YAKAMA NATION

Department of Natural Resources

Environmental Management Program

How-Laak Hush Wit

Sacred Breath of the Columbia River Gorge

An Inter­Tribal Project in collaboration with the Confederated Tribes of

the Umatilla Indian Reservation, the Nez Perce Tribe, and the

Confederated Tribes of Warm Springs to Examine the Effects of

Atmospheric Deposition on Natural and Cultural Resources and to Work

Toward Development of an Air Quality Policy  

in the Columbia River Gorge

Presents

Analysis of Air Quality Data in the Columbia River Gorge

during Temporary Shutdowns at the PGE Boardman Plant

A Report to the Yakama Nation by Dr. Dan Jaffe

Yakama Nation, Post Office Box 151, 401 Fort Road, Toppenish, WA 98948 (509) 865‐5121

February 27, 2008

Dept. of Natural Resources, Deputy Director, Phil Rigdon, prigdon@yakama.com, 509‐865‐5121

Environmental Program Manager, Aja DeCoteau, aja@yakama.com, 509‐865‐5121, ext 6038

Sacred Breath Project Manager, Rebecca Hawk Elwood, relwood@yakama.com, 509‐865‐5121, ext 6079
1

Analysis of Air Quality Data in the Columbia River Gorge during Temporary Shutdowns 

at the PGE Boardman Plant 

Report to the Yakama Nation 

by Dr. Dan Jaffe 

Northwest Air Quality 

NW_airquality@hotmail.com 

February 27, 2008 

Executive Summary 

 In an earlier report, I analyzed 12 years of IMPROVE aerosol data from the site located 

at Wishram, Washington, along with airmass back-trajectories to indicate source region. The 

data were used to identify the 50 worst air quality days in the Columbia River Gorge (CRG) 

between 1993-2004. A key result from that work was that the days with the worst air quality in 

the CRG were associated with transport and sources on the east end of the Gorge, including the 

PGE coal fired power plant at Boardman, Oregon. I have extended this analysis to consider 

months when the PGE Boardman plant was temporarily shutdown and therefore had zero 

emissions. In this way I can more precisely quantify the contribution from the Boardman plant 

to haze in the CRG. 

From this analysis, I find that the PGE Boardman plant has a significant influence on air 

quality in the CRG. The contribution to fine particle mass (haze) at Wishram from the 

Boardman plant is 0.90 ug/m3

 for the entire year, 3.94 ug/m3 if only the month of November is 

considered and 7.40 ug/m3

 if only November days when the airflow is coming “down-gorge” 

(from east to west) is considered. In all 3 cases the results are statistically significant at a 95% 

confidence interval or better. These results indicate a much larger influence from the PGE 

Boardman plant on air quality in the CRG, compared to the February 8, 2008 Science Summary 

Report of the Columbia River Gorge Air Quality Study (abbreviated here as CRG-AQS). The 

most likely cause for this discrepancy is that our analysis is based on data collected at Wishram, 

whereas the CRG-AQS base their conclusions on a computer simulation, and this simulation 

shows a significant discrepancy with the actual data. 

These results have important policy implications regarding pollution controls on the PGE 

Boardman plant: 

1) The PGE Boardman plant has a significant influence on air quality and haze in the 

CRG. Days with the worst air quality in the CRG occur in the fall and are associated 
2

with “down-gorge” atmospheric transport (east to west). For these days, the average 

contribution from the PGE Boardman plant is 7.40 ug/m3. This makes it one of the 

largest contributors to air quality degradation in the CRG during these days. 

2) As emissions from the PGE Boardman plant are reduced, I would expect an 

approximately linear reduction in its contribution to haze in the CRG. In other words, 

a 50% reduction in all emissions from the PGE Boardman plant would bring its 

contribution to fine particle haze in the CRG to 3.70 ug/m3, which is still a very 

significant contribution. 

