Sofuoglu S C, Moschandreas D J
Department of Environmental Engineering, Suleyman Demirel University, Isparta, Turkey.
Indoor Air. 2003 Dec;13(4):332-43. doi: 10.1111/j.1600-0668.2003.00192.x.
The lack of an effective indoor air quality (IAQ) metric causes communication concerns among building tenants (the public), building managers (decision-makers), and IAQ investigators (engineers). The Indoor Air Pollution Index (IAPI) is developed for office buildings to bridge this communication discord. The index, simple and easily understood, employs the range of pollutant concentrations and concentrations in the subject building to estimate a unitless single number, the IAPI, between 0 (lowest pollution level and best IAQ) and ten (highest pollution level and worst IAQ). The index provides a relative measure of indoor air pollution for office buildings and ranks office indoor air pollution relative to the index distribution of the US office building population. Furthermore, the index associates well with occupant symptoms, percentage of occupants with persistent symptoms. A tree-structured method is utilized in conjunction with the arithmetic mean as the aggregation function. The hierarchical structure of the method renders not only one index value, but also several sub-index values that are critical in the study of an office air environment. The use of the IAPI for IAQ management is illustrated with an example. The decomposition of the index leads to the ranking of sampled pollutants by their relative contribution to the index and the identification of dominant pollutant(s). This information can be applied to design an effective strategy for reducing in-office air pollution.
缺乏有效的室内空气质量(IAQ)指标引发了建筑租户(公众)、建筑管理者(决策者)和IAQ调查人员(工程师)之间的沟通问题。室内空气污染指数(IAPI)专为办公楼开发,以弥合这种沟通分歧。该指数简单易懂,利用污染物浓度范围和目标建筑中的浓度来估计一个无量纲的单一数值,即IAPI,范围在0(最低污染水平和最佳IAQ)到10(最高污染水平和最差IAQ)之间。该指数为办公楼室内空气污染提供了一种相对度量,并根据美国办公楼群体的指数分布对办公室内空气污染进行排名。此外,该指数与居住者症状、有持续症状的居住者百分比密切相关。采用树形结构方法并结合算术平均值作为聚合函数。该方法的层次结构不仅产生一个指数值,还产生几个子指数值,这些子指数值在办公空气环境研究中至关重要。通过一个例子说明了IAPI在IAQ管理中的应用。指数的分解导致按采样污染物对指数的相对贡献对其进行排名,并确定主要污染物。这些信息可用于设计减少办公室内空气污染的有效策略。