Impacts of a changed atmosphere: Do increased CO₂ levels decrease human cognitive performance?

Introduction. Climate change has severe consequences for humans, such as health impacts resulting from the burning of fossil fuels, i.e. pollution, and impacts from a changing climate, such as extreme heat and flooding. There is a third, neglected, category that covers impacts from the changed atmosphere per se, i.e. a higher concentration of CO2. Do increased atmospheric CO2 levels influence human cognition negatively? Method. We carried out a rapid evidence assessment. Identified keywords were searched for in title, abstract, and keywords in Scopus and Web of Science. Results were imported into the systematic review software EPPI-Reviewer, and screened according to prespecified criteria. Results Five journal articles were retained after screening. The level of reported details did not allow a meta-analysis; instead, results were descriptively interpreted. All studies took place in environmental chambers in which pure CO2 was inserted to reach levels between 500 ppm and 5000 ppm. Two studies did not find any effect of CO2 on performance, but three studies found that cognitive performance decreased under higher CO2 concentrations. Conclusions. The outcome that human performance might decrease under higher CO2 is already in itself alarming but would have wide-reaching implications on energy use, e.g. of heating and ventilation systems

How should energy researchers respond to the climate emergency?

Globally, individuals, organisations and nations have declared a climate emergency, “a situation that poses an immediate risk to health, life, property, or environment”. Despite this, there has been no noticeable step change in the way that energy research to help tackle climate change is being organised and conducted. How can and should we be changing what we do to face up to this emergency? How should energy researchers who want to tackle (mitigate) climate change respond to this emergency? These are the questions we discuss in this working paper

Behavioural Change as a Domestic Heat Pump Performance Driver: Insights on the Influence of Feedback Systems from Multiple Case Studies in the UK

Heat pumps (HPs) are seen as an increasingly important technology able to contribute significantly towards the decarbonisation of the domestic stock in the UK. However, there appears to be a performance gap between predicted and real-life HP performance, with several studies highlighting the need to include the HP’s interaction with users when examining their performance. This study examines the role of user behaviour in mitigating this performance gap from a systems perspective. A sample of 21 case studies was selected from 700 domestic HPs monitored across the UK via the government’s Renewable Heat Premium Payment Scheme for the collection of qualitative and quantitative socio-technical data. The application of systems thinking facilitated the identification of the underlying interactions between the HP system and its users. The systems analysis revealed that HP performance relies on complex socio-technical system interactions, including behavioural patterns, and that enabling feedback information processes can have a significant impact on user behaviour. The study enabled a deeper perspective on performance influencers relating to behavioural patterns and achieved new insights into the requirements for well-performing HPs. These findings have important implications for policy makers, installers and manufacturers of HP systems and their users

The impact of personal, housing, and neighbourhood factors on personal wellbeing

This study assesses how subjective wellbeing is related to housing and neighbourhood characteristics, controlling for personal variables. The secondary data analysis was based on the English Housing Survey, 2017: Housing Stock Data and the English Housing Survey: Fuel Poverty Dataset, 2017, collected in the period April 2016 to March 2018 (N= 9205). Subjective wellbeing was measured with four variables-life satisfaction, the perception of things being worthwhile in life, feeling happy and feeling anxious-that were dichotomized into low and high wellbeing. Logistic regression analysis showed that personal variables are most strongly related to wellbeing but that both housing and neighbourhood variables are also significantly related to it. Finding it difficult to keep the living room warm, being in fuel poverty, and finding it difficult to meet heating costs were associated with lower wellbeing. Low area satisfaction and not feeling safe were also significantly associated with lower wellbeing. The effects of variables are not constant across all four wellbeing measures used which raises the question ‘which wellbeing’should be addressed

Moisture Performance Criteria for UK Dwellings

The new ventilation regulations in England and Wales have introduced performance criteria for the control of mould. The UK Government\'s Building Regulations Research Programme has funded University College London (UCL) to investigate the extent to which these are the most appropriate criteria for thecontrol of mould in UK dwellings. This paper reports on the plans for this study which involve both field and laboratory related work. Some initial early work has already been undertaken and the paper summarises the progress to date. This initial work is based on analysis of data from a national study of England\'s Home Energy Efficiency scheme (Warm Front). Surveys were undertaken of dwellings and households participating in the scheme in five urban areas. Half-hourly living room and main bedroom temperatures and relative humidity measurements were recorded for two to four weeks (in the heating season) in approximately 1600 dwellings. This data is being analysed to investigate the typical relativehumidities that exist in UK dwellings and also any relationship that exists between these levels and the mould growth that was recorded

Comparison of indoor temperatures of homes with recommended temperatures and effects of disability and age: an observational, cross-sectional study.

OBJECTIVES: We examine if temperatures in winter in English homes meet the recommendation of being at least 18°C at all times. We analyse how many days meet this criterion and calculate the hours per day and night being at/above 18°C. These metrics are compared between households with occupants aged above 64 years or having a long-term disability (LTD) and those younger and without disability. DESIGN: Cross-sectional, observational. SETTING: England. PARTICIPANTS: 635 households. OUTCOMES MEASURES: (1) Mean temperatures, (2) proportion of days of the measurement period meeting the criterion, (3) average hours at/above 18°C, (4) average hours at night at/above 18°C. RESULTS: Mean winter temperatures in the bedroom were MBR=18.15°C (SD=2.51), the living room MLR=18.90°C (SD=2.46) and the hallway MHall=18.25°C (SD=2.57).The median number of days meeting the criterion was 19-31%. For the living room, more days meet the criterion in the group with a LTD (Mdisability=342 vs Mno_disability=301, 95% CI 8 to 74), and with someone over 64 years present (Mabove64=341, Mbelow65=301 95%, CI 8 to 74).The median number of hours/day meeting the criterion was 13-17. In the living room, households with a disability had more hours at 18°C (Mdisability=364, Mno_disability=297, 95% CI 17 to 83) as did the older age group (Mabove64=347, Mbelow65=296, 95% CI 18 to 84). In the hallway, more hours met the criterion in households with a disability (Mdisability=338, Mno_disability=302, 95% CI 3 to 70).247 homes had at least nine hours of at least 18°C at night; no effect of age or disability. CONCLUSIONS: Many households are at risk of negative health outcomes because of temperatures below recommendations

