HOLISTIC VIEW ON THE ROLE OF ICT IN ENVIRONMENTAL SUSTAINABILITY

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1 HOLISTIC VIEW ON THE ROLE OF ICT IN ENVIRONMENTAL SUSTAINABILITY Slavsa Aleksc Venna Unversty of Technology Insttute of Telecommuncatons Favortenstr. 9-11/E389 Venna, Austra Abstract: Informaton and communcaton technology (ICT) has become an ntegral part of our everyday lfe ncludng socal nteractons, busness processes, technology and ecology. However, ts potental benefts and rsks for the envronment are stll not suffcently explored. Ths s manly because of the complex nterdependences between ICT and dfferent other areas of busness and socety that together buld a very complex ecosystem. In ths paper, a holstc approach that treats ICT as a part of the global ecosystem s ntroduced. Ths approach combnes data-centrc methods that are typcally used to analyze communcaton networks wth wdely applcable thermodynamc tools. The proposed approach s well suted to nvestgate complex heterogeneous systems and assess ther envronmental sustanablty. Wthn ths holstc framework, the whole lfecycle of ICT components and systems s consdered. In partcular, we brefly dscuss the applcaton of the presented approach on evaluatng the sustanablty of smartphones, notebooks, data centers, swtches and access network equpment. Addtonally, prelmnary results of an exemplary model of cloud computng use n Austra are presented. 1. INTRODUCTION Although nformaton and communcaton technology (ICT) has been makng an enormous progress for more than thrty years and has already nfluenced many areas of our everyday lfe, ts potental benefts and rsks for the envronment have ganed the nterest of the scentfc research and broad communty only snce recently. Even though many extensve studes on energy effcency of ICT systems have been carred out durng the last several years, the nfluence of ICT on the envronment has stll not been suffcently assessed and understood. On the one hand, broad and ntensve use of advanced ICT applcatons and servces promses substantal mprovements n many branches such as n ndustry, logstcs, trade, healthcare, and educaton as well as n socety. Furthermore, ICT applcatons can be used to optmze varous processes and, consequently, to support new strateges and mechansms for a sustanable explotaton of natural resources. On the other hand, the ever ncreasng number of ICT equpment and ntensve usage of ICT servces lead to a contnuous ncrease of ICT-related energy consumpton. Addtonally, the short lfetme of devces and servces cause an ncreased usage of resources, producton ntensfcaton, and more hazardous e-waste, whch can harm the envronment. The am of ths paper s to present a holstc approach that can be used to evaluate ICT systems and applcatons as well as ther mpacts on the envronment. To llustrate the applcaton of the presented approach, we show exemplary results for some selected ICT devces and systems. In partcular, we show and dscuss the results obtaned by a model of cloud computng use n Austra. 2. THE CONCEPT OF EXERGY A very useful quantty that stems from the second law of thermodynamcs s exergy. It can be used to clearly ndcate the neffcences of a process by locatng the degradaton of energy. In ts essence, exergy s the energy that s avalable to be used,.e., the porton of energy that can be converted nto useful work. In contrast to energy, t s never conserved for real processes because of Internatonal CARE ELECTRONICS Offce (2014). Ths s an authors copy of the work. It s posted here by permsson of the Internatonal CARE ELECTRONICS Offce for your personal use. Not for redstrbuton. The defntve verson wll be publshed n the Proceedngs of the Conference Gong Green CARE INNOVATION 2014, November 2014, Venna, Austra.

