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The life cycle assessment of a UK data centre

  • Operational Intelligence

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Purpose Data centres are high-energy consumers, and historical assessment of their environmental impact has focused largely on energy consumption. Widely adopted assessment methods consider either single issues or do not comprehensively assess links between issues. One exception is the CLEER Model, which compares life cycle energy and greenhouse gas (GHG) emissions of Cloud-based and present-day services. However, there remains the need to verify components for inclusion in a data centre life cycle assessment (LCA), assess quality and quantity of secondary data, benchmark an existing data centre LCA, assess non-Cloud-based services for multiple impacts, and establish facility areas that are sensitive to change. Methods A hybrid approach, combining process-based and economic input output (EIO) data, was used to perform the screening LCA of an existing UK data centre. The study includes the definition of the goal and scope, modelling assumptions, a life cycle inventory, results and interpretation and a sensitivity check. Results and discussion The dominance of the information technology (IT) operational phase to the overall impact and the severity of the impact on human health are concluded. Due to the use of free cooling, the IT-embodied impact is greater than the combined mechanical and electrical operational impact. Electricity production dominates the total life cycle impact; however, the second most significant impact derives from the disposal of metal refining waste products during the manufacture of IT components and electricity distribution networks. The release of carcinogens is one of the largest contributors to the whole life cycle impact and is almost equal in value between the embodied and operational phases. Finally, a sensitivity check found that a Swedish facility optimised for operational energy efficiency with a 1.25-year server refresh resulted in an embodied impact almost double the operational. Conclusions It was concluded that current LCI data, software packages and project data allow for a sufficiently accurate data centre LCA model. The results support the need to broaden environmental impact reduction to beyond operational energy consumption for cooling and that building environmental assessment methods (BEAMs) should consider more embodied impacts. It is concluded also that three parameters are sensitive to design changes that influence the overall impact: operational energy for the IT equipment, cooling and power delivery; the energy mix; and the amount of IT equipment across the facility’s lifetime. The results present a clear need to monitor life cycle impact, develop further tools to compare different design/operation options and functional units, improve data and develop an LCA-based BEAM.
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Assessing the environmental impact of data centres part 2: Building
environmental assessment methods and life cycle assessment
Beth Whitehead
, Deborah Andrews
, Amip Shah
, Graeme Maidment
Faculty of Engineering Science and the Built Environment, London South Bank University, 103 Borough Road, London SE1 0AA, UK
HP Labs, 1501 Page Mill Rd., Palo Alto, CA 94304, USA
article info
Article history:
Received 15 May 2014
Received in revised form
14 July 2014
Accepted 8 August 2014
Available online 20 August 2014
Data centres
Environmental impact
Life cycle assessment
Building environmental assessment
Life cycle assessment tools
Data centres consume high levels of energy to power the IT equipment contained within them, and
extract the heat they produce. Because of the industry's heavy reliance on power, data centre metrics
have historically used operational efciency as a proxy for sustainability. More recently the industry has
begun to recognise that its focus needs to go beyond energy consumption, with the creation of metrics
for issues such as carbon, water and compute efciency. However, single-issue metrics often consider
only the operational phase, omitting impacts from other issues, during other stages in a facility's lifetime.
Further approaches exist to assess more holistically the impact of data centres, such as building envi-
ronmental assessment methods, but none have the capacity to capture fully the interlinked nature of a
system, where improvements in one area and to one impact, can adversely affect a totally different area
and totally different impacts.
The following review of literature summarises the approach of the data centre industry to environ-
mental impact, and provides direction for future research. Part 2 describes the use of building envi-
ronmental assessment methods and tools; and concludes the need to apply life cycle thinking to more
holistically assess the environmental impact of data centres.
©2014 Elsevier Ltd. All rights reserved.
1. Introduction
This paper is the second of a two-part literature review that
explains the background to current methods of assessment used by
the data centre industry, and concludes the need for a more holistic
approach to the management of environmental impact in the
future. Continuing from part 1, this paper describes the use of
building environmental assessment methods and tools; and based
on both parts of the review, concludes the need to apply life cycle
thinking to more holistically assess the environmental impact of
data centres.
2. Building environmental assessment methods
Beyond single-issue metrics, discussed in part 1, building envi-
ronmental assessment methods (BEAMs) are also used, to under-
stand and reduce the impact of data centres on the environment,
while reducing their demand on power infrastructures. BEAMs
award credits for the performance of buildings against benchmarks
within a set number of impact categories. In most schemes, credits
are weighted according to the relative gravity with which they
impact on the environment, and a nal rating awarded such as
Excellent or Outstanding to show the overall performance of the
In the UK, the standard methodology used is the Building
Research Establishment Environmental Assessment Methodology
(BREEAM). This scorecard toolis the only scheme from across the
globe that has a data centre specic framework. The scheme is
voluntary [1], and provides an end rating which acts as a label for
the improvement in environmental performance of a building [2,3].
Across the globe many non-data centre specic assessment
methods exist such as:
HQE (France),
Energy Star for Data Centres (which considers operational ef-
ciency only),
NABERS (Australia),
CASBEE (Japan),
Green Mark (Singapore),
*Corresponding author. Operational Intelligence, 74 Kelvedon Close, Kingston
upon Thames, Surrey KT2 5LF, UK. Tel.: þ44 (0) 7739 019960.
E-mail addresses:,
(B. Whitehead).
Contents lists available at ScienceDirect
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journal homepage:
0360-1323/©2014 Elsevier Ltd. All rights reserved.
Building and Environment 93 (2015) 395e405
Green Star (South Africa),
ESTIDAMA (Middle East),
CEPAS (Hong Kong),
BEAM (Hong Kong),
SBAT (South Africa), and
Green Globes (Canada).
The Australian tool, NABERS, can be used to rate one of three
components eIT, services (to support the IT), and the facility as a
whole. The method is different from other BEAMs because it
benchmarks the greenhouse gases emitted by each component
over a twelve-month period of operation [4]. Likewise, Energy Star
for Data Centres can also be used to rate the energy efciency of
facilities and monitor greenhouse gas emissions. It provides a rat-
ing from 1 to 100 and awards an Energy Star certied building
designation for any building that achieves a score of over 75; to date
41 data centres have been certied [5].
2.1. Evaluation of building environmental assessment methods
Specic concerns with the validity in application of BEAMs to
determine the sustainability of a structure are prevalent in recent
There are many studies that compare existing BEAMs in an in-
ternational setting [6]. Considering only the energy aspect of the
methods, in 2008 Lee and Burnett [7] concluded that although the
baseline performance of buildings using BREEAM, LEED and HK-
BEAM were comparable, BREEAM set the most difcult targets.
However, by 2012 Lee [8] reported that LEED now set more strin-
gent energy targets due to changes in the method. Nonetheless the
overall results were still comparable. In 2012 Ng et al. [9] compared
carbon emissions between methods nding varying results, a
concentration on operation and the need for a common standard to
evaluate carbon emissions of a building. Most comparisons, how-
ever, are generic and although different stakeholders have
completed them, provide similar comparisons and conclusions as
discussed below.
