# G u i d a n c e f o r E s t i m a t i n g N a t u r a l Vi s i b i l i t y C o n d i t i o n s U n d e r t h e R e g i o n a l H a z e R u l e G u i d a n c e f o r T r a c k i n g P r o g r e s s U n d e r t h e R e g i o n a l H a z e R u l eEPA-454/B-03-004 Septembe

r 2003

Guidance f

or T racking Progress Un de rt he Re gio na l Ha ze Ru le

Contract No . 68-D-02-0261 Work Order No. 1- 06

U.S. Envi

ronmen tal Protect ion A

gency Off ic e of Ai r Quali ty Plann in g and Standards Em i ss i ons , Mon

i tori ng an d A na l y sis D i vi si on Ai r Quali ty Trends an

d An al ys is Group Research Triangl

e Park, NCDISCLAIMER

This r epo rt is a wo rk pr epa re d fo r t he Unit ed S t at es G ove rnment by Bat t elle. I n no e vent shall eithe r t he Unit ed S t at es G ove rnment or Bat t elle have a ny resp ons ibil ity o r liabili

t y for a ny consequenc es of an

y us e, misuse, i

nab il ity to use, or reliance upon the i nf ormation contai

ned he r ein , no rdo es eit he rwa rr an t o ro t he rwis e r ep r es en t in a ny w ay t he ac cu r ac y, ad eq ua cy, ef f i cacy , or a ppl i ca bi l i ty of the con ten ts h ere of

. ACKNO WLEDGMENTS The Env ironm ental Prot ection A

gency wis hes to acknowle dge the assistance an d in put provided by

the f oll owin g adv i sors i n the preparation of thi

s gui danc e docum

ent: Rodger Am es, N ati onal

Park Se rvi ce (C ooperati

ve Institute f

or Res earch i

n the A tmos phe re (CIRA ); Shao-H an

g C hu /US EPA ; R

i ch Da m be rg, USEPA ; T am

m y Eag an , F l orida

Dept. of Env i ronm ental Protection; Neil

Fran k, USEPA; Eric

Gi nsb urg, USEPA;Denn

i s Haddow, U.S. Fi sh and W

il dli fe Service; An

n Hess, Colorado Stat e Uni versity ; Hari Iy

er, Dept . of St atistics, Co lo r ad o St at e U nive r sit y; Mik e K o er be r , La ke Mic hig an AirDir ec t o r s C o nso rt ium; Bill Le en ho ut s, U. S. Fis h a nd Wildlife Se rvic e; William M alm, Na t io na l Pa rk S er vic e ( CI RA) ; D eb bie Mill er , N at ional P ar k S er vice; T om Mo or e , West er n Reg ional Air P ar t ner ship; Ja nice Pe t er so n, U. S. Dep ar t ment o f Agricu ltu re , Fo re st Ser vice; Ma rc Pit chfo rd , N at ional Oc eanic a nd A tmosphe ric A dm i ni stra ti on, A i r Re sou rce s L ab orator

y ; R i ch Poi rot, Sta te of Verm ont, Dept. of Env i ronm en tal Cons ervati on; Bruc e Pol kowsky , National Park Se rvi ce; Tom R

osen dah l , USEPA; Dav

id San dberg, U.S. Fis

h an d Wi ldl if e Service; Ji

m Sisler, National

Park Servi ce (CI RA); T im Smi

t h US EP A; Ta mmy

Ea gan, Flor ida De pt of t he E nviro nment ; Ken Walsh, SAIC.Guidance f or Tracking Progress Under the Regional Haze Rule

i 

### TABLE OF CONTENTS

Abbrevi atio ns and Acronyms

................................................ vi Glossary of Terms

........................................................ viii 1. INTRODUCTI ON 1.1 Wh

at is regi onal haze?

.......................................... 1-1 1.2 W h at is th e pur pos e of th i s Tra ck

i n g P rogre ss

gui da n ce docum en t fo rt he r eg io na l ha ze pr o gr am?

.................................... 1-1 1.3 Do es t his g uid an ce do cu men t ap ply t o T r iba l Cla ss I ar ea s a s w ell as mand at or y Feder al Class I ar eas ?

................................ 1-2 1.4 What is the st at ut or y and r egu lato ry basis fo r t he r egio nal haze pr og ra m?

... 1-3 1.5 Wha t ar e t he init ial mile st o ne s o f t he r eg io na l ha ze pr o gr am?

............. 1-3 1.6 What vi sibil

ity m etric wil l b e used for sett in

g goals and tracking progr ess?

... 1-5 1.7 What key requi

rements i n the regional h

aze rule relate to pro gress go als for mandat or y Feder al Class I ar eas ?

........................... 1-5 1.8 Ho w do es a St at e de t er mine the r at e o f pro gr ess it must analyze in t he pr og re ss g oa l develo pment pr oc ess?

............................ 1-6 1.9 Wh

at ot her f actors should be c onsidered in devel oping C lass I area pr og re ss g oa ls?

............................................... 1-8 1.10 Wou ld EP A acc ept a pr og re ss g oa l pro viding for visibi lity deg ra dat ion?

..... 1-9 1.11 What are the regional haze rule requiremen ts for pr ogr ess revi ews and future SIP revisi

ons?

........................................ 1-9 1.12 Wh

at are the maj or analy

tical tasks in volv ed i n addressi ng speci fi c re quir ement s in the re gio nal haze ru le reg ar ding t ra cking p ro gr ess?

....... 1-10Guidance f or Tracking Progress Under the Regional Haze Rule

ii 1.13 What air qual

ity m onitoring is un

der way to sup por t t racking progress to ward im

provin g vi si bi li ty condi tions un der the regional

haze rul e?

....... 1-12 1.14 Wh

y ha ven’ t parti cul

ate m atter m oni tors be en depl oye d at al l mandatory Fede ra l Class I ar eas ?

......................................... 1-13 1.15 Do es t his gu id an ce pe rt ain t o t r ac ki ng o f Cl as s I ar ea ch an ge s in vis ibilit y by western States subm

ittin g regional haze pl ans un der Section 51.309 of the regional

haze rul e?

....................................... 1-14 1.16 Does t hi s guidance on Tracking Progress addr ess all of the requi

red ele men t s o f t he 5- yea rpr o gr es s r ev iew s r eq uir ed un de rt he r eg io na l haze ru le?

.................................................. 1-14 1.17 W h at i n f orm ati on i s prov i de d i n th e rest of

th i s g ui da n ce docum en t?

....... 1-15 2. SUM MARY OF TRACK ING PROGRESS CA LCULATION PROCEDURES 2.1 W h at is th e pur pos e of th i s s ecti on

of th e g ui da n ce docum en t?

............ 2-1 2.2 What is

the sequence of steps needed t o calculate data for t racking progress?

. 2-1 2.3 Th

i s 1 0- ste p p roc es s f

ocu se s on us i n g c om pl ete yea rsof da ta. W h at i f an i nc omp l ete y

ear woul d obv

i ousl y ha ve be en a parti cul arl y bad or good visi bi l i ty y ear?

............................................ 2-9 3. CA LCU LAT IO N O F HA ZE 3.1 Wh

at causes haze ?

............................................. 3-1 3.2 How are haze levels calcul ated?

................................... 3-1 3.3 Ho w a re t he mo nit o ring da t a u se d fo r t he c alc ula t io n o f b extobtaine d?

...... 3-2 3.4 What are the species speci fi c scatt ering ef

fi cien cies f or aer oso l components?

. 3-4 3.5 What eff

ect do es relativ

e hum idi ty have on the haze l

evel s?

.............. 3-6 3.6 How are the f(RH) val ues determi

ned?

............................. 3-10Guidance f or Tracking Progress Under the Regional Haze Rule

iii 3.7 Ho w do es light abso rp t ion co nt ribut e t o light ext inctio n?

............... 3-12 3.8 How is the total ligh t extinction cal

cul ated?

......................... 3-12 3.9 How are deciv

ie w val ues cal cul ated?

.............................. 3-13 3.10 Should outli

ers i n the data be ex

cl uded?

............................ 3-14 4. PROCEDURES FOR COMPARING 5-YEA R PERIODS 4.1 How are

the dail y deci vi ew v al ues , cal cul ated as des cri be d i n Se cti on 3, us ed t o t r ac k p r o gr es s in imp r o vin g v isib ilit y?

......................... 4-1 4.2 Ho w ar e t he se lect ion and aver aging o f the best and w or st days in each y ear done?

............................................... 4-1 4.3 How are the 5-year deci view averages

determi ned?

.................... 4-2 4.4 Wh

at is the n ature of the compari son between 5-y ear average decivi ew val ues?

............................................... 4-2 4.5 Wh

at if si ting or procedural ch

anges are i

mpl em ented at an IMPROVE si

te?

. 4-2 4.6 Wha t if c ha ng es ar e ma de in t he sit es se lec t ed t o co ve ra ma nd at o ry Federal Cl ass I area?

............................................ 4-3 4.7 Ar e t r en ds in t he ind ividua l sp ec ies impo rt an t , as we ll as t he o ve r all t r en d i n vi sib ilit y?

.............................................. 4-3 5. Reference s ............................................................ 5-1 6. Appendix A - Monthly Site-Sp ecific f(r h) Values for

Each Mandatory Federal

Class I Areas

..................................... A-1 7. Appendix

B - Analys is of the

Eff ect of C orr

elatio n Between f

(RH) and SO 4 and f(RH) and NO 3 on Deciview Calculations Using f(RH)

............................................. B-1Guidance f or Tracking Progress Under the Regional Haze Rule

iv 

### List o f Figu res
Fi gure 1 -1 Ex amp le o f met ho d fo r d et er mining M and at o ry Fe de ra l Clas s I ar ea ra t e o f

pro gress to be anal

yzed i n SIP developmen

t pr ocess .................... 1-7 Fi gure 1 -2 Expa

nde d IMPR

OVE Vi si bi l i ty Moni torin g Network

.................. 1-13 Figure 2-1 Su mmary of St ep- by-St ep P ro ces s for Tr ack ing Pr og re ss Ca lculat ions

...... 2-3 Figure 3-1 Summ

ary of Process to Calcul ate Haze Index

......................... 3-2 Figure 3-2 Smo ot hed Ammonium S ulfat e Gr ow t h Cur ve ......................... 3-8 Figure B-1 Boxplot s of y early percentage errors pSO4 yearly for 20 selected IMPROVE sites

....................................... B-10 Figure B-2 Boxplot s of pSO4 mo nth ly for 20 selected IMPROVE sites

................. B-11 Figure B-3 Boxplot s of pSO3 yearlyfor 20 selected IMPROVE sites

.................. B-12 Fi gure B -4 Boxplot s of pNO3 month ly for 20 selected IMPROVE sites

................. B-13 Figure B-5 Boxplot s of pSO4NO3 yearlyfor 20 selected IMPROVE sites

.............. B-14 Fi gure B -6 Boxplot s of pSO4NO3 month ly for 20 selected IMPROVE sites

.............. B-15 Fi gure B -7 Com

parison of perce ntag e errors

i n a verage e xti nction f or LO WE S T 20 % ex t inc t io n d ays ................................... B-16 Figure B-8 Co mpar ison o f per cent age er ro rs in ave ra ge e xt inctio n

f or HIGHEST 2 0%

........................................... B-17 Figures B-9 Compari son of percen tage erro rs in

average deci

view for LOWEST 20% extinction day s. ............................... B-18 Figure B-10 Compari son of percen tage erro rs in

average deci

view fo rHI GH E S T 20 % ex t inc t io n d ays ............................... B-19Guidance f or Tracking Progress Under the Regional Haze Rule

v 

### List of Tables

Tab l e 1-1 Deploym

ent of IMPROVE Si

tes, 1999-2001

......................... 1-4 Table A-1 Val

ue s f or f (R H) deter m i n ted f rom th e g row th of am moni um su l f ate
....... A-4 Table A-2 Re co mmen de d M o nt hly S it e- S pe cif ic f ( RH ) Va lu es fo rE ac h M an da t o ry Fe deral Cl as s I A re a, Ba se d on

th e R epre se n tati v e I MP RO VESi

te Loc ati on ..................................................... A-6 Table A-3 Mo nt hly S it e- Sp ec ific f( RH ) Va lue s fo rE ac h Ma nd at o ry Fe de r al

Cl ass I Area, Bas ed on the Centroid of the A rea (S upp lementa l Infor matio n)

..................................... A-11Guidance f or Tracking Progress Under the Regional Haze Rule

vi 

### Abb re vi at i o n s a n d Ac ro n yms b ag - Ligh t exti ncti on coefficient associat ed with th e absorpt ion by gases b ap - Ligh t exti ncti on coefficient associat ed with th e absorpt ion by par ticles b ext - To tal lig ht exti nct ion coef fi ci ent b sg - Ligh t exti ncti on coefficient associat ed with th e scatter in g by gases b sp - Ligh t exti ncti on coefficient associat ed with th e scatter in g by parti cles BART - bes

t available retrofit tec

hnology CAA– Clea n Ai r Act CAAA – 1990 Clean Air Act Amendme nts CASTNet - C le an Ai

r Statu s a nd Tre ndsNe twork CIRA – Coo perative Institute f

or Re search in the Atmo sphere, Colorado State U niversity CM - Coarse mass dv - Deciview - un it of th e haz e ind ex EPA – Unit ed Stat es En viron men tal Protecti on Agen cy f(RH) – Rel at ive h um id it y adju stm en t fa ctor GCVTC – Gr an d Ca nyon Vis ibi li ty Tr an spor t C omm iss ion IMPROVE – Interagency Monito ring of P rotec ted Vis ual Environments LAC - Li gh t a bsor bin g ca rbon Mm -1 - Inverse megameter (10 -6m -1 ) MAR AMA - Mi d-A tl an ti c Regi ona l Ai r M an ag eme nt Assoc ia ti on NA AQS – National Ambient Air Qualit y Standar ds NESCAUM - N ort

hea st St ate s f or Co ord inat ed Air U se Mana gement NO 2 – Nitrogen dioxide NOAA - Na ti ona l Oc ean ic a nd Atm osph er ic A dm in ist ra ti onGuidance f or Tracking Progress Under the Regional Haze Rule

vii NPS – Unit ed Stat es Depar tmen t of the In teri or, Na tion al Pa rk Ser vice OC - Or ga ni c car bon OMC - Organ ic carbon ma ss OP - Pyroliz ed orga ni cs PIXE - Proton induced x-ray e mission spectroscopy PM – Par ticul ate m att er PM 2.5 – P arti cu

lat e m att er w

ith a n aerod y namic dia me ter le ss

than 2 .5 microns PM 10 – P arti cu

lat e m att er w

ith a n aerod y namic dia me ter le ss

than 1 0 mi cro

ns RH - Relative

humidity RPO - Regi ona l Pl an ni ng Or ga ni za ti on SIP – Stat

e Imp leme

ntation P lan STAPPA - S tat e a

nd Te rrito rial Air Pollu

tio n Program

Ad mini st rato rs TDMA - Tandem

dif fe rent ial mo bi lit y analy zers TIP - Trib al imple

mentatio n plan TOR - Th erm al opt ical r eflectan ce WESTAR

- We stern States

Air Re sou

rces C ouncilGuidance f or Tracking Progress Under the Regional Haze Rule

viii 

### Gl o ss ar y o f Te rms

Aeros ols – Su spe

ns io ns of ti ny li qu id and/ or so lid p arti cl e s i

n t he air. Coar se mass – Mass of particulate matte r with an ae rody nam ic d iam ete r greate r than 2.5 m

icro ns but less than 1 0 m icro ns. Deci view (dv)- T he unit of meas ur ement of ha ze, a s in t he haz e index (H I) defi ned below. Fine particu

late m atter – part ic ul ate matte r wi th an aerody

nam ic diamet er le ss th an 2 .5 m icron s(PM2.5 ). Fine soil – P ar tic ula te ma tt er c ompos ed of p ollu ta nts fr om the E ar th’ s s oil, wit h a n a ero dyna mic dia meter les s t ha n 2. 5 mi cr ons . T he s oil mas s i s c a lcu la ted fr om ch emica l ma ss mea su r ement s o f f ine a lu minu m, fin e si lic on , fin e c alciu m, f ine i ron, an d fi ne titani um as well as their associated oxide s. Haze in dex (HI) – A me

asu re of visibility derived from calculated light extinction measu rements that is de sig ne d s o t hat un if orm ch ang es in the haze in

de x co rres pond toun if orm in cre men tal ch ang es in vi sual pe rce ptio n, across t

he en tire rang e o f co

nd itions from

pristi ne to h ig hl y i m paired. Th

e h aze in de x [i n un its of d ec iv ie ws (dv )] is calcul

ated d irectly from the total light e

xtinctio n [b ext e xpresse

d i n i nv erse me ga mete rs (Mm -1) ] as fol lows: HI = 10 ln (b ext /10 ) Ligh t ab sorbi ng c arb on

- Carb on

parti cl es in the atm osphere that abso rb l ig ht ; al sore porte d as e le men tal car bon. Least- im pai red d ays – Da ta repr esenting a s ubs et of the annu al meas ur emen ts t hat corr espond to t he cl e are st, or

le ast h azy, day s o f t

he ye ar. Ligh t ex tinctio n - A mea su r e of h ow mu ch l ight is ab so rbed or sc a tt er ed a s i t p a ss es t hr ou gh a mediu m, such as th e atm osph ere . The aerosol lig

ht e xtin ctio n re fers to

the absorptio n and scatteri ng by ae rosol s, and the total lig

ht extinctio

n refers to the sum of the

aerosol lig

ht extinctio

n, the absorption of gases (such as NO 2 ), and the

atmosph eric l igh t extin ction (Rayleigh

scattering)

. Mandatory Federal Clas s I are as - C ert ai n na tio na l pa rk s ( over 6, 00 0 a cr es) , wi lder ness ar eas (over 5,000 acre s), n atio nal mem orial p arks(o

ve r 5,00 0 acres), an

d i ntern atio nal parks th at were in exi ste nc e as of Au gu st 19 77. A

ppe nd ix A li sts t he mand atory Fe de ral are as. Most im pai red d ays– Da ta repr esenting a s ubs et of the annu al meas ur emen ts t hat corr espond to t he di rti e st, or ha zi e st, da ys of the ye ar.Guidance f or Tracking Progress Under the Regional Haze Rule

ix Nitra te – Solid or li

quid particulate matte

r contain ing amm oni um n itrate [NH 4 NO 3 ] o

r ot he r ni trate sal ts. Atm osphe ric nitrate ae

rosols are o ften

form ed from the atmosph eric o xidatio n of oxid es o f nitrog

en (NO x ). Organ ic c arb on – Aerosols composed of orga nic compounds, which may resu lt fr om em issions from incomplete combus tion pr ocesses, solvent evap ora tion followed by at mospheric condensat ion, or the oxi datio n o f som e v egetativ e e mi ssio ns. Particu late m atter – Ma teria l that is car ried by liquid or solid aerosol par ticles with aerodynamic di ame ters le ss than 10m

icro ns (in the di scussi ons of thi s rep ort). The

te rm i s used f

or bo th th e i n si tu atmo sphe ric suspe nsi on and the sample c olle cte d by

fil tration or othe r means. Ray leig h sca tte ring – Li gh t sc atte rin g o f th e nat ural gas es in the atm osphere . A

t an e le vat io n o f 1.8 kilo mete rs, the ligh t extin cti on from Rayl ei gh scatte rin g i s appro xim

atel y 10 in ve rse m eg ame ters (Mm

-1 ). Relat ive hum idit y – Pa rt ial p ress ur e of water vapor at the at mospheric tempera tur e divided by the vapor pr ess ur e of wa ter at tha t t emper at ur e, ex pr ess ed as a p erc enta ge. Sulf ate – Solid or li

quid particulate matte

r com posed of sulf uric acid [H

2 SO 4 ], am mon ium bisu lfate [NH 4 HSO 4 ], or amm

oni um sulf ate [(NH4 ) 2 SO 4 ]. At mospheric sulf at e aeros ols a re oft en formed from the at mosp her ic ox ida tio n of s ulf ur diox ide. Total car bon – Su m of the light ab sor bing ca rb on and orga nic car bon. Vis ibil ity impair ment– Any hu manl y per cep tib le cha nge in vi sib ilit y (li ght ext inct ion, vis ua l r an ge, contra st, colorat ion) from that which would have e xisted under nat ura l conditions. This cha nge in atmo sphe ric transpare

ncy resul ts from adde d particu late matte r or trace g

ases.Guidance f or Tracking Progress Under the Regional Haze Rule

1 - 1 1. INTRODUCTI ON 1.1 What is regional haze? Reg ional haz e is visibil

ity impairment cau sed by the c umulat ive air p ollut ant emissions from num erous sources over a wide geographi c area. Vis ibil

ity im pai rmen t is caus ed by

particles and gas es i

n the atm osphere. Som

e parti cles a nd g ase s sc atter li ght wh

i l e others ab sorbl i ght. The net effect is called “light ext inctio n.” The re sult of t hese pr oc esse s is a r edu ct ion o f the am ount o f l igh t from a sce

ne that i s returned to t he observ er, as well as an addi

tion of sc atter ed li ght t o t he si

ght pat h, creat in

g a hazy condition. To a viewer, haze can be perceived as a re ducti on i n th e v i sual cl ari ty of an ob j ect. The pr imary caus e o f reg ional haz e in many part s o f the co unt ry is light sc at t er ing re su l ti n g f rom f i n e p ar ti cl es (i .e ., p ar ti cul ate matte r les s th an 2.5 m i cron s i n di am ete r, ref er re d to as PM2.5 ) in

the atmosphere. Thes e fi ne particl es can c ontain a

variety of ch

em ic al species in cl udin g carbonaceous speci

es (i .e., o rganics and el

em ental carbon), as wel

l as am moni um ni trat e, sulf ates, and soil . Addi

tional ly , coarse particle s between 2.5 an d 10 mi crons i n diam eter can c ont ribut e t o light ext inctio n. E ach o f the se c omp one nt s ca n be nat ur ally occu rr ing o r t he re su l t of h um an acti v i ty . Th e n atu ral l ev els of th es e s pe ci es re su l t i n som e l ev el of v i si b i l i ty imp air men t in t he ab se nc e o f any hu man influ en ce s a nd wil l va ry wit h s ea so n, da ily me t eo r o lo gy, and geogra

phy

. 1. 2 Wh at is t he p urp ose of t hi s Trac kin g Pro gres s gu id an ce d ocu men t fo r th e reg io na l ha ze program? Th i s d ocu men t prov i de s g

ui da n ce to EP A Re gi on al, Sta te, an d Tr i b al ai r q ual i ty man ag eme nt au t ho r it ies an d t he ge ne r al p ub lic, o n ho w E PA int en ds t o ex er cis e it s d isc r et io n in im plem enting Cl ean Ai r Act pro vi sions an

d EPA regulations, co ncerni ng the tr acking of progress under the regional haze program. The guidance i s design ed to im plem ent national poli

cy on these issues . S ect ions 1 69A a nd 16 9B o f the Clean Air Ac t (4 2) U. S. C. § § 7 491 ,7 492 and i m plem en tin g regu l ati ons a t 40 CF R 51.3 08 an

d 51.30 9 con

tai n l egal l y bi ndi ng r equi rem en ts. This docu men t does n ot subs titute f or those provi sions or re gul ati ons, n or is i t a regul ati on i tself

. Thus, i t do es not im

pose bi ndi ng, enf orceabl e requirem

ents on any

party, nor does it assure that EPA may approv e al l i ns tan ce s of i ts a ppl i ca ti on, an d th usthe gui da nc e m ay not a ppl y to a par t icular situ at ion bas ed u po n t he circ umst ance s. T he E PA and St at e de cision mak er s re t ain the di scre tion to adopt approache s on a cas e-by-cas e b asis tha

t di f f er f rom th i s gui dan ce wh ere appropri ate. An

y deci sions b

y EPA rega

rdi ng a p artic

ul ar State im

pl em entation plan (SIP) dem onstration wil

l onl y b e m ade base d on the statut e and regul ations an d wil l onl y b e m ade followi ng notice and opport uni

ty f or publi c review and com

me nt. Therefore, in

terested part ie s ar e fr ee t o r ais e q ue st io ns a nd o bje ct io ns a bo ut t he ap pr o pr iat en es s o f t he ap plic at io n o f t hisGuidance f or Tracking Progress Under the Regional Haze Rule

1 Areas des ign

ated as man

dator y C lass I areas are those Nationa l Parks e xceedi ng 6,000 acres, wilderness areas and na tiona l mem oria l pa rks exceeding 5,00 0 a rea s, and a ll interna tiona l pa rks which were in existence on Augus t 7, 197 7. Visibilit y has b een ide ntified as an impor ta nt valu e in 156 of these area s. S ee 40 CFR par t 81, subp ar t D. The extent of a Cla ss I a rea includes su bsequent changes in boundaries , suc

h as park expansio ns . [CA A s ec tio n 1 62 ( a)]. State s and t

ribes m ay d es ig nate add iti on al ar eas as Clas s I, b ut the requir eme nts of the visibility progr am under section 169A of the CAA app ly only to "mand atory Cla ss I ar eas," and do no t affect these addi

tional areas. For the purpose of this guid ance do cum en t, th e te rm “Clas s I are

a” w ill b e used i

nterc han ge abl y w ith “m and atory Fe de ral Cl ass I are a.” 1 - 2 guid ance t o a par t icular situ at ion; E PA will, and St at es sho uld, co nsider whet her or not t he re co mmendat ions in t his guida nce a re app ro pr iate in that situ at ion. This g uidanc e is a living do cu men t an d ma y be r ev ise d p er io dic ally w it ho ut pu blic n o t ice

. T he E PA we lco mes pu blic com m en ts on thi s docu men t at a ny ti me a nd wi l l consi der those com men ts i n a ny f uture re vi si on of th i s gui dan ce docum en t. Re aders of thi s docu men t are ca utione d n ot to reg ard

sta tem en ts re com men di ng the us e of cer t ain pr oc edu re s o r d efault s as e ither pr eclud ing o t her pr oc edu re s o r infor matio n or pr ovid ing guara ntee s tha t usi ng th ese procedu res or de f aul ts wi l l resu l t in actions th

at are f ull y approv ab l e. As n o t ed ab o ve , E PA ca nno t as su r e t ha t ac t io ns b as ed up o n t his g uid an ce will be fully a pp r o vable in a ll inst an ce s, an d a ll final a ct io ns ma y o nly be t ak en fo llo win g n o t ice an d o pp o rt un it y fo rpu blic com m en t. 1. 3 Do es t hi s gu id an ce d ocu men t a pp ly t o Tri ba l Cla ss I a reas as w ell as man da to ry Federal Class I areas? Not d i re ctl y , a l th oug h th e proc ed

ur es f or c al cul ati n g l i gh t ex ti n cti on an d tracki n g v i si b i l i ty chang es o ver t ime that ar e de scr ibed in t his guida nce c an be u sed by Tribes t hat ar e co nduc t ing their own ai

r quali ty m onitorin g usi ng the Interagenc

y Monitorin

g of Protect ed Vi sual En vi ron men ts (IMP RO VE) protoc ol . The C A A an d the re giona

l ha zerul e c al l f or th e p rotecti on of v i si bi l i ty i n 15 6 “mandatory

Fed eral Class I area s.” 1 Tr ibes can e st ablish Class I ar eas for t he pur pos esof the pre ve nti on of si gn i f i ca nt d eteriorati on program

, but the C A

A doe s n ot prov i def or the in cl usion of Trib al

areas as m

andatory Fede

ral C lass I areas sub

je ct to section 169A

and 169B of the CA A. F or thi s reason, progress goal s do n

ot have to be e stab l i shed f or Tri ba l Class I area s.
Ho we ve r , T r ibe s ma y findit ad va nt ag eo us fo ra n umb er o f r ea so ns t o pa rt icip at e in regional pla nni ng organi zations (RPO) f

or regional

haze an d to devel op regional

haze Tri bal imp leme nt at io n p lan s ( T I P s)

. P ar t icip at io n inan RP O ma y allo w s o me T r ibe s t o bu ildca pa cit yGuidance f or Tracking Progress Under the Regional Haze Rule

2 See 63 Fed era l Reg ist er7254 (Fe bruary 12, 1998), and

40 CFR Part 49.

3 See 45 Fed era l Reg ist er80084 (Dece mbe r 2, 1980).

4 See 64 Fed era l Reg ist er35713 (Jul y 1, 1999) . See

also 4 0 CFR 51.300-309. 1 - 3 and en han ce thei r air qual ity ma nagem ent capabi

li ties. Unde

r the Tribal

Ai r Rule , Tribal go ver nments may elect t o implement air p ro gr ams in much t he sa me way as S t at es, including developm ent of Tribal

im plem entation plans. 2 In t his way, T ribes c an wo rk wit h ot her St at es a nd T ribes o n t he de velop ment a nd adoption of speci

fi c em is sions reduction strategies designed to pro tect air quali ty across a broad r eg io n inc lud ing T r iba l and State lands. 1.4 What is the statutory and regulatory bas is for the regional haze progr am? Sec t ion 1 69A o f the 197 7 Clea n Air Act amendment s (C AAA) se t for t h legislat ive requirem ents f or addressin

g vi si bi li ty i mpa irm ent due to air poll

ution. It established a n

ational vi si bi li ty goal to remedy

existin g im pai rmen t and preven

t future im

pai rmen t in 156 Na

tional Parks and wil derness areas acro ss the count ry desi gnated as mandator y F ederal Class I areas. I t also call ed for EPA t o develop regulations requiring State impl emen tat ion plans (SIPs) t o addr ess vi si bi li ty. These pl

ans m ust in cl ude a long-term strategy and B est Avai la ble Retrofit Techn

ology ( BAR T ) o n c er t ain ex ist ing so ur ce s fo rmak ing “r ea so nable pr o gr es s” t o wa r d t his g o al. The EPA issued i

ni tial vi si bi li ty regulations i

n 1980 3 t ha t ad dr es se d v isibilit y impa irme nt in a m andatory Fede

ral C lass I area that is

“reasonably

attr ib utable ” to a singl

e source or smal

l group of sou rc es . Th e E PA su b se qu en tl y i ss ue d r eg ul ati on s to addr es s reg i on al

h az e ( i .e ., v

i si b i l i ty i m pai rmen t caus ed b y em i ssi ons f rom n um erous s ources

l ocated over a b

road geogr

aph i c regi on), in 1999. 4 Th e re giona

l ha zerul e re qui res State s wi th m an da tory Fe deral Cl as s Iare asto de ve l op SIPs that incl

ude reasonabl

e progress goals f

or im provin g vi si bi li ty i n each ma ndatory Federal Class I area and emi ssion reduction measures to meet t hose goals. 1.5 W hat a re the in itia l milestone s of the regiona l haze program? A f ter pub l i ca

ti on of the regi ona l ha zerul e i n 1 999 , th e f

i rs t ste p i n th e i m plem en tation process was the upgrade and e xpansion of the IMPROVE visi bi li ty m onitorin g network t o 110 si tes national

ly . These si tes were sel ected to represent all m andatory Fede

ral C lass I areas, exc eptGuidance f or Tracking Progress Under the Regional Haze Rule

5 Bering S ea Wilder ness is t oo remote for r outine measu rements of t he kind em ployed by the IMP ROVE visibilit y monitoring networ k.

