The COVID-19 pandemic brought global attention to indoor air quality (IAQ), which is intrinsically linked to clean air change rates. Estimating the air change rate in indoor environments, however, remains challenging. It is primarily due to the uncertainties associated with the air change rate estimation, such as pollutant generation rates, dynamics including weather and occupancies, and the limitations of deterministic approaches to accommodate these factors. In this study, Bayesian inference was implemented on a stochastic CO2-based grey-box model to infer modeled parameters and quantify uncertainties. The accuracy and robustness of the ventilation rate and CO2 emission rate estimated by the model were confirmed with CO2 tracer gas experiments conducted in an airtight chamber. Both prior and posterior predictive checks (PPC) were performed to demonstrate the advantage of this approach. In addition, uncertainties in real-life contexts were quantified with an incremental variance {\sigma} for the Wiener process. This approach was later applied to evaluate the ventilation conditions within two primary school classrooms in Montreal. The Equivalent Clean Airflow Rate (ECAi) was calculated following ASHRAE 241, and an insufficient clean air supply within both classrooms was identified. A supplement of 800 cfm clear air delivery rate (CADR) from air-cleaning devices is recommended for a sufficient ECAi. Finally, steady-state CO2 thresholds (Climit, Ctarget, and Cideal) were carried out to indicate when ECAi requirements could be achieved under various mitigation strategies, such as portable air cleaners and in-room ultraviolet light, with CADR values ranging from 200 to 1000 cfm.

翻译：COVID-19疫情使全球关注与清洁空气换气率密切相关的室内空气质量（IAQ）。然而，室内环境空气换气率的估算仍具挑战性。这主要源于空气换气率估算相关的不确定性因素，包括污染物产生率、天气和 occupancy 等动态变化，以及确定性方法在容纳这些因素时的局限性。本研究在基于随机CO2的灰箱模型中应用贝叶斯推断，以推演模型参数并量化不确定性。通过密闭舱室CO2示踪气体实验，验证了模型估算的通风率和CO2排放率的准确性与稳健性。采用先验预测检验和后验预测检验（PPC）证明该方法的优势。此外，通过为维纳过程引入增量方差{\sigma}，量化了实际场景中的不确定性。该方法随后被应用于评估蒙特利尔两间小学教室的通风条件。依据ASHRAE 241标准计算等效清洁空气流量（ECAi），发现两间教室均存在清洁空气供应不足问题。建议通过空气净化设备补充800 cfm清洁空气输送率（CADR）以满足ECAi要求。最后，确定稳态CO2阈值（Climit、Ctarget和Cideal），以指示当采用包括便携式空气净化器和室内紫外线灯（CADR值范围为200至1000 cfm）在内的多种缓解策略时，ECAi要求可实现的条件。