BEAMs have had a positive impact on the construction industry
[10] by raising awareness of the environmental impact of buildings
and sustainability [1,3], and by driving the reduction of environ-
mental impact [11]. However, they were originally designed to
assess the environmental impact of buildings [12], and as the
paradigm has shifted away from environmental impact towards
sustainability, a best tapproach [1,3] has seen them adopted and
adapted [12,13] in an attempt to encompass the complexities of
sustainability ean approach considered by many to be an over-
simplication of the problem [1,3,14]. Indeed, Pope et al. [15]
described BEAMs as rating systems that look to minimise or avoid
impacts, rather than determine whether a building is or is not
sustainable [14,16].
Consensus-based weightings, which are complex and inexible
[10], are intrinsic to both LEED and BREEAM, which Trusty and
Horst [17] and Cole [1,3] both argue reduces the scientic rigour of
the methods. Indeed experts from different sectors rarely come to a
consensus [18]. However, recent comparisons using statistical
analysis show this division is no longer so apparent, with Lee [11]
noting the achievement of moderate consensus on weightings
and rankings across the ve schemes studied.
More worryingly, is their apparent acceptance as conventional
environmental wisdom[17]. Trusty and Horst [17] highlight how the
award of credits for recycling is not always correct. For example, it's
noted that although recycling halts waste to landll, without
scientically determining the energy used and emissions produced
from both the scenarios (landll and recycling), it cannot be taken
for granted that recycling is the more environmentally benecial of
the two in every case [17]. Without considering the subject more
holistically, the nal outcome is not necessarily the most sustain-
able. Indeed, in BREEAM Data Centres [18] credits are awarded for
the lowest discounted life cycle costs (BREEAM credit Man 12), even
though this could penalise alternative technologies. These studies
highlight the intricacies and interrelationships between impacts on
the environment [17] and show the need for a system that does not
assess them independently [19].
Pope et al. [15] notes that BEAMs look to minimise unsustain-
abilityrather than create sustainability. Furthermore, by the award
of prescriptive credits, they have produced a culture of points
chasing[3,16] and gaming[1], where designers go for easily
obtainable credits over high-value credits that offer big longterm
benets [18]. They are effectively being used as design tools rather
than rating systems [1], and worryingly, studies of the total life
cycle embodied impacts of major building materials have shown
that halving the values found would yield no additional credits [17],
questioning their ability to fully assess the sustainability of a
3. Life cycle assessment (LCA)
The previous discussions show that there is no mechanism
currently employed by the industry to understand the total life
cycle impact from decisions made during the design and operation
of facilities. To truly assess environmental sustainability, a life cycle
approach is required that considers the performance of a building
from its manufacturing to eventual disposal, and for more than just
single issues like energy or carbon. This is not a new viewpoint, and
was already set out by the 2002 Johannesburg World Summit,
which called for a life cycle approach to support models of sus-
tainable consumption and production [20]. Moreover, studies of
buildings show that the greatest impacts on human health and
toxic releases are during the embodied phase, while the greatest
impacts from energy and the resulting GHGs are during the oper-
ational phase [21]. Omitting either phase would therefore be
LCA is a systematic tool for assessing iteratively the impact a
product, process or service has on the environment [22] as shown
in Fig. 1. Through the compilation of an inventory, an LCA looks at
the products and processes contained within a system, from the
extraction of raw materials through manufacturing, transportation,
operation, and eventual disposal [23] efrom cradle to grave. The
assessment uses functional units, which enable designers and en-
gineers to compare design choices based on their potential impacts
on resource use, human health, and ecology [24].
There are three general types of LCA: process-based, input-
output, and hybrid [25,26] which can be completed to varying
degrees of accuracy, from screening to full-blownprocess-based
(detailed) studies [22,27]. Screening LCAs provide an estimated
picture for the environmental impact. They make use of process-
based LCI data from previous studies held in databases, and
where data does not exist, approximate components to the nearest
comparable option by using surrogate LCAsas proxy data [28]. For
example, steel produced in Germany could be used to approximate
steel produced in the UK. Such an LCA allows the user to under-
stand the general pattern of impact in a comparatively short period
of time, by reducing the precision of the study, and helps focus on
areas where improvements could be made.
Where there is a gap in the LCI data, or where an approximation
is not possible, or in complex studies, economic input output (EIO)
data can be used alongside the process-based data in a hybrid LCA
[25,29,30]. EIO looks at the total emissions produced by sectors
within the economy, providing data for the entire supply chain of
that product [31]. A component manufactured within a certain
B. Whitehead et al. / Building and Environment 93 (2015) 395e405396
sector, is then apportioned part of the environmental load based on
its contribution to the total value of the sector (after purchasing has
been accounted for).
3.1. Evaluation of LCA
Research into the application of LCA, and its strengths and
weaknesses, is prolic. Much of the literature concentrates on
guiding practitioners on the general theory of LCA [27e35], and
case studies, with a growing eld of research into broader areas
[36e38] such as: LCSA (life cycle sustainability assessment), LCC
(life cycle costing) and SLCA (social life cycle assessment).
3.1.1. LCSA, LCC and SLCA
LCSA is a young and growing branch of LCA concerned with the
assessment of life cycle environmental, economic and social im-
pacts. From early methods such as proto-LCA [39] and PROSA [40],
opffer [41] derived an equation for LCSA:
LCSA ¼LCA þLCC þSLCA, where LCC stands for (environmental)
life cycle costing. Though the equation suggests a summation of the
three assessments, the conceptual equation actually points to the
need for consistent system boundaries for all methods and equiv-
alent product systems, in an attempt to mitigate double-counting
[42]. Much of the literature concentrates on the general theory of
LCSA [41,43]; and the research and efforts needed to make the
method practical [36e38].
Many of the problems that exist for LCA remain within this
framework such as a lack of data [44]. In addition, the relative in-
fancy [45] of SLCA means that there is no conclusion on a common
set of indicators, and very little inventory data [43], which make the
method time-consuming. Kl
opffer [41] addresses the need for
clarity in whether all three life cycle assessments should be
completed or whether a single life cycle inventory should be
completed with LCC and SLCA included as additional impact cate-
gories, concluding the use of three separate methods.
SLCA is the consideration of social impacts over the full life cycle
of a product, or process. It is in its infancy[45] compared to ELCA
[46], and there is still little experience with the use and imple-
mentation of it[47]. Social impact is difcult to quantify and as a
result there is not one singularlyagreed method. Methods exist that
use quantitative indicators such as Weidema [48], Hunkeler [45],
but so too are there methods that suggest semi-quantitative [49]
and qualitative indicators. There is little agreement in current
literature as to a single method of assessment, and as a result
different methods provide different results. However, more
recently the creation of the Social Hotspot Database [50], and the
UNEP-SETAC guidelines [51] have begun to give data and stand-
ardisation to the method.
A number of methods and models exist for the assessment of the
economic dimension of sustainability such as cost benet analysis
and eco-efciency analysis (CALCAS, 2009a), however LCSA [41]
specically calls for LCC [42,52].
LCC takes into account any capital costs arising from the con-
struction, manufacturing, operation and maintenance, and the end-
of-life including any residual values [53] (BSI, 2008). It is pertinent
to note that LCC is different to whole life costing (WLC) in which
externalities, non-construction costs, income and other intricacies
of the economy are included. LCC, on the other hand only includes
internal costs directly covered by actors esuch as suppliers and
users ewithin the product life cycle to avoid double-counting of
environmental impacts [42]. However, environmental life cycle
costing [54] eas referred to in the equation for LCSA eincludes
externalities that are anticipated to be internalised in the decision-
relevant future[55].
