Predicting the microbial exposure risks in urban floods using GIS, building simulation, and microbial models

London is expected to experience more frequent periods of intense rainfall and tidal surges, leading to an increase in the risk of flooding. Damp and flooded dwellings can support microbial growth, including mould, bacteria, and protozoa, as well as persistence of flood-borne microorganisms. The amount of time flooded dwellings remain damp will depend on the duration and height of the flood, the contents of the flood water, the drying conditions, and the building construction, leading to particular properties and property types being prone to lingering damp and human pathogen growth or persistence. The impact of flooding on buildings can be simulated using Heat Air and Moisture (HAM) models of varying complexity in order to understand how water can be absorbed and dry out of the building structure. This paper describes the simulation of the drying of building archetypes representative of the English building stock using the EnergyPlus based tool ‘UCL-HAMT’ in order to determine the drying rates of different abandoned structures flooded to different heights and during different seasons. The results are mapped out using GIS in order to estimate the spatial risk across London in terms of comparative flood vulnerability, as well as for specific flood events. Areas of South and East London were found to be particularly vulnerable to long-term microbial exposure following major flood events

Simulation of pollution transport in buildings: the importance of taking into account dynamic thermal effects

The recent introduction of the Generic Contaminant Model in EnergyPlus allows for the integrated modelling of multizone contaminant and dynamic thermal behaviour within a single simulation package. This article demonstrates how dynamic thermal simulation can modify pollutant transport within a building. PM2.5 infiltration from the external to internal environment under dynamic thermal conditions is compared in CONTAM, EnergyPlus 8.0, and Polluto, an in-house pollutant transport model developed in EnergyPlus 3.1. The influence of internal temperature on indoor PM2.5 levels is investigated by comparing results from standard CONTAM simulations and dynamic thermal EnergyPlus 8 simulations. Circumstances where the predictions of such models can diverge are identified

The thermal characteristics of roofs: policy, installation and performance

This paper investigates the in-situ performance of UK cold pitched roof structures through a case study dwelling of typical construction using site survey, and estimation of U-values through simple calculation and from measured heat flow data. Significant increases of U-values resulted from under- and un-insulated areas due to installation issues, whilst a higher than expected estimated thermal resistance of the roof space and structure was also noted, potentially associated with heat gains. Both issues are expected to be observed more widely in the stock and contribute to a performance gap for roof insulation

How solid is our knowledge of solid walls? - Comparing energy savings through three different methods

Recent UK-based studies have shown a performance gap between the energy performance of buildings calculated using tabulated thermophysical properties of solid walls and that estimated from in-situ measurements. Solid-walled buildings have been targeted by UK Government policies and incentive schemes to meet climate change mitigation targets and improve the efficiency of the building stock, as they are less efficient and more expensive to treat than cavity walls. Since it is common practice to estimate energy use and potential savings for buildings retrofit assuming standard values from the literature, the performance gap may have serious implications on the decision-making and the cost-effectiveness of energy-saving interventions. The aim of this paper is to compare and contrast the results obtained from three different methods for estimating normalised dwelling energy demand: a) the UK energy performance certificate (EPC) method, which uses the standard assessment procedure (SAP) with tabulated inputs (the business as usual case); b) the SAP calculated using empirical air change rates from pressure tests and U-values estimated analysing monitored data with a Bayesian-based dynamic method developed by the authors; c) a normalised annual consumption (NAC) method based on empirical energy consumption data from smart meter and weather data. The analysis is performed on a sample of dwellings from the Energy Saving Trust “Solid Wall Field Trials” dataset. Results show that EPC estimates are systematically higher (between 7.5% and 22.0%) than SAP. Conversely, the NAC displayed a large range of relative differences (between -77% and +99%) compared to the EPC. This raises questions about the relative merits and purpose of the EPC and SAP bottom up methods compared to the smart-meter data-driven NAC method. Further research is suggested using SAP 2009 to isolate the thermal component of energy demand and compare it directly with the NAC component

Housing as a modifier of air contaminant and temperature exposure in Great Britain: A modelling framework

This paper presents the development of a modelling framework that quantifies the modifying effect of dwelling characteristics on exposure to indoor air pollution and excess temperature. A georeferenced domestic building stock model of Great Britain was created using national housing surveys, historical weather, and local terrain data. Dynamic building performance simulation was applied to estimate indoor air pollution and overheating risk metrics at the individual building level. These metrics were then aggregated at various geographic units and mapped across Britain within a Geographic Information System (GIS) environment to compare spatial trends. Results indicate that flats and newly built properties are characterised by lower indoor air pollution from outdoor sources, but higher air pollution from indoor sources. Flats, bungalows and newly built, more airtight dwellings are found to be more prone to overheating. Consequently, urban populations may experience higher levels of pollution from indoor sources and overheating resulting from the higher prevalence of flats in cities

Using building simulation to model the drying of flooded building archetypes

With a changing climate, London is expected to experience more frequent periods of intense rainfall and tidal surges, leading to an increase in the risk of flooding. This paper describes the simulation of the drying of flooded building archetypes representative of the London building stock using the EnergyPlus-based hygrothermal tool ‘University College London-Heat and Moisture Transfer (UCL-HAMT)’ in order to determine the relative drying rates of different built forms and envelope designs. Three different internal drying scenarios, representative of conditions where no professional remediation equipment is used, are simulated. A mould model is used to predict the duration of mould growth risk following a flood on the internal surfaces of the different building types. Heating properties while keeping windows open dried dwellings fastest, while purpose built flats and buildings with insulated cavity walls were found to dry slowest

‘Hitting the target and missing the point’: Analysis of air permeability data for new UK dwellings and what it reveals about the testing procedure

