristics of a certain industry has been a key issue. This paper measures the green total factor productivity of 32 industrial trades using the Slacks Based Measure(SBM)-DDF method. The effects of three innovation modes in the green transformation of industrial industry, including the independent innovation(Ⅱ), the technology introduction(TI), and the government support(GS), are empirically analyzed based on industry heterogeneity. Results indicate that the green total factor productivities of different industries show significant differences if taking into account the energy input and the undesirable output of pollutant emissions. The green total factor productivities of traditional high input,high pollution, and high energy consumption industrial trades were significantly lower than those with obvious green features. The year of 2009 is a leap year for the industrial green transformation in China. For resource-intensive industries, the II and the GS are the important ways to achieve green transformation. For labor-intensive industries, the TI is the best path to achieve green transformation, while for technology-intensive industries, the II is the primary driving force for the promotion of green developments. In addition, the innovation-compensating effect of the current Chinese environmental regulations to the resource-intensive industries has been revealed. Improving the overall scale and the industrial concentration of the industries is also beneficial for the green transformation of the industries.

Quantitative evaluation of the green production and consumption policies in China

Dual control of energy consumption is an effective method proposed in China to launch and deepen the transition in energy use.It has obtained favorable results;however,the resource consumption and pollution emissions per unit of Gross Domestic Product(GDP)remain high.This article quantitatively studies the current policies’effects to promote the advancement of dual control of energy consumption and develop future policies.Green production and consumption policies promote the development of dual control of energy consumption;therefore,this paper examines these policies through text mining and a quantitative evaluation system.The results suggest strong state demand for developing green production and consumption and the necessity for scientific evaluation;however,the state’s focus on the relevant policy tools is imbalanced.Constraint policy tools have the highest proportion of restricting pollutant emissions but lack comprehensiveness.Incentive and guidance policy tools have the problems of poor targets and low volume.Additionally,by constructing policy modeling consistency(PMC)index models for evaluating green production and consumption policies,six selected policies indicate solid performance,but some still have problems regarding policy timeframe,policy function,and green process.Based on the conclusions,this paper provides some targeted recommendations.

Industrial Green Spatial Pattern Evolution of Yangtze River Economic Belt in China

We use the directional slacks-based measure of efficiency and inverse distance weighting method to analyze the spatial pattern evolution of the industrial green total factor productivity of 108 cities in the Yangtze River Economic Belt in 2003–2013.Results show that both the subprime mortgage crisis and ‘the new normal' had significant negative effects on productivity growth,leading to the different spatial patterns between 2003–2008 and 2009–2013.Before 2008,green poles had gathered around some capital cities and formed a tripartite pattern,which was a typical core-periphery pattern.Due to a combination of the polarization and the diffusion effects,capital cities became the growth poles and ‘core' regions,while surrounding areas became the ‘periphery'.This was mainly caused by the innate advantage of capital cities and ‘the rise of central China' strategy.After 2008,the tripartite pattern changed to a multi-poles pattern where green poles continuously and densely spread in the midstream and downstream areas.This is due to the regional difference in the leading effect of green poles.The leading effect of green poles in midstream and downstream areas has changed from polarization to diffusion,while the polarization effect still leads in the upstream area.

Counteraction of Nogo-A and axonal growth inhibitors by green tea polyphenols and other natural products

Neuronal injuries such as stroke,traumatic brain injury,and spinal cord injury are leading causes of major disability and death.Chronic therapy for these neuronal injuries requires the promotion of axonal regeneration from the remaining neurons（Schwab and Strittmatter,2014）.

Impact of country-of-origin image of Guizhou province on brand trust of green agricultural products

Brand building of agricultural products is the key for agricultural enterprises to gain competitive advantage and occupy the market. Guizhou province is rich in green agricultural products resources and has superior natural resources, but it is at a disadvantage in the market competition. The constraint factor is that the brand is not enough to obtain consumer trust. In order to provide countermeasures and suggestions for Guizhou provincial government and agricultural enterprises to shape green agricultural products brand, this paper explores the influence path of country-of-origin image of Guizhou province on brand trust of green agricultural products. Therefore, based on the theory of Country-of-origin effects this study conducts an empirical research. Taking the country-of-origin image, including natural conditions,technological conditions, brand supervision norms, technology input, government marketing promotion and government policies as antecedent variables, and green agricultural brand trust, including brand competence trust and brand quality trust as dependent variables, the structural equation model was constructed. Through data collection and empirical analysis by using structural equation model, this study found that natural conditions have a positive impact on brand competence trust, and technical conditions have a positive impact on brand quality trust. The brand supervision norms, technology input, government marketing promotion and government policy will all promote consumers to have a positive impact on brand trust in green agricultural products.

Rapid determination of production date for green tea by near-infrared spectroscopy

Coupled with partial least squares(PLS),near infrared(NIR)spectroscopy was applied to develop a fast and nondestructive method to identify the production date of Rizhao green tea aiming at the deficiencies of the existing methods.In the modeling process,the raw spectra were first processed by five-point smoothing and first derivative.And then,moving window back propagation artificial neural network(MW-BP-ANN)was applied to select the characteristic spectral variables.After that,the calibration model was built by PLS,and the optimum model was achieved when 9 principal component scores(PCs)were included.The performances of the calibration models were evaluated according to root mean square error of predictionεRMSEP,correlation coefficient(C p)and residual prediction deviation(σRPD).The optimum results of the calibration model was achieved,andεRMSEP=19.965,C p=0.943 andσRPD=3.07.The overall results sufficiently demonstrate that NIR spectroscopy combined with PLS can be efficiently applied in the rapid identification of green tea production date.

