Quantitative filter forensics for indoor particle sampling

被引:23
|
作者
Haaland, D. [1 ]
Siegel, J. A. [1 ,2 ]
机构
[1] Univ Toronto, Dept Civil Engn, Toronto, ON, Canada
[2] Univ Toronto, Dalla Lana Sch Publ Hlth, Toronto, ON, Canada
关键词
dust; filtration; HVAC; indoor concentration; literature review; particle composition; POLYBROMINATED DIPHENYL ETHERS; CHROMATOGRAPHY MASS-SPECTROMETRY; AIR-CONDITIONING FILTERS; LARGE PUBLIC BUILDINGS; HVAC FILTERS; FUNGAL COLONIZATION; OPERATIONAL CHARACTERISTICS; ASTHMATIC-CHILDREN; ORGANIC-COMPOUNDS; RETAIL STORES;
D O I
10.1111/ina.12319
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Filter forensics is a promising indoor air investigation technique involving the analysis of dust which has collected on filters in central forced-air heating, ventilation, and air conditioning (HVAC) or portable systems to determine the presence of indoor particle-bound contaminants. In this study, we summarize past filter forensics research to explore what it reveals about the sampling technique and the indoor environment. There are 60 investigations in the literature that have used this sampling technique for a variety of biotic and abiotic contaminants. Many studies identified differences between contaminant concentrations in different buildings using this technique. Based on this literature review, we identified a lack of quantification as a gap in the past literature. Accordingly, we propose an approach to quantitatively link contaminants extracted from HVAC filter dust to time-averaged integrated air concentrations. This quantitative filter forensics approach has great potential to measure indoor air concentrations of a wide variety of particle-bound contaminants. Future studies directly comparing quantitative filter forensics to alternative sampling techniques are required to fully assess this approach, but analysis of past research suggests the enormous possibility of this approach.
引用
收藏
页码:364 / 376
页数:13
相关论文
共 50 条
  • [31] Localization for Indoor Applications with a Cheap Sonar by Particle Filter Estimation
    Malagon-Soldara, Salvador M.
    Avalos-Rivera, Estefania D.
    Rivas-Araiza, Edgar A.
    2016 8TH EURO AMERICAN CONFERENCE ON TELEMATICS AND INFORMATION SYSTEMS (EATIS), 2016,
  • [32] A Particle Filter for Smartphone-Based Indoor Pedestrian Navigation
    Masiero, Andrea
    Guarnieri, Alberto
    Pirotti, Francesco
    Vettore, Antonio
    MICROMACHINES, 2014, 5 (04) : 1012 - 1033
  • [33] Indoor Parking Localization Based on Dual Weighted Particle Filter
    Kim, Yunsik
    Chung, Woojin
    Hong, Daehie
    INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING, 2018, 19 (02) : 293 - 298
  • [34] Usefulness of Nonlinear Interpolation and Particle Filter in Zigbee Indoor Positioning
    Zhang, Xiang
    Guo, Hang
    Wu, Helei
    Uradzinski, Marcin
    GEODESY AND CARTOGRAPHY, 2014, 63 (02): : 219 - 233
  • [35] A Method of Map Matching based on Particle Filter in Indoor Positioning
    Deng, Zhongliang
    Ruan, Fengli
    Lu, Shunbao
    Zheng, Ruoyu
    Zeng, Hui
    Fang, Yeqing
    Yang, Yi
    PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON APPLIED SCIENCE AND ENGINEERING INNOVATION, 2015, 12 : 923 - 928
  • [36] Annealed Stein Particle Filter for Mobile Positioning in Indoor Environments
    Piavanini, Marco
    Barbieri, Luca
    Brambilla, Mattia
    Nicoli, Monica
    ICC 2023-IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS, 2023, : 2510 - 2515
  • [37] Indoor Geomagnetic Positioning Based on Joint Algorithm of Particle Filter
    Huang H.
    Qiu K.
    Li W.
    Luo D.
    Xinan Jiaotong Daxue Xuebao/Journal of Southwest Jiaotong University, 2019, 54 (03): : 604 - 610
  • [38] Indoor positioning tracking with magnetic field and improved particle filter
    Zhang, Mei
    Qing, Tingting
    Zhu, Jinhui
    Shen, Wenbo
    INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS, 2017, 13 (11):
  • [39] An Indoor Map Matching Algorithm Based on Improved Particle Filter
    Yu, Baoguo
    Jia, Haonan
    Wang, Xinjian
    Li, Shuang
    2022 IEEE 10TH INTERNATIONAL CONFERENCE ON INFORMATION, COMMUNICATION AND NETWORKS (ICICN 2022), 2022, : 158 - 163
  • [40] Indoor Mobile Robot Localization based on a Particle Filter Approach
    Grami, Takoua
    Tlili, Ali Sghaier
    2019 19TH INTERNATIONAL CONFERENCE ON SCIENCES AND TECHNIQUES OF AUTOMATIC CONTROL AND COMPUTER ENGINEERING (STA), 2019, : 47 - 52