Energy => Carbon Climate => Action

ENGR40

Foothill College

Overview

• Historic carbon emissions => ppm CO2

• CO2 and warming => forcing models

• Economy (GDP) => energy intensity (BTU/$) => carbon intensity => CO2

• 2030 ppm CO2 => current trajectory

• Getting to $100T GDP staying under 450 ppm CO2 => how much clean energy?

GHG Emissions by Source

Carbon Burned Becomes CO2

• If you burn carbon, it must go somewhere

• Plot ATM [CO2] as a function of [carbon]

• It is a perfect straight line (r2 x 100 = 99%)– Slope = 2.55 e10-4 *M tons C / ppm CO2

– Intercept = 297 ppm CO2

– Correlation = .994

• Perfect way to model future carbon emissions• And the effect of carbon mitigation strategies

Carbon Burned and CO2

• Plot atmospheric CO2 as a function of cumulative carbon burned (mega tons)

• Linear regression has an almost perfect correlation coefficient (r2*100) of 99%

• Allows a confident prediction of future CO2 based on future carbon burned.

• Since forcing can be calculated directly from CO2, it is a very important model

Devin Cormia ‘The Gaia Hypothesis’ Carlmont High School AP Bio Term Project 2005

Global Fossil Emissions Through 2000Historic amounts of petroleum, coal, natural gas, and cement production

Carbon Emissions and CO2

• Carbon burned => CO2

• Linear from 1850 to 2000- ppm CO2 =2.55 e10-4 *M tons C

+ 297 ppm (r2*100=99%)

• ~ 50% of carbon goes into atmospheric CO2

– 30% missing carbon

• Trend is constant over 100 years – is this how the biosphere will react over the next 500 years?

Year C burned ppm CO21900 12307 2951910 19174 3001920 28050 3051930 37914 3101940 48566 3101950 62324 3151960 83453 3201970 115935 3251980 164083 3401990 219365 3502000 283373 370

Carbon Emissions and CO2

Carbon Emissions and CO2

250

270

290

310

330

350

370

390

0 50000 100000 150000 200000 250000 300000

Carbon Emissions in Million Tons

Atm

osp

her

ic C

O2

in p

pm

Carbon emissions can be used to predict atmospheric CO2

with 99% confidence using simple linear regression data

Wealth and Energy

• There is a strong correlation between wealth and energy – more income => more energy

• Plot log income as a function of log energy– 85% correlation (r=0.92)– Slope = 0.73– Intercept = 5.11

• In 2025, income at 10,000, population ~8x109

• Energy => 108 BTU x 8x109 people = 800 Quads

Affluence and Energy Use

Log Income vs. Log Energy

• RFF Report - population• Resources For the Future • http://www.rff.org/ • Three groups of countries

– Low income– Medium income– High income

• 800 BTU rise / $1 income• Baseline of ~ 125,000 BTU

Country Income Energy in BTU log income log energyKenya 350 4.00E+06 2.54 6.60Vietnam 390 7.30E+06 2.59 6.86Pakistan 440 1.27E+07 2.64 7.10India 450 1.15E+07 2.65 7.06Zimbabwe 460 1.13E+07 2.66 7.05Armenia 520 2.00E+07 2.72 7.30Congo 570 3.00E+06 2.76 6.48Indonesia 570 1.15E+07 2.76 7.06Georgia 630 2.50E+07 2.80 7.40China 840 2.70E+07 2.92 7.43Iran 1680 7.70E+07 3.23 7.89South Africa 3020 9.40E+07 3.48 7.97Turkey 3100 5.10E+07 3.49 7.71Brazil 3580 3.60E+07 3.55 7.56Venzuala 4310 9.20E+07 3.63 7.96Chile 4590 5.40E+07 3.66 7.73Mexico 5070 6.00E+07 3.71 7.78South Korea 8910 1.41E+08 3.95 8.15New Zealand 12990 1.70E+08 4.11 8.23Isreal 16710 1.21E+08 4.22 8.08Italy 20160 1.20E+08 4.30 8.08Australia 20420 2.64E+08 4.31 8.42Canada 21130 3.32E+08 4.32 8.52France 24090 1.28E+08 4.38 8.11United Kingdom 24430 1.40E+08 4.39 8.15Germany 25120 1.72E+08 4.40 8.24United States 34100 3.07E+08 4.53 8.49Japan 35620 1.43E+08 4.55 8.16