A Cost-benefit Measuring Model of Green Products in Manufacturing Industry

The paper builds up a cost-benefit measuring model of green products in manufacturing industry throughout its full life cycle, which can quantify green products＇ cost and benefit completely and correctly under the circumstance of satisfying enterprise, customer, environment and society. It also puts forth an operable method to estimate social benefit by opportunity cost and establishes a profit maximization-programming model. The model can be applied to justify whether some kinds of green products should be developed and produced.

The Application of Multi-level Fuzzy Judgement in the Appraisement of Green Products

The appraisement of "the green level" for a green product is a problem that has to deal with multi aspects and multi stratification. According to the property of the items that affect "the green level" of the product, they can be divided into aspects, elements and factors. These make appreciable grades. Multi level fuzzy judgement can solve the appraisement problem that considers the influences of design, manufacture, use and recovery in all life cycle or multi life cycle of a product. In the judging process it not only deals with the action of all factors, but also continues to have all messages in grade judgement. The power coefficients stand out as the main items. An example is given to show the judgement process.

The Application of Multi-level Fuzzy Judgement in the Appraisement of Green Products

The appraisement of "the green level" for a green p ro duct is a problem that has to deal with multi-aspect and multi-stratification. According to the property of the items that affect "the green level" of the pro duct, they can be divided into aspects, elements and factors. These make appreci able grades. The multi-level fuzzy judgement can solve the appraisement problem that considers the influences of design, manufacture, use and recovery in all- life cycle or multi-life cycle of product. In the judging process it is not onl y deal with the action of all factors, but also continue to have all messages in grade judgement. The power coefficients stand out as the main items. An example is given to show the judgement process.

Novel closed-cycle reaction mode for totally green production of Cu_(1.8)Se nanoparticles based on laser-generated Se colloidal solution

Non-stoichiometric copper selenide(Cu_(2-x)Se,x=0.18~0.25)nanomaterials have attracted extensive attentions due to their excellent thermoelectric,optoelectronic and photocatalytic performances.However,efficient production of Cu_(2-x)Se nanoparticles(NPs)through a green and convenient way is still hindered by the inevitable non-environmentally friendly operations in common chemical synthesis.Herein,we initially reveal the coexistence of seleninic acid content and elemental selenium(Se)NPs in pulsed laser-generated Se colloidal solution.Consequently,we put forward firstly a closedcycle reaction mode for totally green production of Cu_(1.8)Se NPs to exclude traditional requirements of high temperature and toxic precursors by using Se colloidal solution.In such closed-cycle reaction,seleninic acid works as the initiator to oxidize copper sheet to release cuprous ions which can catalyze the disproportion of Se NPs to form Se O_(3)^(2-)and Se^(2-)ions and further produce Cu_(2-x)Se NPs,and the by-product SeO_(3)^(2-)ions promote subsequent formation of cuprous from the excessive Cu sheet.In experiments,the adequate copper(Cu)sheet was simply dipped into such Se colloidal solution at 70℃,and then the stream of Cu_(1.8)SeNPs could be produced until the exhaustion of selenium source.The conversion rate of Se element reaches to more than 75%when the size of Se NPs in weakly acidic colloidal solution is limited between 1 nm and 50 nm.The laser irradiation duration shows negative correlation with the size of Se NPs and unobvious impact to the p H of the solution which both are essential to the high yield of Cu_(1.8)SeNPs.Before Cu sheet is exhausted,Se colloidal solution can be successively added without influences to the product quality and the Se conversion rate.Such green methodology positively showcases a brand-new and potential strategy for mass production of Cu_(2-x)Se nanomaterials.

Green Measurements for Software Product Based on Sustainability Dimensions

Software is a central component in the modern world and vastly affects the environment’s sustainability.The demand for energy and resource require-ments is rising when producing hardware and software units.Literature study reveals that many studies focused on green hardware;however,limited efforts were made in the greenness of software products.Green software products are necessary to solve the issues and problems related to the long-term use of soft-ware,especially from a sustainability perspective.Without a proper mechanism for measuring the greenness of a particular software product executed in a specific environment,the mentioned benefits will not be attained.Currently,there are not enough works to address this problem,and the green status of software products is uncertain and unsure.This paper aims to identify the green measurements based on sustainable dimensions in a software product.The second objective is to reveal the relationships between the elements and measurements through empirical study.The study is conducted in two phases.Thefirst phase is the theoretical phase,where the main components,measurements and practices that influence the sustainability of a software product are identified.The second phase is the empirical study that involved 103 respondents in Malaysia investigating current practices of green software in the industrial environment and further identifying the main sustainability dimensions and measurements and their impact on achiev-ing green software products.This study has revealed seven green measurements of software product:Productivity,Usability,Cost Reduction,Employee Support,Energy Efficiency,Resource Efficiency and Tool Support.The relationships are statistically significant,with a significance level of less than 0.01(p=0.000).Thus,the hypothesised relationships were all accepted.The contributions of this study revolve around the research perspectives of the measurements to attain a green software product.