A review on buildings energy information: Trends, end-uses, fuels and drivers

Abstract

Buildings are a major contributor to climate change, accounting for one third of global energy consumption and one quarter of CO2 emissions. However, comprehensive information is lacking for the development, evaluation and monitoring of mitigation policies. This paper discusses the remaining challenges in terms of reliability and consistency of the available data. A review of energy use in buildings is presented to analyse its evolution by building types, energy services and fuel sources. Residential buildings are the most consuming, although tertiary expansion requires further analysis to develop sound specific indicators. Heating Ventilation and Air Conditioning (HVAC) systems concentrate 38% of buildings consumption, calling for strengthened standards and incentives for retrofitting. Electrification is rapidly increasing, representing a potential tool for climate change mitigation, if renewable power was promoted. However, energy use in buildings will only curb if global cooperation enables developing nations to break the link between economic growth, urbanisation and consumption. To this aim, efficiency gains both in construction and equipment, decarbonisation of the energy mix and a global awareness on energy conservation are all needed.

Full text

Energy Reports 8 (2022) 626–637
Contents lists available at ScienceDirect
Energy Reports
journal homepage: www.elsevier.com/locate/egyr
Review article
A review on buildings energy information: Trends, end-uses, fuels and
drivers
M. González-Torres a, L. Pérez-Lombard a, Juan F. Coronel a, Ismael R. Maestre b,∗, Da Yan c
aGrupo de Termotecnia, Escuela Superior de Ingenieros, University of Seville, Spain
bDpto. de Máquinas y Motores Térmicos, Escuela Politécnica Superior de Algeciras, University of Cadiz, Spain
cBuilding Energy Research Center, School of Architecture, Tsinghua University, China
article info
Article history:
Received 10 September 2021
Received in revised form 19 November 2021
Accepted 29 November 2021
Available online xxxx
Keywords:
Buildings energy use
Buildings end-uses
HVAC consumption
Fuel sources
Energy drivers
Urbanisation
Buildings energy information
abstract
Buildings are a major contributor to climate change, accounting for one third of global energy
consumption and one quarter of CO2emissions. However, comprehensive information is lacking
for the development, evaluation and monitoring of mitigation policies. This paper discusses the
remaining challenges in terms of reliability and consistency of the available data. A review of energy
use in buildings is presented to analyse its evolution by building types, energy services and fuel
sources. Residential buildings are the most consuming, although tertiary expansion requires further
analysis to develop sound specific indicators. Heating Ventilation and Air Conditioning (HVAC) systems
concentrate 38% of buildings consumption, calling for strengthened standards and incentives for
retrofitting. Electrification is rapidly increasing, representing a potential tool for climate change
mitigation, if renewable power was promoted. However, energy use in buildings will only curb if global
cooperation enables developing nations to break the link between economic growth, urbanisation and
consumption. To this aim, efficiency gains both in construction and equipment, decarbonisation of the
energy mix and a global awareness on energy conservation are all needed.
©2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND
license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Contents
1. Introduction....................................................................................................................................................................................................................... 626
2. Energy use in buildings ................................................................................................................................................................................................... 628
3. Buildings energy services ................................................................................................................................................................................................ 630
4. Energy fuels in buildings................................................................................................................................................................................................. 631
5. Energy drivers in buildings ............................................................................................................................................................................................. 632
5.1. Population............................................................................................................................................................................................................. 632
5.2. Income level ......................................................................................................................................................................................................... 632
5.3. Efficiency............................................................................................................................................................................................................... 633
5.4. Climate .................................................................................................................................................................................................................. 634
5.5. Other Drivers........................................................................................................................................................................................................ 635
6. Conclusions........................................................................................................................................................................................................................ 635
Declaration of competing interest.................................................................................................................................................................................. 636
Acknowledgement ............................................................................................................................................................................................................ 636
References ......................................................................................................................................................................................................................... 636
1. Introduction
Despite the current urgency to halt climate change, the world
energy use and its related CO2emissions keep on growing (Jack-
son et al.,2018). Population and wealth have boosted their
∗Corresponding author.
E-mail address: ismael.rodriguez@uca.es (I.R. Maestre).
increases, as globalisation improves living standards worldwide.
On the contrary, efficiency gains have partially offset those ef-
fects, allowing wealth to grow above consumption. Meanwhile,
energy and emissions have risen at similar rates, thus failing in
decarbonisation in the last two decades (Jackson et al.,2019).
However, their stabilisation seems to be close, as growth rates
have halved since 2013 and the COVID-19 pandemic has radically
altered emissions trajectory (Le Quéré et al.,2021).
https://doi.org/10.1016/j.egyr.2021.11.280
2352-4847/©2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-
nc-nd/4.0/).

M. González-Torres, L. Pérez-Lombard, J.F. Coronel et al. Energy Reports 8 (2022) 626–637
Fig. 1. Final global energy consumption by sector.
Source: Based on IEA data (IEA,2021e,d,b)
Regional disparities show a world split in half. In 2019, devel-
oping nations (non-OECD) represented 82% of the world popula-
tion, generated about 53% of global activity (World Bank,2021)
and were responsible for about two thirds of consumption and
emissions (IEA,2021e). However, people in developed countries
(OECD) are still 4times richer and roughly 3times more con-
sumers and emitters per capita. The gap is narrowing as eco-
nomic expansion enables greater comfort in emerging nations,
albeit increasing energy demand. Fortunately, drops in consump-
tion and emissions in the developed region are about to can-
cel out rises in developing countries as they seek to reduce
inequality (González-Torres et al.,2021a).
Nevertheless, emissions stabilisation will not be sufficient to
limit the global temperature increase to 1.5 ◦C (IPCC,2018). To
face the environmental crisis, most climate policies focus on
decarbonisation by shifting from emissive fossil fuels to clean
renewable sources and by developing Carbon Capture and Storage
techniques. However, these solutions are likely to be constrained
on a global scale in the short term (Peters et al.,2017). Urgent
changes are required, not only in the way energy is supplied,
but also in the way it is consumed (Allouhi et al.,2015). Thus, a
thorough analysis of consumption trends is crucial for addressing
climate change mitigation.
Globally, main consuming sectors are buildings, transport, in-
dustry and others, which clusters minor activities such as agri-
culture, forestry and fishing (Fig. 1). Consumption in every sector
has increased to 9.1 Gtoe in 2019, whereas their shares in final
consumption have remained slightly constant. Buildings were the
most consuming sector, followed by industry and transport. Pop-
ulation growth, built area increase, higher buildings services and
comfort levels, together with the rise in time spent inside build-
ings have raised buildings consumption by 1.2%/yr since 2000.