6 40CFR51.308 (d) (2) (i ). Al so, as di scusse d i

n th e preamble to

the regional h

aze rule ( 64 FR 35728- 9, Jul

y 1, 1 999), re

pres en tativ e m on ito rin g d ata co ll ec ted from thi s ne two rk w ill be use d to e stab li sh bas e li ne co nd it io ns (f or the 200 0- 200 4 pe

riod) fo r e ach Cl ass I are

a and t o t rack pro gre ss tow

ard go als e stablish

ed in future SIPs.
1 - 4 f or th e B eri n g S ea W i l dernes s s i

te 5 . The expan

ded IMPROVE m

onitorin g network was deploy

ed durin g the 1999-2001 tim

e fram e i n accordance wi

th Table 1-1. Representat iv

e moni to ring data collected from thi s networ k wil l b e used to establi sh ba sel i ne cond i tions (f or the 20 00-20 04 peri od) f or each Class I area and to track progre ss towa rd goals established i

n f utur e SIPs. 6 One can

see f rom Tabl e 1-1 that 101 (o r 92%) of the 110 sites ar e exp ect ed t o ha ve at least 4 co mplet e year s o f dat a fo r t he pu rp os e o f det er mini ng bas eline conditions. Onl

y 9 si tes are expect ed to use 3 years of data to establi sh basel in e conditions. Table 1-1 Deploym ent of IMPROVE Sites, 1999-2001

Year Number of

IMPROVE Sites Deployed Number of Years of Data for Calc ulating Bas eline Conditions (2000-2004) 1999 60 5 2000 41 4 2001 9 3 TO TAL 110

Mo st St at es ( and T ribes a s ap pr op riat e) ar e exp ect ed t o s ubmit r egio nal haze SI Ps in t he 2007-2008 tim

e fram e. Nin e western States have the option un der Section 51.309 of the regional ha ze rul e to im plem en t the rec omm

endations of

the G rand Can y on Visi bi l i ty Tr an sport Co mmiss io n ( GC VT C) wit hin t he fr ame wo rk o f t he r eg io na l ha ze rule , pr o vid ed t he y su bmit i ni tia l regi onal ha ze SIP s i n 20 03. Progre ss re

vi ews are to be cond ucted e very 5 y ears af ter SIP sub m i ttal, a nd c omprehen si

ve SIP rev i sions a re req ui red i n 20 18 an d every 10 y ears there af ter.Guidance f or Tracking Progress Under the Regional Haze Rule

1 - 5 1.6 Wha t visibi lity metric will be used for setting go als and tracking progress? As st at ed a t 40 C FR 51 .3 08 ( d) (1 ), base line visi bili t y cond itio ns, p ro gr ess g oa ls, and chan ges i n vi si bi li ty m ust be express ed i

n terms of deci view ( dv ) un

i ts. The de ci vi ew i s a un i t of measu re ment o f haze, implemented in a haze index ( HI ) t hat is der ived fro m calculat ed light ex ti n cti on , a n d th at is des i gn

ed so t h at u n i f orm ch an ge s i n h az i n es s c orre sp on d a

pp rox i mate l y to un i f orm i n crem en tal ch an ge s i n perc ep ti on , a cross

th e en ti rera n ge of con di ti on s, f rom pri sti n e to hi ghl y i m pai red. The HI is expresse d by

the fol lowi ng f ormula:
HI = 1 0 ln(b ext

/10)

where b extrepresents t ot al l igh t extinction expressed in

in verse megam

eters ( i.e., Mm -1 =10 -6 m

-1 ). See Section 3 of this documen t for further details on cal cul ating HI

in dv uni ts from IMPROVE m oni torin g data. 1. 7 Wh at key re qu ireme nt s in th e reg io na l ha ze rule relat e t o p rogre ss g oal s for ma nd at ory Federal Class I areas? In their i ni tial control strat egy SIPs due in 2007-8, St ates are r equired to adopt pro gress goals f or im provin g vi si bi li ty f rom bas elin

e condi tions (represen

ted by 2000-2004) to 2018 (r epr ese nt ed by 20 14 t o 2 018 ) fo r e ach C lass I ar ea in t he St at e. A St at e t hat do es no t have a ny Cl ass I areas wi

ll not establish an

y progress goal s i

n i ts SIP, but it is requi

red to consul

t with other Stat es hav

in g Cl ass I areas that m

ay be i mpa cted by em is sions f rom the State. A Stat e wi thout an y Cl as s Iare aswi

l l also n ee d to a dopt e

m i ss i on r ed uc ti on s trate giesto addre ss

i ts c ontr i bu ti on to vi si bi l i ty i m pai rmen t probl ems i n C l ass I area s l ocated i n othe r States. Sp ec i f i ca l l y , a Sta te is req ui re d to s et progre ss

goa l s f or e ach Cl as s I area i n th e S tate th at:

C prov i de

f or a n i m prov em en t i n v i si b i l i ty f or th e m ost i m pai re d ( i .e ., 2 0% wor st) days o ver t he pe rio d o f the implementat ion p lan, a nd

C ensure n

o degradation in

vi si bi li ty f or t he l east im pai red (i.e., 20% best) day s over the sam e period. I n C las s I ar ea s w it h hi gh er lev els o f vis ibilit y imp air men t , t he co nd it io ns o n t he be st da ys may sti l l be seve ral de ci vi ew s h i gher th an es ti mate d natu

ral con di ti ons . The EP A

ex pe ctstha t f or most of these areas, emission reduction strat egies to im pro ve visibil

ity condi tions on the wo rstGuidance f or Tracking Progress Under the Regional Haze Rule

1 - 6 days sh ould also lead to im

pro vem ents on t he best days. State s should track pr ogr ess on the best days as wel

l as the worst days i

n order to determi

ne if em is sion reduction strategies l ead to an im provemen t in the ove

rall dis tributi on of visi

bi li ty condi tions. If a

degradation i

n be st day conditions i s observed over t im e, St ates should re-evaluate t hei r emi ssion reduction strat egies. T he r ea so nable pr o gr es s g o als mus t pr o vid e fo ra r at e o f impr o ve men t su fficie nt t o at t ain natural condi

tions b y 2064, or jus

tif y a ny al ternative to this

rate based upon f

actors li sted in

169A ( g) ( 1) o f t he Cle an AirAc t an d 3 08 ( d) ( 1) ( i) ( A) o f t he r eg io na l ha ze rule

. St at es will determi ne wh ether they a

re mee ting thei r goals b y c ompari ng vi si bi li ty condi tions f rom one f iveyea r av era geto an othe r (e .g., 200 0-2 004

to 201 3-2 017 ). In

orde r to con duc t the an al y sis f or setti ng prog res s g oals, th

e Sta te shou l d us e th i s Tr ac ki ng Prog res s g ui da nc e docu men t f or de term i ni ng 5-y ea r b as el i ne con di ti ons . A se pa rate gui da nc e docu men t addre ss esmeth

odsf or est imating N at ur al Visibil ity Co ndit ions ( i.e. , t he ult imate g oa l of t he visibil ity impro vement program ).
1.8 How does a State determine the rate of progress it must analyz e in the progres s goal development process? In de ve l opi ng an y prog res s g oal , th e Sta

te w i l l ne ed to an al y zean d c ons i der i

n i ts s et of op t ions t he r at e o f im

pr ove ment be t wee n 200 4 ( when 2 000 -2 004 base line cond itio ns ar e se t ), and fut ur e p er io ds ( su ch as 20 18 ) t ha t , if maint ain ed in su bse qu en t imple men t at io n p er io ds , wo uld resu l t in ach i evi ng e sti mated n atural cond i tions by the y ear 20 64. F or exa

m ple, f or an e astern Cl ass I area f

or which the 20% worst vi si

bi li ty basel in e condi tion i s 29 dv

and the esti

ma ted natural condi

tion i s 11 dv , t he r at e o f im pr ove ment t hat t he St at e must analyze fo r e st ablishing the 2018 progress goal i s equal to 18 dv (i.e., the di ff

erence b etween current and esti ma ted natural condi tions) di vi ded by 60 ye ars (i.e., 2004 to 2064), whi ch equals 0.3 dv

per yea r. Carried out over 14 yea

rs (i.e., 2004 to 2018) , this rate of i mprovem ent would l

ead to a reduct ion i

n the 20% worst average val

ue by 4.2 dv

.Guidance f or Tracking Progress Under the Regional Haze Rule

1 - 7 For t hi s exam

ple, the rate of im

pro vem ent is cal culated as:

or,

Figure 1-1 Exam

ple of m ethod for d eterm

inin g Man datory Federa l Class I area

rate of progress to be analyz ed in SIP devel

opm ent process ( a HI va lues f or 2 004 a re based on 2001 -20 04 d at a, e

tc. ) and, c arri ed out over 14 y ears, this rate would ach

i eve an i m provem ent on the worst day s of:

T he St at e mu st de mo nst r at e in t he SI P w he t he rit find s t ha t t his r at e o f impr o ve men t is reasonable or not , t akin

g in to consideration the relevant statu to ry f acto rs ( see next question )

. I f it finds t hat t his rat e is no t re aso nable, t he St at e sha ll evaluat e alt er nat ive rat es o f pro gr ess a nd i n cl ude a demon strati

on su pp orti n g i ts f i n di n g th at a n al ter n ate ra te is rea son

ab l e. In order toGuidance f or Tracking Progress Under the Regional Haze Rule

7 See CAA se

ction 169A (g ). 1 - 8 determi ne the 2004-2018 progress rate for these anal ys es, the State will n

eed to calculate 2000- 2004 b asel

i ne c ondi tions i n ac cordance

wi th thi s gui danc e docum

ent an d use s eparate EPA guidance f

or est im ating Natural Visi

bili ty Conditions. 1.9 What other factors s hould be considered in devel oping Class I ar

ea progress goals ? Other im port ant is sues to be considered in devel oping C lass I area progress goals i ncl ude the reasonabl

e progress factors in

the CAA , consultation wi th ot her States, Tribes an d Federal lan d ma na ge r s, an d e miss io n r ed uc t io ns d ue t o o t he rCle an AirAc t pr o gr ams . T he r ea so nable progres s f actors 7 to consi der i

n dev elopin g any progress goal

are: - the costs o f com

pli ance; - the tim e neces sary

for compl

ia nce; - t he ene rg y and no n-a ir qu ality enviro nmenta l im pac t s o f co mpliance; and - the remain

in g useful li fe of an y ex isti ng source subject to such requirem ents. In thi s context, non-air qual ity env ironm ental im pacts mi ght in cl ude eff ects on aquatic, terrestrial or materials dam

aged from

acidic deposition, eutro phication of coastal estuaries f

rom ni tro gen depos i ti on, ch an ge s i n th e dep osi ti on of toxi c tra cemetal s or

orga ni cstha t may res ul t f rom emissions ch

anges. The EPA plans to develop additional guidance on how to address t hese f actors i n the goal -setti ng process . Stat es with m

andato ry Federal

Class I areas are r equired to develop Class I area pro gress goal s an d con sul t wi th other States i n de ve l opi ng C l ass I area progres s goal

s an d long-term strate gi es to m eet th es e g oal

s. If on e S tate i s rea son ab l y an ti ci pa ted to ca us e or con tri b ute to v i si b i l i ty i m pai rm en t i n a C l as s I area l oca ted i n an oth er Sta te, th e two Sta

tes are req ui re d to cons ul t wi th one another on

the dev elopmen

t of progre ss g oal s f

or the af f ected C l ass

I area

. Fur t her mor e, t hese St at es must include s t ra t egies in their SI Ps t hat add re ss t heir r esp ect ive co nt ribut ions t o t he haz e in the affect ed C lass I ar ea. A St at e ca n t ake pr ojec t ed e missions red uc ti ons f rom othe r Sta tesi nto a cc oun t i n s etti ng sp ec i f i c C l as s Iare a g oals. Thi s c ons ul tation pr oc ess is e ssent ial becau se o f the re gio nal nat ur e o f the haze pr oblem. The EP A sup po rt s t he regional pla nni ng organi zation process currentl

y un der way to im ple me nt the regional

haze pr og ra m. We exp ect t hat much o f the co nsult at ion, st ra t egy de velop ment, app or t ionment demo nst ra t ions, and t echnica l do cument at ion nee ded for SI Ps o f par t icipat ing St at es w ill be faci li tat ed and developed t hrough t he RPO process.Guidance f or Tracking Progress Under the Regional Haze Rule

1 - 9 In devel oping progress goal s, the regional haze rul e al so requires i

n paragraph 51.308 (d) (1) (vi) that States must take in to account any

em is sion reduction strategies i n pl ace or on the way in order t o meet other Clean Ai r Act requirem

ents. For exam

ple , emission reduction strategies (e.g., strategie s to att ai

n the PM 2.5 and ozone NAA

QS and n ational mobi le source meas

ures such as t he T ier I I o r he avy dut y diesel re gulat ions) implemented in the S t at e and /o r in re gio ns co nt ribut ing t o visibility im pair ment in t he St at e’s C lass I ar eas sho uld be t ake n into acc ou nt by the Stat e, as i

t develops Clas s I area progress goals f or regional

haze. Progress goals f

or regional h az e c er tai n l y ca n n ot b e a n y l es s th an th e l ev el of v i si b i l i ty i m prov em en t ex pe cte d d ue to im plem entation o f em

issi on reduct ion m

easures for o ther pr ogr ams. 1.10 Wo uld E PA a ccept a progress goal providing

for a r educe d ra

te of visi bil ity degr adation? Se ct io n 1 69 A ( a) ( 4) an d o t he rsu bse ct io ns o f t he Cle an AirAc t ca ll fo rr ea so nable progres s "towar

d m eeti ng th e nati onal goal " of el i m i na tin g m an-m ade i m pai rmen t of v i si bi l i ty. Since a ny pro gr ess g oa l calling for d egr ada t ion o f visibi lity, eve n at a mod est ra t e, wo uld no t be pr og re ss t ow ar d t he go al, it is unlikely that EP A co uld p ro po se t o a ppr ove any demo nst ra t ions t hat pur po rt t o s how furt her visibi lity deg ra dat ion as re aso nable pr og re ss, (e .g ., in situa t ions where v is ibil ity would be expected to degrade, and such projec ted degradations would b e l essen ed but n ot reversed

thru pr oposed e m i ssi on con trol strategies). 1.11 Wh at are the regional haze rule requirements for progress reviews and future SIP revisions? Afte r t he initial SI Ps a re app ro ved, St at es w ill co nduc t for mal pro gr ess r eviews , in t he f orm of a SIP revision, ev

ery 5 y ears f rom th e date of SIP su bm i ttal (e .g., i

n 20 13 if the i ni tia l SIP i s s ub m i tted i n 20 08 ). P rogre ss

wi l l b e rev i ew ed f or e ach Cl as s I area b y com pa ri n g “ cu rre n t” condi tions b ased on the m

ost recent 5 co nsecuti

ve y ears of data to t he 2000-2004 bas elin e val ue to determi

ne wh ether air qual

ity im provemen ts are consis

tent with the progress goals e stablis hed i n th e S IP. Pro gr es s rev

i ew s i n 20 18 an d b ey on d sh al l also c om pa reth e cur re n t v i si b i l i ty condi tions to vis ibil

ity condi tions 5 y ears prior, and to the 2000-2004 basel in e val ue. In each 5- year r eview, t he St at e will also c heck pr og re ss in t er ms of emissio ns re duc t ions t o d et er mine whet her emissions r edu ct ions mea sur es c ont ained in t he plan ha ve o ccu rr ed in a t imely and ef f ecti ve man ner. I f pr o gr es s is no t co nsis t en t wit h t he visib ilit y and emis sio n r ed uc t io n g o als es t ab lishe d in th e pre v i ous

SIP , the S tate

m ust ev al ua te th e rea son f or l ack of progres s a

n d ta ke an y appropri ate acti on . If th e l ack of progres s is pri

mari l y du e to e m i ss i on s f rom wi th i n th e S tate , then

th e S tate mus t revis e i ts im ple me ntation plan wi

thin 1 ye ar to in

cl ude addi tional me asures to make progres s. If

th e l ack of progres s is pri

mari l y du e to e m i ss i on s f rom oth er Sta tes , then th e S tateGuidance f or Tracking Progress Under the Regional Haze Rule

8 64 Fed era l Reg ist er35746 (Thursday, July 1, 1999). 1 - 10 m ust rei ni tia te the re gional

plan ni ng process

to addres s thi

s prob l em i n the nex t ma j or SIP revi sion (e.g ., i

n 20 18). If

the State f i nds that i ntern ati onal em i ssi ons s ources

are re spon si

bl e f or a substantial

in crease in em

issi ons in any Class I area o r causing a def

ici ency in vi sibil ity progress, t he St at e must submit a t echnica l demons t ra t ion t o E PA in sup po rt of it s finding. S imi larly, t he Stat e should subm

it a techn ic al dem onstration if

the Stat e fi

nds that unusua

l e ven ts (e.g., la rge wil dfi res), have af

fected v is ibil ity progress during the 5-y

ear period. 8 Giv en t ha t pr o gr es s is deter m i n ed b as ed up on l ong- ter m av erag i n g, t h e E PA b el i ev es th at i t i s u n l i ke l y th at s uch ev en ts will have a significant effect in most cas es. See Sec t ion 3 .1 0 r ega rd ing t re at ment o f ou t liers and ot her data asso ciated with unusual events. Stat es will

be requi red to conduct a comprehensi ve SIP revision in

2018 and ev

ery 10 years there af ter. Thi s proce ss w

i l l i nv olv e re-e va l uati ng r ates of progres s f

or each mandatory Federal Cl

ass I area within

the St ate and est abl

ish in g new vi sibil

ity i mprovemen

t go als f or t hese areas. Usi

ng the previ

ous exam ple , suppose that t he eastern C lass I area m ade onl y 2 dv of t he pla nne d 4.2 dv

of i mprovem ent on the worst days (e.g., from 29 to 27 dv ) by 201 8. I f the l ac k of progress is due to plan

ned em is sion reductions that were not im ple me nted or were inef

fecti ve, t hen t he r evised SI P must include r evised emission r edu ct ion meas ur es ne ede d t o mee t t he origi nal progress goal f

or 2028 illus

trat ed by Figure 1-1. 8 Thi s corresponds to 3 dv per 10 years plus the 2.2 dv

not achieved durin

g the previous im

plem entation period. The revised SIP must also i ncl ude revised em

issi on reduct ion m

easures needed to meet the new Class I area pr ogr ess goals. 1.12 What are the majo r anal ytical tasks involved in addressing

specif ic re quire ments in the regional haze rule regarding tracking progress? As no t ed a bove , t he first st ep in t ra cking p ro gr ess fo r t he r egio nal haze ru le is co llecting and anal yzi ng fi lter sampl es from IMPROVE netwo rk sites. In or der t o identif y the 20% most im paired and 20% least im

paired days

in a part icul ar year, a haze in

dex val ue (in deci

view units) needs to be determi

ned f or each 24-hour sam

ple period, and then

these val ues sh ould be sorted from hi ghest to lowest. Averages (i n deci views) for that yea

r can be calcul ated for HI val

ues ass oci ated wi

th the 20% m ost i m pai red an d 20% l east im pai red da ys. The ave rage HI val

ues f or t he 20% m

ost im pai red and 20% least im

pai red days in each year s hou ld t hen be a ver age d fo r t he five co nsec ut ive years 200 0- 200 4 t o d efine base line con di ti ons . Si m i l arl y , wh en ch ec ki ng m i d-c ours e p rogres s ( e.g ., i n 2 013 ), or f

or ca l cul ati on of current conditions f

or future SIPs, t he an

nual average v

al ues f or t he 20% m

ost im pai red and 20% least im paired days

wil l b e averaged for t he 5 m

ost recent years of data available, and then tho seGuidance f or Tracking Progress Under the Regional Haze Rule

1 - 11 val ues should be compared to t he basel in e val ues for that site. For mandato ry Federal Class I ar eas wit h multiple r epr ese nt at ive monit or s, s epa ra t e visibil ity values and p ro gr ess g oa ls sho uld be establ is hed f or each si te representin

g the area. In order to faci

li tate t hi s trackin

g process, Stat es hav

in g one or more man

dator y F ederal Cl as s I area s a rere qui re d b y th e r ul e to e sta b l i sh, a n d u pdate as n ec es sa ry, th re e i m por tan t vi si bi li ty param eters for the 20% best and 20% worst vis ibil ity days at each m

andatory Fede

ral Cl ass I area wi

thin the Stat e:

C Basel

ine conditions

- Baseli ne conditions represent vis ibil ity f or t he 20% best and wor st day s f or the i ni tia l 5-y ear pe ri od of the regi

onal ha ze progr am . Bas el

i ne cond i tions are cal cul ated b ase d on m

oni tored data c oll

ected d uri ng th e 200 0-200 4 peri

od.

C Curr

ent conditions

- Cu rr en t co nd it io ns f

o rt he be st an d w o r st da ys a r e c alc ula t ed fr o m a 5-y ear a verage ( i n de ci vi ews ), ba sed

on the most recent 5-y

ear b l ock of

moni tored data. Calcul ations of

current conditions f

or each m andatory Fede

ral C lass I area are revised every 5 ye ars at the tim

e of each periodic SIP revi sion and would be used to eval uate: ( 1) t he amo un t o f pr o gr es s ma de in r ela t io n t o t he r ea so nable pro gre ss go als est ablished for t hat mandat or y Federa l Class I are a; (2) t he am

ount of prog ress made si

nce the last 5-year progr ess review, and (3 ) t he amo unt of p ro gr ess mad e fro m the ba seline pe rio d o f the program (2000 -2004 ).

C Estim ate of natur al visibility c onditions- Th e C A A sets a na ti ona l vi si bi l i ty goal of “remed ying existing impair ment a nd pr event ing fut ur e impairment .” Fo llowing fro m the nationa l goal , the regional

haze rul e calls for i mprovem ents on the worst days to remedy exi sti ng i m pai rmen t, and no de grada

tion on the be st day s to preven

t futur e i m pai rmen t. Thu s, t he ult imate g oa l of t he r egio nal haze pr og ra m is “natu ra l cond itio ns,” or t he vi si bi li ty condi tions that would b e experi enced i n the ab sence of

hum an-caused im pairm ent. Under t he haze rule, natur al condi tions need to be estim

ated for the 20% best an d 2 0% wor st d

ay s. Thes e e sti

mate s s h oul d r epre se n t l ong- ter m av erag es , a n al ogou s to the 5 -year a

verages use d to determ

i ne ba sel i ne cond i tions an d curre nt con di tions. A separate guidan

ce documen

t pro vi des a m ethodology f

or developi

ng esti ma tes of natural vi sibil ity condi tions for each Class

I area. Pot ential

appro aches f

or r efi ni ng those esti mates a re also di scu sse d i

n that docum

en t.Guidance f or Tracking Progress Under the Regional Haze Rule

1 - 12 1. 13 W ha t a ir q ua lit y mo ni to rin g i s un der w ay t o su pp ort tra cki ng prog ress t owa rd improving visibil

ity conditions under the regional haze rule? The IMPROVE visi

bi li ty m onitorin g program was i

ni tiated in two mandatory Federal Cl ass I areas i

n 1986 an d grew to in

cl ude 30 si tes in 1988. The IMPROVE program has been coord i na ted an d f un de d th roug h a coop era ti ve m ul ti -org an iza ti ona l approa ch , wi th p arti ci pa ti on by EPA, t he Fed er al land manag er s (D epa rt ment o f Agricu ltu re , U .S . Fo re st Ser vice; De par t ment of In teri or, Nati onal

Park Se rvi ce, F i sh & W i l dli f e Serv i ce, B ureau

of L and Ma

na gem en t), National Oceani c and A tmospheri c Adm in is trat ion (NOA

A), and m ulti-state o rgani

zations s uch as the Mi d-A tl an ti c R eg i ona l A i r M an ag em en t As soc i ati

on (MA RA MA ), N orth ea st S tate s f

or Co o r din at ed AirUs e M an ag eme nt ( NE SC AU M) , We st er n S t at es AirRe so ur ce s C o un cil (WES TAR

), an d The State an d Terri toria l Ai r Pol l uti on Progra

m Ad m i nistrators (STA

PPA). The IMP ROV E mo nito ring p ro t oc ols includ e ae ro so l monito ring o f par t iculat e mat t er mass and its c hemical co mpo nent s, o pt ical monit or ing o f li ght sca t t er ing o r o ver all li ght ext inctio n, a nd photographi

c m oni torin g. Som e but not al

l si tes i nc l ude on-si te m oni torin g of relati ve hum i di ty. T hr o ug h c ale nd ar yea r19 99 , t he I MP RO VE sa mpling sc he du le w as o ne 24

- ho ur ae r o so l sa mple twice a week, o n Wedn

esdays an d Sat urdays. In 1 999, EPA

provi ded f und i ng f or a si gni f i can t exp an sion of

the IM PROV E network. Ful ly depl oyed, the network in cl udes aerosol m

onitorin g at a to tal of 110 m

andatory Fede

ral Cl ass I area si

tes. The new si

tes in the expan

ded network were selec

ted in order to pro vi

de “represen tative” m onitorin g for all b ut o ne of 156 m

andatory Fede

ral C lass I areas. New IM PROVE si

tesbe ga n c om i ng on- l i ne i n 1 999 . Mos

t si teswere f ul l y depl oyed by the en d of 2000, a l though a f ew di d not com

e onl i ne unti l 2001 ( see

Tab l e 1-1). In the expa

nded IMPROVE ne twork , one 2 4-h

our s am ple is c ol l ec ted

every 3 da y s, c ons i stent w

i th th e s am pl i ng sche dul e f or the Federal Reference Method for the PM- 2.5 National Am bi en t Ai r Qual i ty S tandard (N

AA QS). Under thi s schedul e, a to tal of 122 aerosol s am ple s can b e coll

ected for each IMPROVE si te each year. Most of

the n ew IM PROV E si tes i nc l ude aerosol

moni torin g onl y . Wi th l i m i ted network fun ds, priority

was gi ven to aerosol m

onitorin g with c hem ic al composi tion ana ly si s of colle cted pa rti cul ate matte r s am pl es . Th i s a l l ows th e S tate s, Tri

b es an d F ederal l an d m an ag er s to ev

al ua te chang es in visibil

ity impairment and t o id ent ify t he pr incipal type s o f emission so ur ces co nt ribut ing t o t he visibil

ity impairment t her e. Figur e 1- 2 sho ws t he loc at ions o f the monit or ing site s in the expa nded IMP ROV E ne t wo rk . I t sho uld be no t ed t hat so me St at es, Tr ibes, a nd Fed er al Land Man agers ha ve f und ed the opera

tion of a ddi tion al IMPR OVE s i tes to repre sen

t ma nda tory Federal Cl ass I areas or other areas of the country. At the tim e of publ ic ation of this guidelin

e, there are ap pro xi

mately 50 such additional

sites known as IMPROVE pro to col si tes.Guidance f or Tracking Progress Under the Regional Haze Rule

1 - 13 1.14 Why haven’t particulate matter monitors been deployed at all mandatory Feder

al Class I areas? Bec aus e o f the bro ad s pat ial distr ibut ions o f reg ional haz e, and in o rd er t o u se mo nito ring resources eff

ic ie ntly , EPA determi

ned, i n conj unction w

ith State and Fede

ral l and m anagers, that so me neighbo ring mand at or y Feder al Class I ar eas co uld be r epr ese nt ed by a s ingle monit or ing si te.

