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Mobile Energy Efficiency

Mobile Energy Efficiency. Mobile and Environmental Sustainability 20 September 2012. Executive summary.

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Mobile Energy Efficiency

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  1. Mobile Energy Efficiency Mobile and Environmental Sustainability 20 September 2012

  2. Executive summary • In July 2012 the GSMA published “Mobile’s Green Manifesto 2012” which presented aggregate data derived from the Mobile Energy Efficiency (MEE) benchmarking project and quantified the industry’s enabling potential • In 2010, mobile network energy consumption (120 terawatt hours) and carbon emissions (70 million tonnes) are low compared to other industries such as aviation (650 million tonnes of carbon emissions) • Despite considerable growth in connections and traffic between 2009 and 2010, global mobile network energy consumption increased only modestly, by 1.6%, and declined per connection (5.4%) and per unit of traffic (19%) • Mobile enabled an emissions reduction of approximately 3 million tonnes of carbon in 2011. However, mobile has the potential to reduce 900 million tonnes of carbon in 2020, largely driven by machine to machine connections gaining scale

  3. The GSMA’s Mobile Energy Efficiency service benchmarks energy consumption for 35 operators representing over 200 networks

  4. The benchmarking output assists in the measurement and management of industry energy costs and carbon emissions 2010: 5 bn 120 TWh $13 bn 70 Mt 100% South & Central America 90% 80% East Europe 70% Middle East 60% West Europe 50% Africa 40% 30% USA & Canada 20% Asia Pacific 10% 0% Connections Energy Consumption Energy Cost CO2 Emissions If all networks with above average energy consumption are improved to the industry average, this implies a potential energy cost saving of $1 billion per annum at 2010 prices. Improving to the top quartile saves potentially over $2 billion annually Source: GSMA. Note costs exclude the capital cost of diesel generators and their maintenance

  5. Estimated total industry mobile network energy increased slightly from 2009 to 2010, but decreased per connection and per unit traffic Estimated Total industry RAN + Core Energy TWh Estimated Total industry RAN + Core Energy per connection kWh / connection Estimated Total industry RAN + Core Energy per unit traffic kWh / GB +1.6% 25.5 121 119 33.6 -5.4% 24.1 -19% 27.2 Note: This analysis is based on 34 networks where data for 2009 and 2010 was high quality, with the % changes applied to estimated global totals and averages. The dataset was equally split between developed and emerging markets but not truly representative as the growth in connections was lower than the true global total. The definition of energy here is total energy, whether from electricity or diesel Source: GSMA

  6. Mobile has the potential to enable significant reduction of GHG emissions and energy costs

  7. Mobile has the potential to enable emissions savings that are much greater than its own emissions Forecast mobile GHG emissions vs. enabled GHG emissions savings, Mt CO2e 900 3.5 billion M2M connections 100 billion M2M connections 26 million M2M connections 80 75 70 3 18 Note: Includes dematerialisation. Excludes double-counting and rebound effects Source: GSMA Analysis

  8. Smart grids and meters have the largest potential for mobile-enabled emissions reduction Potential GHG emission savings in smart grids & meters, Mt CO2e, 2020 Note: Excludes double-counting and rebound effects Source: GSMA Analysis

  9. Transportation and logistics is the other main area where mobile enabled emissions reduction is high Potential GHG emission savings in transport & logistics, Mt CO2e, 2020 Note: Excludes double-counting and rebound effects Source: GSMA Analysis

  10. Conclusions • The mobile industry needs to continue to address its own emissions, both in terms of measurement and management • To fulfil the significant potential to enable emissions reductions, more work needs to be done to understand how to accelerate growth to fully exploit the potential. Reasons why the enabled emissions reduction today appears relatively low may include the the slow speed of smart grid launches, and the lack of capex in the fleet management sector during tough economic times, but this needs further study

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