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In economies, cleaner technology, increased demand for renewable energy, and more efficient use of natural resources contribute to meeting environmental sustainability targets. The Chinese economy is no exception in its attempts to conserve economic and natural resources via collaborative efforts to embrace cleaner technology, green energy sources, and resource conservation management to preserve resources for future generations. This research examines the influence of cleaner technologies, green energy sources, and natural resource management on reducing greenhouse gas emissions using quarterly data for the Chinese economy from 2000Q1 to 2020Q4. The findings demonstrate that increasing demand for green energy reduces greenhouse gas emissions, hence substantiating the premise of ‘green is clean’ energy development. Additionally, optimum resource usage enhances environmental quality, corroborating the ‘resource cleaner blessing’ hypothesis. The positive link between inward foreign direct investment and greenhouse gas emissions substantiates the ‘pollution haven’ concept, according to which inward foreign direct investment uses unsustainable technology in manufacturing processes, hence degrading air quality indicators. Inadequate access to clean cooking technology and increased population density has a detrimental effect on the country’s environmental sustainability agenda, which must be corrected via sustainable regulations. The causality estimates show the feedback relationship between renewable energy demand (and economic growth) and cleaner technology, between economic growth and green energy (and inbound foreign direct investment), and between population density and economic growth (and green energy). The Impulse Response function estimates suggested that economic growth and population density would likely increase GHG emissions. In contrast, cleaner technology, green energy demand, natural resource management, and inbound foreign direct investment would likely decrease greenhouse gas emissions for the next ten-year time period. The sustainability of the environment and natural resources in China is bolstered by developing cleaner technologies, a greater reliance on renewable energy sources, and better management of natural resources.

Climate change and increased greenhouse gas emissions boost the global average temperature to less than 2°C, which is the estimated breakeven point. The globe is moving into blue pollution economies as the environmental sustainability objective becomes more distorted. The study looked at three United Nations Sustainable Development Goals, namely (i) affordable and clean energy; (ii) industry, innovation, and infrastructure; and (iii) climate change, to see how far the Chinese economy has progressed toward green and clean development strategy. In the context of China, the “pollution damage function” was intended to refer to carbon damages related to carbon pricing, technological variables, sustained economic growth, incoming foreign investment, and green energy. The data was collected between 1975 and 2019 and analyzed using various statistical approaches. The results of the autoregressive distributed lag model suggest that carbon taxes on industrial emissions reduce carbon damages in the short and long run. Furthermore, a rise in inbound foreign investment and renewable energy demand reduces carbon damages in the short term, proving the “pollution halo” and “green energy” hypotheses; nonetheless, the results are insufficient to explain the stated results in the long run. In the long run, technology transfers and continued economic growth are beneficial in reducing carbon damages and confirming the potential of cleaner solutions in pollution mitigation. The causal inferences show the one-way relationship running from carbon pricing and technology transfer to carbon damages, and green energy to high-technology exports in a country. The impulse response estimates suggested that carbon tax, inbound foreign investment, and technology transfers likely decrease carbon damages for the next 10 years. On the other hand, continued economic growth and inadequate green energy sources are likely to increase carbon pollution in a country. The variance decomposition analysis suggested that carbon pricing and information and communication technology exports would likely significantly influence carbon damages over time. To keep the earth’s temperature within the set threshold, the true motivation to shift from a blue to a green economy required strict environmental legislation, the use of green energy sources, and the export of cleaner technologies. Graphical abstract Source: Authors’ self-extract

