Natural Haze Levels II, Final Report ( text extracted from PowerPoin t file ) p. 1 

### Text extracted from Natural Haze Levels II PowerPoint file http://vista.cira.colostate.edu/IMPROVE/Publications/GrayLit/gray_literature.htm http://vista.cira.colostate.edu/IMPROVE/Publications/GrayLit/029_NaturalCondII/naturalhazelevelsIIreport.ppt 

### Slide 1. 

## Natural Haze Levels II: Application of the New IMPROVE Algorithm to Natural

Species Concentrations Estimates Final Report by the Natural Haze Levels II Committee to the RPO Monitoring/Data Analysis Workgroup The Natural Haze Levels II Committee was est ablished in the Spring of 2006 to review and refine, as appropriate, a methodology developed by Roger Ames (CIRA) for applying the new IM PROVE algorithm for estimating light extinction from aerosol species concentrations to natural species concentration es timates. The ultimate purpose of this is to determine natural haze estimates for the 20% best and 20% worst day for each of the visibility
- protected class I areas. This is the final report of the committee which has completed its review and successfully refined the Roger Ames approach, and in so doing has produced natural haze estimates for each of the visibility protected area.


### Slide 2. **Note:** This presentation contains substantial additional information in the notes section of PowerPoint that can be se en in the bottom panel of the “Normal” view mode, and can be printed by selecting “Notes Pages” from the “Print what” selection of the “Print” menu (go to “Files” on the top tool bar and select “Print”). You can also use “Preview” for the “Notes Pages” to more easily read the notes on your computer monitor. These notes were prepared 1. to aid those hearing the presentation b y relieving them of the burden of taking as many notes; 2. to allow those who haven’t heard the presentation to understand it by providing the additional information that is spoken during presentations; and 3. to provide a more complete documentation of the natural haze levels II approach for anyone who may

want to understand it For additional information contact Marc Pitchford at Marc.Pitchfo rd@NOAA.gov Here is the notes section where the additional material associated with each slide of the presentation has been placed. 

### Slide 3. 

## Overall Goal
 Estimate 20% best and 20% worst natural haze levels for visibility

- protected class I areas using the new IMPROVE algorithm for estimating light extinction from aerosol species concentrations.

– Needed for Regional Haze Rule (RHR) rate of progress glide slopes where the new IMPROVE algorithm is used to characterize current haze levelsNatural Haze Levels II, Final Report ( text extracted from PowerPoin t file ) p. 2



### – Should minimize th e technical problems identified in the RHR default natural haze levels that were developed using the original IMPROVE algorithm EPA’s RHR guidance issued in 2003 concerning tracking progress and estimating natural condition were based on the original IMP ROVE algorithm. This guidance defines a consistent set of instructions for implementing the RHR. However, in late 2005 a new IMPROVE algorithm was developed that mitigated some of the technical criticism of the original IMPROVE algorithm especially as it applied to the RHR. Many of the RPOs and states have indicated their preference to use the new algorithm, but to do so they need natural haze conditions for their class I areas determined in a consistent manner (i.e. by the new IMPROVE algorithm). A rep ort describing the new algorithm is available in the Grey Literature Section of the IMPROVE web site at http://vista.cira.colostate.edu/improve/Publications/GrayLit/019_RevisedIMPROVEeq/RevisedIM PROVEAlgorithm3.doc Estimates of natural haze levels using e ither algorithm involves applying the algorithm to estimates of natural species concentrations. The natural species concentration estimate used for this purpose come from the NAPAP State of Science Report 24 by John Trijonis (1990) and are typical values for the eastern U.S. and for the western U.S. Some methodology is needed to adjust these typical values to estimate the 20% best and 20% worst values. The statistical approach used in the EPA guidance document to develop the default best and worst natura l haze levels was subject to criticism. A goal in developing the new values is to avoid the problems identified in the EPA default approach. The visibility guidance documents are available on the IMPROVE web site at http://vista.cira.colostate.edu/improv e/Publications/GuidanceDocs/guidancedocs.htm 

