Green Degree Research Articles

The G-pel method for determining the degree of greening of the area using the city of Penza as an example

The G-pel method for determining the degree of greening of the area using the city of Penza as an example

Comprehensive assessment of the state of the environment in rural and urban areas

The article examines the comfort of the environment in rural and urban areas. To assess the level of environmental comfort, methods were used to determine the degree of greening of populated areas, the state of tree plantations within green public areas, the aggressiveness of the visual environment and the quality index of the urban environment. Based on the results of the research, the comfort of the environment in rural and urban areas was compared and conclusions were drawn.

A Study on Green Classroom and Green Degree Assessment System

A Study on Green Classroom and Green Degree Assessment System

Analysis of Green Innovation of the E-Tailer and Supplier with a Drop Shipping Option in E-Commerce

As customer demand for green products increases in the digital economic era, this study analyses the green innovation of the e-tailer and supplier in drop shipping models. Moreover, drop shipping e-tailers and suppliers with a drop shipping option need to make choices regarding whether to provide green or normal products to the market. When a supplier with a drop shipping option produces green products, more fees may be invested in the production of green products than on normal products. The drop shipping e-tailers and suppliers with a drop shipping option can also choose to sell normal products at a low cost, as before. This study designs four models of drop shipping e-tailers and suppliers with a drop shipping option under different choices, analyzes their operational process in drop shipping models, and investigates five theorems. The optimal pricing decisions and green degree of drop shipping e-tailers and suppliers with a drop shipping option were evaluated in this study. The impacts of the green innovation factor, green elasticity coefficient, manufacturing and distribution costs on the drop shipping e-tailers and suppliers with a drop shipping option, and the effect of other environmental parameters on the green degree of green products are also analyzed through computer simulation. The findings of the simulation analysis provide valuable guidance for e-tailers and suppliers with green innovation in drop shipping models and offer important academic and practical implications for e-commerce and the digital economy.

The Effect of Perceived Real-Scene Environment of a River in a High-Density Urban Area on Emotions

Public sub-health has emerged as a pressing concern in densely populated urban areas. The urban environment, with its innate ability to modulate public emotions, harbors a precious resource in the form of urban rivers, which provide a serene and verdant space. This study focuses on the Liangma River in Chaoyang District, Beijing, selecting two rivers with diverse landscape features as the subjects of research. By employing physiological feedback data in conjunction with a subjective questionnaire, the emotional impact of high-density urban riverside spaces on individuals is quantitatively analyzed. Electrocardiogram (ECG) data, eye movement data, and the positive–negative emotion scale (PANAS) are subjected to data analysis. The study reveals the following key findings: (1) The riverside landscape in high-density urban areas exerts a positive influence on emotional well-being. Individuals in more natural river settings experience greater levels of contentment and relaxation, while those in areas with a higher proportion of artificial elements exhibit increased excitement and happiness. Moreover, scenes characterized by a greater degree of greening have a more pronounced soothing effect on mood. (2) A specific correlation between visual characteristics and emotional fluctuations is observed. The waterfront side of the trail exerts a stronger spatial attraction, and a higher proportion of blue and green spaces significantly contributes to stress relief. (3) The utilization of human-induced engineering technology, which captures emotional changes through physiological feedback, demonstrates a higher level of accuracy and is well-suited for small-scale studies. These findings highlight the potential of arranging diverse types of waterfront footpath landscapes in high-density urban areas and approaching waterfront landscape design and transformation from a novel perspective centered on health intervention. Such efforts hold promise for alleviating the daily pressures faced by the general public and fostering the development of a “healthy city”.

Novel ferrofluid based on water-based deep eutectic solvents: application in dispersive liquid-liquid microextraction of naphthalene-derived plant growth regulators in edible oil

A new ferrofluid extractant (Fe3O4 @SiO2-WDES) was ingeniously prepared by coating magnetic Fe3O4 @SiO2 microspheres with water-based deep eutectic solvent (WDES) and used for dispersive liquid-liquid microextraction (DLLME) and HPLC determination of naphthalene-derived plant growth regulators (PGRs, i.e., 1-naphthylacetic acid, 2-naphthylacetic acid, 1-naphthoxy acetic acid, 2-naphthyloxyacetic acid and 1-naphthylacetamide) in edible oil. Herein, mass transfer of the analytes in DLLME was significantly enhanced via increasing the contact surface by employing the microspheres as the supporter and dispersant of WDES, and phase separation can be efficiently achieved using an external magnet rather than centrifugation in traditional DLLME. Response surface methodology (RSM) based on Box-Behnken design (BBD) was employed for the optimization of core experimental conditions, and Analytical Eco-Scale and Analytical GREEnness Metric Approaches were adopted to evaluate the degree of greenness of the procedure. Under the optimal conditions, satisfactory performances of linearity ranged from 5 to 100 μg/L (R2 ≥ 0.9982), limit of detection (0.58–0.91 μg/L), limit of quantitation (1.9–3.0 μg/L), precision (RSDs ≤ 5.5%), recovery (81.3%−108.1%) and negligible matrix effect were achieved, which introduced a promising alternative route for the determination of naphthalene-derived plant growth regulators in edible oil.

