Land Use Regression Model for Assessing Exposure and Impacts of Air Pollutants in School Children

Abstract

Epidemiologic studies of air pollution need accurate exposure assessments at unmonitored locations. A land use regression (LUR) model has been used successfully for predicting traffic-related pollutants, although its application has been limited to Europe, North America, and a few Asian region. Therefore, we modeled traffic-related pollutants by LUR then examined whether LUR models could be constructed using a regulatory monitoring network in Metropolitan area in Korea. We used the annual-mean nitrogen dioxide (NO 2 ) in 2010 in the study area. Geographic variables that are considered to predict traffic-related pollutants were classified into four groups: road type, traffic intensity, land use, and elevation. Using geographical variables, we then constructed a model to predict the monitored levels of NO 2 . The mean concentration of NO 2 was 30.71 ppb (standard deviation of 5.95) respectively. The final regression model for the NO 2 concentration included five independent variables. The LUR models resulted in R 2 of 0.59. The mean concentration of NO 2 of elementary schools was 34.04 ppb (standard deviation of 5.22) respectively. The present study showed that even if we used regulatory monitoring air quality data, we could estimate NO 2 moderately well. These analyses confirm the validity of land use regression modeling to assign exposures in epi- demiological studies, and these models may be useful tools for assessing health effects of long-term exposure to traffic related pollution.

Associations between Ambient Particulate Matter and Nitrogen Dioxide and Chronic Obstructive Pulmonary Diseases in Adults and Effect Modification by Demographic and Lifestyle Factors

“…Exposure to air pollution was assessed based on geo-coded residential addresses. Concentrations of PM 2.5 , PM 10 , and NO 2 at residential addresses were estimated using land-use regression (LUR) models using a previously described standardized method [ 27 ]. In brief, we modeled air pollutants using LUR models and a regulatory monitoring network, and used ambient concentrations of PM 2.5 , PM 10 , and NO 2 in the study area.…”

Preventive Effect of Residential Green Space on Infantile Atopic Dermatitis Associated with Prenatal Air Pollution Exposure

“…Exposure to TRAP was assessed based on geocoded residential addresses. The concentrations of PM 10 and NO 2 at the participant’s residential address were estimated using land-use regression (LUR) models following a previously described standardized method [ 29 ]. In brief, we modeled TRAP concentrations using a regulatory monitoring network and the ambient concentrations of PM 10 and NO 2 in the study area.…”

Lung Cancer Risk and Residential Exposure to Air Pollution: A Korean Population-Based Case-Control Study

“…Concentrations of PM 10 and NO 2 at residential addresses of the study participants were estimated by land-use regression (LUR) models following a standardized method that has been described elsewhere. 25 In brief, we modeled traffic-related pollutants by LUR using regulatory monitoring networks and used annual means for PM 10 and NO 2 in 2010. LUR models for PM 10 and NO 2 were conducted in nine areas (Seoul, Incheon, Busan, Ulsan, Gyeonggi, Chungcheong, Jeolla-Jeju, Daegu-Gyeongbook-Gangwon, and Gyeongnam) and were optimized locally.…”