Figure

1-2 Expanded

IMPROVE Visibility Monitorin g Network (Site 106 rep resen

ts the US Virgin

Island s)

In a ddit ion, one isolat ed mand at or y Feder al Class I ar ea ( Ber ing Se a, an uninhabit ed a nd i n f re qu en tl y v i si ted i sl an d 2 00m i l es f rom th e c oast of

A l aska ), was con si dere d to b e s o remote f rom e l ectrical

power a nd p eople tha

t it woul d be i m practi cal to coll ect routi ne aerosol sam ples. T he E PA co nsu lt ed wit h t he St at es in o r de rt o de sig n a ne t wo rk t ha t wa s a s r ep r es en t at ive o f allGuidance f or Tracking Progress Under the Regional Haze Rule

1 - 14 mandat or y Feder al Class I ar eas as p os sible. All mandat or y Feder al Class I ar eas (e xcep t Ber ing Sea ) a re cur re nt ly cover ed by at least one IMP ROV E mo nito ring sit e, and s ome a re co ver ed by ad dit io na l IM PR OV E pr o t o co l sit es . I f ch an ge s a r e ma de in t he sit es wh ich co ve rsp ec ific mandat or y Feder al Class I ar eas , a ll the ca lculat ions d iscuss ed in t his do cument sho uld be performed for each site the Stat e chose in the SIP’s moni to ring strategy to represent t he Class I area. 1. 15 D oes th is g ui da nce pert ai n t o t racki ng of C lass I are a ch an ges in vi sib ili ty by wes te rn States submitting regional haze plans under Sec tion 51.309 of the regional haz e rule? Ye s, an y Sta te wi th a m an da tory Fe deral Cl as s I area sh oul d track ch an

ge s i n v i si b i l i ty accordin g to this guida nce, regardless of wh

ether the Stat e has s

ubm itted a regional

haze im ple me ntation plan un

der Section 51.308 or Section 51.309. Western States (and Tribe s as appropri ate) tha t are i m plem en tin g Section 51.309to im

prove ai r qual i ty a t the 16 m

andatory Federal Cl

ass I areas on t he Colorado Plateau, will not be requ ired to set pro gress goals for these areas f or t he 2003-2018 period. But they wil l b e required to track pro gress i n these 16 areas every fi ve y ears accordin

g to Section 51.309 (d) (10). Pro gress revi ews and i mpl em entation pl

an re visions a re re quir ed in 20 08, 201 3, and 2 018 . Fo r e ach mand at or y Feder al Class I ar ea in t he Stat e, the progress revie

w should in

cl ude an ass essm

ent of the f

oll owing:

C Current visi

bili ty conditions (i .e., the most rec ent 5-year average) for t he m ost im paired and least impai

red days;

C Th e di f

f ere nc e b etw een c

urren t con di ti ons an d b as el i ne con di ti ons (20 00- 200 4) f

or most im paired and least impai

red days;

C The chang e in visibi lity co ndit ions o ver t he pa st 5 year s for t he mos t impaired and least im paired days ;

C Th e cha

ng e i n v i si bi l i ty con di ti ons ascom pa red to the State ’s proj ec ti on of visi bi l i ty i m prove men t requi red i n Se cti on 51.3 09 (d) (2 ). 1.16 Does t his guid ance on Tracking Progress address all of the r equir ed el ements

of the 5-year progr

ess reviews re quired under the regional haze r ule? No, th e p ri mary f ocu s of thi s docu men t i s to des cri

be a re com men de d m eth odol ogy f or calcu lating t ot al light ext inctio n values for a manda t or y Feder al Class I ar ea, base d o n ambient m oni tori n g data . Th

e docu men t also prov

i de s b as i c g

ui da n ce on th e ty pe s of v i si b i l i ty as se ssmen

ts n ee de d a s p ar

t of th e 5 -y ea r p rogre ss re v i ew s. How ev

er , the S tate

wi l l n ee d to eval ua te b oth a m bi en t moni tori ng i nf orm ati on a nd the ef f ec ti ve ne ss of em i ss i on r ed uc ti onGuidance f or Tracking Progress Under the Regional Haze Rule

1 - 15 measures i

n the 5-year progr ess revi ews. The EPA will dev elop guidance f

or t he f ull pro gress revi ew proc ess

at a later da

te. 1.17 Wh at inf

or mati on isprovided

in the r est o f this

guidan ce do cum ent? The rem ai nder of this documen

t pro vi des guidance on procedures to measure regi onal haze and t ra ck p ro gr ess t ow ar ds mee t ing t he nat ional visibili t y goa ls. S ect ion 2 of t his do cument pro vides a summ

ary step-by-step description of recommen ded calculations for tr acking progress in reg ional haz e impro vement . S ect ion 3 elabo ra t es o n t hat pr oc ess a nd pr ese nt s eq uat ions a nd supporting i

nf ormation n

eeded to perform the cal

cul ations. Section 4 di

scusses the fi nal com parisons use d f or tracki ng progress

i n v i si bi l i ty. A n appen di x i s i n cl uded i n th i s d ocu men t wh i ch l i sts th e m on th l y re l ati v e h um i di ty co rr ect ion fact or s for eac h mandat or y Feder al Class I ar ea. The se fac t or s ar e us ed fo r c alculat ing l i ght exti nction at each m

andatory Fed eral Class I area

.Guidance f or Tracking Progress Under the Regional Haze Rule

2 - 1 2. SUM MARY OF TRACK ING PROGRESS CA LCULATION PROCEDURES 2.1 What is the

pur pose of th is s ectio n of t he gui dance docum ent? Th i s s ecti on of th e g ui da n ce docum en t de scri b es th e proc es s th

at c oul d b e c ar ried out to t ra ck p ro gr ess in impro ving visibil ity in mandat or y Feder al Class I ar eas , u sing da t a fro m the IMP ROV E mo nito ring sit es. The re quir ed c alculat ion p ro ced ur es sho uld be c ar ried ou t in a nationa ll y c onsi stent man

ner i n order to faci

li tate inter-comparabi

li ty am ong Stat es and n

ational report in g by EPA. The IMPROVE program wi ll perform the se cal

cul ations f

or all IMPROVE an d I MP RO VEprotoc ol

moni tori n g s i tes an d p rov i de th e res ul ts th rough th e I MP RO VEwe

b si te at: ht t p: // vista .c ira. co lost at e. edu /impro ve

as a ser vice for t hos e ag encies w ho d o no t wish t o implement t he pr oc ess t hemselves. The IMPR OVE progra

m wil l en sure that al l data an d cal cul ati ons a re av ail ab l e i n a tim el y man ner, cons i sten t wi th SIP s chedul

es a nd w i l l reduc e the

bur den on States whi ch do not wi sh

to perf orm t he ir o wn ca lcu lat io ns. Da t a p r o vid ed t o t he we b sit e fr o m t he I MP RO VE mo nit o r ing effo rt s w ill b e u se d to c al

cul ate l i gh t ex ti n cti on an d dec i v i ew v al ue s, 5- yea

r a v erag e res

ul ts, an d v i si b i l i ty t r en ds at all I MP RO VE sit es . T his c en t r aliz ed ap pr o ac h w ill as su r e c o nsis t en t t r ea t men t o f all comp osi te components of

PM 2.5 , missi

ng data, data substitution, an d averagi ng, and wi

ll reduce t he effo rt need ed fr om Fe der al, S t at e, Tr ibes, a nd o t her inter est ed p ar t ies o r a genc ies do ing assess me nts. The cal

cul ations sh

ould be done accordin

g to the equations an

d procedures presented i

n Section 3 of

this guida nce docum

ent, which are also detailed on the IMPROVE web si te. A l l moni tori n g data wi l l b e acc es si

b l e f or re v i ew b y th e res ponsi b l e a gen ci es so t h at data f l aggi ng or a dj ustm en ts f or spec i al occurre nc es or othe

r f actors c an

be i m plem en ted ef f ecti ve l y . Howev er, thi s se rvi ce i n n o way usur ps or rel i ev es i ndi vi dual States f rom th ei r regul atory res pon si bi l i ty to as se ss the ch an gei n v i si bi l i ty i n e ach m an da tory Fe deral Cl as s Iare a. The

ai m of this approach is to pr omot e consistency in the calculation pro cedures whil e maki ng the pro cess easier for those Stat es, Trib es, and other parties or agenci es, who choose to do their own assessm ents. 2.2 Wha t is the seq uence of steps ne eded to ca lculate data for tracking progress? Figur e 2- 1 su mmarizes t he st ep- by-st ep p ro ces s for asse ssing visibili t y tr ends . T he process b egi

ns w i th the trans fe

r of qual i ty-as sured, State-revi

ewed, IMPR

OVE PM 2.5 monit or ing da ta to t h e I MP RO VEwe

b si te. Then th e f oll owi n g s eq uen ce of ste pswi l l b e c ar ried out on da ta from each IMPROVE si

te, leadi ng to t he data neede d for calcul ation of trends i n vi si bi li ty at each si te.Guidance f or Tracking Progress Under the Regional Haze Rule

2 - 2 Step 1 - Asse mble Compo site C ompon ents o f PM 2.5 Seve ral of the p artic l e com

ponen ts need ed to asses s PM 2.5 li

ght extin ction are termed composi te components. Such variable s m ay be a com posite of m

ulti ple me asured speci

es, or may b e deri v ed f rom mea su re d s pe ci es b y appropri ate

con v er si on f actors . C om

pos i te c om pon en ts include Fine S oil, w hich is the sum o f sever al cru st al element s; Or ganic C ar bon ( OC) , w hich is the su m of f our m ea su red OCf racti ons an d the p y rol y ze d org an i cs(OP ); Li

gh t Ab sor bi ng Ca rb on (LAC ), which is t he su m of t hre e measu re d element al car bon ( EC ) fra ct ions les s t he OP frac t ion; Coarse Mass, wh

i ch is the di

ff erenc e between m

easure d PM 10 and PM 2.5 mass; Sul

fate, whi ch may b e dete rm i n ed b as ed up on ei th er mea su re men ts o f pa rti cul ate su l f ur or of su l f ate i on , w i th correc ti on f

or as soc i ate d a

m moni um i on;an d N i trate , wh i ch i s c al cul ate d a s th

e m as s of ammonium nitr at e. The first st ep in t he da t a pr oc ess s hou ld be t o c omp lete t hese co mpo nent vari abl es, usi ng a procedure suc

h as that sum mari zed b elow: Note: Al

l of these recomm

ended calcul ations are perf

ormed by the IMPROVE program and are m ade avai la ble on the IMPROVE websi te.Guidance f or Tracking Progress Under the Regional Haze Rule

2 - 3 Figure 2-1 Summary of Step-by-Step Process for Track ing Progress Calc ulationsGuidance f or Tracking Progress Under the Regional Haze Rule

2 - 4 Fi ne Soi l i s ca l cul ated b y sum m i ng th e f i ve crustal elem en ts (Al , Si , Ca, F e, an

d Ti ), acc ou nt ing for t heir p re senc e as oxid es ( e. g. , Al 2 O 3 ), and appl yi ng adj ustmen

t factors t o cor rect for fact or s su ch as non- so il pot assium, and t he pr ese nce o f ot her so il compo nent s. I f any of t he five pr imar y cr us t al e leme nt s is be lo w t he minimum d et ec t io n limit , it is a ss ign ed a v alu e o f ha lf th e m i n i m um detecti on l i m i t. If an y of th e f i v e cru sta l el em en ts i s m i ss i n g f rom th e data set, general ly all f iv e will be m is si ng be cause of the an

al ytical me thod used for these elem

ents. In that case the Fi

ne Soil data are fl

agged as m

is si ng. Or ganic C ar bon is c alculat ed by su mmi ng t he five OC fr act ions a fte r e ach ha s bee n blank co rr ect ed. If t he r esu ltant sum is neg at ive, a value o f zer o is a ssigned for Or ganic C ar bon. Light Abso rbing C ar bon is c alculat ed in a s imi lar w ay, by first summing the t hre e blank correct ed el em

ental carbon f ractions, and s

ubtracting the OP f

raction. If the resul

t after subt ra ct ion is neg at ive, a value o f zer o is a ssigned for Light Abso rbing C ar bon. Coarse Mass is cal

culated by

subtractin

g the PM2.5 val

ue f rom the correspondi

ng PM 10 val ue. If the result after blank subtraction is negativ e, a value of zero is assi

gned for Coarse Mass. Sulf

ate is pref erabl y c al cul ated from the parti cul ate sulf ur determi

nation. If the sulfur val ue i s bel ow the mi ni mum detection lim

it, a val ue of hal f the m in im um de tection li mi t is ass ign ed for sul fa te but i f that anal

y si s i s m i ssi ng, the n the i onic SO 4 = de t er mined by io n c hr o mat o gr ap hy is used. The tot al

mass of sul

fate presen

t is then calcul ated assum

in g it exi sts in the aerosol as am moni um s ulf ate [(NH 4 ) 2 SO 4 ]. N i

trate i s c al cul ate d di rectl y f rom the mea su red ni trate i on values , w ith a fa ct or of 1 .2 9 ap plied t o a cco unt for asso ciat ed a mmonium ion. B ot h Su lfate and Ni trate m eas urem en ts are bl an

k corrected. If

the re sul t is ne gati ve f or ei ther m eas urem en t, a va lu e o f z er o is a ss ig ne d f o rS ul fa t e o rNit r at e a cc o r di ng ly. Step 2 - Assess Missing Var iables On ce th e c al cul ati on s ou tli n ed i n th e f i rs t ste p a b ov e h av e b een com pl ete d, t h e en ti reda ta set should be revi ewed to iden tify any missin g data for the composite co mponents. Those variabl es f or which one or more results are m is si ng sh ould be addressed as i

n the f oll owing s teps to fi l l i n the m i ssi ng d ata wi th l ong-term av erage va l ues . Day s f or whi ch no da ta at al l are availab le are not incl

uded in an

y f urt her calcul

ations.Guidance f or Tracking Progress Under the Regional Haze Rule

2 - 5 Step 3 - Determine Quarter ly Median Concentrations for Missing Variables For each va

riable for whi ch one or more data points were f ound mi ssi ng i n Step 2, qua rter l y medi an va l ue s a re c al cul ate d f or th e curren

t yea r an d e ach of the pre vi ous4 y ea rs of data. F or each

cal endar quarter (i .e., Ja

nua ry-Marc h, A pril -Jun e, Ju l y-Septem ber, Octobe

rDec ember) , t he ca lculat ed med ian values for t he co rr esp ond ing co mplet e qu ar t er s fro m the current year an

d the previous 4 years a

re then averaged to o btain an av erage of up to fi

ve m edi an v al ue s. A l l da ta f or e ach v ari ab l e i n th e data set are u se d to c al

cul ate th e m ed i ans, i n cl udi n g data that hav e b een

set to zero (e.g ., f

or Organ i c Ca rbon , Li ght A bs orbi ng C arb on), an

d those that are base d pa rt ly on assig ned no n-d et ect values (e .g ., Fine So il). T he r esu lting a ver age s o f the qua rt er ly m

edian c onc ent ra t ions a re t hen us ed in su bseq uent st eps t o d et er mine whet her missing data can be replaced with the average val ues. In th i s con text, a c omp l ete qua

rter i s de f i ne d asone i

n w hi ch data f or a spe cies a

re available for at least 50% of t he sa mpling days and which has no mo re t han 10 co nsec ut ive sa mp ling da ys w it h d at a mis sin g f o rt ha t sp ec ies

. Wit h a sa mp ling sc he du le o f e ve ry t hir d d ay, thi s req ui rem en t me an s tha

t no m ore than one c onse cuti

ve month of data ca n b e m i ssi ng. Quarters whi ch do not meet these cri teria sh ould not be used to calcul ate the quarterly a

verage val ues. In carry

in g out this step, care must be taken tha t t he sam pli ng an d anal ytical procedures are uniform

throughout the data period bei ng consi dered. For exam

ple , it m ust be determi

ned that moni to rs have not been m

oved, that filter m

ask si zes hav e not been ch

anged, etc. Such de t er minat io ns r eq uir e a ca r efu l re vie w o f t he hist o ry o f an y sit ing ch an ge s a s w ell a s c ha ng es in th e m oni tori n g p roc ed ur es f or th e s i te. If si ti n g or proce du ral ch an ge s a remade, i t i s i m por tan t to establ i sh that com parabi l i ty i n the m oni torin g data h as b een mai ntai ne d through

out the ch anges . Also see Section 4.5. Step 4 - Obtain f(RH) Values Cal cul ati ons of l i ght exti nction and dec i vi ew v al uesrequi re f(RH) fact or s, w hich adjus t t he light sc at t er ing effect of hygr os co pic ae ro so l spec ies t o a cco unt for par t icle gr ow t h cau sed by wat er vapo r in t he at mosp her e. It is rec ommende d t hat t he f(RH) fact or s us ed be site -sp ecific and be as soc i ate d w i

th m onth l y , ra the r than , e. g., s ea son

al or an nu al ti me f ram es . A tab l e of r ec o mmen de d m o nt hly f(RH) va lue s fo rt he Cla ss I ar ea s is inc lud ed as Ap pe nd ix A o f t his guida nce docum

ent. The appropriate f(RH) val ues are used wi

th moni to rin g data from eac

h IMPROVE site in al

l v isi bili ty calcul ations.Guidance f or Tracking Progress Under the Regional Haze Rule

2 - 6 Step 5 - Evaluate Feasibilit y of Substi tutin g Average Values The re aso n t he gu idance includes a pr oc ess fo r t est ing t he feas ibil ity o f subst itu t ing av er ag e s pe cie s c o nc en t r at io n va lue s fo rmiss ing va lue s is t o max imize t he nu mbe ro f sa mple periods upon wh

ic h ha ze trends can b e assess ed wi thout signifi

cantl y de gradin

g the haze cal cul ati on. The al

terna tiv e, a rul e tha t val i d data f or each spe cies m

ust b e av ail ab l e f or eve ry sam ple period, both tends to reduce t he n umb er of val

id h aze cal cul ations an

d in extreme c ases can resul t in the i ntroduct ion of

substantial

biases i n an nual average worst-case calcul ated haze values . Fo r e xample in the mid-19 90s t he ea st er n Unit ed S t at es su mmert ime IMP ROV E fine particulate ni

trat e data were occasional ly in val ida ted as a resul

t o f the s am

ple r’s ny lon f il ter cl ogging, ty

pic ally durin g periods of h

igh sul fate concen

trat ion. Inv

alida ting thes e sam

ple periods wou l d p rod uc e a b i as ed an n ual av erag e of th e w ors t-c as e h

az e c on di ti on s s i n ce su l f ate s c on tri b ute si gn i f i ca ntl y to the ha zei n th e e as tern Un i ted State s d uri ng the su m mer. How ever, su

bs ti tution of an av er ag e n it r at e v alu e fo rt he miss ing nit r at e w o uld av o id t he bia s a nd wo uld no t sig nific an t ly de gra dethe ha zecal cul ati

on b ec au se

su m mer f i ne pa rticul ateni

trate con centr ati ons are m i nor co nt ribut or s t o ha ze in t he ea st er n Unit ed S t at es. The pr oc ess d esc ribed below is an o bject ive approach for determi

ni ng whether a substi

tut ion c an b e m

ade for m is si ng speci es data without sign if ican tly degradi

ng the calcul

ated haze values. In thi s step, li

ght extin ction cal cul ations b

y e quation 8 i

n Section 3 a

re carried out in

two wa y s f or e ach IMPR OVE s i te h av i n g a n y m i ss i n g data : (1 ) u si

n g th e or i gi n al da ta f rom th e p ast 1 to 5 “com ple te” years, as de fi

ned b el ow in Step 7, and (2) by substi tut in g the appropriate average of the quarterly

me dia n concen trat ions determi ned i n Step 3 for the i

ndi vi dual species co ncent ra t ions in t he da t a se t . C omp ar ison o f the t wo set s o f resu lts t hen de t er mines whet her t he aver age of q uar t er ly m

edian c onc ent ra t ions c an be u sed t o fill i n any missing dat a. This st ep in t he overall process requires s everal

steps in itsel f, as des crib ed bel

ow. Fi rst, for a given

IMPROVE site, t he tot al l igh t extinction val

ues ( b ext , se e Se cti

on 3 ) f or al l da y s wi th n o m i ss i ng da ta a re c al cul ate d. Th

i s c al cul ati on i s done asde scri be d i n S ec ti on 3 of this guida nce docum

ent, usin g the appropriate f(RH) f

ac tors a nd the appropriatecal cul ati

ons of t he ind ividu al c o mpo sit e c o mpo nen t s. Th is ca lcu lat io n pr o du ce s a list o f b ext val ues f or t hat por tion of the or igi

nal data set that had no missi ng val ues. The second step i s to recalculate the b ext values for t he sa me sampling da ys, but wit h t he appropri ate av erage of th e qua rterl y medi an va l ues f or a si ngl e sp eci es (f rom S tep 3 ab ove), subs t itu t ed in plac e o f all of the individual values of t hat spe cies. Fo r e xample, t he ave ra ge o f the quarterly me dia n va lue s of sul

fate at a si

te would be sub stituted for the correspo ndi ng i ndi vi dual sul fate va lue s, for all the da

ys from that site wi

th no mi ssi ng data. The b ext val

ues are thenGuidance f or Tracking Progress Under the Regional Haze Rule

2 - 7 cal cul ate d f

or th e re sul

ti ng da ta s et. The

prod uc t of thi s step i s a se con d s et of b ext val ues, corr esponding one-to -one with tho se calcul ated fro m the origi

nal val ues. Ne xt, the se

two s etsof

b ext val ues are compared f

or each sam

ple day on a calendar y

ear basis. If the di

ff erence b etween the 2 nd b ext val ue rela tive to the 1 st b ext

val ue i s less than

10% for at le ast 90% of the sam

ple days, then i

t is acceptab le

to replac e any

mi ssi ng va lue s f or t hat species wi th th e a pp rop riate

av erag e of th e q ua rterl y med i ans f or th at s pe ci es . If th i s cri ter i on i s n ot m et, then an y m i ssi ng v al uesf or that sp eci

es m ust rem ai n m i ssi ng f or that cal

endar y ear. The pr ece ding p ro ces s sho uld be r epe at ed a s nec essa ry for eac h spe cies w ith any missing da t a, o ne a t a t ime, e. g. , p ro du cing a s et o f b ext val ues wi th the average of

the quarterly

me dia n sul f atecon centr ati on s ub sti tuted f or al l i nd i vi dua l sul f ateva l ue s, th en an othe r s et of b ext val ues wi th an av erag e of th e q ua rterl y med i an n i tra te c on cen tra ti on su b sti tute d f or al l i n di v i du al n i tra te valu es , e t c. Ea ch s uc h se t o f b ext val ues i s compared to the origin al set, to ma

ke a j udgme

nt about substi tut ion of averages f

or just one particle species. Note t hat this process is

to be carried out for each c omposi

te species for each y

ear, i.e., producing up to 30 tests for each 5-y ear period, dependi ng on the ex

tent of missi

ng data. It is expe cted that at any giv en IMPROVE si

te, it may be reasonable an

d appro priate to replace m issi ng data with quart erly

medi ans f or so me speci

es, but n ot for others

. In cal cul ating b ext

val ues in this step of the overall process, a value of 10 i nverse me gam eters (i.e., 10/10 6 m, or 10 Mm -1 ) for Rayleigh scatt ering sh

ould be used for all

sites. I nst an ce s in w hic h d at a o n mo r e t ha n o ne ae r o so l co mpo ne nt ar e mis sing in t he sa me sam ple are li kel y to be rare. As a res

ult, the process for dual

substi tut ion i s not presented at l en gth h ere. How ev

er , s ub sti tuti on of two v ari ab l es i n th e s am e s am pl e c oul d b e don e, su

b j ect to ad eq ua t e ju st ifica t io n a nd t es t ing , su ch as in t he su bst it ut io n t es t de sc r ibe d p r ev io us ly. T he sa me acc ept ance cr iter ion o f less t han 10 % d iff er ence in b ext

va l uesi n 90 % of th

e data s houl d app l y . Fo r e xample, cur re nt ly, li ght abso rbing c ar bon a nd o rg anic ca rbo n dat a ar e likely to eithe r be pres en t or missi ng i n the sa me sa m ples b eca use of the com

mon an al y si s m ethod f or thes e sp eci

es. As a res ul t, thi s su bstituti on test c oul d also be

carri ed out f or those two speci

es s i m ul tane ousl y . That is, the quarterl

y m edi an val ues f or bot h speci

es could b e substituted for their i ndi vi dual val ues at a si te, t he b ext val ues could b e calcul ated, and the compari son m ade to assess whether si m ul tane ous rep l acemen

t of m i ssi ng L AC and OC d

ata wi th av erage s i s ap

propriate. Once the sui

tabil ity of replaci ng m is si ng data wi

th medi ans h as been assess ed as descri

bed above, al l m is si ng data for those species m eetin g the acceptance cri

terion sh ould beGuidance f or Tracking Progress Under the Regional Haze Rule

2 - 8 replac ed wi

th the appropriate quarterly average v

al ues, and the b ext

val ues f or t hose sam

ple s sho uld t hen be c alc ula t ed . M issing da t a fo r s pe cie s no t mee t ing t he c rit er io n sho uld be le ft m i ss i ng , an d n o b ext val ues should be cal

culated for t hose sampl

es. Step 6 - Calculate Deciview Val ues In thi s step the b ext

values calcu late d in St ep 5 ar e co nver t ed t o d eciview va lues u sing eq ua ti on 9 i n Se cti on 3. Note th

at th e a pp rop riate

n es s of su b sti tuti n g a v erag es f or m i ss i n g data could j ust as easi

ly be ev al uated in terms of dec iv

ie w val ues, in stead of the b ext

val ues, si nce a differenc e o f 10% in b ext

is equ ivalent t o a differenc e o f app ro ximately 1 de ciview. Tha t is, if the decivi ew val ues calcul ated with substitut ed averages dif fer f rom those o f the origin

al data by less than 1 deci

view for at leas

t 90% o f the s am

ple s, then replacem

ent of m is si ng data wi

th ann ual av erage va l uesi s ap propriate. Otherwise, the m i ssi ng d ata sh oul d rem ai n m i ssi ng. Step 7 - Check Data Completen ess In this step the dat a sets resulting f rom previous steps are r eviewed for co mpl eteness. In order for a year of

data from a s ite to be used to t rack progress in im provin g vi si bi li ty, all f our quarters of that year sh

ould be at least 50% compl

ete, and overall

, the year s

hould b e 75% co mplet e. Tha t is, co mplet e da t a ( including t hat fil led in by subst itu t ion o f aver age s), sho uld be av aila ble fo rat lea st 50 % o f t he sa mpling da ys in e ac h q ua rt er o f t he yea ran d fo r75 % o f all sche duled sampling da ys for t he year . I n add itio n, t her e sho uld be no mor e t han 10 missing sam pli ng d ays i n a row at an

y tim e duri ng th e ca l endar y ear. W i th a s am pli ng s chedul

e of ev ery thi rd day , thi s req ui rem en t me an s tha

t a si te sh oul d not b e out of ope

rati on f or any peri od of m ore than one c onse cuti

ve month d uri ng th e ca l endar y ear. A n n ual da ta s ets meeti n g th es e c om pl ete n es s cri ter i a sh oul d b e u se d i

n su b se qu en t ste psto ca l cul ate 5- yea r a v erag e v i si b i l i ty re su l ts f or tracki n g p rogre ss . Ev

er y atte m pt sh oul d b e m ade to ge t 5 ye ar s o f co mple t e d at a w it hin e ac h 5

- yea rpe r io d, an d E PA ex pe ct s t ha t failu r e t o mee t t his goa l wi l l b e rare. How ev

er , if max i m um da ta rec ov er y i s n ot ac h i ev ed , EP A b el i ev es th at a mini mum of 3 yea rs o f dat a meet ing t hese co mplet enes s re quir ement s is sufficient t o c alculat e t he 5- yea rav er ag es wit hin e ac h 5

- yea rpe r io d. T his r ec o mmend at io n fo rat lea st 3 ye ar s o ut o f 5 is consistent w

i th th e p ol i cy es tab li sh ed i n EPA ’s reg ul ati ons govern i ng moni tori ng an d a na l y sis of PM 2.5 , whi

ch e stabl i she s m i ni m um data requi

rem ents f or PM 2.5 NA

A QS c om pa ri sons. B ec au se

of the close relationshi

ps between v

is ibil ity im pai rmen t and fi ne particl e concentrations, as we ll

as between the regi

onal haze program a

nd ef forts to attain n

ational am bient ai r quali ty standards, we be lieve t ha t simila rda t a c o mple t en es s p o licie s s ho uld ap ply. Du e t o de lays in d ep lo yment , so me of the 110 IMPROVE m

onitorin g si tes wil l h ave n o more than 3 or 4 years of compl ete data at the ti me w he n bas el i ne con di ti ons are cal cul ate d (T ab l e 1 -1) . The 3 yea r com pl etene ss cri teri onGuidance f or Tracking Progress Under the Regional Haze Rule

2 - 9 wi l l al l ow c al cul ati on of base l i ne con di ti ons at thes e s i

tes . If 3 y ea rs wi th c om pleteda ta a re n ot available, e st imates for base line or cur re nt co ndit ions s hou ld be pr epa re d in co nsult at ion wit h t he Env i ronm en tal Protecti on A

gen cy ’sOf f i ce of Ai r Qual i ty P l an ni ng a nd S tandards

(EPA /OAQPS). In any case, all complete years sh

ould be used in

these calcul

ations. Step 8 - Identify Best and Worst Days In thi s step, the 20% best and 20% worst vis ibil ity days wi thin a y ear are ide

ntif ie d, based on th e dec i v i ew v al ue s. Th i s stepi s c on ducte d on

l y f or th ose yea rsof da ta th at m eet th e data compl eteness requi

remen ts stat ed i n Step 7 above. Step 9 - Calculate Annual Average Deciviews I n t his s t ep , an an nu al a ve r ag e d ec iview va lue is c alc ula t ed fo rt he be st 20 % o f t he da ys in a ye ar an d f

o rt he wo r st 20 % o f t he da ys in t he yea r . T his pr o ce ss us es t he be st an d w o r st da ys i den ti f i ed i n th e pre v i ous

ste p a n d sh oul d b e c ar ried out on l y f or y ea rsmeeti n g th e data completeness requirem

ents. Step 10 - Calculate 5-Year D eciview Average s Once the annual

average decivi

ew val ues are calculated for the 20% best and 20% wor st days i n each ye ar, those value s shoul

d be then averaged to produce best and worst average de ci vi ew va l ue s ov er th e p res cri be d 5- yea r pe riods . A s n

oted ab ove , a m

i ni m um of 3 y ea rs of com pl ete da ta sh oul d b e a v ai l ab l e b ef orea 5 -y ea r a v erag e is c al

cul ate d. I f

3 y ea rswi th com pl ete da t a a r e n o t av aila ble , es t imat es fo rba se line o rcu rr en t co nd it io ns s ho uld be pr ep ar ed in co nsult at ion wit h t he E PA/ OAQP S. The re sult ing est imates for t he 5- year p er iod t hen sho uld be use d asthe b asis f

or tracki ng progress

(Secti on 4). 2.3 Th is 10 -steppro ces s f ocus es o n usin g com

plete yea rs

of da ta. What

if an incom plete yea r wou ld o bv io usly ha ve b een a p art icu larly b ad or go od vi sib ili ty yea r? Th i s p oten ti al occ ur re n ce i s a n i n di ca ti on of on e i n sta n ce i n wh i ch i t wou l d b e a pp rop riate to in cl ude d ata f rom i nc omp l ete y

ears i n c alcul ati ons. F or exa

m ple, su ppose that f or a gi ven y ear, in whi ch data compl

eteness overal

l f ell b el ow the recomme

ndation s tated above, there were 25 de civ iew va lu es ( o ut o f 1 22 sa mp ling pe r io ds ) t ha t we r e a bo ve t he av er ag e f o r 20 % wo r st da ys for the other years i

n a 5-y ear period. The i

ncl usion of these resul

ts in the calcul ation of the 5- ye ar averages (i .e., St ep 10 above) would necess aril y i ncrease the 5-y

ear average f

or t he 20% worst day s, reg ardl ess of the dec i

vi ew v al uesf or the othe

r 97 s am pli ng e pi sodes i n that year. That in crease would b

rin g the 5-yea

r average cl oser to its true val uefor that 5-year period. ThusGuidance f or Tracking Progress Under the Regional Haze Rule