Similar challenges to the adoption of LCC exist as for LCA and
SLCA, including quality of data and difculties with allocation [56];
with additional volatility from the need to select appropriate dis-
count ratesand currencies [56,57]. LCC differs from LCA and SLCA
in the omission of an LCIA from the process as the assessment uses
one single common unit emonetary value ebut enable LCSA all
three should exhibit a consistent product system [56].
3.1.2. LCA
The literature tends to be in agreement on the issues that make
LCA difcult to apply, and the strengths that outweigh these
weaknesses. Concerns with LCA were well reviewed in the litera-
ture by Rebitzer et al. [27],Kl
opffer [39], and Reap et al. [33,34] and
subjective weighting;
poorly dened functional units and system boundaries;
difculty in avoiding allocation;
the use of cut-off criteria that omit important ows;
uncertainty in interpretation decisions;
difculty in data collection and poor data quality in LCI and
the difculty in translating emissions to environmental impact;
the omission of spatial variations.
In 2009, research by CALCAS [36e38] summarised similar issues
backed up by numerous other studies with similar conclusions,
many of which remain evident today as discussed by Cooper and
Kahn [58], and Rack and Valdivia [59].
Most case studies focus on components and construction ma-
terials within buildings such as heating and air conditioning
[23,60,61] servers [62] network switches [63] and building
Fig. 1. The four steps of a life cycle assessment.
B. Whitehead et al. / Building and Environment 93 (2015) 395e405 397
materials [64], yet studies into different construction types and
whole buildings have become ever more prevalent [23,65e68].
Nonetheless, because buildings consume 40% of total global energy
[26], there has been a focus on lifetime energy consumption.
Importantly, there is little evidence of research that considers
detailed LCA for buildings with the inclusion of the building ser-
vices [65]. Some include the operational impact, but few include
the impacts embodied from the manufacturing, replacement,
modications and disposal of the components [64]. When consid-
ering a data centre ewhere components are replaced frequently
and on a large scale ethis is a crucial omission. Studies for con-
ventional buildings show that material impacts from components
within a building can have a marked inuence, and their omission
from LCA studies is one of the major deciencies of simplied LCAs
Data centres are buildings of extremes, and although opera-
tional energy is extremely high, the replacement of IT equipment
every three to ve years [69] also results in huge numbers of
components, all with an embodied impact. Additionally, as the
operational phase becomes more efcient, this embodied impact
will become more relevant [21], particularly if its impact is not
understood and no attempts are made to improve it. Furthermore,
there is a distinct lack of LCI data for building services [65], and
many of the studies thatdo take consideration of these components
are based on streamlined approaches.
As already established, many building studies are incomplete,
for example Verbeeck and Hens [64] note the common omission of
impacts from the replacement of components or modications of
buildings during their operation. Bilec et al. [29] further note the
frequent omission of the construction phase; Carpenter et al. [70],
the management of construction and demolition debris; and Mar-
tinez et al. [71], the inadequacies of most end-of-life scenarios due
to the complexities of the management routes.
A key barrier to the application of LCA in any industry is the lack
of availability of data, particularly for the building service and IT
components; and for the construction and demolition stages.
Future work needs to address this shortage so that data is available
to the same extent as in the construction material industry. Here,
the award of BREEAM credits in return for low life cycle impacting
materials has seen the market adopt the method, and helped to
create a competitive edge for the manufacturers. The inclusion of
further components within these credits would therefore help to
create this data.
The need to deal with complexities of the method, such as
weighting and allocation, can be reduced by the development of
building models and LCA tools by environmental impact experts.
Creating a tool that applies the same model each time, opens the
method up to a far wider audience of non-environmental experts.
With a tool in place, benchmarks and a rating system based on LCA
can be established. A rating system, which is already an accepted
method, would remove the need for the majority of building de-
signers to run LCA models at all. Instead designers and operators
would design their buildings according to the benchmarks pro-
vided by the method.
Regardless of the issues with LCA, it remains a widely adopted
and accepted method for environmental impact assessment.
Beyond the recognition that many stages are being omitted, there is
also evidence that there is a growing demand for designers to go
beyond component-level LCAs to consider the sustainable con-
struction of entire buildings. Further to the ISO standards for LCA
[24,72], Technical Committee CEN/TC 350 (Sustainability of Con-
struction Works) has produced a set of standards that builds on ISO
14044 with specic reference to construction works [73], and is
working on further codes for the assessment of social (prEN 16309)
and economic (prEN 16627) impact eall with an LCA focus. In
addition, it is apparent from the release of The Green Grid [74]
guidelines for data centre LCA, and harmonised standards for the
LCA of ICT equipment (again based on ISO 14044) in ETSI TS 103 199
[75] that the application of LCA to buildings and data centres is
becoming more prevalent.
3.2. Full life cycle impact of energy in data centre components
Continuing the focus of data centre metrics on operational en-
ergy, early life cycle studies of data centres have drawn particular
conclusions surrounding energy.
According to Mahadevan et al. [63] and Liu et al. [63] when
considering products that require energy to run, the energy con-
sumption in operation dominates. Indeed Van Ooteghem and Xu
[76] and Ramesh et al. [77] both found that operational energy
accounted for 80e90% of the building impact. Nonetheless, it is
noted that energy is only one part of a bigger picture that includes
energy demands associated with the full life cycle of a data centre,
and the production of GHGs, air pollutants and toxins, as well as
impacts on natural resources, global warming, society and the
economy emost of which are not represented in current meth-
odologies [78].
The IVF Industrial Research and Development Corporation [79]
found 80% of energy and carbon came from the operational phase
of a computer, which can be assumed broadly equivalent to a
server, with the remaining 20% from pre-use and decommissioning,
as shown in Fig. 2. In addition operational gures for a standard 50-
year building life cycle yielded values of between 70 and 80% of the
overall impact [63]. While the gures appear conclusive, by
considering only operational energy future legislation could
recommend old be replaced with new, irrespective of the embodied
impacts that replacements yield.
Work by Mahadevan et al. [63] supports the need to consider
the full life cycle of IT components and data centres. A study into the
life cycle energy use of network switches projected that as network
equipment becomes more operationally efcient, the embodied
stage will play a larger role in the full life cycle. If the embodied
stage is not fully monitored, there could therefore come a point
where it goes unnoticed that it has become the biggest contributor
to the life cycle [21,73]. Indeed the inadequacies of considering only
the operational phase of IT components without full life cycle
studies [80], and consideration of impacts beyond energy
[74,83,84] have both been discussed at length in the literature.
Discussion of the literature emphasises the need to consider all
stages with careful consideration of the degree of accuracy
3.3. The full life cycle impact of data centres
Scientists at HP Labs have led research into the life cycle impact
of data centres, and their work dominates this area. Data centre life
cycle assessment has largely focused on the energy consumption
(embodied and operational) of IT and M&E infrastructures, but
often at the expense of the built structure, generally considered too
small in comparison [63], rarely are all considered together.
Research by Shah et al. [75], however, highlights the need for more
work in this area, suggesting a hybrid approach eas used by Bilec
et al. [29] ethat combines EIO LCA with a process-based analysis to
estimate the full life cycle impact of data centres.
