Climate Change by the Numbers 3978

8/6/2019 Climate Change by the Numbers 3978

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Climate Change

By the NumbersRobert D. Cormia

Foothill College



Overview

• The Greenhouse effect

• Earth’s biogeochemical thermostat

• Industrial carbon emissions – 250 yrs• GHG forcing models – projected heat

• Warming effects – on the cryosphere

• Affluence, energy, GHGs, and iPAT – Two easy solutions – mpg and efficiency

– One program – the Electron Economy



Solar Energy - earth’s Heat

http://www.ncdc.noaa.gov/oa/climate/globalwarming.html



250 years of Carbon Emissions

It took 125 years to burn the first trillion barrels of oil – we’ll

burn the next trillion in less than 30 years – why should you care?



Rising CO2 over 50 Years

http://earthguide.ucsd.edu/globalchange/keeling_curve/01.html

See saw swings in CO2 result from seasonal ‘biological production’





http://www.mala.bc.ca/~earles/ipcc-tar-feb01.htm

Temperatures over 1000 Years





Story of Vostok

• 500,000 years of ice core data

• CO2 / CH4 and temperature track perfectly!

• Why is this?• Earth uses GHGs as a regulatory process

– Biogeochemical thermostat

–Raise CO

2and you raise temps

• Nothing could be worse than burning carbon – It guarantees that the planet will get warmer



Ice Cores – Story of Vostok



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, withmultiple inputs. Touching one input affects all other inputs, and increases

in temperature becomes a further feedback and multiplier of these inputs.



Vostok CO2 and

Temperature

• The relationshipbetween CO2 and

temperature isnearly perfect(r 2*100 = 99)

• However, the casual

relationship is thebasis for significant(expert)controversy

• Why does this occur?



The Vostok Equilibrium

• Vostok ‘equilibrium’• 100K year cycles

– earth’s orbital

eccentricity• Sun heats up the planet

– Biosphere expands

• CO2 maintains temp

– Otherwise earth wouldbe very cold ~ 0 degrees F

– CO2 has not

exceeded 280 ppmin the last 500K



GHGs and Vostok Data

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



The Thermostat Inputs

• CO2 - largest input

• CH4 – most potent input

• Water vapor – potent GHG• Clouds – absorb / reflect

• Albedo – moderates energy

• Temperature – Reacts to increased forcings

– Amplifies / induces other inputs

http://images.google.com/imgres?imgurl=http://www.bradfordschools.net/hotpot/Unit%25208.1/thermostat.gif&imgrefurl=http://www.bradfordschools.net/hotpot/Unit%25208.1/81.htm&h=568&w=606&sz=15&hl=en&start=16&sig2=hcz6wcjOecLDKDYJiIQfbw&tbnid=HkUBe-M6cbOMtM:&tbnh=127&tbnw=136&ei=RFksSKLaG4_eigHSxozvBQ&prev=/images%3Fq%3Dthermostat%26gbv%3D2%26hl%3Den



Dials on the Thermostat

CO2

CH4

Ice / albedo

Water vapor Clouds

Temperature

GHGs force energy into the planet, surface warming leads to feedbacks

Thermal inertiaClimate feedbacksGHGs



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



The Alpine Effect

90% reflective, 10% absorptive

50% reflective, 50% absorptive

A surface that is 90% reflective absorbs 10% of incident solar radiationA surface that is 50% reflective absorbs 50% of incident solar radiation

When surfaces melt and refreeze, surface texture changes, it is no longer ‘white’, and a much higher amount of incident solar radiation is absorbed .

Alpine surfaces are undergoing these changes, and absorbing five times or more of the solar radiation – not from being warmer, but from being ‘darker’

Permafrost is especially at risk of warming as the surface albedo changes



Carbon Burned and CO2

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

• Linear regression has an almost perfect

correlation coefficient (r 2*100) of 99%• Allows a confident prediction of future

CO 2 based on future carbon burned .

• Since forcing can be calculated directlyfrom CO2, it is a very important model!