Development and validation of chemometric-assisted spectrophotometric models for efficient quantitation of a binary mixture of supportive treatments in COVID-19 in the presence of its toxic impurities: a comparative study for eco-friendly assessment

The use of sustainable solvents has increased significantly in recent years due to advancements in green analytical methods. The number of impurities in the drug substance determines how safe the finished product is. Therefore, during the whole medication planning process, contaminants need to be closely watched. Using chemometric models, the concentrations of hyoscine N-butyl bromide (HYO) and paracetamol (PAR) were determined in the presence of three PAR impurities [P-nitrophenol (PNP), P-aminophenol (PAP), and P-chloroacetanilide (PCA), as well as DL-tropic acid (TRO) as a HYO impurity]. It was possible to isolate and measure these dangerous impurities. Fever and spasms associated with COVID-19 are reported to be considerably reduced when PAR and HYO are taken together. Artificial neural networks, principal component regression, multivariate curve resolution-alternating least squares, and partial least squares are the four chemometric-assisted spectrophotometric models that were created and verified. All of the proposed methods’ quantitative analytical potency was assessed using recoveries%, root mean square error of prediction, and standard error of prediction. For PAR, HYO, PNP, PCA, TRO, and PAP, respectively, the indicated approaches were used in the ranges of 4.00–8.00, 16.00–24.00, 1.00–5.00, 0.40–0.80, 4.00–12.00, and 2.00–6.00 µg/mL. They are able to get around difficulties like collinearity and spectral overlaps. After statistical testing, there was no discernible difference between the recommended methods and the published one. The degree of greenness of the established models was evaluated using three different green assessment methods. In the presence of their harmful impurities, PAR and HYO could be identified using the recommended methods.

Study on the Performance and Green Degree Evaluation of the Reference Cement–Sulfoaluminate Cement Composite System

Study on the Performance and Green Degree Evaluation of the Reference Cement–Sulfoaluminate Cement Composite System

Impact of government fund policy and blockchain technology on closed-loop supply chains in textile and apparel industry

Textile waste presents significant environmental risks for the textile and apparel (T&A) industry; however, most textiles can be recycled, enabling the remanufacturing of energy and fiber for resale in the secondary market. In this regard, the importance of a Government Fund Policy (GFP) has been emphasized to promote recycling and remanufacturing efforts aimed at establishing T&A closed-loop supply chains (CLSCs). Simultaneously, blockchain technology and green-product design have transformed T&A brand marketing dynamics due to their crucial roles in enhancing brand trust and increasing market demand. Nevertheless, there is limited research dedicated to examine the interactive effects of GFP and blockchain technology within T&A supply chains. This paper proposes a stylized CLSC game involving a T&A manufacturer and a retailer. The manufacturer sells new and remanufactured T&A products to the retailer while determining green-product design efforts (i.e., green degree). The retailer determines selling prices but incurs usage costs associated with adopting blockchain technology. Through equilibrium analyses, we find that the simultaneous implementation of GFP and blockchain technology can incentivize T&A manufacturers to enhance the green degree of their products, thereby improving brand trust and market demand. All supply chain agents can benefit from adopting blockchain technology as long as its usage cost is below a threshold level, regardless of whether GFP is implemented or not. Similarly, irrespective of whether blockchain technology is adopted or not, if the ratio between remanufacturing subsidies and environmental taxes exceeds a specific threshold value, GFP will serve as an incentive for sustainability efforts among T&A firms while providing them with greater advantages. Additionally, the simultaneous implementation of GFP and blockchain technology holds significant potential for mitigating environmental pollution, i.e., by carefully selecting appropriate degrees of GFP and blockchain technology parameters, a mutually beneficial outcome can be achieved for T&A firms, consumers, and the environment. These findings have important implications for T&A supply chain managers seeking to optimize CLSCs while integrating blockchain technology. Furthermore, they provide valuable insights into government strategies for implementing GFPs.