2 rreversblty. Any exergy loss ndcates possble process mprovements. The exergy of a macroscopc system s gven by: E x U PV T S n, (1) r r where extensve system parameters are nternal energy (U), volume (V) and the number of moles of dfferent chemcal components,.e., n, whle ntensve parameters of the reference envronment are pressure (P r ), temperature (T r ) and the chemcal potental of component,.e., μ r;. A useful formula for practcal determnaton of exergy s [1]. E x U U 0 Pr ( V V0 ) Tr ( S S0 ) r( n n r 0, ), (2) where the relatvely easly determned quanttes denoted by o n the subscrpt are related to the equlbrum wth the envronment. The exergy content of materals, E x,mat, at a constant temperature, T = T 0, and pressure, P = P 0, can be calculated from: Ex, mat ( ln 0 0 o, ) n RT0 n (3) co, In the above Equaton, c s the concentraton of the element, R s the gas constant, whle μ 0 denotes the chemcal potental for the element relatve to ts reference state. The relaton of exergy loss to entropy producton s gven by: E Ex, n Ex, T S x, loss out r, (4) where ΔS s the entropy (rreversblty) generated n a process or a system. In other words, for processes that do not accumulate exergy, the dfference between the total exergy flows nto and out of the system s the exergy loss due to nternal rreversbltes, whch s proportonal to entropy creaton. The overall exergy loss of a system s the sum of exergy losses n all system components,.e., E x,loss,total = ΣE x,loss,component. analyss has been performed n ndustral ecology to ndcate the potentals for mprovng the use of resources and mnmzng envronmental mpact. The hgher the exergy effcency s,.e., the lower exergy losses, the better the sustanablty of the consdered system or approach. Lfe cycle assessment (LCA) s a technque to evaluate envronmental mpacts of a product or a process over ts entre lfe cycle (.e., raw materal extracton, manufacture, transportaton, operatonal, mantenance, and recyclng phases). LCA analyss c provdes a system perspectve across the whole lfe tme to defne the system boundares and ad decson makng for system optmzaton and product selecton. An approach that combnes the exergy concept wth the LCA analyss we refer here to as the exergybased LCA (ELCA). Fg. 1 vsualzes the approach of E-LCA across the whole product s or system s lfetme. Snce the E-LCA approach consders all exergy nputs durng the whole lfe cycle and we assume here that there s no accumulaton of exergy, the overall exergy losses accumulated durng the product s or system s lfetme equals the total exergy consumpton. Thus, the overall lfetme exergy consumpton s an effectve measure of product s or system s envronmental sustanablty. Snce exergybased analyss s a unversally applcable method to assess process effcency, t s well suted to nvestgate the sustanablty of heterogeneous systems [2-4]. Snce recently, E-LCA has also been used to assess the sustanablty of ICT nfrastructure and applcatons [5-9]. Raw Materal Extracton Materal Transport Manufacturng and Asembly Product Transport Product use End-of lfe Transport Recyclng Materal Reuse Fg. 1: Illustraton of the exergy-based lfe cycle assessment (E-LCA): lfetme exergy consumpton flow. In general, the exergy consumed over the entre lfetme of the system (.e., the total cumulatve exergy) can be dvded nto two components. The frst component s related to the so called emboded exergy, whch s the exergy used for materal extracton, transportaton, manufacturng and recyclng. The second component s composed of the

3 electrcty consumpton of ICT equpment, whch s referred to as operatonal exergy. 3. E-LCA OF ICT DEVICES In an E-LCA, the flow of exergy s determned for each phase of a devce lfecycle. Frst, the emboded exergy of materals used to manufacture the devce s determned. Ths emboded materal exergy acts as the nput nto the system. In the study presented n ths paper, the materal nventory s performed by surveyng the raw materal composton of dfferent components. Examples of a typcal decomposton of a smartphone and a tablet PC are shown n Fg. 2 [6,9]. Smartphone Tablet PC Other 4% Plastc 3% Crcut Boards 11% Battery18% Dsplay 23% Crcut Boards 7% Dsplay 5% Glass 30% Plastc 3% Other 4% Battery21% Stanless Steel 29% Alumnum 23% Glass 19% Fg. 2: Typcal materal decomposton of a smartphone and a tablet PC. The estmaton of exergy consumpton for the raw materal extracton phase s performed on a per-mass bass and accordng to the exergy contents of dfferent materals. The values of mass-specfc exergy for varous materals are manly taken from [5, 8, 10-12]. Then, we calculate the amounts of exergy destructed durng varous LCA phases, ncludng materal extracton, transportaton, manufacturng, use and dsposal. Furthermore, the exergy content and converson effcences of dfferent energy sources are consdered [3]. As a result of the E-LCA, one can determne exergy-based sustanablty ndcators that can be used to easly compare the sustanablty of dfferent concepts, technologes and approaches. An example of exergy lfecycle of a smartphone s presented n Fgs. 3. A reutlzaton of recycled materals of 40 % has been assumed n both cases, and the mx of electrcty generaton sources s chosen accordng to the current stuaton n Austra [13]. Smlarly, we can calculate the exergy lfecycle of network equpment. An exemplary result obtaned by applyng E-LCA to a Unversal Moble Telecommuncatons System (UMTS) base