"How green is the Internet?" summit: Research rapid fire

what we’re going to do is a series of short presentations from the speakers and we’re giving them five minutes each you know we’re not expecting in this session to be able to prevent present a full comprehensive view but we really want to give folks a snapshot of the state of research the state of knowledge and give you a flavor of some of the work that’s being done in the space and hopefully really provide a lot of useful information in terms of the topics that we’re talking about today so with that I’ll turn it over to the first speaker Eric Massenet from Northwestern University thanks thank you Michael so it’s my honor to be the first person presenter in this rapid-fire research session as someone who recently moved to academia I can tell you that rapid-fire isn’t a term that we use often in that world so I’ve had to relearn how to get to the point and get to it quickly so I hope I can do that today but what I’m gonna be talking about is a recent research project which we’re wrapping up now and we’re going to release the results of shortly which had two primary goals and this is a research project conducted by Lawrence Berkeley National Lab and Northwestern University the first goal was to put together an open platform public use model to try to capture the system’s implications of cloud-based technologies the second goal of the the project was to apply that model to answer a question such as this can cloud-based software save energy so I’m going to start with the results of our of our project so what you’re seeing here is a comparison we just did where we’re looking at president present day business software compared to cloud-based business software meaning hosting that cloud that software in the cloud as opposed to doing it in local data centers and so what do I mean by software so if you look to the the lower right-hand corner of the slide you’ll see that our scope including email productivity software this includes things like word processing collaboration and file sharing and customer relationship management software these are some of the most common software applications that are out there and as you can see from our estimated number of business users there are millions and millions of these software licenses and use out there so we had to take a systems approach as John mentioned earlier in the talk the implications of digital services require a systems perspective so we first estimated the net energy use of each one of these systems present-day includes present-day servers and data centers and so if we look at the results here sorry getting there on button you can see that we considered the any energy use of data centers the energy use of the client devices the energy uses of the devices that are used for network transmission and also the embodied emissions of all those various systems components and we compared that to a scenario where all of that software could be hosted in the cloud and we found that the savings are pretty significant so if we look at the top of the graph you can see sort of that the net change between present day and hosting everything in the cloud it’s about 300 petajoules of energy which to put that into perspective that’s the amount of primary energy it takes to generate the electricity that’s used by Los Angeles every single year so the savings aren’t trivial and where do those savings come from so one of the key mechanisms of the savings as you’ll see from the previous graph is that we’re drastically reducing the energy use associated with data centers so so how does that happen if you look at the pie chart here it really explains that the fundamental driving mechanism of the difference between present-day software which is hosted you know currently at a lot of small and efficient dispersed data centers around the country which as you can see requires millions of servers and we’re taking all of those servers and we’re replacing them with highly efficient and far fewer servers and far fewer cloud based data centers so the change in just the number of servers and the infrastructure for providing the services from those servers changes drastically when we move to the crowd to the cloud so do we know that number precisely I mean can we predict those savings precisely well not precisely and I mean I’d be remiss if I didn’t say that a lot of these models come with a lot of caveats as john mentioned earlier in his talk we’re at a sort of chronic lack of data out there but we’re trying to be as transparent as we can and showing you know based on the model which input variables are their most important for driving the results and that’s one of the major goals of the entire project is to put a public use model out there where all of the assumptions all the input values are transparent so the research community can change the assumptions they don’t like and they can involve the the model over time but that said just given this this this major driving mechanism of shifting from inefficient data centers to more efficient daters in the cloud the primary conclusion of our study doesn’t change even in the face of these uncertainties and that is that a shift to the cloud moving away from inefficient data centres towards highly efficient and far fewer data centers is likely to save a lot of energy to the US if we host our software out in the cloud so what about other cloud services software is only one case study so the important points are we always need to take a systems perspective we need to