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



Carbon Emissions and CO2


250

270

290

310

330

350

370

390

0 50000 100000 150000 200000 250000 300000

Carbon Emissions in Million Ton

A t m o s p h e r i c C O

2 i n p p m

Carbon emissions can be used to predict atmospheric CO2

with 99% confidence using simple linear regression data




• Carbon burned => CO2

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

tons C + 297 ppm(r 2*100=99%)

• ~ 50% of carbon goesinto atmospheric CO2

– 50% into soil andoceans

• Trend is constant over 100 years – is thishow the biosphere will

react over the next500 ears?

Year C burned ppm CO2

1900 12307 295

1910 19174 300

1920 28050 305

1930 37914 310

1940 48566 310

1950 62324 315

1960 83453 320

1970 115935 325

1980 164083 340

1990 219365 3502000 283373 370




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 deg C

• Data validated by NASA / NOAA

– Model fits observed ocean warming well

– Also explains the Vostok ice core data



Forcing Model from GISS

• http://www.giss.nasa.gov/

• Definitive work in March 2005

• 1,800 ocean buoys sampling sea temperatures

to a depth of ~2,500 meters from 1990 - 2000• Temps must rise 0.66 0C per 1 W of forcing

• ‘Thermal inertia’ of oceans requires 25 to 50years to experience 60% of total‘equilibration’

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

Earth’s Energy Imbalance: Confirmation and Implications James Hansen,* Larissa Nazarenko, Reto Ruedy, Makiko Sato,Josh Willis, Anthony Del Genio, Dorothy Koch, Andrew Lacis, Ken Lo, Surabi Menon, Tica Novakov, Judith Perlwitz, Gary Russell,Gavin A. Schmidt, Nicholas Tausnev – http://www.sciencexpress.org / 28 April 2004 / Page 1/ 10.1126/science.1110252

http://www.giss.nasa.gov/


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





http://www.grida.no/climate/vital/04.htm





Earth Out of Balance







Calculating Radiative Forcing

5.35 watts x ln

[current ppm CO2]

_______________

[historic ppm CO2]

Temperature increase C = 2/3 Watts radiative forcing

Historic CO2 is 280 ppm, current CO2 is 387 ppm



NASA Climate Model

http://www.giss.nasa.gov/edu/gwdebate/






Putting it all Together

• Spreadsheet modeling

– Carbon burned becomes CO2

– More CO2 leads to radiative forcing

– Radiative forcing warms the earth

– Need to factor in thermal inertia

• Shows where temperatures are headed

• Use it for modeling mitigation strategies

•



Projected 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




Thermal Inertia

• Takes 25 to 50 years to warm to 60%equilibrium => radiative forcing (37.5 yrs)

• You can model that in with an exponent:

• Raise 0.975 to the 37.5th power – Each year 2.5% of warming is realized

– Need 37.5 years to reach 60% equilibrium

• In 37.5 years you are at 39% (pretty close)

With calculus you could do this even better



Spreadsheet Modeling Year 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 58.00

2001 6.12 312.12 373.5 1.69 2.02 1.02 1.00 58.02

2002 6.24 318.36 375.0 1.71 2.05 1.05 1.00 58.05

2003 6.37 324.73 376.6 1.73 2.08 1.07 1.01 58.07

2004 6.49 331.22 378.1 1.76 2.11 1.10 1.01 58.10

2005 6.62 337.85 379.8 1.78 2.14 1.13 1.01 58.13

2006 6.76 344.61 381.4 1.81 2.17 1.15 1.02 58.15

2007 6.89 351.50 383.1 1.83 2.20 1.18 1.03 58.18

2008 7.03 358.53 384.8 1.86 2.23 1.20 1.03 58.20

2009 7.17 365.70 386.6 1.89 2.26 1.23 1.04 58.23

2010 7.31 373.01 388.4 1.91 2.30 1.25 1.04 58.25

2011 7.46 380.47 390.2 1.94 2.33 1.28 1.05 58.28

2012 7.61 388.08 392.1 1.97 2.36 1.31 1.06 58.31

2013 7.76 395.84 394.0 2.00 2.40 1.33 1.07 58.33

2014 7.92 403.76 395.9 2.03 2.43 1.36 1.07 58.36

2015 8.08 411.84 397.9 2.06 2.47 1.39 1.08 58.39

2016 8.24 420.07 399.9 2.09 2.50 1.41 1.09 58.41

2017 8.40 428.47 402.0 2.12 2.54 1.44 1.10 58.44

2018 8.57 437.04 404.1 2.15 2.58 1.47 1.11 58.47

2019 8.74 445.78 406.2 2.18 2.61 1.50 1.12 58.50

2020 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 58.55

2022 9.28 473.07 412.9 2.27 2.73 1.58 1.15 58.58

2023 9.46 482.53 415.2 2.31 2.77 1.61 1.16 58.61

2024 9.65 492.18 417.6 2.34 2.81 1.64 1.17 58.64

2025 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 / .711975 325 0.87 .58 / 1.05