Financial technology (FinTech) depends on high amounts of energy with an upward trend, possibly affecting emissions due to energy consumption (EC). The study investigates tail dependence, contagion, and nonlinear between FinTech, EC, and carbon dioxide emissions (CO2e) with MS-GARCH-copula and MS-GARCH-copula-causality with a daily sample covering 02 Jan 2012–28 December 2022. The method is a generalized version of single-regime GARCH-copula and causality tests to Markov-switching. Empirical results indicated that FinTech, EC, and CO2e series follow nonlinear processes in addition to unit roots as determined by BDS nonlinearity tests and a set of linear and nonlinear unit root tests. Further, for all series, heteroskedasticity and nonlinear forms of heteroskedasticity cannot be rejected by ARCH–LM and White heteroskedasticity tests, leading to the estimation of the series and their joint dynamics by MS-GARCH-copula and a new MS-GARCH-copula based nonlinear Granger-causality test, the RSGCC test, under two distinct regimes characterized with the low and high volatility for extreme tails of data. Positivity and significance of copula parameters under both regimes indicate a high degree of positive but asymmetric tail dependence and contagion between FinTech & EC, in addition to contagion between FinTech & CO2e and EC & CO2e. RSGCC results determine unidirectional causalities from EC to CO2e and from FinTech to CO2e, coupled with bidirectional causality between FinTech and EC, which enhance the dynamics due to feedback effects. The findings of this paper are of importance for two central Sustainable Development Goals. Results could also be used to bring the FinTech markets and EC to the attention of policymakers, researchers, and eco-friendliness-focused portfolio managers.

Organic effluent enrichment in water may selectively promote algal growth, resulting in water pollution and posing a threat to the aquatic ecosystem. Recent harmful algal blooms (HABs) incidents have highlighted information gaps that still exist, as well as the heightened need for early detection technology developments. Although previous research has demonstrated the importance of deep learning in the identification of algal genera, it is still a challenge to identify or to develop the best-suited convolution neural network (CNN) model for effective monitoring of bloom-forming algae. In the present study, efficiency of deep learning models (MobileNet V-2, Visual Geometry Group-16 (VGG-16), AlexNet, and ResNeXt-50) have been evaluated for the classification of 15 bloom-forming algae. To obtain a high level of accuracy, different convolution layers with adaptive moment estimation (Adam), root-mean-square propagation (RMSprop) as optimizers with softmax and rectified linear unit (ReLU) as activation factors have been used. The classification accuracies of 40, 96, 98, and 99% have been achieved for MobileNet V-2, VGG-16, AlexNet, and ResNeXt-50 model, respectively. We believe that the ResNeXt-50 has the potential to identify algae in a variety of situations with high accuracy and in real time, regardless of the underlying hardware. Such studies pave the path for future AI-based cleaner technologies associated with phycological studies for a sustainable future.

In recent years, the value of green innovation in achieving high-quality development in China has been increasingly recognized. However, studies on different types of green innovation under various environmental regulations have not established a systematic framework; especially, those considering external financing constraints are lacking. This study subdivides both environmental regulation and green innovation. Specifically, environmental regulation is divided into command-and-control regulation, market-incentive regulation, and public-participation regulation. Green technology innovation is divided into cleaner production technology innovation and end-of-pipe technology innovation. Moreover, this study explores whether and how environmental regulation affects green technology innovation, and investigates the moderating effect of external financing constraints, by matching the data from China Environmental Yearbook and China Industrial Enterprise Database. The results show that both command-and-control regulation and market-incentive regulation have the U-shaped relationship with cleaner production technology innovation. Meanwhile, public-participation environmental regulation significantly and positively affects cleaner production technology innovation, whereas market-incentive regulation and public-participation regulation have the inverted U-shaped relationship with end-of-pipe technology innovation. In addition, the external financing constraints have a moderating effect on the relationship between environmental regulation and cleaner production technology innovation.

Industrialization plays a crucial role in socio-economic development as it holds significant potential for creating new jobs, tightening the income gap, and promoting the use of advanced technology. As global competition intensifies, emerging economies emulate industrialized economies in accelerating manufacturing activity to improve national welfare and join the new global order. However, policymakers’ understanding of how competitiveness in the industrial sector helps developing countries accomplish their sustainable development goals must be deepened. This paper aims to analyze the connections among competitive industrial performance, renewable energy consumption, urbanization, and load capacity factor (LCF) in the BRICS economies for the period between 1990 and 2018. Robust evidence from the continuously updated fully modified (CUP-FM) and continuously updated bias-corrected (CUP-BC) models shows that greater industrial competitiveness enhances environmental quality. The findings also reveal that income growth ultimately evolves as an ecologically friendly factor, confirming the validity of the load capacity curve (LCC) hypothesis. Another outcome of the econometric analysis indicates that renewable energy consumption contributes to the LCF, whereas urbanization damages the environment. Therefore, BRICS policymakers should concentrate on maintaining their competitiveness, implementing resilient urban planning, and promoting the usage of renewable energy to safeguard the environment while simultaneously achieving rapid economic growth. Graphical Abstract

