Background and objective: Aside from smoking, which is already recognized as a strong risk factor for COPD, interest in the impact of particulate matter (PM) on COPD is increasing. This study aimed to investigate the effect of PM, especially with an aerodynamic diameter ≤2.5 µm (PM_2.5), and its chemical constituents on the exacerbation of COPD. Methods: Data on hospital visits including admission and outpatient clinic visits for exacerbation of COPD in Chuncheon, Korea, between 2006 and 2012 were extracted from the National Health Insurance Service database. PM_2.5 and its chemical constituents were measured on the roof of the four-story Kangwon National University Natural Sciences building once every 3 days. Meteorological data were provided by the Korean Meteorological Administration. Results: During the study period, the mean level of PM_2.5 was 35.0±25.2 µg/m³, and the number of daily hospital visits were 6.42±4.28 and 2.07±1.93 for males and females, respectively. The number of COPD-related hospital visits increased with increasing PM_2.5 after adjusting for meteorological covariates and females tended to be more affected sooner than males. Among the PM_2.5 constituents, Al, Si, and elemental carbon were associated with increased hospital visits and there was a difference according to sex. In males, some constituents of PM_2.5 were related to an increased risk of a hospital visit, mainly on the first and second days of measurement (Lag1 and Lag2). In contrast, there was no significant increase in the risk of hospital visits due to any of the PM_2.5 constituents in females. Conclusion: Concentrations of PM_2.5 mass and some of the PM_2.5 constituents were associated with increased COPD-related hospital visits in Chuncheon.

As a global pollutant, mercury (Hg) is of particular concern in East Asia, where anthropogenic emissions are the largest. In this study, speciated Hg concentrations were measured on Yongheung Island, the westernmost island in Korea, located between China and the Korean mainland to identify the importance of local and regional Hg sources. Various tools including correlations with other pollutants, conditional probability function, and back-trajectory-based analysis consistently indicated that Korean sources were important for gaseous oxidized mercury (GOM) whereas, for total gaseous mercury (TGM) and particulate bound mercury (PBM), regional transport was also important. A trajectory cluster based approach, considering both Hg concentration and the fraction of time each cluster was impacting the site, was developed to quantify the effect of Korean sources and out-of-Korean sources. This analysis suggests that contributions from out-of-Korean sources were similar to Korean sources for TGM whereas Korean sources contributed slightly more to the concentration variations of GOM and PBM compared to out-of-Korean sources. The ratio of GOM/PBM decreased when the site was impacted by regional transport, suggesting that this ratio may be a useful tool for identifying the relative significance of local sources vs. regional transport. The secondary formation of PBM through gas-particle partitioning with GOM was found to be important at low temperatures and high relative humidity.

Fractional green vegetation cover (FVC) is a useful indicator for monitoring grassland status. Satellite imagery with coarse spatial but high temporal resolutions has been preferred to monitor seasonal and inter-annual FVC dynamics in wide geographic area such as Mongolian steppe. However, the coarse spatial resolution can cause a certain uncertainty in the satellite-based FVC estimation, which calls attention to develop a robust statistical test for the relationship between field FVC and satellite-derived vegetation indices. In the arid and semi-arid Mongolian steppe, nadir pointing digital camera images (DCI) were collected and used to produce a FVC dataset to support the evaluation of satellite-based FVC retrievals. An optimal DCI processing method was determined with respect to three color spaces (RGB, HIS, L*a*b*) and six green pixel classification algorithms, from which a country-wide dataset of DCI-FVC was produced and used for evaluating the accuracy of satellite-based FVC estimates from MODIS vegetation indices. We applied three empirical and three semi-empirical MODIS-FVC retrieval models. DCI data were collected from 96 sites across the Mongolian steppe from 2012 to 2014. The histogram algorithm using the hue (H) value of the HIS color space was the optimal DCI method (r² = 0.94, percent root-mean-square-error (RMSE) = 7.1%). For MODIS-FVC retrievals, semi-empirical Baret model was the best-performing model with the highest r² (0.69) and the lowest RMSE (49.7%), while the lowest MB (+1.1%) was found for the regression model with normalized difference vegetation index (NDVI). The high RMSE (>50% or so) is an issue requiring further enhancement of satellite-based FVC retrievals accounting for key plant and soil parameters relevant to the Mongolian steppe and for scale mismatch between sampling and MODIS data.

Background: Ambient air pollution can contribute to the development and exacerbation of COPD. However, the influence of air pollution on objective COPD phenotypes, especially from imaging, is not well studied. We investigated the influence of long-term exposure to air pollution on lung function and quantitative imaging measurements in a Korean cohort of participants with and without COPD diagnosis. Methods: Study participants (N = 457 including 296 COPD cases) were obtained from the COPD in Dusty Areas (CODA) cohort. Annual average concentrations of particulate matter less than or equal to 10 μm in diameter (PM₁₀) and nitrogen dioxide (NO₂) were estimated at the participants’ residential addresses using a spatial air pollution prediction model. All the participants underwent volumetric computerized tomography (CT) and spirometry measurements and completed survey questionnaires. We examined the associations of PM₁₀ and NO₂ with FVC, FEV₁, emphysema index, and wall area percent, using linear regression models adjusting for age, gender, education, smoking, height, weight, and COPD medication. Results: The age of study participants averaged 71.7 years. An interquartile range difference in annual PM₁₀ exposure of 4.4 μg/m³ was associated with 0.13 L lower FVC (95% confidence interval (CI), − 0.22- -0.05, p = 0.003). Emphysema index (mean = 6.36) was higher by 1.13 (95% CI, 0.25–2.02, p = 0.012) and wall area percent (mean = 68.8) was higher by 1.04 (95% CI, 0.27–1.80, p = 0.008). Associations with imaging phenotypes were not observed with NO₂. Conclusions: Long-term exposure to PM₁₀ correlated with both lung function and COPD-relevant imaging phenotypes in a Korean cohort.