### Slide 4. 

## Default Natural Haze Levels Approach
 Ty pical haze level estimates for East and West

– Ty pical light extinction by

appl yi ng the original IMPROVE algorithm to Trijonis natural species concentration estim ates for East and West

– Convert to haze index (deciview units)  20% best and 20% worst haze estimate for East and West

– Best = typical

– 1.28(standard deviation)

– Worst = ty

pical + 1.28(standard deviation)

– Standard deviation is 3dv for the East and 2dv fo r the West (corresponds to the 10th and 90th percentile) A complete description of the default approach for estimating natural haze levels is available in the Guidance for Estimating Natural Visibility Conditions Under the Regional Haze Rule is available at h ttp://vista.cira.colostate.edu/improve/Publications/GuidanceDocs/guidancedocs.htm , as are the results of applying it all of the IMPROVE monitoring sites. The Trijonis estimates of the major species concentrations under natural conditions were typical or mean values for the eastern and western U.S. The methodology used by EPA in the guidance document was based on the assumptions that the deciview distributions were near normal and that the average of the 20% best and 20% worst haze index values were we ll approximated by the 10 th and 90 th percentiles respectively. These assumptions seemed to workNatural Haze Levels II, Final Report ( text extracted from PowerPoin t file ) p. 3

we ll in estimating the 20% best and worst values for current conditions at most monitoring sites. However, these two assumptions were the subject of considera ble scrutiny and criticism.


### Slide 5. 

## Criticism of the Default Approach

• Limitations of the original IMPROVE algorithm

– Biased light extinction estimates at the extremes

– Uses an outdated organic compound mass to carbon mass ratio

– No sea salt (important at a few sites)

– Rayleigh scattering of 10Mm

- 1 used for all site

• Flawed assumptions used to estimate 20% best and worst conditions

– Haze index for natural conditions are not likely to be normally

distributed due to inclusion of Rayleigh scattering

– 10th and 90th percentiles don’t correspond to the best and worst conditions if the distribution were normal **Limitations of the Original IMPROVE A lgorithm:**  The original IMPROVE algorithm tended to underestimate light extinction for the highest haze conditions and overestimate it for the lowest haze conditions. It used a ratio of organic compound mass to carbon mass of 1.4, though the literature indicated that the ratio is higher especially in remote areas. It also didn’t include a term for sea salt, which is important sites near the ocean coasts. As a result of these criticisms, the IMPROVE Steering Committee commissioned the development of a new IMPROVE algorithm which they adopted for its use in December 2005. Many states and RPOs have indicated their int ent to use the new IMPROVE algorithm to estimate current haze condition, because it performs better in regards to bias at the extremes, uses 1.8 as the organic compound mass to organic carbon mass, it includes sea salt and uses site elevation related Rayle igh scattering. A report describing the new algorithm is available at http://vista.cira.colostate.edu/improve/Publications/GrayLit/019_RevisedIMPROVEeq/RevisedIM PROVEAlgorithm3.doc **Flawed A**

**ssumptions:** The basis for the assumption that the natural haze co nditions are normally distributed was that most pollution concentration values (including particle light extinction values) are well represented by lognormal distributions, which when logarithmically transformed (as is the case in conversion of light extin ction to the haze index in deciview units) gives a normal distribution. However, this thinking did not account for the Rayleigh scattering which is a taken to be a constant for any particular monitoring site and is a substantial component of the light ext inction on less hazy days (e.g. natural conditions). By adding this constant to the lognormally distributed light extinction the result is no longer lognormal so the logarithmical transformation to deciview produces a distribution that isn’t normally dist ributed. This flaw assumption also distorted the selection of the standard deviations used to represent the natural distribution for the east and west (3dv and 2dv respectively). These were derived by extrapolating to the least hazy conditions in scatt er plots of each sites standard deviation versus mean haze index for sites in the east and for sites in the west. These scatter plots generally showed that the sites with lower means values had lower standard deviations. However, this characteristic is p rincipally due to the inclusion of a constant Rayleigh scattering. If RayleighNatural Haze Levels II, Final Report ( text extracted from PowerPoin t file ) p. 4 scattering is removed so that the plots are of logarithmically transformed particle extinction, the standard deviations were not systematically smaller for the least hazy sites in a region. The use of the 10th and 90th percentile values as estimates of the mean of the 20% lowest and mean of the 20% highest haze index values is not consistent with the assumption that the natural haze index values are normally distributed. The 8t h and 92nd percentiles are the best estimates of the mean of the 20% best and 20% worst conditions which then changes the multiplicative coefficients from 1.28 to ~1.4 in the equation for estimating the extreme values from the typical values. However sinc e the original distribution were not normal (as discussed above), this critique is less pertinent.


