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This study investigates the efficiency of green bonds as a financial instrument for promoting renewable energy production, with a specific focus on their performance during the Covid-19 pandemic. Using a sample of 55 countries from 2014 to 2022 and employing the Fully Modified Ordinary Least Squares (FMOLS) model to address non-stationarity and cointegration of variables, we find that green bond issuance positively impacts overall renewable energy generation. However, when examining specific sources of green energy, we observe that wind energy benefits the most from green bond financing, while estimates show only marginal significance for hydro energy and no significance for solar energy. Finally, we find that the efficiency of green bonds diminished during the Covid-19 pandemic, but this effect was not uniform across all energy sources. The main implications of this research suggest that while green bonds are efficient tools for promoting wind energy, alternative financial tools are necessary to stimulate growth in the solar and hydro energy sectors. Additionally, the negative effect of Covid-19 highlights the need for more resilient financial instruments during economic crises., Competing Interests: Declaration of competing interest The authors declare they have no competing interests. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

To unravel the challenges in the global diffusion of climate-friendly technologies, this investigation analyzes the diffusion of climate change-related technologies across countries. By using an unbalanced panel of selected European countries over the period 1990-2020, this investigation quantifies the carbon dioxide (CO2) emission effects of the diffusion of climate change-related technologies that are mediated by imports, geographical and technological proximity and free diffusion of technologies. In this study, the effects of domestic development of climate change-related technologies, population and affluence are also accounted for, and the emission effects are estimated using a fixed-effects panel model with instrumental variables. The instrumental variable for foreign technology spillovers is based on the technology support policies adopted in foreign countries. As expected, international spillovers of climate-friendly technologies are negatively linked to CO2 emissions, thus promoting emission reductions across the region. Importantly, emission reductions in Europe are more strongly influenced by international technology spillovers than by domestic innovation activities. Moreover, while all the analyzed technology diffusion channels appear relevant, the results are the most robust regarding import-mediated technology spillovers. Insights from this study support policy recommendations, especially in the trade policy context., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Increasing textile production is associated with an environmental burden which can be decreased with an improved recycling system by digitalization. The collection of textiles is done with so-called curbside bins. Sensor technologies support dynamic-informed decisions during route planning, helping predict waste accumulation in bins, which is often irregular and difficult to predict. Therefore, dynamic route-optimization decreases the costs of textile collection and its environmental load. The existing research on the optimization of waste collection is not based on real-world data and is not carried out in the context of textile waste. The lack of real-world data can be attributed to the limited availability of tools for long-term data collection. Consequently, a system for data collection with flexible, low-cost, and open-source tools is developed. The viability and reliability of such tools are tested in practice to collect real-world data. This research demonstrates how smart bins solution for textile waste collection can be linked to a dynamic route-optimization system to improve overall system performance. The developed Arduino-based low-cost sensors collected actual data in Finnish outdoor conditions for over twelve months. The viability of the smart waste collection system was complemented with a case study evaluating the collection cost of the conventional and dynamic scheme of discarded textiles. The results of this study show how a sensor-enhanced dynamic collection system reduced the cost 7.4% compared with the conventional one. We demonstrate a time efficiency of -7.3% and that a reduction of 10.2% in CO2 emissions is achievable only considering the presented case study., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Antti Martikkala reports financial support and article publishing charges were provided by Tampere University. Bening Mayanti reports financial support was provided by University of Vaasa. Petri Helo reports financial support was provided by University of Vaasa. Andrei Lobov reports financial support was provided by Norwegian University of Science and Technology. Inigo Flores Ituarte reports financial support was provided by Tampere University., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Based on the commitment to improve environmental quality across European Union under the United Nations' Sustainable Development Goals and varying national goals, this study investigates the dynamic linkages between bureaucracy, socioeconomic factors, conventional fossil fuel energy consumption vis-à-vis aggregate fossil and disaggregate fossil (oil, coal, and gas) fuels and environmental quality in the panel of selected 25-EU nations for the period 1990-2017. The study employs relevant second-generation empirical method and unearth the following results: (1) inverted environmental Kuznets curve was validated while fossil fuel consumption has a deteriorating impact on environmental performance due to its positive effect on carbon emission; (2) fossil fuel energy consumption (both aggregate and it components) exerts a dampening impact on environmental performance due to its positive effect on carbon emission; (3) that direct effect of bureaucracy and socioeconomic factors promote environmental quality but the degree or magnitude of influence is significantly different between bureaucratic system and socioeconomic factor, and (4) the moderating or indirect impact of bureaucracy, socioeconomic on the environment via fossil fuel energy consumption is observed and significantly different across the model specification. Moreover, the result reveals a unidirectional causal relationship flows from GDP per capita, bureaucracy and socioeconomic factors to carbon emission, while bi-directional relationships between oil, gas and carbon emission are established. In policy direction, the study therefore recommend that the European Union member countries should further explore the opportunities in clean energy development in order to ameliorate the continent's environmental concerns. Furthermore, in the quest to scale up the bloc's energy transition, significant improvement in the countries' bureaucracy establishment and socioeconomic conditions could hasten the energy transition and efficiency policy while improving the environmental sustainability drive., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)