• Energy Research

Climate change means the UK will experience warmer winters and hotter summers in the future. Concurrent energy efficiency improvements to housing may modify indoor exposures to heat or cold, while population aging may increase susceptibility to temperature-related mortality. We estimate heat and cold mortality and energy consumption in London for typical (non-extreme) future climates, given projected changes in population and housing. Building physics models are used to simulate summertime and wintertime indoor temperatures and space heating energy consumption of London dwellings for 'baseline' (2005-2014) and future (2030s, 2050s) periods using data from the English Housing Survey, historical weather data, and projected future weather data with temperatures representative of 'typical' years. Linking to population projections, we calculate future heat and cold attributable mortality and energy consumption with demolition, construction, and alternative scenarios of energy efficiency retrofit. At current retrofit rates, around 168-174 annual cold-related deaths per million population would typically be avoided by the 2050s, or 261-269 deaths per million under ambitious retrofit rates. Annual heat deaths would typically increase by 1 per million per year under the current retrofit rate, and 12-13 per million under ambitious rates without population adaptation to heat. During typical future summers, an estimated 38-73% of heat-related deaths can be avoided using external shutters on windows, with their effectiveness lower during hotter weather. Despite warmer winters, ambitious retrofit rates are necessary to reduce typical annual energy consumption for heating below baseline levels, assuming no improvement in heating system efficiencies. Concerns over future overheating in energy efficient housing are valid but increases in heat attributable mortality during typical and hot (but not extreme) summers are more than offset by significant reductions in cold mortality and easily mitigated using passive measures. More ambitious retrofit rates are critical to reduce energy consumption and offer co-benefits for reducing cold-related mortality.

AbstractThe UK has introduced legislation that requires net-zero greenhouse gas emissions to be achieved by 2050. Improving the energy efficiency of homes is a key objective to help reach this target, and the UK government’s Clean Growth Strategy aims to get many homes up to an Energy Performance Certificate (EPC) Band of C by 2035. The relationship between home energy-efficiency and occupant health and wellbeing remains an area of ongoing research. This paper explores the nexus between home energy efficiency, energy consumption and self-reported health—an indicator of the general health and wellbeing of the population. We focus on Greater London through secondary data analysis. Energy-efficiency ratings and air infiltration rates of dwellings, derived from EPCs, were aggregated and matched to local area self-reported health and energy consumption data obtained from the Greater London Authority’s (GLA) Lower Layer Super Output Area (LSOA) Atlas database. Our regression model indicates that improving the energy efficiency (SAP) rating by 10 points for a typical home may reduce household gas consumption by around 7% (95% CIs: 2%, 14%). Beta regression finds a positive, but not statistically significant association between median SAP rating and the proportion of the population reporting ‘good or very good’ health when considering all Greater London LSOAs (z score = 0.60, p value = 0.55). A statistically significant positive association is observed however when repeating the analysis for the lowest income quartile LSOAs (z score = 2.03, p value = 0.04). This indicates that the least well-off may benefit most from home energy efficiency programs. A statistically significant positive association is also observed for the relationship between self-reported health and air infiltration rates (z score = 2.62, p value = 0.01). The findings support existing evidence for the predominantly naturally ventilated UK housing stock, suggesting that home energy efficiency measures provide a co-benefit for occupant health provided that adequate air exchange is maintained.

Abstract Historical dwellings make up a significant fraction of the French building stock and require substantial retrofitting to reduce their energy consumption and improve their thermal comfort. In the city center of Cahors, France, the old medieval dwellings are considered as valuable cultural heritage and internal insulation is often the only insulation technique that can be used when the architectural value of the exterior facade is to be preserved. However, internal insulation may have an impact upon the hygrothermal performance of the wall, leading to lowered drying capacity, with possible interstitial condensation and mold growth. Hygrothermal models may be used to assess the risk of failure, but the accuracy of the results depends on how reliable the input data is, including external boundary conditions, which may vary significantly in dense medieval cities such as Cahors. In this study, a Geographical Information System model of Cahors is used to develop EnergyPlus models of individual dwellings. The boundary conditions output by these models are, in turn, used to model the hygrothermal performance of facades with different internal insulations, using the hygrothermal tool Delphin. The Delphin outputs are then analyzed with the VTT model, a mold growth assessment model. Results highlight a quantitative correlation between some urban morphology characteristics and the hygrothermal performance of refurbished walls, with some configurations raising the risk of damage patterns. We find that bio-based insulation presents a better hygrothermal performance than mineral wool in most of the configurations.