Introduction 

In my earlier analysis, I found that the worst air quality days were associated with sources 

in the eastern Columbia River Gorge (CRG) and were much more frequent in the fall, especially 

the month of November, when 18 of the 50 worst days occurred (Jaffe 2006). At the time that 

work was conducted, IMPROVE data was available only through 2004. To extend this work, I 

have incorporated all data through 2006, focusing on a period in late 2005 when the PGE 

Boardman power plant was shutdown due to a problem with a main turbine unit. Since the plant 

was almost fully shutdown in November 2005, this presents an ideal opportunity to examine the 

influence of the PGE Boardman plant during the month when we expect the greatest influence 

from the plant on air quality in the CRG. 

Method 

 Data for this work come from several sources. Aerosol data from the Wishram site for 

1993-2006 is from the IMPROVE program website (http://vista.cira.colostate.edu/improve/). 

Backward airmass trajectories were calculated using the on-line HYSPLIT model 

(http://www.arl.noaa.gov/ready.html). I used identical procedures and meteorological data as in 

my earlier report (Jaffe 2006). Emission data for the PGE Boardman plant were provided by 

Mark Fisher from the Oregon Department of Environmental Quality (ODEQ). The monthly 

NOx and SO2 emissions were determined from continuous emission monitor measurements and 

reported annually to ODEQ on Form F1106 for the years 1992-2006. 
3

Results 

Figure 1 shows the monthly NOx emission for the PGE Boardman plant going back to 

1992. In most months, NOx emissions are close to 1000 tons. Over the 15 year timeframe, there 

have been several periods with extended shutdowns that resulted in significantly lower NOx 

emissions. Simply put, if no coal is burned then no NOx is generated. These shutdowns have 

occurred for a variety of reasons, both scheduled and unscheduled. Of the 163 months for which 

I have data, 33 months have emissions of less than 100 tons/month. 

I assume that if NOx emissions are essentially zero, then all other emissions will be near 

zero. It is important to note that I am using the PGE Boardman NOx emissions as a surrogate for 

all plant emissions.

Boardman NOx emissions

0

200

400

600

800

1000

1200

1400

1600

1800

Jan-93Jan-94Jan-95Jan-96Jan-97Jan-98Jan-99Jan-00Jan-01Jan-02Jan-03Jan-04Jan-05Jan-06Jan-07

NOx emissions (tons/month

Figure 1. NOx emissions (tons/month) for the PGE Boardman plant. 

I examined all of the Wishram IMPROVE data to see if I could identify an improvement 

in air quality in those months when the PGE plant had zero or insignificant emissions. Figure 2 
4

shows the monthly average fine mass concentration (PM2.5) measured at Wishram vs the PGE 

Boardman NOx emissions. 

0

2

4

6

8

10

12

14

16

18

0 500 1000 1500 2000

PGE Boardman NOx emissions (tons/month)

Monthly mean (ug/m3)

Figure 2. Monthly mean fine mass concentration (PM2.5) measured at Wishram vs PGE 

Boardman NOx emissions (tons/month). 

 Figure 2 does not show an obvious relationship, but this is not surprising given the large 

seasonal and daily variations in meteorology and transport. On the other hand if we examine 

Figure 2 closely we see that only when the emissions are high, do we get high PM concentrations 

in the CRG. 

If I segregate the data to compare months with low emissions vs months with high (or 

normal) emissions, I find there is a significant difference. Comparing months that have 

emissions of less than 100 tons, I find that the difference is 0.90 ug/m3

. Using a t-test to compare 

months with emissions above and below 100 tons, this difference is statistically significant with 

a confidence of 95% or greater. Choosing a slightly different segregation criteria (e.g. 200 

tons/month or 300 tons/month) has no impact on this conclusion. Table 1 shows details on the 

data above and below 100 tons/month. 
5

Months with 

emissions >100 tons 

Months with 

emissions <100 tons 

Number 122 30 

Average fine 

mass (ug/m3) 6.06 5.16 

S.D. 2.10 1.50 

Table 1. Comparison of fine mass data (PM2.5) for months with greater than, and less 

than, 100 tons. The difference (0.90 ug/m3) is statistically significant at a confidence of 95% or 

better. 

Based on our earlier findings (Jaffe 2006) I expect to identify an even larger influence on 

air quality from the PGE Boardman plant during the fall, especially November. Of the months 

with very low NOx emissions, one period occurred in November 2005, when the plant suffered 

an extended shutdown (November 2005-June 2006) due to a turbine failure. I will therefore 

evaluate the November 2005 data in more detail. Figure 2 shows a time series of just the 

November data for all years. 

