Malmodin - Energy and Carbon Footprint Performance Metrics

Proceedings of the International Symposium on Sustainable Systems and Technologies, v2 (2014)

Energy and carbon footprint performance metrics for the ICT sector based on LCA Jens Malmodin, Ericsson Research, Sweden, [email protected] Craig Donovan, Ericsson Research, Sweden, [email protected] Abstract Annual greenhouse gas (GHG) emissions per capita is a common way to look at environmental performance in the same way as annual GDP per capita is used as a proxy for economic prosperity and development. In this study, GHG emissions (carbon footprint) per user of ICT or per amount of data transmitted are examined and discussed. The average carbon footprint for ICT has decreased from about 300 kg CO2-eq per average user of ICT in 1990 to about 70-100 kg CO2-eq today. The main reason for this decrease is the increase of users in the mobile subsector where the average carbon footprint has decreased from about 100 kg CO2-eq to about 30-35 kg during the same time. The current carbon footprint per average ICT user is rather small, equating to about 1.3 percent of the global total carbon footprint of about 7 000 kg CO2-eq/capita. However, the total absolute carbon footprint of ICT is increasing, as the increase in number of users/devices/subscriptions outweighs the efficiency improvements we have seen so far. This, however, is more than offset by the enablement potential of ICT to reduce the impact of other sectors, which has been estimated to be around 15 percent. The impact per GB of data is projected to reduce significantly during this period which shows that there is a non-linear relationship between data traffic and the carbon footprint of ICT. Given the rapid advancement of ICT, it is important that studies in this area use up-to-date energy and traffic data in order to achieve reliable results. Proceedings of the International Symposium on Sustainable Systems and Technologies (ISSN 2329-9169) is published annually by the Sustainable Conoscente Network. Melissa Bilec and Jun-Ki Choi, co-editors. [email protected]. Copyright 2014 by Jens Malmodin and Craig Donovan, Licensed under CC-BY 3.0. Cite as: Energy and carbon footprint performance metrics for the ICT sector based on LCA Proc. ISSST, Jens Malmodin and Craig Donovan. Doi information v2 (2014)

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Energy and carbon footprint performance metrics for the ICT sector based on LCA

Introduction Annual greenhouse gas (GHG) emissions per capita is a common way to look at environmental performance in the same way as annual GDP per capita is used as a proxy for economic prosperity and development. In this study, GHG emissions (carbon footprint) per user of ICT or per amount of data transmitted are examined and discussed. The Intergovernmental Panel on Climate Change (IPCC) estimates that stabilizing carbon dioxide (CO2) in the atmosphere to between 445 and 490 parts per million (ppm) (equal to causing a global average temperature of 2 to 2.4 degrees Celsius above pre-industrial levels) requires that emissions start to decline around 2015 and are reduced by 50-85% by 2050 compared to emissions in 2000. It has been estimated that 80% corresponds to a level of about 1,000 kg CO2-eq/capita in 2050 (Jackson 2009) compared to current emission levels of about 7,000 kg CO2-eq/capita (UN 2010), (WRI 2009). This indicates that emissions in 2050 need to return to the same absolute levels as they were in approx.1950. This also indicates that emissions per capita need to be nearly 4 times lower in 2050 compared to 1950, as it is expected there will be about 4 times more people in the world in 2050. The information and communication technology (ICT) sector has developed at a staggering pace and due to the increased use of ICT in society this trend is expected to continue, leading to questions being raised about the future environmental impact of ICT. Due to this fast development, the necessity of using up-to-date data is crucial to the overall quality of any study as the use of older data can lead to incorrect results and conclusions, especially in future forecasts. In order to better understand this fast-paced development in the ICT sector and its environmental impact, up-to-date data for fixed and mobile networks in Sweden have been collected in recent years. The number of mobile and fixed broadband subscriptions, data rates and data traffic per subscription and capita in Sweden is among the highest in the world and Sweden is believed to offer a good indication of the direction of future broadband technology development. Definitions and methodology (Malmodin et al. 2014) defines ICT as including: communication networks from the core network to the end-user equipment. It covers mobile and fixed access networks (including broadband) and data transmission and IP core networks. The term ICT also includes user equipment connected to the networks, such as phones, PCs and modems, enterprise networks, data centers and the operator activities needed for operation and maintenance. It matches the scope for ICT recently used by GeSI (2012), apart from printers which in this study is defined to belong to media, and the scope used in (Malmodin et al. 2010) which also describe how ICT is defined in relation to Entertainment and Media (E&M) products and services, and recently (Malmodin et al. 2013) which also discusses OECDs definition of ICT. The definition of an LCA based carbon footprint is reused from (Malmodin et al. 2013): A carbon footprint of a product is defined as the sum of all relevant greenhouse gas (GHG) emissions which occur during its complete life cycle as determined by a life cycle assessment (LCA). A carbon footprint thus includes raw materials acquisition, production and transports of materials, components and the final assembly and transport of the product itself, as well as use and end-of-life treatment of the product.

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J. Malmodin and C.Donovan

The study is divided into three parts.

Firstly, data and results from earlier extensive studies of the energy and carbon footprint of the ICT sector have been updated and new results are presented divided into a fixed and a mobile part, with performance metrics per user and per amount of data discussed.

Secondly, more detailed and up-to-date data have been collected for the Swedish ICT sector and up-to-date results for fixed and mobile broadband use in Sweden in 2013 are presented, with performance metrics per user and per amount of data discussed.