Smart Energy Research Lab: Energy use in GB domestic buildings 2021

Variation in annual, seasonal, and diurnal gas and electricity use with weather, building and occupant characteristics

The SERL Observatory Dataset: Longitudinal Smart Meter Electricity and Gas Data, Survey, EPC and Climate Data for over 13,000 Households in Great Britain

The Smart Energy Research Lab (SERL) Observatory dataset described here comprises half-hourly and daily electricity and gas data, SERL survey data, Energy Performance Certificate (EPC) input data and 24 local hourly climate reanalysis variables from the European Centre for Medium-Range Weather Forecasts (ECMWF) for over 13,000 households in Great Britain (GB). Participants were recruited in September 2019, September 2020 and January 2021 and their smart meter data are collected from up to one year prior to sign up. Data collection will continue until at least August 2022, and longer if funding allows. Survey data relating to the dwelling, appliances, household demographics and attitudes was collected at sign up. Data are linked at the household level and UK-based academic researchers can apply for access within a secure virtual environment for research projects in the public interest. This is a data descriptor paper describing how the data was collected, the variables available and the representativeness of the sample compared to national estimates. It is intended as a guide for researchers working with or considering using the SERL Observatory dataset, or simply looking to learn more about it

Ventilation rates and moisture-related allergens in UK dwellings

Recent studies show that the UK is one of the countries with the highest asthma prevalence worldwide. It has been suggested that the trend towards the reduction of domestic ventilation rates for energy-efficiency reasons has resulted in poor indoor air quality and may represent a causal factor for the high asthma prevalence in the UK. This study firstly aims to assess whether a link exists between asthma and low ventilation rates in housing. Secondly, the study aims to establish the minimum ventilation rate required in a dwelling in order to control levels of moisture-related pollutants (dust mites, mould) and therefore reduce the number of respiratory hazards. The work was funded by the UK Government's Building Regulations Research Programme. An extensive review was performed of the UK and overseas published information on the links between asthma and domestic ventilation rates. The study also included an analysis of existing UK data sets where respiratory health, mould growth and housing characteristics were surveyed. In addition, the study involved theoretical modeling of a typical UK dwelling, to predict the impact that changes in ventilation rates will have on house dust mite (HDM) in a bed and on mould growth. The literature review has highlighted that most existing data is inadequate for conclusions to be drawn regarding the direct association between ventilation rates and respiratory problems. For moisture-related pollutants the literature offers some advice on the minimum ventilation rates required to reduce pollutants levels. The analysis of existing UK data sets has not revealed any significant direct links between ventilation, respiratory health and moisture-related pollutants. The results of the theoretical modeling indicate that in most cases 0.5 ach-1 is required to avoid mould growth but a significantly higher ventilation rate (0.8 ach-1) may be required to control mites’ growth. Most current guidance on domestic ventilation is based on the assumption that if adequate ventilation is provided for avoiding mould growth, then other IAQ problems will be contained. This study indicates that this may not be the case. In order to fully evaluate the direct link between asthma and low ventilation rates in the UK, a large scale prospective study is needed, where indoor pollutants, respiratory health indicators, air- tightness and ventilation rates are all adequately measured

The impact of COVID-19 on household energy consumption in England and Wales from April 2020 to March 2022

The COVID-19 pandemic changed the way people lived, worked, and studied around the world, with direct consequences for domestic energy use. This study assesses the impact of COVID-19 lockdowns in the first two years of the pandemic on household electricity and gas use in England and Wales. Using data for 508 (electricity) and 326 (gas) homes, elastic net regression, neural network and extreme gradient boosting predictive models were trained and tested on pre-pandemic data. The most accurate model for each household was used to create counterfactuals (predictions in the absence of COVID-19) against which observed pandemic energy use was compared. Median monthly model error (CV(RMSE)) was 3.86% (electricity) and 3.19% (gas) and bias (NMBE) was 0.21% (electricity) and −0.10% (gas). Our analysis showed that on average (electricity; gas) consumption increased by (7.8%; 5.7%) in year 1 of the pandemic and by (2.2%; 0.2%) in year 2. The greatest increases were in the winter lockdown (January – March 2021) by 11.6% and 9.0% for electricity and gas, respectively. At the start of 2022 electricity use remained 2.0% higher while gas use was around 1.9% lower than predicted. Households with children showed the greatest increase in electricity consumption during lockdowns, followed by those with adults in work. Wealthier households increased their electricity consumption by more than the less wealthy and continued to use more than predicted throughout the two-year period while the less wealthy returned to pre-pandemic or lower consumption from summer 2021. Low dwelling efficiency was associated with a greater increase in energy consumption during the pandemic. Additionally, this study shows the value of different machine learning techniques for counterfactual modelling at the individual-dwelling level, and our approach can be used to robustly estimate the impact of other events and interventions