This upward trend has persisted even in periods of crisis such
as the economic recession of 2008 or the COVID-19. Projections
show that, without more stringent policies, the use of energy in
buildings will continue to grow in the future, as consumption in
developing countries gains importance (Levesque et al.,2018).
Contributions of each consuming sector to global CO2emis-
sions allow the assessment of their environmental impact (Ta-
ble 1). To this aim, direct emissions from fuel combustion as well
as indirect emissions from the energy sector must be addressed.
In 2019, industry remained the most emissive sector (38% ), fol-
lowed by buildings and transport (28% ) to total 33.6 Gton (IEA,
2021c). Buildings are the most affected by indirect emissions from
the energy sector, resulting in total emissions nearly three times
above the direct flow. In contrast, direct emissions represented
Table 1
Share of direct and indirect CO2emissions by sector in 2019.
Source: Based on IEA data IEA (2021c).
Sector Direct Indirect Total
Industry 19% 19% 38%
Buildings 9% 19% 28%
Transport 25% 3% 28%
Other 2% 4% 6%
97.5% of total emissions in transport and 50% in the industrial
sector.
In summary, buildings are responsible for about a third of
global energy consumption and a quarter of CO2emissions. They
even represent larger shares of consumption in some of the most
consuming nations (42% in Russia, 41% in the EU, 37% in Japan and
34% in the US (IEA,2021e)). Their significant impact has placed
them at the forefront of climate policies, due to their high po-
tential for improving energy efficiency and generating renewable
energy (Mavromatidis et al.,2016). However, the development,
evaluation and monitoring of these policies could only succeed
if energy information is available, not only for the whole sector,
but also for building types and energy services. Unfortunately,
gathering buildings information among the existing sources is a
major challenge. Problems regarding data collection and elabo-
ration have resulted in few studies on this sector, compared to
industry and transport.
Several authors have reviewed the energy use in buildings
despite data limitations. Pérez-Lombard et al. (2008) highlighted
this sector as a major contributor to energy consumption in 2008.
They summarised information for main building typologies and
end-uses for some countries and criticised the unavailability of
data. Ürge-Vorsatz et al. (2015) presented a simplified global
and regional picture of the 2010 situation in residential and
commercial buildings, before discussing the main drivers of the
demand for energy heating and cooling. Berardi (2017) provided
historical buildings trends up to 2010 and future estimates for US,
EU and BRIC countries, and called for efficiency policies, which
were almost non-existing in emerging nations and insufficient
in developed ones. Similarly, Allouhi et al. (2015) actualised the
2011 status of buildings energy use in US, Australia, China and
EU as a basis for setting and monitoring energy saving policies. In
2016, Cao et al. (2016) made a comparison of energy efficiency,
end-uses and fuel mixes in 2012 for the top three consumers
(US, EU, China) and focused on Zero Energy Buildings (ZEBs)
to address the increasing energy demand. In 2019, Lu and Lai
(2019) discussed the evolution of energy in residential and non-
residential buildings up to 2015 in US, China, Australia and UK,
their energy policies, rating schemes and efficiency standards.
They suggested the need for different policies in developed and
developing countries, the former to promote renewable energy
and the latter to reduce commercial consumption. Finally, Guo
et al. (2020) studied energy and emissions in 2017 for some
countries and proposed a clustering according to the policies they
require. They also analysed how these figures were related to
energy mixes, population, floor area, wealth and the happiness
score.
Thus, there are some time gaps in buildings consumption
trends over the present century. The global picture of the sec-
tor is often overlooked to focus either on residential or tertiary
buildings, or on those countries where data are available. More-
over, the trajectories of the main factors driving changes in the
whole sector are lacking in the literature. Furthermore, the main
difficulties for data collection have not been criticised, so that the
necessary changes in energy statistics to establish the most ap-
propriate way to report buildings information remain unclear and
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M. González-Torres, L. Pérez-Lombard, J.F. Coronel et al. Energy Reports 8 (2022) 626–637
Fig. 2. Final energy consumption in buildings: OECD and the non-OECD (left), China, India, Brazil, Russia, US, EU, Japan (right).
Source: Based on IEA (2021e) and Odyssee (2021) data.
unresolved. Consequently, this paper provides a deep analysis of
buildings energy use for the world, the developed and developing
regions and most consuming nations in the 21st century. Progress
on data availability and main research challenges are discussed to
propose coherent solutions. Are there comprehensive databases
for buildings energy consumption? How do the main accounting
methods differ? Which is the most consistent breakdown by
building types and energy services? Thus, the paper is intended to
reveal data collection requirements to enable proper monitoring
of the sector, and to explain trends based on the analysis of main
drivers of energy use in buildings.
To achieve these goals, the paper starts with a description of
energy use in buildings, its evolution and its disaggregation in
residential and tertiary sectors. Then, it analyses buildings energy
services and fuel mixes. Lastly, it relates consumption to several
drivers, among which population, wealth, efficiency, floor area
and climate are further examined.
2. Energy use in buildings
As the main consuming sector worldwide, analysing energy
use in buildings is of high interest. However, gathering data
for this purpose remains a major challenge. First, buildings are
usually not recognised as an independent sector. Traditionally,
they have been hidden within a large ‘Other’ sector, despite being
responsible for the largest share of consumption. Some sources
have evolved to disaggregate ‘Other’ into different subsectors, of
which ‘Residential’ and ‘Services’ can be added to obtain buildings
data. However, this addition is still a proxy, since it may some-
times include some activities which do not occur in buildings
(non-building energy use), such as street lighting, water supply,
postal courier, etc., which could together represent up to 10%
of buildings consumption (France, 2018). Despite decomposing
into subsectors is of interest, the buildings sector should first be
accounted for independently and then broken down in residential
and non-residential buildings.
Secondly, sources differ in the activities included in each con-
suming sector, making the comparison difficult. In their attempt
to standardise definitions, data collection institutions normally
define sectors according to the United Nations International Stan-
dard Industrial Classification (ISIC) (United Nations,2008). Dis-
crepancies are found regarding water supply, sewerage, waste
management and remediation activities which are either con-
sidered as Services or ‘Other’ sector; repair and installation of
machinery and equipment, which are included in Industry or in
Services; or postal and courier activities, as part of Transport
or Services. These definitions may vary even within databases
from the same source: buildings data in the IEA World Energy
Outlook (IEA,2021g) include non-specified consumption, while it
is accounted for within ‘Other’ in the IEA World Energy Bal-
ances (IEA,2021e), resulting in discontinuities between past and
future trends.