Finally, a comparison and discussion of the performance metrics presented for fixed and

mobile ICT globally and in Sweden are placed into context in relation to other studies and sectors and for total emissions per capita.

The Carbon Footprint of ICT ICT on a global scale The total carbon footprint and operational electricity consumption of the ICT sector globally has been estimated in two recent studies by (Malmodin et al 2010) and (Malmodin et al 2013). The results presented here are based primarily on these studies and data for the number of users, devices, subscriptions and data traffic for the coming years up to 2020 have been updated based on up-to-date prognoses by (Ericsson 2014) and (Cisco 2014). More information can be found in Supplementary Information S1. The total carbon footprint of the ICT sector globally is estimated to increase from about 620 Mt CO2-eq in 2007 to about 1 080 Mt CO2-eq in 2020 (updated from 1 060 Mt estimated in (Malmodin et al 2013), with a large share of the increase in the mobile communications sector due to a higher number of estimated future subscribers). ICTs share of the global carbon footprint is estimated to increase from about 1.3% to about 2% and the share of the faster growing mobile sector is estimated to grow from 0.2% to 0.5% during this period. Currently (2013), the carbon footprint of the ICT sector is estimated to be about 1.6% of the global carbon footprint or about 800 Mt CO2-eq in absolute terms. Figure 1 shows GHG emissions (carbon footprint) per average ICT user and per average fixed and mobile user from 2007 to 2020 (prognosis). Two metrics are presented: firstly the impact per subscriber, which is compared to the per capita world population, and secondly the impact per gigabyte (GB) of data.

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Depending on the definition of user (e.g. only subscriptions or including all devices such as PCs), the carbon footprint for fixed users ranges from 200 - 270 kg CO2-eq per user in 2007 to estimates of 160 - 260 kg CO2-eq in 2020. In contrast, the corresponding figures for mobile users (e.g. all subscriptions) are from about 27 kg CO2-eq per user in 2007 to estimates of 28 - 35 kg CO2-eq in 2020. The estimated increase is mainly related to the manufacturing of larger and more advanced mobile devices in the future. The carbon footprint for the average user of ICT has decreased from 110 - 125 kg to 70 - 100 kg, mainly as the share of mobile users with a much lower footprint has increased. However, the carbon footprint for ICT per capita in the world has increased from about 100 kg to about 130 kg as each user is estimated to have more subscriptions and devices in 2020 and this rate of increase is greater than the population increase. The carbon footprint per amount of fixed data transmitted is estimated to decrease from nearly 6 kg CO2-eq/GB in 2007 to about 0.25 kg CO2-eq/GB. Mobile data is estimated to decrease from about 100 kg CO2-eq/GB to about 0.5 kg CO2-eq/GB during the same period. This clearly highlights that the rapid increase in data capacity is not having a significant impact on the overall carbon footprint of the ICT sector. ICT in Sweden A recent article published by (Malmodin et al. 2014) is considered to be the most detailed and complete LCA study of the operational electricity consumption and carbon footprint for nationwide ICT networks. The results presented here are based primarily on this research, however, the LCA model has been further developed with new data collected for 2013 in order to present the most up-to-date results. The development of fixed broadband in Sweden appears to have entered a more mature stage. Between 2012 and 2013 there was no increase in the number of connected households, with 3.1 million connected lines in both years. Data rates and data traffic continue to increase but at a slightly lower rate than previously. There is an ongoing transition to more fiber connections at the expense of older copper lines (xDSL), however fiber connections are not included in this study. See table S2.1 in Supplementary Information S2 for detailed data about fixed broadband in Sweden in 2010 and 2013. Table 1 below shows GHG emissions for an average fixed broadband (xDSL) subscription for an average household in Sweden 2010. Results for both the actual Swedish electricity mix and a scenario with global average electricity mix are presented. It is evident that the impact from electricity significantly affects the result. In Sweden electricity production is based primarily on hydro and nuclear with relatively low GHG emissions given at 0.06 kg CO2-eq/kWh, whilst the impact from the world average electricity mix is given as 0.6 kg CO2-eq/kWh (Malmodin et al. 2014). Here we see over twice the impact (from 216 to 558 kg CO2-eq) when using the global electricity mix.

A special use case for a household with 4 persons (2 tablets, 1 laptop, 1 high-end desktop) with high data usage in 2013 and with additional broadband telephony (VoIP) and IPTV services (so called triple-play or 3-play) has been assessed for the purpose of this study and is also presented in Table 1. Our research shows that a significant portion of the impact comes from the user devices and this is evident in the result of this scenario with over twice the impact as the average case (from 558 to 1138 kg CO2-eq), however, the carbon footprint per capita remains nearly the same.

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Table 1. Total annual GHG emissions (carbon footprint) per subscriber/line and per capita (average number of persons in connected households) for a number of fixed broadband (xDSL) cases in Sweden.