2000 380 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

0

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



The Melting North Pole

The North Pole is thinning in area ~10% per decade, and thinning inthickness ~1 meter per decade. At these rates, it may be an open sea asearly as 2020 – 2030. Water then becomes an absorber, not a reflector.

http://earthobservatory.nasa.gov/Study/ClimateClues/





Arctic Ice Loss

• Accelerating ice lossover the last 30 years

• One meter already lost,in ~20 years (1975-1995)

• Rate now at 0.1 meters /yr or ~1 meter /decade

• North pole could be gonein summer by ~2015/20

• Affects heat entering the

permafrost, nowwarminghttp://earthobservatory.nasa.gov/Study/ClimateClues /










Arctic Sea Ice Thickness

http://www.nasa.gov/vision/earth/environment/Arctic_Warming_ESU.html





Greenland Ice Change

http://www.comcast.net/data/news/photoshow/html/news/246569.html







Long Term Warming Effects



Wealth and Energy

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

• Plot log income as a function of logenergy

– 85% correlation (r=0.92)

– Slope = 0.73 – Intercept = 5.11

• By 2030, income = $10,000,

population ~8x109



Affluence and Energy Use

slope intercept correlation

.0 730938814 .5 107092 .0 91899

Income in dollars per capita per year

Lo

g

ene

rgyBTU/p

ers

on

/year

Affluence and Energy Us

6.00

6.50

7.00

7.50

8.00

8.50

9.00

2.00 2.50 3.00 3.50 4.00 4.50 5.00

Log Income (base 10

L o g E n e r g y ( b a s e 1 0 )



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

• 10,000 BTU rise / $1 income• Baseline of ~ 125,000 BTU

Country Income

n er gy i nBT U

o g i nc om e

o g e ne rg yKenya 350 . +4 00E 06 .2 54 .6 60

Vietnam 390 . +7 30E 06 .2 59 .6 86

Pakistan 440 . +1 27E 07 .2 64 .7 10

India 450 . +1 15E 07 .2 65 .7 06

Zimbabwe 460 . +1 13E 07 .2 66 .7 05

Armenia 520 . +2 00E 07 .2 72 .7 30

Congo 570 . +3 00E 06 .2 76 .6 48

Indonesia 570 . +1 15E 07 .2 76 .7 06

Georgia 630 . +2 50E 07 .2 80 .7 40

China 840 . +2 70E 07 .2 92 .7 43

Iran 1680 . +7 70E 07 .3 23 .7 89 S ou th A fr ic a 3 02 0 . +9 40E 07 .3 48 .7 97

Turkey 3100 . +5 10E 07 .3 49 .7 71

Brazil 3580 . +3 60E 07 .3 55 .7 56

Venzuala 4310 . +9 20E 07 .3 63 .7 96

Chile 4590 . +5 40E 07 .3 66 .7 73

Mexico 5070 . +6 00E 07 .3 71 .7 78

So uth K or ea 8 910 . +1 41E 08 .3 95 .8 15

N ew Z ea la nd 1 29 90 . +1 70E 08 .4 11 .8 23

Isreal 16710 . +1 21E 08 .4 22 .8 08

Italy 20160 . +1 20E 08 .4 30 .8 08

Australia 20420 . +2 64E 08 .4 31 .8 42

Canada 21130 . +3 32E 08 .4 32 .8 52

France 24090 . +1 28E 08 .4 38 .8 11

United Kingdom 24430 . +1 40E 08 .4 39 .8 15

Germany 25120 . +1 72E 08 .4 40 .8 24

United States 34100 . +3 07E 08 .4 53 .8 49

Japan 35620 . +1 43E 08 .4 55 .8 16

http://www.rff.org/

http://www.rff.org/

http://www.rff.org/



Calculating iPAT

• Calculating i(PAT) – Population

– Affluence

– Technology

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

– Carbon per person grows from ~1.1to ~1.6

– Global GHG emissions rise by ~50%by 2025

•

Effects of population and affluence on CO2 emissionsTHOMAS DIETZ*† AND EUGENE A. ROSA‡ Proc. Natl. Acad. Sci. USA

