LI Xin-wei , ZHANG Hua , ZHANG Yang , ZHANG Ji . Concentrations and Variations of Office Indoor Air Particulate Matters in Jinan[J]. Journal of Environmental and Occupational Medicine, 2014, 31(12): 947-949. DOI: 10.13213/j.cnki.jeom.2014.0231
Citation: LI Xin-wei , ZHANG Hua , ZHANG Yang , ZHANG Ji . Concentrations and Variations of Office Indoor Air Particulate Matters in Jinan[J]. Journal of Environmental and Occupational Medicine, 2014, 31(12): 947-949. DOI: 10.13213/j.cnki.jeom.2014.0231

Concentrations and Variations of Office Indoor Air Particulate Matters in Jinan

  • Objective To assess the concentration of particulate matters in indoor air and its variation tendency.

    Methods Indoor air levels of PM2.5 and PM10 were monitored with LD-5C(B) microcomputer laser fine particulate matter monitor in an office in Jinan during working days from September 2012 to August 2013. The sampling was conducted once an hour, and each lasted 5 min to calculate daily concentrations.

    Results The indoor average concentrations of PM10 and PM2.5 were 0.112 mg/m3 and 0.078 mg/m3, respectively. The monthly average concentrations of indoor particulate matters for January, February, June, July, and October were higher than those of the other months. The PM2.5 concentration of the first quarter was higher (H=10.829, P=0.013) than those of the other three quarters, while there was no significant difference (H=7.284, P=0.063) among the seasons for the PM10 concentrations. The PM2.5 concentration during the heating period (15 November 2012-15 March 2013) was higher (Z=-2.368, P=0.018) than that of the non-heating period, while no significant difference (Z=-0.927, P=0.354) was observed for the PM10 concentrations. The ratios of PM2.5/PM10 during the heating and non-heating periods were 0.79 and 0.65, respectively (Z=-4.897, P=0.000).

    Conclusion The indoor air in Jinan is heavily polluted by particulate matters. The concentrations of particulate matters show seasonal variations. Central heating systems contribute a significant proportion to local indoor PM2.5 concentration.

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