• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

评估复折射率和颗粒密度在低成本颗粒物传感器校准中的价值,用于粒径分辨颗粒物计数和 PM2.5 测量。

Assessing the value of complex refractive index and particle density for calibration of low-cost particle matter sensor for size-resolved particle count and PM2.5 measurements.

机构信息

Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, Washington, United States of America.

Department of Mechanical Engineering, College of Engineering, University of Washington, Seattle, Washington, United States of America.

出版信息

PLoS One. 2021 Nov 11;16(11):e0259745. doi: 10.1371/journal.pone.0259745. eCollection 2021.

DOI:10.1371/journal.pone.0259745
PMID:34762676
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8584671/
Abstract

Low-cost optical scattering particulate matter (PM) sensors report total or size-specific particle counts and mass concentrations. The PM concentration and size are estimated by the original equipment manufacturer (OEM) proprietary algorithms, which have inherent limitations since particle scattering depends on particles' properties such as size, shape, and complex index of refraction (CRI) as well as environmental parameters such as temperature and relative humidity (RH). As low-cost PM sensors are not able to resolve individual particles, there is a need to characterize and calibrate sensors' performance under a controlled environment. Here, we present improved calibration algorithms for Plantower PMS A003 sensor for mass indices and size-resolved number concentration. An aerosol chamber experimental protocol was used to evaluate sensor-to-sensor data reproducibility. The calibration was performed using four polydisperse test aerosols. The particle size distribution OEM calibration for PMS A003 sensor did not agree with the reference single particle sizer measurements. For the number concentration calibration, the linear model without adjusting for the aerosol properties and environmental conditions yields an absolute error (NMAE) of ~ 4.0% compared to the reference instrument. The calibration models adjusted for particle CRI and density account for non-linearity in the OEM's mass concentrations estimates with NMAE within 5.0%. The calibration algorithms developed in this study can be used in indoor air quality monitoring, occupational/industrial exposure assessments, or near-source monitoring scenarios where field calibration might be challenging.

摘要

低成本的光学散射颗粒物 (PM) 传感器报告总颗粒物或特定粒径颗粒物的数量和质量浓度。PM 浓度和粒径由原始设备制造商 (OEM) 的专有算法估算,由于颗粒物散射取决于颗粒物的特性,如大小、形状和复折射率 (CRI),以及环境参数,如温度和相对湿度 (RH),因此这些算法存在固有局限性。由于低成本 PM 传感器无法分辨单个颗粒物,因此需要在受控环境下对传感器性能进行表征和校准。在这里,我们提出了改进的 Plantower PMS A003 传感器质量指数和粒径分辨数浓度的校准算法。采用气溶胶室实验方案来评估传感器间数据的重现性。使用四种多分散测试气溶胶进行校准。PMS A003 传感器的颗粒尺寸分布 OEM 校准与参考单颗粒粒径仪测量结果不一致。对于数浓度校准,不考虑气溶胶特性和环境条件的线性模型与参考仪器相比产生约 4.0%的绝对误差 (NMAE)。针对 OEM 质量浓度估计中的非线性,校准模型中调整了颗粒物的 CRI 和密度,使得 NMAE 在 5.0%以内。本研究中开发的校准算法可用于室内空气质量监测、职业/工业暴露评估或现场校准可能具有挑战性的近源监测场景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d70/8584671/29d38b3dc7e6/pone.0259745.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d70/8584671/6850690f003c/pone.0259745.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d70/8584671/880d17fbba7c/pone.0259745.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d70/8584671/29821b8b32cb/pone.0259745.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d70/8584671/77b8388d5e27/pone.0259745.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d70/8584671/0aa10560f3d8/pone.0259745.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d70/8584671/29d38b3dc7e6/pone.0259745.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d70/8584671/6850690f003c/pone.0259745.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d70/8584671/880d17fbba7c/pone.0259745.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d70/8584671/29821b8b32cb/pone.0259745.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d70/8584671/77b8388d5e27/pone.0259745.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d70/8584671/0aa10560f3d8/pone.0259745.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d70/8584671/29d38b3dc7e6/pone.0259745.g006.jpg

