Electricity consumption in Europe has risen significantly in recent years, with households being the largest consumers of final electricity. Managing and reducing residential power consumption is critical for achieving efficient and sustainable energy management, conserving financial resources, and mitigating environmental effects. Many studies have used statistical models such as linear, multinomial, ridge, polynomial, and LASSO regression to examine and understand the determinants of residential energy consumption. However, these models are limited to capturing only direct effects among the determinants of household energy consumption. This study addresses these limitations by applying a path analysis model that captures the direct and indirect effects. Numerical and theoretical comparisons that demonstrate its advantages and efficiency are also given. The results show that Sub-metering components associated with specific uses, like cooking or water heating, have significant indirect impacts on global intensity through active power and that the voltage affects negatively the global power (active and reactive) due to the physical and behavioral mechanisms. Our findings provide an in-depth understanding of household electricity power consumption. This will improve forecasting and enable real-time energy management tools, extending to the design of precise energy efficiency policies to achieve SDG 7’s objectives.

Luxembourg institutions have the opportunity to reconcile environmental goals with financial stability by implementing Green Fintech solutions, as the banking sector increasingly recognizes the importance of sustainability. This study employs a quantitative approach and analyzes data collected from 150 participants working in the banking industry of Luxembourg. The research aims to assess the consequences of adopting Green Fintech on sustainable development. Banking institutions can boost their financial resilience and mitigate climate-related risks by adopting Green Fintech, which improves their sustainability. The paper emphasizes the importance of Green Fintech in the Luxembourg banking sector for advancing sustainable development goals. To effectively address the increasingly complex environmental concerns, it is crucial to embrace innovative Fintechs.

Biomimicry is increasingly being used to drive sustainable constructional development in recent years. By emulating the designs and processes of nature, biomimicry offers a wealth of opportunities to create innovative and environmentally friendly solutions. Biomimicry in industrial development: versatile applications, advantages in construction. The text emphasizes the contribution of bio-mimetic technologies to sustainability and resilience in structural design, material selection, energy efficiency, and sensor technology. Aside from addressing technical constraints and ethical concerns, we address challenges and limitations associated with adopting biomimicry. A quantitative research approach is implemented, and respondents from the construction industry rank biomimicry principles as the optimal approach to enhance sustainability in the industry. Demographic and descriptive analyses are underway. By working together, sharing knowledge, and innovating responsibly, we suggest approaches to tackle these obstacles and fully leverage the transformative power of biomimicry in promoting sustainable construction industry practices. In an evolving global environment, biomimicry reduces environmental impact and enhances efficiency, resilience, and competitiveness in construction industries.

Air pollution in Jakarta has become a severe concern in the last four months. IQAir, in August 2023, revealed that the level of air pollution had reached 161 points on the Air Pollution Standard Index (APSI). The negative impact on society has placed air pollution as a concern for environmental safety and survival in danger. This condition will encourage the development of a national policy agenda to integrate environmental welfare through various energy efficiency channels. This research analyzes the relationship between air pollutant elements that can reduce air quality. The analysis includes pollutant intensity measured by APSI per unit of pollutant as a measure of efficiency. The aim is to observe energy use, which causes an increase in pollutant levels. This research utilizes dynamic system modeling to produce relationships between parameters to produce factors that cause pollution. The parameters used are motorized vehicles, waste burning in landfills, industry, and power plants. The results of historical behavioral tests and statistical suitability tests show that the behavior is suitable for the short and long term. The simulation results show that the pollution level will worsen by the end of 2027, a hazardous condition for society. The optimistic scenario simulation model proposes immediate counter-measures to reduce pollution to 45.01, the ideal condition. To accelerate improvements in air quality, the Government can plan policies to reduce the use of coal by power plants and industry, as well as the use of electric motorized vehicles, resulting in an ideal reduction in pollution by 2024. In conclusion, pollution can be reduced effectively if the Government firmly implements policies to maintain that air quality remains stable below 50 points.