A simplied study by Shah et al. [75],ofactional data centre
using such a method, found that the IT equipment and cooling
infrastructure contributed the greatest portion to the full life cycle
of each of the four assessed impacts eenergy, global warming
potential (GWP), toxic releases and PM-10 emissions. Unlike when
considering energy, embodied impacts for all infrastructures
B. Whitehead et al. / Building and Environment 93 (2015) 395e405398
(compute, cooling, power and building) were found to be greater
than operational impacts when considering PM-10 pollutants and
toxic releases (Fig. 3), emphasising the complexities associated
with dening one part of the life cycle as the biggest offender [75].
Furthermore, the case study showed that for the built structure,
all embodied impacts were greater than those during operation
[75]. The research also showed that by reducing the amount of IT
equipment (through virtualisation and extended lifetimes),
embodied PM-10 pollutants could be reduced by as much as 20%, as
opposed to only 7% through retrotting an old structure and leav-
ing the IT equipment as it is [75]. This is important to note, because
it is likely that intution would lead designers to concentrate on the
construction phase where emissions are known to be high.
Further studies by Shah et al. [85] into the sources of variability
in data centre LCA looked to identify parameters that have the
largest inuence on the overall environmental impact, and produce
impact factors to simplify the application of LCA to data centres. The
study concluded a similar share of impacts between the embodied
and operational phases, in the same areas of concern as previous
studies [75,82]. Moreover, a comparison of GHG emissions from the
model with three other studies found the impacts were within 15%
of each other. The study concluded main environmental signi-
cance came from the electricity mix and IT capacity. It also found
that the level of redundancy and thermal management contributed,
but to a lesser extent.
In particular, the relevance of electricity mix found by Shah et al.
[82] is strengthened by the research of Honee [86] in Sweden. The
research found embodied emissions due to capital infrastructure
was 33% of the overall impact [83], much higher than other studies,
because of the clean mix of electricity present in the country.
The Shah et al. [82] study is interesting, because a number of
simple impact factors are created from the results, which have been
validated against previous research. However, in an attempt to
promote the application of LCA in data centre design, the factors
reduce the number of parameters to only those that currently have
inuence on the environmental impact of the data centre. This is an
important step, but if used in isolation, eliminates the ability to
continually monitor the total impact, and reduces their applica-
bility as a detailed design tool.
The current limited literature acts as a good foundation for more
detailed benchmarking studies, and agrees that by considering
operational energy alone, the true sustainability of data centres is
not being assessed. These existing studies, however, can be greatly
improved upon with the collection of more detailed data from
existing buildings.
Finally, the literature shows the growing need for comprehen-
sive LCA benchmarking of data centres, and although simplied
impact factors have been created [82], there is still a need for an all-
inclusive approach. This would allow the life cycle impact to be
monitored to ensure shifts in impact do not go unnoticed [35,64],
and if adopted early enough in the design process, could provide
more opportunity to inuence the environmental impact [28,87].
4. The application of LCA to BEAMs
One of the main strengths of BEAMs is the award of an end
rating. The greatest concern, however, is their inability to capture
the full life cycle of structures [88], particular in data centres.
Currently, designers of data centres in the UK can only indirectly
consider embodied impacts through use of the BREEAM Green
Guide to specication, which provides life cycle environmental
rankings for the impact of construction materials [2]. The guide,
however, does not include IT equipment which is replaced every
three to ve years in a data centre, and which was shown by Shah
et al. [75] to greatly affect environmental impact. Indeed, it does not
consider silicon-based components, which are known to have a
large role to play in the embodied impacts of a data centre [89].
Further scrutiny of the credits shows that credits for IT equip-
ment are awarded in Ene 22 [2] if they are procured and run in line
with the EU Code of Conduct on Data Centres [2], with no consid-
eration of their embodied impacts. The scheme continues to place a
high relevance on health and wellbeing credits, evenin data centres
Fig. 2. Operational and embodied impacts of a computer (a) and a building (b).
Fig. 3. Embodied and operational impacts from Shah et al. study [75].
B. Whitehead et al. / Building and Environment 93 (2015) 395e405 399
with small associated function areas and limited staff, many of
which are prescriptive [16] and considered less reliant on scientic
Most importantly, although credit Ene 5 [2] allows three credits
for the use of low or zero carbon technologies, it only provides a
single additional exemplar credit if a contract is taken out with an
energy supplier for electricity from a 100% renewable source.
Considering the signicance of the electricity mix to the overall
impact of a data centre found by Shah et al. [82] and shown in
section 3.3, this credit allocation appears inadequate.
In response to UKGBC (UK Green Building Council) members
calling for the inclusion of embodied impacts, the most recent
BREEAM Consultation Paper [18] concluded the need to move the
mass market forward in terms of integrating sustainability in the life
cycle of buildings. Although there was no solution to this at the
beginning of the last decade [17], UK-GBC members were still
debating the issue in 2010. Indeed, members were split between
the award of credits for low embodied carbon strategies, or a rating
system based on LCA [18], and to date no decision has been made.
Trusty and Horst [17], Watson and Jones [90], Cole [1], Haapio
and Viitaniemi [12] and Biswas [91] have all considered the appli-
cation of LCA to generic BEAMs to fully appraise building sustain-
ability. However, Haapio and Viitaniemi [12] concluded that the
transformation of building environmental assessment tools
(including BEAMs) into sustainability assessment tools was still far
from fruition. Many of the studies highlight the need to integrate
such a system into some sort of 3D software and BIM ebuilding
information modelling [87,88] eto streamline the process [16,92],
yet this is only one step in the complex process of applying LCA to a
rating system.
Historically, embodied impacts have been ignored because
operational energy is known to be far greater than embodied en-
ergy [63]. Yet this has meant that other embodied impacts, which
are now shown in the literature to be of signicance, have also been
ignored [17,75]. Other barriers to the inclusion of LCA in BEAMs
include the poor quality of LCI data, and the lack of relevant case
studies for benchmarking [17]. However, there is general agree-
ment in the literature that the consensus-based nature of the sys-
tems needs to be removed, along with the use of prescriptive
credits, and the assessment moved to an LCA approach that looks to
minimise life cycle ows [17]. For this to happen, benchmarking is
5. LCA building tools
So far, the review of literature has been concerned with the
omission of LCA from the basis of BEAMs because of one very
important reason: BEAMs provide an end rating for building per-
formance, and it is this aspect that has seen their widespread
adoption. The rating provides an intangible benet that allows
clients to market their building as sustainable, and command
higher prices for their building stock. Nonetheless, the design team
uses them more as a design tool [1] than a rating method, and for
this reason it is apparent that a tool based on LCA is incredibly
A number of building environmental assessment tools (BEATs)
already exist that focus on LCA and buildings as reviewed by
Forsberg and Malmborg [13], Seo et al. [93], and Haapio and Vii-
taniemi [12]. The strengths and weaknesses in these papers are
discussed below.
Fig. 4. BEES online software [94].
B. Whitehead et al. / Building and Environment 93 (2015) 395e405400
The BEES (Building for Environmental and Economic Sustain-
ability) online software tool, shown in Fig. 4, allows users to assess
the full life cycle environmental and economic impact of over 230
building products and assembly [21,90,94]. Although the tool pro-
vides comprehensive results for a wide range of impact categories
[90], the database is limited and only includes entries for one
building service ethe plumbing system eand omits impacts from
construction and demolition [12,13].