EIA Global Energy Demand

Future CO2 – the Next 30 Yrs

Year Emissions CO2

2000 283,373 369

2005 318,465 378

2010 357,209 388

2015 399,986 399

2020 447,216 411

2025 499,360 424

2030 556,932 439

Vostok Ice Core Data•A perfect correlation between CO2, temperature, and sea level•For every one ppm CO2, sea level rises 1 meter, temp rises .05 C (global)•Process takes 100 years to add 1 ppm CO2, and reach thermal equilibrium

This is not just a correlation, this is a complex and dynamic process, with multiple inputs. Touching one input affects all other inputs, and increases in temperature becomes a further feedback and multiplier of these inputs.

GHGs and Vostok Data

James Kirchner Department of Earth and Planetary Science, University of California, Berkeley

Forcing Models

• Calculating greenhouse numbers– Start with some basic physics– Get out your log calculator

• CO2 is straightforward to calculate– Generate forcing in watts, temps in

degrees C, factor in thermal inertia

• Data validated by NASA / NOAA– Model fits observed ocean warming well– Also explains the Vostok ice core data

Calculating Radiative Forcing

5.35 watts x ln [current ppm CO2] _______________ [historic ppm CO2]

Temperature increase C = 2/3 Watts radiative forcing

Forcing Model from GISS

• http://www.giss.nasa.gov/ • Definitive work in March 2005• 1,800 ocean buoys sampling temperatures at depth

of 0 to 2,500 meters from 1900 - 2000• Temps must rise 0.66 0C per 1 W of forcing• ‘Thermal inertia’ of oceans requires 25 to 50 years to

experience 60% of total ‘equilibration’• http://www.giss.nasa.gov/research/news/20050428/

Earth Out of Balance

http://www.giss.nasa.gov/research/news/20050428/

Missing feedbacks, asymmetric uncertainties, and the underestimation of future warmingMargaret S. Torn and John Harte AGU GEOPHYSICAL RESEARCH LETTERS, VOL. 33, L10703

Effect of Climate Feedbacks

PPM CO2 Temp input Feedback (g)Final

Temperature

350 0.50 C0.5 1.0 C0.7 1.7 C

400 0.75 C0.5 1.5 C0.7 2.3 C

450 1.00 C0.5 2.0 C0.7 3.3 C

500 1.25 C0.5 2.5 C0.7 4.2 C

550 1.50 C0.5 3.0 C0.7 5.0 C

Estimating the Effect of Climate Feedbacks to an Initial Thermal Input

Spreadsheet ModelingYear G tons C Cum C ppm CO2 forcing (W) temp force temp felt temp owed temp

2000 6.00 306.00 372.0 1.66 1.99 1.00 0.99 58.002001 6.12 312.12 373.5 1.69 2.02 1.02 1.00 58.022002 6.24 318.36 375.0 1.71 2.05 1.05 1.00 58.052003 6.37 324.73 376.6 1.73 2.08 1.07 1.01 58.072004 6.49 331.22 378.1 1.76 2.11 1.10 1.01 58.102005 6.62 337.85 379.8 1.78 2.14 1.13 1.01 58.132006 6.76 344.61 381.4 1.81 2.17 1.15 1.02 58.152007 6.89 351.50 383.1 1.83 2.20 1.18 1.03 58.182008 7.03 358.53 384.8 1.86 2.23 1.20 1.03 58.202009 7.17 365.70 386.6 1.89 2.26 1.23 1.04 58.232010 7.31 373.01 388.4 1.91 2.30 1.25 1.04 58.252011 7.46 380.47 390.2 1.94 2.33 1.28 1.05 58.282012 7.61 388.08 392.1 1.97 2.36 1.31 1.06 58.312013 7.76 395.84 394.0 2.00 2.40 1.33 1.07 58.332014 7.92 403.76 395.9 2.03 2.43 1.36 1.07 58.362015 8.08 411.84 397.9 2.06 2.47 1.39 1.08 58.392016 8.24 420.07 399.9 2.09 2.50 1.41 1.09 58.412017 8.40 428.47 402.0 2.12 2.54 1.44 1.10 58.442018 8.57 437.04 404.1 2.15 2.58 1.47 1.11 58.472019 8.74 445.78 406.2 2.18 2.61 1.50 1.12 58.502020 8.92 454.70 408.4 2.21 2.65 1.52 1.13 58.522021 9.09 463.79 410.6 2.24 2.69 1.55 1.14 58.552022 9.28 473.07 412.9 2.27 2.73 1.58 1.15 58.582023 9.46 482.53 415.2 2.31 2.77 1.61 1.16 58.612024 9.65 492.18 417.6 2.34 2.81 1.64 1.17 58.642025 9.84 502.03 420.0 2.37 2.85 1.67 1.18 58.67