### Slide 6. 

## Natural Haze Levels II Approach

• Adjust each of the measured major species concentrations to the Trijonis natural concentration estimates

– Multipl y each species concentration at a site b y the site

- specific ratio of the (Trijonis natural estimate) divided by the (annual mean concentration) for the species for the 5 year baseline period

– If the annual mean concentration for a species is smaller than the Trijonis natural estimate, make no adjustment

– Current sea salt levels are taken to be natural levels

• Apply the new IMPROVE algorithm to the Trijonis

- adjusted species concentrations at each site to produce a distribution of natural light extinction values
• Convert to deciview and calculate the mean of the 20% best and 20% worst haze levels **Trijonis -** **Ad justed Species Concentrations:**  Unlike the default approach which directly uses the Trijonis natural species concentration estimates to calculate haze lev els, this approach the adjusts the data set of current species concentration using a multiplier applied to each species measurement that gives the Trijonis estimate for that species. Ratio of the Trijonis estimates for each species divided by the annual m ean values for the species is used to transform the entire data set to what is then assumed to be the natural species concentration levels for that site and year. This process is applied to each of the complete years of data (as defined by the tracking re gional haze trends guidance) in the baseline period (2000 through 2004). Sites with 3 complete years of data are treated as having sufficient data for this assessment. Provisional estimate were made for sites with fewer than three complete years (includi ng for Breton Island were one composite year was developed). If any of the current annual mean for any species is less than the Trijonis estimate for that species, the unadjusted species data are used. Trijonis estimates didn’t include sea salt, which is only significant at a few coastal sites. Estimates of current sea salt concentrations determined from Cl ion data (described as part of the new IMPROVE algorithm) are take to be natural contributors to haze. **Fundamental A**

**ssumption:** In the default appro ach, the Trijonis estimates for the east and west were used directly to calculate the haze index, and assumptions were made about the shape and width of the natural haze distribution to permit the 20% best and 20% worst haze conditions to be extrapolated f rom the estimated mean values.Natural Haze Levels II, Final Report ( text extracted from PowerPoin t file ) p. 5 The fundamental assumption inherent in this Natural Levels II approach is that the Trijonis
adjusted species data set is a good estimate of the natural species data set. Thus each site has its own a natural haze distributio n which is derived from the current distribution, so no assumptions about the shape and width of the natural distribution are needed because there are sufficient values to actually calculate the 20% best and 20% worst means for site and year. Another as sumption , that the baseline period of up to five years (2000 through 2004) is sufficiently long and representative of longer time periods to be used in this process to produce reasonable estimate of natural haze levels, was tested using data from long term monitoring sites. The concern was raised about whether the characteristics of the baseline period that included an unusually intense wildfire year in the W estern U.S. (2002) might bias the estimates of natural haze levels for sites that were particularly impacted by smoke from those fires. Comparisons were made between the natural haze estimates based on the five
- year baseline and the 17
- year complete period of record for 22 long
- term IMPROVE sites. The mean difference among the sites between the two es timates of natural haze was 0.2 deciview, which corresponds to an average fractional change of about 2.5%. The site with the greatest difference in the estimates of natural haze is Mesa Verde National Park in Colorado that had a difference of 0.7 deciview (higher estimate of natural haze using the baseline period compared to the long
- term period), wh ich corresponds to about a 9% change. These differences based on the periods of record used in the approach were judged to be within the uncertainty of the me thodology. Given that only a small fraction of the sites have long
- term data, the use of the 5
- year baseline period for each site for the sake of consistency was thought by the committee to be appropriate. **Ap plication of the Ne** **w IMPROVE A lgorithm:**  The n ew IMPROVE algorithm is applied to the Trijonis
- adjusted concentration data set to estimate the light extinction values for what is assumed to be the distribution of natural conditions for each site. These are then converted to deciview values from which the mean of the 20% best and the mean of the 20% worst haze conditions are calculated for each year of the baseline period. **Al ternate A**  **pproaches Tried, but Rejected:** Log
- Transformed Particle Light Scattering Approach