Envest 2 is an online tool from BRE that allows users to assess
the environmental impact and differs from others by including
whole life costing of construction materials and the energy
consumed in operation [95]. Although the tool considers all life
cycle stages [12,90], including estimations for the energy consumed
for heating, cooling, and operating the building, it cannot handle
the energy-specic nature of data centres, and does not include the
embodied impact of the energy consuming components or their
In Australia, ENVEST Au is a prototype tool that includes the
same impacts as the UK version, although it has not been based on
Envest 2 [96]. Its interface, shown in Fig. 5, is more sophisticated,
and the energy consumption is inputted by the user as opposed to
being estimated by the tool.
The tool is user-editable to allow for project-specic data, and
contains life cycle economic as well as environmental impacts. The
tool is the most advanced of the options, but only relevant to
buildings in Australia.
Athena Impact Estimator is a free desktop tool that functions
much like ENVEST, and supersedes the Athena EcoCalculator [97].
Users input information on the building geometry to dialogue boxes
as shown in Fig. 6, and the main life cycle stages (apart from the end
of life [90]) for a number of impact categories are assessed. It origi-
nally did not include the use phase [12], but has been improved to
include operational energy consumption. The tool is constrained to
structural components and only has spatial relevance in US and
Canada, but the user does have exibility to add materials.
The literature reveals many other BEATs including Eco-Quantum
in the Netherlands and EcoEffect in Sweden [88,98], with some
combining existing methods and simulation tools such as BSim
[99]. Some include consideration of the three pillars of sustain-
ability eenvironmental, social and economic efor example SBTool
[96,100] (which assesses the impact of building materials and
operational energy, but not the embodied impact of building
equipment such as servers) and BASF SEEBALANCE from the
chemical industry [101].
Others provide a very basic database and allow for screening
LCAs, for example the ABB tool LCALight [102], whilst others only
consider ICT, like eL-Platform, which focuses on the supply chain
[103] and the Eco-Impact Evaluator by iNEMI [104]. Furthermore,
many are harnessing the benets of building information model-
ling (BIM) to streamline the process such as the integrated BIM-LCA
model described by Dawood et al. [89] and Russell-Smith and
Lepech [105].
Fig. 5. ENVEST Au [96].
Fig. 6. Athena impact estimator [97].
B. Whitehead et al. / Building and Environment 93 (2015) 395e405 401
More specically EETCO ean estimation and exploration tool
used to provide qualitative trends of server decisions on the total
cost of ownership [106] elooks at the carbon emissions and cost
implications of data centre design choices, while ASTRO [107]
provides an integrated environment for the assessment of data
centre reliability, dependability, and LCA for power and cooling.
Haapio and Viitaniemi [12] provide the most important con-
clusions on the most useful BEATs, and although the amount of
tools has increased since the study, the outcomes remain largely
unchanged. They conclude the wide differences between the tools,
which satisfy different, needs, different pillars of sustainability, and
assess different types of buildings, in different regions and for
different cultural factors. It is therefore almost impossible to
compare tools and rate one as better than the other. Rather, each
tool is relevant to a specic problem, and it is down to the user to
research and understand these differences [12,13,90]. In cases
where multiple tools are available for the same problem, there is
concern that the tool that provides the most onerous result will be
adopted [12]. If this result is due to errors that are not disclosed,
then it can create a false view of the assessed building [12].
Although there is strong evidence for a number of LCA tools,
none have the full capacity to assess the life cycle impact of a UK
data centre and all the various components contained within it. In
particular, most tools that consider service life use a predicted
lifetime [13], and do not thoroughly assess maintenance and
refurbishment [12]. In data centres, replacement of components is a
large factor in the impact, and its omission/limited inclusion from
tools is a real weakness.
6. Conclusions
The conclusions in this section build on those made in part 1 of
the paper. It is evident from the review of literature, that the data
centre industry is preparing itself for a paradigm shift from one
focused solely on single issues at one point in a facility's lifetime, to
a more holistic whole life approach.
In an attempt to consider more issues, designers have turned to
BEAMs such as BREEAM. BEAMs go beyond metrics to consider
more than one issue, awarding credits for the performance of
buildings against benchmarks within a range of impact categories.
These credits promote reduced environmental impact, and
amongst many other issues, consider embodied impacts (largely
omitted in the metrics) of certain materials used to construct a
building [2]. However, the partial inclusion of life cycle approaches
in BEAMs, which omit ICT equipment that is replaced every three to
ve years [66], batteries every ten years and building services every
twenty years [53,108] from life cycle credits, means that BEAMs
could be neglecting a signicant part of the environmental picture
that is yet to be fully supported by research. Indeed, there is no
quantitative evidence in the literature that supports the omission of
these components, and as such this approach appears awed. It is
therefore apparent that there is a need for more detailed bench-
marking of the life cycle impact of data centres.
Moreover, because of the prescriptive nature of these methods,
any design using an approach that is not included in the framework
to reduce a building's environmental impact, could appear less
environmentally sustainable than one with exactly the same
impact but designed according to the BEAM criteria [17]. This is
combated by the option to apply for innovation credits; however,
they are limited in number and time-consuming to achieve.
Furthermore, environmental impacts are interrelated. For
example, improving operational efciency of the energy con-
sumption could result in higher manufacturing impacts [75].To
consistently assess the interlinked nature of environmental impacts
of a data centre, it is therefore important to consider all potential
impacts, in all life cycle stages and for all components [75]. By doing
this, an understanding can be gained of the effect of an improve-
ment in one life cycle stage, or of the reduction of an emission on
other stages and other emissions.
Although it is clear that data centres are operationally high
energy consumers, the considerable efforts made by the industry to
improve their energy efciency means that it is quite plausible that
in the future, operational energy use could decrease in proportion
such that the greatest environmental impact in a data centre would
originate from something other than operational energy con-
sumption [63]. Without benchmarks and a method and tools to
monitor this, any shift in impact is likely to go unnoticed [107].In
addition, the increasing prevalence of literature on the application
of LCA to data centres and their components indicates the growing
interest in multi-issue environmental impact over a building's full
life cycle. It is therefore concluded that to support the recent release
of standards aimed at the industry's adoption of LCA, a holistic
approach to monitoring environmental impact, such as life cycle
assessment (LCA), is therefore required [107] to establish environ-
mental hot-spots and evaluate the various trade-offs.
Beyond the benchmarking of the data centre life cycle impact,
there is also the need for a tool for the application of LCA to data
centres, and in particular screening tools to detect trends [109] and
to minimise the risk of negative impacts going undetected.
Research into LCA tools was found in abundance in the litera-
ture, many of which have relevance to whole building design. None,
however, can manage the bespoke nature of data centres, and as a
result it is still difcult for the industry to apply this complex
method in a time-effective manner. It is therefore evident that
there is a need for streamlined tools that are built on comprehen-
sive and detailed frameworks, and that can be used by non-experts.
With these tools in place, data centre life cycle impact can be
optimised at the earliest stages of design, providing the greatest
opportunities to minimise environmental impact. Furthermore, if a
rating system based on LCA is to be achieved, these tools are
imperative to enable mass benchmarking.
6.1. Recommendations
Future work to enable widespread adoption of LCA by the data
centre industry should focus on:
LCA benchmarks for existing data centres using existing data.
Development of a tool that allows non-experts to gain an un-
derstanding of the impact of their facilities in a short period of
Development of an LCA rating system based on benchmarks.