Impact of extended warranty service on product pricing in online direct retailers' competitive market

In this paper, we consider a model composed of the three largest online direct retailers to investigate the impact of extended warranty service on product pricing. A single-period static game model and a dynamic game model with two delays are built. We discuss the optimal game strategies and dynamic evolution game behaviors of retailers and analyze the effects of warranty period and price adjustment speed on system stability. The result shows that the optimal extended warranty price, green degree, and extended warranty period lead to the biggest profits for the retailer. From the perspective of maximum profit, retailers should give priority to extending the warranty period, followed by extending the warranty price and extending the green degree of warranty. For the sake of system stability and player performance, retailers should take recent historical data as a reference, and a relatively slow price adjustment speed is needed. To better maintain the stability of the system, the delay feedback control method is adopted which can successfully control the instability of the system.

Sustainable strategies for green supply chain within the platform economy consider subsidies and marketing efforts.

As consumers' green awareness continues to grow, the level of a product's eco-friendliness and the quality of its marketing have become significant factors in shaping consumers' purchasing decisions. The power structures within the supply chain, as well as corresponding government subsidy policies, are also key elements influencing sustainable strategies for the green supply chain. In a green supply chain comprising one manufacturer and one e-commerce platform, two sales models exist within the online e-commerce platforms: reselling and agency selling. This paper establishes and analyzes three distinct Stackelberg game models, namely: manufacturer-led model without subsidy (bm), manufacturer-led model with subsidy (sm), and platform-led model with subsidy (sp). The results are shown as follows, with the rise of consumers' environmental awareness, more consumers opt for green products, inspiring the manufacturer to increase its optimal greenness and platform to enhance its optimal marketing efforts level. Notably, government subsidies provide a significant stimulus. An increase in the green technology cost coefficient leads to a decline in the manufacturer's profits across all three modes. Intriguingly, the manufacturer's profits are always highest in the sp mode. As the marketing efforts cost coefficient increases, the platform's profits decrease in the bm and sm modes. In contrast, in the sp mode, the platform's profits increase rather than a decrease. The choice of mode primarily depends on the platform's marketing efforts cost coefficient. When this coefficient exceeds a threshold, the platform chooses the sp mode. However, due to the relatively low marketing efficiency in this scenario, the manufacturer prefers the sm mode. For the government, the sp mode involves agency selling, serves as an effective mechanism to redistribute subsidies, thereby yielding the maximum social welfare benefits. Management insights are provided for the manufacturer and platform managers to make decisions about the degree of greenness and marketing efforts level, along with insights for governments to optimize subsidy policies.

Spatial-temporal pattern and influencing factors of tourism ecological security in Huangshan City

It is of important theoretical and practical value to scientifically evaluate tourism ecological security for the sustainable development of tourist cities. The study focuses on the “characteristics of the impact factors on tourism ecological security at different levels” of tourism ecological security that have been neglected in the previous literature. From the perspective of Compound Ecological systems theory, we built an evaluation index system for tourism ecological security in Huangshan City based on the Pressure-State-Impact-Economic-Environmental-Social (PSR-EES) model and used a combination of the entropy weight TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method, traditional and spatial Markov chains, and panel quantile regression to analyze and characterize the spatial-temporal dynamics of security levels and driving factors. The results showed that (1) the level of tourism ecological security of the districts and counties in Huangshan City improved rapidly, but the difference was expanding. The level of tourism ecological security in the four counties was generally higher than that in the three districts. (2) In terms of the spatial-temporal dynamic evolutionary characteristics, the transfer of tourism ecological security in Huangshan City has its characteristics of stability and path dependence. Type transfers usually occur between adjacent levels. The lower the level of tourism ecological security, the higher the probability of upward transfer. A neighborhood background plays an important role in the process by which a higher neighborhood rank increases the probability of upward transfer. (3) Regarding the driving factors, environmental pollution and economic development have a negative inhibitory effect on tourism ecological security, and the negative effect decreases as the level of TES improves. The top three positive effects were government intervention and educational levels. The degree of regional greening and government intervention had greater positive marginal effects on lower-level areas. In contrast, tourism development, educational level, and labor input had greater positive marginal effects on areas with higher TES levels.

