Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Emissions slowdown: Are we on the way to 2°C?

702 views

Published on

A presentation to Industrial Ecology students at the Institute of Environmental Sciences (CML) at Leiden University, at the invitation of Rene Kleijn. I discuss recent trends in CO2 emissions, and link the recent slowdown to emission scenarios. I then go through some key features of 2C scenarios and implications for policy. In the presentation I did not get a chance to present the new scenarios, Shared Socioeconomic Pathways (SSPs), or on stranded assets, but the slides are still included.

Published in: Environment
  • Be the first to comment

  • Be the first to like this

Emissions slowdown: Are we on the way to 2°C?

  1. 1. Emissions slowdown: Are we on the way to 2°C? Glen Peters (CICERO) Institute of Environmental Sciences (CML) at Leiden University, 04/09/2017
  2. 2. • Emission trends in the last decades • Emission scenarios • The trouble with negative emissions – What are negative emissions? • The trouble with carbon capture and storage • Integrated Assessment Models • Stranded assets • Discussion Overview
  3. 3. Key changes in emissions (1960-2016)
  4. 4. Emissions growth has been flat for the last three years, perhaps ending a long period of near continuous growth Emissions from land-use change have no significant trend, but are a declining share of the total emissions. Estimates of fossil fuel and industry emissions are preliminary 2017 estimates. Land-use change is from 2016 and is to be updated. Source: CDIAC; Le Quéré et al 2016; Global Carbon Budget 2016 Three years with near-zero growth! 2017 data (preliminary) 2016 data (to be updated)
  5. 5. CO2 emissions a record high, so expect record high increase in CO2 concentrations (plus El Niño) How many years would it take to verify flat CO2 emissions in atmospheric measurements? Source: Peters (2017), Can we trust emission statistics? Are the emissions data bogus? (no)
  6. 6. Key changes in emissions (2000-2020)
  7. 7. The top four emitters in 2015 covered 60% of global emissions China (29%), United States (15%), EU28 (10%), India (6%) Bunker fuels are used for international transport is 3.1% of global emissions. Statistical differences between the global estimates and sum of national totals are 1.2% of global emissions. Source: CDIAC; Le Quéré et al 2016; Global Carbon Budget 2016 Top emitters: fossil fuels and industry
  8. 8. Declines in some countries are currently balanced by increases in others Positive progress in China, US, EU, offset by increases in India and Rest of the World Source: Global Carbon Budget (2017, unpublished), Peters (2017) Who is winning the emissions tug-of-war? What is behind the sudden change?
  9. 9. The unexpected declines in coal and levelling of cement are offset by continued growth in oil and gas Coal and cement are on the decline, while oil and gas march ahead Source: Global Carbon Budget (2017, unpublished), Peters (2017) Who is winning the emissions tug-of-war? The fossil fuel tug-of-war
  10. 10. Rapid (relative) growth in solar and wind reaches the headlines, but offset by (relative) small changes in fossil fuels Source: BP 2017; Jackson et al 2015; Global Carbon Budget 2016 Solar & wind are helping (a little)
  11. 11. What is causing emissions to change in each country? Tracking Progress (2000-2020)
  12. 12. Focus on too many moving parts makes it difficult to attribute drivers of change We instead perform a nested analysis, slowly digging deeper where needed Source: Peters et al 2017 Nested structure of key indicators
  13. 13. Using annual growth rates (% per year) ΔCO2 = ΔGDP + Δ(Energy Intensity) + Δ(Carbon Intensity) ΔCO2 = ΔGDP + Δ(E/GDP) + Δ(CO2/E) + Δinteractions Kaya Identity Source: Peters et al 2017
  14. 14. CO2 emissions growth (black) slowing due to: Slower GDP growth (green), renewed improvements in efficiency (purple), & renewable energy (orange) All data is smoothed with a 11 year window. Source: Peters et al 2017 China: earlier peak? Earlier peak in emissions if: • Faster declines in intensity • Slower GDP growth • Combination of both China may have peaked already
  15. 15. CO2 emissions growth (black) slowing due to: Slower GDP growth (green), coal to gas (orange) & renewable energy (orange) All data is smoothed with a 11 year window. Source: Peters et al 2017 United States of America: Trump? US needs to lock in gains: • Risk with stronger GDP • Economics of gas & renewables may win
  16. 16. CO2 emissions growth (black) slowing due to: Slower GDP growth (green), continued improvements in efficiency (purple) & renewable energy (orange) All data is smoothed with a 11 year window. Source: Peters et al 2017 European Union: Remains a leader? EU can accelerate gains: • Risk with stronger GDP • Strengthen policies driving efficiency, renewables
