Proposal of a Methodology for Prediction of Indoor PM2.5 Concentration Using Sensor-Based Residential Environments Monitoring Data and Time-Divided Multiple Linear Regression Model.

This study aims to propose an indoor air quality prediction method that can be easily utilized and reflects temporal characteristics using indoor and outdoor input data measured near the indoor target point as input to calculate indoor PM2.5 concentration through a multiple linear regression model. The atmospheric conditions and air pollution detected in one-minute intervals using sensor-based monitoring equipment (Dust Mon, Sentry Co Ltd., Seoul, Korea) inside and outside houses from May 2019 to April 2021 were used to develop the prediction model. By dividing the multiple linear regression model into one-hour increments, we attempted to overcome the limitation of not representing the multiple linear regression model's characteristics over time and limited input variables. The multiple linear regression (MLR) model classified by time unit showed an improvement in explanatory power by up to 9% compared to the existing model, and some hourly models had an explanatory power of 0.30. These results indicated that the model needs to be subdivided by time period to more accurately predict indoor PM2.5 concentrations.

Evaluation of particulate matter concentrations according to cooking activity in a residential environment.

This study aimed to determine the ventilation conditions required for suitable indoor air quality management during cooking in a typical South Korean residential home. We measured the concentrations of particulate matter (PM10) and fine particulate matter (PM2.5) under different ventilation conditions during the cooking of different food materials in the kitchen of a multi-family house, which is the representative residential space in South Korea. Pork belly and mackerel, which are the staple meat and fish products of Korean people, were prepared (200 g of each) and cooked via roasting. The PM10 and PM2.5 concentrations were measured three times for 1 h at 1 min intervals under twelve ventilation conditions. To investigate the PM10 and PM2.5 concentration distribution characteristics and the reduction effect according to ventilation condition, the ratio of the concentration during cooking to the initial concentration was calculated for each condition. Factors causing the emission of PM10 and PM2.5 for each food material and under each ventilation condition were analyzed using principal component analysis and verified using one-way analysis of variance and post hoc analysis. The PM10 and PM2.5 concentrations generated during the cooking of pork belly and mackerel reached their maximum values when no ventilation was used. Under this condition, PM10 concentrations were 246.27 and 1227.71 µg/m3 while the PM2.5 concentrations were 161.93 and 760.82 µg/m3 for pork belly and mackerel cooking, respectively. The PM10 and PM2.5 concentrations were also found to be high when a range hood and air cleaner were used, indicating that it is necessary to improve the performance of ventilation devices and to use appropriate ventilation methods. The use of natural ventilation exhibited a high PM10 and PM2.5 reduction effect compared with the ventilation conditions that used ventilation devices. Using natural ventilation together with ventilation devices was found to be the most effective method of reducing the PM10 and PM2.5 generated during cooking. In conclusion, PM10 and PM2.5 concentrations generated during the cooking of pork belly and mackerel varied depending on the ventilation condition, but they were high when inappropriate ventilation methods were used. Therefore, using appropriate ventilation conditions is effective in reducing PM10 and PM2.5 generated during cooking.

Health risk assessment for multimedia exposure of formaldehyde emitted by chemical accident.

This study was conducted to provide basic data for chemical accident response by assessing the health risks of residents living near a chemical accident site due to long-term exposure. The study considered the temporal concentration changes of the leaked chemical (i.e., its behavior in the environment and dilution) until its extinction. A virtual chemical accident was assumed, in which 40 t of formaldehyde was accidentally discharged for 1 h in Ulsan Metropolitan City, Korea. Formaldehyde concentrations over time in each environmental medium after the accident were calculated using a multimedia environmental dynamics model. Exposure subjects divided into four age groups were considered. Carcinogenic risks due to respiration and non-carcinogenic risks due to soil intake were assessed. For all the age groups, the excess cancer risk did not exceed 1.0 × 10-6, indicating that no harmful health impact was caused by inhalation exposure to formaldehyde. The hazard index exceeded 1 for all the age groups, confirming that harmful health impacts were caused by exposure to soil containing the formaldehyde. This study is the first to assess chronic health risks by reflecting long-term residual and temporal concentration changes of a pollutant released in a chemical accident in each environmental medium until its extinction. This work is also significant in that it reflects the exposure characteristics of the toxic chemical.