2 - 10 i t is reas onabl e to in

cl ude the hi ghe st 20% de ci

vi ew re adi ngs f rom a n i nc omp l ete y

ear, if those va l ue s i nc rease the 5-y ea r av era geof the hi ghes t 20%of

de ci vi ew s, r el ati ve to tha t base d on com pl eteyea rs onl y . F or s i m i l ar rea sons, i

t i s a l so a ppr opri ateto i nc l ude the l owe st 2 0% of dec iview rea dings fr om an inco mplet e year , if tho se va lues d ecr eas e t he 5- year a ver age for t he lowest 20% o f deci

views, relative to t hat based on complete years onl y. As a resul

t, the high

est and lowest decivi

ew readings f

rom in complete years m

ay b e in cluded i n tracking progr ess calcu latio ns, p ro vided t hey meet t he cr iter ia ou t lined abo ve. This inclusio n is analo go us t o t he pol i cy repr es en ted i n prov i si on s of A pp en di ce s K , M , a n d N to 40CFR 5 0 r eg ardi

n g p ar ti cul ate matt er and mak es u se o f incomplet e year s t o p ro vide mor e ac cur at e es t imates for t ra cking progres s. In an y 5- yea r p eri od of

b as el i n e or cu rre n t con di ti on s, th ere sh oul

d b e a t m ost 2 i n com pl ete yea rsof da ta. On e proc es s f

or u si n g a n i n com pl ete yea r of da ta is a s f oll ows . F i

rs t, cal cul atequa

rter l y avera gede ci vi ew va l ue s f rom thos e y ea rs wi th c om pleteda ta (i .e. , th e 3 or mo r e ye ar s me et ing t he da t a c o mple t en es s c r it er ia)

. Se co nd , su bst it ut e t he ap pr o pr iat e q ua rt er ly average deci

view val ues f or all sam pli ng day s i n an in compl ete year that hav

e some m is si ng data, or ev en da y s wi th n o da ta a t al l . Th e pur pos e of th i s s ub sti tuti on i s to f i l l i n th e m i ddl e of th e data se t fr o m t he inc o mp let e ye ar t o de fine t he 20 % hig he st an d l o we st va lu es . Co ns eq ue nt ly, substi tut in g even for days wi

th no data is appropria

te. Third, sort all

deci view val ues wi thin each inc o mp let e ye ar an d c alc ul at e t he av er ag es o f t he 20 % be st an d 2 0% wo r st vis ibilit y da ys. Fin ally, if the a ver age dec iview value o f the 20% wo rst days in t he inco mplet e year is higher t han t he co rr esp ond ing aver age calcu late d fro m all the co mplet e year s, t hen include t he ave ra ge fr om t he i nc omp l ete y

ear a l ong wi th thos e f rom th e com plete y ears and cal cul ate a n ew 5-y ear a verage. Sim il arly , if the average deci

view val ue of the 20% bes

t days i n the i ncom ple te year i s lower t han the corres pon di ng avera gecal cul ate d f

rom al l the com pleteyea rs , th en i nc l ude the avera gef rom the in compl ete year al

ong with those f

rom the compl

ete years, an

d calcul ate a new 5-y

ear average.Guidance f or Tracking Progress Under the Regional Haze Rule

3 - 1 3. METH OD TO CALCULATE THE HAZE INDEX 3.1 What causes haze? Ha zei s c au se d by

the pre senc e of

pa rticl esan d gase s i n th e ai r wh i ch ei the r ab sor b or sc at t er ligh t
. Lig ht r efle ct ed fr o m land sc ap e fe at ur es is s ca t t er ed an d a bso r be d ( at t en ua t ed ) as it pas ses t hro ugh t he at mosp her e t ow ar d t he o bser ver , a nd o t her light is sc at t er ed int o t he obs er ver ’s sight pat h by the int er vening at mosp her e. The deg re e t o w hich light is at t enua t ed by t hese sca t t er ing and a bso rp t ion p ro ces ses c an be e xpr esse d in t er ms of a c oe ffi cient of light ex tin cti on, b ext . Ab sorption of

l i ght due to gase s, b ag , i s c au se d pr i mari l y by the pre senc e of ni tro gen di oxide (NO 2 ) i n the atm osphere, a

nd a bs orption due to parti

cles, b ap , is c au se d p r imar ily by el em ental carbon (al so call

ed ligh t absorbi ng carbon). Scattering b

y gases i n the atm osphere, b sg , is des crib ed by

the Ray le igh scattering theory

[van de H

uls t, 1957] and is ref

erred to as Rayleigh sca t t er ing. T he magnit ude of Ra yleigh scat t er ing var ies de pend ing o n air d ensit y and t he wave lengt h of light . T o s impli fy compar isons of va lues a mong site s at a var iety o f elevat ions, t he IMPROVE pr ogr am assum es a standard value of 10 Mm -1 f or R ay l ei gh sc atte ri n g i n v i si b i l i ty cal cul ati ons r egard l ess of s i te elevati on. Sca

tterin g by particles, b sp , is ca use d by bot h fine and co ar se a er os ol sp ecies a nd is t he larg est co nt ribut or t o t ot al light ext inctio n in most ru ra l locat ions [M al m et al ., 19 94a

]. Th e sum of the se i nd i vi dua l coe f f i ci en ts p rovi de s th

e overa l l l i gh t ex ti nc ti on coef f i cien t, b ext , wh ich is u se d t o ca lcu lat e t he ha ze lev el. 3.2 How are haz e levels calc ulated? T r ac kin g o f t r en ds fo rt he r eg io na l ha ze rule r eq uir es t he ca lcu lat io n o f ha ze lev els , in deci vi ew un i ts, f rom m eas ured p arti cle sp eci

es c once ntrati ons r epres en tativ e of each m andatory Fede ra l Class I ar ea. The spe cies co ncent ra t ions ne ede d ar e r ou t inely m eas ur ed by t he IMPROVE network at selected ma ndatory Federal

Cl ass I areas across the Un ited States. Under IMPROVE prot ocols, particle m easurem ents are m

ade every third day on a 24-hour in

tegrat ed sam pli ng i nterva l , startin g at mi dni ght. PM 2.5 (particulate matter < 2.5 μ m aerody na m i c di am eter) and PM 10 (particulate matter < 10 μ m aerod y n am i c d i am ete r) m as s a remea su re d a t al l si tes , w i th che m i cal speci ation provided f

or the PM 2.5 fraction. The chem ic al speciation resul

ts provide concen tration v al ues f or the maj or chem

i cal consti tuents of PM 2.5 ( i. e. , su lfat e, nit r at e, o r ga nic ca r bo n, ele men t al c ar bo n, an d s o il). T he sp ec ies co nc en t r at io ns a r e u se d a lo ng wit h sit e- sp ec ific correc ti on f

ac tors to c orre ct f

or th e e f f ec ts of rel ati ve hu m i di ty , an d spe ci es -spe cif i c e xti nc ti on ef f i ci en ci es to ac cou n t f or th e d i f f eren t de gr ee to wh i ch each sp ec i es ca us es l i gh t ex ti n cti on , to determi ne dai ly overall li ght extin ction va lue s. These total ligh

t extinction val

ues (express ed as b ext) ar e t he n u se d t o ca lcu lat e t he ha ze ind ex in t er ms o f de civ iew s. Fig ur e 3

- 1 s umma r ize s t his pro cess.Guidance f or Tracking Progress Under the Regional Haze Rule

3 - 2 Figure 3-1 Summ

ary of Process to Calcu

late Haz e Index

3.3 H ow are th e monit oring d ata u sed for th e calculat ion o f b ext obtained? The IMP ROV E ne t wo rk has mo nito ring sit es a t 110 loca t ions t o mo nito r c ond itio ns representative of the 155 m andatory Fede

ral C lass I areas. At each of the si tes, an IMPROVE sam ple r is operated. These sam

ple rs each h ave 4 m odules (i dentif ie d as A, B, C, an

d D) which are used t o co ll

ect par ticulate matter samples f or chemical or gravim

etric analy

sis. Modules A , B, and C col le ct fi ne particl es (0-2.5 : m

), and D c oll

ects PM 10 particles (0-10 : m). The Module A Te flon filter is the pr imary fi lter for pr ovid ing t he fine par t icle mass da t a. Mo dule B , w ith a denuder before the nyl

on fi lter to remove acidi

c gases, is used prim

aril y f or nitrat e. Mod ule C co llects samples o n qua rt z filter s which a re analyzed for car bon in eight t emper at ur e fra ct ions a nd used to det ermi

ne b ot h organic carbon an d li ght absorbi

ng carbon c oncentrations. At som e si tes Mod ul e C us es a s i n gl e q ua rtz f i l ter to co l l ect sa

m pl es wh erea s ot h er si tes us e ta n dem qu ar tz fi lters for quali

ty assurance purpo ses.Guidance f or Tracking Progress Under the Regional Haze Rule

3 - 3 (1) Sulf ate ion concen

trat ion i s determi ned b y m ulti ply in g the concentration of e le me ntal sul fur, as determ

in ed from prot on in duced x-ray

em is sion (PIXE) analy

si s of the Module A sa m ple, b y 3 to a cc oun

t f or th e ox y gen i n th e sulf atei on. W

he n e l em en tal sul f ur data are not avai la ble, sulf ate measured b

y i on chromatographic anal

ys is of the Modul e B sam

ple can b e used to determ i ne the d ry sul f ate con cen tration

. Fi ne particl e sulfate content origi

nates predomi

nan tly from atmospheri

c oxi dation of s

ulf ur dioxide to sulf

uric acid, either by aqueous react ions i n cloud dr oplets o r thro ugh gas-phase ph o t o ch emis t ry. I f t he r e is ina de qu at e a mmo niain t he at mo sp he r e t o fully ne ut r aliz e t he su lfur ic ac i d, th en the res ul ti ng aeros ol s a

re a ci dic. D ep en

di ng on th e a m moni a a va i l ab l e, s ol utions of va ry i ng a cidi ty m ay be f orme d, ran

gi ng f rom a m moni um sul f ate (f ull y ne utral ized) to su

l f uric ac i d. If only the sulf ate ion is m

easured, as is the case at nearly ev ery IMPROVE site, t hen one m ust assum e a form of sulfate (i .e., a degree of neutrali zation b y a mm onia ) and m ulti ply by an appropri ate m

ul tipl i cati on f actor, for i

nstan ce, 1.375 * [SO 4 2- ], if

am moni um s ulf ate is as sum

ed as i s the cas e f or the IMPROV

E program

. The m ass of organi c m ateri al presen t can b e cal

culated f rom the measure d PM 2.5 OC mass, which is de t er mined by ther mal opt ical reflect ance (T OR) analysis [Cho w, et al., 199 3] . An avera geam bi en t pa rticul ateorga

ni c c om poun d i s a ss um ed to ha ve a c ons tan t f racti on of ca rb on by w eig ht

. Or ga nic ca r

bo n ma ss co nc en t r at io n ( OM C) is s imp ly:

wh ere th e f actor of 1.4 wa s s el ected to ad j ust th e or

ga n i c c ar b on mas s f or oth er el em en ts assum ed to be associated wi

th the organic c arbon m

olecul e [Whi te and Roberts, 1977; Japar et al ., 1984]

. Ligh t absor bi ng carbon (LAC), sometimes ref erred t o as elem

ental carbon (EC), is also determi ned b y TOR a nal ys is and is calcul ated from the sum of elem ental carbon f ractions m

in us the py roli zed f raction. Nit r at e io n c o nc en t r at io n is d et er mined by io n c hr o mat o gr ap hic an alys is o f t he sa mple col l ected i n Mod ul e B . A ss um i n g th at th e n i tra te i on i s a ss oci ate d wi th am moni um n i tra te aerosol, [NH 4 NO 3 ], th

e a m moni um n i tra te m as s, [N ITR

A TE] , c an

b e e sti mate d f rom th e n i tra te io n ma ss co nc en t r at io n by u sing a mu lt iplic at io n fa ct o ro f 1. 29 , wh ich ac co un t s fo rt he mas s r at io of NH 4 NO 3 to NO 3 -
.Guidance f or Tracking Progress Under the Regional Haze Rule

3 - 4 (2)

(3) Soi l mas s c on cen

tra ti on , [S OI L] , i s e sti

mate d b y su m m i n g th e m as s of th ose el em en ts predomi nan tly associ ated with soil, wi

th all owance f or o xy gen presen

t in the c omm

on compounds (e .g ., Al

2 O 3 , SiO 2 , CaO , K 2 O, Fe O, Fe 2 O 3 , T iO 2 ) as shown i n Equation 2:

Si n ce pota ss i um ca n ori gi n ate f rom wood sm oke as we l l as f rom soi l , i ron i s u se d a s a

su rrog ate for det er mini

ng [ SO IL] . T he co ncent ra t ions o f the se e lements ar e de t er mined by analysis of t he Module A

sam ple by PIXE. In additi on, a correct ion i s appl ie d for other compounds such as MgO, Na 2 O, an

d carbonate [Mal

m , et. al ., 1994a

]. Co ar se p ar t icle mass ( CM) is est imated gr avimetr ically by subt ra ct ing t he gr avimetr ic fine mass (PM

2.5 from Module A) f

rom total grav

i metric mass (PM 10 fro m Mod ule D) ; - i.e ., in the IMPR OVE progra

m , no ad di tion al chem i cal anal y ses are c arried out on the coars e f raction. 3.4 Wha t are the species mass extinct ion efficiencies for aerosol components?

The g oal of track i n g p rogre ss

gui da n ce i s to ev al ua te c h an ge s i n h az e or v i si b i l i ty attri bu ted to va riousaeros ol

sp ec i es . How ever, asnote d by W hi te [1 986 ], a

ttri bu ti on of atmospheric extin

ction to aeroso l speci

es is an il l-def in ed pro blem. Wh

ereas the sum of m

ass associ ated with each

aerosol speci

es i s roughly

equal to gravi me tric m ass, and theref

ore fractional con tri bu ti on of each sp ec i esto total

mas s c an be cal cul ate d, th

e s am e is n ot ge ne ral l y true f or ex t inc t io n. Be ca us e t wo o rmo r e s pe cie s c an be mixed t o ge t he rin ava r iet y o f wa ys int o a s ing le particle wi

th dif feren t o ptical propert ie s (in

ternall y m ix ed) it i s not possib le

to state, in a gen

eral way, t he amo unt of e xt inctio n at t ribut ed t o t he individual sp ecies. Mo re ove r, a r eview o f the lit er at ur e r ev ea ls t ha t sing le p ar t icle effic ien cy a s it r ela t es t o t he r emo va l o f r ad ian t en er gy a s it pa ss es th rough th e a tm osph ere is def

i n ed i n a m ul ti pl i ci ty of wa y s [ v an de Hul st, 19 57 ; Oui

mette and Fl agan, 1982; W

hi te, 1986; Malm

and K reiden wei s, 1997]. Ouim

ette and Fl agan [1982] defi ne an extin ction ef fi ci ency as the cha

nge i n ex tinction associ ated with the addi tion or removal of a f raction of a s

peci fi c species and W

hi te [1986] argues t hat the m ost meani ngf ul s peci es extin ction ef fi ci ency is associ ated with the decreas e i n tot al extin ction resul

ting f rom an inc r eme nt al r emo va l o f t ha t sp ec ies fr o m t he at mo sp he r e. T he se pa r ame t er s c an be hig hlyGuidance f or Tracking Progress Under the Regional Haze Rule

3 - 5 (4) dep ende nt on a ssu mpt ions c onc er ning par t icle size, mixi ng cha ra ct er istics , a nd che mical and o pt ica l pr o pe rt ies wh ich ar e r ar ely if e ve rmea su r ed

. A fu ll dis cu ss io n o f t he va r io us co nc ep t s is bey ond the scope of thi s guidance. For tracki ng prog res s, a si m ple a nd stra i gh tf orwa rd a ppr oach f or es ti mati ng aeros ol spe cies co nt ribut ion t o e xt inctio n is ou t lined. Mo st ro ut ine aer os ol mo nito ring p ro gr ams and man y sp ec i al study vi si bi l i ty ch ara cteri za ti on program

s w ere de si gned to mea su re b ul k a eros ol species m ass concen

trat ions such as sul fates, ni

trat es, carbonaceous m

aterial , and sel

ected element s [Whit e and Ro ber t s, 1 977 ; Heisler et al., 198 0; Ma lm et al. , 1 994 b; To mbach and Thu rst on, 199 4; Wat so n et al., 199 0; Ma cias et al., 198 1] . T hey wer e no t des igned t o d et er mine

the m i croph y sical and ch em i cal characteri sti cs of

thes e sp eci

es. A ny particle i n the atm osphere sc at t er s a nd /o rab so r

bs a sp ec ific fr ac t io n o f r ad ian t en er gy, wh et he rit is e xt er na lly o rint er na lly mixed. Whe n co mput ing t ot al ext inctio n, t he micro sco pic st ru ct ur e o f the aer os ol ( t hat is, t he ex ten t of i nte rnal or ex tern al m i xi ng) i s f oun d to b e re l ati

ve l y un i m porta nt, so th at the a ss um ption of i ntern al l y vs . ex terna l l y m i xe d parti cles d oes n ot have m uch i m pact on the predi cted re sul ts. This i nsensi tivi ty to to tal scatt ering/exti

nction has b een demonstrated by a num ber of author s, including Ha san a nd Dz ubay [ 198 3] , S loane [1 983 ], and, mor e r ece nt ly, Pilini s et al. [ 199 5] , a nd McM urry et al . [1996 ]. Theref ore , the c al

cul ati on of l i gh t ex ti n cti on f rom aeros ol sp ec i es con cen tra ti on s trea ts eac h spe cies co nt ribut ion se par at ely and mere ly sums the m. This fo rmulat ion implies no i ntera cti on b etween the various ae rosol spe cies wi

th res pect to thei

r contri buti ons to ex tin cti on. Th i s woul d b e th e c as e i f each of th e p ar ti cl es werecom

pos ed of onl y on e s pe ci es (e .g. , s ul f ate particles s epara

te f rom n i trate parti cles w hi ch are s epara

te f rom org an

i c ca rbon particles, etc.). In gene ra l the e xt inctio n co nt ribut ion fo r e ach s pec ies is mod eled a s t he pr od uct of t hre e fact or s: t he dry m ass extin ction eff ici ency for that species ( " i ), the relativ e hum idi ty adj ustmen

t t erm that varies as a f

unction of relativ

e hum idi ty for that sp ecies (

f i (RH)) , and the dry

concentration of that species ( m i ): where " i , the dry m

ass ex tinction eff

ic ie ncy , is def in ed to be the ratio of the to tal extinction associated with species i di v i de d b y i ts m as s a n d th e rel ati v e h um i di ty adj ustm en t factor, f

i (RH) , is def

in ed to be the ratio of scattering b y a species at som e rel ati ve hum i di ty to sc atteri

ng b y that sp eci

es u nde r dry cond i tions, i .e., f i (RH) = b spi (RH)/bspi (RH=0 ) where i refers to the i

th species.Guidance f or Tracking Progress Under the Regional Haze Rule

3 - 6 The ext inctio n efficiencies for so il and co ar se mass ar e t ake n fro m a liter at ur e r eview by Trij onis and Pi tchford [1987]. For soil, the dry extin ction ef fi ci ency of 1 m

2 /g i s u se d, a nd f or coarse mas s, a val

ue of 0.6 m

2 /g is used. For both ni

trat e and sul

fate, a dry extin ction ef fi ci ency of 3 m

2 /g is bas ed on li

terat ure reviews by

Trijonis et al. [1990] and by Whi te [1 990]. Trijonis’ best estim ate for sulf

ates and ni

trat es i s 2.5 m

2 /g with an

error factor of 2, whi

le Wh ite’s average low an d hi gh esti ma tes for the rural W

est are 3.0 and 3.7 m 2 /g respe cti

ve l y . F or org an

i c c arb on mass, Trij onis

estim ates a dry ex

tinction eff

ic ie ncy of 3.75 m

2 /g, again with a n error factor o f 2, and W hi te’s l ow and hi

gh average estim

ates for the rural W

est are 1.8 and 4.1 m 2 /g res pecti ve l y . Based on these e stim

ates, a dry ex

tinction eff

ic ie ncy of 4 m

2 /g is u se d. Mo r e r ec en t ly, M alm e t al. [1 996 ] a nd Cho w et al. [ 200 2] demo nst ra t ed t hat t he as sumpt ion o f the dr y spec ifi c sc at t er ing va l uesy i elded g ood agreemen

t betwe en meas ured a nd c alcul ated ex tin cti on across the en

tire IMPROVE moni

to rin g network. 3.5 Wha t effect does relative humid ity hav e on the h aze levels? Some aerosol com

ponents are hy

groscopic (prin

ci pally sul fates an

d ni trat es), mea

ni ng that particles c omp osed of

those m aterial s grow i

n s ize b y accum ulati ng water f

rom th e atm osphere under m oist condi tions. This causes a

n en han ced am ount o f l igh t scatt erin g that is di

rectly related to the atmospheri

c rela tive h umi dity . Impl

ic it to t he use of

Equation (4) is

an ass ume d li near relationshi

p between aerosol s

peci es m ass an d extin ction. However, the rel ationsh ip b etween me asured ligh

t scatt erin g and h ygroscopi c species m

ass can be qui te nonli near be cause of water upt ake as a funct ion o f relat ive humidity. A nu mber o f aut hor s have at t empt ed t o linear ize t he model , in an em piri cal way , by mul tipl yi ng the h ygroscopi c species by

such a f actor as 1/(1- RH) to accoun t for the pres ence of

water m ass [Wh i te and Rob erts, 19 77; Mal m et al ., 1989]

. However, Mal

m e t al. [1989] and Geb

hart and Mal

m [1989] proposed a dif

feren t appro ach. They m ul tip l i ed the h

y groscopi c sp eci es b y a rel ati ve hum i di ty s catteri ng e nh ancem en t factor, f(RH) , that is cal cul ated on a sampl

in g-period-by

-sam pli ng-period basi s usi

ng Mi e theory, an as sum

ed si zedi stri bu ti on, an d l ab orator y mea su red aeros ol grow th c urv eswh i ch i l l ustrate the si zeof ae r o so l p ar t icle s a s a fu nc t io n o f r ela t ive hu mid it y. T an g [ 19 96 ] pu blish ed gr o wt h c ur ve s s ho win g t he r at io o f pa rt icle dia met er t o pa rt icle di am eter at ze ro relati ve hum i di ty, D/D o , a s a func t ion o f increa sing and dec re asing r elat ive hum idi ty f or a numb er of i

norganic sal

ts. For increasi

ng or decreasi

ng RH , m an y sa l ts ex h i b i t a hy steresis in the D/D o vs . RH

re latio nship, wit h shar p disc ont inuities a t t he de liquesc ence (r elat ive hum idi ty at whi ch the cry stal ab ruptly absorbs water) and cry

stall ization (relative

hum idi ty at whi ch particl es abruptl y l ose water and recrystal

ize) hum idi ties. Becaus e m

ix tures of amm

onia ted sulfat e co mpo unds wit h ot her spe cies have been s how n t o be hygro sco pic belo w t he de liquesc ent val ues [Sloane, 1984; Sloane, 198 6; Stelson and Sein fel d, 1982; Chow et al., 2002] and because the growt h f

actor and li

ght-scattering ef

fi ci ency for am bient aerosols has previ

ously beenGuidance f or Tracking Progress Under the Regional Haze Rule

3 - 7 observed to be rather sm

oot h [Sloane, 1984; Sloane, 1986; Sloane, 1983; We xler and Sei

nf el d, 199 1; Wag go ner et al., 198 1; Da y et a l., 200 0; Ma lm et al. , 2 000 a; Ma lm et al. , 2 000 b; Malm and Day , 2001] , i t is not known w

hether the upp er or lower l i m b of the h y steres i s cu

rve appl i es f or a par t icular aer os ol sa mple. T her efo re , a s a “bes t est imate” for t he su lfate spe cies g ro wt h, t he curves are smoot hed between the deli quescence and crystalli

zation points. Malm et al. [2000 a, b] and Malm and Day [2001] have dem onstr ated t hat in b ot h the East and We st , t he bes t est imate g ro wt h cur ves yield go od agr eement bet wee n measu re d and theoret ic ally

predicted f(RH) fun ct io ns a nd be t we en mea su r ed an d p r ed ict ed amb ien t fine pa rt icle scattering. It is recogni

zed that the sulf

ate f(RH) function is qui

te diff erent for t he East t han W est be ca us e of sul f ateam moni ati on. In the East where

sul f ate s c an be qui te aci dic, a ve rag e growth

of t he su lfate aer os ol beg ins at much low er re lative hu midities ( <30 %) t han in the West . I n t he Colorado Plateau region of the West, growth does not typically in itiate until about 40-50% r ela t ive hu midit y. H o we ve r , be ca us e a mmo niu m mas s c o nc en t r at io n is n o t r o ut ine ly mea su r ed in the IMPROVE program, am moni um s ulf ate is as sum

ed as the f

orm of sul

fate an d the “sm oot hed” am m oni um su l f ate growth cu rve is u se d f

or e sti mati n g sul f ate f(RH ) cu rve s. T his s mo o t h c ur ve is il lus trat ed i n Fi gure 3-2, whic

h sh ows the f(RH) for ammonium sulfat e as a funct ion o f relat ive hum idi ty. The data are lis

ted in A ppendi x A-1. Th e va lue o f

f(RH) r ise s ve ry slo wly fr o m 1 a s t he r ela t ive hu midit y incr ea se s, o nly reachi ng 2at ab out 70% rel

ati ve hum i di ty. H owever, f(RH) is

non-l in ear and i ncreases rapidl y as i t approache s 100 % rel

ati ve hum i di ty (a t whi ch poi nt i t is und ef i ne d). For exa

m ple, f(RH) is

4 at about 90% relativ

e hum idi ty an d in creases to 7.5 at about 95% relativ e hum idi ty. The i mportance o f t his e ffec t is illu st r at ed by co nsid er ing t ha t t he sa me c o nc en t r at io n o f su lfat e a er o so l is resp onsi bl e f or 4 tim es the haze

at 95% re l ati

ve hum i di ty as at 70%relati

ve hum i di ty.Guidance f or Tracking Progress Under the Regional Haze Rule

3 - 8

Figure 3-2 Smoothed Ammonium Sulfate f(RH) Curve

Var iou s funct ions fo r t he hygr os co picit y of pa rt iculat e o rg anic co mpo unds have a lso be en pr o po se d. Ass ump t io ns mu st be mad e a bo ut t he fr ac t io n o f o r ga nic s t ha t ar e s o lub le. Mo de ls t ha t t r ea t wa t er up t ak e fo rno n- ide al mu lt ico mpo ne nt so lut io ns u sing t he o r et ica l an d s emith eoreti ca l th er mody n am i c rel ati on sh i psh av e b een dev el ope d a n d h av e b een appl i ed to b oth vi si bi li ty an d clim ate forcin g problem

s [Saxen a and Peterson, 1981; Pili ni s et al., 1995; Sax

ena et al., 198 6, 199 3] . T he co rr ect t re at ment o f the hygro sco picit y of spe cies in multico mpo nent mixt ur es ( es pe cia lly o r ga nic sp ec ies ) r ema ins p r o ble mat ic, no t o nly be ca us e o f t he lac k o f su it ab le mi xture thermody

nam ic data but also bec ause of the l ack of i nf ormation ab out ot her cri

tical m i xture properties. Sci en ti sts ha ve ex peri men tal l y mea su red grow th of am bi en t pa rticl esasa f un cti on of relati ve h umi dity usi ng tandem

dif feren tial mobi li ty an al yzers (TDMA) i

n non-urb an settin

gsGuidance f or Tracking Progress Under the Regional Haze Rule

3 - 9 [Zhan g et al., 1993; 1994; Swi

etlicki et al., 1999]. One study was carri ed out in Meadv ie w, Arizo na ( wes t end o f Gra nd Ca nyon) ove r a 31- day pe rio d du ring t he su mmer o f 199 1, a se co nd at H opi Poi nt, A ri zon a (m i dpoi nt of Gra nd Ca ny on) , ov er a

13- da y period du

ri ng the wi nte r of 1990, and a thi

rd at Clarem

ont, Californi

a, over an 11-day

period duri

ng the sum

me r of 1987 [Cai et al., 1993; Zh

ang et al ., 1993, 1994; McMurry an d Zhan g, 1991]. A TDMA consists of two DM A s op erate d i

n se ries . Th e f i rs t DM A i s u se d to s el

ect a s ize , w

h i l e th e s ec on d is u se d to me asure the chan

ge i n particl e si ze as relative

hum idi ty i s vari ed. Usually

, a MOUDI si

ze sam ple r [ Ma r ple et al. , 19 91 ] is r un co nc ur r en t wit h t he T DM A t o de r ive es t imat es o f pa rt icle com posi tion

. Base d o n t heir mo deling as sumpt ions, Saxe na et al. [ 199 5] co nclude d t hat at t he Gr and Cany on, aerosol organic s

peci es i ncreased wa

ter absorption by

in organic s peci es, whi

le at Cl aremont the ne

t eff ect of organics

was to dim

in is h water absorption b

y i norganics. On the other hand, Pit chfo rd and M cMu rr y [19 94] sho wed t hat on 6 of t he 8 s ampling days a t t he Gr and Ca n y on stu dy ci ted ab ov e, i f i t i s a ss um ed th at n i tra tes an d sul f ate s u pta ke wa ter at th e s am e rate as meas ur ed in t he labo ra t or y, t hey alone co uld ac co unt for all of t he measu re d wa t er abso rp t ion. Sw i etl i ck i et a l .[1 99 9] made T DM