The rst part should focus on the development of a life cycle
model for an existing data centre, along with an investigation of the
results achieved from running an LCA of the system. The systems,
sub-systems, components, and materials to be included in the
model need to be established, through the detailed exploration of
the engineering design and operation of data centres. A bill of
quantities (BoQ) should be established for the main infrastructures
of the facility, and an LCA model built using datasets available in
LCA software. Due to the lack of data, proxy data should be used (in
a screening LCA) to enable the industry to understand the general
pattern of impact and provide a basis from which more detailed
assessments can be run in the future.
A key to the wider adoption of LCA, in all industries, is the
availability of more data. For the construction industry, which in-
volves extensive materials and processes, the ease with which this
data can be accessed is imperative. This could be achieved by the
creation of a system in which materials, components, and
B. Whitehead et al. / Building and Environment 93 (2015) 395e405402
machinery are delivered to site with their cradle-to-gate life cycle
impact embedded in a barcode, QR (quick response) code or chip.
Such a system would not only provide information, it would also
advocate more sustainable practices, and create a competitive
sustainable market. Furthermore, as suggested by Norris [110] for
social impacts, the life cycle attributes of materials could be pub-
lished on the semantic web, the web marked up with (searchable)
metadata[53], making the data both free and available, much like
technical product information is now, when looking for a
The results of the LCA will provide a benchmark for the industry
that goes beyond the detail of current studies to include every
component of the data centre without exception. It will also
establish the basis for a framework to which more detailed and
accurate LCI data can be added as it becomes available. For example,
with the creation of the EDE metric by The Green Grid [111],itis
likely that more manufacturers will conduct detailed LCAs of their
servers to allow them to report on the metric. The resulting data
from these studies can be included in the LCA framework, which
will allow for more accurate vendor-specic assessments.
Importantly, the model will also provide a framework that fa-
cilitates the continual assessment of energy consumption once a
data centre is in operation, and allow users to understand the
impact of componentry refresh over the full life cycle and for
numerous environmental issues. Indeed, servers are often replaced
because of technological obsolescence, as opposed to them reach-
ing their end of life. By providing a framework, the full impact of
this behaviour can be better understood.
The second tranche of work should focus on development of a
tool that links to the LCA model, and enables engineers to consider
the environmental impact of design decisions without opening any
LCA software, therefore greatly reducing the complexity of
completing an assessment. The tool will also enable benchmarking
of further facilities, which are required to ensure a rating system
and facility label can be achieved in the future.
It was noted that current tools cannot assess fully the bespoke
nature of data centres and that they rely heavily on users inputting
each value by hand. Furthermore, web-based tools and those based
on dialogue box data-entry often require more maintenance to
ensure that there are no bugs in the code, and additional user
rights. The aim of the tool should therefore be to provide a simple
way for design engineers and data centre operators to quickly
evaluate the life cycle impact of the decisions they make during the
design and life time of a facility. Aspects of the tool that are
considered important to promote its adoption and reduce its
complexity are therefore:
a computing environment familiar to designers and operators
such as Excel;
easy linking to QS (quantity surveyor) information to eliminate
hand entry of
quantities and costs and to speed up the LCA process;
an environment that allows for continued monitoring
throughout the life cycle,
for example by inputting real-time energy consumption and
material impacts
from system upgrades and refresh during operation; and
a format that requires little additional technical support because
of a minimised
level of coding, and reduced need for dealing with bugs and
software problems.
With a tool established, benchmarks created from its use can be
used to establish an LCA rating system. This will ensure that
facilities with lower life cycle impacts will gain a rating based on its
life cycle impact, irrelevant of how it is achieved.
Finally, it is prudent to note that whilst the aim of the tool is for
the LCA of data centres, its applicability goes far beyond, and in the
future could be applied to all commercial buildings.
This paper has been developed with the nancial support of the
Engineering and Physical Sciences Research Council (EPSRC) (EP/
H50169X/1) nd HP; who have also gone to great lengths to share
their knowledge and expertise in the elds of data centres and
sustainable IT. Additional support and review of work was provided
by supervisors: Dr Robert Tozer, Dr Alan Dunn and Sophia Flucker.
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... For example, carbon emissions embodied in the purchased servers and the construction of data centers should both be included in SCOPE3 Emissions. To accurately calculate such carbon emissions, sophisticated Life Cycle Assessment (LCA) of a data center must be adopted [21], which is extremely time and cost-consuming. Due to the opacity of manufactural and operational information of a data center, only a few work has been conducted in the LCA of a data center [21]- [24]. ...
... To accurately calculate such carbon emissions, sophisticated Life Cycle Assessment (LCA) of a data center must be adopted [21], which is extremely time and cost-consuming. Due to the opacity of manufactural and operational information of a data center, only a few work has been conducted in the LCA of a data center [21]- [24]. According to the reported results, the majority of the authors discovered that carbon emissions from daily operations of a data center accounts for the majority share of total carbon emissions, with the exception of a data center in Sweden where renewable penetration in the national electrical grid is high [23]. ...
... According to the reported results, the majority of the authors discovered that carbon emissions from daily operations of a data center accounts for the majority share of total carbon emissions, with the exception of a data center in Sweden where renewable penetration in the national electrical grid is high [23]. Fig. 4 illustrates the proportion of different scopes of emission in a data center in the United Kingdom [21]. According to Fig. 4, more efforts should be made in the data center industry to reduce and offset SCOPE2 emissions in order to achieve carbon neutrality more efficiently. ...
Data centers are carbon-intensive enterprises due to their massive energy consumption, and it is estimated that data center industry will account for 8\% of global carbon emissions by 2030. However, both technological and policy instruments for reducing or even neutralizing data center carbon emissions have not been thoroughly investigated. To bridge this gap, this survey paper proposes a roadmap towards carbon-neutral data centers that takes into account both policy instruments and technological methodologies. We begin by presenting the carbon footprint of data centers, as well as some insights into the major sources of carbon emissions. Following that, carbon neutrality plans for major global cloud providers are discussed to summarize current industrial efforts in this direction. In what follows, we introduce the carbon market as a policy instrument to explain how to offset data center carbon emissions in a cost-efficient manner. On the technological front, we propose achieving carbon-neutral data centers by increasing renewable energy penetration, improving energy efficiency, and boosting energy circulation simultaneously. A comprehensive review of existing technologies on these three topics is elaborated subsequently. Based on this, a multi-pronged approach towards carbon neutrality is envisioned and a digital twin-powered industrial artificial intelligence (AI) framework is proposed to make this solution a reality. Furthermore, three key scientific challenges for putting such a framework in place are discussed. Finally, several applications for this framework are presented to demonstrate its enormous potential.
... However, their work does not present enough details for this meta-model. Therefore, we integrated information about the energy and materials flows from an extensive LCA about a DC in the United Kingdom [11]. ...
... The study defined the functional unit "Provision of 1 kW of IT per year in a tier III facility" [11]. Consequently, the authors normalized all energy and material flows on the IT equipment's actual power (e.g., electricity: kWh/(kW*year)). ...