Case Total carbon footprint

per sub/line, per capita and per amount of data

More information

Average xDSL sub/line 2010 (Swedish electricity mix in the use stage)

216 kg CO2-eq/ sub/line

103 kg CO2-eq/ capita

2.1 persons and 1.5 PCs in the average household

0.6 kg CO2-eq/GB

Average xDSL sub/line 2010 (Global electricity mix in the use stage)



1.55 kg CO2-eq/GB

Special xDSL sub/line case 2013 (Global electricity mix in the use stage)



Special case: 4 persons (2 tablets, 1 laptop, 1 high-end desktop) and high data traffic 0.55 kg CO2-eq/GB

with 3-play (xDSL, IPTV, VoIP, see More information) (Global electricity mix in the use stage)



3-play scenario with also broadband telephony (VoIP) and IPTV in addition to the special case described above

Note that the carbon footprint presented is complete in that sense it includes all relevant life cycle stages and all user and network equipment and data services (data centers). More details can be found in Supplementary Information S2 where data and results for different life cycle stages and for different user and network equipment can be found. The use of mobile broadband (3G/WCDMA) started early (2003) in Sweden and after a slow start in terms of subscription and data traffic growth, the development has been more rapid since 2006 and the rapid development continues today with 4G/LTE. The first 4G/LTE network in the world was brought online in Stockholm in 2009 and currently three nationwide 4G/LTE networks are being constructed, out of which one is shared between two of the four main operators. Possible data rates and actual data traffic in Sweden is the highest in the world on a national level in the mobile sector (2013). The estimated annual data traffic in 2013 (based on actual data traffic for the first half of 2013) is about 30 GB/subscriber which equal 2.5 GB/month. Note that this is the average traffic of all 3G and 4G subscriptions and that data traffic per 4G subscriber is even higher. The average traffic for 3G/4G subscriptions with data as stand-alone service is about 6 GB/month. See table S3.1 in the supplementary material for detailed data about the development of mobile broadband networks and subscriptions in Sweden 2006-2013, plus an estimate for 2015. Table 2 below shows GHG emissions for an average 3G mobile broadband subscription in Sweden in 2010. Results for both the actual Swedish electricity mix and a scenario with global average electricity mix are presented.

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Table 2. Total annual GHG emissions (carbon footprint) per average mobile broadband (3G/4G) subscription (sub) in Sweden. For comparison, a GSM sub 2010 with mainly voice/sms and some data and a smartphone, tablet

and a laptop sub in 2013 with 3G/4G subscriptions and high data traffic are also presented.

Case (subscription) Data (/year) Total carbon footprint

per sub and per amount of data

More information

Average mobile 3G sub 2010 (Swedish electricity mix) 8.5 GB

25 kg CO2-eq/sub 2.9 kg CO2-eq/GB

Average mobile device including laptops with 50% of its use allocated to mobile use

Average mobile 3G sub 2010 (Global electricity mix in the use stage, used also in all cases below)

8.5 GB 50 kg CO2-eq/sub 5.9 kg CO2-eq/GB

GSM sub with voice/sms/data 2010 (not included in figure 3) 0.7 GB

34 kg CO2-eq/sub 49 kg CO2-eq/GB 0.4 GB voice/sms, 0.3 GB data

Smartphone and average data 2013 30 GB 42 kg CO2-eq/sub 1.4 kg CO2-eq/GB High-end smartphone

Tablet and high data 2013 70 GB 67 kg CO2-eq/sub 0.96 kg CO2-eq/GB Laptop and high data 2013 (not included in figure 3) 150 GB

115 kg CO2-eq/sub 0.77 kg CO2-eq/GB

Laptop use and manufacturing allocated 100% to mobile

Note that the carbon footprint presented is complete in the sense that it includes all relevant life cycle stages and all user and network equipment and data services (data centers). For comparison, results for a GSM subscriber in 2010 with mainly voice/sms and some data and a smartphone, tablet and laptop sub in 2013 with 3G/4G subscriptions and high data traffic are also presented in table 2. The largest impact comes from the manufacturing of the devices; hence the increasing impact as the complexity and size of device increases. More details can be found in the supplementary material where data and results for different life cycle stages and for different user and network equipment can be found. The carbon footprint results presented in Table 2 can be compared to the global mobile average of 28 - 35 kg CO2-eq estimated in 2020 and presented in Figure 1. With a global electricity mix to make the Swedish figures more international the carbon footprint for a high-end smartphone with 2.5 GB/month has then a footprint which is about 33% higher than the estimated average footprint per global mobile user in 2020. Placing the ICT footprint into context The carbon footprint figures per ICT user presented in this study are summarized below in Figure 2 and placed into context by relating them to similar figures from other sectors and some national and global average figures per capita. This allows us to understand the magnitude of the ICT impact in relation to total GHG emissions per capita. Figure 2 shows that the impact from ICT per subscription/user is a relatively small portion of the overall footprint of the average person in the world, and that mobile communications are a small portion of the total ICT impact.

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Figure 2: Total annual GHG emissions (carbon footprint) per average ICT subscription/user in relation to

similar figures for other sectors and figures per capita in Sweden, US and globally. Why is two US fridges included in Figure 2? Recently it was claimed that a smartphone, if the network and data centers also are included, has about the same annual energy footprint as two fridges in the US. More details and references can be found in Supplementary Information S4. This claim served as one source of inspiration and motivation to complete this study. Our research shows this claim is incorrect by at least one order of magnitude. We find that two fridges consume about 10 times more energy compared to an average smartphone user utilizing a broadband mobile network. Two fridges (modern low energy model) that consume 700 kWh give about 420 kg CO2-eq (world mix: 0.6 kg CO2-eq/kWh) from operation alone which is about 10 times the carbon footprint presented for a high-end smartphone in Sweden in 2013. We consider that part of the reason for the error was the use of older energy and data figures that were multiplied with higher data traffic without considering the rapid changes in the energy consumption and impact of ICT networks. Discussion The pervasive nature of ICT will see a continued increase in the number of subscribers and connected devices in the coming years. While, the ICT share of the global carbon footprint is estimated to increase from about 1.3% to about 2% between 2007 and 2020, the enablement potential for ICT to reduce emissions in the other 98% is substantial. In the recent GeSI

