研究报告

  • 宋伟,孔庆媛,李洪枚.木家具关键挥发性有机化合物散发传质特性[J].环境科学学报,2013,33(6):1703-1719

  • 木家具关键挥发性有机化合物散发传质特性
  • Mass transfer characteristics of key VOCs emission from wood furniture
  • 基金项目:国家科技支撑计划项目(No.2013BAK04B04-01);北京市科技计划项目 (No. D09050603750802); 质检公益性行业科研专项 (No. 201210033,201110013-04, 201010013-4)
  • 作者
  • 单位
  • 宋伟
  • 1. 首都经济贸易大学安全与环境工程学院, 北京 100070;
    2. 国家家具及室内环境质量监督检验中心, 北京 100068;
    3. 清华大学建筑技术科学系, 北京 100084
  • 孔庆媛
  • 1. 首都经济贸易大学安全与环境工程学院, 北京 100070;
    2. 国家家具及室内环境质量监督检验中心, 北京 100068
  • 李洪枚
  • 首都经济贸易大学安全与环境工程学院, 北京 100070
  • 摘要:木家具中挥发性有机化合物(Volatile Organic Compounds, VOCs)的散发是一个污染环境的复杂传质过程.为把握污染物散发全周期特性,首先建立了一套描述散发行为的显性完全解析模型,适用于模拟对人体最不利的无换气情况.然后基于对模型的分析开发了一种简便快捷的实验方法,能够利用木家具在密闭舱中散发的逐时浓度求取目标VOCs的3个重要传质参数:可散发浓度C0、扩散系数D和分配系数K.实验部分测算了从10个厂家依多种原材料定制的5类20件常见家具,参考出现频率、健康影响、可散发量确定了19类关键污染物,发现总体C0DK服从正态分布.此外,结合常见散发参数范围下的数值实验和参数回归分析,提出一组反映散发机理、预测类比不同时空尺度下散发数据的准则关联式,并分析得出空气交换率和承载率对散发影响较大、空气流速对散发影响较小.
  • Abstract:Volatile organic compounds (VOCs) emission from wood furniture is a complex process of mass transfer that has negative environmental impacts. To have a clear picture of emission characteristics in the complete emission period, an explicit fully analytical model describing VOCs emission behavior in the static chamber was firstly established. Emission in the static chamber is the most unfavorable to human health. This model was applied to further develop an experimental method for conveniently, rapidly and simultaneously measuring three significant mass transfer parameters of target VOCs emitted from furniture by making use of emission process concentrations in a static chamber. These transfer parameters include emittable concentration C0, diffusion coefficient D and partition coefficient K. In experiments, we used this method to study twenty pieces in five classes of furniture customized from ten manufacturers with a variety of common raw materials. Nineteen key harmful chemicals were obtained according to the frequency of occurrence, negative effects on health and emittable concentration. In addition, the values of overall C0, D and K fit normal distribution well. Combined with numerical experiments and parameter regression based on common range of emission parameters, a group of dimensionless correlations was attained, which reflected the emission mechanism and could be well applied to the data analogy under different scales in time and space. The correlations indicated that both air change rate and loading factor had greater impacts on emission than that of air velocity.

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