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Although fixed ambient air monitoring stations provide data regarding ambient PM2.5 concentrations within a given community, they present limitations in terms of assessing the actual exposure to individuals and populations using time-activity patterns. The population exposure of a community may be estimated by classifying the population according to the time-activity pattern and modeling their exposure. In this study, we provide a possible methodology to assess the population exposure to PM2.5 in a given community. Five field technicians conducted exposure simulations for similar time-activity groups of preschool children, school students, homemakers, office workers, and elderly, with PM2.5 personal exposure monitoring (PEM) equipment, in Guro-gu, Seoul, Korea. The PM2.5 exposure concentrations were modeled by interpolation (point in polygon, inverse distance weighted, and ordinary kriging methods) and regression models using GPS data and a sensor-based air monitoring instrument network, and were compared with the PEM data. The population exposure to PM2.5 was estimated using the population-weighted average through Monte–Carlo simulation. Elderly presented the highest average PM2.5 exposure concentration followed by office workers, homemakers, preschool children, and school students. The correlation between the measured and modeled exposure was good, in the order of ordinary kriging (R2 = 0.822), inverse distance weighted (R2 = 0.747), and point in polygon methods (R2 = 0.721). Thirty-seven percent of the population in a community was exposed to PM2.5 concentrations higher than 35 μg/m3, which is the Korean Atmospheric Environmental Standard for PM2.5 (24-h average). It is suggested that this methodology could be applied to assess the real-time and long-term cumulative exposures of a given community. It is expected that an exposure surveillance system can be developed based on these results.

The 2014 Time-Use Survey of Statistics Korea revealed that office workers are increasingly spending more than eight hours at work. This study conducted an exposure assessment for office workers in Korea. Indoor and outdoor air pollutants were measured in offices. A self-administered questionnaire was employed to determine work information, indoor air quality (IAQ) awareness, and subjective symptoms for 328 workers. Indoor air concentrations for measured air pollutants were below IAQ guideline values. The average concentrations of target air pollutants did not show significant differences except for benzene, which had relatively a higher concentration in national industrial complexes. The indoor benzene, ethylbenzene, and acetaldehyde concentrations were higher in offices where workers were having dry eye, ophthalmitis, and headache symptoms. This study provides reference values to manage IAQ in offices, suggesting that if the benzene concentration exceeds 4.23 μg/m3 in offices, it could cause dry eye symptoms. Considering the increasing working hours for office workers and health effects, workers’ exposure to indoor pollutants should be reduced. In addition, the IAQ was heavily influenced by outdoor air levels and various indoor sources. Therefore, in areas with relatively high air pollution, greater monitoring and management is required considering the influence of outdoor air quality.

Exposure to indoor particulate matter (PM) is a potential risk factor that increases systemic inflammation and affects erythropoiesis. This study investigated the association between exposure to indoor PM and blood indicators related to anemia (BIRA) in housewives. Indoor PM and blood folate status are important factors in the risk of anemia. This was a housewife cohort study; we recruited 284 housewives in Seoul and Ulsan, Republic of Korea. Indoor exposure to PM2.5 and PM10 was measured by gravimetric analysis and sensors. We investigated the BIRA, such as hemoglobin (Hb), hematocrit, mean corpuscular volume (MCV), mean corpuscular Hb (MCH), and mean corpuscular Hb concentration (MCHC). Statistical analysis was performed by multiple linear regression model and mediation analysis. The association between BIRA and PM was assessed by multiple linear regression models fitted by mediation analyses. The increase in the level of indoor PM2.5 was associated with a decrease in MCV (Beta coefficient (B): −0.069, Standard error (SE): 0.022) and MCH (B: −0.019, SE: 0.009) in gravimetric measurements. The increase in the level of indoor PM2.5 was associated with a decrease in Hb (B: −0.024, SE: 0.011), hematocrit (B: −0.059, SE: 0.033), and MCV (B: −0.081, SE: 0.037) and MCH (B: −0.037, SE: 0.012) in sensor measurements (PM2.5-Lag10). Further, we identified a serum folate-mediated PM effect. The indoor PM exposure was significantly associated with decreased Hb, MCV, and MCH in housewives. Taken together, our data show that exposure to indoor PM is a risk factor for anemia in housewives. Blood folate concentration can be a mediating factor in the effect of indoor PM on BIRA. Therefore, folate intake should be recommended to prevent anemia in housewives. Moreover, indoor PM exposure should be managed.