相似文献

1
Assessing the value of complex refractive index and particle density for calibration of low-cost particle matter sensor for size-resolved particle count and PM2.5 measurements.评估复折射率和颗粒密度在低成本颗粒物传感器校准中的价值,用于粒径分辨颗粒物计数和 PM2.5 测量。
PLoS One. 2021 Nov 11;16(11):e0259745. doi: 10.1371/journal.pone.0259745. eCollection 2021.
2
Development of a calibration chamber to evaluate the performance of low-cost particulate matter sensors.开发一个校准腔室来评估低成本颗粒物传感器的性能。
Environ Pollut. 2019 Dec;255(Pt 1):113131. doi: 10.1016/j.envpol.2019.113131. Epub 2019 Aug 31.
3
Laboratory Evaluation of Low-Cost Optical Particle Counters for Environmental and Occupational Exposures.低成本光学粒子计数器在环境和职业暴露中的实验室评估。
Sensors (Basel). 2021 Jun 17;21(12):4146. doi: 10.3390/s21124146.
4
Field evaluation of nanofilm detectors for measuring acidic particles in indoor and outdoor air.用于测量室内和室外空气中酸性颗粒的纳米薄膜探测器的现场评估。
Res Rep Health Eff Inst. 2004 Sep(121):1-35; discussion 37-46.
5
Calibration of low-cost particulate matter sensors: Model development for a multi-city epidemiological study.低成本颗粒物传感器的校准:多城市流行病学研究的模型开发。
Environ Int. 2020 Jan;134:105329. doi: 10.1016/j.envint.2019.105329. Epub 2019 Nov 26.
6
Effects of aerosol particle size on the measurement of airborne PM with a low-cost particulate matter sensor (LCPMS) in a laboratory chamber.气溶胶粒径对低成本颗粒物传感器(LCPMS)在实验室室内空气中颗粒物测量的影响。
Environ Monit Assess. 2022 Jan 6;194(2):56. doi: 10.1007/s10661-021-09715-6.
7
Field and Laboratory Evaluations of the Low-Cost Plantower Particulate Matter Sensor.低成本 Plantower 颗粒物传感器的现场和实验室评估。
Environ Sci Technol. 2019 Jan 15;53(2):838-849. doi: 10.1021/acs.est.8b05174. Epub 2019 Jan 3.
8
Development and application of an aerosol screening model for size-resolved urban aerosols.用于粒径分辨的城市气溶胶的气溶胶筛选模型的开发与应用。
Res Rep Health Eff Inst. 2014 Jun(179):3-79.
9
Long-term field evaluation of the Plantower PMS low-cost particulate matter sensors.长期实地评估 Plantower PMS 低成本颗粒物传感器。
Environ Pollut. 2019 Feb;245:932-940. doi: 10.1016/j.envpol.2018.11.065. Epub 2018 Nov 24.
10
On-field test and data calibration of a low-cost sensor for fine particles exposure assessment.现场测试和数据校准一种用于细颗粒物暴露评估的低成本传感器。
Ecotoxicol Environ Saf. 2021 Mar 15;211:111958. doi: 10.1016/j.ecoenv.2021.111958. Epub 2021 Jan 25.

引用本文的文献

1
Using low-cost sensors and GPS to assess spatiotemporal variations in personal exposure to PM in the Washington State Twin Registry.利用低成本传感器和全球定位系统评估华盛顿州双胞胎登记处个人暴露于细颗粒物的时空变化。
medRxiv. 2025 Jun 9:2025.06.09.25329147. doi: 10.1101/2025.06.09.25329147.
2
Assessment of aerosol persistence in ICUs via low-cost sensor network and zonal models.通过低成本传感器网络和区域模型评估 ICU 中的气溶胶持久性。
Sci Rep. 2023 Mar 10;13(1):3992. doi: 10.1038/s41598-023-30778-7.

本文引用的文献

1
Methodology for Addressing Infectious Aerosol Persistence in Real-Time Using Sensor Network.利用传感器网络实时解决传染性气溶胶持久性的方法。
Sensors (Basel). 2021 Jun 7;21(11):3928. doi: 10.3390/s21113928.
2
Community Air Sensor Network (CAIRSENSE) project: evaluation of low-cost sensor performance in a suburban environment in the southeastern United States.社区空气传感器网络(CAIRSENSE)项目:美国东南部郊区环境中低成本传感器性能评估
Atmos Meas Tech. 2016 Nov 1;9(11):5281-5292. doi: 10.5194/amt-9-5281-2016.
3
Behavior of Ultrafine Particles in Electro-Hydrodynamic Flow Induced by Corona Discharge.
电晕放电诱导的电流体动力学流动中超细颗粒的行为
J Aerosol Sci. 2020 Oct;148. doi: 10.1016/j.jaerosci.2020.105587. Epub 2020 May 21.
4
Low-cost sensors as an alternative for long-term air quality monitoring.低成本传感器可作为长期空气质量监测的一种替代手段。
Environ Res. 2020 Jun;185:109438. doi: 10.1016/j.envres.2020.109438. Epub 2020 Mar 31.
5
Using Vehicles' Rendezvous for In Situ Calibration of Instruments in Fleet Vehicle-Based Air Pollution Mobile Monitoring.利用车辆交汇进行车队车辆空气污染移动监测中仪器的现场校准。
Environ Sci Technol. 2020 Apr 7;54(7):4286-4294. doi: 10.1021/acs.est.0c00612. Epub 2020 Mar 17.
6
Calibration of low-cost particulate matter sensors: Model development for a multi-city epidemiological study.低成本颗粒物传感器的校准:多城市流行病学研究的模型开发。
Environ Int. 2020 Jan;134:105329. doi: 10.1016/j.envint.2019.105329. Epub 2019 Nov 26.
7
Design and Evaluation of an Aerodynamic Focusing Micro-Well Aerosol Collector.空气动力学聚焦微孔气溶胶收集器的设计与评估
Aerosol Sci Technol. 2017;51(9):1016-1026. doi: 10.1080/02786826.2017.1329515. Epub 2017 May 24.
8
Long-term field evaluation of the Plantower PMS low-cost particulate matter sensors.长期实地评估 Plantower PMS 低成本颗粒物传感器。
Environ Pollut. 2019 Feb;245:932-940. doi: 10.1016/j.envpol.2018.11.065. Epub 2018 Nov 24.
9
Usability of a Personal Air Pollution Monitor: Design-Feedback Iterative Cycle Study.个人空气污染监测仪的可用性:设计反馈迭代循环研究
JMIR Mhealth Uhealth. 2018 Dec 21;6(12):e12023. doi: 10.2196/12023.
10
DESIGN AND OPTIMIZATION OF A COMPACT LOW-COST OPTICAL PARTICLE SIZER.紧凑型低成本光学粒子尺寸分析仪的设计与优化
J Aerosol Sci. 2018 May;119:1-12. doi: 10.1016/j.jaerosci.2018.01.003. Epub 2018 Jan 10.