Autor: Quinteros, María Elisa, Blazquez, Carola, Ayala, Salvador, Kilby, Dylan, Cárdenas-R, Juan Pablo, Ossa, Ximena, Rosas-Diaz, Felipe, Stone, Elizabeth A., Blanco, Estela, Delgado-Saborit, Juana-María, Harrison, Roy M., Ruiz-Rudolph, Pablo
Revista: Environmental Science & Technology
Año: 2023
Número: 48
Paginas: 19473-19486
Volumen: 57
Abstract: Biomass burning is common in much of the world, and in some areas, residential wood-burning has increased. However, air pollution resulting from biomass burning is an important public health problem. A sampling campaign was carried out between May 2017 and July 2018 in over 64 sites in four sessions, to develop a spatio-temporal land use regression (LUR) model for fine particulate matter (PM) and wood-burning tracers levoglucosan and soluble potassium (Ksol) in a city heavily impacted by wood-burning. The mean (sd) was 46.5 (37.4) ?g m-3 for PM2.5, 0.607 (0.538) ?g m-3 for levoglucosan, and 0.635 (0.489) ?g m-3 for Ksol. LUR models for PM2.5, levoglucosan, and Ksol had a satisfactory performance (LOSOCV R2), explaining 88.8%, 87.4%, and 87.3% of the total variance, respectively. All models included sociodemographic predictors consistent with the pattern of use of wood-burning in homes. The models were applied to predict concentrations surfaces and to estimate exposures for an epidemiological study.
Idioma: eng
Base de Datos: PubMed
Ver Más: https://doi.org/10.1021/acs.est.3c00720