To prevent severe air pollution, it is important to analyze time-series air quality data, but this is often challenging as the time-series data is usually partially missing, especially when it is collected from multiple locations simultaneously. To solve this problem, various deep-learning-based missing value imputation models have been proposed. However, often they are barely interpretable, which makes it difficult to analyze the imputed data. Thus, we propose a novel deep learning-based imputation model that achieves high interpretability as well as shows great performance in missing value imputation for spatio-temporal data. We verify the effectiveness of our method through quantitative and qualitative results on a publicly available air-quality dataset.

Background: Particulate matter and urban air pollution affect the human body and can lead to death. Epidemiological studies should consider exposure to pollutants and the diverse responses of individuals, depending on their sensitivity to the pollutants. Methods: In this study, air pollution measurements were obtained hourly at measuring stations operated by national and local governments to increase the reliability of the measured values. A β-ray absorption method was used to analyze the measurements of fine dust and determine the particulate matter content. Results: The air pollution data were log-linear, thereby enabling a comparison of data from different time periods. The comparison was made by focusing on the period of the implementation of Seoul’s fine dust policy. It was observed that the cancer incidence rate decreased after the implementation of the policy. The data on individual characteristics were obtained from a survey of Seoul citizens conducted from 2015 to 2016 using indicators such as quality of life and the social trust of Seoul citizens. Conclusion: The survey on the living environment and residence indicated that 80% of the heads of households were men. Women had a greater dissatisfaction than men with their residential, economic, and social environments. The survey questions on well-being were related to elements of internal and external environments, such as air pollution, noise, and fine dust.

Background There has been an increasing need to update the recommended values of Korean exposure factors for adults aged 19 and older, as using exposure factors developed over a decade ago could reduce risk assessment reliability. Objective Exposure factor data have been compiled and standardized using the latest national statistical reports and academic literature, as well as studies conducted from 2016 to 2018. Methods The updated data contained anthropometric parameters, inhalation rates, food and drinking water ingestion rates, and time-activity patterns and provided technical information on Koreans’ exposure factors classified by sex, age group, per capita and general population, and doer-only for various exposure assessments. Results Although the average life expectancy, body weight, body surface area, and inhalation rate increased slightly compared to the 2007 Korean Exposure Factor Handbook, differences various in food consumption were remarkable. Because of Asians’ similar food preferences, the intake rate of grain products and vegetables in Koreans, Chinese, and Japanese contributed much toward total intake. Koreans spent half their times outdoors compared to Americans and Chinese. Significance This study provided the currently updated exposure factor information for Koreans and could be compared with recommendations provided by exposure factor resources in various countries. Impact statement Exposure to environmental pollutants may significantly vary depending on the exposure factors related to human behaviors and characteristics. Therefore the exposure factors need to be continuously updated along with more extensive survey areas and improved measurement methods. We utilized the existing data with the aim to develop general exposure factors for risk assessment in Korean aged ≥19 years. Measurements and questionnaire surveys were also performed if there were no existing data. This study provided the currently updated exposure factor information for Koreans and could be compared to those of other countries.

Background: Particulate matter and urban air pollution affect the human body and can lead to death. Epidemiological studies should consider the exposure to pollutants and the diverse responses of individuals depending on their sensitivity to the pollutants. Methods: In this study, air pollution measurements were obtained hourly at measuring stations operated by the national and local governments to increase the reliability of the measured values. A β-ray absorption method was used to analyze the measurements of fine dust and determine the particulate matter content. Results: The air pollution data were log-converted to enable the comparison of data from different time periods. The comparison was made, focusing on the period of Seoul's fine dust policy. As a result, the cancer incidence rate also decreased after the policy. The data on individual characteristics were obtained from a survey of Seoul citizens conducted from 2015 to 2016 and using indicators such as the quality of life and social trust of Seoul citizens. Concludions: The survey on the living environment and residence indicated that 80% of the heads of households were men. Women had a greater dissatisfaction than men with the residential, economic, and social environments. The survey questions on well-being were related to the internal and external environment such as air pollution, noise, and fine dust.

