Methodology for assessing exposure and impacts of air pollutants in school children: Data collection, analysis and health effects – A literature review

Abstract

Abstract The aim of this review is to explore the methodologies employed to assess the exposure of children to air pollutants, in particular traffic emissions, at school, and how these methodologies influence the assessment of the impact of this exposure on the children’s health. This involves four main steps: the measurement of air quality at school level, the association between measured air quality and children’s exposure, the association between children’s exposure and health; and source identification. The comparative advantages and disadvantages of the methods used at each of these steps are discussed. Air quality in schools can be measured at three scales: broad scale, across several city blocks using remote monitors; school-based scale, through ground-level monitors installed within the schools or their immediate surroundings (i.e. only a few metres outside the school); and personal exposure scale using portable monitors attached to a sample of children. Although studies have reported high exposure to PAHs (polycyclic aromatic hydrocarbons), submicrometre ( Associating air quality measurements at the broad and medium scale with children’s exposure is challenging: there is spatial and temporal heterogeneity in the distribution of air quality within a school, indoor measurements can often exceed outdoor measurements; and exposure in the classroom is affected by the penetration of outdoor pollutants, wall absorption, emissions from furniture and other materials, level and length of occupancy, and quality of ventilation. This is further exacerbated by the fact that children move around during their school day. Quantifying the contribution of school exposure with observed health symptoms presents further challenges. In addition to ascertaining the impact of non-school-based exposures and co-morbidities, the air pollutant dose intake is affected by daily patterns of physical and traffic activity during and outside school hours which make it difficult to compare the contribution of school-based and non-school-based exposures to the health effect under investigation. Finally, there is strong evidence that low socioeconomic level is highly correlated with the proximity of the school to pollution sources, yet this area of socioeconomic research has been largely unexplored in the assessment of traffic emission exposure.