Indoor concentrations of fine particulate matter (PM 2.5 ), nitrogen dioxide (NO 2 ), and carbon monoxide (CO) were measured across 16 urban public schools in three different seasons. Exceedance of the WHO guidelines for indoor air was observed, mainly for the hourly average NO 2 concentrations. Seasonal variability was statistically significant for indoor NO 2 and CO concentrations, with higher exposures in fall and winter. An extensive list of potential factors at the outdoor environment, school, and room level that may explain the variability in indoor exposure was examined. Factors with significant contributions to indoor exposure were mostly related to the outdoor pollution sources. This is evidenced by the strong associations between indoor concentration of CO and NO 2 and factors including outdoor PM 2.5 and NO 2 concentrations, including length of the nearby roads and the number of nearby industrial facilities. Additionally, we found that poor conditions of the buildings (a prevalent phenomenon in the studied urban area), including physical defects and lack of proper ventilation, contributed to poor air quality in schools. The results suggest that improving building conditions and facilities as well as a consideration of the school surroundings may improve indoor air quality in schools.

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School facility conditions, environment, and perceptions of safety and learning have been investigated for their impact on child development. However, it is important to consider how the environment separately influences academic performance and attendance after controlling for school and community factors. Using results from the Maryland School Assessment, we considered outcomes of school-level proficiency in reading and math plus attendance and chronic absences, defined as missing 20 or more days, for grades 3-5 and 6-8 at 158 urban schools. Characteristics of the environment included school facility conditions, density of nearby roads, and an index industrial air pollution. Perceptions of school safety, learning, and institutional environment were acquired from a School Climate Survey. Also considered were neighborhood factors at the community statistical area, including demographics, crime, and poverty based on school location. Poisson regression adjusted for over-dispersion was used to model academic achievement and multiple linear models were used for attendance. Each 10-unit change in facility condition index, denoting worse quality buildings, was associated with a decrease in reading (1.0% (95% CI: 0.1-1.9%) and math scores (0.21% (95% CI: 0.20-0.40), while chronic absences increased by 0.75% (95% CI: 0.30-1.39). Each log increase the EPA's Risk Screening Environmental Indicator (RSEI) value for industrial hazards, resulted in a marginally significant trend of increasing absenteeism (p < 0.06), but no association was observed with academic achievement. All results were robust to school-level measures of racial composition, free and reduced meals eligibility, and community poverty and crime. These findings provide empirical evidence for the importance of the community and school environment, including building conditions and neighborhood toxic substance risk, on academic achievement and attendance.

This study proposes and applies a novel method for empirically evaluating the role of social structure in the school sorting process. We use administrative records from Baltimore City and suburban Baltimore County public elementary schools (2011 to 2015) to generate a network of schools based on student transfers. We then apply repeated calculations of the Louvian method of community detection to estimate emergent sets of schools that similar parents are likely to consider—which we term emergent consideration sets—and use gravity models to explore the role of social structure, demographics, and geography in observed enrollment patterns. We find that our network-derived emergent consideration sets are better defined by structural boundaries than by student composition or proficiency alone. Within consideration sets, students tend to avoid schools with relatively higher levels of free- and reduced-price meal eligibility and flock toward schools with higher proficiency levels. School racial composition, however, plays a much smaller role in predicting movement between schools, in part because structural constraints generate racially homogeneous consideration sets. Together, these findings highlight how regional social and geographic organization shapes school segregation processes and the policies used to combat them.