Climate change and COP26: Are digital technologies and information management part of the problem or the solution? An editorial reflection and call to action

Nature-based and geo-engineering climate mitigation technologies: Public acceptance and security prospects

Climate change requires mitigation approaches, from nature-based to experimental geoengineering. We examined public attitudes toward six strategies-reforestation in previously forested areas, afforestation in new terrains, direct CO2 capture with underground storage, biomass energy with CO2 capture, stratospheric sulfate aerosols, and orbital mirrors-via a representative Czech survey (N = 3,007). Binary logistic regressions reveal how age, education, employment, and residence shape perceptions of efficacy, risks, and ethics. Results show strong favor for reforestation and afforestation due to ecological benefits and long-term promise; sulfate aerosols and orbital mirrors face skepticism. Surprisingly, participants with only primary education showed greater openness to geoengineering than university graduates. Older respondents favored biomass-based carbon capture but less so certain high-tech solutions. Our findings highlight the importance of policies aligned with diverse public views, ensuring both established and novel measures are harmonized into an effective climate mitigation strategy. These results indicate demographic contexts shape acceptance of climate interventions.

Dynamic correlation of environmental regulation, technological innovation, and corporate carbon emissions: empirical evidence from China listed companies

The notable rise in carbon emissions has profoundly affected humanity's sustainable development. Achieving the "dual-carbon" goal requires understanding how enterprises can effectively reduce their carbon footprint. To elucidate the dynamic correlation of environmental regulation, corporate technological innovation, and corporate carbon emissions, this study employs a Panel Vector Autoregression model to analyze data from listed firms between 2005 and 2021, using GMM regression, impulse response analysis, and variance decomposition. The key findings are: (1) Environmental regulation, corporate technological innovation, and corporate carbon emissions exhibit self-reinforcing mechanisms, though the effect weakens over time. (2) Environmental regulation reduces corporate carbon emissions significantly, and this effect is partially mediated through corporate technological innovation. (3) A bidirectional relationship exists between corporate technological innovation and corporate carbon emissions, where corporate technological innovation has a stronger positive effect on reducing corporate carbon emissions. (4) Environmental regulation promotes corporate technological innovation, while corporate technological innovation gradually mitigates the stringency of environmental regulation. The findings herein offer actionable insights for enterprises to adopt cleaner production strategies and offer a scientific basis for policymakers to enhance environmental regulations in pursuit of a low-carbon economy.

Investigating the dynamics of climate finance disbursements: A panel data approach from 2003 to 2022

This study investigates the intricate dynamics of international multilateral climate finance disbursements from 2003 to 2022 via an extensive dataset from the Climate Funds Update (CFU). By employing panel data econometric models, including pooled ordinary least squares (OLS), fixed effects (FE), and random effects (RE) models, the study elucidates the impact of grants and approved funds on disbursement levels across different income groups. The analysis reveals that while grants do not significantly influence disbursements, the approval of funds plays a critical role in enhancing disbursement efficiency. The random effects model, validated through the Hausman test, emerges as the optimal model for this context. The findings underscore the importance of streamlined approval processes in ensuring effective climate finance disbursements and highlight the need for further investigation into the non-significance of grants. The forecasting results indicate a positive trend in disbursements from 2023 to 2027, with potential fluctuations driven by external factors. This study provides valuable insights for policymakers and stakeholders to optimize climate finance mechanisms and improve fund utilization for sustainable development.

Catalyzing sustainable development goals through the water-energy-food nexus

Water, energy, and food (WEF) are central to sustainable development as they are vital for socio-ecological and socio-economic sustainability and human and environmental wellbeing. How the three are used and managed is central to either the aggravation of climate change or the enhancement of resilience and adaptation strategies. This mixed transdisciplinary study developed a WEF nexus-based framework to guide strategic policy decisions to catalyze progress toward achieving sustainable development goals. The aim is to guide the cross-sectoral management of resources for sustainable development under climate change, increasing demand, depletion, degradation, and uncertainty. Past and present data on resource management was assessed to comprehend future availability toward achieving sustainable development outcomes for people and the planet. The fundamentals of holistic WEF resources management were assessed, highlighting the significance of transformative, cross-sectoral, and circular approaches in enhancing resource use efficiency and sustainability. This is critical for informing sustainable natural resources management decisions.

Green entrepreneurial leadership and AI-driven green process innovation: Advancing environmental sustainability in the Traditional Chinese Medicine industry

Despite much focus has been given on the relationship between leadership, innovation and firm performance, the impact of green entrepreneurial leadership (GEL) and Artificial Intelligence - driven green process innovation (AI-driven GPI) on firm performance (financial and environmental) remains unclear. Based on upper echelons theory, this study hypothesized that GEL has a positive impact on AI-driven GPI, while green technology turbulence (GTT) moderates this relationship. AI-driven GPI acts as a mediator between GEL and firm performance. We tested the research hypotheses using data from 255 Small and Medium Size Enterprises in China's Traditional Chinese Medicine manufacturing industry. The results indicate that GEL positively impacts AI-driven GPI, while GTT negatively moderates this effect. Moreover, AI-driven GPI mediates the GEL - firm performance relationship. This study enhances the understanding of GEL as a unique leadership behavior that encourages innovation, identifies potential opportunities, and takes risks when leveraging AI-driven GPI to improve firm performance. Furthermore, this study addresses the debate on AI's role in environmental sustainability, identifying AI-driven GPI as a strategic pivot for change in governance, values, and culture within firms. The study concludes by providing suggestions for firms to achieve financial and environmental performance in an uncertain technological environment, thereby providing new insights for future research. Based on these findings, policymakers should develop incentives and frameworks to promote AI-driven GPI and incorporate GEL into leadership practices, enhancing firm competitiveness in the Industry 5.0 era and advancing the Sustainable Development Goals.

