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A high-resolution indoor heat-health warning system for dwellings

机译：住宅高分辨率室内热健康警示系统

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摘要

Climate change projections indicate that the world's most populated regions will experience more frequent, intense and longer-lasting heatwave periods over the coming decades. Such events are likely to result in widespread overheating in the built environment, with a consequential increase in heat-related morbidity and mortality. In order to warn the population of such risks, Heat-Health Warning Systems (HHWSs) are being progressively adopted world-wide. Current HHWSs are, however, based solely on weather observations and forecasts and are unable to identify precisely where, when, or to what extent individual buildings (and their occupants) will be affected. In contrast, AutoRegressive models with eXogenous inputs (ARX) have been demonstrated to reliably forecast indoor temperatures in individual rooms using minimal data. Thus, the large-scale deployment of forecasting models could theoretically enable the development of a high-resolution indoor HHWS (iHHWS). In this study, ARX models were tested over the long-lasting UK heatwave of 2018 using hourly monitored dry-bulb temperature data from 25 rooms (12 living rooms and 13 bedrooms) in 12 dwellings, located within the London Urban Heat Island (UHI). The study investigates different approaches to improving the reliability of room-based heat exposure predictions at longer forecasting horizons. The effectiveness of the iHHWS system was assessed by evaluating the accuracy of predictions (using fixed and adaptive temperature thresholds) at different lead times (1, 3, 6, 12, 24, 48 and 72 h ahead). Compared to forecasted indoor temperatures, a Cumulative Heat Index (CHI) metric was shown to increase the reliability of heat-health warnings up to 24 h ahead.
机译：气候变化预测表明，世界上最具人口稠密的地区将在未来几十年中经历更频繁，强烈而更长的热浪时期。这种事件可能导致建筑环境中的广泛过热，其相应地增加了热相关的发病率和死亡率。为了警告这种风险的人口，全世界正在逐步采用热健康警告系统（HHWSS）。然而，目前的HHWSS仅基于天气观测和预测，并且无法正常，何时或在多大程度上识别各个建筑物（及其居住者）的影响。相比之下，具有外源投入（ARX）的自回归模型已被证明是使用最小数据的个别房间可靠地预测室内温度。因此，预测模型的大规模部署理论上可以实现高分辨率室内HHW（IHHWS）的开发。在这项研究中，ARX模型在2018年使用每小时监测的干灯泡温度数据（12位客房和13间卧室）在伦敦城市热岛（UHI）内的12间房间。该研究调查了改善基于房间的热曝光预测的可靠性的不同方法，在更长的预测视野中。通过评估不同铅时间（1,3,6,12,24,48和72小时）的预测（使用固定温度阈值）的预测（使用固定和自适应温度阈值）的准确性来评估IHHWS系统的有效性。与预测室内温度相比，显示了累积热指数（CHI）度量，以提高高达24小时的热健康警告的可靠性。

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  • 来源
    《Building and Environment》 |2020年第1期|106519.1-106519.12|共12页
  • 作者

    Gustin Matej; McLeod Robert S.; Lomas Kevin J.; Petrou Giorgos; Mavrogianni Anna;

  • 作者单位

    Loughborough Univ Sch Architecture Bldg & Civil Engn Loughborough LE11 3TU Leics England|Loughborough Univ UCL London Loughborough EPSRC Ctr Doctoral Training E Loughborough England;

    Loughborough Univ Sch Architecture Bldg & Civil Engn Loughborough LE11 3TU Leics England|Loughborough Univ UCL London Loughborough EPSRC Ctr Doctoral Training E Loughborough England;

    Loughborough Univ Sch Architecture Bldg & Civil Engn Loughborough LE11 3TU Leics England|Loughborough Univ UCL London Loughborough EPSRC Ctr Doctoral Training E Loughborough England;

    Loughborough Univ UCL Energy Inst Univ Coll London Loughborough WC1H 0NN Leics England|Loughborough Univ UCL London Loughborough EPSRC Ctr Doctoral Training E Loughborough England;

    Loughborough Univ UCL Energy Inst Univ Coll London Loughborough WC1H 0NN Leics England|Loughborough Univ UCL London Loughborough EPSRC Ctr Doctoral Training E Loughborough England;

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  • 正文语种 eng
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  • 关键词

    Heatwave; Overheating Indoor temperature; Time series forecasting; ARX model; Indoor heat health warning system (iHHWS);

    机译：热浪;室内温度过热;时间序列预测;ARX模型;室内热卫生警告系统（IHHWS）;

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