UCL Institute for Environmental Design and Engineering, Central House, 14 Upper Woburn Plc, London WC1H 0NN, UK.
UCL Institute for Environmental Design and Engineering, Central House, 14 Upper Woburn Plc, London WC1H 0NN, UK.
Sci Total Environ. 2019 Jun 1;667:390-399. doi: 10.1016/j.scitotenv.2019.02.341. Epub 2019 Feb 25.
Estimates of population air pollution exposure typically rely on the outdoor component only, and rarely account for populations spending the majority of their time indoors. Housing is an important modifier of air pollution exposure due to outdoor pollution infiltrating indoors, and the removal of indoor-sourced pollution through active or passive ventilation. Here, we describe the application of an indoor air pollution modelling tool to a spatially distributed housing stock model for England and Wales, developed from Energy Performance Certificate (EPC) data and containing information for approximately 11.5 million dwellings. First, we estimate indoor/outdoor (I/O) ratios and total indoor concentrations of outdoor air pollution for PM and NO for all EPC dwellings in London. The potential to estimate concentration from both indoor and outdoor sources is then demonstrated by modelling indoor background CO levels for England and Wales pre- and post-energy efficient adaptation, including heating, cooking, and smoking as internal sources. In London, we predict a median I/O ratio of 0.60 (99% CIs; 0.53-0.73) for outdoor PM and 0.41 (99%CIs; 0.34-0.59) for outdoor NO; Pearson correlation analysis indicates a greater spatial modification of PM exposure by housing (ρ = 0.81) than NO (ρ = 0.88). For the demonstrative CO model, concentrations ranged from 0.4-9.9 ppm (99%CIs)(median = 3.0 ppm) in kitchens and 0.3-25.6 ppm (median = 6.4 ppm) in living rooms. Clusters of elevated indoor concentration are found in urban areas due to higher outdoor concentrations and smaller dwellings with reduced ventilation potential, with an estimated 17.6% increase in the number of living rooms and 63% increase in the number of kitchens exceeding recommended exposure levels following retrofit without additional ventilation. The model has the potential to rapidly calculate indoor pollution exposure across large housing stocks and estimate changes to exposure under different pollution or housing policy scenarios.
对人口空气污染暴露的估计通常仅依赖于室外成分，很少考虑到大多数时间在室内度过的人群。由于室外污染渗透到室内，以及通过主动或被动通风去除室内源污染，住房是空气污染暴露的一个重要调节因素。在这里，我们描述了一种室内空气污染建模工具在英格兰和威尔士的空间分布住房存量模型中的应用，该模型是从能源绩效证书 (EPC) 数据开发而来，包含了大约 1150 万套住宅的信息。首先，我们估计了伦敦所有 EPC 住宅的 PM 和 NO 的室内/室外 (I/O) 比值和室外空气污染的总室内浓度。然后，通过模拟英格兰和威尔士在能源效率适应（包括供暖、烹饪和吸烟等内部源）前后室内背景 CO 水平，展示了从室内和室外源估计浓度的潜力。在伦敦，我们预测室外 PM 的 I/O 比值中位数为 0.60（99%置信区间；0.53-0.73），室外 NO 的 I/O 比值中位数为 0.41（99%置信区间；0.34-0.59）；Pearson 相关分析表明，住房对 PM 暴露的空间修饰作用大于 NO（ρ=0.81，ρ=0.88）。对于示范 CO 模型，浓度范围从厨房的 0.4-9.9ppm（99%置信区间）（中位数=3.0ppm）到客厅的 0.3-25.6ppm（中位数=6.4ppm）。由于室外浓度较高且通风潜力较小的住宅较小，城市地区存在室内浓度升高的集群，在没有额外通风的情况下进行 retrofit 后，预计有 17.6%的客厅和 63%的厨房数量超过推荐暴露水平，从而导致室内暴露的数量增加。该模型有可能快速计算大型住房存量的室内污染暴露情况，并估计在不同的污染或住房政策情况下暴露情况的变化。
