【作者】 何中凯；

【导师】 张寅平；

【作者基本信息】 清华大学 ， 土木工程， 2011， 博士

【摘要】 室内空气品质（Indoor air quality，简称IAQ）显著影响人们的舒适、健康和工作效率，而人造板散发的挥发性有机化合物（Volatile organiccompounds，简称VOCs）是造成室内空气品质低劣的主要原因之一。源头控制是改善室内空气品质的最佳方法，因此研究人造板VOC散发控制原理和方法，发展低散发人造板具有重要意义。传统研究中缺乏人造板不同生产阶段的VOC散发分析，导致原材料及生产工艺对人造板VOC散发的影响不明晰，缺乏遴选人造板表面阻隔层的有效方法，并且鲜有研究涉及优化吸附剂在人造板中的掺杂位置。本论文针对上述问题开展了相关研究，主要学术贡献如下：首先，测定了人造板不同生产阶段包括脲醛树脂、木片、施胶纤维、密度板、酚醛树脂等在内散发的VOC种类及可散发含量，发现胶粘剂中的甲醛可散发含量是影响人造板甲醛散发的主要因素，而人造板散发的其它VOC主要来源于木片；生产过程中的干燥及热压工艺有利于人造板中VOC种类及可散发含量的减少；得到了胶粘剂中甲醛可散发含量与人造板甲醛散发因子间的关联式，为在生产过程中预测和控制人造板甲醛散发速率提供了指导。其次，提出了测定人造板表面阻隔层内VOC扩散系数和分离系数的动态/静态舱法，其优点是测试时间短，测试结果精度较高，并导出了描述阻隔层阻隔效果的无量纲关联式，为遴选阻隔层降低人造板VOC散发速率提供了技术手段。第三，发展了简易的密闭环境舱法用于筛选甲醛吸附性能优良的吸附剂，并结合多层材料VOC散发模型建立了人造板中掺杂吸附剂的位置优化模型，提出了求解优化模型的方法，研究证明了较优的掺杂方式是将吸附剂全部置于人造板的顶层，为控制人造板VOC散发提供了理论依据。最后，基于上述分析，提出了低散发人造板的设计方法，并研制了实验室样品，实测结果表明人造板甲醛散发速率可降低约75%。更多还原

【Abstract】 Indoor air quality (IAQ) significantly influences people’s comfort, health andproductivity, and volatile organic compounds (VOCs) emitted from wood-based panelsare recognized as one of the major causes resulting in poor IAQ. Since source control isthe best mean for improving IAQ, it is important to study the control principle andmethod of VOC emissions from wood-based panels, and subsequently developlow-emitting wood-based panels. For the previous studies on this problem, there aresome shortcomings:(1) it lacks VOC emission analysis at different stages ofwood-based panels during its manufacturing process, hence the influence of rawmaterials and manufacturing techniques on VOC emissions from wood-based panels isunclear;(2) it lacks effective method for selecting barrier layers on the surface ofwood-based panels; and (3) there is little research on optimizing the doping position ofadsorbents in wood-based panels. This thesis conducted research for theseaforementioned problems, and the main academic contributions are as follows:Firstly, the VOC species and emittable content at different manufacturing stages ofwood-based panels such as urea-formaldehyde resin, wood chip, wood fiber after resinapplication, medium density fiberboard and phenol-formaldehyde resin are determined.It is observed that the formaldehyde emission from wood-based panels is dominated bythe emittable formaldehyde content in adhesives, whereas the other VOCs emitted fromwood-based panels mainly come from wood chips; the drying and hot-pressingtechniques during manufacturing process are helpful in reducing the VOC species andemittable content in wood-based panels; the correlation between emittableformaldehyde content in adhesives and formaldehyde emission factor from wood-basedpanels is obtained, which provides guidance on predicting and controlling formaldehydeemission rate from wood-based panels during their manufacturing process.Secondly, a novel method, dynamic/static chamber method (DSC method) isproposed to measure the diffusion and partition coefficients of VOC in barrier layers onthe surface of wood-based panels. The method is time-saving and has high accuracy.Moreover, a group of dimensionless correlations for characterizing the effect ofbarrier layers on VOC emissions from wood-based panels is induced. They offer a technical tool to select barrier layers for lowering VOC emission rate fromwood-based panels.Thirdly, a simple closed chamber method is developed to choose adsorbents withexcellent adsorption performance for formaldehyde. Combining the mass transfer modelfor VOC emission from multi-layered materials, an optimization model for determiningthe optimum doping position of adsorbents in wood-based panels is established, andmethod for solving the optimization model is proposed. It is proved that the optimumdoping mode is placing the overall adsorbents into the top layer of wood-based panels,which provides theoretical basis to control VOC emission from wood-based panels.Finally, based on above analysis, a design method for low-emitting wood-basedpanels is put forward and then laboratory samples are prepared. Experimental resultsshow that the formaldehyde emission rate from wood-based panels can be reduced by75%.更多还原