Thirdly, buildings sector definition is heterogeneous, not only
due to the activities it comprises, but also in terms of the energy
flow measured. Some sources account for final energy use (also
referred to as site or delivered energy (U.S. Energy Information
Administration (EIA),2021) or final energy consumption (IEA,
2021f;Eurostat,2021;Odyssee,2021)), while others also add
the indirect consumption related to the energy losses from the
energy sector (total energy consumption (U.S. Energy Information
Administration (EIA),2021)). Similarly, most data sources limit
their accounting to direct emissions from buildings, i.e., emissions
from the combustion of fossil fuels on-site. The impact of the
buildings sector on the environment is then underestimated since
indirect emissions due to electricity and heat generation must
also be considered. This adds uncertainty to buildings emissions
due to the assumptions required for their calculation in the ab-
sence of data. Moreover, the buildings sector could be analysed
from the life cycle perspective. Thus, other indirect energy and
emissions could also be assessed, such as those embedded in
food, equipment and building materials and their transport to
the construction site (Ürge-Vorsatz et al.,2012). However, these
indirect flows are already accounted for in other sectors, and their
inclusion within the building sector requires complex accounting
methods and assumptions. As a result, a life cycle approach could
divert the focus and hinder the effectiveness of energy policy in
buildings.
These issues could only be solved if a standard definition of the
buildings sector and a universal energy conversion method are
proposed. International organisations and national energy agen-
cies should cooperate to harmonise their accounting, collection,
and reporting methodologies on energy use in buildings. There is
already some international cooperation on standard harmonisa-
tion, such as ISO 12655:2013, which focuses on the presentation
of measured energy use of buildings (ISO,2013).
Despite such difficulties, the most reliable data are chosen
to compare regional and national trends for buildings energy
use (Fig. 2). To this aim, the buildings sector is defined as the
sum of residential and commercial figures, thus including non-
buildings energy use and excluding losses from the power sector
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M. González-Torres, L. Pérez-Lombard, J.F. Coronel et al. Energy Reports 8 (2022) 626–637
Fig. 3. Residential (RES) and tertiary (TER) energy consumption for the OECD
and the non-OECD.
Source: Based on IEA data (IEA,2021e).
and embodied energy from the life cycle perspective. Global
increase on energy use in buildings is driven by 42% rise in non-
OECD since 2000, while consumption in the OECD decreases since
2010 (3% ). Most consuming nations strongly influence trends in
both regions. Consumption in Chinese and Indian buildings rose
sharply after their economic expansion and industrialisation to
some 45%. Similarly, trends in other major emerging nations (BRIC
members), namely Brazil, have followed impressive growths to
some 40%, except for Russia, which has only experienced a sig-
nificant increase after 2016. In contrast, US and EU stopped their
upward tendency around 2010. Since then, energy consumption
in US buildings has only risen by 2%, while it has dropped by 12%
in EU, because of efficiency gains from building’s envelopes and
equipment.
The buildings sector clusters many typologies which differ in
their physical (age, size, geometry and construction) and opera-
tional (activities, internal loads, ventilation ratios, schedules, etc.)
features, influencing the demand for energy services. Thus, the
classification of building types is basic for understanding how
energy is used and developing sound energy policies. At least,
they should be broken down into residential (domestic) and non-
residential (tertiary or services) buildings, as most sources have
already done.
The residential sector accounts for the energy use in dwellings.
However, there are difficulties in identifying and separating some
activities that should be allocated to other sectors due to their
purposes. For instance, the charging of electric vehicles in home
garages should be assigned to the transport sector, while home
professional activities should be part of non-residential consump-
tion. This problem has been highlighted with the expansion of
telework during COVID lockdown, since it is not clear how to
measure this energy flow and who should be responsible for
its costs. In addition, there are different typologies within the
residential sector: single-family (which can be split in detached,
semidetached and attached), multi-family (which can be broken
down according to the number of units) and mobile homes.
The tertiary sector covers commercial and public activities
within many different building types (offices, retail, educational,
sanitary, hosting, leisure, etc.). Unfortunately, there are few con-
sistent and reliable studies for this sector due to the hetero-
geneity of these typologies and the lack of information owing
to the difficulties in collecting data, as tertiary buildings are
usually multi-tenanted and share different activities. Moreover,
data sources do not always agree on the activities included in
this sector. For instance, repair and installation of machinery are
sometimes included in industry, while warehousing for trans-
portation is part of transport. Lastly, data for the tertiary sec-
tor normally include non-building consumption (such as street
lighting), which is inconsistent with its definition.
Trends for the residential and services sectors by region are
shown in Fig. 3. Residential consumption accounts for around
three quarters of energy in buildings at global level. In the non-
OECD region, an almost five times larger population results in
twice the residential energy use of the OECD, despite their lower
wealth. The rapid demographic and economic growths in the
developing region have raised residential consumption by 29%,
in contrast to the flat trend of the developed region. On the
other side, 61% of global tertiary energy is still consumed in the
OECD, where economy shifts from industry towards services have
raised non-domestic consumption by 16%. Tertiary consumption
in developing countries will continue its impressive growth as
they increase their living standards and, consequently, their de-
mand for education, health, leisure and entertainment activities.
Although both drivers influence both sectors, population has a
greater impact on residential consumption, while wealth more
significantly affects non-residential energy use.
The distribution among buildings subsectors varies across
countries (Fig. 4), mainly due to different income levels, climatic
conditions, economic structure, etc. National figures confirm the
expansion of the tertiary sector, whose shares are higher in
OECD countries (Japan, US, EU) than in non-OECD nations (Brazil,
Russia, China, India), reinforcing the link between services and
wealth. The highest tertiary shares correspond to the Japan (54% )
Fig. 4. Residential and tertiary shares for Japan, US, EU, Brazil, Russia, China and India.
Source: Based on IEA (2021e) and Odyssee (2021) data.