Systems thinking-informed and data-driven urban decarbonisation framework for individual, community and urban scale climate action

There is an urgent need to rapidly reduce greenhouse gas (GHG) emissions and, although human activity is a primary driver of emissions, a knowledge gap remains in terms of the key individual and collective drivers of emissions, and on how to harmonise citizen-led climate action with top-down emissions mitigation policy. In response to this, an urban decarbonisation framework which was informed by systems thinking was developed to support multi-level climate action and decision making. Another aim was to demonstrate the integration of a data-driven and activity-based GHG emissions model for individuals into the framework to enable decarbonisation. This model was populated using individual activity and lifestyle data which were collected for 172 people using a smartphone application. The resulting emissions drivers were identified as well as their interaction with the overarching urban decarbonisation framework. The research will have important implications in terms of informing emissions mitigation efforts at individual, community and urban scales. By applying the framework, individual data and GHG emissions modelled at scale can inform citizen and population-level actions and high-level emissions mitigation policy for accelerating the sustainability transition that our societies and cities must urgently undergo.

The perfect match between macroalgae and eutectic solvents as a sustainable gateway to ready-to-use extracts towards a (blue + green) economy ─ A perspective review

The article discusses how aligning with the Sustainable Development Goals (SDGs) can foster a sustainable economy, mainly through the (green + blue) economy, which involves valorizing macroalgae to produce ready-to-use extracts. It focuses on the potential of eutectic solvents (commonly known as deep eutectic solvents - DES) as promising candidates for this purpose. Traditional methods for extracting bioactive compounds from macroalgae, which rely on organic solvents and aqueous buffers, often involve harsh conditions and extensive processing. These factors can lead to reduced extract quality and/or low yields. In contrast, if properly designed, DES presents a green and sustainable alternative. They offer advantages such as low volatility, adjustable polarity, and negligible toxicity, making them a more environmentally friendly and efficient option for extraction processes. They can be customized to enhance both biological and technological properties, resulting in extracts with unique characteristics such as increased antioxidant activity, antiproliferative and anti-inflammatory effects, as well as improving the viscoelasticity of polysaccharides (fucoidans, alginates, and κ-carrageenan) from macroalgae. In this sense, the tunable nature of DES enables the optimization of extraction conditions to maximize yield, purity, and bioactivity, making it a smart alternative for producing bio-based products. Despite limited literature on DES for this purpose, the article highlights their potential and outlines the main advantages and challenges needed for macroalgae valorization.

Predictors of climate change literacy in the era of global boiling: a cross-sectional survey of Egyptian nursing students

BACKGROUND

Climate changes have led to health and environmental risks, so it has become essential to measure climate change literacy among the entire population, especially nursing students. The significant role of nursing students in raising public awareness and future healthcare roles emphasizes assessing the predictors of climate change literacy among nursing students.

AIMS

This study seeks to identify the predictors of climate change literacy among nursing students in A Multi-Site Survey.

DESIGN

A multi-site descriptive cross-sectional study adheres to the guidelines outlined in A Consensus-Based Checklist for Reporting Survey Studies collected for five months, from the 1st of July 2023 to November 2023. The study participants comprise 10,084 nursing students from all 27 governments in Egypt. The researcher used the Predictors of Nursing Students' Climate Change Literacy scale in this study. Data was collected, with 25 min average time to complete. Backward multiple linear regression was used to identify these predictors.

RESULTS

In the current study, nursing students demonstrated a moderate understanding of climate science (mean score 14.38), communication and advocacy skills (mean score 14.41), and knowledge of adaptation and mitigation strategies (mean score 13.33). Climate health impacts (mean score 17.72) emerged as the domain with the highest level of knowledge. No significant differences in climate literacy were observed across diverse student backgrounds (all p-values were > 0.05). Perceived faculty knowledge of climate change positively correlated with all four domains of climate literacy and emerged as a significant predictor in multiple linear regression analyses (all p-values were < 0.001).

IMPLICATION

While our findings highlight significant predictors of climate literacy, it is essential to recognize that these results identify associations rather than causal relationships. Based on these associations, it is recommended that nursing professionals be equipped with comprehensive knowledge of climate adaptation strategies to better advocate for and implement effective public health measures.

Triple planetary crisis: why healthcare professionals should care

Humanity currently faces an ecological crisis with devastating consequences to all living species. While climate change is estimated to lead to 250,000 extra deaths per year between 2030 and 2050, pollution is known to cause 9 million premature deaths: a figure much greater than the deaths caused by AIDS, tuberculosis and malaria combined. The healthcare sector is both burdened by, and contributes to, the impact of climate change and environmental degradation. Amidst glaring evidence of the interdependence of human health and the eco system, there is an urgent call for healthcare professionals to concern themselves with the triple planetary threat humanity currently faces. Without immediate mitigative measures, the future seems uncertain. Some healthcare systems at local, national and global levels have taken numerous initiatives to address, mitigate and adapt to these changes, however, these are not sufficient. A lack of awareness among healthcare professionals of the ecological crisis, its interconnectedness, and the role of healthcare in it, plays a significant role in the lack responsibility of healthcare professionals in this space. Therefore, this paper presents a discussion of the current landscape of the triple threat of climate change, loss of biodiversity, and pollution, while emphasising the contribution of healthcare professionals to it. Furthermore, interrelated concepts such as planetary health and eco-anxiety are briefly discussed. This perspective paper also presents several key prospective research areas that may lay the foundation for motivating healthcare professionals to play an active role in preventing and mitigating the ecological crises humanity currently faces.

Applying Digital Technology to Understand Human Experiences of Climate Change Impacts on Food Security and Mental Health: Scoping Review

BACKGROUND

The global impact of climate change ranges from intense heatwaves to extreme weather events that endanger entire ecosystems and people's way of life. Adverse climate change events place undue stress on food and health systems, with consequences for human food security and mental health status. Ubiquitous digital devices, such as smartphones, have the potential to manage existing and emerging climate-related crises, given their ability to enable rapid response, instant communication, and knowledge sharing.

OBJECTIVE

This scoping review aimed to identify digital apps being used to capture or address climate change impacts on food security and mental health to inform the development of a digital citizen science initiative.

METHODS

A scoping review was conducted using 3 peer-reviewed databases (PubMed, IEEE Xplore, and Web of Science) and manual gray literature searches of relevant organizational (ie, governmental and nonprofit) websites to identify articles and reports published between January 2012 and July 2023. Three separate searches were conducted in each database to identify digital apps focused on climate change and (1) food security, (2) mental health, and (3) food security and mental health. Two reviewers conducted initial screening, with a third reviewer resolving any discrepancies. Articles focused on climate change impacts on wildlife or agriculture (ie, not human food security) were excluded. Full-text screening was conducted for shortlisted articles, and a final data abstraction table was generated, summarizing key app features, contextual factors, and participant involvement.

