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Título
An in-depth multivariate analysis of PM2.5 concentration and associated premature deaths in Europe and its strategic relationship with sustainability
Autor(es)
Palabras clave
PM2.5
Air pollution
Machine learning
Public health
Premature deaths
Sustainability
Fecha de publicación
2024
Editor
Elsevier
Citación
Sanz-Martín, L., Parra-Domínguez, J., & Corchado, J. M. (2024). An in-depth multivariate analysis of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si24.svg" display="inline" id="d1e1096"><mml:mrow><mml:mi>P</mml:mi><mml:msub><mml:mrow><mml:mi>M</mml:mi></mml:mrow><mml:mrow><mml:mn>2</mml:mn><mml:mo>.</mml:mo><mml:mn>5</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:math> concentration and associated premature deaths in Europe and its strategic relationship with sustainability. Applied Computing and Geosciences, 23, 100184. https://doi.org/10.1016/j.acags.2024.100184
Resumen
[EN]The strategic importance of sustainability is evident when it comes, for example, to health. Public policies
aimed at mitigating the effects of harmful substances, such as fine particulate matter (PM 2.5), are justified
by the direct link between fine particulate matter and the health of citizens, in this case, premature deaths.
An advanced statistical and exhaustive analysis of different areas and countries shows a strong link between
exposure to 𝑃𝑀2.5, premature deaths in other countries, and significant differences in 𝑃𝑀2.5 levels between
urban and rural areas.
Although 𝑃𝑀2.5 concentration has decreased in most countries studied, this effort must be continued and
aligned with the Sustainable Development Goals of the 2030 Agenda, underlining the need to implement
effective air pollution control policies to reduce the health risks associated with 𝑃𝑀2.5 exposure. To this end,
identifying temporal trends and geographical patterns can guide the development of specific interventions
tailored to the needs of each region.
URI
ISSN
2590-1974
DOI
10.1016/j.acags.2024.100184
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