Investigating the relationship between macroeconomic indicators, renewables and pollution across diverse regions in the globalization era

Georgescu, Irina Alexandra; Oprea, Simona-Vasilica; Bâra, Adela

doi:10.1016/j.apenergy.2024.123077

Cited by 7 publications

(3 citation statements)

References 71 publications

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“…Energy purchased from the grid Energy consumed × 100 (5) ESI = Energy cost from the Grid − Selfgenerated energy cost (6) The economic savings index (ESI) quantifies the cost savings realized by a prosumer from using their own generated energy versus the alternative of purchasing the equivalent amount of energy from the grid. It effectively measures the economic impact of selfsufficiency in energy production.…”

Section: Gdi (%) =mentioning

confidence: 99%

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A Recommendation System for Prosumers Based on Large Language Models

Oprea,

Bâra

2024

Sensors

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As modern technologies, particularly home assistant devices and sensors, become more integrated into our daily lives, they are also making their way into the domain of energy management within our homes. Homeowners, now acting as prosumers, have access to detailed information at 15-min or even 5-min intervals, including weather forecasts, outputs from renewable energy source (RES)-based systems, appliance schedules and the current energy balance, which details any deficits or surpluses along with their quantities and the predicted prices on the local energy market (LEM). The goal for these prosumers is to reduce costs while ensuring their home’s comfort levels are maintained. However, given the complexity and the rapid decision-making required in managing this information, the need for a supportive system is evident. This is particularly true given the routine nature of these decisions, highlighting the potential for a system that provides personalized recommendations to optimize energy consumption, whether that involves adjusting the load or engaging in transactions with the LEM. In this context, we propose a recommendation system powered by large language models (LLMs), Scikit-llm and zero-shot classifiers, designed to evaluate specific scenarios and offer tailored advice for prosumers based on the available data at any given moment. Two scenarios for a prosumer of 5.9 kW are assessed using candidate labels, such as Decrease, Increase, Sell and Buy. A comparison with a content-based filtering system is provided considering the performance metrics that are relevant for prosumers.

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Section: Gdi (%) =mentioning

confidence: 99%

“…The benefits for prosumers include cost savings by optimizing energy usage, which significantly reduces energy bills. Efficient energy management also reduces the overall carbon footprint of the household [ 6 , 7 ], offering environmental benefits. These recommendations empower users to make informed decisions about their energy use.…”

Section: Introductionmentioning

confidence: 99%

A Recommendation System for Prosumers Based on Large Language Models

Oprea,

Bâra

2024

Sensors

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“…By means of the ARDL model, the study finds evidence of a U-shaped EKC between GDP and the environmental footprint. Georgescu et al [15] make a comparison between Nordic countries and Southeast European countries. The conclusion of the study is that Nordic countries exhibit higher levels of urbanizations and economic development, coupled with progressive environmental policies that result in lower CO2 emissions per capita.…”

Section: Economic Growth and Deforestationmentioning

confidence: 99%

Evaluating the Determinants of Deforestation in Romania: Empirical Evidence from an Autoregressive Distributed Lag Model and the Bayer–Hanck Cointegration Approach

Georgescu,

Nica

2024

Sustainability

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This study focuses on deforestation, a key aspect of the current environmental decline linked to worldwide economic development and increasing populations. It examines how renewable energy consumption (RENC), GDP per capita, urbanization (URB) and foreign direct investments (FDI) have influenced the expansion of forest areas (FAG) in Romania from 1990 to 2022, utilizing an autoregressive distributed lag (ARDL) model and the Bayer–Hanck cointegration approach. The main results of the paper are the following: GDP has a positive and statistically significant long-term influence on FAG; URB and FDI have a long-term negative impact on FAG; and RENC is not a significant determinant of FAG. In the short term, a 1% increase in URB leads to an 809.88% decrease in FAG, while a 1% increase in the first and second lag of URB leads to a 323.06%, and 216.26% increase in FAG. This suggests that as more land is developed for urban use (like building homes, businesses, and infrastructure), the immediate consequence is a significant reduction in the area available for forests. This effect indicates a strong inverse relationship between urbanization and the availability of land for forests in the short term. Our results underscore the importance of sustainable development strategies, including green urban planning and robust forest conservation, to offset the adverse effects of increased FDI on Romania’s environmental conservation, emphasizing the need for careful strategic planning and strong environmental policies to balance economic growth with forest protection.

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Dynamic interactions between GDP, renewable energy, innovation, and CO2 emissions in Finland: a fourier-augmented ARDL analysis

Georgescu,

Kinnunen

2024

Lett Spat Resour Sci

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This study uses the novel Fourier-augmented ARDL (FARDL) to explore the impact of renewable energy (REN), the number of patent applications (PA) and GDP per capita on CO2 emissions in Finland during 1990–2022. The findings reveal that in the long run, GDP rises CO2 emissions, while REN and PA decrease CO2 emissions. The FARDL short-run results indicate that both REN and PA have a significant negative impact on CO2 emissions, suggesting that higher adoption of renewable energy and technological innovation contribute to emission reductions. However, GDP does not show a significant effect in the short run, which may indicate a decoupling of economic growth from environmental degradation in the short term. Furthermore, the study highlights the need for policies that promote technological innovation and increased investment in renewable energy to achieve sustainable carbon reduction in the long term.

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Investigating the relationship between macroeconomic indicators, renewables and pollution across diverse regions in the globalization era

Cited by 7 publications

References 71 publications

A Recommendation System for Prosumers Based on Large Language Models

A Recommendation System for Prosumers Based on Large Language Models

Evaluating the Determinants of Deforestation in Romania: Empirical Evidence from an Autoregressive Distributed Lag Model and the Bayer–Hanck Cointegration Approach

Dynamic interactions between GDP, renewable energy, innovation, and CO2 emissions in Finland: a fourier-augmented ARDL analysis

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