A mea su re men ts i n Nor th er n En gl an d a n d f oun d g row th to take place i

n two modes, one m

ode bei ng less h ygroscopi c than the other. They concl uded that growt h coul d be attributed to t he i norganic content of the aerosol. Cocker et al. [2001] meas ured hy groscopi c proper tie s of Pasa den a, Ca l i f orni a, aerosol and concl

uded that growth

f actors i n crea se d w

h en f ore st f i re s were pre se

n t. H owev er , they

wereun ab l e to a ttri b ute th e g row th to an y sin gl e s pe cie s b ec au se co nc ur r en t ae r o so l sp ec iat io n w as no t ca rr ied o ut simu lt an eo us ly. McD ow et al. [ 199 4] measu re d wa t er upt ake by diesel so ot , a ut omo bile exhaus t , a nd wood smoke particles. They found al l three em is sion types ab sorbed water, with the wood smoke sam ple weight in creasi ng by about 10% as sampl

e rela tive h umi dities i ncreased, wh

ereas diesel soot sam ple wei ght i ncreas ed b

y onl y 2%-3%. Ch ug ht ai e t al. [ 19 99 ] ex amine d t he hyd r at io n c ha r ac t er ist ics o f BP 20 00 ( co mmer cia lly avail ab l e ca

rbon bl ack), a nd of carb on produced f

rom n -hexa ne , di ese l f uel , JP8 (a

vi ati on f uel ), pin e needl es, Utah coal, an

d acetyl ene. They

exam in ed water adsorpt ion i

sotherms b etween 20% an d 8 5% r ela t ive hu midit y and co nc lud ed t ha t t he ab ilit y o f bla ck ca r bo ns, pr o du ce d fr o m a variety of f

uel types, to adsorb water generall y i ncreased wi

th age and surf

ace oxidation. At hi

gh re lative hu midity (83 %) , lar ge s ur face a re as d et er mine the a dso rp t ion ca pac ity. At lowe r r elat ive hum idi ty, however, the surf

ace f unctiona l groups determi

ne the ex tent of hy dration. Even a

t 83% relative h umi dity, the water up take was less than 10% of to tal mass for all carbon speciesGuidance f or Tracking Progress Under the Regional Haze Rule

3 - 10 (5) o t he rt ha n B P2 00 0. Be ca us e o f it s la r ge su r fac e a r ea , BP 20 00 ab so r be d a bo ut 40 % o f it s ma ss in wa t er . Co nse qu en t ly, t he y co nc lud ed t ha t co mmer cia l ca r bo n bla ck s a r e n o t ac ce pt ab le mo de ls for fuel-pro duced carbons. Field expe riment s and subs equ ent dat a ana lysis at t he Gr eat Smo ky Mo unt ains and Gr and Canyo n Nat ional P ar ks [ Malm et al., 199 7; Ma lm and Kreid enwe is, 1 997 ; Malm et al., 200 0 a, b] an d, m oregen eral

l y , da ta c oll ected

i n th e I MP RO VEn etwork

[M al m et a l ., 1 99 6] sh

ow th at withi n the un certainty of the m easurem ents and m

odeli ng ass umptions, ambie

nt organics

in rural ar ea s o f t he Un it ed St at es ar e a t mo st o nly we ak ly hygr o sc o pic

. T he r efo r e, ba se d o n t he av aila ble data, t he f(RH) for aerosol organics can be reasonabl y s et equal to one. The addi ti v e exti n cti on b y ch em i ca l sp ec i es em b odi ed i n Equ ati on 4 c an b e c om b i n ed wi th t he effect of RH discu ssed abo ve, t o e st imate t he sc at t er ing o f li ght by fi ne pa rt icles. T he followi ng equati on is

used to estima

te calcul ated particle

li ght scattering:

The brackets i

n Equation 5 i

ndicate the speci es concen trat ion, 3 m

2 /g is the dr y spec ifi

c sc at t er ing eff ic ie ncy for sulfates an

d ni trat es, 4 m

2 /g is the dry speci

fi c scatt ering ef

fi cien cy f or o rganic m

ass, and 1 m

2 /g and 0.6 m

2 /g are t he respective scatter in g eff ici encies for soil an

d coar se mass . 3.6 How are the f(RH

) values determined? Average f

SO4 (RH) values for eac h sampling pe rio d ar e ca lculat ed ba sed on t he ambient h um i di ty , us i n g Ta n g’ s [ 19 96 ] a

m moni um su l f ate growth cu rves . A ss um i n g a l ogn orm al su l f ate mass si ze di stribution, with a geom etric m ass m ean di am eter of 0.3 : m

and a ge ome

tric stan dard dev i ati on, F g , of 2.0, the f SO4 (RH) val

ues are cal

cul ated usin

g D/D o curves that are sm oot hed between the crys

tall ization an d delique scent poin

ts. The f

NO3 (RH) as so cia t ed wit h nit r at es is assum ed to be the same

as f or sulf ates, while f

org (RH) for organic s i s set equal to 1.0. T o as se ss t he ch an ge s in ma n- mad e p o llut io n c o nt r ibu t io ns t o visib ilit y impa irme nt , it is appro priate to use relative h umi dity that is the sam

e for the baseli

ne period and future periodsGuidance f or Tracking Progress Under the Regional Haze Rule

9 U.S . EPA , Inte

rpolatin g Rela tive Humidity Weig hting F actors to Calculate Visi

bility Impairment and the Effects of IMP ROVE M onitor Outliers , pr epar ed by Science Applic at ions Inte rnatio nal Co rporation , Raleigh , NC, EPA Con

tract No. 68-D- 98-113, A ugust 30, 2001

. 3 - 11 wit h chang ed e missions. In o t her wo rd s, it is mor e ap pr op riat e t o e lim inate t he co nfou nding effect s o f inter annua l variat ions in r elat ive humidity, w hile maintaining t ypical reg ional and seasonal h

umi dity patterns. T o t ha t en d, t he U. S. E PA r ec en t ly sp o nso r ed a p r o jec t t o ex amine mea su r ed ho ur ly re lative hu midity dat a o ver a 10 -year per iod (1 988 -1 997 ) w ithin t he Unit ed S t at es t o d er ive month-specif

ic cl im ato logical mean hum idi ty corr ection factor s for each man dato ry Federal

Class I area. 9 Th e h

ourl y RH mea su rem en ts f rom each si te w ere con ve rted to f(RH) values using a nonli near wei ghtin g factor curve (see Fi

gure 3-2). Values ab ove 95% RH were set equal to the f(RH) correspondi

ng to 95% R

H. The res ul ts o f th at work

are th e v al ue s pre se n ted i n A pp en di x A . Th es e rel ati v e h um i di ty factors have been

calcul ated from av

ai la ble hourly relati ve h umi dity data from 292 National Weather Servi

ce stations across the 50 States and the Di strict of Colum bia as wel l as f rom 29 IMPR OVE an d IMPR OVE protocol

moni torin g si tes, 48 C l ean

Ai r Status a nd Tr ends Ne twork (CASTNet) sites, and 13 a dditional si tes admi ni stered by

the National

Park Servi ce. Usi

ng a so ft wa r e t o o l av aila ble fr o m E P A, mo nt hly f(RH) values can be calcu late d fo r a ny locat ion in t he Uni ted St ates. In most regions there is a seasonal

cy cl e of relative

hum idi ty, whi ch is accounted fo rby g en er at ing t he ap pr o pr iat e mo nt hly f(RH) va lu es , as in Ap pe nd ix A. T he 12 mo nt hlyaveraged f(RH) va lue s a r e lis t ed fo rea ch I MP RO VE o rI MP RO VE pr o t o co l sit e a nd t he ir corresponding C lass I areas. The si te specif ic val ues associated listed for each m andatory Fede

ral Class I area in thi s way are recomm ended to be used for all

vi sibil ity an d tr acking progress ca lcu lat io ns f

o rt ha t Cla ss I ar ea . T he se va lue s a r e p r o vid ed in T ab le A- 2. A su pp leme nt al t ab le of 12 m onthly -averaged f(RH) va lue s fo rea ch man da t o ry Fe de r al C las s I ar ea is a lso pr o vid ed in Table A -3 for inf ormational purposes. Ap pe nd ix B e xa mines wit hin- mo nt h c o rr ela t io ns t ha t may e xist be t we en RH an d in o r ga nic aer os ol co ncent ra t ions a nd t he po t ent ial effect on t he co mput ed ha ze inde x. I f the co rr elat ions are signifi cant, then the use of

monthl y-av erage f(RH) could sy

stematically

over- or under-predict the contribution of sulfate or ni trat e to visi

bi li ty i mpa irm ent The resul

ts in Appen dix B show that monthl y a verage f(RH) val

ues are appropriate. The di ff erence i n com puted haze i

ndex val ues re su lt ing fr o m t he u se o f mon t hly valu es o f f(RH) vs. 24 hr v

al ues, is withi n 10% f or 20 IMPROVE si

tes studied.Guidance f or Tracking Progress Under the Regional Haze Rule

3 - 12 (6) 3.7 How does

light abs orption

contr ibute to light extinction? Light absorption by

gaseous species, prim

aril y NO 2 , i s general

l y ne gli gi bl e i n m andatory Fede ra l Class I ar eas and no t included in calculat ions o f li ght ext inctio n. H ow ever , e st imating t he total l i gh t ex ti nc ti on a l so req ui res a k now l edgeof l i gh t ab sor ption b y pa rticl es . Li gh t ab sor ption b y pa rti cl es i s pri mari l y du e to e l em

en tal ca rb on (al so c al l ed l i gh t-a b sor b i n g c ar b on). H orvath [ 19 93 ] ha s r ev iew ed t he mea su r eme nt o f ligh t ab so r pt io n by e leme nt al c ar bo n, wh ile F ulle ret al. [19 99] has exp l ored

the oreti cal l y the va riab i l i ty of ab sor ption e f f i ci en cy asa f un cti on of ca rb on mor pho log y. Es t imated mass abs or pt ion efficiencies o f elementa l carbo n var y by m or e t han a fact or of t wo , a s do dire ct measu re ments . Alt hou gh pa rt icle light abs or pt ion ca n be es t imated in a va ri ety of ways, the

re i s n o one m ethod that i s general

l y acc epted b

y the s cien tif i c com m uni ty. For purposes of this

guida nce, el em ental carbon l igh t absorption is

estim ated usin g:

were LAC

is the concentration of l

igh t-absorbin

g carbon as m

easured usi

ng the Therm

al Optical Re f l ec tan ce(TO R) a

na l y sis m eth od [Chow et al ., 19 93] , an

d 10 i s th e spe ci f i c a bs orpti on ef f i ciency f or LAC, wh

i ch ha s b een use d by a n um ber of s cien

tists [Horvath, 1 993]. 3.8 How is the

total l ight extinction cal

culate d? In addi ti on to pa rti cl e s ca tter i n g a n d p ar ti cl e a b sor pti on , total l i gh t ex ti n cti on n ee dsto inc lud e a t er m b sg , i. e. , fo r Ra yleigh scat t er ing, w hich is scat t er ing by the g as mo lecules in the atm osphere. Th

us, b ext = b sp + b ap + b sg . As in dic at ed in S ec t io n 3

. 7, ca r bo n lig ht ab so r

pt io n is est imated as t en t imes the co ncent ra t ion o f li ght -a bso rbing c ar bon fo r t he pu rp os es o f the guidance. A standard val ue of 10Mm

-1 for Rayleigh sca t t er ing is use d in visibil ity calcu latio ns reg ard l es s of si te e l evati on i n k ee pi ng wi th th e p racti ceof

roun di ng each consta nt i n th e aeros ol extin ction cal cul ation to o ne si

gnifi cant digit and to si

mpl if y c ompari sons of v

al ues am ong si tes at a variety of

elev ations.Guidance f or Tracking Progress Under the Regional Haze Rule

3 - 13 (7)

(8) Co mbining all o f t he fac t o r s d isc us se d a bo ve , t he fo llo win g e qu at io n c o nve rt s p ar t icle sp ec ies c o nce nt ra t io n da t a in u nit s o f μ g/m 3 for a sam

ple period at a moni

to rin g locati on to to tal li ght extinction i

n uni ts o f Mm

-1

.

Malm et . a l. [1 996 ] u sed t his IMP ROV E a lgo rit hm to suc ces sfully reco nst ru ct sca t t er ing at nine si tes, nam el y G rand Can yon, Petrif

ie d Forest, Guadalupe Mountai ns, Yel lowstone, Rocky Moun tai n, G l aci er, Pi nn acl es, B andel

i er Na tion al Parks , and the

Bri dger W i l dern ess Are a. Addit ionally, co mpar isons wer e made bet wee n calcu late d and measu re d ext inctio n at Acad ia and Shena ndo ah Na t ional P ar ks fo r t he t ime per iod 198 8- 199 1. Tho se r esu lts w er e r epo rt ed in t he Fe br ua ry 199 3 IM PROVE re

port " Spa ti al an d Tem pora l Patte rn s a nd the Ch em i cal Com pos i ti on of the Haze i

n the Un ited States,” ISSN No . 0737-5352-26. Fina ll y, Ch ow et al. [2002] has com pa red mea su red an d c al cul ate d s ca

tteri ng at the G rea t Sm oky Mou nta i ns Na ti ona l Par k f or the tim e period 1994-2000 and f ound that, o n average, nephe lom eter measured sc atter in

g is about 6% larger than cal cul ated s catteri

ng, a nd th e RM S error wa s 23%

. 3.9 How are haz e index value s in deciv

iew units c alcul

ated? Once t he light ext inctio n has be en ca lculat ed fo r a monit or ing site , u sing E qua t ion 7 , t he haze index ( HI

) in deci view ( dv ) uni

ts can be c al cul ated. The HI is a visibil

ity met ric bas ed o n t he l i ght-exti nction coef f i cien t that ex pres ses i ncrem en tal changesi n pe rcei ve d vi si bi l i ty [P i tchf ord and Mal m, 1994]. Because

the HI ex pre ss esa re l ati

ons hi p b etw een c

ha ng esi n l i gh t ex ti nc ti on and percei

ved v is ibil ity, it can b e usef

ul i n descri bi ng vi si bi li ty trends. A ch

ange i n the HI of o ne dv is e qu iva len t t o ab o ut a 1 0% ch an ge in e xt inc t io n c o effic ien t , wh ich is a sma ll bu t pe r ce pt ible sceni c chan ge under a wi

de range of v

is ibil ity condi tions. The HI

is defined by t he fo llowing equ at ion:

The val ue of the ha

ze i ndex is near zero dv f

or a pristin

e atmosphere ( dv = 0 for a pure Ray le igh scattering condi

tion) and i

ncreases as visi bi li ty i s degraded.Guidance f or Tracking Progress Under the Regional Haze Rule

10 Walsh , K . “OU TLIERS A NDTHE IR

EFF ECT S ON A

VERA GE VIS IB IL ITY IMPA IRME NT CON DITI ONS,”

EPA Con tract 68- D-9 8-1 13 w

ith Sci en ce Ap pl ic atio nsIn te rnat io nal Corporatio

n. March 20 01. 3 - 14 3.10 Should

outlier s in the data be

excluded? Each a nn ual es ti mateof be st a nd worst da y s shou l d b e b as ed

on a l l va l i d m ea su red aeros ol con cen tra ti on s d uri n g th e c al en da r y ea r. Th i s i n cl udes h i gh con cen tra ti on s a ss oci

ate d wi th re gi on al f ore st f i re s or oth er un us ual ev en ts. A n an al y sis of IMPR OV E da ta 10 co llecte d du ring 199 4- 199 8 r evea led t hat by excluding o ut liers ( measu re ments gr eat er t han 2 s t anda rd deviat ions from the m

ean of the 20% wo rst days) from the calcul ation of the 5-year mean f or t he 20% wor st vi si bi li ty day s, the me an h

aze i ndex chan ged by 0.3% at Great Smoky

Mountains and b

y 2.5% at Gr ea t Sa nd Du ne s. Ch an ge s a t o t he rsit es we r e b et we en t he se t wo va lue s. Simila r ly, c ha ng es in t he calcul ated 5- year m

ean haze i ndex resul

ting f rom the exclusi

on of out li

ers in the 20% best vi sibil ity day s (measurem

ents great er than 2 standar d deviations from the mean of the 20% best da ys) we r e b et we en 0. 6% ( Po int Re yes ) an d 2

. 9% ( Big Be nd )

. T hu s t he impa ct fr o m a s mall num ber of day

s tends to average out when the visi bi li ty i s exam

in ed on a deci

view scal e over a 5- ye ar period. It is i

mportant to in

cl ude these ex

treme concen

trat ions in the estim ates for 5-yea

r base l i ne an d curren t vi si bi l i ty con di ti ons be ca us e the i m pa ct f rom the se even ts m ay be pa rt of natural b ackground and is thus ref le cted in the estim ate for the target vi si

bi li ty levels. When an ou t lier in the dat a is clear ly not re pr ese nt at ive of t he r egio nal haze levels, t he r esu lt sho uld be f l ag ge d a nd an ex pl an ati on provi de d of

the ca us e of the outl i er. If a very l ocalize d f

i re ( f or exam ple, a ne arb y stru ctu ral f i re)seve rel y i m pa ctsthe l oadi ng of a spe cif i c s am pler b ut doe s n ot deg ra de t he visibil

ity o ut side o f the imm

ediat e vicinity (e .g ., wit hin 1 mil e) , t he da t a sho uld be flag ge d in all d at a file s a nd ca lcu lat io ns. Su ch o cc ur r en ce s ma y no t be ap pr o pr iat e fo rinc lus io n in v i si b i l i ty tren dsan al y sis. On th e oth er h an d, e v en ts w h i ch re su l t i n appa re n t outl i er s i n th e data an d d o ha ve an impa ct o n t he r eg io na l visib ilit y (e

. g. , fo r es t fire s) sho uld be inc lud ed in su bse qu en t t r en ds an alys is. T he da t a s ho uld be flag ge d a nd ex pla ine d, if po ss ible, bu t sho uld rem ai n i n th e data set. A ny su ppor ti ng ev i denc e w hi ch may be us ed to he l p qu an ti f y the i m pa ct of the epi sode causi

ng the outlier should be colle cted, if possible

.Guidance f or Tracking Progress Under the Regional Haze Rule

4 - 1 4. PROCEDURES FOR COMPARING 5-YEA R PERIODS 4.1 How are the daily deciview val ues, calculated as des cribed in Section 3, used to track progress in improving visibility? The dai ly deci view val ues f rom the bes

t and worst days i

n each ye ar are fi

rst selected, then averaged over an

nual and 5-y ear periods

, and fi nal ly those 5- year averages are compared to assess pr o gr es s. T his s ec t io n o f t he gu ida nc e d o cu men t de sc r ibe s t he pr o ce du r es fo rca rrying o ut t his proces s. 4.2 How are the selection and averaging of the best and worst days in each year done? Once the dai

ly deci view val ues hav e been calcul ated for each sam

pli ng day at a site, in cl udin g those days

for whi ch m is si ng data were repl aced by

appropriate averages, the deci view val ues f or each y ear are ranked f

rom lowest t o high

est. Then the l

owest 20% o f the dec iv

ie w val ues f or t he y ear (i.e., the best 20% of the day s i n terms of visi bi li ty) are averaged, to produce an annu al aver age dec iview value fo r t he bes t 20% of t he da ys. S imi larly, t he highes t 20% of t he deci view val ues f or t he y ear (i.e., the worst 20% o f the day s i n terms of visi bi li ty) are averaged, gi v i n g th e a n n ual av erag e dec i

v i ew v al ue f or th e w ors t 20 % of

th e day s. The m eth ods us ed to ca l cul ate %i l es are b as ed on th ose f oun d i n In ter pr eta ti on of th e N ati on al A m b i en t A i r Q ual i ty Standard s for Part icul

ate Mat ter ( 40 CFR 50, Appendix N). After so rting the values f rom lowest to hi ghest, the 20 th %ile value fo r year y, is given by

where P 0.20, y is

the 20 th %i l e f

or year y , X

i= the i th numb er in t he o rd er ed se rie s o f n number s, a nd iis the in teger part of the product o f 0.20 an d n . Sim il arly , the 80 th %ile is given by

where P 0.80, y is

the 80 th %i l e f

or year y , X

[i+1] = the ( i +1) th numb er in t he o rd er ed se rie s o f n num bers, and iis

the in teger part of the product o f 0.80 an d n .Guidance f or Tracking Progress Under the Regional Haze Rule

4 - 2 Th i s proc es s s

h oul d b e rep ea

ted f or e ach y ea r of da ta a v ai l ab l e. Note

th at th e data com pl etene ss rec om men da ti ons sta ted ea rl i er i n th i s docu men t may el i m i na te s ome y ea rs f rom be ing inc lud ed in t his c alc ula t io n. Fo rea ch co mple t e ye ar o f da t a fo ra s it e, t he r es ult s o f t his calcul ation are t wo values, i.e., the average decivi ew val ues for the best and wo rst days, r es pe ct ive ly. 4.3 How are the 5-year

deciview aver ages determ

ined? T he an nu al a ve r ag e d ec iview va lue s fo rt he 20 % be st an d 2 0% wo r st visib ilit y da ys in each yea r are f urth er a ve rag ed ove r th e 5 -y ea r pe riodssp ec i f

i ed i n th e re giona l ha zerul e. F or example, t he bas eline 5- year p er iod is 200 0- 200 4. The annua l avera ge d eciview va lues fo r t he 20% best days i

n each ye ar in that period are averaged together, pro duci ng a si ngle average decivi ew val ue for t he best days. Si

mi larl y, the annual

average decivi

ew val ues for the 20% worst days i n each ye ar in that period are averaged together, pro duci ng a si ngle average deci

view val ue for the worst days. Thus eac h 5-y ear period i s characteri

zed by two values, i .e., t he av

erage deci view val ues f or t he b est and worst days, respecti vel y. The se average s over the 2000-2004 ti me p eri od a re th e b as i s a gai ns t wh i ch i m prov em en ts i n wors t da

y vi si bi l i ty an d l ac k of degradation f

or t he b est day v

is ibil ity are judge d. Correspo ndi ng av erages are to be cal cul ated over s ucce ssi ve 5-y ear pe ri ods, i .e., 200 5-200 9, 2010 -2014 , etc. W i thi n a ny sp ec i f i ed 5-y ea r pe riod, th ere sh oul d b e a t l ea st 3 com

pleteyea rs of da ta f rom whic h an nua l ave ra ge s a re dr aw n fo r t his c alc ula t io n o f 5- yea r a ver ag es . T he c alc ula t io n o f 5-year av erages sh ould i ncl ude all c omplete years i

n that period. If a 5-y

ear period has

le ss than th re e c om pl ete yea rsof da ta, th en esti mate s s h oul d b e prepa

re d th rough con su l tati on wi th EPA/OA QPS. 4.4 Wha t is the n ature of the comparison b etween 5- year average deciview values? The comparison shoul

d be a si mpl e arithm etic com paris on of the current 5-ye ar average deci view val ues to t hose f

rom the bas elin

e (i.e., 2000-2004) period. The 5-y ear average deci

view val ues f or t he 20% worst days are com pared to judge progress in im provin g vi si bi li ty, and the 5- year a ver age dec iview values for t he 20 % be st days a re co mpar ed t o c heck whet her any degradation of v

is ibil ity on the best day

s has occurred. The fi

rst such SIP compari son will take pla ce i n 2018, wi

th an i nterim progress check i

n 2013. 4.5 What if siting or procedural changes are implem ented at an IMPROVE site? If si tin g or proced

ural changesthat m

ay af f ect the moni torin g data a t a si te occur, c are mus t be t ak en t o en su r e t he co mpa r ab ilit y o f t he mo nit o r ing da t a b efo r e a nd aft er t he ch an ge isGuidance f or Tracking Progress Under the Regional Haze Rule

4 - 3 implemented . Whe n po ssible, t he monit or ing age ncy sho uld co nduc t co mpar at ive sampling adeq uate to dem

onstra te data c omp arab i l i

ty. 4.6 Wha t if changes a re made in the sit es selected to cover a mandat ory Federal Class I area? Currently

, all ma ndatory Federal

Cl ass I areas are covered b y a t least one IMPROVE m oni torin g si te. The si tes ch osen to represe

nt the di f f eren t ma nda tory F edera

l Class I area s we

re chosen i n c onsu l tation between EPA a nd th e States . If

a dif f eren t si te or addi tion al si tes are se lec t ed t o r ep r es en t a g ive n ma nd at o ry Fe de r al C las s I ar ea , t he ca lcu lat io ns p r es en t ed in t his documen t for tr ends as sessm

ent mus t be perform

ed usi ng the data from

the newl y s el ected m oni torin g si te(s). 4.7 Are trends

in the individual species important, as wel l as the over all trend in visibility? T ho ug h t he r eg io na l ha ze r eg ula t io n c alls fo rt r ac kin g o f ca lcu lat ed ha ze ex pr es se d in dec iview unit s, t he implementa t ion o f the haze re gulat ion ca n only be ac co mplished by red ucing t he co ncent ra t ions o f the par t iculat e sp ecies t hat ar e r esp ons ible for t he man-mad e po rt ion o f the wo rst haze days. To war ds t hat end it is espe cially helpful t o a lso t ra ck t re nds fo r a ll of the particle species that contribute to haze. Apportionin g the haze to the various particl e species con tri bu tors i s a n i m porta nt f i rs t ste p to a ss es si

ng wh i ch pol l uta nts of f er th e b es t ha zered uc ti on opp ortu n i ti es f or em i ss i on s c on

trols. In th e l ong- ter m , tra ck i n g tren dsof sp ec i es con tri b uti on s to ha zeprov i de s i nf orm ati on th at c an be us ef ul i n d eterm i ni ng whether i m plem en ted em i ss i on co nt r o ls a r e h av ing t he ex pe ct ed effe ct s. Ult imat ely a s t he man - mad e c o nt r ibu t io ns t o sp ec ific par t icle spe cies ar e r edu ced below t hos e fro m natu ra l sou rc e, nat ur al haze level est imates can be refi ned. The co nt ribut ion t o ha ze by ea ch pa rt icle spe cies ca nnot be de t er mined in ter ms of t he ha zei nd ex ex pre ss ed i n d ec i vi ew un i ts, w hi ch be ca us e of i ts l oga ri thm i c n atu re c an not appropri ate l

y b e b roken i n to co m pon en ts. The b est approach

to as si gn h az e c on tri b uti on to particle sp eci

es is b y thei r share of the l i ght exti nction ex pres sed i n un i ts of i nv erse megam eters (Mm -1 ) a s de fined by the individual t er ms in equa t ion 8 . T he I MPR OVE web s ite r epo rt s t he species contrib

ution to light extin

ction f or each si te and sam

ple period as wel

l as ann ual trends at each si te for t he worst , best, and middl e haze days

.Guidance f or Tracking Progress Under the Regional Haze Rule

5 - 1 5. REFERENCES Ca i, X. ; T ur pi n, B. J. ; M cM ur ry, P

. H. P ar t icle gr o wt h a s a fu nc t io n o f siz e a nd hu mid it y ( T DM A) , in 1 99 2 M ea su r eme nt s o f Ae r o so l Co mpo sit io n a nd Op t ics in Me ad vie w, AZ ( in conj unc tion wi th Proj ect MO HA

VE).Re port on Proj ect RP2 023-1 1 to Ele ctri c Power Res earch Insti

tute (EPRI), Pa

l o Al to, Cali f orni a, Un i versi ty of Mi nn eapol i s, Mi nn esota, 1993. Cho w, J.C , Wa t so n, J. G. , P rit chet t , L. C. , P ierso n, W. R. , Fr azier , C .A. and P ur cell, R. G. , T he DRI t her mal/o pt ical reflect ance car bon a nalysis syste m: des cr ipt ion, evalua t ion, and appl i cations i n U .S. ai r qual i ty s tudi es, Atmos. Environ ., 27 (A), (8), 1185-1201, 1993. Chow, J.C., B ach

man n, J .D., Wi erm

an , S.S.G., M atha

i , C.V., M al

m , W.C ., Wh

i te, W.H ., Muelle r, P.K., Kumar, N., Watson, J.G., Critic al Revi ew Di scussi

on: Vis ibil

ity : Scien ce and Reg ulati on, J. Air

and W aste Manag e. Ass oc., 52 , 973-999. Ch ug ht ai, A. R. ; Willia ms, G. R. ; At t eya , M. M. O. ; M iller , N. J. ; S mit h, D. M. Ca r bo na ce o us pa rt icle hy dration. Atmos. Environ

. 33, 2679-2687, 1999. Co ck er , I II , D .R ., Whit lo ck , N .E ., Flag en, R. C. , S einfe ld, J. H. Hyg ro sc o pic pr o pe rt ies o f Pasa den a, Ca l i f orni a aerosol

. Aerosol Science and Technology , 35 , 637-647, 2001. Day, D.E., Malm

, W.C. and Kreidenweis, S.M. , Aeroso l l igh t scat tering measurem

ents as a f unc tion of re l ati ve hum i di ty, J. of Air & Was te Management Association , 50 , 710-716, 2000. Ful le r, K., Malm

W., and K

reiden wei s, S., Effects of m

ix in g on extin ction by carbonaceous particles, J. Geophys. Research , 104 :15, 941-15, 954, 1999. Ge b h ar t, K .A . a n d M al m , W .C ., A

n i n v esti ga ti on of th e s ize distr i b uti on s of pa rti cul ate su l f ate concent rat ions measured dur ing W HIT EX, In Tr ansactio ns of the AWMA/EPA Int ’l Sp ecialt y Confer ence on V isibi lity and Fine P ar t icles, e dit ed by C. V. Mat hai, Air a nd Waste Man

agem ent Ass ociati on, 157-169, 1989. Ha sa n, H. an d D zu ba y, T

. G. , Ap po rt io ning ligh t ex t inc t io n c o effic ien t s t o ch emic al s pe cie s in atm ospheric aerosol s, Atmos . Envir on., 17 , 1573-1581.Guidance f or Tracking Progress Under the Regional Haze Rule

