Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/122236
Author(s): Pedro T. B. S. Branco
Conceição Alvim Ferraz
F. G. Martins
Sofia I. V. Sousa
Title: Quantifying indoor air quality determinants in urban and rural nursery and primary schools
Issue Date: 2019
Abstract: Poor indoor air quality can adversely affect children's health, comfort and school performance, but existing literature on quantifying indoor air pollutants (IAP) determinants' in nursery and primary schools is limited. Following previous studies, this study mainly aimed to quantify determinants of selected IAP, in nursery and primary schools from both urban and rural sites, accounting for seasonal variations. In 101 indoor micro environments (classrooms, bedrooms and canteens) from 25 nursery and primary schools, CO2, CO, HCOH, NO2, O-3, total volatile organic compounds, PM1, PM2.5, PM10, total suspended particles (TSP), and meteorological/ comfort parameters were continuously sampled (occupancy and background levels), from at least 24 h to 9 consecutive days (not simultaneously) in each studied room; in some cases weekend was also considered.Children faced thermal discomfort and inadequate humidity, respectively in 60.1% and 44.1% of the studied classrooms. They were also exposed to high levels of IAP, namely PM2.5 and CO2 respectively in 69.0% and 41.3% of the studied classrooms, mostly in urban sites, depending on season and on occupancy and activity patterns (different amongst age groups). As PM2.5 and CO2 were the major concerning IAP, multivariate linear regression models were built to quantify (explained variability and relative importance) their main determinants, in both occupancy and non -occupancy (background) periods. Models for occupancy periods showed higher explained variability (R-2 = 0.64, 0.57 and 0.47, respectively, for CO2, PM2.5 and PM10) than for non occupancy. Besides background concentrations (43.5% of relative importance), relative humidity (21.1%), flooring material (17.0%), heating (6.7%) and age group of the occupants (5.3%), adjusted for season of sampling (6.4%) were predictors in CO2 occupancy model. In the cases of PM2.5 and PM10 occupancy concentrations, besides background concentrations (71.2% and 67.2% of relative importance, respectively for PM2.5 and PM10), type of school management (8.8% and 15.2%) and flooring material (13.9% and 13.9%), adjusted for season of sampling (6.1% and 3.8%), were the main predictors.These findings support the need of mitigation measures to reduce IAP levels, and prevention actions to avoid children's exposure. Reducing the time spent indoors in the same microenvironment by doing more and/or longer breaks, improving ventilation and cleaning actions, and avoiding or making a better maintenance hardwood flooring materials, chalkboard use and VOC emitting materials, are practices that should be implemented and their impacts quantified.
URI: https://hdl.handle.net/10216/122236
Related Information: info:eu-repo/grantAgreement/FCT - Fundação para a Ciência e Tecnologia/Programa de Financiamento Plurianual de Unidades de I&D/UID/EQU/00511/2019 /Projeto Estratégico do LEPABE - Laboratório de Engenharia de Processos, Ambiente, Biotecnologia e Energia/LEPABE
Document Type: Artigo em Revista Científica Internacional
Rights: restrictedAccess
Appears in Collections:FEUP - Artigo em Revista Científica Internacional

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