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Sustainable development is inseparable from rational and responsible use of resources and promotion of green entrepreneurship. The contemporary green development agenda encompasses climate, economic, technical, social, cultural, and political dimensions. International efforts to greening the global development are conducted by the major economies, including China as the world’s largest consumer of energy and the biggest emitter of greenhouse gases. China is aware of its environmental problems, as well as of its part of the overall responsibility for the accomplishment of the sustainable development goals. By means of the decarbonization efforts, the latter are integrated both into the national development agenda (the concept of ecological civilization) and China’s international initiatives (the greening narrative within the Belt and Road Initiative). Over the past decade, China has made a breakthrough on the way to promoting green entrepreneurship and greening of its development (better quality of air and water, renewable energy, electric vehicles, and organic farming). On the other hand, emissions remain high, agricultural land loses productivity, and freshwater resources degrade due to climate change. In conventional industries (oil, coal mining, and electric and thermal energy), decarbonization faces an array of impediments. In this chapter, the authors summarize fundamental provisions of China’s approach to building an ecological civilization and measures to reduce emissions and achieve the carbon neutrality status within the nearest decades. The analysis of obstacles to the decarbonization of the economy and possible prospects for the development of green entrepreneurship summarizes China’s practices for possible use in other countries.

Marine seaweeds, characterised by high-valued bioactive compounds, are used worldwide for several applications, including human food, animal feed, pharmaceutics and cosmetics, bioplastics, agricultural fertilisers, biofuels, and others. Seaweed production can be carried out through different approaches, from on-land or sea-based cultivation to the harvesting of wild stocks. The latter can be of particular importance in the case of seasonal algal over-proliferations, often caused by eutrophic conditions associated with intensive human industrial activities, and which wreak havoc with ecosystem functioning and hinder economic activities. In Europe, Italy experiences seaweed blooms in several coastal basins, such as the Lagoon of Venice and the Lagoon of Orbetello (Tuscany). Here, the proliferating seaweed represents a disturbance to the natural ecosystem and to local business and touristic activities. These biomasses hold no economic value in the country and are systemically removed and disposed of. Re-purposing the biomass to produce seaweed-derived commercial goods would provide benefits for the environment and local economic activities while promoting a sustainable business within a Circular Economy framework and contribute to the UN Sustainable Development Goals number 12 (‘Responsible consumption and production’), and number 14 (‘Life under water’), among others.

The report is an environmental impact assessment of two conjoining water streams in the lower area of the Wembury catchment where freshwater meets the coast. The assessment was conducted as there were concerns that the streams may be causing exceedances of the Environmental Quality Standards (EQS) due to catchment-based inputs from anthropogenic activities.

Water, sediment samples, and other parameters were collected, measured, and treated to preserve the concentration of nutrients and metals at three sites. A comparison with the neighbouring river Erme was made to determine if the findings were coherent. The report includes recommendations and mitigation strategies needed to improve the environmental quality of the system.

Findings indicate several breaches of EQS: water nitrogen, copper and zinc, and sediment copper. The highest recorded concentrations were mainly at sites one and two, likely from point source inputs from Wembury town and pollution accumulation from upstream land use such as arable and agricultural land. A special precaution must be taken for sediment copper, increasing monitoring to ensure values do not exceed Probable Effects Level (PEL) possibly becoming dangerous for the fauna and flora but also for humans. River Erme showed to also have EQS breaches but to some degree displayed an overall better ecological status. Despite several breaches in the legal limits, Wembury displays an overall good ecological status supporting life above and below water and is therefore an appropriate model for promoting environmental stewardship. It is to be noted that the material of the coursework was further edited after its original submission.

The main objective of the present investigation is to develop a novel efficient stochastic model for availability optimization of reverse osmosis machine system (ROMS) for water purification under the concepts of exponentially distributed decision variables and various redundancy strategies at the component level.

ROMS is a complex framework configured in a series structure using six subsystems. Initially, a state transition diagram is developed and Chapman–Kolmogorov differential-difference equations are derived using Markov birth death process. The steady-state availability of the ROMS is derived for a particular case. The impact of variation in failure and repair rates measured on availability. Furthermore, an effort is made to predict the optimal availability of the ROMS system using the metaheuristic algorithms, namely, dragonfly algorithm (DA), grasshopper optimization algorithm (GOA) and whale optimization algorithm (WOA).