transcever staton (Node B) s shown n Fg. 4. Fg. 5 llustrates the relaton between the emboded and the operatonal exergy for Node B and smartphone. It becomes evdent when comparng the overall emboded and operatonal exergy consumptons that the man contrbutors to the exergy losses of the entre devce lfecycle are the manufacturng and materal extracton processes, n the case of a smartphone, and the hgh operatonal energy consumpton when consderng a rado base staton. Ths dfference n the relaton of emboded to operatonal exergy for rado base statons and smartphones s manly due to the fact that rado base statons have several tmes longer lfecycles than modern moble devces and that moble devces are optmzed for low energy consumpton. To obtan the results presented n Fg. 5 t has been assumed that the lfecycle of a smartphone s two years, whle that of a base staton s 10 years. Thus, the specfc ssue n modern ICT systems s that new generatons of devces and technologes are launched wthn short cycles of only a few years. Even f new technologes are usually more energy effcent, both processng power and use ntensty ncrease, whch consequently lead to more or less constant power consumpton despte the contnuous mprovements n energy effcency. Another mportant ssue s the ncreased resource explotaton and envronmental polluton, due to ever-ncreasng producton volumes and decreasng lfetme, as well as nadequate dsposal of ICT hardware. These ssues can only be properly addressed usng a holstc approach that consders the whole lfecycle of products and servces. 4. E-LCA OF ICT SYSTEMS Addtonal to nvestgatng sustanablty of ICT devces, E-LCA can be appled to analyze complex ICT systems that nclude a large number of nterconnected elements. As an example of such an analyss, we present the a model that has been used to estmate the lfecycle exergy consumpton related to

4 the ntroducton and use of cloud computng n Austra wthn the tme perod from 2012 to The model comprses several submodels such as those for core networks, access networks, data centers as well as dfferent scales of enterprse computng nfrastructures for small, medum and large scale enterprses ncludng IT equpment, network nfrastructure and end-user equpment. E-LCA for Smartphone Fg. 3: An example of exergy-based lfecycle for a smartphone. E-LCA for Node B Fg. 4: An example of exergy-based lfecycle analyss (E-LCA) for a Unversal Moble Telecommuncatons System (UMTS) base transcever staton (Node B). Relaton between the emboded and the operatonal exergy for Node B and smatphone [GJ] Smartphone [GJ] Node B Emboded (Materals, Manufacturng, Transportaton, Dsposal) Operatonal (Electrcty from Grd) Emboded (Materals, Manufacturng, Transportaton, Dsposal) Operatonal (Electrcty from Grd) Fg. 5: The relaton between the emboded and the operatonal exergy for Node B and smartphone. 4.1 Network Model The network core model ncludes core swtches and routers havng capacty of about 1 Tb/s, whch are placed across Austra and connected through fber cables. As regards the operatonal phase of access networks, we used a model that has been developed and used to estmate the energy consumpton of an Austra-wde network [14]. To provde moble access to cloud users, we modeled a UMTS rado access

5 network comprsng base transcever statons (Node B) and rado network controllers (RNC) as well as servng GPRS support nodes (SGSN) and gateway GPRS support nodes (GGSN). We assumed that the wreless backhaul s realzed mostly usng mcrowave lnks (95%), but also copper cables (4%) and optcal fbers (1%) are consdered for the backhaul. The network model consders varous data on technology penetraton, market shares and populaton denstes as well as typcal core and access network archtectures. The statstcal data for Austra are obtaned from several sources such as the Statstcs Austra, the Austran Regularty Authorty for Broadcastng and Telecommuncatons (RTR), Austran network operators and the Forum Moblkommunkaton (FMK). For a more complete descrpton of the access network model and the man assumptons made for E-LCA of RAN, the reader s refereed to [5,6,14]. 4.2 Electrcty Generaton Whle estmatng the total exergy consumpton of the operatonal (use) phase, we assumed three dfferent electrcty producton sources as typcally used n Austra [13]. The consdered sources nclude hydroelectrc power plants, fosslfuel power plants and renewable (.e., photovoltac and wnd turbne) power plants. In partcular, hydropower plants play a substantal role n the Austran energy sector. As reported n [13], around 58% (41 GWh) of the total electrcty produced n Austra was orgnatng from hydroelectrc power statons n Hence, we assume that 58% of the total electrcal energy consumed by the ICT equpment s generated by hydroelectrc power plants, 35% by fossl-fuel power plants and 7% by renewable energy sources. Addtonally, we consdered the specfc exergy losses for dfferent electrcty generaton methods, both the waste of exergy due to the transmsson losses and nternal exergy destructon due to rreversbltes of the energy converson. The consdered energy effcences of hydroelectrc power plants, fossl-fuel power plants, wnd turbne systems and solar photovoltac systems are 90%, 36%, 88.5% and 25%, respectvely [3,6,8]. 