– We used the new IMPROVE algorithm to produce particle extinction levels (i.e. no Rayleigh scattering). These were log
- transformed and shown to have very nearly normal distributions for most monitoring site since the distortion caused by having a constant Rayleigh scattering term was elimina ted. Then we used a statistical approach similar to that used in the default natural haze approach to estimate the 20% best and 20% worst haze conditions. These values looked reasonable. However once we realized that we had sufficient data at nearly eve ry monitoring site so that we could adjust each sample periods data and we wouldn’t need to test for the distributions and make assumptions about the width of the distribution to estimate the best and worst conditions, so we abandoned this type of approach

. Modified Application of the New IMPROVE Algorithm

– Some on the committee were concerned that the new IMPROVE algorithm’s empirical approach for partitioning the sulfates, nitrates and organic compounds into the two particle size distributions (thus affecting the extinction efficiency and water growth properties of these species) would be inappropriate under natural emissions conditions. The empirical approach uses the concentrations of the three species to determine what fraction of each is in the less efficient light scattering small particle size distribution and how much would be in the more efficient light scattering large size distribution. W hen man
made emissions are substantially reduced so that natural haze sources are dominant (i.e. attainment of the RHR goal), the concentrations of sulfates and nitrates, and to a lesser extentNatural Haze Levels II, Final Report ( text extracted from PowerPoin t file ) p. 6 the organic concentrations will be substantially reduced, so the IMPROVE algorithm would have a higher fraction of these components in the smaller size distribution. Ho wever, the concerned committee members argued that the same meteorological conditions that produced large size distributions (e.g. in
- cloud chemistry, particle growth through aging) would still apply with about the same frequency in various regions as is c urrently the case. For example, fog events would be just as frequent under natural conditions as currently is the case. In other words, they were arguing that the empirical approach that determines the fraction of the mass of these species to large and s mall sizes will not work well if the emissions are significantly different than those for wh ich it was developed. An approach to preserve the current splits of sulfate, nitrates organic carbon was developed. This was done by using the new IMPROVE algor ithm’s empirical approach applied to current conditions for every sample period to determine the split between large and small particle size distribution. These sample
- period specific splits were applied to the Trijonis
- adjusted concentrations to estimate the natural haze levels. The affect of this approach was to generate natural haze level estimates that were higher, principally because the sulfate and nitrate extinction efficiencies were much larger. However, these natural haze level values were only slightly higher then those without this adjustment, principally because the higher extinction efficiencies affected sulfate and nitrate concentrations which under natural conditions are relatively minor contributors to haze. In the end an alternative te chnical discussion convinced the committee that the new IMPROVE algorithm should be used without any modification. The basic point of the discussion was that wh ile the frequency of meteorological conditions that generate large size distribution particles might be similar for current conditions and natural levels, the concentrations of the primary pollutants (including SO 2 , NO x , and VOCs) would be so low that particles would not generally grow to the sizes that current high concentrations of these pollutant s allows. Another reason for using the new IMPROVE algorithm without modification was to avoid having to develop justify that the approach selected for the modification would produce better results than from the unmodified algorithm. In the long term, th e technical community can see if the new IMPROVE algorithm continues to perform well when emission patterns and rates are significantly different than today. Substitution for Some of the Trijonis Species Values