5 - 2 Hei sler, S.L., Henry, R.C., Watson, J.G., and Hidy, G.M., “Th e 1978 Denv

er win ter haze study vol um e II.” ER T docum en t #P-5417 -1. En

vi ronm en tal Res earch a

nd Te ch nol ogy , Inc ., West Lake Vi

ll age, CA, 1980. Horva th, H., A tmos phe ri c l i ght a bs orption -A re vi ew, Atmos . Envir

on., 27 (A), 3, 293-317, 1993. Japar, S.M., Szkarlat, A.C., Gor se, Jr., R.A., Heyerdah l, E.K., Johns on, R.L., Rau, J.A., and Huntzicker, J.J. Comparison of solv ent extract ion and thermal opt ical carbon analy

sis methods : Ap

pli cation to di ese l

ve hi cle ex ha ust ae rosol

. Environ. Sci. Technol

. 18 : 231- 234, 1984. Low en tha l , D. H., Rog ers , C. F. , Sa

xe na , P., W ats on, J.G ., a

nd Ch ow, J .C. , Sens i

ti vi ty of estim ated ligh t extinction coeffi

cien ts t o model assum

ptions and measurem

ent erro rs, Atmos . Envir

on., 29 , 751-766, 1995. Mac i as, E.S., Z

wicker, J .O. an

d W hi te, W.H ., Regi

onal ha ze c ase studi es i n the south

western U.S.-II.s ource c ontri

buti ons, Atmos

Envir on., 15 , 1987-1997, 1981. Malm, W. C. , I yer, H. , Wa t so n, J. , a nd La t imer, D .A. , S ur vey of a va riet y of re cep t or mod eling tech n i qu es , In Tra n sa cti on s of th e A WMA /EPA In ’l Sp ec i al ty Con f eren ce on Visi b i l i ty and Fi ne Particl es, edi ted by C.V. Mathai , Ai

r and Waste Managem

ent Ass ociati on, 1989. Mal m, W .C., Sisler J.F., Huff ma n D., Eldred, R.A., and C ahi ll , T.C., Spatial

and seas onal

trends i n pa rtic l e concen

tration and opti cal

ex tin cti on i n the U.S. J. Geophys. Res. 99 (D1):1347- 1370, 1994a. Mal m , W.C . Geb

ha rt, K.A ., Molenar, J.V ., Cah i l l , T.A., El

dred, R .A., a

nd H uf f man , D., Exa mini ng t he r elat ionship be t wee n at mosp her ic aer os ols a nd light ext inctio n at Mo unt Rai ni er an d North C asc ades

National Parks , Atmos . Envir

on., 28 , 3 47- 360 , 1 994 b. Malm, W. C. , Mo lenar, J.V ., Eldr ed, R. A., and S isler, J.F ., Exa mini ng t he r elat ionship a mong atm ospheric aerosol s an

d li ght s catteri

ng a nd e xti nction i n the Gra nd C an y on A rea, J. Geophys . Res., 101 (D14), 19251-19265, 1996. Malm, W. C. and Kr eidenw eis, S .M. , T he effect s o f mode ls of ae ro so l hygro sco picit y on t he apportionm

en t of ex tin cti on, Atmos . Envir

on., 31 , 1965-1976, 1997.Guidance f or Tracking Progress Under the Regional Haze Rule

5 - 3 Mal m, W .C., Day, D., and Krei denweis, S.M., Comparis on of m easured and recons

truct ed scattering duri

ng an in tensi ve f ie ld s tudy at Great Smoky Mountains National Park, paper #97-WA70.02, presen

ted at t he A

ir an d Waste Man

agem ent 90 th An

nual Meetin g, Pittsburgh, PA, 1997. Malm, W. C. , E xamining the r elat ionship be t wee n aer os ol co ncent ra t ion and par t ial scat t er ing eff ic ie nci es near the Gran

d Cany on, Presented at t he 91 st

Annual Me et ing o f the Air and Waste Man

agem ent Ass ociati on, Pittsburgh, PA, 1998. Mal m, W .C., Day, D., and Krei denweis, S.M. Ligh

t scatt erin g characteri stics of

aerosols as a fun ct io n o f r ela t ive hu midit y: p ar t I

- - A c o mpa r iso n o f mea su r ed sc at t er ing an d a er o so l conc en trations us i

ng th eoretical model s. J. Air and Waste Management Association , 50, 686-700, 2000a. Mal m, W .C., Day, D., and Krei denweis, SM., Ligh

t scatt erin g characteri stics of

aerosols at am bient and as a

fun ction of rel

ative hum idi ty: part II—a comparis on of m easured sca tterin g an d aeros ol c once

ntrati ons usi ng s tatis tic al model s. J. Air and W

aste Management Association, 50 , 1 74- 182 , 2 000 b. Ma lm, W. C. and Da y, D .E . E st imat es o f ae ro so l sp ec ies s ca t t er ing c har ac t er ist ics a s a func t io n o f relati ve hum i di ty. Atmos. Environ ., 35, 2845-2860, 2001. Marpl e, V.A.; Rub ow, K.L.; Beh m , S.M. A m

i croorif i ce un i form deposi t im pactor (MOUDI): des cri pti on, ca l i bra tion , and use

. Aerosol Science and Technology , 14, 434, 1991. Mc Do w, S. R. ; V ar t ian en , M. ; S un , Q. ; H o ng , Y. ; Y ao , Y. ; Ka men s, R. M. Co mbu st io n a er o so l water c onten

t and i ts ef f ect on p oly

cy cl i c arom ati c h y drocarb on rea

cti vi ty. Atmos. Environ. 29 , 791-797, 1994. McMurry , P.H.and Zhan

g, X. Optical

propert ie s of Los A

ngel es aerosols: an

anal ys is of data acqui red durin g SCAQS. Fi

nal Report o n Project SCAQS-5-8 to t he Coordin ating Research Council, A

tlanta, Georgia, Un

iv ersi ty of Mi nne apoli s, Mi

nne sota, 1991. McM urry, P.H., Zh

ang, X., L e, C.-T., Is sue s i n aerosol meas urem en t for optics a sse ssm

en ts, J. Geophys . Res., 101 , 19189-19197. Oui mette, J.R. a

nd F l agan , R.C., Th e ex tin cti on coef f i eci en t of m ul tic omp onen

t aerosol s, Atmos. Envir on., 16 , 2405-2419, 1982.Guidance f or Tracking Progress Under the Regional Haze Rule

5 - 4 Pilin is, C. , Pa nd is, S. N. , an d S ein field , J. H. , Se nsit ivit y o f dir ec t clima t e fo r cin g b y at mo sp he r ic aerosols to aerosol

si ze a nd c omp osi

tion , J. Geo

phys . Res., 100 (D9), 18739-18754, 1995. Pit chfo rd , M. L. a nd Ma lm, W.C. , D evelo pment and a pplicat ions o f a st anda rd visual index, Pr ese nt ed a t t he Co nfere nce o n Visibil ity and F ine Par t icles, Air and Wa st e Ma nage ment As soci ati on, Vi en na , Au stri a, Septem

ber, Atmos . Envir

on., 28 (5), 1049-1054, 1994. Pitchf ord, M.L. and McMurry, P.H. Relationsh ip b etween m

easured water vapor growt h an d chem i stry of a tmos phe ri c aerosol

f or Gran d Can y on, A ri zona , i n wi nter 1 990. Atmos. Environ

. 28 , 827-839, 1994. Saxena, P., an

d Peters on, T.W ., The

rm ody na m i cs of m ul tic omp onen

t el ectrol y tic aerosols, J. Coll oid Int erfac e Sci., 79 , 496-510, 1981. Sax en a P. , Hudi sche

ws ky j , A .B. , Se i gneu

r, C ., a nd Sei nf el d, J .H. , A com pa rati ve study of equi l i bri um approac he s to the chem

i cal characterization of

sec onda ry aerosols, Atmos. Envir on., 20 , 1471-1483, 1986. Sa xe na , P. , Mu elle r , P. K. , Kim, Y. P. , Se infe ld, J. H. , an d K o ut r ak is, P. , Co up ling t he rmo dyn amic theory wi th m eas urem en ts to cha racteri ze acidi ty of atm ospheric parti

cles, Aeroso l Sci. Tech nol., 19 , 279-293, 1993. Saxena, P. Hi

l dem an n, L .M.; McM

urry, P.H.; Sei

nf eld, J.H.Organ

i cs a l ter hy groscopi c b ehavi or of a tmos phe ri c parti cles. Journal of Geophysical Research , 100 , 18755-18770, 1995. Sloane, C.S., Optical propert ies of aerosols-comparison of m easurements with m

odel calcul

ations, Atmos . Envir

on., 17 , 409-416, 1983. Sloane , C.S., Optic al

properties of

aerosols of

m i xe d com posi tion , Atmos . Envir

on., 18 , 871-878, 1984. Sloane , C.S., Ef

f ects of com posi tion on ae rosol l i ght s catteri

ng e f f i ciencies, Atmos . Envir

on., 20 , 1025, 1986. Sloane , C.S., and Wolf

f, G. T., Change i

n aerosol optical

propert ie s wi

th chan ge i n ch em ic al com posi tion , Atmos . Envir

on., 19 , 669-680, 1985. Stelson, A.W .; Sei

nf el d, J.H., Relativ

e hum idi ty an d temperature dependen

ce of the am

moni um nitra te dissoc iation c onst ant ; Atmos . Envir on., 16(5) , 983-992, 1982.Guidance f or Tracking Progress Under the Regional Haze Rule

5 - 5 Swiet li cki, E .; Zho u, J .C. ; Berg , O. H.; Ma rt insson, B .G. ; Frank, G.; C eder felt, S .I .; De sek, U.; Be rne r , A. ; B irmilli, W. ; Wie de ns o hle r , A. ; Y us ki ew icz , B. ; B o we r , K. N. A c lo su r e s t ud y of s ub- m i crom eter ae rosol particle h y groscopi c b ehavi or. Atmospheric Research , 50 (3- 4) , 205-240, 1999. Tan g, I.N., Chem

i cal and si ze e f f ects of hy groscopi c aerosol s on l

i ght s catteri

ng c oef f i cien ts, J. Geophys . Res., 101 , (D14), 19245-19250, 1996. Tom b ach , I. A n d Th ur sto n , S. A ., Th e q

ual i ty of th e S CE NE S m ea su re men ts: th e rol es

of da ta qua lity go als and evo lving te chno log y, in Proc. Aerosols andAtmospheric O ptics: Radiat ive Ba lanc e and

Vis ual Air

Quality, Air

and W aste Manag emen t Ass oc., Pittsburgh, PA, 1994. Tri j oni s, J.C ., and Pi

tchf ord, M., Prelimi nary ext incti on bud get resu lts f

rom the RES OLVE program edit ed by P. S. Bhar dwa ja, Air a nd Was t e Ma nage ment As so ciat ion, Pit t sbur gh, PA, 1987. Trij oni s, J.C., Ma

l m , W.C., Pi

tchf ord, M., Whi

te, W.H., Charl son, R., an d Husar, R ., Vis i

bi l i ty: Exist ing and hist or ical co ndit ions- cau ses a nd effec t s, in Sate Sci. State Technol. Rep. 24, Natl. Aci d Precip. A ssessm

ent Program, Wash

in gto n, D.C., 1990. Van de Hulst, H.C., Light scattering b y s ma ll particles, John W

il ey & Sons, New York, NY, 1957. Wa tson, J .G., Ch

ow, J.C., R

i chards , L.W ., Haas e, D.L ., McD ade, C ., Dietri ch , L.D., M oon, D., Chi nki n, L., and Sl

oane, C., The 1989-90 Phoeni x urban haze study . Volum

e I: program pla n. DRI documen

t 8931.1F, prepared for Arizona De partment of Env

ironm ental Quality, Phoeni

x, AZ , by Desert Research Institute, Reno, NV, 1990. Wexl er, A . and Sei

nf eld, J., Se cond-gen

eration i norga ni c aerosol model , Atmos . Envir

on., 25 A, 2731, 1991. Waggoner, A.P., Weiss, R.E., Ahl quis t, N.C. , Covert, D. S., wil l, S., and Ch

arls on, R.J., Opt ic al characteri sti cs of

atm ospheric aerosol s, Atmos . Envir on., 15 , 1891-1909, 1981. White, W.H ., and R obe rt s, P .T ., On t he nat ur e and or igins of visibili t y red ucing a er os ols in t he Los A nge l es A i r Bas i n, Atmos . Envir

on., 11 , 803-812, 1977.Guidance f or Tracking Progress Under the Regional Haze Rule

5 - 6 Wh i te, W.H., On the theoreti cal and e m pi ric al bas i s f or apportioni

ng ex tin ction by aerosol s: a cri tic al revi ew, Atmos. Environ. , 20 , 1659-1672. White, W.H ., Co nt ribut ions t o light sca t t er ing, I n: Acidic D epo sitio n: S t at e o f Science and Te chno log y Repo rt 24, J. T rijonis ( lead a ut hor ), Nat ional Acid P re cipit at ion Ass essment Program , Wa sh i ngton , DC, pp 85-10 2, 1990

. Zhan g, X.Q.; McMurry, P.H.; Heri ng, S.V.; Casucci

o, G.S . Mix

in g characteri stics a

nd water conten t of su bm i cron a erosol s m eas ured i n L os An gel es a nd a t the Gra nd C an y on. Atmos

. Envir on. 27A , 1593-1607, 1993. Zh an g, X. Q. ; T ur pi n, B. J. ; M cM ur ry, P

. H. ; H er ing , S

. V. ; S t o lze nbu r g, M. R. Mie t he o ry evalua t ion o f spec ies co nt ribut ions t o t he 19 90 w inter t ime visi bili t y red uct ion in t he Gr and Can yon . J. Of Air and Waste Management Association , 44 , 153-162, 1994.A - 1 

### APPENDI X A



## Mont hly Sit e-Sp ecific f(RH) Values for Each Mandatory Federal ClassI Area1 U.S . EP A, Int erpola ting Rela tive Humidity W eighting Fa ctor s to C alcu lat e Visibility I mpair ment

and the Eff ec ts o f IMPROV

E Mo ni to r Outl ie rs, pre pare d by Sc ie

nc e Ap pl ic atio nsIn te rnat io nal Corporatio

n, Rale ig h, NC, EPA

Con tract No. 68-D- 98-113, A ugust 30, 2001

. A - 2 

### APPENDI X A Origin of Relative Humidity and f(RH) Values

In t er ms of visibili

t y red uct ion ca use d by fine par t icles, it is app ro pr iate t o t re at re lative hum i di ty d i f f eren tly f or di f f eren t obj ecti ve s. If the ob j ecti ve i s the most rel i ab l e sh ort-term est imate o f visibi

lity, t hen t he measu re d o r e st imated re lative hu midity for t he sp ecific time and lo ca t io n o f t he ae r o so l sp ec iat io n d at a is mo st ap pr o pr iat e. On t he o t he rha nd , if t he o bje ct ive is t o a sses s t he long -t er m change s in man-made visibi lity im pair ment, it is ap pr op riat e t o u se r elat ive hum i di ty th at i s the sam e f or the b ase l i

ne peri od and f uture pe ri ods. In other words , i

t is more appropri ate

to el i m i n ate th e c on f oun di n g e f f ects o f v ar y i n g r el ati v e h um i di ty , if th e pur pos e is to track the visi

bili ty eff ects o f ai r po ll ution emi ssions over extended time peri ods. A n um b er of approach es

werecon si dere d to pre v en

t v ari ati on s i n th e rel ati v e h um i di ty adjus t ment fa ct or fro m confo unding effor t s t o t ra ck p ro gr ess r elat ed t o e mission co nt ro ls. T he sim plest appro ach would use the same typi cal or overall av

erage adjustment factor for all Class I areas at all

tim es. However, this

would en han ce the contrib

utions of h

ygroscopi c particl

e species in dry loc at ions a nd du ring t ypically dr y seaso ns abo ve wha t t hey tr uly shou ld be, while red ucing their contri

butions in moi st locations a

nd seas ons. Such di stort ions of the contrib

utions to haze by hy groscopi c parti cle sp eci es a re un ne ces sary i f a set of Cl

ass I area-spe cif

i c adjustm

en t factors are us ed that ref

l ect se ason

al changesi n re l ati ve hum i di ty. A se co nd ap pr o ac h w o uld be t o r ev iew r ela t ive hu midit y da t a o ve ra lo ng pe r io d o f t ime to deriv e clim atological estim ates for relati

ve h umi dity adj ustmen

t factors. These cli

ma to logical esti mates woul d then b e us ed to esti mate vi si bi l i ty e xti nction coef f i cien ts. The se e sti

mates a re more l ike ly to refl ect “typi cal” rela tive h umi dity at the dif feren t manda to ry F ederal

Cl ass I areas dur ing different t imes of year and, t hus, ar e mor e likely to be mor e ap pr op riat e fo r e st ablishing trends i n v i si bi l i ty a t the m andatory Fed eral Class I area s. Re cen tl y , the U .S. EPA

sp on sor ed a proj ect to ex

am i n e m ea su re d h ourl y re l ati v e h um i di ty data over a 10-year period withi n the Un ited States, t o derive m

onth-speci fi

c clim atological me an hum idi ty correction f

actors for each m

andatory Fede

ral C lass I area. 1 The

resu l ts of th at work are pr es en t ed in t he t ab le b elo w. T he se r ela t ive hu midit y fac t o r s ha ve be en ca lcu lat ed fr o m av aila ble hourly relati ve h umi dity data from 292 National

Weather Servi

ceA - 3

st at ions a cr os s t he 50 St at es a nd t he Dist rict of Co lumbia as we ll as fro m 29 I MPR OVE and IMP ROV E p ro t oc ol mo nito r sit es, 48 C AST Net site s, a nd 13 add itio nal site s ad mini st er ed by t he National Park Se rvi ce. Th e h ourl y RH mea su rem en ts f rom each si te w ere con ve rted to f(RH) values using a nonli near wei ghtin g factor curve, based on a modifi ed am moni um s ulf ate growt h curve. Val

ues above 95% RH were s et equal to the f(RH) corr esponding to 95% RH. For days i n whi ch at least 16 ho ur s o f va lid R H d at a w er e a va ilable , da ily ave r ag es we r e d et er mined fr o m t he se ho ur ly f(RH) va lu es at ea ch sit e. Mo nt hly a ve r ag es we r e t he n c alc ul at ed fr o m t he da ily f(RH) averages at each si te. The m onthly average f(RH) values wer e inte rp olat ed a t 1/ 4- deg re e incre ments using t he i nv erse di stan ce we i ghti

ng te ch ni que (w i th a d i stan ce i nterp ola tion ex ponent of 1):

wh er e t he mo nt hly f(RH) g o f t he gr id c ell is ca lcu lat ed fr o m f(RH) w at t he we at her st at ion, and t he hori zontal di stan ce b etween the gri

d cel l cen ter an d the weath er stati on, x wg , su mmed ove r a ll the weather stations wi

thin a 250-mi le radius with v alid f(RH) values for t hat mont h. I n mo st r eg io ns t he r e is a s ea so na l cyc le o f r ela t ive hu midit y wh ich is a cc o un t ed fo rby t his process of appropriate f(RH) va l uesf or each month of the y ear f rom th e dai l y-average d va

l ues . Thus, the 12 m

onthly -averaged f(RH) va lue s d et er mined in t his w ay fo rea ch Cla ss I ar ea sho uld be use d f or all aerosol spe ciati on da

ta or model

predi cti ons f or that locati on. Howe

ver, a m ore compl ic ated approach has also been i nve stigated, as descri

bed b el ow. The regional h

aze regulation requires separate t racking of v isi bili ty changes f

or t he worst 20 % a n d b est 20 % of

v i si b i l i ty da y s. If th ere is a si gn i f i ca n t cor re l ati on i n an y mon th at a n y si te be t we en da ily r ela t ive hu mid it y an d t he su lfa t e o rnit r at e c o nc en t r at io ns , t he n u se o f t he mo nt hlyaveraged f(RH) will sy

st emat ically

ove r- or unde r- pr edict t he co nt ribut ion t o visibility im pair ment o f t he ae r o so l sp ec ies

. Fo rt un at ely, t his c o nc er n c an be t es t ed at a n umb er o f lo ca t io ns in all regi ons of the c ountry

usi ng th e IMP ROVE

datab ase . If

the u se of

monthl y-average d va

l ueswere found to cause large systematic bi ases in any region of the count ry, the Class I areas i n those regi ons woul d re qui

re two f(RH) val

ues f or each m onth. One val

ue would b e the average f(RH) associ ated with rel

ative hum idi ty condi tions that correspond to the worst 20% and the other val ue asso ciat ed w ith r elat ive humidity co ndit ions t hat co rr esp ond t o t he bes t 20% of t he light ex tin cti on val ues . The ref ore, ther e i s the potential that som e Cl ass I area l ocati ons c oul d requ

i re up to 24 f(RH) val

ues f or use in calcul ating e

xtin ction f or aero sol data.A - 4

Th e U .S. N ati

ona l Par k Se rvi cehas te ste d th

i s p oss i bi l i ty by exam i ni ng da ta f or ea ch of the 1 2 m onths f rom 2 0 m andatory Fed eral Class I area s wh

ere re l ati ve hum i di ty m eas urem en ts are ma de. In nearl

y a ll cases, no statistically

signifi cant correlations

were found b etween m

easured concen trations of

SO 4 2- , NO 3 - and [SO 4 2- + NO 3 - ] vs. daily val ues of rel ative hum idi ty i n a l arge maj ority of months. Furthermore, decivi ew calcul ations were made usin

g day-speci fi

c vs. clim atological val ues f or t he rel ative hum idi ty adj ustmen

t factor for each of 10 y

ears i n 15 mandat or y Feder al Class I ar eas . I n 14 o f the 15 a re as, litt le if any dif fere nce w as o bser ved in t he yea r-to-y ea r ca l cul ati ons f or th e m ea n d ec i vi ew va l ue s f or th e 2 0% wors t an

d 20 % b es t da

y s, n or was there any diff

erence in the tr ends. Some dif

ference i n the mean

decivi ew val ue for t he worst 20% days w as o bser ved in o ne manda t or y Feder al Class I ar ea. Ho weve r, t he o ver all tr end in t he mea n wo rs t and bes t de civie w va lue s fo r t his s it e w as similar us ing t he t wo t ype s o f f(rh) va l ues . Th es e re sul

ts s ugg es t the

re i s a rel ati ve l y we ak correl ati on b etw een h

y gros cop i c c om

ponen ts of PM an d re l ati ve hu m i di ty an d that the choi

ceof a “ cl i matol ogical ” v s. “

da y-spe cif i c”meth od f or computin g f(RH) has litt le app ar ent effect on o bser ved t re nds in visibil ity. C ons equ ent ly, the sim pler cl im ato logical appro ach i s used in

regional h

aze calcul ations.A - 5

Tabl e A-1 V alu es f

or f(RH ) Dete rmined f

ro m the Gr owth of

Amm onium

Sulf ate
RH f(RH) RH f(RH) RH f(RH) 1 1.00 34 1.00 67 2.03 2 1.00 35 1.00 68 2.08 3 1.00 36 1.00 69 2.14 4 1.00 37 1.02 70 2.19 5 1.00 38 1.04 71 2.25 6 1.00 39 1.06 72 2.31 7 1.00 40 1.08 73 2.37 8 1.00 41 1.10 74 2.43 9 1.00 42 1.13 75 2.50 10 1.00 43 1.15 76 2.56 11 1.00 44 1.18 77 2.63 12 1.00 45 1.20 78 2.70 13 1.00 46 1.23 79 2.78 14 1.00 47 1.26 80 2.86 15 1.00 48 1.28 81 2.94 16 1.00 49 1.31 82 3.03 17 1.00 50 1.34 83 3.12 18 1.00 51 1.37 84 3.22 19 1.00 52 1.41 85 3.33 20 1.00 53 1.44 86 3.45 21 1.00 54 1.47 87 3.58 22 1.00 55 1.51 88 3.74 23 1.00 56 1.54 89 3.93 24 1.00 57 1.58 90 4.16 25 1.00 58 1.62 91 4.45 26 1.00 59 1.66 92 4.84 27 1.00 60 1.70 93 5.37 28 1.00 61 1.74 94 6.16 29 1.00 62 1.79 95 7.40 30 1.00 63 1.83 96 9.59 31 1.00 64 1.88 97 14.1 32 1.00 65 1.93 98 26.4 33 1.00 66 1.98Guidance for Track ing Progr ess U nder the Regional Haze R ule

A - 6



### Ta ble A -2 Recommended Monthly Site-Specific f(RH) Values for E ach Mandatory Federal Class I Area,
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Class I Area S i t e Na m e Code Sit e St LAT LONG f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) Aca dia Aca dia 1 ACAD1 ME 44.38 -68.3 7 3.2 2.8 2.8 3.2 3.2 3.3 3.7 3.7 3.9 3.5 3.4 3.5 Agua Tib ia Agua Tib ia 100 AGTI 1 CA 33.38 -116. 87 2.4 2.3 2.4 2.2 2.2 2.2 2.2 2.3 2.3 2.2 2.1 2.2 Alpine Lakes Snoqua lmie Pass 80 SNPA1 W A 47.38 -121. 37 5.3 5.0 3.7 3.6 4.2 3.1 3.5 3.4 3.8 4.9 5.5 5.3 Anaconda - Pi ntl er Sula 71 SULA1 MT 45.88 -114. 12 3.4 3.0 2.6 2.3 2.3 2.2 1.9 1.8 2.0 2.5 3.3 3.4 A n s e l A d a m s Kaiser 110 KAI S1 CA 37.13 -119. 12 3.0 2.7 2.5 2.1 2.0 1.7 1.7 1.7 1.8 1.9 2.3 2.7 Arches Canyonl ands 50 CANY1 UT 38.38 -109. 87 2.6 2.3 1.8 1.6 1.5 1.2 1.3 1.5 1.5 1.6 2.0 2.3 Badlands Badlands 59 BADL1 SD 43.63 -101. 87 2.8 2.8 2.8 2.6 2.8 2.7 2.4 2.4 2.3 2.3 2.9 2.8 Bandelier Bandelier 33 BAND1 NM 35.88 -106. 37 2.3 2.1 1.8 1.6 1.6 1.4 1.7 2.0 1.9 1.7 2.0 2.3 Bering Sea (a) Big Bend Big Bend 31 BI BE1 T X 29.38 -103. 12 1.8 1.7 1.5 1.4 1.5 1.5 1.6 1.8 1.9 1.7 1.7 1.7 Black Cany on of t he Gunnison W eminuche 55 W EM I1 CO 37.63 -107. 87 2.5 2.3 2.0 1.7 1.7 1.5 1.7 2.0 1.9 1.7 2.2 2.4 Bob M arsh all Monture 73 MON T 1 MT 47.13 -113. 12 3.3 2.9 2.6 2.4 2.4 2.4 2.1 2.0 2.3 2.7 3.2 3.3 Bosque del Apache Bosque del Apache 38 BOAP1 NM 33.88 -106. 87 2.2 2.0 1.6 1.4 1.4 1.3 1.7 1.9 1.9 1.6 1.8 2.2 Boundary

W aters Canoe Area Bounda ry W ate rs 23 BOW A1 MN 47.88 -91.6 2 2.9 2.6 2.6 2.3 2.5 2.8 3.0 3.1 3.2 2.7 3.1 3.1 Breton Breton 20 B R ET1 LA 29.13 -89.1 2 3.5 3.3 3.3 3.3 3.4 3.6 3.8 3.8 3.6 3.4 3.4 3.5 Bridger Bridger 65 BRI D1 W Y 42.88 -109. 87 2.5 2.3 2.3 2.1 2.1 1.8 1.5 1.5 1.8 2.0 2.5 2.4 Brigant ine Brigant ine 5 B R I G 1 NJ 39.38 -74.3 7 2.9 2.6 2.7 2.6 2.9 3.0 3.2 3.4 3.4 3.2 2.8 2.9 Bry ce Canyon Bry ce Canyon 49 BRCA1 UT 37.63 -112. 12 2.6 2.4 2.0 1.6 1.5 1.3 1.3 1.5 1.5 1.6 2.0 2.4 Cabinet Mountai ns Cabinet Mountai ns 75 C AB I1 MT 47.88 -115. 62 3.7 3.2 2.8 2.5 2.5 2.4 2.1 2.1 2.4 2.9 3.6 3.8 Caney Creek Caney Creek 29 CACR1 AR 34.38 -94.1 2 3.3 3.0 2.7 2.8 3.2 3.2 3.0 3.0 3.2 3.2 3.1 3.3 Canyonl ands Canyonl ands 50 CANY1 UT 38.38 -109. 87 2.6 2.3 1.8 1.6 1.5 1.2 1.3 1.5 1.5 1.6 2.0 2.3 Cap e Ro m ain Cap e Ro m ain 15 ROMA1 SC 32.88 -79.6 2 3.2 2.9 2.8 2.7 2.9 3.3 3.3 3.6 3.5 3.4 3.1 3.1 Capitol Reef Capitol Reef 52 C AP I1 UT 38.38 -111. 37 2.7 2.5 2.0 1.7 1.6 1.4 1.4 1.6 1.6 1.7 2.1 2.5 Caribou Las sen Volc anic 90 L A VO1 CA 40.63 -121. 62 3.7 3.1 2.8 2.4 2.3 2.1 2.0 2.0 2.1 2.3 3.1 3.5 Carlsbad Cav erns Guadalupe Mount ains 32 GUM O 1 T X 31.88 -104. 87 2.4 2.0 1.6 1.4 1.6 1.5 1.9 2.2 2.4 1.7 1.9 2.3 Cha ssa how itzka Cha ssa how itzka 18 CHAS1 FL 28.63 -82.6 2 3.5 3.2 3.1 3.0 3.0 3.5 3.5 3.7 3.7 3.5 3.4 3.6 Chi ri cah ua NM Chiricahua 39 CHI R1 AZ 32.13 -109. 37 2.0 1.9 1.6 1.2 1.2 1.1 1.7 2.0 1.7 1.5 1.6 2.1 Chiricahua W Chiricahua 39 CHI R1 AZ 32.13 -109. 37 2.0 1.9 1.6 1.2 1.2 1.1 1.7 2.0 1.7 1.5 1.6 2.1 Co hutta Co hutta 12 COHU1 G A 34.88 -84.6 2 3.4 3.1 2.9 2.7 3.2 3.6 3.6 3.7 3.7 3.5 3.2 3.4 Cra ter Lake Cra ter Lake 86 CRLA1 O R 42.88 -122. 12 4.6 4.0 3.7 3.5 3.2 2.9 2.6 2.7 2.9 3.6 4.6 4.7 Craters of

the Mo on Craters of the Mo on 69 CRM O 1 ID 43.38 -113. 62 3.1 2.7 2.3 2.0 2.0 1.8 1.4 1.4 1.6 2.0 2.7 3.0 Cucam onga San Gabriel 93 SAGA1 CA 34.38 -118. 12 2.6 2.5 2.5 2.2 2.2 2.1 2.2 2.2 2.3 2.2 2.2 2.3 Den ali Den ali 102 DENA1 AK 63.75 -148. 75 2.5 2.3 2.1 1.9 1.8 2.1 2.5 2.9 2.8 3.0 2.9 3.0Guidance for Track ing Progr ess U nder the Regional Haze R ule