consider not only the data centers but the client-side devices the network transmission system how people behave and so to look at other services we always have to take this system’s approach and when we look at broader cloud services such as streaming video or let’s say digital music as John pointed out the research can get immensely challenging because these systems quickly get very complex but just because the research is difficult doesn’t mean that this question goes away right so how green is the cloud this is a question that’s becoming more and more relevant because society is moving in this direction and understanding the implications of this shift both the positive implications of it and the negative implications of it are really important moving forward so if we think that you know the ship is already leaving the port a better understanding of the system will allow us to steer that ship in the right direction and the good news is there’s a lot of great research going on these days that’s focused on this question but I think all of us in this room who conduct research in the area would admit that the existing body of research is very good but it’s also very difficult to draw let’s say you know hard conclusions from that research because different studies use different system boundaries a lot of studies don’t display all of their data or their modeling methods in a fully transparent manner and even more importantly the technologies and behaviors change very quickly over time right so a study that provided very valid results a few years ago might be obsolete today just based on the pace of technology change and the way people interact with those devices so the second goal of the project was to come up with a public use model that would hopefully provide value to the research community and we’re calling that that that model clear so it’s the cloud energy and emissions research model the primary audience is the research community and we chose the name clear just because one of the primary points of the research is to make transparent all of the assumptions and data sources and hopefully clarify the role of the cloud in our energy system moving forward so this is an open public use model that considers all major and uses of energy in the economy it documents all of its equations and data sources fully if you have better data or you don’t like the assumptions it allows for users to change that it allows for users to update the assumptions over time and most importantly we hope that it’s sort of a starting point for the research community which is basically something that can be critiqued and improved over time that can be a valuable resource for all of us so the key points of the public use model which I’ll wrap up with are that it takes a systems approach so in our case study that I presented we looked at the implications of moving software from local inefficient data centers to the cloud now and that’s in that study we only considered sort of the IT system but if we wanted to look at for example streaming video one would have to consider not only the shifts in the IT systems but also are we transporting things less because we’re no longer manufacturing DVDs are we using the system’s more in driving up our home entertainment system energy use are we manufacturing fewer DVDs and thereby reducing energy use and emissions in that segment of the economy the truth is we need to look at the entire system in order to have an informed answer and that’s what we hope to do with this public use model and as I mentioned it’s it’s it’s freely available to the public users can change assumptions we’ve got a user interface this this tool will be launched very soon and the goal is really just to put something out there – to start hopefully kickstart the research in a direction that is going to help us make continued progress in understanding the implications of the cloud lastly I just wanted to thank my research collaborators from Lawrence Berkeley Lab and Northwestern University and I’d also like to thank Google who funded the research and I think I did I’m Scott Matthews I’m a professor at Carnegie Mellon University and I’ve been working in the area of information technology systems for most of my academic career which is about 20 years I like the others I’d like to thank everyone for both coming and for Google for putting this together this is gonna build on the last two talks by emphasizing the kinds of activities and processes that the internet enables and I’m gonna talk about something most of us understand which is shopping and how the Internet has enabled changes in shopping and the way in which we’ve chosen to study those changes which is to look at the system’s effects and we’ve been looking at energy carbon dioxide and other indicators of that over time but as John first said and then Eric repeated these system effects which happen as a result of the internet are really important and I hope you will sort of learn and take away something from this that’ll help you in your everyday thoughts both at home and at work in terms of what you could do to have greener shopping via use of the internet so I’ll first talk about a case study that we did on physical goods

because that is both a good case study of something that’s going to continue for a long time and something will also serve as a benchmark and a baseline for the next part which will be on digital goods and in this study we worked with a specific e-commerce company as several years ago to compare retail and electronic commerce systems this was actually a study for a flash drive which I don’t think anybody actually buys anymore that’s okay and one of the benefits of working with the company who sponsored the study by comm at the time was that they gave us all of the purchase records for flash drives and we knew where people were in the u.s. that we’re buying them and thus how far the warehouse shipments and stuff were this study and the other one that I’m gonna show in a minute uses lifecycle assessment without going into a lot of detail about what that is that’s a cradle to grave framework for thinking about all of the activities from the beginning of making something to the end of when you receive it and keeping track and accounting for all the pieces separately what you’ll see though and this particular graph is expressing the carbon footprint on a per item basis is that the there’s a shift in what are the activities that lead to the big impact and so as you can