金屬表面清洗製程作業勞工職業暴露及健康風險管理;Chemical exposure and associated health risk management resulting from metal surface cleaning processes

NCUIR > Engineering College > Executive Master of Environmental Engineering > Electronic Thesis & Dissertation > Item 987654321/81828

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/81828

Title:	金屬表面清洗製程作業勞工職業暴露及健康風險管理;Chemical exposure and associated health risk management resulting from metal surface cleaning processes
Authors:	翁靜賢;Weng, Ching-Hsien
Contributors:	環境工程研究所在職專班
Keywords:	金屬表面處理業;作業環境監測;暴露評估與分級管理;半定量推估方法;定量推估模式;定量監測方法;健康風險管理;Metal surface processing;environmental monitoring;exposure assessment and graded management;semi quantitative assessment;quantitative estimation;quantitative analysis;health risk management
Date:	2019-08-21
Issue Date:	2019-09-03 17:05:22 (UTC+8)
Publisher:	國立中央大學
Abstract:	在金屬表面處理清洗的製程中，化學品會經由空氣逸散到作業環境中，或藉由皮膚吸收進入人體，使作業勞工暴露接觸到有害物可能導致健康危害。本研究廠址就現有的作業環境測定計劃，已對廠內危害物質依法令規定實施作業環境監測，委外環測公司所測得之有害物濃度值皆符合法定容許暴露標準，但檢測結果皆未應用於現場勞工作業改善之依據，而歷年作業環境監測數據亦未實施管理及統計，無法反應作業實際狀況。本研究選擇化學表面清洗作業環境製程區域(半導體清洗區、光電清洗區、剝金王水室、化學表面處理區)常用五種化學品(硝酸、鹽酸、丙酮、氫氟酸、氫氧化鉀)之作業環境監測數據，利用三種以上之作業環境測定數據統計評估工具(半定量-CCB、定量推估、統計分析)得出預測結果，並結合環境測定實際值，評估化學課勞工職業暴露與健康風險評估，掌握長期實際暴露型態並實施化學品風險分級管理，依健康風險推估結果，提出職場相對應之健康風險管理策略。化學品暴露評估方法及對策包含：初步危害分析、相加效應評估、健康風險評估、健檢數據異常分析與化學品分級管理。綜合以上結果發現，利用模式推估進行分級之化學品，以半定量模式所得出之風險等級為第三級或第四級，表示目前使用這些有容許濃度規範之化學品，皆屬於中高風險，應實施工程控制或就其作業程序及方法實施檢點，採取必要改善措施（如設備操作、維護、監督、自主檢查等），半定量評估結果，亦可作為評估下一次作業環境監測點參考。利用定量無通風推估評估之風險結果皆處於第三級，列入例行性持續評估即可。使用統計分析對有容許濃度規範之化學品進行評估，在半導體清洗區硝酸的風險等級為第三級，屬於中高風險建議優先管理之，應每三個月委外實施定量環境監測，其他風險等級為第二級者：建議提供作業勞工個人防護具，並依其結果進行自主健康風險管理，提出風險減緩控制措施建議並持續監控。以相加效應評估研究廠址的化學品危害，其化學品危害相加效應都小於1，符合作業環境測定容許限值。將化學課勞工健康檢查異常項目進行分析與統計，血液常規檢查中的白血球與紅血球無明顯異常現象，推論化學課作業人員無受到化學性危害明顯暴露影響。但從健康檢查其它數據，發現作業人員在一般檢查項目肝功能、血脂肪列為健康管理第2~3級，後續對其作業勞工健康風險管理措施，藉由推展勞工健康照護服務，強化勞工健康風險評估及健康管理相關作為，推動職場健康管理活動(如適性選配工、健檢異常個案管理等)，避免職業病危害，達到職業安全保護目的。 ;During the process of the metal surface cleaning, chemicals can be emitted to the air of the workplace and may be absorbed by the body through the skin. Exposure to harmful chemicals is known to cause hazards to the health of the workers. The studied site of this thesis has implemented a program of environmental monitoring of existing on-site hazardous materials, in which the contracting environmental analytical lab has run tests on the concentrations of regulated hazardous substances and the results by far have met the permissible standards. However, these results have not served as a reference for operation improvement, nor has been the environmental monitoring data properly managed over the past years. It does not reflect the actual situation. Hence, in this study we looked into the environmental monitoring data of five often-used chemicals, including nitric acid, hydrochloric acid, acetone, hydrofluoric acid and potassium hydroxide, in different chemical surface cleaning areas, such as Semiconductor Cleaning Area, Photoelectric Cleaning Area, Dissolving Gold with Chlorazoic Acid Area, and Metal Finishing Area. More than three measurements and evaluation methods, such as ILO-CCB, Quantitative Estimation, and Statistical Analysis were used to predict the result. We combined the actual environmental assessment value to evaluate the occupational exposure hazard and health risk on employees who handle chemicals in works (Chemical Department). In order to implement chemical risk grading management and to handle exposure patterns chronically, a health risk management strategy was proposed according to the health risks assessment results. As for the chemical exposure analysis and strategy methods, they include primary hazard analysis, additive effect assessment, health risk analysis, abnormal health checkup, and chemical grading management. According to the results using the modified analogy method to classify the chemicals as well as the semi-quantitative method to assess the risk level, it was found that the risk grades were at level 3 or 4. The results indicated that although the currently used chemical concentrations meet the statutory permissible, they are still classified as moderate to high-risk chemicals. It is necessary to take improvement measures, for example, implement engineering control or enhance inspection points for operating procedures and methods. Other improvements can be equipment operation, maintenance, supervision, self-inspection, and so on. The semi-quantitative assessment results can also be used as a reference for the next operational environmental monitoring. The risk results of the quantitative non-ventilation estimation were at level 2, indicating that this can just be the routine checkup. Statistical analysis was used to evaluate chemicals with permissible concentration. In the semiconductor cleaning area, the risk level of nitric acid was at level 3, a moderate to high risk. It is recommended to be managed firstly and should be monitored and measured every three months. As for other chemicals with level 3 risks, it is recommended to provide personal protective equipment for operators, conduct self-health risk management, propose risk reduction control measures and continue the monitoring. The chemical hazard rate of this site was assessed by the additive effect, and the result showed the risk level is less than 1, which is within the environmental monitoring acceptable limit. When examining the blood checkup results of Chemical Department employees, there was no visible abnormality in their white blood cells and red blood cells. It was inferred that the chemical department employees were not affected directly from the chemical exposure workplace. However, from the other health checkup data, it was found that employees’ liver function and cholesterol were classified as level 2 and 3 in health management. To fully achieve the purpose of occupational safety protection and to avoid the occupational hazard, there are several measures to take. For example, promote employees’ health care service, strength the awareness of employees’ health risk assessment and health management, promote workplace health management activities, such as adaptive operator selection, follow-up on employees’ abnormal health checkup cases, and so on.
Appears in Collections:	[Executive Master of Environmental Engineering] Electronic Thesis & Dissertation

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