Human exposure to air pollution is a major public health concern. Environmental policymakers have been implementing various strategies to reduce exposure, including the 10th-day-no-driving system. To assess exposure of an entire population of a community in a highly polluted area, pollutant concentrations in microenvironments and population time–activity patterns are required. To date, population exposure to air pollutants has been assessed using air monitoring data from fixed atmospheric monitoring stations, atmospheric dispersion modeling, or spatial interpolation techniques for pollutant concentrations. This is coupled with census data, administrative registers, and data on the patterns of the time-based activities at the individual scale. Recent technologies such as sensors, the Internet of Things (IoT), communications technology, and artificial intelligence enable the accurate evaluation of air pollution exposure for a population in an environmental health context. In this study, the latest trends in published papers on the assessment of population exposure to air pollution were reviewed. Subsequently, this study proposes a methodology that will enable policymakers to develop an environmental health surveillance system that evaluates the distribution of air pollution exposure for a population within a target area and establish countermeasures based on advanced exposure assessment.

Depending on the characteristics of the industrial area, toxicity evaluation of human body, risk assessment and health impact assessment may directly cause cancer due to air pollution. Environmental data collection is from August 2018 to January 31, 2019, and the average, minimum, and maximum values of air pollution data respectively. According to the global data on global trends using the Big Data, high blood pressure is confirmed at 33rd place in the world, and myocardial infarction among the environmental diseases is confirmed to be lower than Korea. Disease that occurred in Jeolla province industrial complex considering the characteristics of our country was identified as representative. Air pollutants are considered to be the causes of allergic diseases in Korea. PM10 was found to be higher than the control area (28.8804348 (㎍ / ㎥), 31.7065217 (㎍ / ㎥) and 32.8532609 (㎍ / ㎥). The mean concentrations of PM2.5 in the middle and high exposure areas were lower than those of the control areas, but the highest in the intermediate exposure areas was 16.5978261 (㎍ / ㎥), 16.1086957 (㎍ / ㎥) and 17.1847826 (㎍ / ㎥) respectively. The relationship between the major variables of environmental exposure in Yeosu was confirmed to be correlated with high blood pressure, chronic obstructive pulmonary disease (COPD), bronchitis, cerebrovascular, diabetes, thyroid disease, sinus infection, anemia and pneumonia.

School classrooms are one of the most densely populated indoor environments. Students are likely to be exposed to indoor air pollutants because they spend most of their time in the classroom. Consequently, indoor air quality (IAQ) management in classrooms is essential. Air purifiers have been installed in all school classrooms by the Ministry of Education in Korea because of concerns regarding particulate matter (PM). This study assessed the IAQ in school classrooms and suggested IAQ management methods. Sensor-based instruments were installed in each test classroom to measure the PM and carbon dioxide (CO2) concentrations on weekdays over six months in 2019. The PM10 (PM of 10 μm or less in diameter) concentration in the classroom was

There has been an increasing need for the risk assessment of external environmental hazards in children because they are more sensitive to hazardous chemical exposure than adults. Therefore, the development of general exposure factors is required for appropriate risk assessment in Korean children. This study aimed to determine the general exposure factors among Korean children aged &le, 18 years. We developed the recommended exposure factors across five categories: physiological variables, inhalation rates, food and drinking water intake, time&ndash, activity patterns, and soil and dust ingestion. National databases were used, and direct measurements and questionnaire surveys of representative samples were performed to calculate the inhalation rate, water intake, and soil ingestion rate. With regard to the time&ndash, activity patterns, the daily inhalation rates ranged from 9.49 m3/day for children aged 0&ndash, 2 years to 14.98 m3/day for those aged 16&ndash, 18 years. This study found that Korean children spent an average of 22.64 h indoors, 0.63 h outdoors, and 0.73 h in-transit on weekdays. The general exposure factors of Korean children were studied for the first time, and these results could be used to assess children&rsquo, s exposure and risk. They also suggest the differences compared with the results of international results.

Many consumer spray products are sold for various purposes. Use of spray products can cause adverse health effects. This study evaluated exposure factors for consumer spray products and assessed the particle inhalation exposure. Six consumer spray products were evaluated: an automobile interior cleaner, car deodorizing spray, anti-static spray, waterproofing spray, microorganism deodorizer, and disinfectant spray. The exposure factors were based on 10,000 respondents over 15 years old. Inhalation dose was calculated from the concentration released into the room air and time used. The use rates of the spray products ranged from 0.4 to 11% and differed significantly by gender (p 0.001). Aerosol types had a higher mass per use and longer duration of usage than trigger types. The median concentration of the trigger type ranged from 17.35 to 373.38 mg/m