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SMARTer2020 study (GeSI 2012), the potential for ICT to reduce the impact of other sectors was estimated to be around a 15% reduction in the global carbon footprint of non-ICT sectors, thereby significantly offsetting the increased footprint of the ICT sector alone. The results show that a mobile broadband subscriber has a significantly smaller footprint than a fixed xDSL subscriber by around one order of magnitude. Thus, as the ICT sector continues to expand, modernization of ICT equipment plays a vital role in determining the magnitude of the sectors carbon footprint. There is now increasing focus across the industry on end-to-end energy consumption in ICT networks with a strong drive to reduce total network energy. As much of the impact comes from energy use during operation, this attention to energy consumption by the industry will be instrumental in determining the long-term impact of the ICT sector. In this study, two metrics for evaluating the carbon footprint of ICT are presented; firstly, based on the human element of a subscriber or per capita value and, secondly, based on the digital element of data traffic in the network. The subscriber metric is considered to be the more versatile as it allows for the ICT footprint per subscriber or person to be placed into the broader context of the total carbon footprint per capita. In this context, the results show that the average ICT impact per capita is around 100 kg CO2-eq, which is particularly low given the total estimated global impact per capita of 7000 kg CO2-eq. It has been estimated by Jackson (2009) that that the per capita GHG emissions need to be about 1 000 kg CO2-eq in 2050. The impact and enablement potential of ICT will become increasingly important when considering how to achieve future scenarios for GHG reduction. In contrast, while the data metric does not lend to placing the ICT footprint into a broader context, it is still value to understand the development of the ICT sector itself from an environmental perspective. What is evident is that there is not a linear relationship between the carbon footprint of ICT and data traffic, in other words, projected significant increases in data traffic do not lead to significant increases in the ICT footprint. The assessment of energy consumption and data traffic in Sweden shows that the increase in data traffic currently in Sweden (about double data traffic in three years) gives an energy footprint in 2013 (0.75 kWh CO2-eq/GB) that is about half compared to the energy footprint in 2010. It is also very important to know what is included and what is not included in this figure. This figure does not include any user equipment like PCs and is only 0.25 kWh/GB if data services (data centers) are excluded and becomes even smaller (0.1 kWh/GB) if only the network and not the residential gateway is included. Such figures that are intended to represent the energy consumption of various parts of what we call the Internet are compared to other similar figures and differences are discussed in Supplementary Information S5. Conclusion In this paper we have presented the total estimated carbon footprint of the ICT sector in relation to the total global carbon footprint and projected this for a 2020 scenario. We have also presented the ICT footprint of the nationwide ICT network in Sweden and placed this in the global context through the use of the global electricity mix. Finally, we have placed the impact in relation to a subscriber or per capita value in context of the current total footprint of a person globally. The results show that the share of the ICT sectors global footprint in relation to the total global footprint is estimated to increase from about 1.3% to about 2% between 2007 and 2020, whilst the impacts per subscriber remain relatively constant for the same period. This increase is significantly offset by the potential for ICT to reduce the global carbon in other non-ICT sectors by around 15%. The impact per GB of data is estimated to reduce significantly during this period which shows that there is a non-linear relationship between data traffic and

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the carbon footprint (i.e. an increase in data traffic does not lead to a significant increase in the environmental impact). However, the data traffic metric has some limitations for placing the ICT footprint into the context of the total global footprint. Given the rapid advancement of ICT, it is important that studies in this area use up-to-date energy and traffic data in order to achieve reliable results. Acknowledgements The authors would like to acknowledge our colleagues and friends at TeliaSonera and CESC (Centre for Sustainable Communications) in Sweden for their valuable data and insights. References

Cisco. 2013. Cisco Visual Networking Index: Forecast and Methodology, 20122017. Available at: http://www.cisco.com/c/en/us/solutions/collateral/service-provider/ip-ngn-ip-next-generation-network/white_paper_c11-481360.html

Cisco. 2014. Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 20132018. Available at: http://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/white_paper_c11-520862.html

Ericsson. 2013. Ericsson Mobility Report. November 2013. Available at: http://www.ericsson.com/res/docs/2013/ericsson-mobility-report-november-2013.pdf

IPCC. 2007. Climate change 2007: Mitigation. Contribution of working group III to the Fourth Assessment Report of the Intergovernmental Panel on climate Change. Cambridge, Cambridge University Press.

Jackson, T. 2009. Prosperity Without Growth. Earthscan books. (ISBN 978-91-7037-649-8, Swedish version)

Lundn, D., J. Malmodin. 2013. Changes in environmental impacts over time in the fast developing ICT industry. LCM 2013, 26-29 August 2013, Gothenburg. Available at: http://conferences.chalmers.se/index.php/LCM/LCM2013/paper/view/580/180

Malmodin, J., . Moberg, D. Lundn, G. Finnveden and N. Lvehagen. 2010. Greenhouse Gas Emissions and Operational Electricity Use in the ICT and Entertainment & Media Sectors. Journal of Industrial Ecology 14(5):770790.

Malmodin, J., P. Bergmark and D. Lundn. 2013. The future carbon footprint of the ICT and E&M sectors. Paper presented at ICT for Sustainability (ICT4S), 9-12 February 2013, Zurich.

Malmodin, J., D. Lundn., . Moberg, M. Nilsson and G. Andersson. 2014. Life cycle assessment of ICT carbon footprint and operational electricity use from the operator, national and subscriber perspective in Sweden. Journal of Industrial Ecology xx(x):xxxxxx.

