Regional Haze Rule Reasonable Progress Goals I.Overview II.Complications III.Simplifying Approaches Prepared by Marc Pitchford for the WRAP Reasonable Progress Goals Workshop - January 10 & 11, 2006, Tucson, AZ

Overview of the Regional Haze Rule Reduce the worst haze conditions to natural levels –Design rate of reduction is the uniform rate that would reduce baseline haze to natural levels in 60 years Protect the best haze conditions (least hazy) –Best haze should not increase above the baseline value Haze metric is in deciview (dv) units and related to light extinction by –haze (dv) = 10 x ln[(light extinction)/10]

Estimate light extinction from IMPROVE particle data Calculate best and worst haze conditions –Each year identify and average the 20% of days with the largest (worst) and the 20% smallest (best) light extinction –Calculate mean of the best and worst for 5-year periods [baseline: 2000 to 2004, first trend point: 2005 to 2009, etc.] –Daily, best & worst values are available for each site from the IMPROVE and VIEWS web sites Haze Metric

Natural Haze Levels Default values (EPA Guidance) –Typical natural species concentrations for the East & West estimated by John Trijonis –Converted to light extinction, then deciview using same algorithms as use with measurements –Typical natural haze values are then adjusted using a an inferred frequency distribution to worst and best natural haze values –Values for each class I area are available from EPA and on the IMPROVE and VIEWS web sites

East – West dichotomy due principally to Organic Carbon and Ammonium Sulfate Variations within East & West are due to geographic variations in relative humidity Default Natural Levels ComponentAverage Concentration E/W (µg/m 3 ) Trijonis’ Error Factor Dry Extinct. Efficiency (m 2 /g) Dry PM Extinction (Mm –1 ) Ammonium sulfate0.23/ /0.36 Ammonium nitrate Organics (POM)1.4/ /1.88 Elemental carbon Fine soil Coarse matter SumFine 2.25/1.21 Coarse /5.04 Estimates of natural species concentrations for West & East based on work by John Trijonis for NAPAP in the late 1980s Default Worst Natural Haze Levels

Uniform Rate of Progress Uniform rate of progress calculation: (29dv – 11dv)/60years = 0.3dv/year. Progress required by 2018 (14 years): 14 x 0.3 = 4.2dv or reduced from 29dv to 24.8dv

Complications Current & natural haze conditions vary due to meteorological and emissions-activity variations –5-year averaging helps but doesn’t eliminate variation, which can affect glide path calculations –Massive smoke plume impacts in some years can dramatically impact the worst haze values, (and occasionally will clog the filter so invalidates the data)

Complications Caused by Interannual Variations in Meteorology & Emissions

Clogged IMPROVE channel A filter (PM 2.5 mass & XRF) during July & Aug.

Data filled in using the other 3 IMPROVE channels shows massive organic and elemental carbon from forest fire smoke impacts.

Natural Conditions Complications Default natural levels have been criticized –Geographic regions are too large (e.g. natural levels in NW are not likely the same as in SW) –Speciation measurements at some sites are smaller than default values –Approach for converting from typical to worst and best natural haze conditions is flawed –Doesn’t include sea salt (a problem for coastal sites) or elevation-specific Rayleigh light scattering –Doesn’t fully account for organic carbon (ratio of OM to OC should be higher than 1.4) –Some think it should include haze from non-U.S. man-made emissions Some RPOs and states will use refined natural levels

Current Annual Average Coarse Matter Concentration Excess Over Default Natural Annual Concentration From Ivar Tombach

Flawed Extrapolation Method from Typical to Worst and Best Natural Haze Levels Default method –Assumes that haze data (dv) are normally distributed, and that the 10 th and 90 th percentile values for a site are good predictors of the average best and worst conditions, so best & worst = mean  –Because it includes Rayleigh scattering, haze (dv) is not normally distributed (especially for pristine sites) –If it were normally distributed a more accurate estimate of the average of the best and worst condition would be at the 8 th and 92 nd percentile, so worst and best = mean  (~10% change)

Dry Light Extinction (From GEOS-CHEM Modeling by EPRI for VISTAS)

Haze Algorithm Complications In response to criticisms IMPROVE has adopted a new algorithm to estimate haze, that includes –sea salt term based on chloride data, –site-specific Rayleigh based on elevation & T, –larger ratio of organic mass to organic carbon (1.8 instead of 1.4) –split terms for sulfate, nitrate, & organic into two size distribution each with new f(RH)

New IMPROVE Haze Algorithm where and nitrate and organic are split using the same process

Simplifying Approaches VIEWS web site has current conditions, natural levels, glide slopes and increments –Using the current algorithm (new algorithm will be available by March) –Aerosol extinction components for current conditions can be displayed Compare the total increment needed to the current aerosol component extinction –Permits assessment of how much each component contributes –A linear rollback approach can be used as a screening tool to help identify plausible emissions scenarios

Incremental Decrease in Light Extinction Needed for Worst Days by 2018

Table shows dv and extinction for recent years and RHR default future trends 2004 to 2019 Increment = 30.6 – = 6.56Mm to 2064 Increment = – = 3.86Mm -1

VIEWS Display of Aerosol Extinction Trends Table with trend points also has baseline values

Shows that it will likely take reductions in more than one component to meet the default increment of haze reduction at Petrified Forest. Would require about 75% reduction of man-made sulfate plus nitrate to achieve the goal (Maybe the high coarse mass was an anomaly and will be reduced.)

Summary The Regional Haze Rule is conceptually pretty simple, but There are detailed calculations and considerations that complicate progress goal calculations. VIEWS provides current and natural conditions, and increments, plus aerosol components of haze. These can be used to test the feasibility of emission control scenarios