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M. González-Torres, L. Pérez-Lombard, J.F. Coronel et al. Energy Reports 8 (2022) 626–637
and US (44% ), where the consumption is roughly equally dis-
tributed between residential and commercial buildings. Among
the emerging nations, the importance of each subsector is deter-
mined by the balance between population density and per capita
income. For instance, India presents the highest residential share
(88% ) for being the most populous (460 cap/km2) and poorest (6.7
k$/cap) country. On the contrary, Brazil has a high tertiary share
(33% ) due to low population density (25.3 cap/km2) despite low
per capita incomes (14.7 k$/cap) (World Bank,2021).
3. Buildings energy services
Disaggregating buildings consumption by energy services (also
referred to as end-uses) allows users and owners to better un-
derstand their consumption patterns to identify cost-effective
saving measures (Froehlich et al.,2011). Moreover, it would help
policymakers to develop instruments targeting the most intensive
services and devices.
However, energy disaggregation at this level is hardly avail-
able, as utility meters are unable to distinguish the energy con-
sumed for each particular use (U.S. Energy Information Admin-
istration (EIA),2017). Several methods have been developed
to compile these data. Direct metering using distributed sen-
sors (Glasgo et al.,2017) provides the most accurate information,
whereas the installation and maintenance costs and the lack
of a regulatory framework prevent its widespread use. Other
methods involve non-intrusive load monitoring (Zoha et al.,2012),
which estimates consumption by classifying measurements from
a single sensing point through a pattern recognition algorithm.
Thus, despite fewer installation costs, calibration and training
sensors are required. Finally, engineering and statistical methods,
such as regression models or neural network modelling, are also
used (Swan and Ugursal,2009). They need detailed information
on the characteristics of buildings and equipment performance
and stock, which must be gathered through comprehensive sur-
veys. The US Residential Energy Consumption Survey (RECS) (U.S.
Energy Information Administration (EIA),2015) and the Commer-
cial Buildings Energy Consumption Survey (CBECS) (U.S. Energy
Information Administration (EIA),2012) are the main reference
in this regard. However, they cannot be released on a yearly
basis due to their high preparation, collection and processing
time and cost. In Europe, energy services information is still
insufficient, though the Odyssee–Mure project (Bosseboeuf et al.,
2015) is working on harmonising and centralising national data
from National Statistical Offices and surveys carried out by gov-
ernments, utilities or equipment manufacturers. Similarly, the
IEA Energy Efficiency Indicators (EEI) database (IEA,2020) has
collected available energy services information for these and four
additional nations (Canada, Korea, Morocco and Japan). In China,
Tsinghua University has continuously collected information on
residential energy and behaviour through large-scale surveys
since 2008 (Zhang et al.,2010;Hu et al.,2017). For the rest of
the world, with some exceptions, energy information by end-use
is almost non-existent.
Despite energy services classification varies among sources,
this paper classifies them in Heating, Ventilation and Air Con-
ditioning (HVAC), Domestic Hot Water (DHW), lighting, cook-
ing and other equipment, mainly appliances and other plug-in
devices. Their shares for the world and the most consuming
countries are presented in Fig. 5, according to the latest available
and reliable data for each region.
HVAC systems are the most consuming service worldwide
(38% ), both in residential (32% ) and tertiary (47% ) sectors. They
have become almost essential in parallel with the spread of the
demand for thermal comfort, considered a luxury not long ago.
It is the largest end-use in every country except India, where
Fig. 5. Buildings consumption by end-uses for the world, US, EU, China, India
and Russia.
Source: Based on IEA (2021d,2017), U.S. Energy Information Administration (EIA)
(2019)and Odyssee (2021)data.
Fig. 6. Main end-uses by consuming sector. World, 2020.
Source: Based on IEA data (IEA,2021d).
warmer weather and a lower income level push consumption to-
wards basic ceiling fans and more indispensable end-uses, mainly
cooking. Thus, HVAC’s contribution to buildings energy consump-
tion depends to a large extent on climate and wealth. Richest
countries (US, EU) have higher shares than emerging ones (China,
India), while the largest fraction is found in Russia because of
the coldest climate. In summary, HVAC consumption represents
about 12% of final energy use worldwide and up to some 25% in
rich or cold regions such as the UE or Russia. Their weight in
consumption is even comparable to main end-uses from other
sectors, such as passenger cars in transport (Fig. 6). Consequently,
policies should address this highly consuming end-use, namely
in the developed region, by improving and retrofitting buildings’
envelopes and HVAC systems (Pérez-Lombard et al.,2012).
DHW is the second buildings energy service at global level
(13% ), followed by cooking (8% ) whose large shares in less de-
veloped countries contrast with the small figures in developed
nations. Lighting represents the lowest share (5% ) and contin-
ues to decrease as LEDs replace less efficient traditional bulbs.
Finally, other equipment gathers 36% of consumption, being more
important in countries with higher access to electricity (37% in
US vs. 7% in India). Progress has made electric devices more
affordable and widespread, whereas technology efficiency gains
have offset their increasing demand in US and EU over the last
years. Their important share would require further disaggregation
to reveal which types of equipment are responsible for such
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M. González-Torres, L. Pérez-Lombard, J.F. Coronel et al. Energy Reports 8 (2022) 626–637
a large impact on consumption. However, energy estimates for
plug-in devices are particularly difficult to disentangle and there
is no consensus on the sub-categories to be defined, as it consists
of a miscellaneous mix of devices with minor energy shares.
4. Energy fuels in buildings
Building’s energy mix strongly impacts on primary energy and
CO2emissions. Buildings mainly use electricity, biofuels (biomass,
liquid biofuels and biogases), natural gas, oil products (LPG, gasoil
and fuel-oil), coal, district heating and ‘other renewables’. Among
these fuels, there is huge uncertainty in renewable informa-
tion for biomass and other renewables. On the one hand, non-
marketed biomass cannot be measured, so the weight of biofu-
els depends to a large extent on the reliability of the assump-
tions made for its estimation, especially in developing economies,
where it represents a significant share of the energy use. On the
other hand, ‘other renewables’ should include not only on-site
generation of electricity and heat, but also other technologies that
take renewable energy from the building’s environment. How-
ever, they are usually not measured (solar thermal, photovoltaics
and heat pumps) or not even measurable, such as daylighting,
natural ventilation, free-cooling, and passive cooling and heating
systems.
Due to the importance of their share, heating and cooling
fuels play a dominant role in buildings energy mix. Fossil fu-
els are the most frequent heat source, although the prolifera-
tion of heat pumps has increased heating electrical consump-
tion in recent years. For cooling generation, electricity is almost
the only source, given the limited market for gas engine driven
chillers, gas-driven air conditioners and absorption refrigerating
machines (Pérez-Lombard et al.,2011b).
