A Low-Cost Liquid-Based Capacitive Sensor for PM2.5 Monitoring

被引:0
|
作者
Ashoori, Ehsan [1 ]
Parsnejad, Sina [1 ]
Yin, Heyu [1 ]
Figueroa, J. [1 ]
Sepulveda, N. [1 ]
Mason, Andrew J. [1 ]
机构
[1] Michigan State Univ, Elect & Comp Engn Dept, E Lansing, MI 48824 USA
关键词
Particulate matter; PM2.5; capacitive detection; lock-in amplifier;
D O I
10.1109/MWSCAS47672.2021.9531893
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
PM2.5 is one of the main sources of air pollution and could negatively affect the human health. The available commercial PM monitoring devices are often bulky and expensive and thus not useful for personal use. Toward the implementation of personal/wearable PM monitoring devices, this paper presents a low-cost, liquid-based capacitive monitoring device that uses in-house fabricated electrodes and a custom PCB with off-the-shelf components. The fabricated device is designed to detect concentration of particles in a liquid environment which enables integration of the capacitive detection with future electrochemical-based analysis of PM elemental composition. In this liquid-based detection scheme, a minimum detection level of 4.6 x 10(6) particles/mu L is achieved which corresponds to the particles sampled from an unhealthy level of PM2.5 in the air. The detection response shows a linearity of R-2 =0.9934 during the experiments.
引用
收藏
页码:907 / 910
页数:4
相关论文
共 50 条
  • [1] Evaluation of Low-Cost Sensors for Ambient PM2.5 Monitoring
    Badura, Marek
    Batog, Piotr
    Drzeniecka-Osiadacz, Anetta
    Modzel, Piotr
    JOURNAL OF SENSORS, 2018, 2018
  • [2] Statistical field calibration of a low-cost PM2.5 monitoring network in Baltimore
    Datta, Abhirup
    Saha, Arkajyoti
    Zamora, Misti Levy
    Buehler, Colby
    Hao, Lei
    Xiong, Fulizi
    Gentner, Drew R.
    Koehler, Kirsten
    ATMOSPHERIC ENVIRONMENT, 2020, 242
  • [3] Assessing low-cost sensor for characterizing temporal variation of PM2.5 in Bandung, Indonesia
    Kurniawati, Syukria
    Santoso, Muhayatun
    Nurhaini, Feni Fernita
    Atmodjo, Djoko Prakoso D.
    Lestiani, Diah Dwiana
    Ramadhani, Moch Faizal
    Kusmartini, Indah
    Syahfitri, Woro Yatu N.
    Damastuti, Endah
    Tursinah, Rasito
    KUWAIT JOURNAL OF SCIENCE, 2025, 52 (01)
  • [4] Analysis of spatiotemporal PM2.5 concentration patterns in Changwon, Korea, using low-cost PM2.5 sensors
    Song, Bonggeun
    Park, Kyunghun
    Kim, Taehyeung
    Seo, Gyeongho
    URBAN CLIMATE, 2022, 46
  • [5] Improving data reliability: A quality control practice for low-cost PM2.5 sensor network
    Qiao, Xiaohui
    Zhang, Qiang
    Wang, Dongbin
    Hao, Jiming
    Jiang, Jingkun
    SCIENCE OF THE TOTAL ENVIRONMENT, 2021, 779
  • [6] PM2.5 in Sri Lanka: Trend Analysis, Low-cost Sensor Correlations and Spatial Distribution
    Dhammapala, Ranil
    Basnayake, Ashani
    Premasiri, Sarath
    Chathuranga, Lakmal
    Mera, Karen
    AEROSOL AND AIR QUALITY RESEARCH, 2022, 22 (05)
  • [7] Evaluation of nine machine learning regression algorithms for calibration of low-cost PM2.5 sensor
    Kumar, Vikas
    Sahu, Manoranjan
    JOURNAL OF AEROSOL SCIENCE, 2021, 157
  • [8] Investigation on daily exposure to PM2.5 in Bandung city, Indonesia using low-cost sensor
    Delvina Sinaga
    Wiwiek Setyawati
    Fang Yi Cheng
    Shih-Chun Candice Lung
    Journal of Exposure Science & Environmental Epidemiology, 2020, 30 : 1001 - 1012
  • [9] Characterizing outdoor infiltration and indoor contribution of PM2.5 with citizen-based low-cost monitoring data
    Bi, Jianzhao
    Wallace, Lance A.
    Sarnat, Jeremy A.
    Liu, Yang
    ENVIRONMENTAL POLLUTION, 2021, 276
  • [10] Performance evaluation of twelve low-cost PM2.5 sensors at an ambient air monitoring site
    Feenstra, Brandon
    Papapostolou, Vasileios
    Hasheminassab, Sina
    Zhang, Hang
    Boghossian, Berj Der
    Cocker, David
    Polidori, Andrea
    ATMOSPHERIC ENVIRONMENT, 2019, 216