It is observed that the ROMS system predicts optimal availability of 0.999926 after five iterations with a population size of 300 by the WOA. The findings of this study are significant for reliability engineers as well as for maintenance engineers to ensure the availability of ROMS for water purification.

In the present investigation, a novel stochastic model is developed for ROMS, and metaheuristics algorithms are applied to predict the optimal availability.

In response to water scarcity in Sri Lanka, the government is implementing strategies such as rainwater harvesting, efficient irrigation, wastewater treatment and desalination. Initial efforts include the establishment of a desalination plant in Jaffna, with additional plans for the dry zones (DZ). The study aims to comprehensively identify the barriers to establishing desalination plants in the DZ and provide recommendations to mitigate these barriers. Additionally, this research provides valuable insights aimed at minimizing barriers to the construction of future desalination plants within Sri Lanka.

The study used qualitative methods, using an expert survey to identify current and future barriers, along with strategies for overcoming them. The collected data were analysed using the template analysis technique.

Regarding desalination plant establishment, various barriers such as high capital costs, high energy expenses, brine discharge, pollution, emissions, technical challenges, health concerns and waste disposal have been identified. However, specific strategies exist to address and mitigate each of these obstacles.

The study offers recommendations to environmental experts and government on expediting the approval procedures for desalination plants in Sri Lanka’s DZ. Adapted to Sri Lanka’s specific challenges, it highlights strategies and barriers essential for upcoming desalination projects. Furthermore, it emphasizes the financial advantages such as increased production and job creation resulting from establishing desalination facilities.

Through this study, promoting sustainable practices and fostering community involvement, it aims to enhance livelihoods, accelerate economic development and improve overall well-being through reliable access to water. Additionally, the study aims to enhance understanding of the importance of desalination in alleviating water scarcity, promoting community engagement and ultimately facilitating improved living conditions, health outcomes and economic opportunities in Sri Lanka’s DZs.

This study provides crucial direction for decision-makers by highlighting the main barriers to the establishment of desalination plants in Sri Lanka and outlining practical solutions. Implementing these strategies helps meet the region’s increasing water demands, advance sustainable water management, improve the standard of living for nearby communities and promote the socioeconomic development of desalination plants in Sri Lanka’s DZ.

The purpose of this study is to examine the vital link between manufacturing firms and the environment, delving into the intricate connections among factors affecting these firms. Specifically, it investigates how the environmental performance of manufacturing firms is shaped by their adoption of environmental management practices and the regulatory environment in which they operate.

Data are currently being collected through a structured questionnaire from employees working in manufacturing firms in Pakistan. Random sampling was used to select the participants. The hypotheses were tested using PLS-SEM analysis.

The study reveals a positive correlation between green manufacturing practices and superior environmental performance. Effective environmental management systems further help firms reduce their environmental footprint. External environmental regulations play a significant role as moderators, influencing the strength and direction of the relationship between green manufacturing, environmental management and environmental performance.

The practical implications offer valuable insights and guidance for manufacturing companies seeking to improve their environmental responsibility and performance. Additionally, policymakers gain insights into how regulatory frameworks can be designed or modified to better support sustainability efforts within the manufacturing sector.

This study offers timely insights for sustainable business practices, aligning with corporate responsibility efforts. It contributes to both academic knowledge and provides actionable guidance for fostering environmentally responsible practices in the manufacturing sector.

The purpose of this paper is to explore a new grey relational analysis model to measure the coupling relationship between the indicators for the water environment status assessment. Meanwhile, the model deals with the problem that the changing of indicator order may result in the changing of the degree of grey relation.

The binary index submatrix of the sample matrix is given first. Then the product of the matrix and its own transpose is used to measure the characteristics of the index and the coupling relationship between the indicators. Thirdly, the grey relational coefficient is defined based on the matrix norm, and a grey coupling relational analysis model is proposed.