see in the retail system customer transport is a big deal warehousing is about the same in both and in terms of e-commerce of course the last mile delivery to your house as well as packaging and your use of your computer and the network associated with it are big deals but you might also notice that the results are actually pretty close this is not a order of magnitude differences not a factor too different and even with the error bars to a first approximation we would think at the time we did this study that it was almost a wash but perhaps slightly beneficial to be buying things via e-commerce and so just to emphasize what we found with that and to sort of summarize the takeaways from that it’s really important how far people live from retail and how they’re getting there are you taking the bus are you walking taking a bike and how many things you buy when you’re there we had a certain number of goods that we allocated from a particular retail shopping trip this wasn’t just going to the store and buying a flash drive very few people do that and ironically the more stuff you would buy the lower footprint you would have for retail I don’t know that that’s necessarily a message we’re trying to promote which is to buy more though the delivery is of course also an issue and we assume that was being delivered by truck if you delivered by air it would be a lot higher and the scale effects which I want to make sure I emphasize also is that at the time we did the study it was small single-digit percents of e-commerce as a function of total retail it’s now about 6% and that doesn’t include buying airline tickets online this is large this is getting to be a very big problem and one thing that I often tell my kids when they’re always talking about buying stuff online and then complain we’re sitting in traffic is that FedEx truck might be going to our house and so if we start buying more and more things and that 6% increases eventually you will be surrounded by trucks doing those kinds of deliveries and that’s one of those Mart effects that John mentioned earlier just to sort of wrap up though just to promote the same messages we did a similar study that was funded by Microsoft a couple of years ago with John kumys helped where as he noted earlier and he showed this slide we were tracking a digital good though from the traditional way versus the new digital way and this is from music and you can again see the same kinds of shifts over the different categories the thing I want to emphasize here as John’s already made one of the points is that you could sort of sort of consider this as a shift from physical to streaming and the reason that that would matter then is that aside from the bits to atoms that John mentioned one thing to think about is that if there is this really large potential reduction from having a physical good CD or some other piece of physical media for music streaming may in fact be good if you’re streaming a few number of times but if you stream hundreds of times eventually the total energy use could in fact be higher than the energy in the traditional system and so I say that in the sense of to keep that in mind and to hope that the efficiency continues and the last thought is on context beyond the scale effects that one of the things that’s important is that all of these results I just showed in the last four and a half minutes were relative and that’s great because we’re showing that we think e-commerce is and the Internet has been better in terms of reducing energy use but realize that we’re using more total energy by doing both right we have parallel systems in place that are doing things the old physical way as well as the new electronic way and we’re clearly using more total energy to have it both ways and so we really have to try to think about how to continue to do things that are going to make sure the internet side is as efficient as it possibly can be so that that total is minimized thank

you hi thanks Scott thanks Michael for having me here so I will tell you I’m gonna talk about how much energy it takes to send data across the internet and of course after this morning I need to say what I mean by internet open or rather which part of the internet I’m talking about and I am NOT talking the left part of one of the slides of John this morning all that included terminal devices and data centers I’m talking only about internet transmissions and I’m also not talking wireless but only word transmissions and this being said I have this number for you which is point to kilowatt hours per gigabyte and of course to arrive to such a number one can do can deploy several methodologies what we have done was a bottom-up case study which was a conference that we organized simultaneously in Switzerland and in Japan and to sort of create this of course we do that time zone difference we only had a few hours per day that we could have common sessions but in those couple of hours per day we tried to give the sense of common common conference cross site question-and-answer sessions and so on and to realize this on on a technological level we deployed for Cisco TelePresence streams in parallel which meant about 20 megabits per second per direction or a total of 40 megabits per second for the entire conference and excuse me the map is not that scale Switzerland is not that big as were certainly knows and we had because it was a real-time application we had to guarantee a maximum delay we could not send a stream scene from Switzerland eastwards over continental Europe and Asia because there we could not do this so we had to take the longer route westwards seen from Switzerland across the Atlantic northern America and the Pacific which meant almost 70,000 miles and 2425 routers but now because we had guarantee the quality of service to such a level we had a very good control and data on those routers along the way and also the fibers so we knew very exactly what is there what their energy consumption is and also what the traffic was so by relating