UK Abstract Mould growth and damp in homes can have serious adverse effects on the health of occupants. Such risks may be greatest in certain dwellings, particularly those with poor energy efficiency and ventilation, and certain locations may have greater proportions of at-risk dwellings, meaning greater risks for the resident population and a potential spatial variation in mould exposure across the country. This abstract describes the application of a building physics metamodel to around 11 million dwellings across England and Wales to estimate indoor moisture levels and mould growth risk at individual address-level. This metamodel is derived from dynamic thermal simulations of indoor temperatures, relative humidity, and surface moisture levels, predicting the mould severity index (MSI) according to building characteristics given indoor sources of moisture. We estimate a mould prevalence of 10.4% across the stock, with the greatest risks in urban areas such as London. Retrofitting does not adequately mitigate this risk without ventilation improvements, while fuel subsidies can reduce risks but with obvious energy
{"title":"Estimating spatial variation of moisture risks in English and Welsh dwellings","authors":"Jonathon Taylor, P. Symonds","doi":"10.14293/ICMB210061","DOIUrl":"https://doi.org/10.14293/ICMB210061","url":null,"abstract":"UK Abstract Mould growth and damp in homes can have serious adverse effects on the health of occupants. Such risks may be greatest in certain dwellings, particularly those with poor energy efficiency and ventilation, and certain locations may have greater proportions of at-risk dwellings, meaning greater risks for the resident population and a potential spatial variation in mould exposure across the country. This abstract describes the application of a building physics metamodel to around 11 million dwellings across England and Wales to estimate indoor moisture levels and mould growth risk at individual address-level. This metamodel is derived from dynamic thermal simulations of indoor temperatures, relative humidity, and surface moisture levels, predicting the mould severity index (MSI) according to building characteristics given indoor sources of moisture. We estimate a mould prevalence of 10.4% across the stock, with the greatest risks in urban areas such as London. Retrofitting does not adequately mitigate this risk without ventilation improvements, while fuel subsidies can reduce risks but with obvious energy","PeriodicalId":328421,"journal":{"name":"Estimating spatial variation of moisture risks in English and Welsh dwellings","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127859873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：