Analysis of environmental and energy indicators in Latin America and the Caribbean: an evaluation from multivariate techniques and big data on sustainability

Автор: Ruff C., Shamaeva E.F., Gutirrez B., Matheu A., Golovin A.A., Pugach A.D., Cornejo C., Ruiz M., Abbas N.

Журнал: Сетевое научное издание «Устойчивое инновационное развитие: проектирование и управление» @journal-rypravleni

Статья в выпуске: 3 (60) т.19, 2023 года.

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In the current context of concern for environmental impacts derived from human activity, the focus on sustainable development and environmental impact assessment (EIA) has gained prominence. The Brundtland Commission highlights the importance of meeting current needs without compromising future ones, leading to international treaties and public policies to address the environmental crisis. In Latin America and the Caribbean, the Latin American and Caribbean Initiative for Sustainable Development (ILAC) seeks to promote sustainable development in key areas. Environmental indicators are used to measure progress, but the complexity of the data presents challenges in measuring and monitoring environmental dynamics. Models such as Pressure-State-Response (PSR) and Driving Forces-Pressure-State-Impact-Response (FPEIR) help to analyze the interactions between human activities, environmental pressures, states and societal responses. Energy efficiency and destination are crucial for sustainable use of energy resources and emission reduction. Dynamic biplots and multivariate analyses allow us to examine the evolution of variables and countries in terms of installed capacity to produce electricity, proportions of renewable primary energy supply and fossil fuel subsidies. Trends in the increase of renewable energy production capacity are evident, while the correlation between the proportion of fossil fuel subsidies and the renewable proportion of primary energy supply presents a weak inverse relationship. Although environmental information presents challenges, the analysis of indicators and conceptual models contributes to the understanding of environmental dynamics and progress towards sustainable development in the region.

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Sustainable development, environmental indicators, renewable energy, multivariate methods

Короткий адрес: https://sciup.org/14129404

IDR: 14129404

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