Jamie Leonard , Hatice Ceylan Koydemir , Vera S. Koutnik , Derek Tseng , Aydogan Ozcan , Sanjay K Mohanty
{"title":"智能手机支持的微塑料快速定量","authors":"Jamie Leonard , Hatice Ceylan Koydemir , Vera S. Koutnik , Derek Tseng , Aydogan Ozcan , Sanjay K Mohanty","doi":"10.1016/j.hazl.2022.100052","DOIUrl":null,"url":null,"abstract":"<div><p>Developing methods to quickly detect microplastics is critical to assessing the extent of microplastic contamination in the environment. However, current methods to quantify microplastics from environmental samples can take several hours to days and often require access to expensive specialized microscopy instruments. Herein we report a smartphone-based method to rapidly quantify microplastics. The method involves isolating microplastics from soil or water by density separation and vacuum filtration, staining the isolated plastic polymers with Nile Red, and quantifying the strained microplastics as small as 10 µm using a smartphone-based fluorescence microscope with an opti-mechanical attachment. The smartphone-enabled quantification using an algorithm eliminates time-consuming digestion steps and manual counting, thereby enabling quantification of microplastic concentration in environmental samples within 1 h. The method successfully detected a wide range of plastic polymers, but a dilution step was often needed if the samples contained high concentrations of particulates or non-plastic debris to minimize optical overlap or blocking. This method could serve as an initial assessment tool to rapidly quantify microplastics in environments in remote places with limited access to expensive resources and open the possibility to increase the frequency of monitoring microplastic concentration in engineered systems such as wastewater treatment plants.</p></div>","PeriodicalId":93463,"journal":{"name":"Journal of hazardous materials letters","volume":null,"pages":null},"PeriodicalIF":6.6000,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666911022000053/pdfft?md5=93fdb20c2459e2530808de497c75bb47&pid=1-s2.0-S2666911022000053-main.pdf","citationCount":"10","resultStr":"{\"title\":\"Smartphone-enabled rapid quantification of microplastics\",\"authors\":\"Jamie Leonard , Hatice Ceylan Koydemir , Vera S. Koutnik , Derek Tseng , Aydogan Ozcan , Sanjay K Mohanty\",\"doi\":\"10.1016/j.hazl.2022.100052\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Developing methods to quickly detect microplastics is critical to assessing the extent of microplastic contamination in the environment. However, current methods to quantify microplastics from environmental samples can take several hours to days and often require access to expensive specialized microscopy instruments. Herein we report a smartphone-based method to rapidly quantify microplastics. The method involves isolating microplastics from soil or water by density separation and vacuum filtration, staining the isolated plastic polymers with Nile Red, and quantifying the strained microplastics as small as 10 µm using a smartphone-based fluorescence microscope with an opti-mechanical attachment. The smartphone-enabled quantification using an algorithm eliminates time-consuming digestion steps and manual counting, thereby enabling quantification of microplastic concentration in environmental samples within 1 h. The method successfully detected a wide range of plastic polymers, but a dilution step was often needed if the samples contained high concentrations of particulates or non-plastic debris to minimize optical overlap or blocking. This method could serve as an initial assessment tool to rapidly quantify microplastics in environments in remote places with limited access to expensive resources and open the possibility to increase the frequency of monitoring microplastic concentration in engineered systems such as wastewater treatment plants.</p></div>\",\"PeriodicalId\":93463,\"journal\":{\"name\":\"Journal of hazardous materials letters\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":6.6000,\"publicationDate\":\"2022-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2666911022000053/pdfft?md5=93fdb20c2459e2530808de497c75bb47&pid=1-s2.0-S2666911022000053-main.pdf\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of hazardous materials letters\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666911022000053\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ENVIRONMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of hazardous materials letters","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666911022000053","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ENVIRONMENTAL","Score":null,"Total":0}
Smartphone-enabled rapid quantification of microplastics
Developing methods to quickly detect microplastics is critical to assessing the extent of microplastic contamination in the environment. However, current methods to quantify microplastics from environmental samples can take several hours to days and often require access to expensive specialized microscopy instruments. Herein we report a smartphone-based method to rapidly quantify microplastics. The method involves isolating microplastics from soil or water by density separation and vacuum filtration, staining the isolated plastic polymers with Nile Red, and quantifying the strained microplastics as small as 10 µm using a smartphone-based fluorescence microscope with an opti-mechanical attachment. The smartphone-enabled quantification using an algorithm eliminates time-consuming digestion steps and manual counting, thereby enabling quantification of microplastic concentration in environmental samples within 1 h. The method successfully detected a wide range of plastic polymers, but a dilution step was often needed if the samples contained high concentrations of particulates or non-plastic debris to minimize optical overlap or blocking. This method could serve as an initial assessment tool to rapidly quantify microplastics in environments in remote places with limited access to expensive resources and open the possibility to increase the frequency of monitoring microplastic concentration in engineered systems such as wastewater treatment plants.