globalchange  > 气候变化与战略
DOI: 10.1016/j.atmosenv.2020.117291
论文题名:
Improved method for the optical analysis of particulate black carbon (BC) using smartphones
作者: Chen G.; Wang Q.; Fan Y.; Han Y.; Wang Y.; Urch B.; Silverman F.; Tian M.; Su Y.; Qiu X.; Zhu T.; Chan A.W.H.
刊名: Atmospheric Environment
ISSN: 1352-2310
出版年: 2020
卷: 224
语种: 英语
英文关键词: Cameras ; Carbon ; Climate change ; Combustion ; Cost effectiveness ; Image processing ; Light absorption ; Mean square error ; Optical data processing ; Particles (particulate matter) ; Smartphones ; Air pollution measurements ; Atmospheric particulate matter ; Black carbon ; Incomplete combustion ; Measurement techniques ; Reference measurements ; Root mean square errors ; Smart-phone cameras ; Cost benefit analysis ; black carbon ; absorption ; accuracy assessment ; atmospheric pollution ; black carbon ; combustion ; elemental carbon ; emission ; image processing ; mobile phone ; model validation ; particulate matter ; Article ; color ; combustion ; detection algorithm ; image processing ; polarimetry ; priority journal
学科: Black carbon ; Image processing ; Light absorption ; Low cost air pollution measurement ; Smartphone camera
中文摘要: Black carbon (BC) is a major component in atmospheric particulate matter (PM), which causes adverse health impacts and contributes significantly to climate change. Without widespread and accurate BC measurements, it remains difficult to track incomplete combustion sources and reduce BC emissions. Currently commercial BC sensors remain too costly to be deployed widely. In this work, a fast, cost-effective, and easily accessible method based on a smartphone camera was used to quantify color information of PM collected on filters to estimate BC and elemental carbon (EC) loadings. A robust RGB (red, green, blue)-based linear interaction model was built and validated using 1878 PM samples collected in three different regions with collocated BC and EC measurements. After applying image correction methods, this model shows a good predictability with an R-squared (R2) of 0.904 with state-of-the-art BC measurement techniques, and a coefficient of variation of the root mean square error (CV(RMSE)) of 25.3% despite the complex sources and different reference measurement techniques. This work validates the viabilities of using smartphones to quantify BC or EC loading on PM filters with a unified model and track incomplete combustion sources. © 2020 Elsevier Ltd
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/160914
Appears in Collections:气候变化与战略

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作者单位: Department of Chemical Engineering & Applied Chemistry, University of Toronto, Toronto, ON, Canada; BIC-ESAT and SKL-ESPC, College of Environmental Sciences and Engineering, Peking University, Beijing, China; Division of Occupational and Environmental Health, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada; Southern Ontario Centre for Atmospheric Aerosol Research (SOCAAR), Toronto, Ontario, Canada; Divisions of Occupational Medicine and Respirology, Department of Medicine, University of Toronto, Toronto, Ontario, Canada; School of Urban Construction and Environmental Engineering, Chongqing University, Chongqing, China; Environment Monitoring and Reporting Branch, Ontario Ministry of the Environment, Conservation and Parks, Toronto, ON, Canada

Recommended Citation:
Chen G.,Wang Q.,Fan Y.,et al. Improved method for the optical analysis of particulate black carbon (BC) using smartphones[J]. Atmospheric Environment,2020-01-01,224
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