李盛, 樊琳, 王先良, 吴允萍, 许军, 李昕蓉, 王金玉. 兰州市某城区住宅室内空气颗粒物污染现状及影响因素[J]. 环境与职业医学, 2021, 38(7): 747-751. DOI: 10.13213/j.cnki.jeom.2021.20589
引用本文: 李盛, 樊琳, 王先良, 吴允萍, 许军, 李昕蓉, 王金玉. 兰州市某城区住宅室内空气颗粒物污染现状及影响因素[J]. 环境与职业医学, 2021, 38(7): 747-751. DOI: 10.13213/j.cnki.jeom.2021.20589
LI Sheng, FAN Lin, WANG Xianliang, WU Yunping, XU Jun, LI Xinrong, WANG Jinyu. Indoor particulate matter pollution and its influencing factors in a residential area of Lanzhou City[J]. Journal of Environmental and Occupational Medicine, 2021, 38(7): 747-751. DOI: 10.13213/j.cnki.jeom.2021.20589
Citation: LI Sheng, FAN Lin, WANG Xianliang, WU Yunping, XU Jun, LI Xinrong, WANG Jinyu. Indoor particulate matter pollution and its influencing factors in a residential area of Lanzhou City[J]. Journal of Environmental and Occupational Medicine, 2021, 38(7): 747-751. DOI: 10.13213/j.cnki.jeom.2021.20589

兰州市某城区住宅室内空气颗粒物污染现状及影响因素

Indoor particulate matter pollution and its influencing factors in a residential area of Lanzhou City

  • 摘要: 背景

    住宅室内空气污染与人体健康密切相关,颗粒物是重要的室内污染物之一。

    目的

    了解兰州市某城区住宅室内颗粒物污染情况及影响因素。

    方法

    于2020年9月(非采暖季)和11月(采暖季),收集兰州市某城区大气环境监测数据,在该区大气污染最严重的监测站点所在区域3 km以内的范围随机选择1所小学,在该小学二年级通过问卷筛查选择30名小学生,以其家庭作为监测住宅,每户住宅分别选择客厅和一个卧室为采样点进行室内PM2.5、PM10、温度和相对湿度检测,同时问卷调查住宅特征。超标率比较采用χ2检验;中位数的差异分析采用Mann-Whitney U检验;不同季节室内颗粒物超标的住宅特征影响因素采用多因素logistic回归分析;不同季节住宅室内温度、相对湿度与颗粒物浓度的相关性,不同季节住宅室内外颗粒物浓度的相关性采用Spearman等级相关分析。

    结果

    30户住宅室内PM2.5、PM10质量浓度(后称浓度)中位数分别为128.90、155.40 μg·m-3,超标率分别为79.2%、50.8%;PM2.5、PM10浓度采暖季高于非采暖季(Z=-6.716,-6.550;P < 0.05),超标率采暖季高于非采暖季(χ2=19.943,29.037;P < 0.05)。室内温度、相对湿度的中位数分别为22℃、43%,超标率分别为5.8%、12.5%,相对湿度超标率采暖季高于非采暖季(χ2=9.219,P < 0.05)。非采暖季,拖地或吸尘的频率 < 1次·d-1是PM10超标的危险因素,OR(95% CI)值为10.248(1.747~60.107);开窗通风频率 < 2次·d-1对PM2.5、PM10均有影响,OR(95% CI)值分别为5.196(1.413~19.110)、12.079(1.845~79.097)。非采暖季,室内温度、相对湿度与PM2.5r=-0.771,-0.672;P < 0.05)、PM10浓度均呈负相关(r=-0.664,-0.632;P < 0.05)。住宅室外空气中PM2.5、PM10浓度采暖季(81.00、144.00 μg·m-3)高于非采暖季(18.00、38.00 μg·m-3)(Z=-9.141,-9.136;P < 0.05)。非采暖季,室内外PM10浓度呈弱正相关(r=0.294,P < 0.05);在采暖季,室内外的PM2.5、PM10浓度均呈明显正相关(r=0.597,0.708;P < 0.05)。

    结论

    兰州市某城区住宅室内存在颗粒物污染情况,采暖季较严重;拖地吸尘频率、开窗通风频率、温度、相对湿度和室外颗粒物污染对室内颗粒物水平有影响。

     

    Abstract: Background

    Indoor air pollution is closely related to human health, and particulate matter is one of the important indoor pollutants.

    Objective

    This study investigates the indoor particulate matter pollution level and its influencing factors in residential buildings in an urban area of Lanzhou.

    Methods

    In September (non-heating season) and November (heating season) of 2020, the air monitoring data in an urban area of Lanzhou City were collected. A primary school was randomly selected within 3 km of a monitoring station with the most serious air pollution. A total of 30 students in grade 2 in the school were selected through questionnaire survey, and their families were selected as monitoring sites. Indoor PM2.5, PM10, temperature, and relative humidity were detected in a living room and a bedroom in each of the 30 households. The residential characteristics were investigated by questionnaires. Chi-square test was used to analyze unqualified rates. Mann-Whitney U test was used for median comparison. Multiple logistic regression analysis was used to evaluate selected influencing factors of the levels of indoor particulate matter in different seasons. Spearman rank correlation was used to analyze the season-specific correlations of indoor temperature and relative humidity with particulate matter level, as well as the season-specific correlations between indoor and outdoor particulate matter levels.

    Results

    The median concentrations of indoor PM2.5 and PM10 were 128.90 μg·m-3 and 155.40 μg·m-3, and the unqualified rates were 79.2% and 50.8%, respectively, in the selected 30 households. The median concentrations of indoor PM2.5 and PM10 were higher in heating season than those in non-heating season (Z=-6.716, -6.550, P < 0.05), and so were the unqualified rates (χ2=19.943, 29.037, P < 0.05). The median indoor temperature and relative humidity were 22℃ and 43%, and the unqualified rates were 5.8% and 12.5%, respectively. The unqualified rate of relative humidity was higher in heating season than in non-heating season (χ2=9.219, P < 0.05). In non-heating season, mopping or dust collection less than 1 time per day was a risk factor for unqualified PM10, and the OR (95% CI) was 10.248 (1.747-60.107); opening windows less than 2 times per day was a risk factor for unqualified PM2.5 and PM10, and the ORs (95% CIs) were 5.196 (1.413- 19.110) and 12.079 (1.845-79.097), respectively. In non-heating season, temperature and relative humidity were negatively correlated with PM2.5 (r=-0.771, -0.672, P < 0.05) and PM10 (r=-0.664, -0.632, P < 0.05) concentrations. The median concentrations of outdoor PM2.5 and PM10 were higher in heating season (81.00 and 144.00 μg·m-3) than in non-heating season (18.00 and 38.00 μg·m-3) (Z=-9.141, -9.136, P < 0.05). In non-heating season, there was a weak positive correlation between indoor and outdoor PM10 concentrations (r=0.294, P < 0.05). In heating season, the indoor and outdoor correlations of both PM2.5 and PM10 were significantly positive (r=0.597, 0.708, P < 0.05).

    Conclusion

    There is indoor particulate matter pollution in selected households in the urban area of Lanzhou, especial in heating season. The levels of indoor particulate matter may be influenced by mopping and dust collection frequency, ventilation frequency, temperature, relative humidity, and outdoor particulate matter pollution.

     

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