  17. 17. CO2 emissions growth (black) growing due to: Strong GDP growth (green), low improvements in efficiency (purple) All data is smoothed with a 11 year window. Source: Peters et al 2017 India: Can rapid growth be avoided? Uncertainties: • Coal expansion • Renewables growth 2017 may be a one-off decline!
  18. 18. The future is uncertain, and we use scenarios to explore these future uncertainties Emission scenarios
  19. 19. • “Holding the increase … to well below 2°C … pursue efforts to limit … to 1.5 °C …” • “global peaking … as soon as possible … undertake rapid reductions … achieve a balance between … sources and … sinks … in the second half of this century” • This is roughly consistent with 2°C, 66% ‘chance’ – This gives a median temperature of about 1.6-1.8°C • IEA 450 scenario is a 50% ‘chance’ at 2°C The Paris Agreement Source: Peters (2017)
  20. 20. Source: IEA World Energy Outlook (2016) IEA Emission Scenarios (energy only) Current Policies: Policies in place as of mid-2016; New Policies: includes Nationally Determined Contributions (consistent with Paris Agreement); 450 Scenario: Keep global average temperature increase below 2°C above pre-industrial levels by 2100 (50% chance)
  21. 21. IEA below 2C scenario requires net zero by: 2040 for fuel transformation, 2050 for power generation, 2060 total CO2 Source: ETP (2017) Energy Technology Perspectives
  22. 22. IPCC assessed about 1200 scenarios, and about 120 different “2°C scenarios” Different scenarios cover different models, policy start dates, technology portfolios, etc Light lines: The IPCC Fifth Assessment Report assessed about 1200 scenarios using Integrated Assessment Models (IAMs) Dark lines: Detailed climate modelling was done on four Representative Concentration Pathways (RCPs) Source: Fuss et al 2014; CDIAC; IIASA AR5 Scenario Database; Global Carbon Budget 2016 There are many options to stay below 2°C
  23. 23. IPCC assessed about 1200 scenarios, and about 120 different “2°C scenarios” Different scenarios cover different models, policy start dates, technology portfolios, etc Light lines: The IPCC Fifth Assessment Report assessed about 1200 scenarios using Integrated Assessment Models (IAMs) Dark lines: Detailed climate modelling was done on four Representative Concentration Pathways (RCPs) Source: Fuss et al 2014; CDIAC; IIASA AR5 Scenario Database; Global Carbon Budget 2016 There are many options to stay below 2°C External to the IAM community, lack of understanding of negative emissions and their consequences…
  24. 24. There are not many variations in pathway to keep below 2°C, but there are many different baselines Baseline uncertainty may be one of the biggest uncertainties on cost! Importance of the baseline Emission pledges
  25. 25. Source: Shades of Climate Risk (2017) Scenario stress testing
  26. 26. The trouble with negative emissions
  27. 27. Net emissions = CO2 emissions from fossil fuels, industrial processes, land-use change, and bioenergy with CCS Source: Anderson & Peters (2016) The trouble with negative emissions
  28. 28. Net emissions = CO2 emissions from fossil fuels, industrial processes, land-use change, and bioenergy with CCS CO2 removal starts in 2020-2030 and rises to 15 billion tonnes CO2 per year in 2100 Source: Anderson & Peters (2016) The trouble with negative emissions
  29. 29. Less CO2 removal requires more rapid reductions in fossil fuel and industry emissions Source: Anderson & Peters (2016) Are negative emissions a moral hazard? With BECCS Without BECCS
  30. 30. A schematic of negative emissions
  31. 31. Carbon Capture and Storage (CCS) and “Negative Emissions” allows the budget to be exceeded Note: Totals are not always consistent because medians are not additive, and some columns have different numbers of scenarios Source: Peters (2016) The carbon budget and CCS
  32. 32. CCS allows the use of fossil fuels and BECCS offsetting of previous or postive emissions If CCS (hence BECCS) don’t live up to scale, fossil fuels use has to decline rapidly Source: Peters (2016) No CCS means no fossil fuels (or no 2°C)
  33. 33. BECCS is not just for 2°C, but whenever there is mitigation BECCS is used in scenarios To stabalise temperature at any given level, likely we need to have negative emissions Source: IIASA AR5 Scenario Database (own calculations) BECCS by forcing level in 2100 ~1.6°C ~2.0°C ~2.6°C ~3.4°C Median temperature
  34. 34. • Even if BECCS is a “moral hazard”, we still need research, development, deployment, ... – …but we need to act as if BECCS will not work at scale – …treat “Plan A (high BECCS)” as a pleasant surprise • We can’t just accept model results, we have to challenge them, make sure they are robust • No matter at what temperature we stabilize, we need negative emissions A few clarifications…
