Natural Haze Levels II, Final Report (text extracted from PowerPoint 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 established in the Spring of 2006 to review and 

refine, as appropriate, a methodology developed by Roger Ames (CIRA) for applying the new 

IMPROVE algorithm for estimating light extinction from aerosol species concentrations to 

natural species concentration estimates. 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 seen 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 by 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.Pitchford@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 levels 
Natural Haze Levels II, Final Report (text extracted from PowerPoint file) p. 2

– Should minimize the 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 IMPROVE 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 report 

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 either 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 natural 

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/improve/Publications/GuidanceDocs/guidancedocs.htm

Slide 4.

Default Natural Haze Levels Approach 

 Typical haze level estimates for East and West 

– Typical light extinction by applying the original IMPROVE algorithm to Trijonis 

natural species concentration estimates 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 = typical + 1.28(standard deviation) 

– Standard deviation is 3dv for the East and 2dv for 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 

http://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 well 

approximated by the 10th and 90th percentiles respectively. These assumptions seemed to work 
Natural Haze Levels II, Final Report (text extracted from PowerPoint file) p. 3

well in estimating the 20% best and worst values for current conditions at most monitoring sites. 

However, these two assumptions were the subject of considerable 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 Algorithm:

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 intent 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 Rayleigh scattering. A report describing the new algorithm is 

available at 

http://vista.cira.colostate.edu/improve/Publications/GrayLit/019_RevisedIMPROVEeq/RevisedIM

PROVEAlgorithm3.doc

Flawed Assumptions:

The basis for the assumption that the natural haze conditions 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 extinction 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 extinction 

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 distributed. 

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 scatter 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 principally due to the inclusion of a constant Rayleigh scattering. If Rayleigh 
Natural Haze Levels II, Final Report (text extracted from PowerPoint 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 8th 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 since 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 

– Multiply each species concentration at a site by 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-Adjusted Species Concentrations:

Unlike the default approach which directly uses the Trijonis natural species concentration 

estimates to calculate haze levels, 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 

mean 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 regional 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 (including 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 

Clion data (described as part of the new IMPROVE algorithm) are take to be natural 

contributors to haze.

Fundamental Assumption:

In the default approach, 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 from the 

estimated mean values. 
Natural Haze Levels II, Final Report (text extracted from PowerPoint file) p. 5

The fundamental assumption inherent in this Natural Levels II approach is that the Trijonisadjusted species data set is a good estimate of the natural species data set. Thus each site has 

its own a natural haze distribution 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 assumption, 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 Western 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 estimates 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), 

which 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 methodology. 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.

Application of the New IMPROVE Algorithm:

The new 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.

Alternate Approaches 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 eliminated. 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 every 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. When manmade 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 extent 
Natural Haze Levels II, Final Report (text extracted from PowerPoint 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. However, 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 currently 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 small sizes will not work well if the emissions are significantly different than those for 

which 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 algorithm’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 technical discussion convinced the committee that the new IMPROVE 

algorithm should be used without any modification. The basic point of the discussion was that 

while 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 SO2, NOx, and VOCs) would be so low that particles would not generally 

grow to the sizes that current high concentrations of these pollutants 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, the 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 

species 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 organic 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 assumed 

to be natural.

4. Other variations of the above with all or various fractions of the natural sourcedominated 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 counterexamples to the underlying assumptions in each of them, and it would have greatly expanded 
Natural Haze Levels II, Final Report (text extracted from PowerPoint 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 assumption 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 Wilderness, 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 natural 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-adjustment 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 sulfate, 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 the left (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 distributions 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 the 

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 dashed bars which current conditions 

are much higher than the Trijonis values, while coarse mass (orange) and fine soil (yellow) have 
Natural Haze Levels II, Final Report (text extracted from PowerPoint 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 glide 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. The 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 values 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 

IMPROVE algorithm to the Trijonis estimate of natural species 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 difference. The general pattern is similar except on the West 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 

contours 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 higher 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 influence.

Slide 11.
Natural Haze Levels II, Final Report (text extracted from PowerPoint 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 IMPROVE 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 Analysis Workgroup 

• •Review comments received by August 25, 2006 will be considered in preparation of the

RPO Monitoring/Data Analysis 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 available 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 

Workgroup at their scheduled call in August 2006 (10am Pacific Time Aug 14, 2006). Comment 

received by August 25 will be considered prior to issuing a Workgroup-approved version which 

will be forwarded to the five RPO for their consideration. All of this material will be made 

available on the VIEWS web site.

Slide 14.

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 produced 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 available on the VIEWS web site.
Natural Haze Levels II, Final Report (text extracted from PowerPoint file) p. 10

Slide 15.

CENRAP

MANE-VU & Midwest RPO

Slide 16.

VISTAS + VI

Slide 17.

WRAP

Slide 18.

WRAP

Slide 19.

WRAP

Slide 20.

WRAP

Slide 21.

WRAP