• Energy Research
• 12. Responsible consumption close
• 7. Clean energy close
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Voice search based on artificial intelligence is the fastest means of searching for information and can be easily used in a very familiar way by ordinary users without separate education or learning. Voice bot’s voice search can interact on the same level as face-to-face communication and provide customized services optimized for users. It is most important for these new technologies to develop from a non-face-to-face social structure caused by COVID-19 to a long-term sustainable technology rather than short-term development. Therefore, the purpose of this study is to empirically verify the structural relationship between the quality, interactivity, and consumers’ sustainable use intentions for voice search services called ‘voice bots’ in Korea, an advanced country of computer science and technology. A survey was conducted on Korean consumers aged 20 or older who use voice search services, and the following main results were derived. First, the playfulness, certainty, and empathy of the ‘voice bot’ have a positive effect on the interactivity with the ‘voice bot’. Second, interactivity with the ‘voice bot’ has a positive effect on consumers’ sustainable use intention. Third, the playfulness and certainty of ‘voice bot’ have a positive effect on consumers’ sustainable use intention. Fourth, the playfulness, certainty, and empathy of the ‘voice bot’ have a positive effect on consumers’ sustainable use intention through interactivity with the ‘voice bot’. This study is meaningful in that it empirically identified the importance of interactivity by deriving the service quality factors required for sustainable use of voice search services, one of the new innovative technologies.

Accumulation of waste tyres causes an environmental disaster because of the rapid rise in transport vehicle demand resulting from modern developments, Covid-19 and similar pandemics. Thus, recycling waste tyres in the form of aggregates as a sustainable construction material can be a solution to reduce the environmental problems. Current research focuses on the impact resistance and mechanical properties of the crumb rubber self-compacting alkali-activated concrete reinforced with 1% steel fibres (SFs) where fine and coarse crumb rubbers (CR) are partially replaced with 10% and 15% replacement ratios. The compressive, flexural, splitting tensile strengths and modulus of elasticity were investigated; impact resistance was found using a drop hammer impact test. The incorporation of CR reduced the mechanical properties, and the reduction was found more with increased rubber contents, whereas the incorporation of SF compensated for the strength loss. The impact performance was enhanced with the CR and SF incorporations. The 15% CR incorporation improved the impact energy up to three times, whereas both 1% SF and 15% CR incorporations significantly enhanced the impact energy up to 30 times. Similar mechanical strengths were obtained for the different sizes of CR. However, impact performance was significantly influenced by the sizes of CR.

COVID-19 has changed the permeability of borders in transboundary environmental governance regimes. While borders have always been selectively permeable, the pandemic has reconfigured the nature of cross-border flows of people, natural resources, finances and technologies. This has altered the availability of spaces for enacting sustainability initiatives within and between countries. In Southeast Asia, national governments and businesses seeking to expedite economic recovery from the pandemic-induced recession have selectively re-opened borders by accelerating production and revitalizing agro-export growth. Widening regional inequities have also contributed to increased cross-border flows of illicit commodities, such as trafficked wildlife. At the same time, border restrictions under the exigencies of controlling the pandemic have led to a rolling back and scaling down of transboundary environmental agreements, regulations and programs, with important implications for environmental democracy, socio-ecological justice and sustainability. Drawing on evidence from Southeast Asia, the article assesses the policy challenges and opportunities posed by the shifting permeability of borders for organising and operationalising environmental activities at different scales of transboundary governance.