### Ta ble A -2 Recommended Monthly Site-Specific f(RH) Values for E ach Mandatory Federal Class I Area,
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Class I Area S i t e Na m e Code Sit e St LAT LONG f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH)

A - 7 Desolati on Bli ss 95 BLI S1 CA 38.88 -120. 12 3.2 2.8 2.5 2.0 1.9 1.6 1.5 1.5 1.7 1.8 2.4 3.0 Diamond Peak Cra ter Lake 86 CRLA1 O R 42.88 -122. 12 4.6 4.0 3.7 3.5 3.2 2.9 2.6 2.7 2.9 3.6 4.6 4.7 Dolly Sods Dolly Sods 8 DOS O 1 W V 39.13 -79.3 7 3.0 2.7 2.7 2.5 3.5 3.1 3.2 3.5 3.5 3.1 2.8 3.1 Dom e Land Dom e Land 109 DOME1 CA 35.63 -118. 12 2.6 2.3 2.2 1.9 1.9 1.8 1.8 1.8 1.9 1.9 2.0 2.2 Eagle Cap Stark ey 76 STAR1 O R 45.13 -118. 62 4.3 3.8 3.2 2.9 2.7 2.4 2.0 2.1 2.4 3.3 4.2 4.5 Eagle s Nest W hit e Riv er 56 W HRI 1 CO 39.13 -106. 87 2.2 2.2 2.0 2.0 2.0 1.7 1.8 2.1 2.1 1.8 2.1 2.1 Emigrant Yos em ite 96 YOSE1 CA 37.63 -119. 62 3.0 2.9 2.7 2.2 2.1 1.7 1.5 1.5 1.6 1.8 2.3 2.7 Ever glades Ever glades 19 EVER1 FL 25.38 -80.6 2 2.6 2.5 2.5 2.3 2.3 2.6 2.5 2.8 2.9 2.7 2.5 2.6 Fit zpat rick Bridger 65 BRI D1 W Y 42.88 -109. 87 2.5 2.3 2.3 2.1 2.1 1.8 1.5 1.5 1.8 2.0 2.5 2.4 Flat Tops W hit e Riv er 56 W HRI 1 CO 39.13 -106. 87 2.2 2.2 2.0 2.0 2.0 1.7 1.8 2.1 2.1 1.8 2.1 2.1 Ga liuro Chiricahua 39 CHI R1 AZ 32.13 -109. 37 2.0 1.9 1.6 1.2 1.2 1.1 1.7 2.0 1.7 1.5 1.6 2.1 Gates of t he Mount ains Gates of t he Mount ains 74 GAM O 1 MT 46.88 -111. 62 2.8 2.5 2.4 2.3 2.3 2.2 2.0 1.9 2.1 2.4 2.7 2.7 Ge arhar t Mountain Cra ter Lake 86 CRLA1 O R 42.88 -122. 12 4.6 4.0 3.7 3.5 3.2 2.9 2.6 2.7 2.9 3.6 4.6 4.7 Gila G ila C liffs 42 GICL1 NM 33.13 -108. 12 2.1 1.9 1.6 1.3 1.3 1.2 1.9 1.9 1.8 1.6 1.8 2.2 Glacier Glacier 72 GLAC1 MT 48.63 -114. 12 3.9 3.4 3.1 2.9 3.0 3.0 2.5 2.5 3.0 3.3 3.7 3.8 Glacier Peak North Cascades 81 NOCA1 W A 48.63 -121. 12 4.5 4.1 3.6 3.4 3.3 3.0 2.9 3.1 3.5 4.2 4.7 4.7 Go at Roc ks W hit e Pass 79 W HPA1 W A 46.63 -121. 37 4.8 4.2 3.8 3.6 3.4 3.1 2.9 3.0 3.5 4.3 4.9 5.0 Grand Canyon Grand Canyon, Hance 48 GRCA2 AZ 35.88 -111. 87 2.5 2.4 2.0 1.6 1.4 1.2 1.4 1.7 1.7 1.7 2.0 2.3 Grand Teton Yellowsto ne 66 YELL2 W Y 44.63 -110. 37 2.5 2.3 2.2 2.1 2.1 1.9 1.7 1.6 1.8 2.1 2.4 2.5 Gr eat G ulf Gr eat G ulf 4 GRGU1 NH 44.38 -71.1 2 2.8 2.6 2.6 2.8 2.9 3.0 3.3 3.5 3.6 3.2 3.0 2.9 Great Sand Dunes Great Sand Dunes 53 GRSA1 CO 37.63 -105. 62 2.4 2.3 2.0 1.9 1.9 1.7 1.9 2.3 2.2 1.9 2.3 2.4 Great Smoky Mou ntai ns Great Smoky Mou ntai ns 10 GRSM1 T N 35.63 -83.8 7 3.6 3.0 3.0 2.8 3.2 3.6 3.6 3.6 3.7 3.4 3.3 3.5 Guadalupe Mount ains Guadalupe Mount ains 32 GUM O 1 T X 31.88 -104. 87 2.4 2.0 1.6 1.4 1.6 1.5 1.9 2.2 2.4 1.7 1.9 2.3 Hale akala Hale akala 108 HALE1 HI 20.75 -156. 25 2.7 2.6 2.5 2.5 2.4 2.3 2.4 2.4 2.3 2.5 2.7 2.6 Hawaii Volcanoes Hawaii Volcanoes 107 H A VO1 HI 19.25 -155. 25 3.0 2.9 2.9 2.9 2.9 2.9 3.0 3.0 3.0 3.0 3.3 3.0 Hells Cany on Hells Cany on 77 HECA1 O R 44.88 -116. 87 3.7 3.1 2.4 2.1 2.0 1.8 1.5 1.4 1.6 2.2 3.4 3.8 Hercules - Glade Hercules - Glade 28 HEGL1 MO 36.63 -92.8 7 3.2 2.9 2.6 2.6 3.0 3.0 3.0 3.0 3.2 2.9 3.0 3.2 Hoover Hoover 97 HOO V1 CA 38.13 -119. 12 3.1 2.7 2.5 2.0 1.9 1.6 1.5 1.5 1.6 1.8 2.3 2.8 Isle Royale Isle Royale 25 I SLE1 MI 47.38 -88.1 2 3.1 2.6 2.7 2.5 2.4 2.9 3.2 3.4 3.5 2.9 3.3 3.3 James Rive r Face James Rive r Face 7 J AR I1 VA 37.63 -79.6 2 2.9 2.7 2.6 2.4 2.9 3.1 3.2 3.3 3.4 3.0 2.7 3.0 Jarbidge Jarbidge 68 JARB1 NV 41.88 -115. 37 2.9 2.6 2.1 2.1 2.2 2.0 1.6 1.4 1.4 1.6 2.4 2.8 Joh n Muir Kaiser 110 KAI S1 CA 37.13 -119. 12 3.0 2.7 2.5 2.1 2.0 1.7 1.7 1.7 1.8 1.9 2.3 2.7 Joshua Tree Joshua Tree 101 JOSH1 CA 34.13 -116. 37 2.4 2.3 2.3 2.0 2.0 1.9 1.5 2.0 2.0 2.0 1.9 2.1Guidance for Track ing Progr ess U nder the Regional Haze R ule



### Ta ble A -2 Recommended Monthly Site-Specific f(RH) Values for E ach Mandatory Federal Class I Area,
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Class I Area S i t e Na m e Code Sit e St LAT LONG f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH)

A - 8 Joy ce Kil mer - Sli ckro ck Great Smoky Mou ntai ns 10 GRSM1 T N 35.63 -83.8 7 3.6 3.0 3.0 2.8 3.2 3.6 3.6 3.6 3.7 3.4 3.3 3.5 Kaiser Kaiser 110 KAI S1 CA 37.13 -119. 12 3.0 2.7 2.5 2.1 2.0 1.7 1.7 1.7 1.8 1.9 2.3 2.7 Kalm iops is Kalm iops is 89 KALM1 O R 42.63 -124. 12 4.5 3.9 3.7 3.5 3.3 3.1 2.9 3.0 3.1 3.6 4.4 4.4 Kings Cany on Sequ oia 98 SEQU1 CA 36.38 -118. 87 2.9 2.6 2.5 2.2 2.1 1.8 1.7 1.7 1.8 1.9 2.3 2.5 La G arita W eminuche 55 W EM I1 CO 37.63 -107. 87 2.5 2.3 2.0 1.7 1.7 1.5 1.7 2.0 1.9 1.7 2.2 2.4 Las sen Volc anic Las sen Volc anic 90 L A VO1 CA 40.63 -121. 62 3.7 3.1 2.8 2.4 2.3 2.1 2.0 2.0 2.1 2.3 3.1 3.5 Lava Beds Lava Beds 87 LABE1 CA 41.63 -121. 62 4.0 3.4 3.1 2.8 2.6 2.4 2.2 2.2 2.4 2.8 3.6 4.0 Linv ill e Gorge Linv ill e Gorge 13 L I GO1 NC 35.88 -81.8 7 3.2 3.0 2.9 2.7 3.2 3.6 3.6 3.9 3.9 3.4 3.1 3.2 Lostwood Lostwood 62 LOS T 1 ND 48.63 -102. 37 3.0 2.9 3.0 2.3 2.2 2.5 2.5 2.3 2.2 2.4 3.2 3.2 Lye Brook Lye Brook 3 LYB R1 VT 43.13 -73.1 2 2.8 2.6 2.7 2.6 2.8 2.9 3.1 3.3 3.4 3.2 2.9 2.9 Ma m m ot h C ave Ma m m ot h C ave 9 MACA1 KY 37.13 -86.1 2 3.3 3.0 2.9 3.0 4.1 4.7 4.6 3.5 3.5 3.2 3.1 3.4 Marble Moun tain T rinity 104 TRI N1 CA 40.88 -122. 87 4.0 3.4 3.2 2.9 2.8 2.6 2.5 2.6 2.7 2.9 3.6 3.9 Maroo n Bel ls - Snowmass W hit e Riv er 56 W HRI 1 CO 39.13 -106. 87 2.2 2.2 2.0 2.0 2.0 1.7 1.8 2.1 2.1 1.8 2.1 2.1 Mazat zal I ke's Back bone 46 I KBA1 AZ 34.38 -111. 62 2.2 2.0 1.8 1.4 1.3 1.2 1.4 1.7 1.6 1.5 1.8 2.1 Medic ine La ke Medic ine La ke 63 MELA1 MT 48.38 -104. 37 3.0 2.9 2.9 2.2 2.2 2.4 2.4 2.1 2.2 2.3 3.1 3.1 Mesa Verde Mesa Verde 54 MEVE1 CO 37.13 -108. 37 2.8 2.6 2.2 1.7 1.7 1.3 1.7 2.0 1.9 1.8 2.2 2.6 Mingo Mingo 26 M I NG1 MO 36.88 -90.1 2 3.2 2.9 2.7 2.6 2.9 3.0 3.1 3.1 3.2 2.9 3.0 3.2 Mission Moun tai ns Monture 73 MON T 1 MT 47.13 -113. 12 3.3 2.9 2.6 2.4 2.4 2.4 2.1 2.0 2.3 2.7 3.2 3.3 Mokelumne Bli ss 95 BLI S1 CA 38.88 -120. 12 3.2 2.8 2.5 2.0 1.9 1.6 1.5 1.5 1.7 1.8 2.4 3.0 Moose horn Moose horn 2 MOOS1 ME 45.13 -67.3 7 3.0 2.7 2.7 2.9 2.9 3.1 3.5 3.6 3.8 3.3 3.2 3.2 M o u n t A d a m s W hit e Pass 79 W HPA1 W A 46.63 -121. 37 4.8 4.2 3.8 3.6 3.4 3.1 2.9 3.0 3.5 4.3 4.9 5.0 Mount Bal dy Mount Bal dy 43 BAL D1 AZ 34.13 -109. 37 2.2 2.1 1.7 1.4 1.3 1.2 1.6 1.9 1.7 1.6 1.9 2.3 Mount Hood Mount Hood 85 MOH O 1 O R 45.38 -121. 87 4.6 4.1 3.7 3.6 3.2 3.0 2.7 2.8 3.2 4.1 4.8 4.8 Mount Jef

ferson Th ree Sisters 84 THSI1 O R 44.38 -122. 12 5.3 4.6 4.4 4.3 3.8 3.4 2.7 2.7 3.1 4.3 5.2 5.3 Mount Rai nier Mount Rai nier 78 MORA1 W A 46.88 -122. 12 5.3 4.7 4.4 4.3 3.9 3.7 3.4 3.6 4.2 5.1 5.5 5.6 Mount W ashingt on Th ree Sisters 84 THSI1 O R 44.38 -122. 12 5.3 4.6 4.4 4.3 3.8 3.4 2.7 2.7 3.1 4.3 5.2 5.3 Mount Zi rkel Mount Zi rkel 58 MO Z I1 CO 40.63 -106. 62 2.2 2.2 2.0 2.1 2.2 1.8 1.7 1.8 2.0 1.9 2.1 2.1 Mountai n Lakes Cra ter Lake 86 CRLA1 O R 42.88 -122. 12 4.6 4.0 3.7 3.5 3.2 2.9 2.6 2.7 2.9 3.6 4.6 4.7 Nor th Abs aroka Nor th Abs oraka 67 NOAB1 W Y 44.63 -109. 37 2.4 2.2 2.2 2.1 2.1 1.9 1.6 1.5 1.8 2.0 2.3 2.4 North Cascades North Cascades 81 NOCA1 W A 48.63 -121. 12 4.5 4.1 3.6 3.4 3.3 3.0 2.9 3.1 3.5 4.2 4.7 4.7 Okefenoke e Okefenoke e 16 OKEF1 G A 30.63 -82.1 2 3.3 3.0 3.2 3.0 3.2 3.8 3.4 3.6 3.6 3.4 3.3 3.4 Olym pic Olym pic 83 OLYM1 W A 48.13 -122. 87 4.2 3.9 3.6 3.5 2.9 3.2 2.7 3.3 3.8 4.3 4.5 4.4 Otter Cree k Dolly Sods 8 DOS O 1 W V 39.13 -79.3 7 3.0 2.7 2.7 2.5 3.5 3.1 3.2 3.5 3.5 3.1 2.8 3.1Guidance for Track ing Progr ess U nder the Regional Haze R ule



### Ta ble A -2 Recommended Monthly Site-Specific f(RH) Values for E ach Mandatory Federal Class I Area,
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Class I Area S i t e Na m e Code Sit e St LAT LONG f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH)

A - 9 Pasayt en Pasayt en 82 PASA1 W A 48.38 -119. 87 4.6 4.1 3.5 3.3 3.2 2.9 2.8 2.9 3.4 4.1 4.7 4.8 Pecos W heeler Peak 35 W HPE1 NM 36.63 -105. 37 2.4 2.2 1.9 1.8 1.8 1.6 1.8 2.1 2.1 1.8 2.2 2.4 Petr if ied Fo rest Petr if ied Fo rest 41 P E FO1 AZ 35.13 -109. 87 2.4 2.1 1.7 1.4 1.3 1.2 1.5 1.8 1.6 1.6 2.0 2.3 Pine M ountain I ke's Back bone 46 I KBA1 AZ 34.38 -111. 62 2.2 2.0 1.8 1.4 1.3 1.2 1.4 1.7 1.6 1.5 1.8 2.1 Pinnacles Pinnacles 92 PI NN1 CA 36.38 -121. 12 3.4 3.4 3.5 2.6 2.4 2.2 2.1 2.2 2.2 2.4 2.4 2.9 PointReyes PointReyes 91 PORE1 CA 38.13 -122. 87 3.6 3.2 3.1 2.6 2.5 2.3 2.4 2.4 2.5 2.5 2.9 3.3 President ial Range - Dry Ri ver Gr eat G ulf 4 GRGU1 NH 44.38 -71.1 2 2.8 2.6 2.6 2.8 2.9 3.0 3.3 3.5 3.6 3.2 3.0 2.9 Rawah Mount Zi rkel 58 MO Z I1 CO 40.63 -106. 62 2.2 2.2 2.0 2.1 2.2 1.8 1.7 1.8 2.0 1.9 2.1 2.1 Red Rock Lakes Yellowsto ne 66 YELL2 W Y 44.63 -110. 37 2.5 2.3 2.2 2.1 2.1 1.9 1.7 1.6 1.8 2.1 2.4 2.5 Redwood Redwood 88 REDW 1 CA 41.63 -124. 12 3.8 3.6 3.8 3.6 3.8 3.9 4.2 4.2 3.7 3.4 3.6 3.4 Roc ky Mountain Roc ky Mountain 57 ROM O 1 CO 40.38 -105. 62 1.9 2.0 2.0 2.1 2.3 2.0 1.9 1.9 2.0 1.8 2.0 1.9 Roo sevelt Ca m pobe llo Moose horn 2 MOOS1 ME 45.13 -67.3 7 3.0 2.7 2.7 2.9 2.9 3.1 3.5 3.6 3.8 3.3 3.2 3.2 Saguaro Saguaro 40 SAGU1 AZ 32.13 -110. 62 1.8 1.6 1.4 1.1 1.1 1.0 1.4 1.7 1.5 1.4 1.5 2.0 Saint Ma rks Saint Ma rks 17 SAMA1 FL 30.13 -84.1 2 3.5 3.3 3.2 3.1 3.2 3.6 3.8 3.8 3.7 3.5 3.4 3.6 Salt Creek Salt Creek 36 SACR1 NM 33.38 -104. 37 2.2 1.9 1.5 1.5 1.6 1.5 1.7 1.9 2.0 1.7 1.8 2.0 San Gabriel San Gabriel 93 SAGA1 CA 34.38 -118. 12 2.6 2.5 2.5 2.2 2.2 2.1 2.2 2.2 2.3 2.2 2.2 2.3 San G orgon io San G orgon io 99 S A GO1 CA 34.13 -116. 87 2.5 2.6 2.4 2.1 2.1 1.8 1.7 1.8 1.9 1.8 1.9 2.1 San Jac into San G orgon io 99 S A GO1 CA 34.13 -116. 87 2.5 2.6 2.4 2.1 2.1 1.8 1.7 1.8 1.9 1.8 1.9 2.1 San P edro P arks San P edro P arks 34 SAPE1 NM 36.13 -106. 87 2.4 2.2 1.9 1.6 1.6 1.4 1.7 2.0 1.9 1.7 2.1 2.3 San Rafael San Rafael 94 RAFA1 CA 34.63 -120. 12 3.0 2.8 2.8 2.5 2.5 2.4 2.5 2.6 2.7 2.6 2.4 2.6 Saw tooth Saw tooth 70 S A W T 1 ID 44.13 -114. 87 3.3 2.8 2.3 2.0 2.0 1.8 1.4 1.4 1.5 2.0 2.9 3.3 Scapegoat Monture 73 MON T 1 MT 47.13 -113. 12 3.3 2.9 2.6 2.4 2.4 2.4 2.1 2.0 2.3 2.7 3.2 3.3 Selway - Bitterroot Sula 71 SULA1 MT 45.88 -114. 12 3.4 3.0 2.6 2.3 2.3 2.2 1.9 1.8 2.0 2.5 3.3 3.4 Seney Seney 22 SENE1 MI 46.38 -85.8 7 3.3 2.8 2.9 2.7 2.6 3.0 3.3 3.6 3.7 3.3 3.5 3.4 Sequ oia Sequ oia 98 SEQU1 CA 36.38 -118. 87 2.9 2.6 2.5 2.2 2.1 1.8 1.7 1.7 1.8 1.9 2.3 2.5 Shenandoah Shenandoah 6 SHEN1 VA 38.63 -78.3 7 2.9 2.6 2.7 2.4 2.9 3.1 3.2 3.5 3.5 3.0 2.7 2.9 Shini ng Rock Shini ng Rock 11 S H RO1 NC 35.38 -82.8 7 3.3 3.0 2.9 2.7 3.2 3.6 3.6 3.9 3.9 3.5 3.2 3.3 Sierra Ancha Sierra Ancha 45 SI AN1 AZ 34.13 -110. 87 2.2 2.0 1.7 1.4 1.3 1.1 1.5 1.8 1.6 1.5 1.8 2.2 Simeonof Simeonof 105 SI ME1 AK 55.25 -160. 75 4.2 4.2 3.8 4.0 4.2 4.6 5.0 5.2 4.5 3.7 3.9 4.2 Sipsey Sipsey 21 SI PS1 AL 34.38 -87.3 7 3.3 3.0 2.8 2.7 3.1 3.4 3.5 3.5 3.5 3.3 3.1 3.3 South W arner Lava Beds 87 LABE1 CA 41.63 -121. 62 4.0 3.4 3.1 2.8 2.6 2.4 2.2 2.2 2.4 2.8 3.6 4.0 Straw berry Mou ntain Stark ey 76 STAR1 O R 45.13 -118. 62 4.3 3.8 3.2 2.9 2.7 2.4 2.0 2.1 2.4 3.3 4.2 4.5 Supersti tio n T onto 44 TONT1 AZ 33.63 -111. 12 2.1 1.9 1.6 1.3 1.2 1.1 1.4 1.7 1.6 1.5 1.7 2.1Guidance for Track ing Progr ess U nder the Regional Haze R ule



### Ta ble A -2 Recommended Monthly Site-Specific f(RH) Values for E ach Mandatory Federal Class I Area,
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Class I Area S i t e Na m e Code Sit e St LAT LONG f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH)

A - 10 Swanquarter Swanquarter 14 SW AN1 NC 35.38 -76.1 2 2.9 2.7 2.6 2.4 2.7 3.0 3.1 3.2 3.1 3.0 2.7 2.9 Sycamore Canyo n Sycamore Canyo n 47 SYCA1 AZ 35.13 -111. 87 2.4 2.4 2.0 1.6 1.5 1.2 1.5 2.0 1.9 1.8 2.0 2.3 Teton Yellowsto ne 66 YELL2 W Y 44.63 -110. 37 2.5 2.3 2.2 2.1 2.1 1.9 1.7 1.6 1.8 2.1 2.4 2.5 T heod ore R oos evelt T heod ore R oos evelt 61 THRO1 ND 46.88 -103. 37 2.9 2.8 2.8 2.4 2.4 2.5 2.4 2.2 2.2 2.3 3.0 3.0 Thousand Lakes Las sen Volc anic 90 L A VO1 CA 40.63 -121. 62 3.7 3.1 2.8 2.4 2.3 2.1 2.0 2.0 2.1 2.3 3.1 3.5 Th ree Sisters Th ree Sisters 84 THSI1 O R 44.38 -122. 12 5.3 4.6 4.4 4.3 3.8 3.4 2.7 2.7 3.1 4.3 5.2 5.3 Tuxedni Tuxedni 103 TUXE1 AK 59.75 -152. 75 3.6 3.4 2.9 2.8 2.8 2.9 3.6 3.9 3.8 3.4 3.5 3.7 UL Bend UL Bend 64 ULBE1 MT 47.63 -108. 62 2.6 2.4 2.4 2.3 2.2 2.1 1.9 1.8 1.9 2.2 2.6 2.6 Upp er Buffalo Upp er Buffalo 27 UPBU1 AR 35.88 -93.1 2 3.2 2.9 2.6 2.7 3.1 3.1 3.0 3.0 3.2 3.0 3.0 3.2 Ventana Pinnacles 92 PI NN1 CA 36.38 -121. 12 3.4 3.4 3.5 2.6 2.4 2.2 2.1 2.2 2.2 2.4 2.4 2.9 Virgi n I slands (b) Virgi n I slands 106 VI I S1 VI 18.75 -155. 75 Voyageurs Voyageurs 24 VOYA2 MN 48.38 -92.8 7 2.7 2.4 2.3 2.2 2.2 2.8 2.5 2.7 2.9 2.5 2.8 2.7 W ash akie Nor th Abs oraka 67 NOAB1 W Y 44.63 -109. 37 2.4 2.2 2.2 2.1 2.1 1.9 1.6 1.5 1.8 2.0 2.3 2.4 W eminuche W eminuche 55 W EM I1 CO 37.63 -107. 87 2.5 2.3 2.0 1.7 1.7 1.5 1.7 2.0 1.9 1.7 2.2 2.4 W est Elk W hit e Riv er 56 W HRI 1 CO 39.13 -106. 87 2.2 2.2 2.0 2.0 2.0 1.7 1.8 2.1 2.1 1.8 2.1 2.1 W heeler Peak W heeler Peak 35 W HPE1 NM 36.63 -105. 37 2.4 2.2 1.9 1.8 1.8 1.6 1.8 2.1 2.1 1.8 2.2 2.4 W hite Mou ntain W hite Mou ntain 37 W H I T 1 NM 33.38 -105. 62 2.2 1.9 1.6 1.5 1.5 1.4 1.7 1.9 2.0 1.7 1.8 2.1 W ichit a Mounta ins W ichit a Mounta ins 30 W I MO1 O K 34.63 -98.6 2 2.8 2.6 2.4 2.4 2.7 2.5 2.2 2.4 2.7 2.5 2.6 2.8 W in d C ave W in d C ave 60 W I CA1 SD 43.63 -103. 37 2.5 2.5 2.5 2.5 2.6 2.5 2.2 2.2 2.1 2.2 2.6 2.5 W olf I sland Okefenoke e 16 OKEF1 G A 30.63 -82.1 2 3.3 3.0 3.2 3.0 3.2 3.8 3.4 3.6 3.6 3.4 3.3 3.4 Yellowsto ne Yellowsto ne 66 YELL2 W Y 44.63 -110. 37 2.5 2.3 2.2 2.1 2.1 1.9 1.7 1.6 1.8 2.1 2.4 2.5 Yolla Bo lly

- Midd le Eel T rinity 104 TRI N1 CA 40.88 -122. 87 4.0 3.4 3.2 2.9 2.8 2.6 2.5 2.6 2.7 2.9 3.6 3.9 Yos em ite Yos em ite 96 YOSE1 CA 37.63 -119. 62 3.0 2.9 2.7 2.2 2.1 1.7 1.5 1.5 1.6 1.8 2.3 2.7 a: No part iculate ma tter sam plin g or visibility monitor ing i s conducted in t he Berin g Sea Wildern ess. b : f(RH) values for Vi rgi n Isl an ds Nat iona l Par k were n ot calcul ated becau se of the lim ited RH dat a avai lable.Guidance for Track ing Progr ess U nder the Regional Haze R ule

A - 11 Tabl e A-3 Mo nthl

y Site- Specific

f(RH ) Val ues f or Each Mandator

y Fe der al C las s I Are a, Based on the C entro id of the Area (Supplem ental I nformation)

Site Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Class I Area S i t e Na m e Ma p ID Code St LAT LONG f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) Aca dia Aca dia 1 ACAD1 ME 44.37 68.26 3.3 2.9 2.8 3.4 3.1 3.0 3.4 3.8 4.0 3.8 3.6 3.5 Agua Tib ia Agua Tib ia 100 AGTI 1 CA 33.41 116.98 2.4 2.4 2.4 2.2 2.2 2.2 2.3 2.3 2.3 2.3 2.1 2.2 Alpine Lakes Snoqua lmie Pass 80 SNPA1 W A 47.42 121.42 4.3 3.8 3.5 3.9 2.9 3.2 2.9 3.1 3.3 3.9 4.5 4.5 Anaconda - Pi ntl er Sula 71 SULA1 MT 45.98 113.42 3.3 2.9 2.5 2.4 2.4 2.3 2.0 1.9 2.1 2.5 3.2 3.3 A n s e l A d a m s Kaiser 110 KAI S1 CA 37.65 119.20 3.0 2.7 2.4 2.1 1.9 1.7 1.6 1.6 1.6 1.8 2.3 2.7 Arches Canyonl ands 50 CANY1 UT 38.64 109.58 2.6 2.3 1.8 1.6 1.6 1.3 1.4 1.5 1.6 1.6 2.0 2.3 Badlands Badlands 59 BADL1 SD 43.74 101.94 2.6 2.7 2.6 2.4 2.8 2.7 2.5 2.4 2.2 2.3 2.7 2.7 Bandelier Bandelier 33 BAND1 NM 35.78 106.27 2.2 2.1 1.8 1.6 1.6 1.4 1.7 2.1 1.9 1.7 2.0 2.2 Bering Sea (a) 60.45 172.79 Big Bend Big Bend 31 BI BE1 T X 29.31 103.19 2.0 1.9 1.6 1.5 1.6 1.6 1.7 2.0 2.1 1.9 1.8 1.9 Black Cany on of t he Gunnison W eminuche 55 W EM I1 CO 38.58 107.70 2.4 2.2 1.9 1.9 1.9 1.6 1.7 1.9 2.0 1.8 2.1 2.3 Bob M arsh all Monture 73 MON T 1 MT 47.75 113.38 3.6 3.1 2.8 2.6 2.7 2.7 2.3 2.2 2.6 2.9 3.5 3.5 Bosque del Apache Bosque del Apache 38 BOAP1 NM 33.79 106.83 2.1 1.9 1.6 1.4 1.4 1.3 1.8 2.0 1.9 1.6 1.8 2.2 Boundary