The Lancet Countdown is an international collaboration that independently monitors the health consequences of a changing climate. Publishing updated, new, and improved indicators each year, the Lancet Countdown represents the consensus of leading researchers from 43 academic institutions and UN agencies. The 44 indicators of this report expose an unabated rise in the health impacts of climate change and the current health consequences of the delayed and inconsistent response of countries around the globe—providing a clear imperative for accelerated action that puts the health of people and planet above all else.\ud \ud The 2021 report coincides with the UN Framework Convention on Climate Change 26th Conference of the Parties (COP26), at which countries are facing pressure to realise the ambition of the Paris Agreement to keep the global average temperature rise to 1·5°C and to mobilise the financial resources required for all countries to have an effective climate response. These negotiations unfold in the context of the COVID-19 pandemic—a global health crisis that has claimed millions of lives, affected livelihoods and communities around the globe, and exposed deep fissures and inequities in the world's capacity to cope with, and respond to, health emergencies. Yet, in its response to both crises, the world is faced with an unprecedented opportunity to ensure a healthy future for all.

Management of the natural and built environments can help reduce the health impacts of climate change. This is particularly relevant in large cities where urban heat island makes cities warmer than the surrounding areas. We investigate how urban vegetation, housing characteristics and socio-economic factors modify the association between heat exposure and mortality in a large urban area.We linked 185,397 death records from the Greater London area during May-Sept 2007-2016 to a high resolution daily temperature dataset. We then applied conditional logistic regression within a case-crossover design to estimate the odds of death from heat exposure by individual (age, sex) and local area factors: land-use type, natural environment (vegetation index, tree cover, domestic garden), built environment (indoor temperature, housing type, lone occupancy) and socio-economic factors (deprivation, English language, level of employment and prevalence of ill-health).Temperatures were higher in neighbourhoods with lower levels of urban vegetation and with higher levels of income deprivation, social-rented housing, and non-native English speakers. Heat-related mortality increased with temperature increase (Odds Ratio (OR), 95% CI = 1.039, 1.036-1.043 per 1 °C temperature increase). Vegetation cover showed the greatest modification effect, for example the odds of heat-related mortality in quartiles with the highest and lowest tree cover were OR, 95%CI 1.033, 1.026-1.039 and 1.043, 1.037-1.050 respectively. None of the socio-economic variables were a significant modifier of heat-related mortality.We demonstrate that urban vegetation can modify the mortality risk associated with heat exposure. These findings make an important contribution towards informing city-level climate change adaptation and mitigation policies.

With a changing climate and increased urbanisation, the occurrence and the impact of flooding is expected to increase significantly. Floods can bring pathogens into homes and cause lingering damp and microbial growth in buildings, with the level of growth and persistence dependent on the volume and chemical and biological content of the flood water, the properties of the contaminating microbes, and the surrounding environmental conditions, including the restoration time and methods, the heat and moisture transport properties of the envelope design, and the ability of the construction material to sustain the microbial growth. The public health risk will depend on the interaction of these complex processes and the vulnerability and susceptibility of occupants in the affected areas. After the 2007 floods in the UK, the Pitt review noted that there is lack of relevant scientific evidence and consistency with regard to the management and treatment of flooded homes, which not only put the local population at risk but also caused unnecessary delays in the restoration effort. Understanding the drying behaviour of flooded buildings in the UK building stock under different scenarios, and the ability of microbial contaminants to grow, persist, and produce toxins within these buildings can help inform recovery efforts. To contribute to future flood management, this paper proposes the use of building simulations and biological models to predict the risk of microbial contamination in typical UK buildings. We review the state of the art with regard to biological contamination following flooding, relevant building simulation, simulation-linked microbial modelling, and current practical considerations in flood remediation. Using the city of London as an example, a methodology is proposed that uses GIS as a platform to integrate drying models and microbial risk models with the local building stock and flood models. The integrated tool will help local governments, health authorities, insurance companies and residents to better understand, prepare for and manage a large-scale flood in urban environments.

Abstract Covid-19 has caused great challenges to the energy sector, particularly in residential buildings with low-income households. This study investigates the impact of the confinement measures due to the Covid-19 outbreak on the energy demand of seven residential archetype buildings in Greater London. Three levels of confinement for occupant schedules are proposed and compared with the base case before Covid-19. The archetypes, their boundary conditions, and input parameters are set up according to statistics from English Housing Survey (EHS) sample data for low-income housing. The base case scenario (normal life without confinement measures) is validated against the measured data energy consumption from the National Energy Efficiency Data-Framework (NEED) statistics. The results show that electricity consumption is significantly lower than that for heating and hot water for all the archetypes. By comparing the base case scenario with the full Covid-19 lockdown scenario, the results indicate that heating and hot water consumption (kWh) for all the residential archetypes increases, on average, by 10%, and total electricity demand (kWh) increases by 13%. The study highlights the importance of introducing detailed occupancy profiles in multi-zone building energy simulation models during a pandemic that leads to a greater shift towards home working, which may increase the risk of fuel poverty in low-income housing.