Vol. 94, pp. 175–179, January 1997 Ecology



Global Carbon Profiles

.India 0 3

.China 0 6

.Mexico 1 0

.France 2 0.Germany 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



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

The Population Problem



Fuel Switching

• How do get to the hydrogen economy ?

• Just add hydrogen to your fuel source! – Coal is 85% carbon (15% hydrogen)

– Petroleum is ~2 hydrogen / 1 carbon (CH2) – Methane has 4 hydrogen / 1 carbon (CH4)

• Pounds of CO 2 per KwHr (equiv) energy

– Coal = 2.0 – Petroleum = 1.6

– Methane = 1.2

– Wind = 0



GHG Emissions by Source



Carbon Intensity of Energy

An ideal mixture of primary energy for electricity requires significant renewables





Automobile Emissions

• Fastest way to lowering GHGs isdriving less

• 40% of US CO2 is associated with

petroleum

• If we doubled CAFE, we wouldhalve CO2

– We could reach 2020 emission goalstomorrow

• If the US all drove hybrids – no

imported oil



Honda Insight – MPG Champ

1 liter - 3 cylinders‘electric turbocharger’

61 / 70 MPGSeating for two

2,000 poundsAll aluminum body



A Real Hybrid Vehicle

Gas Electric Synergy Drive™ - ‘plug-in hybrids’ coming soon



Electric Vehicles (EVMT)

• In the US we use 400 million gallons of gasolinea day (400 x 10 6 gallons/day)

• At 20 mpg that is 8 billion miles a day (8 x 10 9 )

• Cross check VMT chart (3.0 trillion miles/year )• An electric car uses 0.25 KwHr per mile

• US would need 2.5 billion KwHrs per day (EV)to replace gasoline (~25% charging overhead)

• Where can we get 2.5 x 10 9 KwHrs per day?

Building the Electron Economy – Robert D. Cormia 2010



US GDP/VMT

VMT data from green car congress =>http://www.greencarcongress.com/2008/05/us-vehicle-mile.html



Energy Efficiency/Liquidity

• US buildings use 60% of all electricity

• Could we be 40% more efficientwith energy?

– (40% is the typical efficiency goal forLEED)

• 40% energy reduction of 60%

electricity is 24%• 24% of 10.5 x 109 KwHrs a day = 2.5

x 109 / day

• ~2.5 x 109 KwHrs/day is needed







Vision the Electron Economy



It’s all About the Numbers!

• It’s about number sense (numeracy) – Scale of energy use (BTU/person)

– Global population and income (iPAT)

– Atmospheric CO 2 and forcing models

• Projecting energy, CO2, and temperature

• Build spreadsheets / predicative models

– Don’t like the results? Change your world!

• It is our job as educators to understand this!



References

• http://www.eia.doe.gov/ • http://www.giss.nasa.gov/

• http://www.rff.org/

• http://yosemite.epa.gov/

• http://www.grida.no/climate/

• http://www.ipcc.ch/

• http://www.climate.org/CI/sis.shtml

• http://www.theclimateproject.org/ • http://www.climatecentral.org/

• http://apolloalliance.org/

http://www.eia.doe.gov/


http://www.rff.org/

http://yosemite.epa.gov/

http://www.grida.no/climate/

http://www.ipcc.ch/

http://www.ipcc.ch/

http://www.climate.org/CI/sis.shtml

http://www.theclimateproject.org/


http://www.climatecentral.org/


http://apolloalliance.org/


http://creativecommons.org/licenses/by-nc-nd/2.5/




http://www.climate.org/CI/sis.shtml

http://www.ipcc.ch/

http://www.grida.no/climate/

http://yosemite.epa.gov/

http://www.rff.org/


http://www.eia.doe.gov/

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Climate Change by the Numbers 3978