RESULTS

From the 656 records screened, 14 digital apps met the inclusion criteria. The food security apps (n=7, 50%) aimed to capture traditional knowledge to preserve food systems, conduct food security assessments, and aid users in decreasing food insecurity risk. The mental health apps (n=7, 50%) assessed climate change-related stress and provided users with coping strategies following adverse weather events. No digital apps examined the intersection of climate change, food security, and mental health. Key app features included user-to-user communication (n=5, 36%), knowledge databases (n=5, 36%), data collection and analysis (n=3, 21%), gamification (n=1, 7%), and educational resources (n=2, 14%) to address climate change impacts on food security or mental health. In total, 3 approaches to participant involvement were used across studies, including contributory (n=1, 7%), collaborative (n=1, 7%), and cocreative (n=1, 7%) approaches, to ensure the relevance and use of digital apps.

CONCLUSIONS

Most digital apps identified provided a service to citizens to either prevent adverse climate change-related health impacts or manage these effects following an acute event or a natural disaster. The capacity of ubiquitous digital tools to enable near real-time communication, the involvement of various stakeholder groups, and their ability to share relevant educational resources in a timely manner are important for developing tailored climate change adaptation and mitigation strategies across jurisdictions.

Public environmental concern, government environmental regulation and urban carbon emission reduction-Analyzing the regulating role of green finance and industrial agglomeration

In the multifaceted realm of environmental governance, emphasizing public environmental participation as an informal regulatory mechanism, alongside the influence of formal governmental environmental regulation on regional carbon emissions, contributes to providing empirical evidence and policy insights for China's "dual‑carbon target" action plan. Using data from 282 prefecture-level cities in China from 2011 to 2020, this research develops an analytical framework for urban carbon emissions encompassing public environmental concern, environmental regulation, green finance, and industrial agglomeration. And through an amalgamation of theoretical insights and empirical validation, the study elucidates the mechanisms by which public environmental concern impact urban carbon emissions. It further delves into the mediating role of environmental regulation and the moderating effects of green finance and industrial agglomeration. It reveals that: (1) Public environmental concern significantly reduces urban carbon emissions, particularly in northern cities, non-environmental protection key cities, and resource regeneration cities. And this suppressive influence is markedly more potent via mobile platforms compared to PC channels; (2) Environmental regulation serves as a partially mediating role between public environmental concern and urban carbon emissions, suggesting that public environmental concern reduces emissions by amplifying governmental environmental oversight; (3) Both green finance and industrial agglomeration play a positive moderating role on the effect of public environmental concern in reducing urban carbon emissions.

Predicting carbon dioxide emissions in the United States of America using machine learning algorithms

Carbon dioxide (CO2) emissions result from human activities like burning fossil fuels. CO2 is a greenhouse gas, contributing to global warming and climate change. Efforts to reduce CO2 emissions include transitioning to renewable energy. Monitoring and reducing CO2 emissions are crucial for mitigating climate change. Strategies include energy efficiency and renewable energy adoption. In the past few decades, several nations have experienced air pollution and environmental difficulties because of carbon dioxide (CO2) emissions. One of the most crucial methods for regulating and maximizing CO2 emission reductions is precise forecasting. Four machine learning algorithms with high forecasting precision and low data requirements were developed in this study to estimate CO2 emissions in the United States (US). Data from a dataset covering the years 1973/01 to 2022/07 that included information on different energy sources that had an impact on CO2 emissions were examined. Then, four algorithms performed the CO2 emissions forecast from the layer recurrent neural network with 10 nodes (L-RNN), a feed-forward neural network with 10 nodes (FFNN), a convolutional neural network with two layers with 10 and 5 filters (CNN1), and convolutional neural network with two layers and with 50 and 25 filters (CNN2) models. Each algorithm's forecast accuracy was assessed using eight indicators. The three preprocessing techniques used are (1) without any processing techniques, (2) processed using max-min normalization technique, and (3) processed using max-min normalization technique and decomposed by variation mode decomposition (VMD) technique with 7 intrinsic mode functions and 1000 iterations. The latter with L-RNN algorithm gave a high accuracy between the forecasting and actual values. The results of CO2 emissions from 2011/05 to 2022/07 have been forecasted, and the L-RNN algorithm had the highest forecast accuracy. The L-RNN model has the lowest value of 1.187028078, 135.5668592, and 11.64331822 for MAPE, MSE, and RMSE, respectively. The L-RNN model provides precise and timely forecasts that can help formulate plans to reduce carbon emissions and contribute to a more sustainable future. Moreover, the results of this investigation can improve our comprehension of the dynamics of carbon dioxide emissions, resulting in better-informed environmental policies and initiatives targeted at lowering carbon emissions.

Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review

The recent advancements made in the realms of Artificial Intelligence (AI) and Artificial Intelligence of Things (AIoT) have unveiled transformative prospects and opportunities to enhance and optimize the environmental performance and efficiency of smart cities. These strides have, in turn, impacted smart eco-cities, catalyzing ongoing improvements and driving solutions to address complex environmental challenges. This aligns with the visionary concept of smarter eco-cities, an emerging paradigm of urbanism characterized by the seamless integration of advanced technologies and environmental strategies. However, there remains a significant gap in thoroughly understanding this new paradigm and the intricate spectrum of its multifaceted underlying dimensions. To bridge this gap, this study provides a comprehensive systematic review of the burgeoning landscape of smarter eco-cities and their leading-edge AI and AIoT solutions for environmental sustainability. To ensure thoroughness, the study employs a unified evidence synthesis framework integrating aggregative, configurative, and narrative synthesis approaches. At the core of this study lie these subsequent research inquiries: What are the foundational underpinnings of emerging smarter eco-cities, and how do they intricately interrelate, particularly urbanism paradigms, environmental solutions, and data-driven technologies? What are the key drivers and enablers propelling the materialization of smarter eco-cities? What are the primary AI and AIoT solutions that can be harnessed in the development of smarter eco-cities? In what ways do AI and AIoT technologies contribute to fostering environmental sustainability practices, and what potential benefits and opportunities do they offer for smarter eco-cities? What challenges and barriers arise in the implementation of AI and AIoT solutions for the development of smarter eco-cities? The findings significantly deepen and broaden our understanding of both the significant potential of AI and AIoT technologies to enhance sustainable urban development practices, as well as the formidable nature of the challenges they pose. Beyond theoretical enrichment, these findings offer invaluable insights and new perspectives poised to empower policymakers, practitioners, and researchers to advance the integration of eco-urbanism and AI- and AIoT-driven urbanism. Through an insightful exploration of the contemporary urban landscape and the identification of successfully applied AI and AIoT solutions, stakeholders gain the necessary groundwork for making well-informed decisions, implementing effective strategies, and designing policies that prioritize environmental well-being.