our traffic to the total traffic of the particular router of our fiber we could know which energy our transmission is responsible for and so we have not done a small marginal effect as John where is John said that this morning but at Rio we attributed a share of it and how this looks it’s it’s there it’s the accumulated energy as seen from Switzerland going towards Japan and that’s almost 1,800 watts for the conference transmission and doubling this for things such as air conditioning lighting and so on what has been talked this morning which in networkers language is called power usage efficiency PUA we double this we arrived to almost 3600 watt for the 40 megabits per second and transforming this into kilowatt hours per gigabyte I get to to the number that I started my talk with and I like to stress out that this we believe is a conservative estimate for several reasons a we have many routers about double the average number of routers for an internet transmission the beauty of two of course speaking at Google of a pure you of PUA of two is ridiculous Google works with 1.1 but the worldwide average in internet for Internet routers is about 1.6 1.7 so doubling this was actually conservative and at the two ends we had very very low loads I typically low loads so we do think that this is a conservative estimate for wire connections only and of course excluding the terminal devices so it’s only internet transmission to put this this number in in relation I have I have here two things that you might transmit across the Internet a typically sized ebook that’s three megabyte and if we take our number there then we get to the energy which is 0.6 what hours not kilowatt hours or around a third of a gram of the co2 which is roughly like you come home you turn on the light to take off your shoes you turn it off and that’s about the energy that that that’s consumed or a two hours high-definition video conference as we had it just with one stream not with

four in parallel to replace a business meeting amounts to some nine gigabyte which is almost a kilogram of co2 which gets you flying from almost from here to Palo Alto actually nice or or driving for that matter because one kilometer driven is roughly the same as one kilometer on an airplane as one of the passengers obviously so my take-home message for you is I have not talked about the energy of terminal devices but comparing it to that the energy needed for transmission usually it’s much larger so transmitting there is so we’ll said this morning that we have to focus on where we put the research efforts and there is also a board outside with the question as the internet grows what are the impacts on the environment that we should be thinking about and what I think is that transmission over wireless over wired excuse me Carrie will talk in a minute about the wireless over wired networks it’s probably one of the things that we do not need to worry so much about compared to the other transmissions second that this remains relevant of course Wireless will become more and more important but due to trends such as cloud computing IPTV this will remain important and thirdly something very new for today no one has said this before that sending bits usually is much more efficient than sending atoms thank you morning my name’s Carrie Hinton I’m from the center of energy-efficient telecommunications based at the University of Melbourne in Australia which is a fairly long plane flight from where we are today okay so what I want to talk about is wireless access to cloud services it’s important that I make it clear that I’m not talking about all cloud services and I’m not talking about all wireless networks I’m talking about the the cloud ecosystem when you access a cloud service via wireless so I’ve tried to indicate that here by excluding wireline services and Enterprise Services I’ve not talked about enterprise it’s all about basically Wireless now the reason we did this is because wireless access to cloud service is really growing quickly and we wanted to get an idea as to what this meant in terms of understanding the energy consumption the various components of the network and in fact both the Jonathan and Eric have touched on this in the data centers are pretty energy efficient and that it’s the edge network that’s the real key in the exercise okay so we undertook the study by getting a measure of the number of users and the various technologies which is on the far side and we see that for example this is looking towards 2015 the forecast figures that we were at had access to said about 67% of users are going to start using wireless as in 4G they know a group of home Wi-Fi users and also a Wi-Fi hotspot users now you take that we take the energy efficiency of the various technologies they’re listed here on the left-hand side notice this is a log plot this is important to appreciate this is a log plot so those heights in differences of the various energy efficiencies in joules per bit our orders of magnitude it’s not a matter of three times but like 30 or times and what we see is that that home Wi-Fi is the least efficient the reason for that is because although it’s a small cell technology there’s only one or two users per device Wi-Fi hotspots good small cell size but also lots of users Wireless 4G is not so good and the reason it’s not so good is although it’s a shared technology it’s a large cell the network is good that’s why it in fact that network is typical in wire technologies and as Vlad said a moment ago it’s quite energy efficient and then finally datacenters now when you bring us all this together we get down to the plot at the bottom and the key point that we’re trying to make here is that when you start talking about energy efficiency of wireless cloud services you ought to talk about the entire ecosystem and what we see here is that the reality is that data centers are about 10% we’re looking at the two right-hand plots one’s a low estimate Netherlands highest number for 2015 data centers about 