Forcing / Heat From CO2

Year CO2 Forcing (W) 0C / 0F

1900 300 0.40 .27 / .48

1950 310 0.60 .40 / .71

1975 325 0.87 .58 / 1.05

2000 370 1.78 1.2 / 2.1

2025 420 2.37 1.6 / 2.8

2050 480 3.15 2.1 / 3.8

2075 510 3.50 2.3 / 4.2

2100 540 3.84 2.6 / 4.6

Forcing, Predicted Temperature, and Climate Lag, 2000 - 2100

00.51

1.52

2.53

3.54

4.55

2000 2025 2050 2075 2100

ForcingFeltOwed

0F -Model built assuming ~60% of forcing is felt in 25 – 50 years

Ocean Acidification

Ocean acidification is equally as dangerous as climate change, and actually slows the rate of the ocean’s CO2 pump, making GHG emissions more significant.

So What Can We Do?

• Stop burning fossil fuels – quickly• Invest in energy efficiency - lower BTU/$• Develop biofuels at scale – quickly• Replace coal with natural gas and wind• Put solar PV on EVERY viable rooftop• Lower building energy by at least 50%• Increase vehicle fuel efficiency => 50 mpg• Rethink nuclear power => thorium / PBMR

Clean Energy Economy

Honda Insight – MPG Champ

1 liter - 3 cylinders‘electric turbocharger’

61 / 70 MPGSeating for two

2,000 poundsAll aluminum body

No Gas Required

Move Differently

• SolarSegway™• Range ~8 - 12 miles• Battery packs can be

charged locally (~5 hrs)• Emission free vehicle

– Solar panels ‘extra’

• Projected cost of $2,500 in quantity

Sustainability Base

Will it be Enough?

• Probably not, but it’s the right direction

• Focus on efficiency and fuel switching

• Phasing out fossil fuels is necessary for pollution and geopolitical reasons alone

• Building and vehicle efficiency save $s

• Need to counter the effect of I=PAT– population => wealth => energy => IMPACT

Global Carbon Profiles

India 0.3

China 0.6

Mexico 1.0

France 2.0Germany 2.2

England 2.5

Canada 4.0

USA 5.1

Developing World

Europe

North America

Tons of carbon per person – year 2000 average = ~1.1 2025 at least 1.25

Calculating I=PAT

• Calculating I=PAT– Population– Affluence– Technology

• Look at 6.6 x 109 people growing to ~8 x 109

• Carbon per person grows from ~1.2 to ~1.5

• Global GHG emissions rise by 50% by 2025

• Cannot have global energy based on carbon

8 billion people @ 1.25 tons each = 10 G tons of carbon / yearThat is 50% more carbon emissions than today!

The Population Problem

Numbers Matter

• Get BTU per dollar GDP from 8,000 to 5,000– stretch goal is 2500 BTU/$ , radical efficiency

• At $100T GDP => still at 500 quads energy

• Lower carbon intensity from %85 to <50%

• Increase efficiency while simultaneously lowering carbon intensity => diet / exercise

• Produce energy locally with PV and wind

• Replace all of coal with advanced nuclear

From Information to Choices

We can do this, but the clock is running!

What You Can Do

• Drive less, drive smart • Invest in clean energy• Conserve on energy use• We need to cut CO2 emissions by 80%• Be deeply aware of the problem

– This is the most significant problem facing the planet over the next 50 to 100 years

– Single largest economic opportunity ever!

References

• http://www.realclimate.org/ • http://www.giss.nasa.gov/• http://www.sc.doe.gov/ober/CCRD/model.html• http://www.nersc.gov/projects/gcm_data/ • http://www.fuelcells.org/• http://www.solarelectricpower.org/ • http://www.nrel.gov/• http://www.eia.doe.gov/ • http://en.wikipedia.org/wiki/Peak_oil