Schools, Air Pollution, and Active Transportation: An Exploratory Spatial Analysis of Calgary, Canada

Assessing schoolchildren's exposure to air pollution during the daily commute - A systematic review

Air pollution is mostly caused by emissions from human activities, and exposure to air pollution is linked with numerous adverse human health outcomes. Recent studies have identified that although people only spend a small proportion of time on their daily commutes, the commuter microenvironment is a significant contributor to their total daily air pollution exposure. Schoolchildren are a particularly vulnerable cohort of the population, and their exposure to air pollution at home or school has been documented in a number of case studies. A few studies have identified that schoolchildren's exposure during commutes is linked with adverse cognitive outcomes and severe wheeze in asthmatic children. However, the determinants of total exposure, such as route choice and commute mode, and their subsequent health impacts on schoolchildren are still not well-understood. The aim of this paper is to review and synthesize recent studies on assessing schoolchildren's exposure to various air pollutants during the daily commute. Through reviewing 31 relevant studies published between 2004 and 2020, we tried to identify consistent patterns, trends, and underlying causal factors in the results. These studies were carried out across 10 commute modes and 12 different air pollutants. Air pollution in cities is highly heterogeneous in time and space, and commuting schoolchildren move through the urban area in complex ways. Measurements from fixed monitoring stations (FMSs), personal monitoring, and air quality modeling are the three most common approaches to determining exposure to ambient air pollutant concentrations. The time-activity diary (TAD), GPS tracker, online route collection app, and GIS-based route simulation are four widely used methods to determine schoolchildren's daily commuting routes. We found that route choices exerted a determining impact on schoolchildren's exposure. It is challenging to rank commute modes in order of exposure, as each scenario has numerous uncontrollable determinants, and there are notable research gaps. We suggest that future studies should concentrate on examining exposure patterns of schoolchildren in developing countries, exposure in the subway and trains, investigating the reliability of current simulation methods, exploring the environmental justice issue, and identifying the health impacts during commuting. It is recommended that three promising tools of smartphones, data fusion, and GIS should be widely used to overcome the challenges encountered in scaling up commuter exposure studies to population scales.

Analysis of Spatio-temporal Characteristics and Driving Forces of Air Quality in the Northern Coastal Comprehensive Economic Zone, China

Comprehensive analysis of air quality is essential to underpin knowledge-based air quality conservation policies and funding decisions by governments and managers. In this paper, air quality change characteristics for the Northern Coastal Comprehensive Economic Zone from 2008 to 2018 were analyzed using air quality indices. The spatio-temporal pattern of air quality was identified using centroid migration, spatial autocorrelation analysis and spatial analysis in a geographic information system (GIS). A spatial econometric model was established to confirm the natural and anthropogenic factors affecting air quality. Results showed that air pollution decreased significantly. PM2.5, PM10, and O3 were the primary pollutants. The air quality exhibited an inverted U-shaped trend from January to December, with the highest quality being observed in summer and the lowest during winter. Spatially, the air quality showed an increasing trend from inland to the coast and from north to south, with significant spatial autocorrelation and clustering. Population, energy consumption, temperature, and atmospheric pressure had significant negative impacts on air quality, while wind speed had a positive impact. This study offers an efficient and effective method to evaluate air quality change. The research provides important scientific information necessary for developing future air pollution prevention and control.

Exploratory Temporal and Spatial Analysis of Myocardial Infarction Hospitalizations in Calgary, Canada

Spatial and temporal analyses are critical to understand the pattern of myocardial infarction (MI) hospitalizations over space and time, and to identify their underlying determinants. In this paper, we analyze MI hospitalizations in Calgary from 2004 to 2013, stratified by age and gender. First, a seasonal trend decomposition analyzes the seasonality; then a linear regression models the trend component. Moran's I and hot spot analyses explore the spatial pattern. Though exploratory, results show that most age and gender groups feature a statistically significant decline over the 10 years, consistent with previous studies in Canada. Decline rates vary across ages and genders, with the slowest decline observed for younger males. Each gender exhibits a seasonal pattern with peaks in both winter and summer. Spatially, MI hot spots are identified in older communities, and in socioeconomically and environmentally disadvantaged communities. In the older communities, higher MI rates appear to be more highly associated with demographics. Conversely, worse air quality appears to be locally associated with higher MI incidence in younger age groups. The study helps identify areas of concern, where MI hot spots are identified for younger age groups, suggesting the need for localized public health policies to target local risk factors.