Isiugo Kelechi, Jandarov Roman, Cox Jennie, Chillrud Steve, Grinshpun Sergey A, Hyttinen Marko, Yermakov Michael, Wang Julian, Ross James, Reponen Tiina
Department of Environmental Health, University of Cincinnati,160 Panzeca Way, Kettering Laboratory, Cincinnati, Ohio USA 45267.
Lamont-Doherty Earth Observatory at Columbia University.
Atmos Environ (1994). 2019 Mar 15;201:223-230. doi: 10.1016/j.atmosenv.2018.12.053. Epub 2019 Jan 9.
Black carbon (BC) is a descriptive term that refers to light-absorbing particulate matter (PM) produced by incomplete combustion and is often used as a surrogate for traffic-related air pollution. Exposure to BC has been linked to adverse health effects. Penetration of ambient BC is typically the primary source of indoor BC in the developed world. Other sources of indoor BC include biomass and kerosene stoves, lit candles, and charring food during cooking. Home characteristics can influence the levels of indoor BC. As people spend most of their time indoors, human exposure to BC can be associated to a large extent with indoor environments. At the same time, due to the cost of environmental monitoring, it is often not feasible to directly measure BC inside multiple individual homes in large-scale population-based studies. Thus, a predictive model for indoor BC is needed to support risk assessment in public health. In this study, home characteristics and occupant activities that potentially modify indoor levels of BC were documented in 23 homes, and indoor and outdoor BC concentrations were measured twice. The homes were located in the Cincinnati-Kentucky-Indiana tristate region and measurements occurred from September 2015 through August 2017. A linear mixed-effect model was developed to predict BC concentration in residential environments. The measured outdoor BC concentrations and the documented home characteristics were utilized as predictors of indoor BC concentrations. After the model was developed, a leave-one-out cross-validation algorithm was deployed to assess the predictive accuracy of the output. The following home characteristics and occupant activities significantly modified the concentration of indoor BC: outdoor BC, lit candles and electrostatic or high efficiency particulate air (HEPA) filters in heating, ventilation and air conditioning (HVAC) systems. Predicted indoor BC concentrations explained 78% of the variability in the measured indoor BC concentrations. The data show that outdoor BC combined with home characteristics can be used to predict indoor BC levels with reasonable accuracy.
黑碳（BC）是一个描述性术语，指不完全燃烧产生的吸光颗粒物（PM），常被用作与交通相关空气污染的替代指标。接触黑碳与不良健康影响有关。在发达国家，室外黑碳的渗透通常是室内黑碳的主要来源。室内黑碳的其他来源包括生物质炉和煤油炉、点燃的蜡烛以及烹饪过程中食物的烧焦。家庭特征会影响室内黑碳水平。由于人们大部分时间都在室内，人类接触黑碳在很大程度上可能与室内环境有关。同时，由于环境监测成本较高，在大规模基于人群的研究中直接测量多个家庭室内的黑碳往往不可行。因此，需要一个室内黑碳预测模型来支持公共卫生风险评估。在本研究中，记录了23个家庭中可能改变室内黑碳水平的家庭特征和居住者活动，并对室内和室外黑碳浓度进行了两次测量。这些家庭位于辛辛那提 - 肯塔基 - 印第安纳三州地区，测量时间为2015年9月至2017年8月。开发了一个线性混合效应模型来预测住宅环境中的黑碳浓度。测量的室外黑碳浓度和记录的家庭特征被用作室内黑碳浓度的预测指标。模型开发完成后，采用留一法交叉验证算法评估输出结果的预测准确性。以下家庭特征和居住者活动显著改变了室内黑碳浓度：室外黑碳、点燃的蜡烛以及供暖、通风和空调（HVAC）系统中的静电或高效空气过滤器（HEPA）。预测的室内黑碳浓度解释了测量的室内黑碳浓度变异性的78%。数据表明，室外黑碳与家庭特征相结合可以以合理的准确度预测室内黑碳水平。