November Fine mass concentations at Wishram with PGE 

Boardman monthly NOx emissions.

0

2

4

6

8

10

12

14

16

18

19931994199519961997199819992000200120022003200420052006

Fine mass (ug/m3)

0

200

400

600

800

1000

1200

PGE Emissions (tons/month

Figure 3. Average fine mass (PM2.5) concentrations for November 1993-2006 at Wishram (red 

triangles) and PGE Boardman NOx emission (blue squares). In November 2005 the PGE 

Boardman plant was essentially shut down due to a turbine problem so NOx emissions were near 

zero for that month. 
6

From an air quality point of view, the cleanest November on record was in 2005, with an average 

fine mass concentration of 4.61 ug/m3. I compared the mean concentration for November 2005 

with all other November data. A bar graph comparison is shown in Figure 4 and a summary of 

the results is shown in Table 2. 

Fine mass concentration for November 

IMPROVE data

0

2

4

6

8

10

12

PM2.5 (ug/m3) 

 All Nov except 2005 Nov 2005

Figure 4: Comparison of IMPROVE data from Wishram for November 2005 data (red bar on 

right) with all other Novembers data (blue bar on left). The error bars show the 95% confidence 

interval for each dataset and these do not overlap. A t-test confirms that the difference (3.94 

ug/m3) is statistically significant with a confidence of greater than 95%. More detailed data are 

shown in Table 2. 

Table 2. Comparison of November 2005 IMPROVE observations with all other November 

observations. A t-test confirms that the difference (3.94 ug/m3

) is statistically significant with a 

confidence of greater than 95%. 

All November 

data except 2005 

November 

2005 

Number of 

IMPROVE 

observations 

108 10 

Mean fine mass 

concentration 

(ug/m3

) 

8.55 4.61 

S.D. 6.76 3.74 
7

So far I have analyzed the impacts of the PGE Boardman emissions on all data and on 

only November data. Again, referring to our previous work, I found that the influence from 

sources in the Eastern end of the CRG was strongest when airmass trajectories indicated strong 

transport from the east end of the Gorge. So I have further segregated our analysis by only 

looking at the data when back trajectories indicated this transport. As I reported earlier (Jaffe 

2006), these days are associated with the highest fine mass concentrations in the CRG. Example 

trajectories can be found in our earlier report. 

 Figure 5 compares the fine mass concentration from November 2005 with all other 

November data, but in both cases, only days with airmass transport from the eastern CRG are 

included. While this significantly reduces the number of data points, it points out the strong 

influence from the PGE Boardman emissions. For dates with transport from the eastern CRG, 

the average fine mass concentration in November 2005 is 5.94 ug/m3, compared to 13.34 ug/m3

for all other November data with similar transport patterns. 
8

Fine mass concentration for November IMPROVE 

data with Trajectories from East Gorge 

0

2

4

6

8

10

12

14

16

18

All years exc 2005

(n=23)

2005 (n=5)

PM2.5 ug/m3

Figure 5. Fine mass (PM2.5) concentration for all November IMPROVE data (1993-2006) for 

days with trajectories arriving at Wishram from the eastern end of the CRG. In November 2005 

the PGE Boardman plant was essentially shut down due to a turbine problem. As a result, 

concentrations at Wishram were significantly reduced. Each bar shows the mean and the error 

bars show the 95% confidence interval around each mean. A t-test confirms that the difference 

(7.40 ug/m3) is statistically significant at a confidence of greater than 95%. Table 3 shows the 

detailed data. 

All November data except 2005 

with East Gorge trajectories 

November 2005 data with 

East Gorge trajectories 

Count 23 5 

Mean fine mass 

concentration (ug/m3

) 13.34 5.94 

S.D. 8.33 1.51 

Table 3. Comparison of November 2005 IMPROVE observations with all other November 

observations, that exhibit airmass transport from the eastern CRG. A t-test confirms that the 

difference (7.40 ug/m3) is statistically significant with a confidence of greater than 95%. 

