Health effects of home energy efficiency interventions in England: a modelling study

Abstract

ObjectiveTo assess potential public health impacts of changes to indoor air quality and temperature due to energy efficiency retrofits in English dwellings to meet 2030 carbon reduction targets.DesignHealth impact modelling study.SettingEngland.ParticipantsEnglish household population.InterventionThree retrofit scenarios were modelled: (1) fabric and ventilation retrofits installed assuming building regulations are met; (2) as with scenario (1) but with additional ventilation for homes at risk of poor ventilation; (3) as with scenario (1) but with no additional ventilation to illustrate the potential risk of weak regulations and non-compliance.Main outcomePrimary outcomes were changes in quality adjusted life years (QALYs) over 50 years from cardiorespiratory diseases, lung cancer, asthma and common mental disorders due to changes in indoor air pollutants, including secondhand tobacco smoke, PM2.5 from indoor and outdoor sources, radon, mould, and indoor winter temperatures.ResultsThe modelling study estimates showed that scenario (1) resulted in positive effects on net mortality and morbidity of 2241 (95% credible intervals (CI) 2085 to 2397) QALYs per 10 000 persons over 50 years follow-up due to improved temperatures and reduced exposure to indoor pollutants, despite an increase in exposure to outdoor-generated particulate matter with a diameter of 2.5 μm or less (PM2.5). Scenario (2) resulted in a negative impact of −728 (95% CI −864 to −592) QALYs per 10 000 persons over 50 years due to an overall increase in indoor pollutant exposures. Scenario (3) resulted in −539 (95% CI −678 to -399) QALYs per 10 000 persons over 50 years follow-up due to an increase in indoor exposures despite the targeting of pollutants.ConclusionsIf properly implemented alongside ventilation, energy efficiency retrofits in housing can improve health by reducing exposure to cold and air pollutants. Maximising the health benefits requires careful understanding of the balance of changes in pollutant exposures, highlighting the importance of ventilation to mitigate the risk of poor indoor air quality.

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

“…Chen et al (2012) demonstrated a correlation between estimated exposure to indoor PM 10 from outdoor sources in different US cities based on typical infiltration rates in local building stocks [43]. The population-wide health consequences arising from changes in indoor air quality following energy efficient adaptation in the English housing stock has been estimated by Hamilton et al [39] using a nationally-representative housing stock model. Spatial variation in mortality risks from high indoor temperatures have been examined across London, accounting for population age, Urban Heat Island (UHI) impacts, with building physics models estimating indoor temperatures for individual dwellings [44]; results indicate that housing may be an important contributor to heat exposure.…”

“…Dimitroulopoulou et al modelled NO 2 , CO, PM 10 and PM 2.5 from both indoor and outdoor sources [37], demonstrating how low ventilation rates may increase exposure and the high relative importance of indoor sources. Indoor air quality modelling has been performed across sets of London [38] and English housing archetypes [39], showing how flats may have higher levels of pollution from indoor sources and lower levels from outdoor sources, relative to houses. Models of energy-efficient changes to the building fabric indicate reductions in permeability lead to an increase in indoor air pollution and decrease in outdoor air pollution in the indoor environment [38,40].…”

Estimating the Influence of Housing Energy Efficiency and Overheating Adaptations on Heat-Related Mortality in the West Midlands, UK

“…The reduction in fabric U-value is based on the UK Government's Standard Assessment Procedure (SAP) for Energy Rating of Dwellings, with the lowest possible U-value for the fabric component selected based on the fabric type and dwelling age [35]. The change in permeability is estimated based on the work by a Hong et al [36] or b UK SAP, following the methods described by Hamilton et al [37].…”

Participatory system dynamics modelling for housing, energy and wellbeing interactions

“…increased thermal comfort and fuel poverty alleviation. Positive effects on occupants' physical and mental health have been investigated in several studies, based on self-reported health measurements (Gilbertson, Grimsley, Green, & Group, 2012;Gilbertson, Stevens, Stiell, & Thorogood, 2006), modelling studies (Hamilton et al, 2015;Wilkinson et al, 2009), or meta-analysis (Maidment, Jones, Webb, Hathway, & Gilbertson, 2014). However, if not implemented correctly, energy-efficiency interventions may result in negative unintended consequences, such as reduced indoor air quality, increased fuel poverty or a failure of the primary aim of the policy (Davies & Oreszczyn, 2012).…”