Humidifier disinfectant (HD) is a household biocidal product used in humidifier water tanks to prevent the growth of microorganisms. In 2011, a series of lung injury cases of unknown causes emerged in children and pregnant women who had used HD in Korea. This study investigated changes in the nationwide number of cases of humidifier disinfectant-associated lung injury (HDLI) in concordance with nationwide HD consumption using data covering the entire Korean population. More than 25 kinds of HD products were sold between 1994 and 2011. The number of diagnosed HDLI, assessed by S27.3 (other injuries of lungs) of the Korea National Health Insurance Service (NHIS) data, sharply increased by 2005, subsequently decreased after 2005, and almost disappeared after 2011 in concordance with the annual number of HD sales. The number of self-reported HDLIs, assessed using data from all suspected HDLI cases registered in the Korea Ministry of Environment, changed with the annual number of HD sales, with a delay pattern, potentially induced by the late awareness of lung injury diseases. The present study suggests that changes in the nationwide annual consumption of HD products were consistent with changes in the annual number of HDLI cases in Korea.

Background Particulate matter (PM) less than 2.5 μm in diameter and 10 μm (PM10) contains heavy metals, but whether exposure to PM is significantly associated with the burden of heavy metal exposure in the population is unknown. We investigated the association between exposure to PM and blood concentrations of lead (Pb), cadmium (Cd), and mercury (Hg) in Korean housewives. Materials & Methods From July 2017 to January 2020, we recruited 115 housewives in Ulsan, Republic of Korea. After excluding participants with missing information, we finally included 88 Korean housewives in our study. We measured the concentrations of indoor PM using a gravimetric method 24 h before blood sampling and the concentrations of Cd, Pb, and Hg in blood, twice at a 1-year interval. We used a linear mixed effect model to estimate the associations between indoor PM and blood heavy metals. Results Exposure to PM10 was significantly associated with blood concentrations of Cd among Korean housewives. A 10 μg/m3 increase of PM10 the previous day was associated with a 2.8% (95% confidence interval (CI) = 1.1%, 4.6%) and a 1.5% (95% CI = −0.1%, 3.1%) increase in blood concentrations of Cd and Pb in the linear mixed effect model, respectively. Conclusion There was a significant association between indoor PM exposure and blood Cd concentrations among Korean housewives. This result suggests that the body burden of heavy metals is significantly associated with air pollution.

Objectives: Determining the time activity patterns of urban populations is critical when performing an exposure assessment. The purposes of this study were to classify urban populations in Korea by their time activity patterns and to identify factors that influence these patterns. Methods: The time activity patterns of 31,634 and 20,263 individuals were obtained from two national databases collected in 2004 and 2009, respectively. The two largest metropolitan cities in Korea, Seoul and Busan, were selected for this analysis. For each city, multivariate linear regressions were performed to determine factors affecting the time spent in a residence and in transit. We also used cluster analysis to classify each urban population by activity pattern. Results: Nine distinctive activity patterns were identified in the Seoul and Busan populations, respectively, and the resulting classified population groups had specific characteristics. The identified patterns were similar for Seoul and Busan. The most significant factors affecting time spent in a residence were employment status, age, marriage status, education, and gender. Gender, education, employment status, and monthly income were significant factors affecting time spent in transit. Conclusion: These results indicate that, in addition to region, exposure scientists in Korea should consider classifying populations based on age, gender, and occupation.

PURPOSE The objective of this study was to measure secondhand smoke (SHS) exposure in personal computer (PC) rooms with the purpose of determining the strength of scientific evidence supporting the legislative ban on smoking in PC rooms located in the Republic of Korea. MATERIALS AND METHODS From June to September 2012, particulate matter (PM2.5) and air nicotine concentration (ANC) were measured in the smoking and non-smoking areas of PC rooms in Goyang City, Korea. In 28 randomly sampled PC rooms, field investigators completed an observational questionnaire on building characteristics, smoking policies, and evidence of smoking. The geometric means (GM) of PM2.5 and ANC in smoking and non-smoking areas were compared. RESULTS Evidence of smoking was identified in both the smoking and non-smoking areas of all PC rooms. The GMs of PM2.5 and ANC in both areas were high and did not differ significantly (174.77 μg/m(3) and 48.95 μg/m(3) in smoking areas; 93.38 μg/m(3) and 41.30 μg/m(3) in non-smoking areas). Overall PM2.5 concentrations were 5.5-fold higher than those listed in the World Health Organization guidelines. CONCLUSION This study supported previous reports that a partial smoking ban did not protect individuals from SHS exposure. Furthermore, the results from our study suggest how research can support policy. Countries in which smoke-free policies are not yet comprehensive may find our results useful.