UN. 2010. United Nations, Population Division of the Department of Economic and Social Affairs of the United Nations Secretariat, World Population Prospects: The 2010 Revision. Available at: http://esa.un.org/unpd/wpp/index.htm

WRI. 2009. World Greenhouse Gas Emissions in 2005. World Resource Institute. Available on line at http://www.wri.org/resources/charts-graphs/world-greenhouse-gas-emissions-2005

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Supplementary Information (S) Energy and carbon footprint performance metrics for the ICT sector based on LCA Jens Malmodin, Ericsson Research, Sweden, [email protected] Craig Donovan, Ericsson Research, Sweden, [email protected] (S1) ICT on a global level Figure S1 below show the total GHG emissions and operational electricity consumption (use stage only) of the ICT sector divided into a fixed and a mobile part on the highest level.

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Figure S1.1: Total GHG emissions (carbon footprint) and operational electricity consumption of the ICT

sector globally 2007-2020. The total GHG emissions (carbon footprint) (1) and operational electricity consumption (2) are presented split on a fixed (A1, B1) and a mobile (A2, B2) part.

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The results presented in figure S1.1 are based primarily on studies of the total carbon footprint and operational electricity consumption of the ICT sector globally (Malmodin et al 2010, Malmodin et al 2013). Data for number of users, devices, subscriptions and data traffic for the coming years up to 2020 have been updated based on up-to-date prognoses by (Ericsson 2014) and (Cisco 2014). Data centers, data transmission and IP core have been allocated to the fixed and mobile part based on their share of total data traffic. 1.25 billion Tablets and 0.45 billion laptops have been allocated 50% to the mobile part based on mobile use based in turn on data traffic (Cisco 2014).

Table S1.1. Global ICT sector key data for 2007 and 2020. The subscription (sub) numbers are per mid-year. Fixed devices and networks Mobile devices and networks Users in 2007 2 - 2.7 billion users 1 2.95 billion users (= subs) Users in 2020 3 - 5 billion users 2 7.6 - 9.5 billion users (= subs) Data traffic in 2020 vs 2007 30x 500x (including voice as data)

Additional information In addition, 8 billion IP connected

devices is estimated in 2020 (Cisco 2014)

10 billion M2M devices is assumed in the connected devices scenario

(Malmodin et al. 2013) Current prognosis: 3 billion 2020

(Cisco 2014) 1 Users defined as all fixed PSTN and broadband subscriptions plus active LAN ports with a PC connected 2 Users defined as all fixed PSTN and broadband subscriptions plus all PCs (including active LAN ports with a PC connected). By this definition several PC users in a connected household is also counted as users.

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(S2) ICT in Sweden Table S2.1 below shows detailed data about fixed broadband in Sweden 2010 and 2013. Subscription data are based on (PTS 2012) and (PTS 2013). Energy consumption data are based on (Malmodin et al. 2014) for the year 2010 and 2013 are estimated in this study (based on 2010 data and the new subscription data).

Table S2.1. Number of fixed broadband data subscriptions (subs), electricity consumption and data traffic per year in fixed broadband networks in Sweden 2010 and 2013.

2010 2013 More information Subs (lines) PSTN data (data modems) (0.6 million) (0.1 million) Dial up modems - Narrowband xDSL 1.7 million 1.4 million Fiber 0.55 million 1.1 million Cable TV 0.55 million 0.6 million Total subs (lines) 2.8 million 3.1 million Not including PSTN subs Energy consumption PSTN access nodes (145 GWh) (145 GWh) Not included in totals xDSL access nodes 56 GWh 56 GWh 1 Fiber access nodes 17 GWh 34 GWh Cable-TV access nodes 17 GWh 19 GWh CPE: Modems, routers and gateways 327 GWh 310 GWh

New combo gateways are assumed in 2013 replacing old modem+router setups

Data transmission and IP core network

95 GWh (75%, 0.08 kWh/GB)

87 GWh (70%, 0.04 kWh/GB)

Allocation: % of total data traffic = % of total electricity consumption

Total energy consumption 512 GWh 522 GWh Network: Access + CPE + IP core (not including user equipment and data centers) Data traffic and performance metrics Total data traffic 1.2 million TB 2.2 million TB Data traffic in 2013 is estimated Data traffic per sub (line) 360 GB/sub 710 GB/sub Energy per data 0.43 kWh/GB 0.24 kWh/GB Energy per sub (line) 183 kWh/sub 168 kWh/sub 1 Even if number of subs/lines is decreasing it is assumed that the same network equipment is in operation with about the same energy consumption The energy consumption for fixed broadband in Sweden is not expected to grow anymore as number of lines has stopped to increase. A small decrease is even estimated per subscription (line), mainly as a result of new combo gateways that is assumed to have replaced all older modem and router setups in 2013. Question now is if fixed broadband will start to decline in the near future as users move to mobile broadband (4G)? The total energy consumption of PSTN nodes was about 145 GWh in 2010 but main use is classical voice telephony and not data transmission. Fixed voice subscriptions have decreased from 5.4 million 2010 to only 4 million in 2013 but the same energy consumption (same network) can be assumed.

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Figure S2.1 below shows GHG emissions for an average fixed broadband (xDSL) subscription for an average household in Sweden 2010. Results for both the actual Swedish electricity mix and a scenario with global average electricity mix are presented. Note that the carbon footprint presented is complete in that sense it includes all relevant life cycle stages and all user and network equipment and data services (data centers). A special use case for a household with 4 persons (2 tablets, 1 laptop, 1 high-end desktop) with high data usage in 2013 is also presented in figure S2.1.