10% and the reason for that really comes down to the point that was made by previous speakers and that is there’s a lot of work being done on making data centers energy efficient the problem is the way we get to them and the problem is that basically whilst technologies are not as anywhere near energy efficient as data centers but that’s just is one aspect I want to make the point that there are groups working very hard on improving wireless technologies and I expect that the improvements will actually bring these numbers down by 2015 in this plot I’ve assumed business-as-usual improvements in wireless technology trends over the last 10 years and extrapolated out but there are groups around the planet who are working hard at Toronto we proved that green touch which is of which I’m a member is one example example of that okay so this next plot is looking at cloud services and it’s looking at interactive cloud services and what we’ve done here is we’ve measured the amount of data that’s being typed in for interactive cloud service and we’ve got this amount of

data typed in on the bottom line here so we talked about bytes okay so 200 bytes 200 bytes 300 bytes say you’re typing into a Google Docs a word processor and we then measure the amount of traffic that goes between your unit in this case it’s a laptop and the data center and we’ve plotted that along the vertical axis the key point to pick up is if there’s a thousandfold multiplier in other words for every 200 bytes you put in you put 200,000 Bice’s exchanged between your device and the network and so this is an issue especially if you’re going to use Wireless for that connection between the laptop or the personal device and then it work is that thousand times multiplier will actually crank up the energy consumption of that link so I guess what I want to finish off on is saying this we have just done this through measurements and we don’t know the purpose of that data why is there a thousand times multiplier there and I guess one of the questions that I like to throw out to this audience is why is that a thousand multiplying in other words for every byte I type II and I generate a thousand bytes off to the neck and back and is that multipliers crucial can we get away with reducing that because as we migrate to using these interactive cloud services via wireless connections this thousand times multiplier is going to kick in and the more and more people who do this is going to begin a bigger and bigger challenge so as I said I like to throw out into the audience why is it a thousand and do we need to be so large thank you good morning I’m Pat Martin carrion of the University of California Davis and I’m delighted to be here my conclusion that the net impact of the internet is to increase travel arises from numerous studies conducted by myself and others during my 30 years of research in this very question the question is a complex one I agree and there’s no doubt that the Internet has eliminated some travel I’m simply contending that it’s generating more traveled and it’s eliminating I base this conclusion first and foremost on several aggregate studies that account for multiple simultaneous effects including longer term indirect and feedback effects that are often neglected in studies in this area I hope you’ll take for granted those aggregate studies that I don’t have time to present today so there in the background informing what I do want to present which are several conceptual mechanisms by which these effects occur so on the next few slides they’ll all have the same basic structure as shown on this one we’ll talk about an assertion that the Internet or information and communication technology in general has a certain characteristic which has one or more implications which has a certain impact on travel so I’ll give you my top four reasons starting with number 4 a la David Letterman the first one is that you know there’s no question that the Internet has allowed many of our daily activities to be completed faster or has eliminated them altogether think telecommuting teleconferencing online shopping these are things that we can now do without traveling to be sure similarly the Internet can save us money in a lot of different ways including through the ability to comparison shop and find the best deals and you can doubtless think of other ways that saves us money that I don’t have time to go into so the question is what do we do with that time and that money that we’re saving generally we apply them to other activities some of those other activities will incidentally involve travel but some of them will actually be travel so the young man from Hotwire over here is exemplifying the process that I think is at work namely if you make travel cheaper people will travel more and that’s going to be a recurring theme in each of the next few slides number two number three we’ve always been able to read a magazine listen to the radio or even talk to another passenger while we travel but information and communication technology has vastly expanded the range of activities available to us while we travel and has dramatically increased the share of travelers who are always equipped to use otherwise wasted time productively or at least pleasantly as a consequence travel time is less of a burden than it used to be in turn that means we’re less motivated to reduce it than we used to be for example were less inclined to telecommute or to move closer to work if we’re able to use our commute time productively at the margin and we may actually make more trips because our ability to stay connected to home friends and work when we travel makes it less stressful to be away from home now imagine a not-too-distant future in which we have the convenience comfort and privacy of automobile travel combined with complete hands-free operation travel time will become even less burdensome and absent any policy or price signals to the contrary we will be

