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CoagLite: A low-computational-cost integral model for simulating indoor ultrafine particle dynamics
Chen Chen1, Chuanhao Wang2, Wenxin Wang2
1Department of Architecture and Civil Engineering, Xiamen University, Xiamen 361005, China; Department of Building Science, School of Architecture, Tsinghua University, Beijing 100084, China; Fujian Province University Key Laboratory of Intelligent and Low-carbon Building Technology, Xiamen University, Xiamen, Fujian 361005, China; Xiamen Key Laboratory of Integrated Application of Intelligent Technology for Architectural Heritage Protection, Xiamen University, Xiamen, Fujian 361005, China; Fujian Key Laboratory of Digital Simulations for Coastal Civil Engineering, School of Architecture and Civil Engineering, Xiamen University, Xiamen, Fujian 361005, China.
Abstract:
Despite the harm to human health caused by ultrafine particle (UFP) pollution, the high cost of measurement instruments limits its monitoring. Simulating UFP concentrations is important for large-scale and long-term exposure assessments; however, such work is constrained by the substantial computational demands caused by dominant coagulation effects. Strong correlations between coagulation rates across the whole size ranges of 10-100 nm and total UFP concentrations were determined using our previous dataset of 13,843 samples measured in a residence in Beijing City, China, and used to derive effective coagulation coefficients (ECC) for both size-resolved and total UFPs. These coefficients were used to establish an integral formulation for simulating size-resolved and total indoor UFP concentrations, which we named the "CoagLite model". CoagLite model simulations were validated using our previously measured data and found to be highly consistent with traditional Fuchs model simulations. Moreover, CoagLite was nearly 30 times faster owing to the substantially reduced computational load, which enabled large-scale and long-term indoor UFP simulations. The size-resolved ECC values and CoagLite model were further cross-validated using an independent dataset of 10,626 samples collected from a residence in Xiamen City, China. The applicability domain for the model parameters was identified, demonstrating that the CoagLite model performs well under typical residential conditions.
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