Distribution and Influencing Factors of Airborne Bacteria in Public Facilities Used by Pollution-Sensitive Population: A Meta-Analysis.

The aim of this study was to support management of airborne bacteria in facilities used by pollution-sensitive individuals (in daycares, medical facilities, elder care facilities, and postnatal care centers). A field survey was conducted on 11 facilities from October 2017 to April 2018. Elder care facilities in industrial, urban, and forested areas were excluded. Two indoor, and one outdoor, measuring points were selected per facility. These points were located in areas most often used by the residents. Measurements were taken at random time-points before February 2018 and at specific times in the morning and afternoon thereafter. The relationships among bacterial counts, carbon dioxide concentrations, dust levels, temperature, relative humidity, and ventilation were examined. The pooled average bacterial counts at the daycares, medical facilities, elder care facilities, and postnatal care centers were 540.25 CFU m-3, 245.49 CFU m-3, 149.63 CFU m-3, and 169.65 CFU m-3, respectively. Considering the upper 95% confidence interval, the bacterial counts in many daycares may in fact be >800 CFU m-3, which is the threshold set by the Korean Ministry of the Environment. The pooled average indoor: outdoor bacterial count ratio was 1.13. Indoor airborne bacterial counts were influenced mainly by their sources. This study found no significant correlations among indoor temperature, relative humidity, carbon dioxide concentration, dust levels, and airborne bacterial counts, unlike previous studies. Airborne bacteria management at daycares should be a top priority. The sources of airborne bacteria must also be identified, and a management plan must be developed to control them.

Reliability of Low-Cost, Sensor-Based Fine Dust Measurement Devices for Monitoring Atmospheric Particulate Matter Concentrations.

Currently, low-cost, sensor-based fine dust measurement devices are commercially available in South Korea. This study evaluated the reliability of three such devices-Yi Shan A4, Plantower PMS7003, and Plantower PMS7003-in comparison to long-term consecutive monitoring systems for discharge and prevention facilities regarding fine dust control. The performance of these devices for concentration intervals over time was examined through real-time comparison using a GRIMM (Model: 11-A, dust spectrometer from Grimm Technologies) as a reference; this included a correction factor (C-Factor), calculated by a gravimetric method and an equivalence test. For comparison, the reference and target devices were installed in a chamber with fine dust concentrations of 2 µg/m3, with temperature and humidity maintained at 20 °C and 40%, respectively. The fine particulate matter (PM)2.5 concentrations were classified into five intervals: ≤40 µg/m3, 40⁻80 µg/m3, 80⁻120 µg/m3, 120⁻160 µg/m3, and 200⁻230 µg/m3. Statistical analysis was performed using data obtained from national stations for monitoring and controlling fine dust released from facilities under high fine dust loading conditions. The results showed that the measurements of all target devices, which were corrected according to the reference device, provided accurate values at PM2.5 concentrations of ≥40 µg/m3. The statistical analysis results suggest that the evaluated devices are more reliable than the conventional numerical-analysis-based monitoring system.

Indoor radon concentration in Korea residential environments.

The purpose of this study is to provide basic data for the evaluation and management of health effects with respect to exposure to radon within residential environments in South Korea. It is part of a case-control study to develop a management plan based on indoor radon exposure levels and assess their impact on health. To investigate the long-term cumulative concentration levels of radon, 599 patients who have respiratory diseases were recruited in South Korea, and alpha track detectors were installed in their residences for a period of 3 months from mid-2015 to late 2016. A survey was then conducted to determine the factors affecting the radon concentration. The radon concentration levels were analyzed in conjunction with the survey results. The results show that the arithmetic mean of the radon concentrations in domestic residences was in the range of 70.8 ± 65.2 Bq/m3. An analysis of covariance (ANCOVA) was performed to identify the environmental factors affecting the radon concentration and contributing to variations in the residential radon concentration based on the height of the residence. The results show that the contribution of the local environmental factor to the variation in radon concentration (p < 0.05) was greater than that of other environmental factors. Although no statistically significant difference was found with regard to the construction year of the building before the control (p > 0.05), the same was found with regard to the construction year after the control (p < 0.05).