The goal of this study is to determine the difference in CO2 emissions between 2019-2020 and 2020-2021, more specifically during lockdown periods during the COVID-19 pandemic. In the beginning of the pandemic, most countries were forced into lockdowns, and a countless number of people had to continue their daily work from home in isolation. Previously, people would go to an office or to school and leave their houses empty for eight hours, without having lights or any electronics on. Because of this, there should be a direct correlation between electricity usage before and during lockdowns, as a private residence should have higher electricity consumption during 2020-2021, when they are at home. Using machine learning, we will investigate to see if COVID-19 affected CO2 emissions as a result of more electricity usage in private residences. A model will be made to predict what the CO2 emissions would be for 2019-2020, based on electricity usage data from 2020-2021. Then, the real CO2 emissions from 2019-2020 will be compared with the model’s predicted values, and the difference will indicate if COVID-19 caused an inconsistency between actual and predicted CO2 emissions. Factors that were taken into account when making a model were independent variables relating to outdoor conditions, the number of people living in the house, and the temperature that the thermostat is set at, making the response variable CO2 emissions.

Covid-19 affects the personal lives of millions and led to an economic crisis. Changed behavioral patterns and a reduction of industrial activity result in a reduction in power demand, and thus Covid-19 impacts the power systems around the world. Bottom-up mapping of the effect of Covid-19 on the energy demand is challenging, if not impossible. In order to analyze the impact of the pandemic on power demand, we instead propose a simplified approach based on an econometric analysis that quantifies the country-wide load reduction of Covid-19, using the number of active cases as well as the specific lockdown period as proxies. The time span covered is from 1 January 2016 to 31 August 2020. This long time span allows us to investigate the effect of Covid-19 on the power demand. We find that in Germany (DE) and Great Britain (GB) the power demand is reduced by about 1–1.7 MW per case, while in France the demand increased by 1 MW per case during times outside of the lockdown. On the other hand, in France the lockdown itself has a much higher load reduction effect in France than in GB and DE. Based on the elasticity of power demand regarding Covid-19 cases, we calculate the impact of Covid-19 on the power prices through reduced loads. We find that Covid-19 reduced power prices by 3 to 6 EUR per MWh. The effect of Covid-19 on carbon emissions in the power sector is likely to be small. In Germany, the country with the highest absolute level, emissions in the power sector were reduced by approximately 2% (4 Mio. t CO2).

The COVID-19 pandemic has forced many organizations around the world to make full use of a variety of emerging online communication platform technologies. Universities are among the organizations that have asked students, tutors, and lecturers to use a number of different online communication platforms to ensure the education process remains uninterrupted. However, the COVID-19 pandemic has generated considerable challenges for the global higher education community while using such emerging technologies. This research has two main goals. First, this paper will begin by investigating whether the online learning platforms used by university students during the COVID-19 period have presented any challenges to their learning. Second, the paper will then go on to address proposed solutions by developing a conceptual model to reduce the impact of such challenges. This research uses an exploratory qualitative research approach, supported by literature content analysis techniques. The data set for this study was collected during the first peak of the pandemic period in Malaysia, between the 16th of May 2020 and the 5th of June 2020. We used SPSS to conduct a descriptive analysis and NVivo12 to analyse data collected from 486 students from different universities in Malaysia. These students disclosed various obstacles they encountered when they used IT platform applications for online learning. These obstacles include (a) work and information overload received from instructors, (b) inadaptability and unfamiliarity of the new online learning environment, and (c) personal health challenges related to stress and anxiety. Based on previous relevant research, this study introduced a set of motivational factors and developed a conceptual motivational model for sustainable and healthy online learning.

There is a pressing need to accelerate the development of advanced technologies to prevent Coronavirus in large gatherings. The present system is an integration of tunnel disinfectant spray system and solar setup which utilises the solar energy to power a pump which pushes the required amount of chemical mixture into the nozzles of the spray system in order to eliminate any incoming virus or bacteria on the clothes of a particular person without wetting it. Data was gathered for a mall in New Delhi related to occupancy levels before and after lockdown. A 47% and 35% spike in energy and disinfectant mixture to pump was evaluated on weekends. A 70% reduction in operating cost was registered for solar based system in comparison to non-solar setup. Optimum conditions by considering efficiency and cost effectiveness evaluated are 8 number of nozzles, nozzle angle 55 degrees spray pressure 200 bar, and pressure 200 bar.