even less inclined to reduce it number two there is a veritable alphabet soup of applications designed to improve the flow of travel in various parts of the system 80 is v2v rfid CMS et Cie that’s an actual acronym not just etc but etc and to the extent that these applications are successful that’s going to increase the effective capacity of the transportation network and guess what that’s going to decrease the cost or the time or both involved in traveling so there’s considerable evidence to support the observation that when time and cost of travel decrease the demand for travel increases so we have the paradox that the better these applications are at improving travel the greater need there is going to be for them as they will create new travel and last but not least we have two branches on our final mechanism on the personal side again down through history we’ve been inspired to travel by maps personal accounts and artistic representations of the exotic and the unknown what’s new these days is that the Internet has again increased the reach and the intensity of that inspiration on the business side information and communication technology has been the engine driving the globalization of Commerce it’s expanded the spatial reach of a firms market lowered barriers to entry decreased operations costs lower operations costs translate to lower prices which translates guess what to greater demand which translates to more transportation of raw materials and finished products to meet the greater demand at the same time we have distributed teams cross-training broader client base among other mechanisms that are generating increased need for personal travel for business so in both the personal and business cases the result is more and longer trips I could say a lot more on the subject you can imagine 30 years of research but time is up and I look forward to continuing the conversation over the rest of the day thank you hi good morning my name is Misha I’m assistant professor from unit Michigan I’m delighted to be here I’m here also on behalf of my colleagues dr. William saying the Ramsey ahead who are fortunate not to be able to make it today so I’m going to talk about sustainability implications for person electronic product so this is a much more complicated question that it sounds it really depends on how depends on how in person electronics interact with the environment so generally there are four levels interaction at infrastructure device level applications level and interaction with at the economy and a society level so much of work has been done in the first two layers infrastructure and device and they were how much environment impacts has cost because of making the infrastructure and making the products and also at the application level what’s the impact because of how the consumers actually use them at the product so well the the the take-home message here is that picked effect technology does not necessarily mean better environmental performance so here is a wide amount of the megatrend for person electronics is that they are getting smaller and smaller we saw earlier today the global shipments of smartphones had already surpassed the PCs combined laptop desktop combined and global shipment tablets will all soon surpass PCs shipment combined as well so they are getting smaller and smaller does it come with better environmental performance probably yes so people have looked at the lifecycle greenhouse gas emissions of laptop versus desktop computers the result varies lot because of different scopes of different studies but it’s safe to say that generally laptop use generates less greenhouse gas emission in its life cycle the tech stop does which makes sense because they are smaller we less materials less energy to make it and less energy to operate that which comes with less greenhouse gas emissions so is that really that simple not really so there are a lot of other factors we need to take into account when asking what’s a real environment implications for personal collection ik products so this is a typical life cycle person electronic computers the products and as well as other general products at the very beginning a raw materials aging process stage because the products getting smaller smaller we use less

material that’s for sure but we use more variety of materials it has a lot of environment implication that long as the lungs of their amazed that we putting most stuff in a smaller product which makes that recycling reduce more difficult and end-of-life at the process the manufacturing stage most of the environment impact four-person electronic products happen in a manufacturing stage instead of the use phase yet most of our research folks and polish folks still for in use phase last attentions being paid to the manufacturing stage in the use phase it’s an infamous rebound effect that first of all I when it comes to personal Ektron ik star to aspect for ribbon effects first of all better technology better products tend to be used more we spend more time our phones our tablets second it’s true that from a poor for functionality based or product basis we use less material less impact but we need a mobile we use mobile radial products to to provide specific functionality to fill our specific demands the community of personal electronic products getting larger and larger that comes with larger environment impacts so finally an inner life because the average life span of person electronics getting shorter and shorter my first for Mars used the for three years my last one I use three months and that as a result more and more electronic waste has been generated every year and most of the tronic generate electronic waste generate in developed countries has been shifted to countries like China India Pakistan where there are informally recycled reused by informally I mean for example using bare hands instead of machines which has a lot of environmental health problem for the local workers and residents and also create a lot of environment impact in local community but on the other hand this electronic waste business