The evolution of the fuel mix in buildings (Fig. 7) shows that
consumption growth has been supplied mainly by electricity and
gas, accounting for 55% of the energy use in 2020. Electricity
(33% ) has replaced biomass (24% ) as the main energy source. The
higher access to electricity in the developing region (Nejat et al.,
2015) has driven shifts towards electric technologies, like the
substitution of biomass for cooking. The expansion of the market
of electrical equipment, such as small appliances and electron-
ics, is also a driver for buildings electrification. Moreover, HVAC
systems have become widespread, driving the use of electricity
mainly for space cooling, but also for heating (Hojjati and Wade,
2012) with the use of heat pumps in mild climates.
Fossil fuels consumption has decreased thanks to the reduc-
tion of the use of oil products (10% ) in favour of less emissive
natural gas (22% ), while the use of coal is marginal and constant
Fig. 7. Buildings fuel mix evolution for the world.
Source: Based on IEA data (IEA,2021e,d).
(3% ). The increase in natural gas, which is mostly used for space
heating, has been partially offset by efficiency gains (condensing
boilers, gas furnaces...). However, the long lifetime of heating
equipment compared to other end-uses hinders the promotion
of enhanced heating technologies, thus delaying their effect on
energy consumption (Hojjati and Wade,2011). Lastly, the share
of district heating has remained roughly constant (6% ), whereas
on-site renewables have appeared in buildings up to 2%.
Regional differences in fuel mixes are plotted in Fig. 8. In the
OECD, electricity was already the major source in 2000, followed
by natural gas, and their shares have increased while replacing
the supply of coal and oil products. For instance, in US, buildings
energy mix was almost equally distributed between electricity
(49% ) and gas (41% ) in 2019. The electricity share in the EU is
limited to a third of buildings energy consumption, as they mainly
rely on gas (35% ) and have more significant figures for biofuels
(11% ), oil (10% ) and heat (7% ). Japanese buildings are the most
electrified (53% ) and they stand out for their high oil share (24% )
above that of gas (19% ).
In contrast, fuel availability and access to electricity constrain
the use of marketed energy carriers in the non-OECD, mainly
in rural areas (Chaturvedi et al.,2014). Consequently, electricity
was a minor source in 2000, whereas it has doubled its share to
25% in 2019 due to economic development and urbanisation. In
developing economies, the large consumption of biofuels (36% )
is due to traditional biomass, and their fossil fuels consumption
has risen due to gas increases. Data for India in 2000 illustrate
the energy mix of the least developed countries, where buildings
energy demand was mainly supplied by non-marketed biomass
(wood), fossil fuels accounted for 19% and electricity was below
7%. In 2019, they still presented the highest biofuels share among
the studied countries, although electricity has tripled, and fossil
fuels have increased to 23%. Electricity shares in China (30% )
and Brazil (61% ) have also risen and are comparable to those of
developed countries, while biofuels still contribute by 18%. China
has the highest renewable fraction (9% ) due to numerous policies
promoting the use of on-site solar energy, which contrasts with
their high fossil fuels fraction (35% ), equally divided between gas,
coal and oil. Russia differs from other non-OECD members since
it relies mainly on gas (38% ) and heat (36% ) and electrification is
only 15% of buildings energy mix.
Policy intentions targeting electrification could be a keystone
for reducing the energy environmental impact (Miller,2018).
Electric end-uses are more efficient, so they could reduce energy
consumption, while lessening CO2emissions if electricity were
produced from non-emitting sources (renewable and nuclear). In
contrast to other consuming sectors, buildings electrification is
feasible because all their services can be electrified. Main barriers
are found for space heating and DHW in the coldest climates,
where electrification would require the use of ground or water
source heat pumps, since low outdoor temperatures penalise the
performance of air-to-water equipment. With all, encouraging the
use of heat pumps for space and water heating can quickly and
cost-effectively reduce final consumption and emissions through
electrification (Langevin et al.,2019).
However, fossil electricity generation in 2019 still represented
63% worldwide (IEA,2021a), adding 5.6 Gton to the 3Gton
directly emitted in buildings. Current electricity mix could make
electrification a threat rather than an opportunity to tackle cli-
mate change, by increasing emissions instead of achieving desir-
able reductions (González-Torres et al.,2021b). Thus, renewable
electricity promotion is a priority for future sustainability (Mai
et al.,2018).
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Fig. 8. Changes of buildings fuel mix (2000–2019) for the OECD and the non-OECD regions and for US, EU, Japan, Russia, China, India and Brazil.
Source: Based on IEA (2021e) and Odyssee (2021) data.
5. Energy drivers in buildings
Buildings are responsible for a significant share of world en-
ergy use and related CO2emissions, but which are the main
factors driving their change? To answer this question, some activ-
ity indicators commonly available in datasets, such as population
and wealth, could be analysed. However, other more specific
indicators are harder to find and less reliable, since they are
difficult to measure, especially in developing countries (Ürge-
Vorsatz et al.,2015). Examples include urbanisation, floor areas,
number of buildings, number of occupants, equipment stock, fuel
prices, climate indicators and culture and human behaviours. To
this extent, detailed information could only be obtained through
comprehensive census, data collection from random samples and
subsequent data processing and modelling (Haas,1997), requir-
ing huge work and investment. In this respect, US’s surveys on
residential (RECS) (U.S. Energy Information Administration (EIA),
2015) and commercial sectors (CBECS) (U.S. Energy Information
Administration (EIA),2012) remain as the most valuable refer-
ences. Odyssee–Mure project (Bosseboeuf et al.,2015) and IEA EEI
database (IEA,2020) collect and publish meaningful information
from European countries and IEA members, though they are
subject to the national sources on which they are based. Data
limitations prevent a quantitative analysis of the impact of these
factors on buildings energy trends. However, they are briefly
examined below to explain consumption patterns for the selected
nations where information is available. Main drivers under the
scope of this paper are population, wealth, efficiency, floor area
and climate.
5.1. Population
Population is commonly chosen as a key activity indicator for
energy use and related CO2emissions (Blanco et al.,2014). In
this respect, Fig. 9 shows the relation between buildings energy
consumption and population for different regions. As expected,
population growth leads to energy consumption increases. How-
ever, there is an imbalance in per capita terms among nations.