Airtightness testing is widely undertaken to assess the as-built performance of dwellings, in support of achieving energy and ventilation strategies. Mandatory schemes operate in some countries, such as the UK, to ensure that dwellings are built in accordance with their design air permeability. However, testing is only useful if the results give a true picture of the airtightness of the building. Previous literature has investigated factors which could influence airtightness test results but has not questioned data quality, despite the pressure on builders to achieve design targets. This paper presents air permeability results from the largest UK dataset, comprising 144,024 dwellings tested under the Air Tightness Testing and Measurement Association (ATTMA) scheme. The data show an unexpected distribution of test results with narrow peaks just within test targets. Such results were not expected theoretically but do reflect findings in other fields where performance-based targets are in place. Such a close match between design and tested airtightness may be achieved by remedial works taking place during the test rather than afterwards. Recommendations are made with respect to quality assurance systems, design guidance and on-site sealing practices to increase the likelihood of long-term airtight buildings being constructed first time

Indoor pm2.5 exposure in London's domestic stock: Modeling current and future exposures following energy efficient refurbishment

Simulations using CONTAM (a validated multi-zone indoor air quality (IAQ) model) are employed to predict indoor exposure to PM2.5 in London dwellings in both the present day housing stock and the same stock following energy efficient refurbishments to meet greenhouse gas emissions reduction targets for 2050. We modelled interventions that would contribute to the achievement of these targets by reducing the permeability of the dwellings to 3m3m-2hr-1 at 50 Pa, combined with the introduction of mechanical ventilation and heat recovery (MVHR) systems. It is assumed that the current mean outdoor PM2.5 concentration of 13?g.m-3 decreased to 9?g.m-3 by 2050 due to emission control policies. Our primary finding was that installation of (assumed perfectly functioning) MVHR systems with permeability reduction are associated with appreciable reductions in PM2.5 exposure in both smoking and non-smoking dwellings. Modelling of the future scenario for non-smoking dwellings show a reduction in annual average indoor exposure to PM2.5 of 18.8?g.m-3 (from 28.4 to 9.6?g.m-3) for a typical household member. Also of interest is that a larger reduction of 42.6?g.m-3 (from 60.5 to 17.9?g.m-3) was shown for members exposed primarily to cooking-related particle emissions in the kitchen (cooks). Reductions in envelope permeability without mechanical ventilation produced increases in indoor PM2.5 concentrations; 5.4?g.m-3 for typical household members and 9.8?g.m-3 for cooks. These estimates of changes in PM2.5 exposure are sensitive to assumptions about occupant behaviour, ventilation system usage and the distributions of input variables (±72% for non-smoking and ±107% in smoking residences). However, if realised, they would result in significant health benefits

Indoor PM2.5 exposure in London's domestic stock: Modelling current and future exposures following energy efficient refurbishment

Simulations using CONTAM (a validated multi-zone indoor air quality (IAQ) model) are employed to predict indoor exposure to PM2.5 in London dwellings in both the present day housing stock and the same stock following energy efficient refurbishments to meet greenhouse gas emissions reduction targets for 2050. We modelled interventions that would contribute to the achievement of these targets by reducing the permeability of the dwellings to 3 m3 m−2 h−1 at 50 Pa, combined with the introduction of mechanical ventilation and heat recovery (MVHR) systems. It is assumed that the current mean outdoor PM2.5 concentration of 13 μg m−3 decreased to 9 μg m−3 by 2050 due to emission control policies. Our primary finding was that installation of (assumed perfectly functioning) MVHR systems with permeability reduction are associated with appreciable reductions in PM2.5 exposure in both smoking and non-smoking dwellings. Modelling of the future scenario for non-smoking dwellings show a reduction in annual average indoor exposure to PM2.5 of 18.8 μg m−3 (from 28.4 to 9.6 μg m−3) for a typical household member. Also of interest is that a larger reduction of 42.6 μg m−3 (from 60.5 to 17.9 μg m−3) was shown for members exposed primarily to cooking-related particle emissions in the kitchen (cooks). Reductions in envelope permeability without mechanical ventilation produced increases in indoor PM2.5 concentrations; 5.4 μg m−3 for typical household members and 9.8 μg m−3 for cooks. These estimates of changes in PM2.5 exposure are sensitive to assumptions about occupant behaviour, ventilation system usage and the distributions of input variables (±72% for non-smoking and ±107% in smoking residences). However, if realised, they would result in significant health benefits

Mapping indoor overheating and air pollution risk modification across Great Britain: A modelling study

Housing has long been thought to play a significant role in population exposure to environmental hazards such as high temperatures and air pollution. However, there is sparse data describing how housing may modify heat and air pollution exposure such that housing's role in poor health and mortality from these hazards may be estimated. This paper describes the development of individual-address level indoor overheating and air pollution risk modifiers for Great Britain, for use alongside historical weather, outdoor air pollution, population socio-economic data, and mortality data in a large-scale epidemiological investigation. A geographically-referenced housing stock database was developed using the Homes Energy Efficiency Database (HEED) and the English Housing Survey (EHS). Simulations of unique combinations of building, fabric, occupation, and environment were run using a modelling framework developed for EnergyPlus 8.0, estimating indoor temperature metrics, indoor/outdoor ratio of pollution from outdoor sources, and indoor air pollution from multiple indoor sources. Results were compiled, matched back to individual properties in HEED, and mapped using Geographical Information Systems (GIS). Results indicate urban areas had higher numbers of buildings prone to overheating, reduced levels indoor air pollution from outdoor sources, and higher air pollution from indoor sources relative to rural areas, driven largely by variations in building types. The results provide the first national-scale quantitative estimate of heat and indoor air pollution modification by dwellings, aggregated at levels suitable for inclusion in health analysis