Web-Based Visualization of Scientific Research Findings: National-Scale Distribution of Air Pollution in South Korea.

BACKGROUND: As scientific findings of air pollution and subsequent health effects have been accumulating, public interest has also been growing. Accordingly, web visualization is suggested as an effective tool to facilitate public understanding in scientific evidence and to promote communication between the public and academia. We aimed to introduce an example of easy and effective web-based visualization of research findings, relying on predicted concentrations of particulate matter ≤ 10 µg/m3 (PM10) and nitrogen dioxide (NO2) obtained from our previous study in South Korea and Tableau software. Our visualization focuses on nationwide spatial patterns and temporal trends over 14 years, which would not have been accessible without our research results. METHODS: Using predicted annual average concentrations of PM10 and NO2 across approximately 250 districts and maps of administrative divisions in South Korea during 2001-2014, we demonstrate data preprocessing and design procedures in the Tableau dashboard, comprising maps, time-series plots, and bar charts. RESULTS: Our visualization allows one to identify high concentration areas, a long-term temporal trend, and the contrast between two pollutants. The application of easy tools for user-interactive options in Tableau suggests possible easy access to the scientific knowledge of non-experts. CONCLUSION: Our example contributes to future studies that develop the visualization of research findings in further intuitive designs.

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.

BACKGROUND: Pediatric allergic diseases are a major public health concern, and previous studies have suggested that exposure to traffic-related air pollution (TRAP) exposure is a risk factor. These studies have typically assessed TRAP exposure using traffic measures, such as distance to major roads, or by modeling air pollutant concentrations; however inconsistent associations with pediatric allergic diseases have often been found. Using road proximity and density, we previously found an association between TRAP and atopic eczema among approximately 15,000 children living in Seoul, Korea, heavily populated and highly polluted city in which traffic is a major emission source. We aimed to conduct a parallel analysis using modeled air pollution concentrations and thus examine the consistency of the association. Specifically, we examined the associations of individual-level annual-average concentrations of NO2, PM10, and PM2.5 with symptoms and diagnoses of three pediatric allergic diseases including asthma, allergic rhinitis, and atopic eczema. METHODS: The study population included 14,614 children from the Seoul Atopy Friendly School Project Survey in Seoul, Korea, in 2010. To assess individual exposures to TRAP among these children, we predicted annual-average concentrations of NO2, PM10, and PM2.5 at the children's home addresses in 2010 using universal kriging and land use regression models along with regulatory air quality monitoring data and geographic characteristics. Then, we estimated odds ratios (ORs) of the three allergic diseases for interquartile increases in air pollution concentrations after adjusting for individual risk factors in mixed effects logistic regression. RESULTS: Symptoms and diagnoses of atopic eczema symptoms showed an association with NO2 (OR = 1.07, 95% confidence interval = 1.02-1.13; 1.08, 1.03-1.14) and PM10 (1.06, 1.01-1.12; 1.07, 1.01-1.13). ORs of PM2.5 were positive but not statistically significant (1.01, 0.95-1.07; 1.04, 0.98-1.10). No association was found between asthma and allergic rhinitis, although PM2.5 showed a marginal association with allergic rhinitis. CONCLUSIONS: Our consistent findings regarding the association between TRAP and the prevalence of atopic eczema using traffic measures and surrogate air pollutants suggested the effect of TRAP on children's health. Follow-up studies should elucidate the causal link, to support subsequent policy considerations and minimize adverse health effects in children.

Association between Exposure to Traffic-Related Air Pollution and Prevalence of Allergic Diseases in Children, Seoul, Korea.

Although there has been suggestive evidence of the association between TRAP and ADs, findings remained inconsistent possibly due to limited population. We investigated the association between TRAP and ADs in a large population of children with rich spatial coverage and expanded age span in Seoul, Korea. TRAP exposures were estimated by categorized proximity to the nearest major road (≤150, 150-300, 300-500, and >500 m) and density of major roads within 300 meters from children's residences. We estimated the association between two TRAP exposures and three ADs using generalized mixed model after adjusting for individual characteristics. We also investigated whether the association varied by household and regional socioeconomic status. We found associations of atopic eczema with road density [OR = 1.08; 95% CI = 1.01-1.15] and road proximity [1.15, 1.01-1.32; 1.17, 1.03-1.34; and 1.16, 1.01-1.34 for ≤150, 150-300, and 300-500 m, resp., compared to >500 m]. There was no association with asthma and allergic rhinitis. Effect estimates were generally the highest in the low socioeconomic region. Children living in areas surrounded by large and busy roads were likely to be at greater risks for atopic eczema, with increased vulnerability when living in deprived areas.

Ordinary kriging approach to predicting long-term particulate matter concentrations in seven major Korean cities.

OBJECTIVES: Cohort studies of associations between air pollution and health have used exposure prediction approaches to estimate individual-level concentrations. A common prediction method used in Korean cohort studies is ordinary kriging. In this study, performance of ordinary kriging models for long-term particulate matter less than or equal to 10 µm in diameter (PM10) concentrations in seven major Korean cities was investigated with a focus on spatial prediction ability. METHODS: We obtained hourly PM10 data for 2010 at 226 urban-ambient monitoring sites in South Korea and computed annual average PM10 concentrations at each site. Given the annual averages, we developed ordinary kriging prediction models for each of the seven major cities and for the entire country by using an exponential covariance reference model and a maximum likelihood estimation method. For model evaluation, cross-validation was performed and mean square error and R-squared (R(2)) statistics were computed. RESULTS: Mean annual average PM10 concentrations in the seven major cities ranged between 45.5 and 66.0 µg/m(3) (standard deviation=2.40 and 9.51 µg/m(3), respectively). Cross-validated R(2) values in Seoul and Busan were 0.31 and 0.23, respectively, whereas the other five cities had R(2) values of zero. The national model produced a higher crossvalidated R(2) (0.36) than those for the city-specific models. CONCLUSIONS: In general, the ordinary kriging models performed poorly for the seven major cities and the entire country of South Korea, but the model performance was better in the national model. To improve model performance, future studies should examine different prediction approaches that incorporate PM10 source characteristics.