亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Introducing Eyewear Lenses as Passive Samplers for Assessing Inhalation Exposure to Airborne Chemicals

眼镜 吸入染毒 镜头(地质) 聚二甲基硅氧烷 环境科学 暴露评估 聚碳酸酯 人口 吸入 职业暴露 环境化学 污染
作者
Anping Guo,Erica Sharma,Samiyan Qureshi,Norah H. B. Beach-Diplock,Parshawn Amini,Joseph O. Okeme
出处
期刊:Environmental Science & Technology [American Chemical Society]
卷期号:59 (49): 26384-26395
标识
DOI:10.1021/acs.est.5c12605
摘要

Wearable passive samplers are inexpensive tools for assessing personal exposure to diverse contaminants through a combination of exposure pathways. This versatility, however, can be a disadvantage when it is critical to assess a specific pathway. Here, we aim to develop eyewear lenses as passive samplers that can capture inhalation exposure as a primary pathway for airborne contaminants. We designed polycarbonate lens samplers with and without a polydimethylsiloxane (PDMS) coating and compared their surface properties and chemical uptake. We compared the chemical profiles they sampled from indoor lab and office environments using solvent-soaked wipes to extract the chemicals by wiping the lens surfaces and analyzing the wipe extracts using non-targeted screening on LC-QTOF-MS. Compared to the comparably transparent uncoated lenses, the PDMS-coated lenses were up to six times rougher in morphology. This difference, unexpectedly, did not yield significant differences in the chemical profiles measured between the PDMS-coated and uncoated polycarbonate lenses. Combined, both lens types sampled over 900 features, with diverse physico-chemical properties, annotated at varying levels of confidence. Level 2 features include phthalates and organophosphate esters commonly used as plasticizers. These promising results form the foundation for further developing the lenses as passive sampling eyewear for easily assessing inhalation exposure at the population level.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
愤怒的若颜完成签到,获得积分10
4秒前
守望发布了新的文献求助10
4秒前
bkagyin应助守望采纳,获得10
10秒前
25秒前
难过洙完成签到,获得积分10
28秒前
欧阳万仇发布了新的文献求助10
31秒前
35秒前
桐桐应助欧阳万仇采纳,获得10
39秒前
Index发布了新的文献求助10
39秒前
111完成签到 ,获得积分10
46秒前
林子鸿完成签到 ,获得积分10
53秒前
漠尘完成签到,获得积分10
55秒前
1分钟前
1分钟前
学术混子发布了新的文献求助10
1分钟前
1分钟前
失眠的白云完成签到,获得积分10
1分钟前
1分钟前
1分钟前
米米发布了新的文献求助10
1分钟前
Akim应助科研通管家采纳,获得30
1分钟前
乐乐应助科研通管家采纳,获得10
1分钟前
1分钟前
慕青应助学术混子采纳,获得10
1分钟前
SciGPT应助米米采纳,获得30
2分钟前
2分钟前
2分钟前
学术混子发布了新的文献求助10
2分钟前
阔达的泽洋完成签到,获得积分10
2分钟前
万能图书馆应助伍声痕采纳,获得10
2分钟前
skicular完成签到 ,获得积分10
2分钟前
高贵飞丹完成签到,获得积分10
3分钟前
chenshertrai发布了新的文献求助10
3分钟前
3分钟前
CodeCraft应助学术混子采纳,获得10
3分钟前
伍声痕发布了新的文献求助10
3分钟前
伍声痕完成签到,获得积分10
3分钟前
3分钟前
3分钟前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Art Therapy and Career Counseling 600
The Oxford Handbook of Digital Classical Studies 550
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7619187
求助须知:如何正确求助?哪些是违规求助? 9194669
关于积分的说明 19706160
捐赠科研通 7191201
什么是DOI,文献DOI怎么找? 3272388
关于科研通互助平台的介绍 2435020
邀请新用户注册赠送积分活动 2267604