is also provide a lot of employment beings for local people the people after poverty and provide cheap easy access to digital technology for the local people as well so there are a lot of trade-offs of when it comes to our sustainability implications or in their life electronic products so and you can see it’s a very complicated problem and there’s no easy answer we ask you what’s the real implications for person electronic products but thing I think if the takeaway message here is that better technology does not necessarily mean better environment performance it really depends on how consumers use it and how we design the product the service is the policy to encourage people to use it in these other ways with that I my colleagues then I thank you for your attention hi my name’s Elaine and I’m the head of sustainability at Ericsson and Ericsson is the global Swedish telecommunication company we’re in 180 countries have more than 110,000 employees and not everyone knows it but more than 50% of all data transferred goes over in Ericsson network but today I’m also representing an organization called Jesse the global East sustainability initiative and Jesse is an ICT industry association which has more than 31 members today and many of the companies are also here in the room and I’ll talk a little bit about some research that jesse has been doing but then end with a couple of thoughts and reflections from Eric’s inside so um there was a study done by Jesse and in 2008 and this was called smarter 2020 and smarter 2020 was really industry benchmark looking at what is the impact of the ICT sector and and all the member companies of Jesse were supporting this study and in providing data and expertise in order to conduct it that study was just updated last year into something called smarter 2020 and that’s the results presented here and we looked at the whole of the ICT sector so everything from devices to networks and and so on and this study showed that about 9.1 Giga tons of co2 emissions could be offset by smarter use of technology and that the abatement the global abatement potential of the ICT sector could offset future emissions by about 16% so while the sector has been you know I would say around 2% representing around 2% of global co2 emissions the abatement potential is

about 16 and a half percent by 2020 and and again this is seven times the size of the sector’s own input sorry impact and I think that why this study important is it really highlighted the need that Professor Kumi started with which is really the system effects and the study looked at six key areas so looked at energy and all the work you know that’s going on today around smart grids looked at the transportation sector looking how ICT could impact on intelligent transport and even telecommuting and alternative forms of transportation in manufacturing buildings and so on in each one of these from an abatement potential point of view I would say energy and transportation were the two most significant areas contributing roughly 20% of the future abatement potential each and the study is quite detailed but looked into the countries that you see on the bottom here in greater detail looked at sort of deep-dive cases into each one of these countries Brazil Canada US UK and so on so I think that one of the findings also of a smarter 2020 and is that yes while the sector will grow in terms of energy use and in total emissions there is this huge potential here but we really don’t see that it will happen on its own and I want to comment on the last speaker from University of Michigan really looking at consumer behavior and how to change behavior and the importance of the government and the policy frameworks surrounding how we live and work and I think one of the challenges for the ICT sector is that the technology is evolving so much more quickly than the policy frameworks that are supporting it so it is a bit of a gap and so we see that all the companies and I think that’s reflected here by by the nature of this event as such that the companies need to play a bigger role and a greater responsibility in in helping to raise awareness about these issues and also being transparent and providing data into the different studies so as I said the ICT abatement potential is about seven times the size of the sector zone in point and and this is just comparing the the smart 2020 earlier study with with the the now updated one and it’s about a 16 percent difference in as we got better data and as the industry came a little further along we saw even more promising results than in the first study so and then this is a some new research that ericsson has been working on and I want to thank professor Kumi for referencing so much of Erikson’s research and one of the first presentations but here the two new things that we’re working on in our latest research is really looking at the effect of not just ICT but the entertainment and media sector but perhaps more importantly today it’s been the wireless industry has been referenced today we have about six and a half billion mobile subscriptions but we see from ericsson side we’re working with different scenarios that we called networked society scenarios where we see by 2020 some 50 billion connected devices and so in our latest research we’re looking at well well what will be the energy and co2 impact of the connected devices so this is some of our research we will publish a paper early next week describing some of this work but but the main takeaway here is that even with the connected device scenario this means pretty much anything that can be connected or that can benefit from being connected will be connected in the future I’d like to the example of I think it was the cows or the sheep so we’re giving earlier but but here are showing that the net impact of the connected device scenario really won’t be that significant we know we don’t see it having sort of a too much of a greater impact beyond the ICT impact already today so with that thank you you