 Taken together, these three analyses present a consistent picture of the influence from the 

PGE Boardman plant on air quality in the CRG. Using the analysis for all months, I find that the 
9

PGE Boardman influence is, on average, 0.90 ug/m3. Comparing only November data, I find 

that the influence is significantly larger at 3.94 ug/m3. Comparing only November data for days 

with likely transport from the eastern CRG, I find the influence is greatest at 7.40 ug/m3

. Table 4 

summarizes the results and also derives the % contribution at Wishram due to the PGE 

Boardman emissions. 

Table 4. Summary of fine mass concentrations at Wishram (ug/m3

) with and without PGE 

Boardman influence. 

With Boardman 

influence 

(ug/m3) 

Without Boardman 

influence 

(ug/m3)

Difference 

(ug/m3)

Fine mass due to 

PGE Boardman 

(%) 

All months1 6.06 5.16 0.90 14.9 

All November 

data2

8.55 4.61 3.94 46.1 

All November data 

w/ trajectories 

from East Gorge3 

13.34 5.94 7.40 55.5 

1

This row compares months where PGE Boardman emissions are less than 100 tons vs all other 

months. 

2

This row compares the November 2005 data (plant shutdown) with all other November data. 

3

This row compares November 2005 data with east gorge trajectories with all other November data 

with east gorge trajectories. 

Comparison with other studies 

 A number of agencies have been involved in a significant air quality study in the CRG 

between 2000-2007. Only data from one year was considered (2004) and the primary 

conclusions were derived from analysis of a regional air quality model. The Columbia River 

Gorge Air Quality Study, Science Summary Report (abbreviated here as CRG-AQS) was 

released on February 8th, 2008. I will compare our results to those in this report. 

As part of the observations and modeling that was conducted for the CRG-AQS report, 

attention focused on one air pollution episode, which occurred between November 8-14, 2004. 

The CRG-AQS report, as well as our earlier work (Jaffe et al., 2006) found that emissions in the 

east end of the CRG were largely responsible for this episode. Thus it is reasonable to compare 

the results from this November episode with our results for November when trajectories are 

coming from the eastern CRG. By reference to the bottom line of Table 4 (above), we see that 

the PGE Boardman plant is responsible for approximately 55% of the fine mass during these 

episodes. In contrast the CRG-AQS report states that Electric Generation Units (EGUs) east of 
10

the CRG (essentially only the PGE Boardman plant) were responsible for 32% of the fine mass 

at Wishram (CRG-AQS, pg 87), a significant discrepancy with our results. 

 In addition, our analysis indicates that for the November episodes with down-gorge 

transport, the PGE Boardman contribution is 7.40 ug/m3

 at Wishram, whereas in the CRG-AQS 

report they conclude that EGUs are responsible for only 3.17 ug/m3 (2.64 ug/m3 + 0.53 ug/m3, 

Table 5-7, pg 85). Thus the CRG-AQS study appears to significantly under-estimate the 

influence from the PGE Boardman plant. A likely source of this discrepancy is that our analysis 

was based on analysis of the IMPROVE data collected at the Wishram site, whereas the CRGAQS conclusions were based largely on a computer simulation of air quality in the CRG. In 

Figure 5-1 of the CRG-AQS (pg 74) there is one graph comparing the computer simulation with 

observations from several sites in the CRG. For the November cases (right side of Figure 5-1) 

the model is performing very poorly. For example, for the worst air quality days the observed

scattering coefficients is up to 250 Mm-1, however the "predicted" (i.e. modeled) value is low by 

about a factor of 3. In short, this simulation does a poor job of reproducing the observational 

data and appears to significantly underestimate the contribution to haze from sources in the CRG 

for the worst air quality days of the year. 

 The report goes on to estimate the influence from EGUs in the east of the CRG in 2018. 

It does this by assuming a “presumptive BART" control level for the Boardman power plant. 

This limit is assumed to be 0.23 lbs of NOx per million BTU or 1323 lbs NOx per hour (CRGAQS, pg 92). This translates into annual NOx emissions of 5790 tons/year. Given that the 

current emissions are 800-1000 tons/month during normal operations (see Figure 1), the 5790 

tons/year limit is approximately a 50% reduction in NOx emissions from current levels. The 

"presumptive BART" control also results in a 70% reduction in SOx emissions (CRG-AQS, pg 

92). For the November episode considered, and using these assumed emissions in 2018, the 

resulting influence from PGE Boardman is 0.95 ug/m3

 (CRG-AQS, Table 7-9, pg 108). Our 

results suggest a much larger level of influence. Referring to the bottom line of Table 4 (above), 

for the November episode, I estimate the current influence from PGE Boardman at 7.40 ug/m3

. 