Digitization and carbon emissions: how does the development of China's digital economy affect carbon intensity?

The digital economy and the pursuit of carbon peak and carbon neutrality have emerged as crucial focal points for China's future development. However, the intricate relationship between the digital economy and carbon intensity remains uncertain. Based on the construction of the digital economy evaluation index system, using panel data for 30 provinces in China from 2011 to 2019, this study estimates the impact of the digital economy development on carbon intensity by adopting the system-generalized method of moments (SYS-GMM) technique. The results show that the digital economy can effectively reduce the carbon intensity. This conclusion was supported by robustness tests. However, the carbon emission reduction effect of the digital economy exhibits heterogeneity with respect to the digital economy dimensions and regions. In addition to digital industrialization and industrial digitization reducing the carbon intensity, the digital economy development carrier has an inverted U-shaped nonlinear relationship with carbon intensity. Additionally, the digital economy has a more obvious inhibitory effect on carbon intensity in the eastern region. Most importantly, besides the mediating effects of technological progress and financial development, this paper finds that the digital economy can increase carbon intensity through human capital accumulation. These conclusions provide a certain scientific basis for the effective implementation of China's digital economy and carbon peak and carbon-neutral development strategy.

Tree-structured parzen estimator optimized-automated machine learning assisted by meta-analysis for predicting biochar-driven N2O mitigation effect in constructed wetlands

Biochar is a carbon-neutral tool for combating climate change. Artificial intelligence applications to estimate the biochar mitigation effect on greenhouse gases (GHGs) can assist scientists in making more informed solutions. However, there is also evidence indicating that biochar promotes, rather than reduces, N2O emissions. Thus, the effect of biochar on N2O remains uncertain in constructed wetlands (CWs), and there is not a characterization metric for this effect, which increases the difficulty and inaccuracy of biochar-driven alleviation effect projections. Here, we provide new insight by utilizing machine learning-based, tree-structured Parzen Estimator (TPE) optimization assisted by a meta-analysis to estimate the potency of biochar-driven N2O mitigation. We first synthesized datasets that contained 80 studies on global biochar-amended CWs. The mitigation effect size was then calculated and further introduced as a new metric. TPE optimization was then applied to automatically tune the hyperparameters of the built extreme gradient boosting (XGBoost) and random forest (RF), and the optimum TPE-XGBoost obtained adequately achieved a satisfactory prediction accuracy for N2O flux (R2 = 91.90%, RPD = 3.57) and the effect size (R2 = 92.61%, RPD = 3.59). Results indicated that a high influent chemical oxygen demand/total nitrogen (COD/TN) ratio and the COD removal efficiency interpreted by the Shapley value significantly enhanced the effect size contribution. COD/TN ratio made the most and the second greatest positive contributions among 22 input variables to N2O flux and to the effect size that were up to 18% and 14%, respectively. By combining with a structural equation model analysis, NH4+-N removal rate had significant negative direct effects on the N2O flux. This study implied that the application of granulated biochar derived from C-rich feedstocks would maximize the net climate benefit of N2O mitigation driven by biochar for future biochar-based CWs.

Green growth path dependence momentum under the prism of COP26: the role of financial deepening, ICT development, and export diversification

Financial deepening is important in resource allocation for more productive enterprises, leading to sustainable green growth. Moreover, rapid development in the digital economy and export diversification significantly affect green growth. From this perspective, our study explores the impact of financial deepening, ICT development, and export diversification on green growth in China's economies from 1996 to 2021. The study explores the linkage between financial deepening, ICT development, export diversification, and green growth by employing the nonlinear autoregressive distributed lag (NARDL) approach. The results obtained in the long run are as follows: positive shock in financial deepening brings positive change in green growth, whereas negative shock in financial deepening reduces green growth. In the long run, positive shock in ICT enhances green growth, but negative shock in ICT does not impact green growth. Moreover, positive shock in export diversification brings positive change in green growth, whereas negative shock in export diversification reports an insignificant impact on green growth. Based on findings, it is suggested that financial deepening, ICT development, and export diversification are conducive to sustainable green growth.

Is green FinTech reshaping the finance sphere? Unravelling through a systematic literature review

The revolutionary and transformative potential of FinTech has led to the Green Digital Finance Alliance, noting the dawn of a new era of FinTech-"the green FinTech", yet, surprisingly, the scholarly exploration surrounding climate finance in general and green FinTech and climate FinTech remains restrained. In our attempt to decode the intricate interlinkage between green finance and FinTech, the study wrestles with the theoretical complexity of the "green FinTech" concept through a systematic review of relevant studies and conceptual mapping. We develop a comprehensive grasp of the concept, how to leverage it to combat the pressing climate crisis, and its implications for the FinTech segment-the first of its kind in the scanty green FinTech literature. Based on the PRISMA analysis, we find that green FinTech promotes a green economy through its manifold impact on all aspects of the finance sphere, thereby channelling climate finance and promoting sustainability. It has the power to heighten inclusivity, disclosure, trust, and democratisation, thus reducing information asymmetry and greenwashing. Hence, FinTech integration can be game-changing in eliminating the hurdles before conventional green finance. However, the literature remains fragmented, along with a young, growing green FinTech market. Therefore, this study proposes a framework for future researchers by providing a holistic research agenda to fully integrate "green FinTech" into practical real-world applications.

