Volatile organic compounds (VOCs) emitted from furniture severely influence indoor air quality. Prior studies have mainly focused on the emissions from building materials and vehicle cabin materials, but rarely refer to indoor furniture. Considering the complex internal structure of furniture, this study presents a two-layer numerical model to describe the emission behaviors of VOCs from wooden furniture. A multi-parameter regression method was then proposed to determine the key parameters in the furniture, i.e., the initial emittable concentration, the diffusion coefficient and the partition coefficient. Experiments were conducted in a 1 m³ environmental chamber for VOC emissions from two kinds of wooden furniture (panel furniture and solid wood furniture). The agreement between model predictions and test data (R² = 0.97–0.99) demonstrated the effectiveness of the model and measured key parameters. Compared with the traditional single-layer model, the two-layer numerical model can characterize the whole emission process from furniture better. In addition, the impact of temperature on the key parameters for furniture emissions was explored. With an increase in temperature from 23 °C to 35 °C, the diffusion coefficients for different VOCs from different wooden furniture, increase by 200%–2993%, while partition coefficients decrease by 41%–94%. This pattern conforms with that of VOC emissions from building materials. The present study should be helpful for source characterization of furniture and the associated exposure assessment.

家具排放的挥发性有机化合物 (VOC) 会严重影响室内空气质量。以往的研究主要集中在建筑材料和车厢材料的排放上，很少涉及室内家具。考虑到家具内部结构复杂，本研究提出了一个两层数值模型来描述木制家具中VOCs的排放行为。然后提出了一种多参数回归方法来确定家具中的关键参数，即初始可排放浓度、扩散系数和分配系数。实验在 1 m ³两种木制家具（板式家具和实木家具）的VOC排放环境试验室。模型预测与测试数据之间的一致性 (R ² = 0.97–0.99) 证明了模型和测量的关键参数的有效性。与传统的单层模型相比，两层数值模型可以更好地刻画家具的整个排放过程。此外，还探讨了温度对家具排放关键参数的影响。随着温度从 23°C 升高到 35°C，不同木制家具中不同 VOCs 的扩散系数增加 200%–2993%，而分配系数降低 41%–94%。这种模式符合建筑材料的VOC排放模式。本研究应有助于家具的来源表征和相关的暴露评估。