4.2 Model of Data Centers For the cloud model for Austra, we assume that there are 10 medum-scale data centers, of whch 4 are located n Venna [15], and one large cloud data center. We consdered a typcal realzaton of data centers usng the three-ter archtecture. Based on the forecasts n [16-18] we defned scenaros for the development of cloud computng n Austra from 2012 untl 2020 that nclude the predcted trends n network traffc, number of users and usage ntensty. Here, we apply E-LCA to assess two types of data centers. Frst, we consder a cloud data center wth 20,000 servers, whch ncludes correspondng network equpment (swtches, routers and cablng) and N + 1 redundancy n case of power outage. There s an ar-coolng system that has a roughly constant electrcty consumpton of about 2.75 MW [14]. In ths case study, the area floor of the data center s assumed to be 4,645 m 2. The second model s for a medum-scale data center wth 185 servers and 567 kw of the total electrcty consumpton. The medum-scale data center conssts of rack mounted servers and an ar dstrbuton systems. In the estmaton of the emboded exergy, we consder addtonally to the rack mounted servers also cables, swtches, routers and server cabnets. The man assumptons made for both the cloud center and the medum-scale data center model can be found n [8]. Whle the total cumulatve exergy consumpton of the consdered large cloud data center wth 20,000 enterprse servers and assumng a lfetme of 9 years, s estmated to be around 1.5 PJ, the emboded exergy s approxmately 209 TJ. Smlarly, total exergy consumpton of the medum-scale data center s calculated to be around 20 TJ and the contrbuton of the emboded exergy s about 2.3 TJ. The manufacturng and assembly phases contrbute mostly to the total emboded exergy. For nstance, n case of the large data center, these two phases contrbute by approxmately 130 TJ, whch s more than 70% of the entre emboded exergy consumpton. Smlarly, an exergy consumpton of 1.4 TJ has been calculated for manufacturng and assembly phases of the medum-scale data center, whch s approxmately 60% of the total emboded exergy. [PJ] Large Data Center Emboded (Materals, Manufacturng, Transportaton, Dsposal) Operatonal (Electrcty from Grd) Fg. 6: The relaton between the emboded and the operatonal exergy for the large data center wth 20,000 enterprse servers and assumng 40% of recycled resources beng reused.

6 The emboded exergy loss of the large data center can be reduced to about 186 TJ by reusng 40% of the recycled materals and to 145 TJ f 60% of the recycled materals are reused. However, the most exergy s consumed durng the operatonal phase, whch accounts for about 1.3 PJ or 87% of the total. The operatonal exergy s for almost a factor of 7 larger than the emboded exergy as t s evdent from Fg. 6, whch shows the relaton between the emboded and the operatonal exergy for the large data center wth 40% of materals beng recycled. Hence, the best mprovements can be acheved by applyng technques amed at reducng the operatonal energy consumpton of data centers. 4.2 Overall Model The man components of the overall model are brefly descrbed n prevous sectons. It comprses data centers, access networks, core network as well as devces of prvate and busness users. The emboded exergy consumpton (EEC) refers to the sum of exergy consummatons of dfferent phases such as raw materal extracton, transportaton between dfferent phases, manufacturng/assembly and dsposal/recyclng. For all end-user devces as well as network and processng elements, we defne a specfc servce lfetme. For nstance, we assume that a smartphone wll be replaced by a new devce after 2 years of operaton, whle a PC s used for 4 years. A longer servce lfetme of 9 years s assgned to the network equpment. 5. SUSTAINABILITY OF CLOUD COMPUTING In ths secton, we present some prelmnary results obtaned by the model for cloud computng use n Austra that has been brefly descrbed n Secton 4. The cumulatve exergy flow from 2012 to 2020 s graphcally presented n Fg. 7. The fgure shows the flow of exergy for all phases of the system s lfe cycle ncludng the raw materal extracton, transportaton, manufacturng, operaton and dsposal. The exergy values presented nclude data centers and networks as well as devces of prvate and busness users. In ths partcular example, 40% of materal reutlzaton s assumed. The total cumulatve exergy consumpton has been estmated to be PJ, of whch 82.1 PJ (22.8 TWh of electrcty) s consumed durng the operatonal phase. Thus, the man part of the total exergy s related to the emboded exergy, whch accounts for about PJ or 65% of the total (see Fg. 8). Ths result s dfferent from the result obtaned when consderng data centers only, where 87% of the total exergy s consumed durng the operatonal phase. Ths s manly because n the overall model, end-user devces contrbute sgnfcantly to the ncrease of the emboded exergy due to ther hgh quantty and short servce lfetme. On the other hand, materal reutlzaton plays less sgnfcant role n reducng the total exergy consumpton. The total cumulatve exergy consumpton assumng 40% materal reutlzaton s PJ (see Fg. 7) and n case of 60% reutlzaton we obtaned a value of 216 PJ. Wth no materal reutlzaton at all, the estmated total exergy consumpton s 233 PJ. Hence, materal reutlzaton has a moderate savng potental of less than 10%. E-LCA for moble cloud computng n Austra from 2012 to 2020 Fg. 7: E-LCA for cloud computng n Austra from 2012 to flow nclusve prvate and busness user devces, data centers, UMTS RAN, and core network and assumng 40% materal reutlzaton.

