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Spatio-temporal statistical analysis of PM1 and PM2.5 concentrations and their key influencing factors at Guayaquil city, Ecuador

Rincon, Gladys; Morantes, Giobertti; Roa-López, Heydi; Cornejo-Rodriguez, Maria del Pilar; Jones, Benjamin; Cremades, Lázaro V.

Authors

Gladys Rincon

Giobertti Morantes

Heydi Roa-López

Maria del Pilar Cornejo-Rodriguez

Lázaro V. Cremades



Abstract

Guayaquil, Ecuador, is in a tropical area on the equatorial Pacific Ocean coast of South America. Since 2008 the city has been increasing its population, vehicle fleet and manufacturing industries. Within the city there are various industrial and urban land uses sharing the same space. With regard to air quality there is a lack of government information on it. Therefore, the research’s aim was to investigate the spatio-temporal characteristics of PM1 and PM2.5 concentrations and their main influencing factors. For this, both PM fractions were sampled and a bivariate analysis (cross-correlation and Pearson's correlation), multivariate linear and logistic regression analysis was applied. Hourly and daily PM1 and PM2.5 were the dependent variables, and meteorological variables, occurrence of events and characteristics of land use were the independent variables. We found 48% exceedances of the PM2.5-24h World Health Organization 2021 threshold’s, which questions the city’s air quality. The cross-correlation function and Pearson’s correlation analysis indicate that hourly and daily temperature, relative humidity, and wind speed have a complex nonlinear relationship with PM concentrations. Multivariate linear and logistic regression models for PM1-24h showed that rain and the flat orography of cement plant sector decrease concentrations; while unusual PM emission events (traffic jams and vegetation-fires) increase them. The same models for PM2.5-24h show that the dry season and the industrial sector (strong activity) increase the concentration of PM2.5-24h, and the cement plant decrease them. Public policies and interventions should aim to regulate land uses while continuously monitoring emission sources, both regular and unusual.

Citation

Rincon, G., Morantes, G., Roa-López, H., Cornejo-Rodriguez, M. D. P., Jones, B., & Cremades, L. V. (2023). Spatio-temporal statistical analysis of PM1 and PM2.5 concentrations and their key influencing factors at Guayaquil city, Ecuador. Stochastic Environmental Research and Risk Assessment, 37, 1093–1117. https://doi.org/10.1007/s00477-022-02310-2

Journal Article Type Article
Acceptance Date Sep 6, 2022
Online Publication Date Nov 6, 2022
Publication Date 2023-03
Deposit Date Nov 9, 2022
Publicly Available Date Mar 28, 2024
Journal Stochastic Environmental Research and Risk Assessment
Print ISSN 1436-3240
Electronic ISSN 1436-3259
Publisher Springer Science and Business Media LLC
Peer Reviewed Peer Reviewed
Volume 37
Pages 1093–1117
DOI https://doi.org/10.1007/s00477-022-02310-2
Keywords General Environmental Science; Safety, Risk, Reliability and Quality; Water Science and Technology; Environmental Chemistry; Environmental Engineering
Public URL https://nottingham-repository.worktribe.com/output/13458115
Publisher URL https://link.springer.com/article/10.1007/s00477-022-02310-2

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