The paper provides a novel grey relational analysis model based on the norm of matrix. The properties, normalization, symmetry, relational order invariance to the multiplicative, are studied. The paper also shows that the model performs very well on the water environment status assessment in the eight cities along the Yangtze River.

The model in this paper has supplemented and improved the grey relational analysis theory for panel data.

This study aims to elucidate the dyeing kinetics and thermodynamic relationships of CI Reactive Red 24 (RR24) on cotton fabrics, achieve the recycling of inorganic salts and water resources and obtain comprehensive data on color parameters, fastness and other characteristics of fabrics dyed with the recycled dyeing residual wastewater.

The dyeing wastewater obtained through advanced oxidation technology was used as a medium for dyeing cotton fabrics with RR24. The absorbance value of the dyeing residue served as an evaluation index, and the relevant kinetic and thermodynamic parameters were calculated based on this absorbance. The color parameters and fastness of the fabric samples were measured to compare the performance of different dyeing media.

Dyeing cotton with RR24 in both media follows pseudo-second-order kinetics. When dyeing with wastewater media, the dye adsorption in the first 45 min increased by 0.082–1.29 g/kg compared with conventional dyeing. Furthermore, the half-dyeing time was shortened by 4.19–11.99 min and the equilibrium adsorption amount was reduced by 0.277–0.302 g/kg. The adsorption of RR24 on cotton fabrics conformed to the Freundlich model. Fabrics dyed using recycled wastewater exhibit a deeper color, with reduced red light and enhanced blue light, resulting in an overall deeper apparent color.

These dyeing kinetics and thermodynamic properties are beneficial for comprehending and interpreting the dyeing performance and behavior of reactive dyes in dyeing wastewater. They lay a theoretical foundation for the treatment and recycling of dyeing wastewater.

The purpose of this paper is to construct a grey incidence model for panel data that can reflect the incidence direction and degree between indicators.

Firstly, this paper introduces the concept of a negative matrix and preprocesses the data of each indicator matrix to eliminate differences in dimensions and magnitudes between indicators. Then a model is constructed to measure the incidence direction and degree between indicators, and the properties of the model are studied. Finally, the model is applied to a practical problem.

The grey-directed incidence degree is 1 if and only if corresponding elements between the feature indicator matrix and the factor indicator matrix have a positive linear relationship. This degree is −1 if and only if corresponding elements between the feature indicator matrix and the factor indicator matrix have a negative linear relationship.

The example shows the number of days with good air quality is negatively correlated with the annual average concentration of each pollutant index. PM_2.5, PM₁₀ and O₃ are the main pollutants affecting air quality in northern Henan.

This paper introduces the negative matrix and constructs a model from the holistic perspective to measure the incidence direction and level between indicators. This model can effectively measure the incidence between the feature indicator and factor indicator by integrating information from the point, row, column and matrix.

The presence of green spaces plays a vital role in promoting urban sustainability. Urban green parks (UGPs) help create sustainable cities while providing fundamental ecological functions. However, rapid urbanization has destroyed crucial green areas in Ranchi City, endangering inhabitants’ health. This study aims to locate current UGPs and predict future UGP sites in Ranchi City, Jharkhand.

It uses geographic information system (GIS) and analytical hierarchical process (AHP) to evaluate potential UGP sites. It involves the active participation of urban communities to ensure that the UGPs are designed to meet dweller’s needs. The site suitability assessment is based on several parameters, including the normalized difference vegetation index (NDVI), land use and land cover (LULC), population distribution, PM 2.5 levels and the Urban Heat Island (UHI) effect. The integration of these factors enables an evaluation of potential UGP’s sites.

The findings of this research reveal that 54.39% of the evaluated areas are unsuitable, 15.55% are less suitable, 12.76% are moderately suitable, 11.52% are highly suitable and 5.78% are very highly suitable for UGPs site selection. These results emphasize that the middle and outer regions of Ranchi City are the most favorable locations for establishing UGPs. The NDVI is the most important element in UGP site appropriateness, followed by LULC, population distribution, PM 2.5 levels and the UHI effect.

This study improves the process of integrating AHP and GIS, and UGPs site selection maps help urban planners and decision-makers make better choices for Ranchi City’s sustainability and greenness.