  35. 35. Negative emission technologies
  36. 36. Source: MCC 2016 Negative emission technologies
  37. 37. Source: Smith et al. 2016 Land, water & energy requirements
  38. 38. The trouble with carbon, capture & storage
  39. 39. A typical CCS facility today is about 1MtCO2/yr storage (e.g., Sleipner) → 1000 facilities per 1GtCO2 We can build 10’s of CCS facilities, but can we scale up to 10,000s over the next decades? Today, there is capture capacity of 28MtCO2/yr, but only about 7.5MtCO2/yr is verified as stored (IEA). Source: Based on IIASA AR5 Scenario Database Carbon Capture and Storage
  40. 40. We have had great success in solar and wind, and largely consistent with scenarios (IPCC) Scenarios indicate the path to 2°C requires large scale bioenergy and CCS (with little progress) Source: Peters et al 2017, Based on IIASA AR5 Scenario Database Solar/wind versus CCS
  41. 41. • Deployment rates consistent with historical examples – Nuclear in Europe, coal in China • Energy system optimization models: – Short-term reductions more expensive than cost of negative emissions in the long-term (given constraints, model structure) • Comparisons of CCS deployment in IAMs – Large variation in results not explained by model assumptions – CCS complex interplay of several factors in each model Sources: van Sluisveld et al (2015); van Vuuren et al (2015); Koelbl et al (2014) Why do models love CCS?
  42. 42. Today, robust scientific debate over 1EJ/yr, scenarios are 100-300EJ/yr between 2050 and 2100 Need to have a clear and accessible narrative on why 100-300EJ/yr is carbon neutral Source: Based on IIASA AR5 Scenario Database Bioenergy use
  43. 43. This is direct output from the AR5 scenario database, land areas comparable to the size of India Some in the IAM community have critiqued figures like this as misleading. Source: Based on IIASA AR5 Scenario Database Land use for energy crops
  44. 44. • Bioenergy ranges are broad, generalizations are elusive • Results determined by a combination of assumptions: – Biomass feedstock supplies – Bioenergy options and costs – Other technology options and costs – Integrated systems modeling – Baselines • Elucidating & assessing this requires a dedicated effort… Why do models love bioenergy? Source: Rose et al (2014)
  45. 45. The range of estimates is primarily driven by the choice of alternative assumptions & should be viewed as ‘what if’ scenarios Larger estimates are invariably based on more challenging assumptions, which would be more difficult to implement in practice Source: Slade et al (2014) Bioenergy potential
  46. 46. High bioenergy use can be consistent with minimal land impacts, on the assumption of yield improvements Afforestation leads to greater land impacts Source: Humpenöder et al (2014) Importance of yield improvements
  47. 47. A new generation of emission scenarios
  48. 48. In the lead up to the IPCC’s Sixth Assessment Report new scenarios have been developed to more systematically explore key uncertainties in future socioeconomic developments Five Shared Socioeconomic Pathways (SSPs) have been developed to explore challenges to adaptation and mitigation. Shared Policy Assumptions (SPAs) are used to achieve target forcing levels (W/m2). Source: Riahi et al. 2016; IIASA SSP Database; Global Carbon Budget 2016 Shared Socioeconomic Pathways (SSPs)
  49. 49. Each SSP represents a different hypothetical “world” Each world has different baselines and challenges to mitigation and adaptation Five Shared Socioeconomic Pathways (SSPs) have been developed to explore challenges to adaptation and mitigation. Shared Policy Assumptions (SPAs) are used to achieve target forcing levels (W/m2). Source: Riahi et al. 2016; IIASA SSP Database; Global Carbon Budget 2016 Shared Socioeconomic Pathways (SSPs)
  50. 50. Viewing the all the scenarios on one figure is easier, but hides many of the important features of SSPs Several SSP realisations are taken forward as SSP-RCP combinations for CMIP6 Five Shared Socioeconomic Pathways (SSPs) have been developed to explore challenges to adaptation and mitigation. Shared Policy Assumptions (SPAs) are used to achieve target forcing levels (W/m2). Source: Riahi et al. 2016; IIASA SSP Database; Global Carbon Budget 2016 Shared Socioeconomic Pathways (SSPs) No climate policy baselines
  51. 51. 2°C scenarios have rapid declines in CO2 emissions over the century, leading to net negative emissions (removing carbon from the atmosphere) Fossil fuel & industry CO2 Five Shared Socioeconomic Pathways (SSPs) have been developed to explore challenges to adaptation and mitigation. Shared Policy Assumptions (SPAs) are used to achieve target forcing levels (W/m2). Source: Riahi et al. 2016; IIASA SSP Database; Global Carbon Budget 2016
