Imaging VOC distribution in cities and tracing VOC emission sources with a novel mobile proton transfer reaction mass spectrometer.

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2020
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Abstract
Volatile organic compounds (VOCs) are important precursors of ozone (O) and secondary organic aerosols (SOAs). Tracing VOC pollution sources is important for controlling VOC emissions and reducing O and SOAs. We built a novel mobile proton transfer reaction mass spectrometry (M-PTR-MS) instrument to image the distribution of VOCs and trace their emission sources in cities and industrial parks. The M-PTR-MS is composed of a vibration-resistant proton transfer reaction mass spectrometry (PTR-MS) with a global positioning system receiver, modified box vehicle, and geographic information system (GIS) software. The PTR-MS, mounted on a vehicle, sends VOC data and vehicle position information to the GIS software. These data are used to image the space distribution of VOCs in real time while the vehicle platform is in motion and the VOC sources are precisely traced using the GIS. The spatial data resolution of the M-PTR-MS is typically 0.8 m. The limits of detection, sensitivity, and repeatability of the M-PTR-MS are 43.5 ppt, 347 counts ppb, and 2.4% (RSD, n = 5), respectively. The intensity of reagent ions is stable over 8 h (RSD = 0.45%). Compared with commercial PTR-MS equipment, the M-PTR-MS demonstrated high consistency, with a correlation coefficient of 92.665%. Several field experiments were conducted in China using the M-PTR-MS. In one field experiment, the VOC distribution along three different routes was surveyed; the navigation monitoring lasted 1.8 h over a distance of 26.7 km at an average speed of 15 km h. The VOC sources in an industrial park were identified by analyzing the components near different factories. The main species from a VOC source in an underground garage was related to paint. The M-PTR-MS instrument can be used by environmental protection agencies to trace VOC pollution sources in real time, and by researchers to survey VOC emissions in regions of concern.
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liang2020imagingenvironmental Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Liang, Qu;Bao, Xun;Sun, Qin;Zhang, Qiangling;Zou, Xue;Huang, Chaoqun;Shen, Chengyin;Chu, Yannan;
Journal Environmental pollution (Barking, Essex : 1987)
Year 2020
DOI
S0269-7491(19)37339-7
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