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According to an analysis by the International Energy Agency based on industry data from cisco, the internet protocol (IP) data traffic has more than doubled in 2019 compared to 2016. In addition to an increased number of people and devices with internet access, new trends on the application level can be identified as drivers of this exponential growth. Carsharing, Industry 4.0, or smart home applications are examples of the rising importance of the Internet within new product systems. Therefore, it is indispensable for environmental analyses to account for both, the positive and negative effects of increased internet usage. The existing approaches to account for the resource consumption of information and communication technology (ICT) equipment have different system boundaries or focus exclusively on energy intensity, what offers the basis for further development. This paper provides a new approach for the life cycle assessment of cloud-based services. The presented meta-model accounts for different access technologies and physical topologies. It is based on a literature analysis of bottom-up studies focusing on the energy intensity of the Internet. Furthermore, a new approach is being developed to integrate the carbon intensity of the manufacture of the used network equipment. The meta-model is applied to selected case studies, which reveal the high relevance of customer premise equipment and data centers in the use stage, whereas data centers seem to be the dominating element concerning the manufacturing stage.
... The study shows that non-operational emissions account for 6.5% of the total life-cycle climate change impacts of a data center. 60 We calculated that the yearly non-operational energy consumption of a data center is around 432 MWh electricity per MW of critical (IT) power based on the data from the reference, assuming a 5-year IT refresh rate as the additional data centers run intermittently. 60 ...
... 60 We calculated that the yearly non-operational energy consumption of a data center is around 432 MWh electricity per MW of critical (IT) power based on the data from the reference, assuming a 5-year IT refresh rate as the additional data centers run intermittently. 60 ...
As the share of variable renewable energy (VRE) grows in the electric grid, so does the risk of curtailment. While energy storage and hydrogen production have been proposed as solutions to the curtailment problem, they often pose technological and economic challenges. Here, we analyze the potential of data center load migration for mitigating curtailment and greenhouse gas (GHG) emissions. Using historical hourly electricity generation, curtailment, and typical data center server utilization data, we simulate the effect of migrating data center workloads from the fossil-fuel-heavy PJM to the renewable-heavy CAISO. The results show that load migration within the existing data center capacity during the curtailment hours in CAISO has the potential to reduce 113–239 KtCO 2e per year of GHG emissions and absorb up to 62% of the total curtailment with negative abatement costs in 2019. Our study demonstrates the overlooked role that data centers can play for VRE integration and GHG emissions mitigation.
... Data centres are buildings that house information technology (IT) equipment to store and process data and services such as the internet (Whitehead et al., 2015). The rapid expansion of digital technologies resulted in building many data centres on a rapid scale (Parker, 2019). ...
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The rapid expansion of digital technology used by individuals and organisations has resulted in the need for many data centres on a rapid scale. Data centres are high energy-consuming buildings during their operation. Therefore, data centres are increasingly being built in regions with good access to energy infrastructure and cold climates to reduce the cooling energy demands of the facilities. This paper presents location factors that must be considered when estimating and modelling the capital cost of data centres built outside the UK. The research presented here is based on a questionnaire survey conducted as a pilot study of an impending Delphi study. The participant's responses were obtained via an open-ended questionnaire with a cross-sectional timeframe. A thematic analysis of the responses revealed six overarching themes: ease of doing business, design, customer pricing, land, power & fibre, and supply chain. The three most dominant are land, power & fibre, and supply chain. This pilot study confirmed the knowledge gap and supported the need that further investigatory work is required. A complete Delphi study will develop the themes identified in this pilot study to achieve consensus on their significance and support an assessment of the impact of location on the modelling and forecasting of capital expenditure for hyperscale data centres.
... In addition, the production and distribution of routers, Internet access equipment, and computer are included in the system boundary. At the same time, the construction of data center infrastructure is excluded because of the unavailable LCIA data and dominance of the operational phase to the overall environmental impacts 53 . The energy intensity of the network for the video traffic class (EI network ) is calculated as follows: ...
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Since 2020, the COVID-19 pandemic has urged event holders to shift conferences online. Virtual and hybrid conferences are greener alternatives to in-person conferences, yet their environmental sustainability has not been fully assessed. Considering food, accommodation, preparation, execution, information and communication technology, and transportation, here we report comparative life cycle assessment results of in-person, virtual, and hybrid conferences and consider carbon footprint trade-offs between in-person participation and hybrid conferences. We find that transitioning from in-person to virtual conferencing can substantially reduce the carbon footprint by 94% and energy use by 90%. For the sake of maintaining more than 50% of in-person participation, carefully selected hubs for hybrid conferences have the potential to slash carbon footprint and energy use by two-thirds. Furthermore, switching the dietary type of future conferences to plant-based diets and improving energy efficiencies of the information and communication technology sector can further reduce the carbon footprint of virtual conferences.
... Finally, the endof-life recycling phase can also be tuned to be energy efficient. However, existing Life Cycle Assessments demonstrate that for data centers [151], the usage phase is responsible for the vast majority of their environmental impact, mainly due to the electricity consumption. Therefore, reducing that energy consumption is one of the most important factors to reduce the overall environmental footprint of data centers. ...
Energy consumption is an emerging concern in multiple domains and fields, including ICT and data centers. In fact, the energy consumption of data centers has drastically increased in the last decade for both hardware and software entities, especially due to the democratization of cloud services and the huge amount of transiting data. Formerly, The energy consumption was mainly related to the used hardware, and its capacity to maintain a low power consumption while achieving tasks. However, the running software is in fact as important as hardware, and is as responsible for very substantial gains or drawbacks in energy consumption.The ultimate goal of this thesis is to help developers and practitioners understand and actively think about green software design in their work, in order to reduce the energy consumption of their software and deliver energy efficient products. We thus contribute to supplement green software design knowledge.. To achieve this, we start with conducting a qualitative study with developers, to discuss the multiple hurdles they are facing and their requirements to promote green software design within companies.To reduce software energy consumption, practitioners have to measure it and track its evolution first. In our second contribution we investigate the problem of energy consumption variations. We provide guidelines on controllable factors that one could easily tune to reduce this variation and conduct steady and reproducible energy measurements.Once practitioners are able to measure the energy consumption of their software, they can work on reducing it and produce energy efficient software. Thus, this thesis delivers 3 more contributions, focusing on the Java language. The first contribution aims at helping developers choose and configure their execution environment. We identified substantial differences in energy consumption using multiple JVM platforms with different JIT and GC configurations for different use cases. The second and third contributions study the impact on energy consumption of small changes that developers often apply on their source code (code refactoring and API/methods substitutions respectively). We show through these studies that structure oriented code refactorings do not substantially alter software energy consumption. On the other hand, Java I/O methods substitution drastically changed the energy consumption depending on the use case.This thesis contributes to enrich the knowledge on green software design and provides insights and approaches to enhance the energy efficiency at multiple levels of software development.
... However, their load balancing scheme doesn't provide insights into how the load balancer evaluates the building energy demands or how the greenness of the energy supply is obtained. Using a life cycle assessment framework, Whitehead demonstrates a comprehensive data center site level life cycle costs analysis in (Whitehead, 2015). All energy use in Whitehead's models were deduced from annualized PUE values, precluding coincident energy source evaluations with their framework. ...
There is great interest in how the growth of artificial intelligence and machine learning may affect global GHG emissions. However, such emissions impacts remain uncertain, owing in part to the diverse mechanisms through which they occur, posing difficulties for measurement and forecasting. Here we introduce a systematic framework for describing the effects of machine learning (ML) on GHG emissions, encompassing three categories: computing-related impacts, immediate impacts of applying ML and system-level impacts. Using this framework, we identify priorities for impact assessment and scenario analysis, and suggest policy levers for better understanding and shaping the effects of ML on climate change mitigation. The rapid growth of artificial intelligence (AI) is reshaping our society in many ways, and climate change is no exception. This Perspective presents a framework to assess how AI affects GHG emissions and proposes approaches to align the technology with climate change mitigation.