Development and evaluation of a hybrid smart solar dryer

A hybrid smart solar dryer (HSSD) based on indirect forced convection and a controlled auxiliary heating system was developed, fabricated, and tested to be convenient for sunny and cloudy weather conditions. The achievements of the developed dryer focus on controlling the temperature of the dryer, increasing the drying rate, reducing energy consumption, and providing high-quality products. The HSSD was tested and evaluated for drying basil and sage herbs at 30, 40, and 50°C. The results showed that the fresh basil and sage leaves of 1 kg with a moisture content of 84.7% and 75.53% (wet basis) were dried within 58, 46, 32 and 38, 28, and 20 h at 30, 40, and 50°C, respectively. Correspondingly, the traditional drying methods achieved 96 h outdoors and 144 h indoors at room temperature. The average of the fabricated flat-plate solar collector efficiency (thermal efficiency, ηfpsc ) was ranged from 49.18% ± 9.52% to 66.02% ± 2.8%. The highest drying rates were achieved with the HSSD method. Moreover, the HSSD method led to a remarkable saving in energy with values ranging from 25.54% to 77.1% versus the traditional drying methods. While the best quality in terms of essential oil content and microbial load for the dried basil and sage herbs was achieved by the HSSD at 40°C. Finally, the HSSD is a promising energy-efficient method where it can save 70% of energy consumption, thus reducing the carbon footprint of drying processes, and providing higher quality products compared to the conventional methods.

European citizens' stance on limiting energy use for climate change mitigation

Citizens' attitudes and beliefs towards climate change are decisive in the adoption of mitigating measures. Limiting the use of energy in the context of climate change can be one of the mitigation measures, and therefore, understanding the position of the citizens towards it is important. With this aim, we used data from the 10th European Social Survey to relate the European citizens' beliefs and attitudes on limiting the use of energy to tackle climate change. We have used variables related to demography and individuals' perception of society and its policies. Statistical models were successfully fitted to data. Individuals with higher levels of trust in scientists have a higher degree of satisfaction with the national economies, are more worried about climate change and are more capable of assuming self-responsibility in climate change mitigation. These individuals have higher probabilities of believing that climate change mitigation could be achieved by limiting the use of energy. The EU citizens are, however, very skeptical in relation to the probability of many other citizens adopting measures to limit the use of energy.

What affects China's green finance? Evidence from cryptocurrency market, oil market, and economic policy uncertainty

This paper discusses the dynamic long- and short-term effects of bitcoin price (BTP), crude oil price (COP), and uncertainty of economic policy (EPU) on China's green bond (CGB) market, separately. Depending on the quantile autoregressive distributed lag method, the empirical results are shown that BTP and EPU exert substantial positive and negative effects on the CGB market in the long term for most circumstances, while their effects reflect not prominent in the short term. The main contributions can be summarized as follows. Given that China is the largest bitcoin mining state and a major green bond issuer, this study first explores the linkages between them. Furthermore, both long- and short-term effects are investigated from BTP, COP, and EPU to CGB, and long-term effects are dominated in the interrelationships among variables, indicating that the CGB market is mainly driven by permanent shocks. In addition, the mentioned long-term effects are deeply discussed from time- and quantile-varying aspects. This approach considers diverse situations in the bond market and various incidents that occur at various durations of time. The results underscore the significance of market participants gaining a deeper comprehension of how BTP, COP, and EPU impact green bond within varying market conditions. Implementing specific policies, such as establishing a cohesive and efficient bond market and making careful adjustments to economic policies, can be advantageous in maintaining stability within the CGB market.

Exploring the Darkverse: A Multi-Perspective Analysis of the Negative Societal Impacts of the Metaverse

The Metaverse has the potential to form the next pervasive computing archetype that can transform many aspects of work and life at a societal level. Despite the many forecasted benefits from the metaverse, its negative outcomes have remained relatively unexplored with the majority of views grounded on logical thoughts derived from prior data points linked with similar technologies, somewhat lacking academic and expert perspective. This study responds to the dark side perspectives through informed and multifaceted narratives provided by invited leading academics and experts from diverse disciplinary backgrounds. The metaverse dark side perspectives covered include: technological and consumer vulnerability, privacy, and diminished reality, human-computer interface, identity theft, invasive advertising, misinformation, propaganda, phishing, financial crimes, terrorist activities, abuse, pornography, social inclusion, mental health, sexual harassment and metaverse-triggered unintended consequences. The paper concludes with a synthesis of common themes, formulating propositions, and presenting implications for practice and policy.

Contribution of anthropogenic pollutant sources to greenhouse gas emissions: a case study from a developing country

Anthropogenic greenhouse gas (GHG) emissions are the primary cause of climate change, one of the biggest challenges for humankind. To tackle this problem, the international community is looking for ways to reduce GHG emissions. To create reduction strategies in a city/province/country, there is a need for an inventory that provides emission amounts from different sectors. This study aimed to develop a GHG emission inventory for Karaj, a megacity in Iran, using international guidelines such as AP-42 and ICAO, and IVE software. The emissions of mobile sources were accurately calculated by a bottom-up method. The results showed that power plant with 47% of the total emissions is the primary GHG contributor in Karaj. Residential and commercial units with 27% and mobile sources with 24% of the total emissions play a critical role in emitting GHGs in Karaj. On the other hand, the industrial units and the airport have negligible (2%) contribution to the total emissions. Subsequent estimates showed that GHG emissions per capita and per GDP of Karaj were 6.03 t per person and 0.47 t per thousand US dollars, respectively. These amounts are higher than the global averages (4.97 t per person and 0.3 t per thousand US dollars). The relatively high GHG emissions in Karaj are due to the sole reliance on the consumption of fossil fuels. To reduce emissions, mitigation strategies such as developing renewable energy sources, switching to low-emission transportation, and raising public awareness should be implemented.

Financial development-green growth nexus in China: the role of technological capital

It is undeniable fact that financial development and technological capital are fundamental determinants that help in the achievement of green growth. This is important to explore the nexus between financial development, technological capital, and green growth in China. This study utilizes the quantile autoregressive distributed lag (QARDL) approach for exploring the effect of financial development and technological capital on green growth. The study measures financial development through financial market development and financial institutions development. The study concludes that technological progress and both measures of financial development produce a positive impact on green growth in China in most quantities in long run. The study provides various important policy suggestions that help in upgrading sustainable green growth in China.

