Saturday, November 19, 2011

The Relationship Between Energy Costs, Global Temperatures, CO2, and Energy Consumption (Part IV)

Below is the result of running a linear regression analysis on the model posted in Part I of this series of blogs solving for global temperatures (Temp5). This simulation is similar to the one done in Part III except this time the temperature variable being evaluated contains the running five year average of global temperatures.

R2

0.99

           

Adjusted R2

0.97

           

SE

0.030

           
               

Term

Coefficient

95% CI

SE

t statistic

DF

p

Intercept

-23.22

-47.24

to 0.79

10.615

-2.19

9

0.0564

Temp

-0.09777

-0.32014

to 0.12460

0.098301

-0.99

9

0.3459

CO2

0.01546

-0.01863

to 0.04956

0.015072

1.03

9

0.3317

Energy Cost

-0.102

-0.219

to 0.015

0.0516

-1.98

9

0.0794

USP

-2.602

-8.271

to 3.067

2.5060

-1.04

9

0.3261

Energy Cons

2.7961E-08

1.9196E-09

to 5.4003E-08

1.1512E-008

2.43

9

0.0381

CO2 GDP

-0.000432

-0.004280

to 0.003416

0.0017010

-0.25

9

0.8052

CO2 GDP1

0.0002631

-0.0030553

to 0.0035816

0.00146694

0.18

9

0.8616

Coal KWH1

3.359

-0.876

to 7.594

1.8722

1.79

9

0.1064

NG KWH1

1.007

-0.460

to 2.474

0.6485

1.55

9

0.1549

Oil KWH1

1.93

-0.02

to 3.88

0.863

2.24

9

0.0521

NP KWH1

8.649

-4.094

to 21.393

5.6334

1.54

9

0.1591

BIO KWH1

1.463

-2.617

to 5.543

1.8036

0.81

9

0.4382

Hydro KWH1

1.534

-0.890

to 3.957

1.0713

1.43

9

0.1860

Geo KWH1

0.1998

-4.0556

to 4.4552

1.88113

0.11

9

0.9177

Solar KWH1

3.759

-4.558

to 12.075

3.6762

1.02

9

0.3333

Wind KWH1

2.843

-1.707

to 7.394

2.0116

1.41

9

0.1912

Source of variation

Sum squares

DF

Mean square

F statistic

p

Model

0.737

16

0.046

52.60

<0.0001

Residual

0.008

9

0.001

   

Total

0.745

25

     

Coefficients

Coefficient Value

Value

Temperature

Ave

Temperature

Intercept

-23.22

1.00E+00

-2.32E+01

1.00E+00

-23.22

Coal KWH1

3.359

1.48E+00

4.97E+00

9.00E-01

3.0231

NG KWH1

1.007

4.71E+00

4.74E+00

3.10E+00

3.1217

Oil KWH1

1.93

1.85E+00

3.57E+00

1.15E+00

2.2195

NP KWH1

8.649

2.30E-01

1.99E+00

2.30E-01

1.98927

Hydro KWH1

1.534

3.67E-01

5.63E-01

3.67E-01

0.562978

Geo KWH1

0.1988

9.20E-02

1.83E-02

9.20E-02

0.0182896

Solar KWh1

3.739

4.17E-02

1.56E-01

5.00E-01

1.8695

Wind KWH1

2.843

1.43E-01

4.07E-01

1.40E+00

3.9802

CO2 GDP

-0.000432

5.10E+02

-2.20E-01

4.80E+02

-0.20736

CO2 GDP1

0.0002631

4.16E+02

1.09E-01

3.90E+02

0.102609

USP

-2.602

1.80E-01

-4.68E-01

1.60E-01

-0.41632

Energy Cost

-0.102

1.00E+01

-1.02E+00

1.00E+01

-1.02

Biomass KWH1

1.463

3.21E-01

4.70E-01

3.21E-01

0.469623

Energy ConsP

2.80E-08

9.46E+07

2.65E+00

5.50E+07

1.537855

CO2

0.01546

3.90E+02

6.03E+00

4.30E+02

6.6478

Temp

-0.09777

7.00E-01

-6.84E-02

7.00E-01

-0.068439

Result

6.74E-01

0.6103056

The model has excellent correlation as shown by the R² variable equal to 0.99. The results indicate that the 2009 value for the 5 year average of global temperature can decrease from 0.7 degrees to .6 degrees by decreasing the United States reliance on coal, natural gas, and oil by 25% and increasing the United States reliance on Solar and Wind energy by 25% (highlighted in red). Nuclear power, hydro power, biomass, and geothermal variables were held constant. Other 2009 variables were adjusted to keep up with the trends of using renewable energies such as increased energy costs, higher global temperatures (Temp – even with lower CO2 emissions the global temperature trend is upward), lower energy consumption (including the USP variable), and lower CO2 to GDP numbers.

Global warming alarmist may look at this result as proof that moving to renewable energy sources will eliminate CO2 and therefore, reduce global temperatures. This, however, is not true and this result can be misleading as will be revealed in future blog posts evaluating this model further.

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