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31 kWh

Electricity operation: 309 kWh1.5 PCs on average

29 kWh (360 GB, 0.08 kWh/GB)

183 kWh

0 100 200 300

Operation (Swedish electricity)

Operation (Global average electricity)

4.8 kWh

Operation (other energy)

Manufacturing (including EoLT)

0 100 200 300 400 500 600kg CO2-eq /average xDSL

subscription/line(/year)

Average inSweden 2010

(0.06 kg CO2-eq/kWh)

with global (US) electricity mix

(0.6 kg CO2-eq/kWh)

Special use case for Sweden 2013with global (US) electricity mix

(0.6 kg CO2-eq/kWh)

96 kWh, 1 modern gateway

593 kWh, 1 laptop,1 high-end desktop, 2 tablets

(2 work laptops and 4 smartphonesalso uses the xDSL/WiFi but they

are not included)

245 kWh

90 kWh (1800 GB, 0.05 kWh/GB)

Figure S2.1: GHG emissions (carbon footprint) for different life cycle stages, devices and network

components for a fixed broadband (xDSL) subscription (sub) in Sweden in 2010.

13


Table S3.1 below shows detailed data about mobile broadband in Sweden 2006-2015. Subscription data and mobile data traffic data are based on (PTS 2008), (PTS 2010), (PTS 2012) and (PTS 2013). Table S3.1. Number of mobile broadband data subscriptions (subs), electricity consumption and data traffic

per year in mobile broadband networks (3G/4G) in Sweden 2006-2015. 3G networks

Network energy consumption

Subscriptions (mid-year)

Energy per sub [kWh/sub]

Data per sub [GB/sub]

Energy per data [kWh/GB]

2006 105 GWh 1.2 million 90 0.2 500 2007 113 GWh 2008 120 GWh 3.1 million 40 4 9 2009 127 GWh 2010 134 GWh 6.4 million 1 21 8.5 2.5 3G and 4G networks

2011 170 GWh 2012 195 GWh 9.7 million 20 18 1 2013 220 GWh 10.5 million 2 21 30 3 0.7 3 2015 est. 250 GWh 12 million 21 >45


0 10 20 30 40

TransmissionIP metro/core

Mobiledevice

Operatoractivities

Data centers

Accessnetwork

0 10 20 30

Operation (Swedish electricity)

Operation (Global average electricity)

Operation (other energy)

Manufacturing (including EoLT)

kg CO2-eq /average mobile3G subscription

(/year)

Average mobile 3G subin Sweden 2010(0.06 kg CO2-eq/kWh)

with global (US) electricity mix

(0.6 kg CO2-eq/kWh)

with smartphoneand average data traffic

(0.6 kg CO2-eq/kWh)

Control &core nodes

1.3 kWh

2.5 kWh

0 10 20 30 40 0 10 20 30 40

3G/4G 2013 and tabletand high data traffic

(0.6 kg CO2-eq/kWh)

23 kWh

2.7 kWh

4 kWh

13 kWh

1.3 kWh

2.5 kWh

23 kWh

2.7 kWh

4 kWh

13 kWh 3 kWh 15 kWh

20 kWh

32 kWhBase load: 20 kWhData traffic: 12 kWh

7 kWh

Figure S3.2: GHG emissions (carbon footprint) for different life cycle stages, devices and network

components for a mobile broadband (3G/4G) subscription (sub) in Sweden in 2010. For comparison, the electricity consumption in the Swedish GSM networks was estimated to about 170 GWh in 2010 for the three nationwide GSM networks in operation by that time. About 12 million subscribers (including GSM voice use by 3G/4G smartphone subscribers) used the GSM networks in 2010 with their subscriptions and the electricity consumption of the GSM networks per subscription was then about 14 kWh/year. However, if only the about 6 million GSM only subscriptions in 2010 is counted according to (PTS 2012) the electricity consumption per GSM subscription was about 27 kWh/year. Two of the three nationwide GSM networks have recently been modernized and merged into one network and it is estimated that the energy consumption have been reduced by about 25% or by 15%-20% for all GSM networks. At the same time, GSM only subscriptions are decreasing as more and more subscribers get new 3G/4G mobile devices. There was also about 4 million M2M subs at the end of 2013 (mainly GSM, increasing by about 1 million per year) but their combined data traffic was only in the order of 0.1% of total mobile data traffic and their revenue was only about 2% of total revenue or about 1/10 compared to an average human sub. These M2M subs are not included in the performance metrics, e.g. carbon footprint per human sub, presented in the main article.

15


(S3) False claim: Two US fridges = one US smartphone (including the network) More correct is that two fridges has an energy footprint that is at least 10 times higher The original report (no scientific peer review) behind the claim is (Mills 2013). And excellent debunking of the claim and more information with links to news and more appropriate scientific references can be found in an excellent blog by Jonathan Koomey, see (Koomey 2013). There are two main reasons for the very high estimate in the claim of the energy consumption of the network part for a typical mobile broadband subscription:

The estimated network use energy (electricity) consumption (300 kWh) is derived from older estimates of energy consumed per amount of data sent in the network. As this study shows energy/data figures change fast and should be used with care. Older figures can lead to wrong estimates. It is better to work with energy/sub figures over time as they are more stable. The more detailed and up-to-date study of the Swedish 3G/4G networks presented in this paper estimates the energy consumption to be 23 kWh/sub per year for the base stations and mobile core nodes and another 10.5 kWh for other network parts including data transport, data centers and the operators own stores and offices. The total (33.5 kWh) is about 9 times lower than the estimate made in the claim. US networks have similar or only slightly higher energy consumption per subscriber as Swedish networks.