Environmentally sustainable smart cities and their converging AI, IoT, and big data technologies and solutions: an integrated approach to an extensive literature review

There have recently been intensive efforts aimed at addressing the challenges of environmental degradation and climate change through the applied innovative solutions of AI, IoT, and Big Data. Given the synergistic potential of these advanced technologies, their convergence is being embraced and leveraged by smart cities in an attempt to make progress toward reaching the environmental targets of sustainable development goals under what has been termed "environmentally sustainable smart cities." This new paradigm of urbanism represents a significant research gap in and of itself. To fill this gap, this study explores the key research trends and driving factors of environmentally sustainable smart cities and maps their thematic evolution. Further, it examines the fragmentation, amalgamation, and transition of their underlying models of urbanism as well as their converging AI, IoT, and Big Data technologies and solutions. It employs and combines bibliometric analysis and evidence synthesis methods. A total of 2,574 documents were collected from the Web of Science database and compartmentalized into three sub-periods: 1991-2015, 2016-2019, and 2020-2021. The results show that environmentally sustainable smart cities are a rapidly growing trend that markedly escalated during the second and third periods-due to the acceleration of the digitalization and decarbonization agendas-thanks to COVID-19 and the rapid advancement of data-driven technologies. The analysis also reveals that, while the overall priority research topics have been dynamic over time-some AI models and techniques and environmental sustainability areas have received more attention than others. The evidence synthesized indicates that the increasing criticism of the fragmentation of smart cities and sustainable cities, the widespread diffusion of the SDGs agenda, and the dominance of advanced ICT have significantly impacted the materialization of environmentally sustainable smart cities, thereby influencing the landscape and dynamics of smart cities. It also suggests that the convergence of AI, IoT, and Big Data technologies provides new approaches to tackling the challenges of environmental sustainability. However, these technologies involve environmental costs and pose ethical risks and regulatory conundrums. The findings can inform scholars and practitioners of the emerging data-driven technology solutions of smart cities, as well as assist policymakers in designing and implementing responsive environmental policies.

Effect of environmental taxes on environmental innovation and carbon intensity in China: an empirical investigation

Environmental taxes are deemed to be an important carbon mitigating factor and also encourage the producers to adopt environmentally friendly technologies. Therefore, the main objective of the analysis is to evaluate the environmental taxes on environmental innovations and carbon intensity in China. The novel quantile autoregressive distributed lag (QARDL) is applied to investigate the model empirically. From the results, we confer that the short and long run estimated coefficients of environmental taxes are positive and significant at most quantiles in the environmental innovation model, implying that the higher the rate of environmental taxes, the higher the rate of environment-related innovations. However, the estimates of environmental taxes are significant and negative in both short and long run at more than half quantiles in the carbon emissions model, suggesting the positive role of environmental taxes in reducing carbon emissions. In general, our findings imply that an increase in environment-related taxes helps reduce carbon intensity and promote environmental innovation in China. The study suggests that policymakers in China should promote environmental innovation and expand the environmental tax base to achieve the objective of carbon neutrality.

How Avatar Identification Affects Enjoyment in the Metaverse: The Roles of Avatar Customization and Social Engagement

Despite growing interest in studying the metaverse, a theory-driven investigation into the factors that contribute to an enjoyable metaverse experience remains scarce. The current study examined the impacts of avatar identification, social engagement, and avatar customization on users' enjoyment of the metaverse based on the impression management theory. A total of 301 metaverse users were recruited for the study. The hypothesized models of mediation effect of social engagement and moderation effect of avatar customization were tested between avatar identification and enjoyment. Results indicated that social engagement mediates the relationship between avatar identification and enjoyment in metaverse participation. Furthermore, the significant moderation effect implied that the degree of avatar customization affected the relationship between avatar identification and enjoyment in the metaverse. Empirical evidence from this study contributes to theorizing the transformative role of social engagement and conditional effects based on avatar customization in shaping a positive emotion (i.e., enjoyment) from a metaverse experience. The findings allow researchers and practitioners to gain an initial understanding of the factors contributing to a favorable metaverse experience.

Sustainable Soil Management: Effects of Clinoptilolite and Organic Compost Soil Application on Eco-Physiology, Quercitin, and Hydroxylated, Methoxylated Anthocyanins on Vitis vinifera

Climate change and compostinS1g methods have an important junction on the phenological and ripening grapevine phases. Moreover, the optimization of these composting methods in closed-loop corporate chains can skillfully address the waste problem (pomace, stalks, and pruning residues) in viticultural areas. Owing to the ongoing global warming, in many wine-growing regions, there has been unbalanced ripening, with tricky harvests. Excessive temperatures in fact impoverish the anthocyanin amount of the must while the serious water deficits do not allow a correct development of the berry, stopping its growth processes. This experiment was created to improve the soil management and the quality of the grapes, through the application of a new land conditioner (Zeowine) to the soil, derived from the compost processes of industrial wine, waste, and zeolite. Three treatments on a Sangiovese vineyard were conducted: Zeowine (ZW) (30 tons per ha), Zeolite (Z) (10 tons per ha), and Compost (C) (20 tons per ha). During the two seasons (2021-2022), measurements were made of single-leaf gas exchange and leaf midday water potential, as well as chlorophyll fluorescence. In addition, the parameters of plant yield, yeast assimilable nitrogen, technological maturity, fractionation of anthocyanins (Cyanidin-3-glucoside, Delphinidin-3-glucoside, Malvidin-3-acetylglucoside, Malvidin-3-cumarylglucoside, Malvidin-3-glucoside, Peonidin-3-acetylglucoside, Peonidin-3-cumarylglucoside, Peonidin-3-glucoside, and Petunidin-3-glucoside), Caffeic Acid, Coumaric Acid, Gallic Acid, Ferulic Acid, Kaempferol-3-O-glucoside, Quercetin-3-O-rutinoside, Quercetin-3-O-glucoside, Quercetin-3-O-galactoside, and Quercetin-3-O-glucuronide were analyzed. The Zeowine and zeolite showed less negative water potential, higher photosynthesis, and lower leaf temperature. Furthermore, they showed higher levels of anthocyanin accumulation and a lower level of quercetin. Finally, the interaction of the beneficial results of Zeowine (soil and grapevines) was evidenced by the embellishment of the nutritional and water efficiency, the minimizing of the need for fertilizers, the closure of the production cycle of waste material from the supply chain, and the improvement of the quality of the wines.

