Background: The semiconductor industry is known to use a number of chemicals, but little is known about the exact chemicals used due to the ingredients being kept as a trade secret. Objectives: The objective of this study was to analyze chemical use using a safety data sheet (SDS) and chemical inventory provided by a major semiconductor company, which operated two factories (A and B). Methods: Descriptive statistics were obtained on the number of chemical products and ingredients, photoresists, and carcinogens, classified by the International Agency for Research on Cancer (IARC), as well as trade secret ingredients. The total chemical use per year was estimated from chemical inventories mass (kg). Results: A total of 428 and 432 chemical products were used in factories A and B, respectively. The number of pure chemical ingredients, after removing both trade secret ingredients and multiple counting, was 189 and 157 in factories A and B, respectively. The number of products containing carcinogens, such as sulfuric acid, catechol, and naphthalene was 47/428 (A) and 28/432 (B). Chemicals used in photolithography were 21% (A) and 26% (B) of all chemical products, and more than 97% among them were chemicals containing trade secret ingredients. Conclusions: Each year, 4.3 and 8.3 tons of chemicals were used per person in factories A and B, respectively. Because of the high level of commercial secrecy and the use of many unregulated chemicals, more sustainable policies and methods should be implemented to address health and safety issues in the semiconductor industry.

The goal of this study is to develop a general population job-exposure matrix (GPJEM) on asbestos to estimate occupational asbestos exposure levels in the Republic of Korea. Three Korean domestic quantitative exposure datasets collected from 1984 to 2008 were used to build the GPJEM. Exposure groups in collected data were reclassified based on the current Korean Standard Industrial Classification (9th edition) and the Korean Standard Classification of Occupations code (6th edition) that is in accordance to international standards. All of the exposure levels were expressed by weighted arithmetic mean (WAM) and minimum and maximum concentrations. Based on the established GPJEM, the 112 exposure groups could be reclassified into 86 industries and 74 occupations. In the 1980s, the highest exposure levels were estimated in "knitting and weaving machine operators" with a WAM concentration of 7.48 fibers/mL (f/mL); in the 1990s, "plastic products production machine operators" with 5.12 f/mL, and in the 2000s "detergents production machine operators" handling talc containing asbestos with 2.45 f/mL. Of the 112 exposure groups, 44 groups had higher WAM concentrations than the Korean occupational exposure limit of 0.1 f/mL. The newly constructed GPJEM which is generated from actual domestic quantitative exposure data could be useful in evaluating historical exposure levels to asbestos and could contribute to improved prediction of asbestos-related diseases among Koreans.

This study aimed to assess the characteristics of exposure to both PM_2.5 and black carbon (BC) among subway workers. A total of 61 subway workers, including 26, 23, and 12 subway station managers, maintenance engineers, and train drivers, respectively, were investigated in 2018. Real-time measurements of airborne PM_2.5 and BC were simultaneously conducted around the breathing zones of workers. Maintenance engineers had the highest average levels of exposure to both PM_2.5 and BC (PM_2.5, 76 µg/m³; BC, 9.3 µg/m³), followed by train drivers (63.2 µg/m³, 5.9 µg/m³) and subway station managers (39.7 µg/m³, 2.2 µg/m³). In terms of the relationship between mass concentrations of PM_2.5 and BC, train drivers demonstrated the strongest correlation (R = 0.72), indicating that the proportion of BC contained in PM_2.5 is relatively steady. The average proportion of BC in PM_2.5 among maintenance engineers (13.0%) was higher than that among train drivers (9.4%) and subway station managers (6.4%). Univariate and mixed effect multiple analyses demonstrated the type of task and worksite to be significant factors affecting exposure levels in maintenance engineers and subway station managers. The use of diesel engine motorcars in tunnel maintenance was found to be a key contributor to PM_2.5 and BC exposure levels among subway workers.

The goal of this study was to evaluate the hazardous chemical exposure control system in a semiconductor manufacturing company and recommend an appropriate exposure surveillance system for hazardous agents. We reviewed compliance-based chemical exposure data compiled between 2012 and 2014 by the study company. The chemical management system, characteristics of chemical use and hazardous gas monitoring system were also investigated. We evaluated the airborne isopropyl alcohol (IPA) and acetone generally used as cleaning solvents, volatile organic compounds and metals levels using internationally recommended sampling and analytical methods. Based on the results of past working environment measurement data and of our investigation, the overall current exposure to chemicals by semiconductor workers during routine production work appears to be controlled below occupational exposure limits. About 40% of chemical products used were found to contain at least one unidentifiable trade-secret substance. There are several situations and maintenance tasks that need special attention to reduce exposure to carcinogens as much as possible. In addition, a job-exposure matrix as a tool of surveillance system that can examine the exposure and health status of semiconductor workers according to type of operation and type of job or task is recommended.

A job-exposure matrix (JEM) is an important surrogate indicator to evaluate past exposure levels. Although a Korean asbestos JEM has been constructed previously, this JEM includes only a few industrial and occupational groups. This study aimed to reconstruct the JEM by integrating the latest organized data to improve its utility. We used recent Korean standard industry and occupation codes and extracted 36 articles from a systematic literature review to initiate the reconstruction of the previous Korean asbestos JEM. The resulting data consisted of 141 combinations of industrial and occupational groups. Data from the Netherlands's JEM were also reviewed and categorized into 70 industrial and 117 occupational groups by matching with the Korean data. We also utilized Germany's data, which consisted of 10 industrial and 14 occupational groups. The reconstructed Korean asbestos JEM had 141 combinations of industries and occupations. The time periods are from the 1980s to the 2000s in 10-year intervals. Most of the data were distributed between the 1990s and the 2000s. Occupations with high exposure to asbestos included knitting and weaving machine operators, automobile mechanics or assemblers, ship mechanics or assemblers, mineral ore and stone products processing mechanics, and metal casting machine operators or mold makers. The reconstructed Korean asbestos JEM has expanded the type and duration of the occupational groups of the previous JEM and can serve as an important reference tool for evaluating asbestos exposure and designing compensation and prevention policies in Korea.

In a previous study, we estimated exposure prevalence and the number of workers exposed to carcinogens by industry in Korea. The present study aimed to evaluate the optimal exposure intensity indicators of airborne lead exposure by comparing to blood lead measurements for the future development of the carcinogen exposure intensity database. Data concerning airborne lead measurements and blood lead levels were collected from nationwide occupational exposure databases, compiled between 2015 and 2016. Summary statistics, including the arithmetic mean (AM), geometric mean (GM), and 95th percentile level (X95) were calculated by industry both for airborne lead and blood lead measurements. Since many measurements were below the limits of detection (LODs), the simple replacement with half of the LOD and maximum likelihood estimation (MLE) methods were used for statistical analysis. For examining the optimal exposure indicator of airborne lead exposure, blood lead levels were used as reference data for subsequent rank correlation analyses. A total of 19,637 airborne lead measurements and 32,848 blood lead measurements were used. In general, simple replacement showed a higher correlation than MLE. The results showed that AM and X95 using simple replacement could be used as optimal exposure intensity indicators, while X95 showed better correlations than AM in industries with 20 or more measurements. Our results showed that AM or X95 could be potential candidates for exposure intensity indicators in the Korean carcinogen exposure database. Especially, X95 is an optimal indicator where there are enough measurements to compute X95 values.