Even if all emissions were reduced by 70% in 2018 emissions, then the influence would still be 

approximately 2.22 ug/m3

, much larger than the value reported in the CRG-AQS report. 
11

 In addition, the CRG-AQS compares the 2018 base case with 5 alternate emission 

scenarios. Case 1 represents a total zero out of the PGE Boardman emissions. From this 

analysis the authors state: 

“Since major SO2 and NOx emission reductions at the Boardman Power Plant are already 

reflected in the 2018 inventory (i.e., presumptive BART controls), practically zero sensitivity to 

Case 1 is seen.” (CRG-AQS, pg 97). 

This statement is inconsistent with their own results and certainly inconsistent with the 

results of our study. It is very puzzling how the study could conclude that by reducing 

Boardman emissions to 50-70% of current levels brings the influence at Wishram to 0.95 ug/m3, 

and then to claim that zeroing out of these emissions will have no further influence. Our results 

indicate that the current PGE Boardman influence during these November episodes is 7.40 ug/m3

and I would expect a linear relationship between this influence and the degree of emission 

control, assuming all pollutants were reduced a similar %. 

 In summary, our analysis of times when the PGE Boardman plant was temporarily 

shutdown indicate a much larger influence on air quality in the CRG, compared to the CRG-AQS 

study. I believe the primary cause for this discrepancy is that the CRG-AQS result is based on a 

computer simulation, which does a poor job of reproducing the actual data for the worst air 

quality days of the year. 
12

References 

Pitchford M.L, Green M.C. Morris R., Emery C., Sakata R., Swab C., and Mairose P.T. 

Columbia River Gorge Air Quality Study, Final Science Summary Report. February 8th, 

2008. 

Jaffe D.A. Who is polluting the Columbia River Gorge? Final report to the Yakama Nation. 

Northwest Air Quality, Inc., Seattle, Wash., December 31, 2006. 

Appendix: Summary of data used. More detailed data can be obtained from the 

IMPROVE website or from the author. ND indicates no data.

Month 

Boardman 

NOx 

emissions 

(tons) 

Average fine 

mass at 

Wishram 

(ug/m3) 