Climate change remains a global challenge requiring international collaborative action. Another area where countries have successfully committed to a long-term multilateral resolution is the liberalization of international trade. Integration into the world economy has proven a powerful means for countries to promote economic growth, development, and poverty reduction. The broad objectives of the betterment of current and future human welfare are shared by both global trade and climate regimes. Yet both climate and trade agendas have evolved largely independently through the years, despite their mutually supporting objectives. Since global emission goals and global trade objectives are shared policy objectives of most countries, and nearly all of the World Bank's clients, it makes sense to consider the two sets of objectives together. This book is one of the first comprehensive attempts to look at the synergies between climate change and trade objectives from economic, legal, and institutional perspectives. It addresses an important policy question - how changes in trade policies and international cooperation on trade policies can help address global environmental spillovers, especially GHG emissions, and what the (potential) effects of (national) environmental policies that are aimed at global environmental problems might be for trade and investment. It explores opportunities for aligning development and energy policies in such a way that they could stimulate production, trade, and investment in cleaner technology options.

This paper focuses on the relevant drivers of eco-innovation in 5,135 small and medium-sized enterprises (SMEs). In particular, we study if there are differences between the determinants of end-of-pipe and adoption of cleaner technologies between small and medium firms located in 27 European countries. Using a bivariate probit, significant differences comparing small with medium firms are found. Network involvement measured by cooperation with universities and research agencies is essential in both types of eco-innovation in small firms, but not for mid-sized firms. With regard to environmental regulation, subsidies are important only for small firms, especially for the adoption of cleaner technologies. On the contrary side, existing environmental regulation is a key factor to explain the adoption of cleaner technologies for medium firms but not for smaller ones.

In manufacturing processes many technological operations are designed, in which the adhesive properties of the treated surface are very important. These are processes related to application of any coating on the surface, such as gluing, painting, varnishing and others. Durability of coatings depends on proper preparation of the surface to which they are going to be applied. Conventional methods, such as grinding, sandblasting with subsequent washing and degreasing, as well as galvanic treatment applied to e.g. aluminium alloys - require the use of not only specific equipment but also chemical substances. They often lead to a significant burden on the environment due to their harmful properties. In an experimental study, attention was drawn to the significant environmental aspects of such a technological process and work was carried out to demonstrate whether it is possible to eliminate toxic and hazardous substances and to create good adhesion conditions by laser processing. To this purpose, samples were made out of two representative materials: X6Cr17 steel and AW-2024 aluminium alloy, abrasive surface treatment or in a galvanic bath and then washed, degreased and dried. Laser surface treatment without the use of additional chemicals was proposed as an environmentally cleaner technology. Surface roughness and adhesion of the test polymer coating were measured for comparative evaluation of the applied treatment methods. Obtained results were discussed in terms of the possibility of eliminating harmful influences and implementing laser treatment as a cleaner technology in the production of components requiring coating.

The dual objectives of air pollutant control and carbon emission reduction highlight the importance of determining investment methods in end-of-pipe (EOP) technology to achieve cost optimization goals. This paper aims to bridge the gap between the cooperative control theory and practical applications. We propose a framework using optimal control theory to obtain a technology investment path while considering the two-way synergy effect. To verify the effectiveness of the model, we considered three typical technologies in ultra-low emission transformation of a certain steel process. The used case in the study set the emission reduction of SO 2 , NO x and CO 2 as 55%, 70% and 80% compared to their basic cases, respectively. Considering the synergy effect, the peaks of the installed capacity of three technologies including carbon capture, denitrification, and desulfurization were obtained as 0.12 million tons, 5 million tons, and 15 million tons. Also, the related net emissions for the pollutant were 300, 400, and 1000 million tons. We found that terminal desulfurization and denitrification technology increase CO 2 emissions accounting for about 2% due to the negative synergy. However, the negative emission contribution from carbon abatement technology is greater accounting for about 40%. We also found that different policy objectives and emission factors have a greater impact on the investment path. These results demonstrate that we cannot completely ignore the negative emission reduction effects when adopting these EOP technologies. It is necessary to reevaluate these negative effects to the greatest extent so as to develop a more reasonable technological path, which is a guarantee for achieving the expected emission reduction targets.