Korea was one of the major consumers of asbestos in the late 1900s, and asbestos-related disease patients have been reported continuously to date, owing to long disease latency. Several studies have been conducted to predict the future incidence of malignant mesothelioma and lung cancer in Korea, but little is understood about the latency time. Therefore, the aim of this study is to estimate the latency period of malignant mesothelioma and asbestos-related lung cancer in Korea and its determinants. We obtained information from the Environmental Health Centers for Asbestos in Korea on the history of asbestos exposure and demographic characteristics of 1933 patients with malignant mesothelioma and asbestos-related lung cancer. In our study, the latency periods for malignant mesothelioma and lung cancer were 33.7 and 40.1 years, respectively. Regardless of the disease type, those with a history of exposure related to the production of asbestos-containing products or asbestos factories had the shortest latency period. In addition, we observed that those who worked in or lived near asbestos mines tended to have a relatively long disease latency. Smoking was associated with shorter latency, but no linear relationship between the lifetime smoking amount (expressed in pack years) and latent time was observed. In addition, the age of initial exposure showed a negative linear association with the latency period for mesothelioma and lung cancer.

Biocides are non-agricultural chemical agents for the prevention of unhygienic pests. The worldwide demand for biocidal products has been rapidly increasing. Meanwhile, biocides have been causing negative health effects for decades, resulting in public health scares. Therefore, governments around the world have tried to strictly control biocides, and it is necessary to prioritize the health risks of biocides for efficient management. Chemical ranking and scoring (CRS) methods have been developed for the effective management of chemicals. However, existing methods do not use suitable variables to evaluate biocides, thus possibly underestimating or overestimating the actual health risks. We developed a new CRS method that reflects the exposure and toxicity characteristics of biocides. Eleven indicators were chosen as appropriate for prioritizing biocides, and scoring based on the globally harmonized system of classification and labeling of chemicals (GHS) improved the efficiency of the method. Correlations between individual indicators in this study were low (−0.151–0.325), indicating that each indicator was independent and well-chosen for prioritizing biocides. The effect of each indicator on the total score showed that carcinogenicity, mutagenicity, and reproductive toxicity (CMR) chemicals ranked high with r = 0.558. This result demonstrated that the most dangerous toxicants should play a more decisive role in the top ranking than the others. We expect that our method can be efficiently used to screen regulated biocides by prioritizing their health hazards, thus leading to better policy decision making about biocide use.

Physical and chemical cleaning for the removal of indoor microorganisms, which can cause allergic reactions and respiratory diseases, is labor-intensive and time-consuming. An ultra-low volume (ULV) sprayer, a newly introduced device to inactivate pathogenic microorganisms, allows the disinfectant particles to reach hard-to-reach spaces indoors and is more cost-effective than the existing methods. However, few studies have been conducted to verify the efficiency of the ULV sprayer. Here, we verified the disinfection efficiency of the ULV sprayer for inactivating total bacteria present on indoor surfaces, considering the factors affecting bacteria inactivation, and presented the optimal ULV sprayer usage conditions to achieve the highest disinfection efficiency depending on room size. The total bacteria removal efficiency was high (range: 0.56–2.46 log₁₀ reductions), including hard-to-reach spaces. A response surface model was developed to identify the individual and interactive effects of the disinfectant concentration, spray amount, and room size on total bacteria disinfection efficiency. These three variables had interactive effects on the total bacteria disinfection efficiency. The experimental data were fitted to a second-order polynomial model, with high coefficients of determination (R²) for all models (R² > 0.82). The optimum conditions were a spray amount of 3.08–6.40 L in 160 m³, 3.78–7.22 L in 230 m³, and 5.68–8 L in 300 m³ surface area when using dilution rates of 100 times. These conditions predicted a bacterial disinfection efficiency of >1.10 log₁₀ reductions (92%) on all surfaces. Our results clearly indicate that the ULV sprayer effectively inactivates total bacteria present on indoor surfaces.