Air Pollution Monitoring Design for Epidemiological Application in a Densely Populated City

Abstract

Introduction: Many studies have reported the association between air pollution and human health based on regulatory air pollution monitoring data. However, because regulatory monitoring networks were not designed for epidemiological studies, the collected data may not provide sufficient spatial contrasts for assessing such associations. Our goal was to develop a monitoring design supplementary to the regulatory monitoring network in Seoul, Korea. This design focused on the selection of 20 new monitoring sites to represent the variability in PM2.5 across people’s residences for cohort studies. Methods: We obtained hourly measurements of PM2.5 at 37 regulatory monitoring sites in 2010 in Seoul, and computed the annual average at each site. We also computed 313 geographic variables representing various pollution sources at the regulatory monitoring sites, 31,097 children’s homes from the Atopy Free School survey, and 412 community service centers in Seoul. These three types of locations represented current, subject, and candidate locations. Using the regulatory monitoring data, we performed forward variable selection and chose five variables most related to PM2.5. Then, k-means clustering was applied to categorize all locations into several groups representing a diversity in the spatial variability of the five selected variables. Finally, we computed the proportion of current to subject location in each cluster, and randomly selected new monitoring sites from candidate sites in the cluster with the minimum proportion until 20 sites were selected. Results: The five selected geographic variables were related to traffic or urbanicity with a cross-validated R2 value of 0.69. Clustering analysis categorized all locations into nine clusters. Finally, one to eight new monitoring sites were selected from five clusters. Discussion: The proposed monitoring design will help future studies determine the locations of new monitoring sites representing spatial variability across residences for epidemiological analyses.

Association between exposure to traffic-related air pollution and pediatric allergic diseases based on modeled air pollution concentrations and traffic measures in Seoul, Korea: a comparative analysis

“…We estimated a few summary predictors with more than 300 geographic variables using partial least squares (PLS) [34]. For PM 2.5 , because the PLS summary predictors showed an overfitting pattern, we instead applied land use regression, including five geographic variables selected using forward selection [35]. These models showed good performance for all three pollutants (cross-validated R 2 s of 0.83, 0.82, and 0.69 for NO 2 , PM 10 , and PM 2.5 , respectively), indicating good prediction ability.…”

Ambient Air Pollution and Kawasaki Disease in Korean Children: A Study of the National Health Insurance Claim Data

“… 27 , 28 The urban background monitoring sites are mostly located at the community‐service centers in largely populated residential areas. 29 Thus, these monitoring sites may well represent air pollution exposure to residents of the district. Majority of the children under 5 years old lived Seoul Metropolitan Area including Seoul and its neighboring metropolitan cities (Incheon and Gyeonggi‐do), and there are 66 districts with relatively small sizes (median size=44 km 2 in 2007).…”

Installation Planning in Regional Thermal Power Industry for Emissions Reduction Based on an Emissions Inventory

“…According to the investigation and verification, the total emissions from thermal power units in this region were 298,431.18 (SO 2 ), 60,321.190 (NO x ), and 72,007.47 (PM) tons, while the values were 311,706.7 (SO 2 ), 709,217.7 (NO x ), and 85,140.7 (PM) tons, according to the Annual Statistic Report [17]. The probable reason is that the statistics of some thermal power plants in the region were not accurately recorded.…”