资源环境科技发展态势分析平台

Background:

School classrooms, where students spend the majority of their time during the day, are the second most important indoor microenvironment for children.

Objective:

We investigated factors influencing classroom exposures to fine particulate matter (${\mathrm{PM}}_{2.5}$), black carbon (BC), and nitrogen dioxide (${\mathrm{NO}}_2$) in urban schools in the northeast United States.

Methods:

Over the period of 10 y (2008–2013; 2015–2019) measurements were conducted in 309 classrooms of 74 inner-city schools during fall, winter, and spring of the academic period. The data were analyzed using adaptive mixed-effects least absolute shrinkage and selection operator (LASSO) regression models. The LASSO variables included meteorological-, school-, and classroom-based covariates.

Results:

LASSO identified 10, 10, and 11 significant factors ($p<0.05$) that were associated with indoor ${\mathrm{PM}}_{2.5}$, BC, and ${\mathrm{NO}}_2$ exposures, respectively. The overall variability explained by these models was $R^2=0.679$, 0.687, and 0.621 for ${\mathrm{PM}}_{2.5}$, BC, and ${\mathrm{NO}}_2$, respectively. Of the model’s explained variability, outdoor air pollution was the most important predictor, accounting for 53.9%, 63.4%, and 34.1% of the indoor ${\mathrm{PM}}_{2.5}$, BC, and ${\mathrm{NO}}_2$ concentrations. School-based predictors included furnace servicing, presence of a basement, annual income, building type, building year of construction, number of classrooms, number of students, and type of ventilation that, in combination, explained 18.6%, 26.1%, and 34.2% of ${\mathrm{PM}}_{2.5}$, BC, and ${\mathrm{NO}}_2$ levels, whereas classroom-based predictors included classroom floor level, classroom proximity to cafeteria, number of windows, frequency of cleaning, and windows facing the bus area and jointly explained 24.0%, 4.2%, and 29.3% of ${\mathrm{PM}}_{2.5}$, BC, and ${\mathrm{NO}}_2$ concentrations, respectively.

Discussion:

The adaptive LASSO technique identified significant regional-, school-, and classroom-based factors influencing classroom air pollutant levels and provided robust estimates that could potentially inform targeted interventions aiming at improving children’s health and well-being during their early years of development. https://doi.org/10.1289/EHP10007