| Title: | Quantifying indoor air quality determinants in urban and rural nursery and primary schools |
| Author(s): | Branco P; Alvim-Ferraz MCM; Martins FG; Sousa SIV; |
| Address: | "LEPABE - Laboratory for Process Engineering, Environment, Biotechnology and Energy, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal. LEPABE - Laboratory for Process Engineering, Environment, Biotechnology and Energy, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal. Electronic address: sofia.sousa@fe.up.pt" |
| DOI: | 10.1016/j.envres.2019.108534 |
| ISSN/ISBN: | 1096-0953 (Electronic) 0013-9351 (Linking) |
| 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 microenvironments (classrooms, bedrooms and canteens) from 25 nursery and primary schools, CO(2), CO, HCOH, NO(2), O(3), total volatile organic compounds, PM(1), PM(2.5), PM(10), total suspended particles (TSP), and meteorological/comfort parameters were continuously sampled (occupancy and background levels), from at least 24?ª+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 PM(2.5) and CO(2) 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 PM(2.5) and CO(2) 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)?ª+=?ª+0.64, 0.57 and 0.47, respectively, for CO(2), PM(2.5) and PM(10)) 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 CO(2) occupancy model. In the cases of PM(2.5) and PM(10) occupancy concentrations, besides background concentrations (71.2% and 67.2% of relative importance, respectively for PM(2.5) and PM(10)), 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" |
| Keywords: | "*Air Pollutants Air Pollution, Indoor/*statistics & numerical data Child *Environmental Monitoring Humans Particulate Matter Schools Ventilation Children Exposure Indoor air quality Nursery and primary school;" |
| Notes: | "MedlineBranco, P T B S Alvim-Ferraz, M C M Martins, F G Sousa, S I V eng Research Support, Non-U.S. Gov't Netherlands 2019/06/21 Environ Res. 2019 Sep; 176:108534. doi: 10.1016/j.envres.2019.108534. Epub 2019 Jun 12" |