On energy transition-led sustainable environment in COP26 era: policy implications from tourism, transportation services, and technological innovations for Gulf countries

The present generation is witnessing the most devastating effects of global warming far beyond what was evident in the pre-industrial era. To forestall further ecosystem destruction, nations are working assiduously toward achieving sustainable global environment in decades to come, specifically by 2050. This ambitious goal prompts the convergence of countries in the last climate conference tagged COP26 which provides the roadmap to global sustainability. The resolutions of COP26 motivate the present study to assess the energy transition-led sustainable environment in Gulf countries, considering tourism, transport services, and technological innovation. The study employs annual data from 2005 to 2019 by relying on advanced second-generation estimators comprising cross-sectional ARDL (CS-ARDL), common correlated effects mean group (CCEMG), and augmented mean group (AMG). The study conducts robustness checks using quantile regression (QR) and quantile plots (QP). The results reveal that nonrenewable energy, tourism, and transport services hinder sustainable environment due to their inducing impacts on carbon emissions. Renewable energy and technological innovations promote sustainable environment by moderating the surge in carbon emissions. The QR results reveal that the regressors' effects are not one-off. For instance, the moderating effects of renewable energy correspond to increasing levels of the quantiles. In contrast, nonrenewable energy posits the opposite, thus confirming the energy transition-led sustainable environment hypothesis in the Gulf countries. Policy implications that drive sustainable environment are suggested based on the findings.

Modeling of carbon dioxide fixation by microalgae using hybrid artificial intelligence (AI) and fuzzy logic (FL) methods and optimization by genetic algorithm (GA)

In this study, we are reporting a novel prediction model for forecasting the carbon dioxide (CO₂) fixation of microalgae which is based on the hybrid approach of adaptive neuro-fuzzy inference system (ANFIS) and genetic algorithm (GA). The CO₂ fixation rate of various algal strains was collected and the cultivation conditions of the microalgae such as temperature, pH, CO₂ %, and amount of nitrogen and phosphorous (mg/L) were taken as the input variables, while the CO₂ fixation rate was taken as the output variable. The optimization of ANFIS parameters and the formation of the optimized fuzzy model structure were performed by genetic algorithm (GA) using MATLAB in order to achieve optimum prediction capability and industrial applicability. The best-fitting model was figured out using statistical analysis parameters such as root mean square error (RMSE), coefficient of regression (R²), and average absolute relative deviation (AARD). According to the analysis, GA-ANFIS model depicted a greater prediction capability over ANFIS model. The RMSE, R², and AARD for GA-ANFIS were observed to be 0.000431, 0.97865, and 0.044354 in the training phase and 0.00056, 0.98457, and 0.032156 in the testing phase, respectively, for the GA-ANFIS Model. As a result, it can be concluded that the proposed GA-ANFIS model is an efficient technique having a very high potential to accurately predict the CO₂ fixation rate.

Analyzing the nexus between energy transition, environment and ICT: A step towards COP26 targets

In line with the Sustainable Development Goals and the recent COP26 summit, energy transition, low carbon emissions and technology have become extremely important subjects in the agenda of governments and policymakers. The present study thus discusses the nexus between energy transition, economic growth, CO₂ emissions and information and communications technology (ICT) in BRICS countries applying the novel GMM-PVAR method proposed on the annual data for the period 2000-2017. This method is strong to the issue of endogeneity which is commonly faced in the context of panel data analysis but mostly ignored in the literature. The findings of this research demonstrate that carbon emissions have a positive and significant effect on energy transition; similarly, raising economic growth augments the consumption of energy transition. Furthermore, ICT is found to be a significant choice in the development of energy transition and the solution of environmental challenges. Overall, technological factors in addition to economic and environmental factors also have great roles in the development of renewable energy and energy transition. Thus, results from this study call for government supports to develop ICT across the BRICS countries.

The effect of mandatory environmental regulation on green development efficiency: evidence from China

The existing literature finds that mandatory environmental regulation (MER) can significantly reduce environmental pollution. However, much less is known about how the implementation of MER affects green development efficiency (GDE). Based on the Air Pollution Control Action Plan which was enforced in 2013 in China's most developed regions as an exogenous shock, we find that first, MER has a significant negative effect on the improvement of GDE by reducing regional scale efficiency. Second, MER mainly reduces the GDE of cities with stronger regulation intensities and with larger economic volumes. Third, MER also has a negative impact on regional green total factor productivity by changing technical progress. We suggest that when implementing MER, governments should enhance regional and global cooperation, promote green technology, and use comprehensive policy tools to stimulate firms' green innovation.

The differences of climate change perception, responsibility and climate-friendly behavior among generations and the main determinants of youth's climate-friendly actions in the EU

The role of society to mitigate climate change is particularly important. However, generations, different age cohorts are differently related to and concerned about climate change. The main criticism of the young generation is that they talk about climate change a lot but do not behave in a climate-friendly manner. Therefore, the aim of this paper is to analyze the difference of climate change perception, responsibility and climate-friendly behavior among Baby Boomer generation, Generations X, Y and Z in all European Union (EU) countries. After applying the Chi-square test, the results showed that younger people in the EU tend to have the perception of climate change more often than their older counterparts. Moreover, people from younger generations tend to place responsibility of solving climate change on the business/industrial sectors and environmental groups more often than the preceding generations do. Furthermore, more of young people assumed personal responsibility, used environmentally friendly alternatives to personal cars, and considered carbon footprint before purchasing a product, as opposed to older generations. However, the youth separated waste and decreased the use of disposable items less comparing with older generations. Applying binary logistic regression, the results showed that climate change perception and placement of responsibility on environmental groups positively and statistically significantly influenced all climate-friendly actions of the youth. Personal responsibility statistically significantly decreased probability of all climate-friendly actions. Responsibility placement on the government and business/industrial sectors reduced the probability to carry out waste reduction behavior. Thus, this study revealed that young people are not always climate-friendly, and this study provides the insights into how to promote climate-friendly behavior among youths.

Medical informatics and climate change: a framework for modeling green healthcare solutions

OBJECTIVE

The aim of this study was to develop a theory-based framework to enhance and accelerate development, selection, and implementation of solutions mitigating the climate impact of healthcare organizations.