– We use the Trijonis estimated natural spec ies concentrations for the anthropogenically
- dominated species (i.e. sulfate, nitrate and elemental carbon), but tried various approaches to use currently monitoring values for the naturally
- dominated species (i.e. organic carbon, fine soil and coarse mass ). A number of different variations were tried including: 1. Trijonis
- adjusted values for each component except for organic carbon; all currently measured organic carbon was assumed to be natural. 2. Trijonis
- adjusted values for each component except for org anic carbon; 80% of the currently measured organic carbon was assumed to be natural. 3. Trijonis
- adjusted values for each component except for organic carbon, fine soil and coarse mass; all currently measured organic carbon, fine soil and coarse mass is assu med to be natural. 4. Other variations of the above with all or various fractions of the natural source
dominated species being used in place of the Trijonis estimates for those species. Ultimately these were all rejected because we could find regional and site
- specific counter
examples to the underlying assumptions in each of them, and it would have greatly expandedNatural Haze Levels II, Final Report ( text extracted from PowerPoin t file ) p. 7 what we saw as our charge which was to employ the new IMPROVE algorithm to the Trijonis natural species estimates. Counter
- examples to the ass umption that all or most of the organic carbon in remote areas is from natural sources included sites that are heavily impacted by large urban sources where transportation is a primary source of carbonaceous particulate matter (e.g. San Gorgonio W ilderness , just east of L.A., Saguaro, very near Tucson) also sites impacted by smoke from agricultural burning. Similar cases could be made for specific sites and regions of the country for fine soil and dust from construction, mining and agriculture. The effort to produce site
- specific and regional rules for how much of these species should be assumed to be from natural sources would have required more time and resources than were available. Such an effort should be further explored for future refinements of na tural haze level estimates.


### Slide 7. 

## Trijonis **- Adjusted Specie Frequency Distributions** 

• Sipsey

Alabama

• Each aerosol species mass concentration frequency distribution scaled to estimated natural mass concentrations

• If current species mean is less than natural estimate, the that species is not scaled

• Geometric shape of species distributions is unchanged Current 2000

- 2004 Natural Estimate Hanging bars Solid

- current mean Dashed

- natural estimate mean These two plots demonstrate the Trijonis
- adju stment to the measurement data for a specific site and year. Both plots are frequency distributions (number of sample periods with species concentrations in specific narrow ranges). Different colors are used to show each of the major species (ammonium su lfate, ammonium nitrate, organic mass, elemental carbon, fine soil, coarse mass and sea salt). The top plot shows the distributions of the current species concentrations, while the bottom plot shows the distributions of the adjusted species concentrations . Note that the concentrations shown on the x
- axis are logarithmically scaled units of microgram/meter cubed. As a result of the log
- scale, the Trijonis
- adjusted distributions have the same shape as the current distribution, only they are translated to th e lef t (this is because multiplication and division of numbers is equivalent to addition and subtraction of their logarithms). Reconstructed total mass (RCTM) is the sum of the distributions for the major species. Notice that the shape of these distrib utions is not the same in the upper and lower plots. This is because each of the species is adjusted by different ratios of Trijonis to current mean conditions. The dangling bars at the tops of the two plots show the locations of the mean values for th e current conditions (short solid bars) and the natural levels (longer dashed bars). The bars are identical in the top and bottom plots. Notice that the sulfate (dark blue) and elemental carbon (green) have large displacements between their solid and das hed bars which current conditions are much higher than the Trijonis values, while coarse mass (orange) and fine soil (yellow) haveNatural Haze Levels II, Final Report ( text extracted from PowerPoin t file ) p. 8 their solid and dashed bars much closer together indicating that the current conditions are only a little higher than the Trijonis estimates of natural concentrations. Current sea salt (solid red bar) mean levels are assumed to equal the natural levels (dashed red bars). Thought not called for in the RHR or guidance for implementing the RHR, species specific rate of progress g lide slopes can be calculated for each monitoring site. Such glide slopes can more explicitly show which aerosol species offer the greatest opportunities for contributing to reduce haze. 

### Slide 8. 

## Current and Natural Haze Frequency Distributions

• Sipsey Alabama

• Natural scenario joint distribution shape is derived from scaling current aerosol species mass concentrations to natural condition estimates

• Allows estimation of best and worst 20% dv or aerosol species extinction
Slide 9. 