Study on a green degree evaluation model of construction for prefabricated buildings

To promote new urbanisation and the transformation of the construction industry, a green degree (GD) evaluation model for prefabricated buildings was proposed under the guidance of the industrial green concept. A combined ordered weighted average operator was used to assign weights to each index. On this basis, a GD evaluation model for prefabricated buildings was established by combining normal cloud theory and matter-element theory. The application effect was analysed using the dual-case method. The results indicated that for a steel-frame-supported prefabricated structure, the GDs of energy resource indicators and environmental protection indicators were both in level 2. The GD of construction management indicators, technological innovation indicators and social coordination indicators was in 3. The overall trend was from level 2 to level 3. For prefabricated concrete structures, all indicators had a GD of level 2. In contrast, frame-supported prefabricated structures had more development advantages and had important practical significance in guiding the transformation of the construction industry and the development of new urbanisation. The GD evaluation model could obtain comprehensive evaluation results under different assembly structures, providing assistance for the green development of the construction industry.

Assessment of Green Banking Performance

Internal and external pressures are pushing the financial system towards an increasingly environmentally responsible orientation. The damaging practices of green-washing necessitate the search for new ways of monitoring. The question then arises, how can one measure the actual degree of greenness of a banking industry? This study aims to create a new methodology framework to measure green performance in the banking industry using multi-criteria methods. We offer a theoretical contribution. First, a set of criteria was identified at the theoretical level. Second, the criteria were evaluated by practitioners and aggregated using the ‘TOPSIS’ method. This index may constitute a basis for ranking banks. The results showed that the most important factors to be considered when evaluating the performance of green banking are the greenness of the customers, the development of innovations leading to a green economy, the availability of green financial products and services, and the promotion of green education. These results lead to the conclusion that both banks and clients should become “greener” and utilize more green innovations and financial products/services.

A Fuzzy Parameterized Multiattribute Decision-Making Framework for Supplier Chain Management Based on Picture Fuzzy Soft Information

Supplier selection as a multiattribute decision-making (MADM) problem has various inherent uncertainties due to a number of symmetrical variables. In order to handle such information-based uncertainties, rational models like intuitionistic fuzzy sets have already been introduced in the literature. However, a picture fuzzy set (PiFS) with four dimensions of positive, neutral, negative, and rejection is better at capturing and interpreting such kinds of ambiguous information. Additionally, fuzzy parameterization (FPara) is helpful for evaluating the degree of uncertainty in the parameters. This study aims to develop a fuzzy parameterized picture fuzzy soft set (FpPiFSS) by integrating the ideas of PiFS and FPara. This integration is more adaptable and practical since it helps decision makers manage approximation depending on their objectivity and parameterization uncertainty. With the assistance of instructive examples, some of the set-theoretic operations are examined. A decision support framework is constructed using matrix manipulation, preferential weighting, fuzzy parameterized grades based on Pythagorean means, and the approximations of decision makers. This framework proposes a reliable algorithm to evaluate four timber suppliers (initially scrutinized by perusal process) based on eight categorical parameters for real estate projects. In order to accomplish suppliers evaluation, crucial validation outcomes are taken into account, including delivery level, purchase cost, capacity, product quality, lead time, green degree, location, and flexibility. To assess the advantages, dependability, and flexibility of the recommended strategy, comparisons in terms of computation and structure are provided. Consequently, the results are found to be reliable, analog, and consistent despite the use of fuzzy parameterization and picture fuzzy setting.

Optimal government and manufacturer incentive contracts for green production with asymmetric information.

Governments commonly utilize subsidy policy to incentivize manufacturers to produce green products, promoting sustainable development. However, in the presence of information asymmetry, some manufacturers may dishonestly misrepresent the green degree of their products to secure higher subsidies. This study examines different incentive contracts between the government and a green product manufacturer who keeps private information of a product's green-degree in a principal-agent model. Lump-sum transfer and fixed- and flexible-proportion benefit-sharing contracts are proposed to investigate screening and improving green-degree issues. To further enhance the flexible-proportion benefit-sharing contract, we construct a non-linear coordinated contract based on the Nash bargaining solution. The revelation principle and Nash bargaining are performed for comparison and analysis of the contracts. We find that the lump-sum contract reveals true green-degree information but fails to impel manufacturers to improve product's green-degree in developing countries where green product development is in initial stages. In contrast, both fixed- and flexible- proportion benefit-sharing contracts are effective in reveling and enhancing green-degree. The non-linear coordination contract optimizes resource allocation and achieves Pareto improvement. An applied case study for inkjet printer operations and numerical experiments corroborate our model findings.

How Does Green Store Brand Introduction Influence the Effects of Government Subsidy on Supply Chain Performance?

