From: Douglas Hawkins

To: Aagenes, Jason D. Subject: Re: Possible Statistical Analysis Project

Date: Thursday, July 05, 2007 12:03:14 PM

Attachments: Writeup.pdf

Hi, Jason,

I attach a draft writeup of the data set. There are indeed relationships between the plant parameters
and the NOx emissions.

If we want to use these relationships to reduce NOx, we will need to talk some more about what can and can not be varied independently, but that is perhaps a question for another day.

Let me know of any changes, additions or clarifications needed, and I'll update and get a clean copy over to you.

Best,

Doug

----- Original Message -----

From: Aagenes, Jason D.

To: Douglas Hawkins (rr)
Sent: Monday, June 25, 2007 11:55 AM Subject: RE: Possible Statistical Analysis Project

Doug, Thanks for your reply. I will wait to receive your proposal. There is some urgency to this project as the Minnesota Pollution Control Agency is expecting a response from us in the next couple of

weeks. Please let me know if you would be able to support the project in that time period. Thanks again, Jason Aagenes

From: Douglas Hawkins (rr) [mailto:dhawkins@douglashawkins.com]

Sent: Friday, June 22, 2007 5:37 PM
To: Aagenes, Jason D.
Cc: Douglas Hawkins LLC Subject: Re: Possible Statistical Analysis Project

Hi, Jason,

Just picked up this e-mail.

Yes, I would think I can add useful insights to the project. I will take a look at your attachment and get back to you.

The e-mail address you used is technically non-existent, and will become genuinely so not too far

into the future. Can you change your address book entry for me to dhawkins@douglashawkins.com (and see if you can get Dave's address book updated also.)

Best,4713 Hibiscus Avenue, Edina, MN 55435-4001 cell: (612) 718-5033 e-mail:dhawkins@mn.rr.com fax: (952) 926-8117 web: www.douglashawkins.com 

## Memorandum

To: Jason Aagenes Subject: Analysis of NOx Emission Study Data Date: July 4, 2007

Executive Summary

Three of the plant parameters ha ve a clear relationship to NOx emissions – the kiln off-gas temperature and burn zone temperature have a negative relationship with NOx emissions, and heat input a positive relationship. The impact of line 1 feed rate is less clear, and pre-heat temperature does not appear to have any relationship with NOx emissions.

Background

You provided hourly data measured ove r four days. The variables were:

• Average NOx emissions (in ppm) over the hour,

• Average line 1 feed rate (in tph),

• Pre-heat temperature (in degrees F),

• Kiln off-gas temperature (in degrees F),

• Heat input (in MMBtu/hour),

• Burn zone temperature (in degrees F).

The object of the study was to determine whether any of the 5 plant operating parameters affects NOx emissions, and if so, what the relationship is.Relationship of NOx emissions to plant parameters 2 Preliminaries

The first step was a calculation of the averages , standard deviation, ma ximum, and minimum of the six measured quantities. With some self-e xplanatory abbreviations for the variable names and rounding all values to the ne arest whole number, this gave:

Variable N Mean SD Minimum Maximum Avg_NOx 84 300 32 209 389 L_1_feed 95 234 19 155 272 Preht_tem 95 2160 29 2117 2289 Off_gas_t 95 1949 17 1895 2004 Heat_inpu 95 152 11 124 206 Burn_temp 94 2473 15 2434 2500

All variables were fairly tightly controlled, with standard deviations of the order of 10% of the mean for the line 1 feed and heat input, and 1% for the three temperatures. The average NOx
emission had a standard deviation of 10% of its mean, which is also quite low.

Pairwise Graphics

Next, the average NOx emission was plotted agai nst each of the five plant parameters. The resulting plots are shown as Figures 1 – 5 in th e Appendix. Each plot also shows the linear regression line that might be used to predict average NOx using that parameter alone as a predictor. Main featur es of the graphs are:

• Visually, average NOx seems to increase with line 1 feed rate a nd heat input, and to decrease with off-gas temperature. Neith er pre-heat temperature nor burn zone temperature seems to have much connection with the NOx emission.

• There is a visual outlier – an hour whose average NOx emission of 209 ppm is far below that of any other hour. This observati on does not however correspond to an unusual setting in any of th e plant parameters.

• The straight regression lines shown on the pl ots do quite well in capturing the broad sweep of the relationships with the plant parameters.

Correlation Matrix

The next step was to compute the correlation of each pair of the six variables. This gave:

Avg_NOx L_1_feed Preht_tem Off_gas_t Heat_inpu L_1_feed 0.4391 Preht_tem -0.0521 -0.0995 Off_gas_t -0.3960 -0.5749 0.3854 Heat_inpu 0.4318 0.3552 0.2138 0.1575 Burn_temp 0.0102 -0.2142 0.2026 0.4835 0.6905

Correlations above 0.2 are statisti cally significant at the 5% level, indicating a possible ‘real’ relationship.

The significant correlation of average NOx with line 1 feed rate, off-gas temperature and heat input quantify the impression of the plots of appa rent relationships among these variables. The non-significance of pre-heat temp erature and burn temperature al so agrees with the plots.Relationship of NOx emissions to plant parameters 3 The rest of the table shows correlations among the plant parameters. These correlations presumably result from operator management – pe rhaps high feed rate causes the operator to increase the heat input – and from the laws of physics – a higher heat input will lead to a higher burn zone temperature. These co rrelations and their source are not central to this statistical analysis, but will become important in any efforts to modify NOx emissions.