Most populated countries, such as China or India, have the lowest
per capita consumption figures together with other emerging
countries such as Brazil. Despite Indian population is four-fold
the American’s and over twice the European’s, it still consumes
half as much as developed countries. Thus, their per capita energy
consumption in buildings (0.13 toe/cap) is about ten times lower
than in US (1.5 toe/cap) and six times below the EU (0.82 toe/cap).
An early convergence in per capita terms is unlikely, due to
their slow trends and the huge distance between their starting
points. Note that buildings energy consumption increases in Rus-
sia and decreases in Japan despite constant population, revealing
the importance of analysing additional drivers to explain such
changes.
Fig. 9. Buildings consumption vs. population for the OECD and the non-OECD
regions and for US, EU, Japan, Russia, China, India and Brazil.
Source: Based on IEA (2021e), Odyssee (2021) and World Bank (2021) data.
5.2. Income level
Differences in per capita consumption can be partially ex-
plained by wealth figures, which are positively correlated (Fig. 10).
Indeed, higher affluence allows for better comfort levels and
entertainment activities, as citizens can afford energy and equip-
ment, as well as larger living and leisure space (Santamouris et al.,
2007). Moreover, as an economy thrives, it tends to shift from
industry to tertiary activities, also leading to higher consumption
in buildings. However, this correlation should be broken, as de-
veloped nations have already achieved. US, EU and Japan have
increased wealth while decreasing per capita consumption due
to more efficient buildings and equipment and the saturation
of energy services (Haas et al.,2008). This trend was also fol-
lowed by Russia, though it deviated due to a noticeable increase
in the built-up area since 2013 (ISI Emerging Markets Group
Company,2021). The OECD path should serve as a roadmap for
emerging countries to decouple development trajectories from
consumption as soon as possible. Note also that nations have
evolved to converge in terms of buildings energy intensity of GDP
(20 toe/M$), after the impressive rise in wealth in developing
countries. In other words, their buildings consume roughly the
same by unit of GDP, reinforcing the link between energy use
in buildings and activity generation. Thus, every nation would
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M. González-Torres, L. Pérez-Lombard, J.F. Coronel et al. Energy Reports 8 (2022) 626–637
Fig. 10. Buildings consumption per capita vs. wealth for the OECD and the
non-OECD regions and for US, EU, Japan, Russia, China, India and Brazil.
Source: Based on IEA (2021e), Odyssee (2021) and World Bank (2021) data.
consume the same energy in buildings, if they had the same GDP.
The only exception is Russia, where the cold climate and the poor
thermal insulation of buildings (Lychuk et al.,2012) resulted in
higher consumption figures for its wealth level (47 toe/M$).
5.3. Efficiency
Efficiency is postulated as the basic instrument to decouple
energy use and economic growth, as it allows energy savings
with no detriment to the welfare of buildings occupants (De Rosa
et al.,2014). In developed countries, wealth has enabled the
spread of efficient but expensive equipment. They have also ben-
efited from electricity access which allows the use of electrical
devices, less consuming than those supplied by other sources.
Moreover, they can afford buildings designs which lessen heat-
ing and cooling demand by implementing energy conservation
measures, both for building envelope and mechanical equipment.
Hopefully, globalisation is playing an important role in reducing
efficiency differences between regions by transferring the latest
technological achievements across borders.
Regulatory bodies have three basic instruments to promote
energy efficiency in buildings: regulations, auditing and certi-
fication. Energy regulations, also referred to as ‘building en-
ergy codes’, set minimum efficiency requirements at compo-
nent (prescriptive approach) or global levels (performance ap-
proach) for the design, construction and retrofitting of build-
ings (Pérez-Lombard et al.,2011a). Energy auditing are investiga-
tions to identify areas with potential retrofit opportunities in ex-
isting buildings and propose efficiency measures accordingly (Ma
et al.,2012). Finally, certification schemes encompass any pro-
cedure (benchmarking, rating and labelling) allowing the com-
parative determination of the quality of new or existing build-
ings in terms of their energy use (Pérez-Lombard et al.,2009).
These instruments require improved calculation methodologies
and the definition of efficiency indicators (Wong et al.,2020). This
way, users could better understand their consumption patterns
and adopt conservative behaviours, while decision-makers could
design more stringent and effective energy policies.
However, measuring energy efficiency in buildings is a com-
plex issue. Energy intensity, defined as the ratio of energy con-
sumption (input) to an activity indicator (output) (Pérez-Lombard
et al.,2013), is the most common efficiency metric. Main dif-
ficulties for its assessment lie in the suitability and availability
of activity data. General purposes of other consuming sectors
are clear: industry aims to generate products and wealth, while
transport aims to move goods and passengers. Thus, tonnes of
Fig. 11. Buildings per capita energy consumption vs. per capita floor area
selected countries: World, US, EU, Japan, Russia, China, India, New Zealand,
Spain, France, Germany and Sweden. Indian and Russian values are only available
for 2017 and 2013, respectively. World figures correspond to 2019.
Source: IEA (2021e,2020), Odyssee (2021), Jiang et al. (2018), Alliance for an
Energy Efficient Economy (AEEE) (2018), Bashmakov (2016) and World Bank
(2021).
product or Gross Value Added, and passenger-kilometres or ton-km
are proper activity indicators to evaluate industry and trans-
port efficiency, respectively. In contrast, energy is used in build-
ings to provide different services: comfort, lighting, hot water,
cooking, etc. Therefore, the activity indicator should vary among
end-uses (Xu and Ang,2014) and the construction of efficiency
indicators requires highly disaggregated data.
Most prevalent activity indicator is building floor area, though
it correlates better with space heating and cooling than with
other end-uses, such as water heating, equipment or cooking
(Belzer,2014). Thus, urbanisation, in terms of per capita floor
area, is a meaningful metric to assess space requirements for liv-
ing, working, health, education and entertainment. Fig. 11 shows
the relation between per capita energy consumption and per
capita floor area in buildings for the world and some countries.
Constant lines of energy consumption per square metre (referred
to as energy use intensity) could serve as an efficiency indica-
tor. Countries with the largest per capita floor area (above 50
m2/cap) correspond to those with higher per capita consumption
(above 0.6 toe/cap). On the other side, India has the lowest per
capita consumption (0.13 toe/cap) due to its low urbanisation
(12 m2/cap). China stands out for its impressive area growth
as a result of the continuous shift from rural to urban areas,
which leads to lifestyles changes and increases personal living
space (Jiang et al.,2018). However, in per capita terms, Chinese
lower income keeps consumption low, despite building areas
approaching those of developed countries (45 m2/cap).