With the rising awareness of environmental protection and concern for sustainable development, green products have been highly favored by consumers, enterprises, and the government. As a matter of fact, not only do manufacturers produce green products, but retailers would also like to introduce their green store brands. However, the costly green investment hinders the improvement of the products’ green degree. Therefore, the government may provide financial support to motivate enterprises to increase their products’ green degree. This study investigates how the presence of green store brands and government subsidies affect green supply chain performance. Four models are discussed using the Stackelberg game theoretic approach, and then, the optimal solutions in different cases are compared. The results show that (1) regardless of the government subsidy, the green store brand introduction always reduces the manufacturer’s profit and improves the retailer’s profit and environmental benefit; (2) In most cases, the implementation of a government subsidy can effectively improve the products’ green degree and benefit the supply chain members. However, it is surprising to find that the government subsidy may be detrimental to the manufacturer once the green store brand is introduced; (3) Interestingly, the introduction of green store brand may have an expansion effect, a shrinkage effect or even an inverse effect on the effects of government subsidies on supply chain performance, and these effects become more significant with the increasing green preference of consumers, product substitute, and subsidy rate. The new findings also provide some implications for supply chain members and the government in green supply chain management (GSCM) and green innovation.

A green sustainable approach for the determination of a complex quintet hepatoprotective mixture using dual wavelength HPLC coupled with diode array detection: Compliance with greenness and whiteness metrics

The wide spread of chronic liver disease is increasing constituting a worldwide health burden. Accordingly, mixed combinations of silymarin, N-acetyl cysteine, with antioxidant vitamins have been introduced. However, the great diversity between the analyzed components makes their simultaneous determination a rather difficult task. The water-soluble vitamins, vitamin C, and N-acetyl cysteine are highly hydrophilic with poor retention while the lipophilic vitamins, vitamin E and B-carotene, in addition to silymarin are strongly retained on the column. In this study, a novel and selective HPLC with diode array detection method has been proposed for the simultaneous determination of the five compounds using a gradient elution system of methanol and 0.025 M KH2PO4 adjusted to pH 2.5 with different flow rates. The method was fully validated as per ICH guidelines. Low limits of detections in the range 0.35–133.5 and of quantitation in the range of 1.07–404.7 μgmL−1 were obtained. The proposed method enabled the successful determination of the cited compounds in their combined pharmaceuticals with high accuracy and precision. Finally, method’s eco-friendliness and sustainability were investigated using greenness and whiteness assessment tools. The results revealed that the proposed method showed high degree of greenness and whiteness and is better than selected reference methods.

An Integrated Approach to Green Mines Based on Hesitant Fuzzy TOPSIS: Green Degree Analysis and Policy Implications

China proposes to construct green mines as one of the significant means to elevate the green degree of mining industry and protect the mining environment. This paper constructs six evaluation indicators, namely mine environment, Resource development mode, Comprehensive utilization of resources, Energy conservation and emission reduction, Technological innovation and digital mining, Enterprise management and corporate image, to reflect green degree of mining firms. An improved multiattribute evaluation method (MAEM) is proposed based on hesitant fuzzy TOPSIS and kernel method. A case study of green mining firms in Panxi, southwestern China is provided to demonstrate the application of the proposed model. According to the research in this paper, it is more appropriate to expand the data in accordance with the optimistic criteria. The results also show that the improved hesitant fuzzy TOPSIS is a better method in the evaluation of green degree. Through the results of this paper, a reasonable and scientific method is introduced for the evaluation of the green degree of mining firms, and it can be promoted to the evaluation of the mineral resource development efficiency.

Novel bionanomaterial based on Spirulina maxima algae and graphene oxide for lead microextraction and determination in water and infant beverages.

A new hybrid bionanomaterial composed of graphene oxide (GO) and Spirulina maxima (SM) algae was synthesized and applied to develop a preconcentration method based on the dispersive micro-solid phase extraction (D-μ-SPE) technique for the determination of Pb in water and infant beverages. In this work, Pb(II) was extracted with 3mg of the hybrid bionanomaterial (GO@SM) followed by a back-extraction step using 500 µL of 0.6mol L-1 HCl. Then, a 1.5 × 10-3mol L-1 dithizone solution was added to the sample containing the analyte to form a purplish red-colored complex for its detection by UV-Vis spectrophotometry at 553nm. An extraction efficiency of 98% was obtained after optimization of experimental variables such as GO@SM mass, pH, sample volume, type, and time of agitation. A detection limit of 1μg L-1 and a relative standard deviation of 3.5% (at 5μg L-1 Pb(II), n = 10) were achieved. The calibration linear range was obtained between 3.3 and 95µg L-1 Pb(II). The proposed method was successfully applied for the preconcentration and determination of Pb(II) in infant beverages. Finally, the greenness degree of the D-µ-SPE method was evaluated using the Analytical GREEnness calculator (AGREE), obtaining a score of 0.62.