dc.contributor
Universitat Politècnica de Catalunya. Doctorat en Enginyeria Ambiental
dc.contributor
Universitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental
dc.contributor
Universitat Politècnica de Catalunya. EScGD - Engineering Sciences and Global Development
dc.contributor.author
Sánchez Balseca, Joseph
dc.contributor.author
Pérez Foguet, Agustí
dc.identifier
Sánchez-Balseca, J.; Pérez-Foguet, A. Spatially-structured human mortality modelling using air pollutants with a compositional approach. "Science of the total environment", Març 2022, vol. 813, p. 152486:1-152486:21.
dc.identifier
https://hdl.handle.net/2117/365130
dc.identifier
10.1016/j.scitotenv.2021.152486
dc.description.abstract
The human mortality models with a demographic approach are performed in function of time. The addition of information (social, economic, and environmental) in the structure of demographic models allows fitting observed values better. Air pollution influences human mortality and could be used as an environmental covariate in the demographic models. The levels of air pollutants describe quantitatively the parts of a whole (air), called composition, and their statistical treatment should consider this characteristic in the modelling process. This article evaluated the association between human mortality data with levels of air pollutants as a composition using a spatially-structured model. The spatially-structured modelling approach in the human mortality data captures the spatial heterogeneity of air pollutant concentrations (local environmental conditions). Human mortality data is defined as the number of deaths, and in this work, it was analyzed with both total and disaggregated presentation. The disaggregation was by (i) sex and (ii) sex and age-group. A likelihood ratio test suggested the model with air pollutants as covariates treated under a compositional approach (proposed model) is more appropriate than the model based only on time explanatory variable in yearly basis. The proposed model was evaluated in 48 counties in Spain, each with its mortality and air pollution dataset. The modelling approach in this work presented adequate quality model indexes and could be applied to make short-term predictions with different air pollution scenarios.
dc.description.abstract
Joseph Sánchez Balseca is the recipient of a full scholarship from the Secretaria de Educación Superior, Ciencia, Tecnología e Innovación (SENESCYT), Ecuador. We thank the research group on Engineering Sciences and Global Development (EScGD) and the Agència de Gestió d'Ajuts Universitaris i de Recerca de la Generalitat de Catalunya (Ref. 2017 SGR 1496).
dc.description.abstract
Peer Reviewed
dc.description.abstract
Postprint (author's final draft)
dc.format
application/pdf
dc.relation
https://www.sciencedirect.com/science/article/abs/pii/S0048969721075641
dc.rights
© 2022. Elsevier
dc.rights
https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights
Attribution-NonCommercial-NoDerivatives 4.0 International
dc.subject
Àrees temàtiques de la UPC::Desenvolupament humà i sostenible::Degradació ambiental::Contaminació atmosfèrica
dc.subject
Àrees temàtiques de la UPC::Desenvolupament humà i sostenible::Desenvolupament humà::Salut
dc.subject
Air--Pollution - Statistics
dc.subject
Environmental statistics
dc.subject
Negative binomial
dc.subject
Aire -- Contaminació -- Estadístiques
dc.title
Spatially-structured human mortality modelling using air pollutants with a compositional approach