Three different patterns are found among the studied coun-
tries: (a) efficiency improvements in most developed nations,
which have achieved area growth compatible with consumption
drop, thanks to successful energy policies; (b) efficiency improve-
ments with rises in consumption in China, where improved living
standards have induced area growth above energy demand; (c)
constant efficiency in Spain, where the construction boom and
the growth of the economy have boosted the floor area and the
energy use at the same pace. Regarding absolute figures, energy
use intensity in most developed countries (around 15 koe/m2)
contrasts with that of some emerging nations, such as China
(7koe/m2), thanks to energy conservation habits rather than to
higher efficiency levels. A higher intensity in India (11 koe/m2)
is explained by the large occupancy density of their buildings,
resulting in a quarter the area and half the consumption of China,
for roughly the same population.
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M. González-Torres, L. Pérez-Lombard, J.F. Coronel et al. Energy Reports 8 (2022) 626–637
Fig. 12. Buildings energy use intensity (left) and heating energy intensity (right) vs. Heating Degree Days for selected countries: US, EU, Japan, Russia, China, India,
New Zealand, Spain, France, Germany and Sweden. Figures correspond to 2018, except for India (2017) and Russia (2013) (left) and US (2017) and China (2014)
(right).
Source: IEA (2021e,2020), IEA and CMCC (2021), Odyssee (2021), Jiang et al. (2018), Alliance for an Energy Efficient Economy (AEEE) (2018) and Bashmakov (2016).
Note also that countries such as Germany and New Zealand
show large differences in per capita consumption at similar levels
of urbanisation and wealth, which can be explained by climate.
The severe climate in the former contrasts with the mild cli-
mate in the latter. Similarly, the high Russian energy use in-
tensity is mainly driven by the extremely cold weather surging
the demand for space heating, which is above 62% of buildings
consumption (IEA,2017).
5.4. Climate
Weather is also considered as a key driver for buildings con-
sumption since it obviously affects HVAC and DHW energy de-
mand. Furthermore, other weather dependent conditions, such as
daylight, temperature and humidity have a great impact on the
use of certain equipment (lamps, refrigerators, dryers, etc.) and
on the number of hours indoors.
Heating Degree Days (HDD) are commonly used to correlate
energy consumption and climate. They measure the cold weather
intensity over a certain period by accounting for the difference
between the outdoor temperature and a base temperature, be-
low which heating systems are presumed to turn on. However,
discrepancies among datasets are found in the choice of the
base temperature, which may vary depending on the inhabitants’
tolerance to cold temperatures, building type, building envelope,
occupancy density, etc. Moreover, HDD can be corrected to ad-
dress the potential effects of additional climatic parameters, such
as humidity and solar radiation, by using the Heat Index, Hu-
midex or Environmental Stress Index as input parameters (Atalla
et al.,2018).
Energy use intensity is plotted vs. HDD for some nations in
Fig. 12 (left). Buildings consumption per floor area is clearly
higher in colder areas. Swedish low consumption compared to
Russian, reflects the priority on high performance envelopes and
highly efficient district heating systems in Northern Europe (Be-
rardi,2017). Again, China stands out for the reduced stock of
heating systems and lower comfort levels. However, energy use
intensity does not correlate well with HDD, since two-fold differ-
ences are found for countries around 2000 degree-days. A better
correlation results if only consumption figures for heating pur-
poses are considered Fig. 12 (right). However, it requires HVAC
consumption disaggregation, which is not always available. Also,
the quality of the correlation highly depends on the uncertainties
added by the extended use of non-marketed wood for heating, as
Fig. 13. Weather-adjusted (dashed lines) and real (solid lines) buildings energy
use in US, EU, China, India, Japan and Russia.
well as on the size of the country, which could cluster different
climate regions (e.g., US).
Climate could also be responsible for short-term fluctuations
in energy consumption, as milder-than-usual weather could lessen
annual energy demand, while the severity of winter or hot sum-
mer seasons could cause occasional consumption peaks. In prin-
ciple, a better monitoring of energy use in buildings can be
achieved if consumption is corrected to neutralise weather ef-
fects, commonly assuming a linear regression with heating degree
days (Makhmalbaf et al.,2013). Fig. 13 plots trends with and
without weather adjustment for the most consuming nations. The
method succeeds in removing main annual fluctuations only in US
and EU, allowing a better understanding of the evolution of the
buildings sector. However, for the rest of the countries, climate is
a negligible driver for energy use in buildings, especially in devel-
oping nations, where the response to weather variations does not
result in increased energy use, but in decreased thermal comfort,
as low-income levels restrict energy expenditure. Therefore, there
is no reason for climate adjustment in these cases since it could
lead to unreal fluctuations (China).
In the long-term, climate change could modify buildings en-
ergy patterns, especially for HVAC systems. Energy demand will
shift towards cooling (Roberts,2008) while passive approaches
will become less effective due to the temperature rise. This,
along with more frequent extreme weather events, such as heat
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M. González-Torres, L. Pérez-Lombard, J.F. Coronel et al. Energy Reports 8 (2022) 626–637
waves (De Wilde and Tian,2011), could raise energy consump-
tion. Consequently, the related emissions growth could intensify
climate change, resulting in a dangerous vicious circle.
5.5. Other Drivers
Other factors also influence energy use in buildings, though
they are more difficult to quantify than those analysed above.
Some of them are briefly commented below and meaningful
references are given to complete the discussion here provided.
The number of buildings (Berrill et al.,2021) can be introduced
to decompose urbanisation (m2/cap), which can be driven by
an increase in building size (m2/build) or by a growing demand
for buildings per capita (build/cap). Smaller households or more
commercial buildings per capita would lead to higher consump-
tion levels, as their occupants do not share energy-consuming
equipment (Bertoldi et al.,2018). US’s figures from 2005 to 2015
show that residential urbanisation has decreased to 69 m2/cap
since the average home size has drop to 187 m2and the number
of dwellings per person has decreased to 0.37 build/cap (average
household size of 2.7 people) (U.S. Energy Information Admin-
istration (EIA),2015,2005). For tertiary sector over the period
2003–2018, urbanisation has risen to 28 m2/cap due to the in-
creases in buildings per capita (18 buildings per 1000 citizens) and
in the average building size (1519 m2) (U.S. Energy Information
Administration (EIA),2003,2018).
Demography can also be a driver, as ageing population tends
to result in more single person households (World Business Coun-
cil for Sustainable Development,2008), a minor energy use for
entertainment activities and a higher residential energy con-
sumption because they stay more time at home and demand
higher comfort levels.