## Natural Haze Levels **II** The map shows site values and contours of estimates of the 20% worst natural haze levels (deciview units) using the new approach at IMPROVE and IMPROVE protocol sites. Values based on with less than 3 year of valid baseline data are shown in red. Th e value for Breton Island, LA was based on four years of data with n>= 70 values, because no baseline year met RHR completeness criteria


### Slide 10. 

## Default Natural Haze Levels This map is shown for comparison of to the previous map. It contains the valu es and contours of natural haze estimates using the default approach as described in the EPA guidance document for estimating natural haze conditions for the RHR. Basically it applies the original IM PROVE algorithm to the Trijonis estimate of natural spec ies concentrations plus 3.84dv (i.e. 1.28x3dv) for the eastern sites, or plus 2.56dv (i.e. 1.28x2dv) for the western sites. It instructive to view these in slideshow mode and to flip back and forth while looking at specific regions or sites to see the dif fe rence. The general pattern is similar except on the W est coast where sea salt is responsible for a very noticeable increase using the new methodology. Sea salt also make a detectable difference at a few eastern coastal sites, but they don’t shift the c ontours as noticeably. Some high elevation sites have lower values using the new methodology due primarily to the lower values used at higher elevation for Rayleigh scattering in the new IMPROVE algorithm. However many other high elevation sites have hig her natural estimate values using the new methodology (principally in the Pacific Northwest and Rocky Mountains), probably due to the broader distribution of current (and therefore assumed natural) haze levels associated with a higher incidence of wildfire inf luence. 

### Slide 11.Natural Haze Levels II, Final Report ( text extracted from PowerPoin t file ) p. 9 

## Natural Haze Levels II, 10 **- Year Rate of Progress Glide Path**  This map shows the rate of progress (deciview reduction per decade) required to reach natural levels in 60 years for site and using contours determined using the new IMPROV E algorithm and the estimates of natural haze levels II approach. 

### Slide 12

. 

## Default Natural Haze Levels, 10 **- Year Rate of Progress Glide Path**  This map shows the rate of progress (deciview reduction per decade) required to reach natural levels in 60 years for site and using contours determined using the original IMPROVE algorithm and the default estimates of natural haze. This map is shown for comparison to the previous map, which shows the new approach glide path results using the same contour intervals . Though not identical to the previous maps, the results are very similar. In fact they are much more similar than the comparisons between the default and new method natural levels maps. For example the effects of sea salt on the west coast is no longer obvious. 

### Slide 13

. 

## Status and Next Steps

• •This presentation is the final report of the Natural Haze Levels II Committee of the RPO Monitoring/Data Anal ys is Workgroup

• •Review comments received by August 25, 2006 will be considered in preparation of the RPO Monitoring/Data Analy sis Workgroup approved approach

• •Workgroup approved approach is forwarded to the RPOs for their consideration by August 31, 2006

• •This presentation, including the natural haze estimates and any modifications will be made availab le on VIEWS The information in this presentation constitute the final report of the Natural Haze Levels II Committee, which is scheduled to be presented to the RPO Monitoring/Data Analysis Wo rkgroup at their scheduled call in August 2006 (10am Pacific Ti me Aug 14, 2006). Comment received by August 25 will be considered prior to issuing a Wo rkgroup
- approved version which will be forwarded to the five RPO for their consideration. All of this material will be made available on the VIE WS web site.


### Slide 1 4. 

## Appendix •Tables of Natural Haze Level II Estimates for all IMPROVE Sites by RPO and State The tables that follow include only the IMPROVE site estimates of natural levels, as well as the current worst haze and 10
- year glide slopes. These were produ ced from an Excel spreadsheet (NaturalLevelsII.xls) which is an excerpt of another spreadsheet (NC_summary.xls) that contains both the default and new method natural haze estimates for all sites (including Protocol sites). Both of these Excel files is ava ilable on the VIE WS web site.Natural Haze Levels II, Final Report ( text extracted from PowerPoin t file ) p. 10



### Slide 15. CENRAP MANE

- VU & Midwest RPO Slide 16. VI STAS + VI Slide 17. WRAP Slide 18. WRAP
Slide 19. WRAP Slide 20. WRAP Slide 21. WRAP