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This is a set of aggregated data tables that underly the key figures in the SERL stats report "Smart Energy Research Lab: Energy use in GB domestic buildings 2021" (Volume 1). The report describes domestic gas and electricity energy use in Great Britain in 2021 based on data from the Smart Energy Research Lab (SERL) Observatory, which consists of smart meter and contextual data from approximately 13,000 homes that are broadly representative of the GB population in terms of region and Index of Multiple Deprivation (IMD) quintile. The report shows how residential energy use in GB varies over time (monthly over the year and half-hourly over the course of the day), with occupant characteristics (number of occupants, tenure), property characteristics (age, size, form, and Energy Performance Certificate (EPC)), by type of heating system, presence of solar panels and of electric vehicles, and by weather, region and IMD quintile.

The decarbonisation of heating in the United Kingdom is likely to entail both the mass adoption of heat pumps and widespread development of district heating infrastructure. Estimation of the spatially disaggregated heat demand is needed for both electrical distribution network with electrified heating and for the development of district heating. The temporal variation of heat demand is important when considering the operation of district heating, thermal energy storage and electrical grid storage. The difference between the national and urban heat demands profiles will vary due to the type and occupancy of buildings leading to temporal variations which have not been widely surveyed. This paper develops a high-resolution spatiotemporal heat load model for Great Britain (GB: England, Scotland a Wales) by identifying the appropriate datasets, archetype segmentation and characterisation for the domestic and nondomestic building stock. This is applied to a thermal model and calibrated on the local scale using gas consumption statistics. The annual GB heat demand was in close agreement with other estimates and the peak demand was 219 GWth. The urban heat demand was found to have a lower peak to trough ratio than the average national demand profile. This will have important implications for the uptake of heating technologies and design of district heating.

Risk management is an effective way to mitigate the adverse consequences of extreme events, and plays an important role in climate change adaptation. On the basis of the literature, this paper presents a conceptual framework for managing the risk of extreme events under climate change, and accordingly summarizes the recent developments with a focus on several key topics. In terms of risk determinants, the impacts of climate variability on the frequency of extreme events are addressed, and the various meanings and measurements of specific vulnerability are compared. As for the process of risk management, the dynamic assessment approach regarding future climate condition is emphasized. Besides, in view of decision making the available means to enhance the effectiveness of adaptation and mitigation strategies are highlighted. Finally, uncertainty is discussed with respect to its sources and solution.

China is confronted with an unprecedented water crisis regarding its quantity and quality. In this study, we quantified the dynamics of China?s embodied water use and chemical oxygen demand (COD) discharge from 2010 to 2015. The analysis was conducted with the latest available water use data across sectors in primary, secondary and tertiary industries and input?output models. The results showed that (1) China?s water crisis was alleviated under urbanisation. Urban consumption occupied the largest percentages (over 30%) of embodied water use and COD discharge, but embodied water intensities in urban consumption were far lower than those in rural consumption. (2) The ?new normal? phase witnessed the optimisation of China?s water use structures. Embodied water use in light-manufacturing and tertiary sectors increased while those in heavy-manufacturing sectors (except chemicals and transport equipment) dropped. (3) Transformation of China?s international market brought positive effects on its domestic water use. China?s water use (116?80 billion tonnes (Bts))(9) and COD discharge (3.95?2.22 million tonnes (Mts)) embodied in export tremendously decreased while its total export values (11?25 trillion CNY) soared. Furthermore, embodied water use and COD discharge in relatively low-end sectors, such as textile, started to transfer from international to domestic markets when a part of China?s production activities had been relocated to other developing countries.

Decarbonisation of energy systems requires deep structural change. The purpose of this research was to analyse the rates of change taking place in the energy systems of each Member State of the European Union (EU), and the EU in aggregate, in the light of the EU's climate change mitigation objectives. Trends on indicators such as sectoral activity levels and composition, energy intensity, and carbon intensity of energy were compared with decadal benchmarks derived from deep decarbonisation scenarios. The methodology applied provides a useful and informative approach to tracking decarbonisation of energy systems. The results show that while the EU has made significant progress in decarbonising its energy system. On a number of indicators assessed the results show that a significant acceleration from historical levels is required in order to reach the rates of change seen on the future benchmarks for deep decarbonisation. The methodology applied provides an example of how the research community and international organisations could complement the transparency mechanism developed by the Paris Agreement on climate change, to improve understanding of progress toward low-carbon energy systems.

Climate change threatens to undermine the past 50 years of gains in public health. In response, the National Health Service (NHS) in England has been working since 2008 to quantify and reduce its carbon footprint. This Article presents the latest update to its greenhouse gas accounting, identifying interventions for mitigation efforts and describing an approach applicable to other health systems across the world.A hybrid model was used to quantify emissions within Scopes 1, 2, and 3 of the Greenhouse Gas Protocol, as well as patient and visitor travel emissions, from 1990 to 2019. This approach complements the broad coverage of top-down economic modelling with the high accuracy of bottom-up data wherever available. Available data were backcasted or forecasted to cover all years. To enable the identification of measures to reduce carbon emissions, results were disaggregated by organisation type.In 2019, the health service's emissions totalled 25 megatonnes of carbon dioxide equivalent, a reduction of 26% since 1990, and a decrease of 64% in the emissions per inpatient finished admission episode. Of the 2019 footprint, 62% came from the supply chain, 24% from the direct delivery of care, 10% from staff commute and patient and visitor travel, and 4% from private health and care services commissioned by the NHS.This work represents the longest and most comprehensive accounting of national health-care emissions globally, and underscores the importance of incorporating bottom-up data to improve the accuracy of top-down modelling and enabling detailed monitoring of progress as health systems act to reduce emissions.Wellcome Trust.

AbstractThe UK government heat strategy is partially based on decarbonisation pathways from the UK MARKAL energy system model. We review how heat provision is represented in UK MARKAL, identifying a number of shortcomings and areas for improvement. We present a completely revised model with improved estimations of future heat demands and a consistent representation of all heat generation technologies. This model represents all heat delivery infrastructure for the first time and uses dynamic growth constraints to improve the modelling of transitions according to innovation theory. Our revised model incorporates a simplified housing stock model, which is used produce highly-refined decarbonisation pathways for residential heat provision. We compare this disaggregated model against an aggregated equivalent, which is similar to the existing approach in UK MARKAL. Disaggregating does not greatly change the total residential fuel consumption in two scenarios, so the benefits of disaggregation will likely be limited if the focus of a study is elsewhere. Yet for studies of residential heat, disaggregation enables us to vary consumer behaviour and government policies on different house types, as well as highlighting different technology trends across the stock, in comparison with previous aggregated versions of the model.