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Big Data Analysis on the State of Automotive Cabin Air Filters in China

IOP conference series. Earth and environmental science, 2020-11, Vol.571 (1), p.12083 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd ;2020. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1755-1307 ;EISSN: 1755-1315 ;DOI: 10.1088/1755-1315/571/1/012083

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  • Title:
    Big Data Analysis on the State of Automotive Cabin Air Filters in China
  • Author: He, Yongao ; Du, Tianqiang ; Wei, Shuhong ; Yin, Wei ; Tian, Cheng ; Li, Chuanjie
  • Subjects: Air filters ; Air purification ; COVID-19 ; Data analysis ; Geographical distribution ; Inspection ; Particle size distribution ; Particulates ; Research facilities
  • Is Part Of: IOP conference series. Earth and environmental science, 2020-11, Vol.571 (1), p.12083
  • Description: Under the influence of the COVID-19, consumers pay more and more attention to the safety and health of the air in the car. As the core component of the air purification in the car, the performance of the cabin air filter is a hot topic for vehicle enterprises and parts enterprises. This paper introduces the inspection and data analysis of cabin air filter products in China by China Automotive Technology And Research Center, which includes the product geographical distribution, brand compliance rate, the compliance rate of different testing items. Based on the analysis of fractional efficiency of 0.3 μm, 2.5 μm and 10 μm particle sizes and particle sizes distribution in the atmosphere, this paper puts forward the view that it is necessary to pay more attention to the fractional efficiency of particulates which below 1 μm. In addition, the existing problems of cabin air filter are studied by data and its development direction is prospected.
  • Publisher: Bristol: IOP Publishing
  • Language: English
  • Identifier: ISSN: 1755-1307
    EISSN: 1755-1315
    DOI: 10.1088/1755-1315/571/1/012083
  • Source: IOP Publishing (Open access)
    AUTh Library subscriptions: ProQuest Central
    IOPscience (Open Access)
    Alma/SFX Local Collection
    Coronavirus Research Database
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