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The report is the result of the research project "Values and Norms for the Green Transition in ‘Blue Denmark' ", which investigates the social and cultural conditions that are believed to support or impede the green transition of Danish shipping and associated sectors and organisations. The green transition has received a great deal of attention in Blue Denmark. There is wide agreement that the green transition is both necessary and urgent. At the same time, there is considerable uncertainty about which directions to follow and how to prepare best for the fundamental changes ahead. The aim of this investigation is to support and improve the work towards a green transition by analysing the concepts and different under- standings of the process involved; the new types of organisation that are required by the transition; the obstacles identified by stakeholders that can impede the process; and the forces identified by stakeholders that can support the process. The ambition is that the investigation of these experiences will help clarify the cultural and social conditions that underlie the green transition.
Digital technology and entertainment is a significant driver of electricity use globally, resulting in increased GHG emissions. Research has been conducted on electricity use associated with adigital services, but to date no complete study of television distribution has been conducted. Here we present the first assessment of electricity used for distribution and viewing of television over different distribution platforms terrestrial, satellite, cable and online streaming. We use a novel methodology that combines life cycle assessment techniques with models of the diversity of actual user behaviour, derived from detailed audience monitoring and online behaviour analytics data. This can be applied to assess overall electricity usage for a given media company's services and allows comparison of the electricity demanded per viewerhour of each distribution platform. We apply this to a representative national TV provider - the British Broadcasting Corporation – and show the mean estimate for BBC distribution/viewing electricity use in 2016 is 2171 GWh, resulting in emissions of 1.12 MtCO2e. We show that viewing over streaming, cable and satellite platforms used a mean of 0.17–0.18 KWh per device-hour (88–93 gCO2e) while terrestrial broadcast used a mean of 0.07 kWh (36 gCO2e). We identify home networking equipment and set-top boxes as key hotspots in the system, and show that though streaming is similar in impact to cable and satellite, this is because people use smaller devices to view – meaning the networking equipment in and beyond the home has a higher impact while the end device has a lower one.
Conference Paper
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For sustainable building design, computational tools, mostly in the form of simulations, are employed to determine loads and to predict systems performance typically in terms of energy use. Currently, sustainability, in the building domain, is judged by a rating system. Design choices are validated, by measuring against one. The objective of the framework is to provide a general approach to processing the informational needs of any rating system, by identifying, categorizing and organizing relevant data requirements. Aspects of sustainability that designers deal with intuitively will have a structured guideline and gauge as one selects a rating system of choice.
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Data centers operate continuously so their annual energy costs per square foot are higher than those of typical office building. One of the best ways to improve data center energy efficiency is to reduce heat loads attributed to power conversion within both information technology equipment and data center infrastructure. With an efficient UPS system, an intermediate reduction in overall electrical power demand can be achieved. Besides this, energy efficiency can be improved by optimizing air management in building, capitalizing on free cooling, efficient air handling and choosing right sized electrical and mechanical system so that they can operate efficiently.
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Using panel data for 161 countries, we explore the determinants of cross-country disparities in personal computer and Internet penetration. We find evidence indicating that income, human capital, the youth dependency ratio, telephone density, legal quality, and banking sector development are associated with technology penetration rates. Estimates from Blinder-Oaxaca decompositions comparing rates in the developed-country total to developing countries (Total, Brazil, China, Indonesia, India, Mexico, and Nigeria) reveal that the main factors responsible for low rates of technology penetration rates in developing countries are disparities in income, telephone density, legal quality, and human capital. In terms of dynamics, our results indicate fairly rapid reversion to long-run equilibrium for Internet use, and somewhat slower reversion for computer use.
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Purpose At present, many urban areas in Mediterranean climates are coping with water scarcity, facing a growing water demand and a limited conventional water supply. Urban design and planning has so far largely neglected the benefits of rainwater harvesting (RWH) in the context of a sustainable management of this resource. Therefore, the purpose of this study was to identify the most environmentally friendly strategy for rainwater utilization in Mediterranean urban environments of different densities. Materials and methods The RWH systems modeled integrate the necessary infrastructures for harvesting and using rainwater in newly constructed residential areas. Eight scenarios were defined in terms of diffuse (D) and compact (C) urban models and the tank locations ((1) underground tank, (2) below-roof tank, (3) distributed-over-roof tank, and (4) block tank). The structural and hydraulic sizing of the catchment, storage, and distribution subsystems was taken into account using an average Mediterranean rainfall, the area of the harvesting surfaces, and a constant water demand for laundry. The quantification of environmental impacts was performed through a life cycle assessment, using CML 2001 Baseline method. The necessary materials and processes were considered in each scenario according to the lifecycle stages (i.e., materials, construction, transportation, use, and deconstruction) and subsystems. Results and discussion The environmental characterization indicated that the best scenario in both urban models is the distributed-over-roof tank (D3, C3), which provided a reduction in impacts compared to the worst scenario of up to 73% in diffuse models and even higher in compact ones, 92% in the most dramatic case. The lower impacts are related to the better distribution of tank weight on the building, reducing the reinforcement requirements, and enabling energy savings. The storage subsystem and the materials stage contributed most significantly to the impacts in both urban models. In the compact density model, the underground-tank scenario (C1) presented the largest impacts in most categories due to its higher energy consumption. Additionally, more favorable environmental results were observed in compact densities than in diffuse ones for the Global Warming Potential category along with higher water efficiencies. Conclusions The implementation of one particular RWH scenario over another is not irrelevant in drought-stress environments. Selecting the most favorable scenario in the development of newly constructed residential areas provides significant savings in CO2 emissions in comparison with retrofit strategies. Therefore, urban planning should consider the design of RWH infrastructures using environmental criteria in addition to economic, social, and technological factors, adjusting the design to the potential uses for which the rainwater is intended. Recommendations and perspectives Additional research is needed to quantify the energy savings associated with the insulation caused by using the tank distributed over the roof. The integration of the economic and social aspects of these infrastructures in the analysis, from a life cycle approach, is necessary for targeting the planning and design of more sustainable cities in an integrated way.
Conference Paper
In this paper, we forecast the future carbon footprint of the Information and Communication Technology (ICT) and Entertainment and Media (E&M) sectors in the year 2020 including the ICT and E&M related impact from a networked society, i.e. a society where both people and things are connected and communicate with each other. We also discuss sector boundaries, the full impact from the networked society, uncertainty, use of the Carbon Disclosure Project (CDP) as data source and important perspectives when assessing ICT. Link to paper: Conference proceedings:
The rationale behind environmental LCC is presented, with a specific focus on key issues that one must consider prior to, and during, the assessment. Specific discussions on the appropriate system boundaries, as well as other links to life cycle assessment, are discussed. These methodological issues include the definition of the functional unit and the most appropriate means for data aggregation. The interpretation of the results and the use of portfolio presentations of LCC as a function of the key environmental impact are recommended. Input-output-based LCC is also presented and applied to the cross-cutting washing machine case. © 2008 by the Society of Environmental Toxicology and Chemistry (SETAC).