刘萌萌, 曹赟, 张晓彤, 张文颖, 蒋林霖, 杨玉燕, 杜航, 樊琳, 王先良. 我国12城市住宅居室内PM2.5污染特征及影响因素分析[J]. 环境卫生学杂志, 2024, 14(3): 233-239, 253. DOI: 10.13421/j.cnki.hjwsxzz.2024.03.008
    引用本文: 刘萌萌, 曹赟, 张晓彤, 张文颖, 蒋林霖, 杨玉燕, 杜航, 樊琳, 王先良. 我国12城市住宅居室内PM2.5污染特征及影响因素分析[J]. 环境卫生学杂志, 2024, 14(3): 233-239, 253. DOI: 10.13421/j.cnki.hjwsxzz.2024.03.008
    LIU Meng-meng, CAO Yun, ZHANG Xiao-tong, ZHANG Wen-ying, JIANG Lin-lin, YANG Yu-yan, DU Hang, FAN Lin, WANG Xian-liang. PM2.5 characteristics and influencing factors in residential homes across 12 cities in China[J]. Journal of Environmental Hygiene, 2024, 14(3): 233-239, 253. DOI: 10.13421/j.cnki.hjwsxzz.2024.03.008
    Citation: LIU Meng-meng, CAO Yun, ZHANG Xiao-tong, ZHANG Wen-ying, JIANG Lin-lin, YANG Yu-yan, DU Hang, FAN Lin, WANG Xian-liang. PM2.5 characteristics and influencing factors in residential homes across 12 cities in China[J]. Journal of Environmental Hygiene, 2024, 14(3): 233-239, 253. DOI: 10.13421/j.cnki.hjwsxzz.2024.03.008

    我国12城市住宅居室内PM2.5污染特征及影响因素分析

    PM2.5 characteristics and influencing factors in residential homes across 12 cities in China

    • 摘要:
      目的 了解我国典型城市住宅居室内PM2.5的污染特征及影响因素,为做好居室健康防护提供科学依据。
      方法 采用现况研究,2018年4月—2019年3月,选取12个典型城市共612户家庭,分别于暖季和冷季检测其室内PM2.5浓度、温度和湿度,并通过问卷调查获取家庭居室基本特征。利用配对t检验、单因素方差分析和温湿度校正的协方差分析比较居室内PM2.5浓度差异,采用多因素线性回归分析居室内PM2.5浓度的影响因素。
      结果 我国12城市家庭居室内PM2.5质量浓度几何均数为54.0 μg/m3M(P25P75)为53.9(30.6,94.5)μg/m3。51.4%的居室PM2.5超过《室内空气质量标准》(GB/T 18883-2022)中规定的PM2.5的标准限值50 μg/m3。冷季居室内PM2.5质量浓度高于暖季(t=-18.14, P < 0.001);不同室内采样点之间的PM2.5质量浓度未发现差异(暖季:t=0.56, P=0.578;冷季:t=0.06, P=0.956);经过温湿度校正后,冷季上下风向区间居室内PM2.5浓度存在差异(F=5.94,P=0.015,P′=0.003);不同行政区划间居室内PM2.5浓度差异具有统计学意义(暖季:F=29.13,P < 0.001;冷季:F=66.89,P < 0.001)。多因素回归分析显示,近五年内装修过、室内种植花草、使用中央空调是居室内PM2.5质量浓度升高的危险因素,OR(95%CI)值分别为5.700(2.564,12.671)、6.212(2.515,15.341)、8.585 (1.969,37.434)。使用空气净化器是保护因素,OR(95%CI)值为0.065(0.027,0.161)。
      结论 我国典型城市住宅居室的PM2.5污染水平整体较高,且城市间季节和地理分布差异较明显。近五年内装修、使用中央空调是居室内PM2.5浓度偏高的危险因素,使用空气净化器是保护因素。

       

      Abstract:
      Objective To investigate the characteristics and influencing factors of fine particulate matter (PM2.5)pollution in residential homes in representative cities of China, and to provide a scientific basis for effective indoor health protection measures.
      Methods Using a cross-sectional research design, from April 2018 to March 2019, a total of 612 homes were selected from 12 representative cities; indoor PM2.5 concentrations, temperature, and humidity were measured during both warm and cold seasons, and the general characteristics of the homes were collected through a questionnaire survey. Indoor PM2.5 concentrations were compared using the paired t test, one-way analysis of variance, and covariance analysis with temperature and humidity adjustment. A multivariable linear regression analysis was used to determine factors influencing indoor PM2.5 concentrations.
      Results The geometric mean of indoor PM2.5 mass concentrations across the 12 cities was 54.0 μg/m3, and the median (P25, P75)was 53.9 (30.6, 94.5)μg/m3. The indoor PM2.5 of 51.4% of the surveyed homes exceeded the standard limit for PM2.5 (50 μg/m3)specified in the Standards for Indoor Air Quality (GB/T 18883-2022). The mass concentration of indoor PM2.5 in the cold season was higher than that in the warm season(t=-18.14, P < 0.001). No differences were found in the PM2.5 mass concentration between different indoor sampling points (warm season: t=0.56, P=0.578; cold season: t=0.06, P=0.956). After adjusting for temperature and humidity, there was a significant difference in the indoor PM2.5 concentration between upwind and downwind areas in the cold season (F=5.94, P=0.015, P'=0.003). The indoor PM2.5 concentration was significantly different for homes in different administrative regions (warm season: F=29.13, P < 0.001; cold season: F=66.89, P < 0.001). The multivariable regression analysis showed that having a decoration in the past five years, growing houseplants, and the use of central air conditioners were risk factors associated with increased indoor PM2.5 concentrations, and OR(95%CI)were 5.700 (2.564, 12.671), 6.212 (2.515, 15.341), and 8.585 (1.969, 37.434), respectively; the use of air purifiers was a protective factor, with OR(95%CI) being 0.065 (0.027, 0.161).
      Conclusion Indoor PM2.5 pollution levels in residential homes in representative cities of China are generally high, with significant variations in seasonal and geographical distributions among cities. Having an interior decoration in recent five years and the use of central air conditioners are risk factors contributing to higher indoor PM2.5 concentrations, while the use of air purifiers is a protective factor.

       

    /

    返回文章
    返回