MATERIALS AND METHODS

Existing frameworks were combined to develop the Green-MIssion (Medical Informatics Solutions) framework. It was further developed and refined by mapping solutions from project plans and reviewing it with an expert panel.

RESULTS

The framework classifies solutions into three categories: (1) monitor and measure environmental impact of a healthcare setting; (2) help create and increase awareness among employees and patients; and (3) interventions to reduce environmental impacts.

DISCUSSION AND CONCLUSION

The framework combines concepts from healthcare information technology and environmental sciences and can be used to structure green medical informatics solutions for different healthcare settings. Furthermore, research should evaluate its application for measuring and assessing the impact of green medical informatics solutions on environmental sustainability and climate resilience.

Impact of urbanization, industrialization, electrification and renewable energy on the environment in BRICS: fresh evidence from novel CS-ARDL model

Increased demand for water, energy, infrastructure, and other natural resources has resulted from an increase in anthropocentric activities recently, which has led to climate change, land erosion, pollution growth, and a decline in biodiversity. During the period 1972-2021, the aim of this study is how industrialization, urbanization, and renewable energy affect the environment of five industrialized economies-Brazil, Russia, India, China, and South Africa (BRICS)-implemented. Concerning slope heterogeneity, cross-sectional dependence (CSD), and a mixture of I (0) and I (1) variables, this paper used a fresh panel technique known as cross-sectionally augmented autoregressive distributive lag (CS-ARDL). When it comes to protecting water, land, and forest resources while also lowering carbon emissions, the estimate of energy, urbanization, electrification, and industrialization is favorably substantial. The findings show that rising industrialization, urbanization, income, and electrification can stimulate environmental degradation. On the other hand, renewable energy in industrialized economies may significantly lessen the environmental degradation in the BRICS region. In the BRICS region recently, urbanization is booming, all countries are expanding industrial zones, and consumption of electricity is skyrocketing. So, this research is very important in the BRICS context. The research also applied an augmented mean group (AMG) to get the impact of all variables on the environment in all BRICS countries. Because of their different economic sizes, public policy, industrial policy, population policy, immigration, and trade policy, the magnitude of impacts and signs of impacts are different. There is some evidence to suggest that renewables may be a panacea for BRICS energy security and environmental deterioration; consequently, boosting alternative energy sources, green urbanization, and environmentally-friendly urbanization should be a part of all governments' energy and environmental plans worldwide. Hence, these countries' decision-makers should re-review their population, energy, urbanization, and industrial policies to adopt a sustainable environment.

Adopting net-zero in emerging economies

In recent years, rapid reduction in natural resources alongside climate change has prompted industries to adopt sustainable operational practices. Globalization is arguably a boon for people and societies worldwide but has also led to significant disruptions to our natural ecosystem. Consequently, it has caused environmental concerns and issues around public health. The net-zero economy has recently emerged as a pivotal way to conserve the environment, mitigate health issues and address sustainable development goals (SDGs). The extant literature and relevant industrial reports have shown that automobiles significantly contribute to greenhouse gas emissions. Therefore, the current study is conducted to identify the critical success factors (CSFs) of net-zero adoption with respect to the automobile industry. The fuzzy decision-making trial and evaluation laboratory (DEMATEL) technique is applied to establish a dyadic relationship (cause-effect) among the identified CSFs. The top three CSFs are found to be focus on research and development activities, International Collaborations and Strategic Planning and Effective Roadmap. Finally, this study provides theoretical and practical implications for relevant industries to implement net-zero effectively.

A realistic perspective for CO2 triggered tuning of electrical conductivity

To seek sustainable CO₂ sequestration and conversion, an electrochemical cell has been investigated for carbon capture and utilization strategy (CCU). In this cell, atmospheric CO₂ is captured under ambient conditions and incorporated into power generation using zinc nanopowder as the catalyst. As a result, a method was developed to tune the electronic property of zinc by passing CO₂. It was observed that nearly three orders of magnitude of conductivity could be changed along with achieving a carbon capture strategy. The system also exhibited good stability. In this process, it was observed that efficient current generation could be achieved due to zinc's active participation as a catalyst. The detailed physicochemical characterizations of catalysts were also examined. XRD, FTIR and TEM analysis perform the structural and morphological characterization. The system performance was further investigated using different criteria.

Is #SDG13 Trending Online? Insights from Climate Change Discussions on Twitter

Anthropogenic activities over the past few decades have led to increased vulnerability of environmental and ecological stability on this planet. Accelerated climate change is one such subset of the environmental problems that threatens the very existence of humankind in twenty first century. Governments, United Nations (UN) and other humanitarian agencies across the globe have developed and devised strategies for climate action that requires grater public awareness and actions. Social media has played a vital role in information dissemination and raising public awareness of climate change in the digital era. To this aid, an upsurge has been documented in recent times regarding discussions over climate change with #SDG13 (Sustainable Development Goals) at its epicenter. Following the principles of Actor Network Theory (ANT) we analyzed a large volume of Twitter data to understand general citizens' perception and attitude towards climate change. Our findings unveil people's opinion on causes and concerns related to barriers of adopting a more sustainable consumption and lifestyle practice. There is also a growing apathy towards sluggish government actions that makes little difference. People were also found to exchange innovative concepts and measures towards mitigating the effects of climate change.

Climate change, human health, and the exposome: Utilizing OMIC technologies to navigate an era of uncertainty

Climate change is an anthropogenic phenomenon that is alarming scientists and non-scientists alike. The emission of greenhouse gases is causing the temperature of the earth to rise and this increase is accompanied by a multitude of climate change-induced environmental exposures with potential health impacts. Tracking human exposure has been a major research interest of scientists worldwide. This has led to the development of exposome studies that examine internal and external individual exposures over their lifetime and correlate them to health. The monitoring of health has also benefited from significant technological advances in the field of "omics" technologies that analyze physiological changes on the nucleic acid, protein, and metabolism levels, among others. In this review, we discuss various climate change-induced environmental exposures and their potential health implications. We also highlight the potential integration of the technological advancements in the fields of exposome tracking, climate monitoring, and omics technologies shedding light on important questions that need to be answered.