Lubinda Nabiwa*, Joseph Simfukwe, Patrick Hayumbu, Daniel Masilu Masekameni, Nandi Mumba, Mwaba Sifanu and Stephanus J. L. Linde,
{"title":"用个人光学粒子计数器定量测定地下铜矿呼吸性粉尘浓度","authors":"Lubinda Nabiwa*, Joseph Simfukwe, Patrick Hayumbu, Daniel Masilu Masekameni, Nandi Mumba, Mwaba Sifanu and Stephanus J. L. Linde, ","doi":"10.1021/acs.chas.5c0003710.1021/acs.chas.5c00037","DOIUrl":null,"url":null,"abstract":"<p >Exposure assessments are conducted using standardized gravimetric sampling (SGS) methodologies. However, the gravimetric analysis of respirable dust (RD) provides only one data point. Based on this background, this study aims to quantify RD concentration and peak RD exposure detected as time-series data using a personal optical particle counter (OPC) for possible applications of exposure monitoring in near-real time. Thirty pairs of side-by-side RD exposure samples were collected (22 personal and 8 static) using the Nanozen DustCount 9000Z1 OPC and SGS (NIOSH 0600). The SGS samples were sent for gravimetric analysis in an ISO 17025:2005-accredited analytical laboratory. A correction equation for the OPC sensor was established using linear regression and was used to correct the RD concentrations that were quantified by the OPC. The RD concentrations quantified by the OPC sensor were strongly correlated with those of the SGS method (<i>r</i> = 0.93), and the Bland-Altman analysis showed a consistent pattern and that, on average, the SGS method measured 0.27 mg/m<sup>3</sup> higher than the OPC sensor. The time-weighted average RD<sub>opc</sub> concentrations were less than 1.5 mg/m<sup>3</sup> for the mine sections sampled; the highest peak RD<sub>opc</sub> concentration was 11.51 mg/m<sup>3</sup>. The results from the side-by-side sampling showed a consistently positive bias, and the Pearson correlation was strong. Thus, the results from Nanozen DustCount 9000Z1 could be corrected using the SGS results and linear regression. The corrected RD concentration can be used to assess the efficacy of the engineering controls in-time. The exposure data from the OPC complement the SGS results by providing additional exposure data such as peak exposure and particle size distribution. From the corrected RD exposure data, the RCS was estimated. Based on the results of this estimate, there is potential for overexposure to RCS at this mine; thus, miners are likely to develop silicosis.</p>","PeriodicalId":73648,"journal":{"name":"Journal of chemical health & safety","volume":"32 3","pages":"326–335 326–335"},"PeriodicalIF":0.0000,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Quantification of Respirable Dust Concentration at an Underground Copper Mine Using a Personal Optical Particle Counter\",\"authors\":\"Lubinda Nabiwa*, Joseph Simfukwe, Patrick Hayumbu, Daniel Masilu Masekameni, Nandi Mumba, Mwaba Sifanu and Stephanus J. L. Linde, \",\"doi\":\"10.1021/acs.chas.5c0003710.1021/acs.chas.5c00037\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >Exposure assessments are conducted using standardized gravimetric sampling (SGS) methodologies. However, the gravimetric analysis of respirable dust (RD) provides only one data point. Based on this background, this study aims to quantify RD concentration and peak RD exposure detected as time-series data using a personal optical particle counter (OPC) for possible applications of exposure monitoring in near-real time. Thirty pairs of side-by-side RD exposure samples were collected (22 personal and 8 static) using the Nanozen DustCount 9000Z1 OPC and SGS (NIOSH 0600). The SGS samples were sent for gravimetric analysis in an ISO 17025:2005-accredited analytical laboratory. A correction equation for the OPC sensor was established using linear regression and was used to correct the RD concentrations that were quantified by the OPC. The RD concentrations quantified by the OPC sensor were strongly correlated with those of the SGS method (<i>r</i> = 0.93), and the Bland-Altman analysis showed a consistent pattern and that, on average, the SGS method measured 0.27 mg/m<sup>3</sup> higher than the OPC sensor. The time-weighted average RD<sub>opc</sub> concentrations were less than 1.5 mg/m<sup>3</sup> for the mine sections sampled; the highest peak RD<sub>opc</sub> concentration was 11.51 mg/m<sup>3</sup>. The results from the side-by-side sampling showed a consistently positive bias, and the Pearson correlation was strong. Thus, the results from Nanozen DustCount 9000Z1 could be corrected using the SGS results and linear regression. The corrected RD concentration can be used to assess the efficacy of the engineering controls in-time. The exposure data from the OPC complement the SGS results by providing additional exposure data such as peak exposure and particle size distribution. From the corrected RD exposure data, the RCS was estimated. Based on the results of this estimate, there is potential for overexposure to RCS at this mine; thus, miners are likely to develop silicosis.</p>\",\"PeriodicalId\":73648,\"journal\":{\"name\":\"Journal of chemical health & safety\",\"volume\":\"32 3\",\"pages\":\"326–335 326–335\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-05-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of chemical health & safety\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://pubs.acs.org/doi/10.1021/acs.chas.5c00037\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of chemical health & safety","FirstCategoryId":"1085","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acs.chas.5c00037","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Quantification of Respirable Dust Concentration at an Underground Copper Mine Using a Personal Optical Particle Counter
Exposure assessments are conducted using standardized gravimetric sampling (SGS) methodologies. However, the gravimetric analysis of respirable dust (RD) provides only one data point. Based on this background, this study aims to quantify RD concentration and peak RD exposure detected as time-series data using a personal optical particle counter (OPC) for possible applications of exposure monitoring in near-real time. Thirty pairs of side-by-side RD exposure samples were collected (22 personal and 8 static) using the Nanozen DustCount 9000Z1 OPC and SGS (NIOSH 0600). The SGS samples were sent for gravimetric analysis in an ISO 17025:2005-accredited analytical laboratory. A correction equation for the OPC sensor was established using linear regression and was used to correct the RD concentrations that were quantified by the OPC. The RD concentrations quantified by the OPC sensor were strongly correlated with those of the SGS method (r = 0.93), and the Bland-Altman analysis showed a consistent pattern and that, on average, the SGS method measured 0.27 mg/m3 higher than the OPC sensor. The time-weighted average RDopc concentrations were less than 1.5 mg/m3 for the mine sections sampled; the highest peak RDopc concentration was 11.51 mg/m3. The results from the side-by-side sampling showed a consistently positive bias, and the Pearson correlation was strong. Thus, the results from Nanozen DustCount 9000Z1 could be corrected using the SGS results and linear regression. The corrected RD concentration can be used to assess the efficacy of the engineering controls in-time. The exposure data from the OPC complement the SGS results by providing additional exposure data such as peak exposure and particle size distribution. From the corrected RD exposure data, the RCS was estimated. Based on the results of this estimate, there is potential for overexposure to RCS at this mine; thus, miners are likely to develop silicosis.