Residential Building Systems Group and Indoor Environment Group, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
Int J Environ Res Public Health. 2022 May 28;19(11):6603. doi: 10.3390/ijerph19116603.
Recent studies have succeeded in relating emissions of various volatile organic compounds to material mass diffusion transfer using detailed empirical characteristics of each of the individual emitting materials. While significant, the resulting models are often scenario specific and/or require a host of individual component parameters to estimate emission rates. This study developed an approach to estimate aggregated emissions rates based on a wide number of field measurements. We used a multi-parameter regression model based on previous mass transfer models to predict formaldehyde emission rate for a whole dwelling using field-measured, time-resolved formaldehyde concentrations, air exchange rates, and indoor environmental parameters in 63 California single-family houses built between 2011 and 2017. The resulting model provides time-varying formaldehyde emission rates, normalized by floor area, for each study home, assuming a well-mixed mass balance transport model of the home, and a well-mixed layer transport model of indoor surfaces. The surface layer model asserts an equilibrium concentration within the surface layer of the emitted materials that is a function of temperature and ; the dwelling ventilation rate serves as a surrogate for indoor concentration. We also developed a more generic emission model that is suitable for broad prediction of emission for a population of buildings. This model is also based on measurements aggregated from 27 homes from the same study. We showed that errors in predicting household formaldehyde concentrations using this approach were substantially less than those using a traditional constant emission rate model, despite requiring less unique building information.
最近的研究成功地将各种挥发性有机化合物的排放与每种排放材料的详细经验特征相关联,从而实现物质质量扩散转移。虽然这些模型意义重大,但通常是特定于场景的,或者需要大量的单个组件参数来估计排放率。本研究开发了一种基于大量现场测量来估计综合排放率的方法。我们使用了一种基于先前质量传递模型的多参数回归模型,根据现场测量的、时间分辨的甲醛浓度、空气交换率以及 2011 年至 2017 年间在加利福尼亚州建造的 63 座单户住宅中的室内环境参数,预测整个住宅的甲醛排放率。该模型为每个研究住宅提供了按建筑面积归一化的时变甲醛排放率,假设住宅采用混合良好的质量平衡传输模型和室内表面的混合层传输模型。表面层模型断言,排放材料的表面层内存在一个平衡浓度,这是温度和的函数;居住通风率是室内浓度的替代物。我们还开发了一种更通用的排放模型,适用于广泛预测建筑物群体的排放。该模型也是基于同一研究中来自 27 个家庭的测量结果汇总得出的。我们表明,尽管需要的独特建筑信息较少,但与传统的恒定排放率模型相比,使用该方法预测家庭甲醛浓度的误差要小得多。