7 a) b) [PJ] BU RAN BU PU Fg. 8: Break down of the cumulatve exergy consumpton of cloud computng use n Austra from 2012 to Fg. 8 shows a breakdown of the cumulatve exergy consumpton of the modelled cloud computng use n Austra. From Fg. 8a s evdent that the man contrbutors to the emboded exergy are busness and prvate end-user devces, whle rado access network (RAN) contrbutes most to the operatonal exergy. Emboded exergy s countng for about 99% of the total cumulatve exergy consumed by prvate user devces and for about 71% by busness user devces as evdent from Fg. 8b. Dfferently, exergy consumpton of the core network, RAN and data centers s strongly domnated by the operatonal exergy, namely 81% of cumulatve exergy s operatonal exergy n case of the core network, 96% n case of UMTS RAN and 86% n data centers. Thus, t s clear that n order to acheve maxmum mprovements n the entre system, one should concentrate on technques for reducng operatonal energy consumpton n networks and data centers, whle consderng potentals for mnmzng the emboded exergy of end-user devces. CONCLUSIONS Modern nformaton and communcaton technologes (ICT) are affectng our everyday busness and socal lfe. They also nfluence the envronment due to the broad use of ICT applcatons, ICT-related energy consumpton and an ever ncreasng number of electronc devces. In ths paper, we presented a holstc approach based on a combnaton of the exergy concept and lfe cycle assessment (LCA), whch we appled to study the sustanablty of ICT devces such as end-user devces and network equpment as well as of cloud computng on an example of a model made for Austra. Our results have shown that the mpact of ICT on the envronment grows wth tme and that there s a potental to slow down ths trend. It should be noted that we concentrated here on the mpacts related to the lfe cycle of ICT hardware and not on mpacts that result from the change n producton, transport, and consumpton processes due to the applcatons of ICT. Nevertheless, the obtaned results clearly show the need for a holstc approach that take nto consderaton the whole system, whch ncludes addtonally to data centers also the nterconnectng network and end-user devces. In order to acheve maxmum mprovements n the entre system, one should concentrate on technques for reducng operatonal energy consumpton n networks and data centers, whle consderng potentals for mnmzng the emboded exergy of end-user devces. Even though an optmzed desgn and management of data centers s an mportant step towards a sustanable cloud, the huge number of end-user devces and ther short servce tme have much hgher mpact on the overall system s exergy consumpton. It s manly because end-user devces contrbute most to the hgh emboded exergy consumpton that s related to the materal extracton, transportaton, manufacturng and recyclng processes. 8. REFERENCES [1] Socolow, R.H.; Rochl. G.I. Effcent Use of Energy, a Physcs Perspectve, Amercan Insttute of Physcs (AIP): Sprng Branch, TX, USA, 1975; p [1] Gutowsk, T.; Dahmus, J.; Threz, A.; Branham, M.; Jones, A. A Thermodynamc Characterzaton of Manufacturng Processes. IEEE Internatonal Symposum on Electroncs and the Envronment, Orlando, FL, USA, 7 10 May 2007; pp [2] Masn, A.; Ayres, R.U. An Applcaton of Accountng to Four Basc Metal Industres. CMER, INSEAD, Fontanebleau, France, 1996; pp [3] Rosen, M.A.; Bulucea, C.A. Usng exergy to understand and mprove the effcency of electrcal power technologes. Entropy 2009, 11, [4] Hannemann, C.R.; Carey, V.P.; Shah, A.J. Lfetme Consumpton as a Sustanablty Metrc for Enterprse Servers. ASME Int. Conference on Energy

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