Buildings sector structure, also referred to as building type
mix, is also a major driver. Higher shares of most intensive build-
ing types would rise sectoral energy consumption. For instance,
tertiary buildings in the US are twice more intensive (25 koe/m2)
than residential ones (12 koe/m2), while most intensive non-
residential types could double (47 koe/m2for health care) or even
triple (77 koe/m2for food services) average figures (U.S. Energy
Information Administration (EIA),2012).
Rises in electricity and fuel prices (Greening et al.,2001) could
in principle drive consumption decline. However, rather than
preventing energy use, they tend to widen the gap between high
and low-income citizens. They may also lead to fuel switching to
cheaper energy sources. Policy makers could take advantage of
this strategy to promote the use of cleaner sources and reduce
related CO2emissions.
Lastly, behavioural aspects, lifestyle and socio-cultural habits
(Huebner et al.,2015) play an important role in determining the
time spent indoors, and consequently equipment usage patterns.
Also, they strongly influence choices of cooking and diet (Hager
and Morawicki,2013), as well as equipment stock, which would
result in different consumption figures. Individual practices are
essential for reducing wasteful behaviours, through a rational
use of energy. Low-energy practices, encompassing new tech-
nology choices and new behaviours in their uses, could reduce
buildings consumption by more than 10% by 2100 (Levesque
et al.,2019). However, these changes are hardly induced by
policy measures, except by incentives for the adoption of efficient
technologies and time-of-use tariffs. In this respect, Buildings
Energy Management Systems (BEMS) could play an important
role in two ways. On the one hand, metering would provide
users with information to improve buildings’ performance and
to identify cost-cutting opportunities by detecting inefficiencies,
benchmarking and planning load and energy usage (Ahmad et al.,
2016). On the other hand, monitoring and control techniques
would compensate unconscious occupant behaviours by schedul-
ing controls, system optimisation, occupant detection control, and
variable speed control (Cheng and Lee,2018). In parallel, be-
havioural changes should be stimulated by increased awareness
of energy conservation as a scarce and polluting resource (Wolske
et al.,2020;Marghetis et al.,2019), which could be promoted by
billing and metering feedback, education and advice.
6. Conclusions
Buildings currently account for a third of global consumption
and a quarter of CO2emissions. Their significant impact has
placed them at the forefront of climate policies, due to their
high potential for electrification, energy efficiency improvement
and on-site renewable generation. However, the development,
evaluation and monitoring of sound policies requires meaningful
information, not only for the whole sector, but also for building
types and energy services. To this end, buildings should be treated
as an independent sector in energy statistics. Key activity indica-
tors such as floorspace, number of buildings and equipment stock
should be collected and reported. Although surveying, metering
and modelling fundamentals are well established, the lack of in-
formation is hindering the quantification of efficiency and carbon
indicators. Further work and international consensus are needed
for buildings information standardisation.
As for building types, energy use is commonly split into res-
idential (72% ) and non-residential (28% ) buildings. They should
be treated both together and separately, as their physical and
operational differences require specific policies. Information is
lacking, especially for the tertiary sector, due to harder data col-
lection and the variety of their activities. This problem should not
be overlooked as it already accounts for about half of buildings
consumption in developed nations and is expanding impressively
in emerging countries.
Regarding buildings services, HVAC systems have become al-
most essential in parallel with the spread of the demand for ther-
mal comfort. They are the most consuming end-use worldwide,
accounting for 38% of buildings consumption, thus meaning about
12% of global final energy. Consequently, incentives and standards
should promote energy-efficient HVAC retrofitting, which will
otherwise be delayed due to their long lifetime.
Population, urbanisation and wealth put pressure on buildings
consumption, which has risen by 1.2%/yr since 2000. Population
boosts energy use, especially in emerging economies, due to their
rising per capita consumption and access to electricity. Urbani-
sation grows dramatically in developing countries due to shifts
from rural to urban areas and lifestyle changes. Higher affluence
allows for better comfort levels, higher penetration of equipment
and larger living and leisure floorspace.
Consumption growth has been mainly supplied by electricity
and natural gas, accounting for 55% of energy use. Electricity
has already replaced biomass as the main energy source, mainly
due to the increased accessibility in the developing region, the
expansion of cooling demand and heat pumps for heating, and the
growing market for electrical equipment, such as small appliances
and electronics. However, in 2019, electricity only represented
a third of the final energy consumption in buildings, and great
efforts would be necessary for full electrification.
Energy use intensity is the principal efficiency indicator for
buildings, whereas it is only available for the few countries where
energy use and floor area information are collected. In developed
countries, more efficient buildings and equipment, and the satu-
ration of energy services, have allowed significant reductions in
energy intensity to roughly 15 koe/m2.
Reducing energy use in buildings will not be possible unless
global cooperation enables developing nations to break the link
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M. González-Torres, L. Pérez-Lombard, J.F. Coronel et al. Energy Reports 8 (2022) 626–637
between economic growth, urbanisation and consumption. Cus-
tomised development approaches are needed for these nations
to reduce the existing gap in terms of income, floor area and
energy use per capita. Technicians and politicians must work
together to implement and stimulate efficiency improvement and
on-site renewable promotion as key demand-side instruments.
Despite assuming that buildings could be fully electrified once
the power grid is ready to satisfy their demand, the world should
not solely rely on supply-side electricity decarbonisation in the
short term for climate change mitigation. Moreover, buildings
embodied energy and other GHG emissions cannot be disregarded
due to their significant environmental impact. The synergistic
effect among construction and buildings sectors is an important
challenge to be addressed.
In summary, efficiency improvement and decarbonisation will
hardly be able to reduce emissions to safe levels unless global
awareness of energy as a scarce and polluting commodity drives
real conservation habits. Buildings are constructed to serve hu-
man beings, so the quantity and quality of the service demanded
is largely in our hands. It is time to move from words to actions.
Declaration of competing interest
The authors declare that they have no known competing finan-
cial interests or personal relationships that could have appeared
to influence the work reported in this paper.
Acknowledgement
The authors acknowledge support and funding from Univer-
sity of Seville, Spain, University of Cadiz, Spain and the Eu-
ropean Commission Horizon 2020 project ReCO2ST (Residential
Retrofit assessment platform and demonstrations for near zero
energy and CO2 emissions with optimum cost, health, comfort
and environmental quality) (grant no. 768576).
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