The network manufacturing energy in the claim was estimated to be equal to the use energy based on another study which stated that the manufacturing energy is about 60% of the use energy (Humar et al. 2011) and then it was assumed that this figure somehow would rise to 100% if a complete network view was used. There was a large error in (Humar et al. 2011) as primary energy in the manufacturing stage was compared directly with secondary electric energy in the use stage without converting the secondary electric energy to primary energy (it takes about 3 kWh of primary energy to produce 1 kWh electric energy and the waste heat can and are seldom used). The estimate of the primary energy consumed was high to begin with but there was also a mismatch between the size of the base station and its energy consumption. Together with the mix of energy forms, a too high embodied energy to begin with and the wrong assumption that manufacturing energy = use energy, the estimate was in the end about 50 times (!) higher than results presented by base station manufacturers such as the authors represents, e.g. (Malmodin et al. 2014).

The energy consumption estimate for the manufacturing of the smartphone itself (100 kWh) in the claim is also higher than results from studies made by smartphone manufacturers. That is if the 100 kWh is to be interpreted as electric energy (hard to tell based on the report). But as the whole background report behind the claim is about electricity consumption and two fridges consumes electricity it can be assumed to also be electricity. The same error of mixing primary and secondary energy described above for network manufacturing energy seems to also be the case here. Manufacturing energy or embodied energy is a result from an LCA and it describes nearly without exceptions primary energy and not electric energy. Table S4.1 on the next page shows a step-by-step comparison of the false claim and results presented in this study.

16


Table S4.1. Step-by-step comparison of the false claim and results presented in this study.

User and network equipment/part False claim This study Energy CO2-eq Energy CO2-eq

Mobile broadband network use energy consumption including data transport and data services (data centers)

300 kWh (electricity) 900 kWh

(primary energy)

180 kg

33.5 kWh (electricity) 100 kWh

(primary energy)

20 kg

Mobile broadband network manufacturing energy consumption


(primary energy)

180 kg 30 kWh 2

(primary energy) 6 kg

Smartphone use and manufacturing


(primary energy)

60 kg 75 kWh 2

(primary energy) 15 kg

Actual smartphone use (3 kWh) (2 kg) Total 2 100 kWh 420 kg 210 kWh 42 kg 1 It is assumed that it takes about 3 kWh primary energy to produce 1 kWh secondary electric energy (measured at the consumer including transformation and distribution losses) on average in the world and that this assumption also is valid for US electricity with about the same share of fossil fuels in the production mix. 2 It is assumed that about 0.20 kg CO2-eq is emitted for every kWh of primary energy consumed in the manufacturing stage. As most energy consumed during the manufacturing stage is electricity in the ICT sector, the global average electricity model used (0.6 kg CO2-eq/kWh, secondary electric energy) gives about 0.2 kg CO2-eq/kWh (primary energy). This should be seen as a conservative estimate that gives a slightly larger result as oil based primary fuel energy has an average of about 0.26 kg CO2-eq and that about 10% to 30% is primarily oil based fossil fuel consumed for transports and travel in the manufacturing stage of ICT products.

17


(S5) Comparison of figures for energy consumption per amount of data transmitted Table S5.1 below show Swedish data traffic in comparison to other countries and the EU; note that the growth was higher in Western Europe, Japan and US in 2009, about 40-50% per year according to MINTS (2009).

Table S5.1. Year-end 2009 estimates for monthly Internet traffic based on MINTS (2009). Country / region Traffic per capita (GB/month) Traffic growth per year (2009) Western Europe and Japan 5 US 7 40% - 50% Sweden, based on (Malmodin et al. 2014) 10.5 1 30% Hong Kong 22.5 South Korea 30 1 This is for 2009 to be comparable to MINTS (2009), the results for Sweden in 2010 is 14 GB/capita. Table S5.2 below shows energy per amount of data figures for fixed broadband data flows presented in this study compared to some other studies that present similar figure which in turn has been used in other studies.

Table S5.2. Comparison of energy per amount of data figures for fixed broadband data flows for various parts of the network based on (Malmodin et al. 2014). All energy figures presented are per GB data.

Network part Weber (2009) 1 Baliga (2009) 2 Coroama (2009) Malmodin (2014) Year of data 2010 1 Future model 2 2009 2010 (2013) Main access type xDSL optical LAN xDSL CPE (average modem/router/ gateway for xDSL in this study)

1.2 kWh

0.11 kWh Not included (seen as access network) 0.3 kWh

(0.15 kWh) Access network (xDSL/DSLAM in this study)

0.06 kWh 0.2 kWh

(point of access is 5/32 Gbps routers)

0.08 kWh (0.04 kWh)

Data transmission and IP core network

0.08 kWh (0.04 kWh)

International submarine cable system (share) 3 no info

0.02 kWh (0.01 kWh)

Open (Internet) enterprise data centers (share) 3 2.3 kWh Not included

Not included as a p2p video conference was

studied

1 kWh (0. 5 kWh)

