Evaluation of the Exposure to Environmental Pollutants Emanating from National Industrial Complexes

The industrial complexes built during the course of economic development in South Korea played a pivotal role in the country’s rapid economic growth. However, this growth was accompanied by health problems due to the pollutants released from the industrial complexes inevitably located near residential areas, given the limited land area available in South Korea. This study was conducted to evaluate the exposure to each pollutant emanating from industrial complexes for residents living in nearby areas, and to determine the substances requiring priority attention in future surveys. Pollutants were comprehensively categorized according to their emission and exposure levels based on data previously collected from the study areas. The emission, ambient concentration, and biomarker concentration levels of major pollutants emitted from eight national industrial complexes (Ulsan, Pohang, Gwangyang, Yeosu, Chungju, Daesan, Sihwa, and Banwol) were determined and tabulated. Each of the values was compared with the national/local average values, reference values, or control area concentrations depending on availability. Substances with completed exposure pathways and with high values for emissions, ambient concentrations, and biomarker concentrations were considered the substances posing exposure risks to the residents living near the corresponding industrial complex. The substances requiring continuous monitoring or supplementary exposure investigation were also categorized and presented. Lead and benzene had higher values for emissions, ambient concentrations, and biomarker concentrations in the Ulsan Industrial Complex area; thus, they were most likely to pose exposure risks to residents living in the area’s neighborhoods. In other areas, styrene, xylene, cadmium, nitrogen oxide, trichloroethylene, nickel, manganese, and chromium required continuous monitoring, and arsenic, nickel, manganese, and chromium required biomarker measurements. In conclusion, the substances identified and categorized in this study need to be given appropriate attention in future surveys on exposure risks and health effects related to industrial complexes

Comparison of the air change per hour measured over four seasons in the residential buildings of the urban, rural, and industrial areas of South Korea: K-IOP Study

Air infiltration, calcuated by air changes per hour (ACH) is a key factor in assessing the potential amount of air borne pollutants moving from outdoor into indoor spaces. We measured the natural ACH through fall, winter, spring, and summer (2 weeks/season), in 81 nonsmoking elderly houses located in urban (n = 29), industrial (n = 26) and rural (n = 26) areas from 2021 to 2022 consecutively. Indoor CO2 data measured at dawn (01:00 to 05:00 a.m.) over four season was used to estimate the ACH. Moreover, morning ACHs were also calculated from the CO2 level monitored in the morning, when the levels were dropped significantly with opening a window during fall, winter, and spring. The ACH at dawn over the four seasons ranged from 0.02 to 0.03,while that in the morning with opening a window was 0.2 to 0.3. Our multivariate regression models demonstrated that the difference in CO2 concentration during dawn was positively associated with the ACH change after adjusting for seasonality. In addition, after controlling for the study area, ACH was approximately 50 % higher during summer than during the other seasons (p < 0.05). This study elucidates the seasonal and regional distributions of ACH; a determination of these patterns may further contribute to future simulation or prediction studies assessing the associations among indoor air quality, activity patterns and ventilation practices among Korean elderly population

Ambient particulate matter and surrounding greenness in relation to sleep quality among pregnant women: A nationwide cohort study

Background: Particulate air pollution and residential greenness are associated with sleep quality in the general population; however, their influence on maternal sleep quality during pregnancy has not been assessed. Objective: This cross-sectional study investigated the individual and interactive effects of exposure to particulate matter (PM) air pollution and residential greenness on sleep quality in pregnant women. Methods: Pregnant women (n = 4933) enrolled in the Korean Children's Environmental Health Study with sleep quality information and residential address were included. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). The average concentrations of PM (PM2.5 and PM10) during pregnancy were estimated through land use regression, and residential greenness in a 1000 m buffer area around participants' residences was estimated using the Normalized Difference Vegetation Index (NDVI1000-m). Modified Poisson regression models were used to estimate the associations between PM and NDVI and poor sleep quality (PSQI >5) after controlling for a range of covariates. A four-way mediation analysis was conducted to examine the mediating effects of PM. Results: After adjusting for confounders, each 10 μg/m3 increase in PM2.5 and PM10 exposure was associated with a higher risk of poor sleep quality (relative risk [RR]: 1.06; 95% confidence interval [CI]: 1.01, 1.11; and RR: 1.09; 95% CI: 1.06, 1.13, respectively), and each 0.1-unit increase in NDVI1000-m was associated with a lower risk of poor sleep quality (RR: 0.97; 95% CI: 0.95, 0.99). Mediation analysis showed that PM mediated approximately 37%–56% of the association between residential greenness and poor sleep quality. Conclusions: This study identified a positive association between residential greenness and sleep quality. Furthermore, these associations are mediated by a reduction in exposure to particulate air pollution and highlight the link between green areas, air pollution control, and human health