June-93 104.5 6.18 

July-93 426.2 4.53 

August-93 1141 7.33 

September-93 1082.4 8.01 

October-93 1103 9.34 

November-93 1076.7 13.77 

December-93 1042.6 10.45 

January-94 973.9 8.36 

February-94 1046.38 6.89 

March-94 1116.08 5.13 

April-94 1106.32 5.05 

May-94 195.99 6.79 

June-94 492.68 4.57 

July-94 1169.02 7.82 

August-94 1542.76 7.35 

September-94 1159.65 7.31 

October-94 767.9 6.46 

November-94 801.2 4.48 

December-94 994.5 ND 

January-95 949.4 ND 

February-95 0 ND 

March-95 0 ND 

April-95 0 7.17 

May-95 12.8 6.20 

June-95 0 5.65 

July-95 206.5 6.96 

August-95 913.4 5.19 

September-95 785.1 8.74 

October-95 600.8 5.23 

November-95 372.8 6.13 

December-95 0 6.35 

January-96 0 4.11 

February-96 0 7.90 

March-96 0 5.18 

April-96 0 2.89 

May-96 0 4.16 

June-96 0 5.00 

July-96 195 6.84 

August-96 687 7.64 

September-96 702 5.08 

October-96 915 5.73 

November-96 952 6.64 

December-96 889 4.70 

January-97 184 6.39 

February-97 0 4.18 

March-97 0 4.52 

April-97 0 5.55 

May-97 0 6.16 

June-97 0 3.95 

July-97 153 6.32 

August-97 586 6.72 

September-97 519 7.39 
13

October-97 329 6.63 

November-97 651 8.39 

December-97 826 6.83 

January-98 719 5.59 

February-98 304 3.81 

March-98 708 4.83 

April-98 752 7.38 

May-98 62 4.14 

June-98 0 4.74 

July-98 678 8.00 

August-98 784 6.97 

September-98 861 7.47 

October-98 909 9.49 

November-98 942 6.64 

December-98 1012 4.01 

January-99 870 4.39 

February-99 583 4.01 

March-99 547.9 5.81 

April-99 731.8 6.16 

May-99 383.6 3.87 

June-99 349.8 3.42 

July-99 823.8 6.55 

August-99 891.3 7.69 

September-99 904.5 7.81 

October-99 1005.6 6.38 

November-99 949.7 7.04 

December-99 907.8 3.28 

January-00 799.9 3.72 

February-00 912.2 4.59 

March-00 898.8 4.11 

April-00 770.3 4.53 

May-00 266.3 3.51 

June-00 0 ND 

July-00 255.6 ND 

August-00 871.6 ND 

September-00 731 ND 

October-00 969 ND 

November-00 947.7 ND 

December-00 782.9 ND 

January-01 853.7 9.40 

February-01 898.2 7.26 

March-01 1009.2 4.18 

April-01 957.1 4.63 

May-01 560.9 4.99 

June-01 604.1 4.43 

July-01 1048.7 6.73 

August-01 993.1 7.25 

September-01 950.7 4.98 

October-01 1023.1 4.44 

November-01 851.5 7.79 

December-01 1019.3 5.54 

January-02 951.1 4.43 

February-02 849.4 3.76 

March-02 499 3.30 

April-02 465.9 3.80 

May-02 726.8 3.25 

June-02 0 4.72 

July-02 286.1 7.81 

August-02 779.5 6.52 

September-02 873.8 5.82 

October-02 976.9 7.23 

November-02 1005.5 16.58 

December-02 988.3 6.20 

January-03 899 5.31 

February-03 883.8 4.09 

March-03 953.7 2.02 

April-03 926.5 2.01 

May-03 853.2 5.34 

June-03 51.4 6.43 

July-03 925.8 4.41 

August-03 926.2 5.90 

September-03 958.5 7.13 

October-03 954.2 5.98 

November-03 878.3 7.36 

December-03 870.4 4.48 

January-04 975.9 3.47 

February-04 802.4 6.15 

March-04 918.3 3.89 
14

April-04 823.7 4.92 

May-04 0 3.71 

June-04 0 4.18 

July-04 41.4 8.83 

August-04 750.1 5.21 

September-04 864.9 5.43 

October-04 944 5.33 

November-04 835 10.35 

December-04 857.1 4.42 

January-05 1061 5.71 

February-05 913.2 6.68 

March-05 844.1 3.68 

April-05 962.4 3.04 

May-05 72.5 3.49 

June-05 830.3 5.65 

July-05 868.8 8.36 

August-05 973.7 10.61 

September-05 1020.8 5.59 

October-05 756.4 5.29 

November-05 10.3 4.61 

December-05 0 6.80 

January-06 0 2.48 

February-06 405 3.86 

March-06 0 3.61 

April-06 0 4.70 

May-06 97.5 7.03 

June-06 13.2 6.33 

July-06 1016.6 7.07 

August-06 1033.7 7.89 

September-06 821.8 5.80 

October-06 882 5.47 

November-06 970.6 6.65 

December-06 1087.5 6.07 

IMPROVE sample dates in November with airmass trajectories suggesting transport from the 

east end of the CRG. 

19-Nov-2006 14-Nov-2003 1-Nov-1995 

1-Nov-2006 25-Nov-2002 24-Nov-1993 

24-Nov-2005 4-Nov-2002 28-Nov-2006 

21-Nov-2005 1-Nov-2002 7-Nov-2002 

18-Nov-2005 18-Nov-2001 24-Nov-2001 

15-Nov-2005 12-Nov-2001 9-Nov-2001 

9-Nov-2005 17-Nov-2000 29-Nov-2000 

14-Nov-2004 14-Nov-2000 20-Nov-2000 

1-Nov-2004 7-Nov-1998 15-Nov-1997 

8-Nov-2004 12-Nov-1997 10-Nov-1993