Multiple Regression Analysis

The final analysis is a multiple regression. In th is, the NOx output is predicted using all five of the plant parameters together. This an alysis gave rise to the following output:

Unweighted Least Squares Linear Regression of Avg_NOx

Predictor

Variables Coefficient Std Error T P VIF

Constant 3873.17 880.636 4.40 0.0000 L_1_feed -0.40003 0.25410 -1.57 0.1195 2.9 Preht_tem 0.00144 0.09916 0.01 0.9885 1.2 Off_gas_t -0.91634 0.24708 -3.71 0.0004 2.2 Heat_inpu 3.30005 0.64446 5.12 0.0000 4.1 Burn_temp -0.88628 0.33976 -2.61 0.0109 3.6

R-Squared 0.4565 Resid. Mean Square (MSE) 575.406 Adjusted R-Squared 0.4212 Standard Deviation 23.9876

Looking at each of the lines in turn, if a ll other plant parameters remain the same,

• a 1 tph increase in line 1 feed rate is associated with a 0.40 ppm decrease in NOx;

• a 1 o F increase in preheat temperature is associated with a 0.001 ppm increase in NOx;

Neither of these coefficients is statistically signi ficant. Thus the data do not reliably indicate that either of these plant parameters has any impact on NOx emissions when the other plant parameters are taken into account. Turning to the next three lines:

• a 1 o F increase in kiln off-gas temperature is a ssociated with a 0.92 ppm decrease in NOx;

• a 1 MMBtu/hr increase in the heat input, all other plan t parameters remaining the same, is associated with a 3.3 ppm increase in average NOx.

• a 1 degree increase in the burn zone temperatur e is associated with a reduction of 0.89 ppm in average NOx.

Interpretation of the relationships should con centrate on these three signi ficant plant parameters.

Explaining the Discrepancies between the Correlation and the Regression Fits.

There are two discrepancies to notice. The original correlation analysis saw a significant
association between line 1 feed rate and NOx, but no discernibl e relationship between burn zone temperature and NOx emissions. The multiple regression reached the opposite conclusion p— that line 1 feed rate did not have a well-quantif ied relationship with NOx emissions, but that burn temperature did. The reason for this differe nce lies in the rela tionship among the plant parameters due to operator action and the laws of physics. For example, it is likely that, inRelationship of NOx emissions to plant parameters 4 response to increases or decreases in the line 1 feed rate, the opera tors make adjustments to other controllable parameters, and it is th e effect of these downstream cha nge that leads to the apparent
correlation between feed rate and NOx emissions.

And on the other side, it appears that the burn zo ne temperature has an effect on NOx emissions (as evidenced by the multiple regression) but that the burn zone temperature is so much a resultant of other changing plan t parameters that the association is masked in the overall relationship.

Quality of the Regression Predictions

Figure 6 is a plot of the actual NOx values against the values predicted by the regression model. This graph is a check on the qua lity of the regression. It show s that the measured NOx values follow the line predicted by the model as thes e predictions range from 240 to 340 ppm. The individual hourly averages differ from this line with a standard deviation of 24 ppm.Relationship of NOx emissions to plant parameters 5 Appendix – Graphs

170 190 210 230 250 270 200 250 300 350 400 

### Avg_NOx vs L_1_feedAvg_NOx

L_1_feed

Figure 1

2110 2170 2230 2290 200 250 300 350 400 

### Avg_NOx vs Pre-heat TempAvg_NOx

Preht_tem

Figure 2Relationship of NOx emissions to plant parameters 6 1920 1950 1980 2010 200 250 300 350 400 

### Avg_NOx vs Kiln Off-Gas TempAvg_NOx

Off_gas_t

Figure 3

120 140 160 180 200 250 300 350 400 

### Avg_NOx vs Heat inputAvg_NOx

Heat_inpu

Figure 4Relationship of NOx emissions to plant parameters 7 2430 2450 2470 2490 2510 200 250 300 350 400 

### Avg_NOx vs Burn Zone TempAvg_NOx

Burn_temp

Figure 5

230 270 310 350 200 250 300 350 400 

### Actual vs Predicted NOx emissionsAvg_NOx

Predicted

Figure 6Doug Hawkins

----- Original Message -----

From: Aagenes, Jason D.

To: dhawkins@mn.rr.com

Sent: Friday, June 15, 2007 1:53 PM Subject: Possible Statistical Analysis Project

Doug, Dave Skolasinski of Cleveland-Cliffs referred me to you as a potential resource for completing a statistical analysis on data that we’ve collected. We are trying to determine if there is any correlation between the amount of NOx that is emitted from our furnace stacks and various operating parameters (fuel input rate, production throughput, operating temperatures, etc.). We believe that a correlation exists and that we could use some of the operating data to predict and quantify what the resulting NOx

emission rate is.

Would you be able to help with this project? If so, please develop a proposal and

submit to me. I’ve included a sample of the data set with hourly data averages (minute by minute data is also available). Please review and let me know if you would be interested in helping with this project. Regards,

**Jason Aagenes** Section Manager - Environmental Affairs

Cleveland-Cliffs United Taconite LLC

P.O. Box 180

Eveleth

, MN 55734 Office (218) 744-7803

Mobile (218) 290 -5936 Fax (218) 744-7635 jdaagenes@cleveland-cliffs.com

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