  52. 52. According to scenarios, most mitigation occurs by decarbonising the energy system (as opposed to energy efficiency) Five Shared Socioeconomic Pathways (SSPs) have been developed to explore challenges to adaptation and mitigation. Shared Policy Assumptions (SPAs) are used to achieve target forcing levels (W/m2). Source: Riahi et al. 2016; IIASA SSP Database; Global Carbon Budget 2016 Carbon intensity (CO2/Energy)
  53. 53. Bioenergy may be as high as 500EJ/yr in 2100, cycling about 50GtCO2/yr biogenic carbon into the atmosphere Crop areas could use 250-1500 million hectares (India is 330 million hectares) Five Shared Socioeconomic Pathways (SSPs) have been developed to explore challenges to adaptation and mitigation. Shared Policy Assumptions (SPAs) are used to achieve target forcing levels (W/m2). Source: Riahi et al. 2016; IIASA SSP Database; Global Carbon Budget 2016 Bioenergy (exajoules)
  54. 54. Carbon Capture & Storage (CCS) could be as high as 50GtCO2/yr in 2100, with more potential for leaks at scale Five Shared Socioeconomic Pathways (SSPs) have been developed to explore challenges to adaptation and mitigation. Shared Policy Assumptions (SPAs) are used to achieve target forcing levels (W/m2). Source: Riahi et al. 2016; IIASA SSP Database; Global Carbon Budget 2016 Carbon capture and storage
  55. 55. Bioenergy with CCS could be up to 40GtCO2/yr in 2100, & net negative 20GtCO2/yr putting pressure on CO2 cycle Five Shared Socioeconomic Pathways (SSPs) have been developed to explore challenges to adaptation and mitigation. Shared Policy Assumptions (SPAs) are used to achieve target forcing levels (W/m2). Source: Riahi et al. 2016; IIASA SSP Database; Global Carbon Budget 2016 Bioenergy with CCS
  56. 56. Energy optimization models Integrated Assessment Models
  57. 57. • Energy system optimisation models (generally) – Find “best available” from given alternatives – Prone to corner solutions • Structural and parametric uncertainties • Model validation • What is feasible? – Physical, technical, economic, social, political, … (Global) energy system optimization
  58. 58. Smith et al 2005 (agricultural sector): estimated realistically achievable potential (~10% of biological potential) “Although this value is derived predominantly from expert judgment, it may be useful…” What is “feasible”?
  59. 59. Scenarios and the oil/gas industry Stranded assets
  60. 60. Climate change is a long-term problem, fossil fuel industries have long-term investments Can’t stop the discussion in 2040… Light lines: The IPCC Fifth Assessment Report assessed about 1200 scenarios using Integrated Assessment Models (IAMs) Dark lines: Detailed climate modelling was done on four Representative Concentration Pathways (RCPs) Source: Fuss et al 2014; CDIAC; IIASA AR5 Scenario Database; Global Carbon Budget 2016 There are many options to stay below 2°C
  61. 61. Source: Statoil Energy Perspectives (2016); IIASA AR5 Scenario Database Oil: Looking beyond 2040…
  62. 62. Because oil consumption declines faster after 2040, existing assets become stranded Source: Statoil Energy Perspectives (2016); IIASA AR5 Scenario Database Oil: Looking beyond 2040…
  63. 63. Because oil consumption declines faster after 2040, existing assets become stranded Building infrastructure to meet 2040 demand will come with high risk in the follow decades Source: Statoil Energy Perspectives (2016); IIASA AR5 Scenario Database Oil: Looking beyond 2040…
  64. 64. A rapid decline in coal gives more space for oil and gas, CCS dependent Though, coal producers have a different view… Source: Statoil Energy Perspectives (2016); IIASA AR5 Scenario Database “depending on what you think about coal”
  65. 65. Discussion
  66. 66. • Positive progress in the last few years – Currently, CO2 emission and concentration data consistent – Changes driven by China, but generally weaker economies • Expect emissions in the next ten years to be flat(ish) – An emission tug-of-war between forces up and forces down – Paris Agreement pledges consistent with flat emissions • Are we on the way to 2°C? – Positive progress in wind and solar – Negative progress in most other areas… Discussion (1)
  67. 67. • It appears 2°C will require negative emissions – To offset hard to mitigate sectors (e.g., rice) – To offset earlier emissions (too much CO2) – It could be more cost effective (?) • If negative emissions don’t work – We followed the wrong pathway – We may need geoengineering • All negative emission technologies have issues – We need serious investment in technologies Discussion (2)
  68. 68. Peters_Glen cicero.oslo.no cicerosenterforklimaforskning glen.peters@cicero.oslo.no Glen Peters

×