(


The Weber (2009) figure (3.5 kWh/GB) is from the US which at that time (2009/2010) had about 2/3 of the data traffic per capita compared to Sweden (see table S5.1). The figure was extrapolated from older data using rather high growth rates to not underestimate energy/data for the purpose of the study (comparing downloading to physical delivery of CDs). Taking this in consideration the figure was a good approximation knowing it was probably a bit high and a good example how energy/data figure can be used even if the source data is dated back a few years. Considering the higher data traffic in Sweden per capita the figure compares well to this study. However, in the case of downloading larger files the performance of a data center is usually better but a conservative estimate was made for the purpose of that study. The Baliga (2009) study has modeled what can be considered as more of a state-of-the-art new all IP/optical network with high data traffic. The model looks to be excellent for such networks in the future but it seems the results for typical access data rates of today (or in 2010, 2.5 Mbps sold, 0.1 Mbps on average, 400 GB/year) is too low which can be explained by that this is an extreme case for the model. The figure 75 J/bit or 0.17 kWh/GB was presented in the study for Internet and low access data rates. The new equipment data used in the model is not representative for installed equipment in 2009/2010 and the CPE part power draw was only 5 W on average as only a simple modem was modelled. The physical data transmission links at the edge of the network seems to be underestimated compared to this study and the edge/metro/core part approaches zero for low bit rates (


Supplementary Information References Baliga et al 2009, Energy Consumption in Optical IP Networks. IEEE. Journal of Lightwave

Technology. Volume 27, issue 13: http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=4815495&url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel5%2F50%2F5133707%2F04815495.pdf%3Farnumber%3D4815495

Coroama, V., L. Hilty, E. Heiri, F. Horn. 2013. The direct Energy Demand of Internet Data Flows.

Journal of Industrial Ecology 17(5):680-688. Humar, I., Ge Xiaohu, Xiang Lin, Jo Minho, Chen Min, and Zhang Jing. 2011. Rethinking

energy efficiency models of cellular networks with embodied energy. Network, IEEE. vol. 25, no. 2. pp. 40-49.

Koomey, J. 2013. Does Your iPhone Use As Much Electricity As a New Refrigerator? Not Even

Close. Available at: http://thinkprogress.org/climate/2013/08/25/2518361/iphone-electricity-refrigerator/

Lundn, D., J. Malmodin. 2013. Changes in environmental impacts over time in the fast

developing ICT industry. LCM 2013, 26-29 August 2013, Gothenburg. Available at: http://conferences.chalmers.se/index.php/LCM/LCM2013/paper/view/580/180

Malmodin, J., . Moberg, D. Lundn, G. Finnveden and N. Lvehagen. 2010. Greenhouse Gas

Emissions and Operational Electricity Use in the ICT and Entertainment & Media Sectors. Journal of Industrial Ecology 14(5):770790.

Malmodin, J., P. Bergmark and D. Lundn. 2013. The future carbon footprint of the ICT and

E&M sectors. Paper presented at ICT for Sustainability (ICT4S), 9-12 February 2013, Zurich. Malmodin, J., D. Lundn., . Moberg, M. Nilsson and G. Andersson. 2014. Life cycle

assessment of ICT carbon footprint and operational electricity use from the operator, national and subscriber perspective in Sweden. Journal of Industrial Ecology xx(x):xxxxxx.

Mills, Mark P., The Cloud Begins With coal. Sponsored by National Mining Association American

Coalition for Clean Coal Electricity. Available at: http://www.tech-pundit.com/wp-content/uploads/2013/07/Cloud_Begins_With_Coal.pdf?c761ac

PTS (The Swedish Post and Telecom Agency). 2008. The Swedish Telecommunications Market

2007 - PTS-ER-2008:15. www.statistics.pts.se/start_en/. Accessed in October 2011. PTS (The Swedish Post and Telecom Agency). 2010. The Swedish Telecommunications Market



First Half Year 2013 - PTS-ER-2013:21. www.statistics.pts.se/start_en/. Accessed in January 2013.

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Schien, D., P. Shabajee, M. Yearworth and C. Priest. 2013. Modeling and Assessing Variability in Energy Consumption During the Use Stage of Online Multimedia Services. Journal of Industrial Ecology 17(6):800-813.

Weber et al. 2010b. The Energy and Climate Change Impacts of Different Music Delivery

Methods. The Journal of Industrial Ecology. vol. 14, no. 5. October. pp. 754769. Available at: http://dx.doi.org/10.1111/j.1530-9290.2010.00269.x

21

Table 1. Total annual GHG emissions (carbon footprint) per subscriber/line and per capita (average number of persons in connected households) for a number of fixed broadband (xDSL) cases in Sweden.Table 2. Total annual GHG emissions (carbon footprint) per average mobile broadband (3G/4G) subscription (sub) in Sweden. For comparison, a GSM sub 2010 with mainly voice/sms and some data and a smartphone, tablet and a laptop sub in 2013 with 3G/4G ...ReferencesTable S1.1. Global ICT sector key data for 2007 and 2020. The subscription (sub) numbers are per mid-year.Table S2.1. Number of fixed broadband data subscriptions (subs), electricity consumption and data traffic per year in fixed broadband networks in Sweden 2010 and 2013.Table S3.1. Number of mobile broadband data subscriptions (subs), electricity consumption and data traffic per year in mobile broadband networks (3G/4G) in Sweden 2006-2015.Table S4.1. Step-by-step comparison of the false claim and results presented in this study.Table S5.1. Year-end 2009 estimates for monthly Internet traffic based on MINTS (2009).Table S5.2. Comparison of energy per amount of data figures for fixed broadband data flows for various parts of the network based on (Malmodin et al. 2014). All energy figures presented are per GB data.Another new study (Schien et al. 2013) also compares energy/data figures from several other studies and also present own new figures. The new figures presented for mobile access and Internet network (0.3 kWh/GB) and fixed access and Internet network (...

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Malmodin - Energy and Carbon Footprint Performance Metrics