Exposure to air pollution has a significant impact on the health of urban populations, so the improvement of methods that model the concentrations of air pollutants within complex urban areas is important in health studies to adequately asses the exposure of the population. This paper presents several hybrid, high-resolution models to simulate the variability of ambient NO2 concentrations in Seoul, the capital of South Korea. These models combine the Community Multiscale Quality (CMAQ) as a regional photochemical model with a fine scale model of either the California Puff dispersion model (CALPUFF) or the land use regression model (LUR). We compared high-resolution estimates of the spatial NO2 concentration from four different hybrid models, including 1) raw CMAQ-CALPUFF; 2) observation-fused CMAQ-CALPUFF; 3) raw CMAQ-LUR; and 4) observation-fused CMAQ-LUR. We conducted numerical simulations of the NO2 concentrations during the winter season and compared the results with field data obtained from mobile measurements captured from December 2017 to February 2018. The results indicate that observation-fused hybrid models offered improved agreement with the mobile measurements: for the CMAQ-CALPUFF model, statistical bias and error were reduced to about 82% and 57%, respectively by using observation-fused CMAQ. We also found significant differences in the sub-grid variability of the NO2 concentrations for the different hybrid models. The predictions obtained with CMAQ-CALPUFF showed concentrations that were more widely distributed (1.7 and 1.4 times for the 10–90th range, observation-fused case) when compared to the only-CMAQ and CMAQ-LUR predictions, respectively. Our study suggests that a properly evaluated hybrid model can increase the predictive accuracy of air pollutant concentration in complex urban areas to improve exposure assessments in health studies.

Children spend a considerable amount of time in daycare centers, kindergartens, and elementary schools. Poor indoor air quality (IAQ) in the educational facilities can affect the health of the children and impair their academic performance. The prediction of real-time PM10 concentration could be useful to intervene the problem of poor IAQ. This study developed models to predict real-time indoor PM10 concentration in the daycare centers, kindergartens, and elementary schools using outdoor environmental data. Indoor PM10 concentrations were measured in 54 daycare centers, 12 kindergartens, and 21 elementary schools in Seoul, South Korea, using a real-time monitor (AirGuard K) over a period of one year. Multiple linear regression models were used to predict real-time indoor PM10 concentration in these educational facilities using outdoor PM10 and meteorological data as input variable. Four formations (original, ratio of indoor-to-outdoor, root-transformation, and log-transformation) for dependent variable were compared to determine the best performance of the model. A 10-fold cross-validation method was used to evaluate the accuracy of the prediction models. Daycare centers showed the highest indoor PM10 concentration. Root-transformed models with high accuracy were developed to predict the real-time indoor PM10 concentration in educational facilities every 10 min. The R2 of the prediction models were 0.64 in the daycare centers, 0.45 in the kindergartens, and 0.43 in the elementary schools. The 24 h profile of the predicted indoor PM10 was similar to the measured PM10 concentration. The prediction models could provide real-time PM10 levels in educational facilities without direct indoor measurement and observation.

Since the global enforcement of smoke-free policies, indoor smoking has decreased significantly, and the characteristics of non-smokers&rsquo, exposure to secondhand smoke (SHS) has changed. The purpose of this study was to assess the temporal and spatial characteristics of SHS exposure in non-smokers by combining questionnaires and biomarkers with time activity patterns. To assess SHS exposure, biomarkers such as cotinine and 4-(methylnitrosamino)-1-3-(pyridyl)-1-butanol (NNAL) in urine and nicotine in hair were collected from 100 non-smokers in Seoul. Questionnaires about SHS exposure and time activity patterns were also obtained from the participants. The analysis of biomarker samples indicated that about 10% of participants were exposed to SHS when compared with the criteria from previous studies. However, 97% of the participants reported that they were exposed to SHS at least once weekly. The participants were most exposed to SHS in the outdoor microenvironment, where they spent approximately 1.2 h daily. There was a significant correlation between the participants&rsquo, time spent outdoors and self-reported SHS exposure time (r2 = 0.935). In this study, a methodology using time activity patterns to assess temporal and spatial characteristics of SHS exposure was suggested. The results of this study may help develop policies for managing SHS exposure, considering the time activity patterns.

Most people may be affected by indoor air quality at home since it is where they spend most of their time. Although air pollutants (APs) concentrations such as particulate matter, SO2, NO2, CO, and...