W aters Canoe Area Bounda ry W ate rs 23 BOW A1 MN 47.95 91.50 3.0 2.6 2.7 2.4 2.3 2.9 3.1 3.4 3.5 2.8 3.2 3.2 Breton Breton 20 B R ET1 LA 29.73 88.88 3.7 3.5 3.7 3.6 3.8 4.0 4.3 4.3 4.2 3.7 3.7 3.7 Bridger Bridger 65 BRI D1 W Y 42.98 109.76 2.5 2.4 2.3 2.2 2.1 1.8 1.5 1.5 1.7 2.0 2.4 2.4 Brigant ine Brigant ine 5 B R I G 1 NJ 39.46 74.45 2.8 2.6 2.7 2.6 3.0 3.2 3.4 3.7 3.6 3.3 2.9 2.8 Bry ce Canyon Bry ce Canyon 49 BRCA1 UT 37.62 112.17 2.6 2.4 1.9 1.6 1.5 1.3 1.3 1.5 1.5 1.6 2.0 2.4 Cabinet Mountai ns Cabinet Mountai ns 75 C AB I1 MT 48.21 115.71 3.8 3.3 2.9 2.6 2.7 2.7 2.3 2.2 2.6 3.0 3.7 3.9 Caney Creek Caney Creek 29 CACR1 AR 34.41 94.08 3.4 3.1 2.9 3.0 3.6 3.6 3.4 3.4 3.6 3.5 3.4 3.5 Canyonl ands Canyonl ands 50 CANY1 UT 38.46 109.82 2.6 2.3 1.7 1.6 1.5 1.2 1.3 1.5 1.6 1.6 2.0 2.3 Cap e Ro m ain Cap e Ro m ain 15 ROMA1 SC 32.94 79.66 3.3 3.0 2.9 2.8 3.2 3.7 3.6 4.1 4.0 3.7 3.4 3.2 Capitol Reef Capitol Reef 52 C AP I1 UT 38.36 111.05 2.7 2.4 2.0 1.7 1.6 1.4 1.4 1.6 1.6 1.7 2.1 2.5 Caribou Las sen Volc anic 90 L A VO1 CA 40.50 121.18 3.7 3.1 2.8 2.5 2.4 2.2 2.1 2.1 2.2 2.4 3.0 3.4 Carlsbad Cav erns Guadalupe Mount ains 32 GUM O 1 T X 32.14 104.48 2.1 2.0 1.6 1.5 1.6 1.6 1.8 2.1 2.2 1.8 1.9 2.1 Cha ssa how itzka Cha ssa how itzka 18 CHAS1 FL 28.75 82.55 3.8 3.5 3.4 3.2 3.3 3.9 3.9 4.2 4.1 3.9 3.7 3.9 Chi ri cah ua NM Chiricahua 39 CHI R1 AZ 32.01 109.39 2.0 2.0 1.6 1.3 1.3 1.1 1.8 2.1 1.8 1.5 1.6 2.2 Chiricahua W Chiricahua 39 CHI R1 AZ 31.84 109.27 2.0 1.9 1.6 1.2 1.3 1.1 1.8 2.1 1.8 1.5 1.6 2.2 Co hutta Co hutta 12 COHU1 G A 34.92 84.58 3.3 3.1 3.0 2.8 3.4 3.8 4.0 4.2 4.2 3.8 3.4 3.5 Cra ter Lake Cra ter Lake 86 CRLA1 O R 42.90 122.13 4.6 3.9 3.7 3.4 3.2 3.0 2.8 2.9 3.1 3.6 4.6 4.6 Craters of

the Mo on Craters of the Mo on 69 CRM O 1 ID 43.47 113.55 3.1 2.7 2.3 2.0 2.0 1.8 1.4 1.4 1.6 2.0 2.8 3.0 Cucam onga San Gabriel 93 SAGA1 CA 34.25 117.57 2.5 2.4 2.4 2.2 2.1 2.1 2.1 2.2 2.2 2.2 2.1 2.2 Den ali Den ali 102 DENA1 AK 63.72 148.97 2.5 2.3 2.1 1.9 1.9 2.2 2.5 3.0 2.8 2.9 3.0 3.1 Desolati on Bli ss 95 BLI S1 CA 38.98 120.12 3.2 2.8 2.4 2.0 1.8 1.6 1.5 1.6 1.7 1.9 2.4 3.0 Diamond Peak Cra ter Lake 86 CRLA1 O R 43.53 122.10 4.5 4.0 3.6 3.7 3.2 3.1 2.9 2.9 3.1 3.7 4.6 4.6 Dolly Sods Dolly Sods 8 DOS O 1 W V 39.11 79.43 3.0 2.8 2.8 2.6 3.1 3.4 3.5 3.9 3.9 3.3 3.0 3.1Guidance for Track ing Progr ess U nder the Regional Haze R ule
Tabl e A-3 Mo nthl

y Site- Specific

f(RH ) Val ues f or Each Mandator

y Fe der al C las s I Are a, Based on the C entro id of the Area (Supplem ental I nformation)

Site Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Class I Area S i t e Na m e Ma p ID Code St LAT LONG f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH)

A - 12 Dom e Land Dom e Land 109 DOME1 CA 35.70 118.19 2.5 2.3 2.2 1.9 1.8 1.8 1.8 1.8 1.8 1.9 2.0 2.2 Eagle Cap Stark ey 76 STAR1 O R 45.10 117.29 3.8 3.2 2.5 2.1 2.0 1.9 1.6 1.6 1.6 2.3 3.4 4.0 Eagle s Nest W hit e Riv er 56 W HRI 1 CO 39.69 106.25 2.2 2.2 2.0 2.0 2.1 1.9 1.8 2.0 2.0 1.9 2.1 2.1 Emigrant Yos em ite 96 YOSE1 CA 38.20 119.75 3.2 2.8 2.5 2.1 1.9 1.7 1.5 1.6 1.6 1.9 2.4 2.9 Ever glades Ever glades 19 EVER1 FL 25.39 80.68 2.7 2.6 2.6 2.4 2.4 2.7 2.6 2.9 3.0 2.8 2.6 2.7 Fit zpat rick Bridger 65 BRI D1 W Y 43.27 109.57 2.5 2.3 2.2 2.1 2.1 1.8 1.5 1.5 1.7 2.0 2.4 2.4 Flat Tops W hit e Riv er 56 W HRI 1 CO 39.97 107.25 2.3 2.2 2.0 2.0 2.0 1.8 1.7 1.9 1.9 1.8 2.2 2.2 Ga liuro Chiricahua 39 CHI R1 AZ 32.56 110.32 2.0 1.8 1.5 1.2 1.2 1.1 1.5 1.8 1.6 1.5 1.6 2.1 Gates of t he Mount ains Gates of t he Mount ains 74 GAM O 1 MT 46.87 111.81 2.9 2.6 2.4 2.3 2.3 2.3 2.0 1.9 2.1 2.4 2.8 2.8 Ge arhar t Mountain Cra ter Lake 86 CRLA1 O R 42.49 120.85 4.0 3.4 3.1 2.8 2.7 2.5 2.3 2.3 2.4 2.8 3.7 3.8 Gila G ila C liffs 42 GICL1 NM 33.22 108.25 2.1 1.9 1.6 1.3 1.4 1.2 2.1 2.0 1.8 1.6 1.8 2.2 Glacier Glacier 72 GLAC1 MT 48.51 114.00 4.0 3.5 3.2 3.1 3.2 3.4 2.8 2.6 3.2 3.5 3.8 3.9 Glacier Peak North Cascades 81 NOCA1 W A 48.21 121.04 4.2 3.7 3.4 3.8 2.9 3.2 2.9 3.1 3.3 3.9 4.4 4.4 Go at Roc ks W hit e Pass 79 W HPA1 W A 46.54 121.48 4.3 3.8 3.4 4.2 2.8 3.4 3.0 3.2 3.1 3.8 4.4 4.6 Grand Canyon Grand Canyon, Hance 48 GRCA2 AZ 35.97 111.98 2.4 2.3 1.9 1.5 1.4 1.2 1.4 1.7 1.6 1.6 1.9 2.3 Grand Teton Yellowsto ne 66 YELL2 W Y 43.68 110.73 2.6 2.4 2.2 2.1 2.1 1.8 1.5 1.5 1.7 2.0 2.4 2.6 Gr eat G ulf Gr eat G ulf 4 GRGU1 NH 44.31 71.22 2.8 2.6 2.6 2.8 2.9 3.2 3.5 3.8 4.0 3.4 3.1 2.9 Great Sand Dunes Great Sand Dunes 53 GRSA1 CO 37.73 105.52 2.4 2.3 2.0 1.9 1.9 1.8 1.9 2.3 2.2 1.9 2.4 2.4 Great Smoky Mou ntai ns Great Smoky Mou ntai ns 10 GRSM1 T N 35.63 83.94 3.3 3.0 2.9 2.7 3.2 3.9 3.8 4.0 4.2 3.8 3.3 3.4 Guadalupe Mount ains Guadalupe Mount ains 32 GUM O 1 T X 31.83 104.80 2.0 2.0 1.6 1.5 1.6 1.5 1.9 2.2 2.2 1.8 1.9 2.2 Hale akala Hale akala 108 HALE1 HI 20.81 156.28 2.7 2.6 2.6 2.5 2.4 2.3 2.5 2.4 2.4 2.5 2.8 2.7 Hawaii Volcanoes Hawaii Volcanoes 107 H A VO1 HI 19.43 155.27 3.2 2.9 3.0 3.0 3.0 2.9 3.1 3.2 3.2 3.2 3.7 3.2 Hells Cany on Hells Cany on 77 HECA1 O R 45.34 116.57 3.7 3.1 2.5 2.2 2.1 2.0 1.6 1.6 1.8 2.4 3.5 3.9 Hercules - Glade Hercules - Glade 28 HEGL1 MO 36.69 92.90 3.2 2.9 2.7 2.7 3.3 3.3 3.3 3.3 3.4 3.1 3.1 3.3 Hoover Hoover 97 HOO V1 CA 38.14 119.45 3.1 2.8 2.5 2.1 1.9 1.6 1.5 1.5 1.6 1.8 2.3 2.8 Isle Royale Isle Royale 25 I SLE1 MI 47.99 88.83 3.1 2.5 2.7 2.4 2.2 2.6 3.0 3.2 3.8 2.7 3.3 3.3 James Rive r Face James Rive r Face 7 J AR I1 VA 37.62 79.48 2.8 2.6 2.7 2.4 3.0 3.3 3.4 3.7 3.6 3.2 2.8 3.0 Jarbidge Jarbidge 68 JARB1 NV 41.89 115.43 3.0 2.6 2.1 2.1 2.2 2.2 1.6 1.4 1.4 1.6 2.4 2.8 Joh n Muir Kaiser 110 KAI S1 CA 37.39 118.84 2.9 2.6 2.4 2.1 1.9 1.7 1.7 1.7 1.7 1.9 2.2 2.6 Joshua Tree Joshua Tree 101 JOSH1 CA 34.03 116.18 2.4 2.3 2.2 2.0 2.0 1.9 2.0 2.0 2.0 2.0 1.9 2.0 Joy ce Kil mer - Sli ckro ck Great Smoky Mou ntai ns 10 GRSM1 T N 35.43 84.00 3.3 3.1 2.9 2.7 3.3 3.8 4.0 4.2 4.2 3.8 3.3 3.5 Kaiser Kaiser 110 KAI S1 CA 37.28 119.18 3.0 2.7 2.5 2.1 1.9 1.7 1.6 1.7 1.7 1.9 2.3 2.7 Kalm iops is Kalm iops is 89 KALM1 O R 42.27 123.93 4.5 3.9 3.8 3.5 3.5 3.3 3.2 3.2 3.3 3.6 4.4 4.3 Kings Cany on Sequ oia 98 SEQU1 CA 36.82 118.76 2.8 2.6 2.4 2.1 1.9 1.8 1.7 1.7 1.8 1.9 2.3 2.5 La G arita W eminuche 55 W EM I1 CO 37.96 106.81 2.3 2.2 1.9 1.8 1.8 1.6 1.7 2.1 2.0 1.8 2.2 2.3 Las sen Volc anic Las sen Volc anic 90 L A VO1 CA 40.54 121.57 3.8 3.2 2.9 2.5 2.4 2.2 2.1 2.1 2.2 2.4 3.1 3.5Guidance for Track ing Progr ess U nder the Regional Haze R ule
Tabl e A-3 Mo nthl

y Site- Specific

f(RH ) Val ues f or Each Mandator

y Fe der al C las s I Are a, Based on the C entro id of the Area (Supplem ental I nformation)

Site Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Class I Area S i t e Na m e Ma p ID Code St LAT LONG f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH)

A - 13 Lava Beds Lava Beds 87 LABE1 CA 41.71 121.34 4.0 3.4 3.1 2.7 2.6 2.4 2.3 2.3 2.4 2.7 3.5 3.8 Linv ill e Gorge Linv ill e Gorge 13 L I GO1 NC 35.89 81.89 3.3 3.0 3.0 2.7 3.3 3.9 4.1 4.5 4.4 3.7 3.2 3.4 Lostwood Lostwood 62 LOS T 1 ND 48.60 102.48 3.0 2.9 2.9 2.3 2.3 2.6 2.7 2.4 2.3 2.4 3.2 3.2 Lye Brook Lye Brook 3 LYB R1 VT 43.15 73.12 2.7 2.6 2.6 2.6 2.8 3.0 3.3 3.6 3.7 3.3 2.9 2.8 Ma m m ot h C ave Ma m m ot h C ave 9 MACA1 KY 37.22 86.07 3.4 3.1 2.9 2.6 3.2 3.5 3.7 3.9 3.9 3.4 3.2 3.5 Marble Moun tain T rinity 104 TRI N1 CA 41.52 123.21 4.4 3.8 3.7 3.3 3.4 3.2 3.2 3.2 3.2 3.4 4.1 4.2 Maroo n Bel ls - Snowmass W hit e Riv er 56 W HRI 1 CO 39.15 106.82 2.2 2.1 2.0 2.0 2.1 1.7 1.9 2.2 2.1 1.8 2.1 2.1 Mazat zal I ke's Back bone 46 I KBA1 AZ 33.92 111.43 2.1 1.9 1.7 1.3 1.3 1.1 1.5 1.7 1.6 1.5 1.7 2.1 Medic ine La ke Medic ine La ke 63 MELA1 MT 48.50 104.29 3.0 2.9 2.9 2.3 2.2 2.5 2.5 2.2 2.2 2.4 3.2 3.2 Mesa Verde Mesa Verde 54 MEVE1 CO 37.20 108.49 2.5 2.3 1.9 1.5 1.5 1.3 1.6 2.0 1.9 1.7 2.1 2.3 Mingo Mingo 26 M I NG1 MO 36.98 90.20 3.3 3.0 2.8 2.6 3.0 3.2 3.3 3.5 3.5 3.1 3.1 3.3 Mission Moun tai ns Monture 73 MON T 1 MT 47.40 113.85 3.6 3.1 2.7 2.5 2.6 2.6 2.3 2.2 2.5 2.9 3.5 3.6 Mokelumne Bli ss 95 BLI S1 CA 38.58 120.03 3.2 2.8 2.4 2.0 1.9 1.6 1.5 1.6 1.7 1.9 2.4 2.9 Moose horn Moose horn 2 MOOS1 ME 45.12 67.26 3.0 2.7 2.7 3.0 3.0 3.1 3.4 3.8 3.9 3.5 3.2 3.2 M o u n t A d a m s W hit e Pass 79 W HPA1 W A 46.19 121.50 4.3 3.8 3.4 4.4 2.9 3.5 3.1 3.3 3.1 3.9 4.5 4.6 Mount Bal dy Mount Bal dy 43 BAL D1 AZ 34.12 109.57 2.2 2.0 1.7 1.4 1.3 1.2 1.6 1.9 1.7 1.6 1.8 2.2 Mount Hood Mount Hood 85 MOH O 1 O R 45.38 121.69 4.3 3.8 3.5 3.9 3.0 3.2 2.9 3.0 3.1 3.9 4.5 4.6 Mount Jef

ferson Th ree Sisters 84 THSI1 O R 44.55 121.83 4.4 3.9 3.6 3.7 3.1 3.1 2.9 2.9 3.0 3.8 4.6 4.5 Mount Rai nier Mount Rai nier 78 MORA1 W A 46.76 122.12 4.4 4.0 3.6 4.7 3.1 3.7 3.3 3.5 3.4 4.1 4.7 4.7 Mount W ashingt on Th ree Sisters 84 THSI1 O R 44.30 121.87 4.4 3.9 3.6 3.7 3.1 3.1 3.0 2.9 3.0 3.8 4.6 4.6 Mount Zi rkel Mount Zi rkel 58 MO Z I1 CO 40.55 106.70 2.2 2.2 2.0 2.1 2.2 1.9 1.7 1.9 2.0 1.9 2.1 2.1 Mountai n Lakes Cra ter Lake 86 CRLA1 O R 42.34 122.11 4.3 3.6 3.3 3.0 2.9 2.6 2.5 2.5 2.6 3.1 4.1 4.3 Nor th Abs aroka Nor th Abs oraka 67 NOAB1 W Y 44.77 109.78 2.4 2.3 2.2 2.2 2.1 1.9 1.7 1.6 1.8 2.0 2.4 2.4 North Cascades North Cascades 81 NOCA1 W A 48.54 121.44 4.1 3.7 3.4 3.7 2.9 3.2 2.9 3.2 3.5 3.9 4.4 4.4 Okefenoke e Okefenoke e 16 OKEF1 G A 30.74 82.13 3.5 3.2 3.1 3.0 3.6 3.7 3.7 4.1 4.0 3.8 3.5 3.6 Olym pic Olym pic 83 OLYM1 W A 47.32 123.35 4.5 4.1 3.8 4.1 3.2 3.5 3.1 3.5 3.7 4.4 4.8 4.8 Otter Cree k Dolly Sods 8 DOS O 1 W V 39.00 79.65 3.0 2.8 2.8 2.6 3.2 3.5 3.7 4.1 4.0 3.3 3.0 3.1 Pasayt en Pasayt en 82 PASA1 W A 48.85 120.52 4.2 3.7 3.4 3.7 2.9 3.2 2.9 3.2 3.3 3.9 4.4 4.5 Pecos W heeler Peak 35 W HPE1 NM 35.93 105.64 2.3 2.1 1.8 1.7 1.7 1.5 1.8 2.1 2.0 1.7 2.0 2.2 Petr if ied Fo rest Petr if ied Fo rest 41 P E FO1 AZ 35.08 109.77 2.4 2.2 1.7 1.4 1.3 1.2 1.5 1.8 1.7 1.6 1.9 2.3 Pine M ountain I ke's Back bone 46 I KBA1 AZ 34.31 111.80 2.2 2.0 1.7 1.4 1.3 1.1 1.4 1.8 1.6 1.5 1.7 2.1 Pinnacles Pinnacles 92 PI NN1 CA 36.49 121.16 3.2 2.8 2.6 2.4 2.3 2.0 2.0 2.1 2.1 2.3 2.5 2.9 PointReyes PointReyes 91 PORE1 CA 38.12 122.90 3.6 3.3 3.1 2.7 2.5 2.3 2.5 2.6 2.6 2.7 2.9 3.3 President ial Range - Dry Ri ver Gr eat G ulf 4 GRGU1 NH 44.21 71.35 2.8 2.6 2.6 2.8 3.0 3.4 3.7 4.0 4.3 3.5 3.1 3.0 Rawah Mount Zi rkel 58 MO Z I1 CO 40.70 105.94 2.1 2.1 2.0 2.1 2.3 2.0 1.8 2.0 2.0 1.9 2.1 2.0 Red Rock Lakes Yellowsto ne 66 YELL2 W Y 44.67 111.70 2.7 2.5 2.3 2.1 2.1 1.9 1.7 1.6 1.8 2.1 2.6 2.7Guidance for Track ing Progr ess U nder the Regional Haze R ule
Tabl e A-3 Mo nthl

y Site- Specific

f(RH ) Val ues f or Each Mandator

y Fe der al C las s I Are a, Based on the C entro id of the Area (Supplem ental I nformation)

Site Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Class I Area S i t e Na m e Ma p ID Code St LAT LONG f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH)

A - 14 Redwood Redwood 88 REDW 1 CA 41.56 124.08 4.4 3.9 4.6 3.9 4.5 4.7 4.9 4.7 4.3 3.7 3.8 3.4 Roc ky Mountain Roc ky Mountain 57 ROM O 1 CO 40.28 105.55 1.7 1.9 1.9 2.1 2.3 2.0 1.8 2.0 1.9 1.8 1.8 1.7 Roo sevelt Ca m pobe llo Moose horn 2 MOOS1 ME 44.88 66.95 3.0 2.7 2.7 3.0 3.0 3.1 3.4 3.8 3.9 3.5 3.3 3.2 Saguaro Saguaro 40 SAGU1 AZ 32.25 110.73 1.8 1.6 1.4 1.1 1.1 1.1 1.4 1.8 1.6 1.4 1.6 2.1 Saint Ma rks Saint Ma rks 17 SAMA1 FL 30.12 84.08 3.7 3.4 3.4 3.4 3.5 4.0 4.1 4.4 4.2 3.8 3.7 3.8 Salt Creek Salt Creek 36 SACR1 NM 33.61 104.37 2.1 1.9 1.5 1.5 1.7 1.6 1.8 2.0 2.1 1.8 1.8 2.1 San Gabriel San Gabriel 93 SAGA1 CA 34.27 117.94 2.5 2.5 2.4 2.2 2.2 2.1 2.2 2.2 2.2 2.3 2.1 2.2 San G orgon io San G orgon io 99 S A GO1 CA 34.18 116.90 2.7 2.8 2.6 2.3 2.2 1.9 1.8 1.9 1.9 1.9 1.9 2.2 San Jac into San G orgon io 99 S A GO1 CA 33.75 116.65 2.5 2.4 2.4 2.2 2.1 2.0 2.1 2.1 2.1 2.1 2.0 2.1 San P edro P arks San P edro P arks 34 SAPE1 NM 36.11 106.81 2.3 2.1 1.8 1.6 1.6 1.4 1.7 2.0 1.9 1.7 2.1 2.2 San Rafael San Rafael 94 RAFA1 CA 34.78 119.83 2.8 2.7 2.7 2.4 2.3 2.3 2.5 2.5 2.4 2.5 2.3 2.5 Saw tooth Saw tooth 70 S A W T 1 ID 44.18 114.93 3.3 2.9 2.3 2.0 2.0 1.8 1.4 1.4 1.5 2.0 2.9 3.3 Scapegoat Monture 73 MON T 1 MT 47.17 112.73 3.2 2.8 2.6 2.4 2.5 2.4 2.1 2.0 2.3 2.6 3.1 3.1 Selway - Bitterroot Sula 71 SULA1 MT 45.86 114.00 3.5 3.0 2.6 2.3 2.4 2.3 1.9 1.9 2.1 2.6 3.3 3.5 Seney Seney 22 SENE1 MI 46.26 86.03 3.3 2.8 2.9 2.7 2.6 3.1 3.6 4.0 4.1 3.4 3.6 3.5 Sequ oia Sequ oia 98 SEQU1 CA 36.50 118.82 2.5 2.4 2.4 2.2 1.9 1.8 1.7 1.6 1.8 1.9 2.3 2.3 Shenandoah Shenandoah 6 SHEN1 VA 38.52 78.44 3.1 2.8 2.8 2.5 3.1 3.4 3.5 3.9 3.9 3.2 3.0 3.1 Shini ng Rock Shini ng Rock 11 S H RO1 NC 35.39 82.78 3.3 3.0 2.9 2.7 3.4 3.9 4.1 4.5 4.4 3.8 3.3 3.4 Sierra Ancha Sierra Ancha 45 SI AN1 AZ 33.82 110.88 2.1 2.0 1.7 1.3 1.3 1.1 1.5 1.8 1.6 1.5 1.7 2.1 Simeonof Simeonof 105 SI ME1 AK 54.92 159.28 4.3 4.1 3.6 3.9 3.9 4.3 5.0 5.2 4.5 3.8 4.0 4.3 Sipsey Sipsey 21 SI PS1 AL 34.34 87.34 3.4 3.1 2.9 2.8 3.3 3.7 3.9 3.9 3.9 3.6 3.3 3.4 South W arner Lava Beds 87 LABE1 CA 41.33 120.20 3.6 3.1 2.7 2.4 2.3 2.1 1.9 1.9 2.0 2.3 3.1 3.4 Straw berry Mou ntain Stark ey 76 STAR1 O R 44.30 118.73 3.9 3.3 2.8 2.9 2.3 2.4 2.0 2.0 1.9 2.6 3.7 4.1 Supersti tio n T onto 44 TONT1 AZ 33.63 111.10 2.1 1.9 1.6 1.3 1.3 1.1 1.5 1.7 1.6 1.5 1.7 2.1 Swanquarter Swanquarter 14 SW AN1 NC 35.31 76.28 2.9 2.7 2.6 2.5 2.9 3.2 3.4 3.5 3.4 3.1 2.8 2.9 Sycamore Canyo n Sycamore Canyo n 47 SYCA1 AZ 34.03 116.18 2.4 2.3 2.2 2.0 2.0 1.9 2.0 2.0 2.0 2.0 1.9 2.0 Teton Yellowsto ne 66 YELL2 W Y 44.09 110.18 2.5 2.4 2.2 2.1 2.1 1.9 1.6 1.5 1.7 2.0 2.4 2.5 T heod ore R oos evelt T heod ore R oos evelt 61 THRO1 ND 47.30 104.00 2.9 2.8 2.8 2.3 2.3 2.5 2.4 2.2 2.2 2.3 3.0 3.0 Thousand Lakes Las sen Volc anic 90 L A VO1 CA 40.70 121.58 3.8 3.2 2.9 2.5 2.4 2.2 2.1 2.1 2.2 2.4 3.1 3.5 Th ree Sisters Th ree Sisters 84 THSI1 O R 44.29 122.04 4.5 4.0 3.6 3.7 3.1 3.1 3.0 2.9 3.0 3.8 4.6 4.6 Tuxedni Tuxedni 103 TUXE1 AK 60.15 152.60 3.5 3.3 2.9 2.7 2.7 2.9 3.6 4.0 3.9 3.5 3.5 3.7 UL Bend UL Bend 64 ULBE1 MT 47.55 107.87 2.7 2.5 2.5 2.3 2.2 2.2 2.0 1.8 1.9 2.2 2.7 2.7 Upp er Buffalo Upp er Buffalo 27 UPBU1 AR 35.83 93.21 3.3 3.0 2.7 2.8 3.4 3.4 3.4 3.4 3.6 3.3 3.2 3.3 Ventana Pinnacles 92 PI NN1 CA 36.22 121.59 3.2 2.9 2.8 2.4 2.3 2.1 2.2 2.3 2.2 2.4 2.5 2.9 Virgi n I slands (b) Virgi n I slands 106 VI I S1 VI 18.33 64.79 Voyageurs Voyageurs 24 VOYA2 MN 48.59 93.17 2.8 2.4 2.4 2.3 2.3 3.1 2.7 3.0 3.2 2.6 2.9 2.8Guidance for Track ing Progr ess U nder the Regional Haze R ule
Tabl e A-3 Mo nthl

y Site- Specific

f(RH ) Val ues f or Each Mandator

y Fe der al C las s I Are a, Based on the C entro id of the Area (Supplem ental I nformation)

Site Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Class I Area S i t e Na m e Ma p ID Code St LAT LONG f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH) f( RH)

A - 15 W ash akie Nor th Abs oraka 67 NOAB1 W Y 43.95 109.59 2.5 2.3 2.2 2.1 2.1 1.8 1.6 1.5 1.8 2.0 2.4 2.5 W eminuche W eminuche 55 W EM I1 CO 37.65 107.80 2.4 2.2 1.9 1.7 1.7 1.5 1.6 2.0 1.9 1.7 2.1 2.3 W est Elk W hit e Riv er 56 W HRI 1 CO 38.69 107.19 2.3 2.2 1.9 1.9 1.9 1.7 1.8 2.1 2.0 1.8 2.1 2.2 W heeler Peak W heeler Peak 35 W HPE1 NM 36.57 105.42 2.3 2.2 1.9 1.8 1.8 1.6 1.8 2.2 2.1 1.8 2.2 2.3 W hite Mou ntain W hite Mou ntain 37 W H I T 1 NM 33.49 105.83 2.1 1.9 1.6 1.5 1.5 1.4 1.8 2.0 2.0 1.7 1.8 2.1 W ichit a Mounta ins W ichit a Mounta ins 30 W I MO1 O K 34.74 98.59 2.7 2.6 2.4 2.4 3.0 2.7 2.3 2.5 2.9 2.6 2.7 2.8 W in d C ave W in d C ave 60 W I CA1 SD 43.55 103.48 2.5 2.5 2.5 2.5 2.7 2.5 2.3 2.3 2.2 2.2 2.6 2.6 W olf I sland Okefenoke e 16 OKEF1 G A 31.31 81.30 3.4 3.1 3.1 3.0 3.3 3.7 3.7 4.1 4.0 3.7 3.5 3.5 Yellowsto ne Yellowsto ne 66 YELL2 W Y 44.55 110.40 2.5 2.4 2.3 2.2 2.2 1.9 1.7 1.6 1.8 2.1 2.5 2.5 Yolla Bo lly

- Midd le Eel T rinity 104 TRI N1 CA 40.11 122.96 4.0 3.4 3.1 2.8 2.7 2.5 2.4 2.5 2.6 2.7 3.3 3.6 Yos em ite Yos em ite 96 YOSE1 CA 37.71 119.70 3.3 3.0 2.8 2.3 2.1 1.8 1.5 1.5 1.5 1.8 2.4 2.8 Zion Zion 51 ZI ON1 UT 37.25 113.01 2.7 2.4 2.0 1.6 1.5 1.3 1.2 1.4 1.4 1.6 2.0 2.4 a: No part iculate ma tter sam plin g or visibility monitor ing i s conducted in t he Berin g Sea Wildern ess. b : f(RH) values for Vi rgi n Isl an ds Nat iona l Par k were n ot calcul ated becau se of the lim ited RH dat a avai lable.B - 1 

### APPENDI X B



## Analysis of the Effect of Correlation Between f(RH) and SO 4 

## and f(RH) and NO 3 

## on Deciview Calcu lation s us ing f(RH)Guidance f or Tracking Progress Under the

Regional Haze R ule

B - 2 The regional h

aze regulation requires separate t racking of v isi bili ty changes f

or t he worst 20 % a n d b est 20 % vi si

b i l i ty da y s. If th ere is a si gn i f i ca n t cor re l ati on i n an y mon th at a n y si te be t we en da ily r ela t ive hu mid it y an d t he su lfa t e o rnit r at e c o nc en t r at io ns , t he n u se o f t he mo nt hlyaveraged f(RH) will sy

st emat ically

ove r- or unde r- pr edict t he co nt ribut ion t o visibility im pair ment of the aero sol speci es. This App endix pr ese nt s an a nalysis of po t ent ial biases as so ciat ed w ith co rr elat ions between rel

ative hum idi ty an d in organic h ygroscopi c aerosol speci

es usi ng data coll

ected at 20 man da tory Fe deral Cl as s I are aswhere

rel ati ve hu m i di ty mea su rem en ts w ere made. The

ef f ec t of any correl ation

that may exist between

SO 4 and/or NO 3 and f(RH) appe ars to i ndu ce smal l errors t ha t ar e, o n a ve r ag e, wit hin 1 0% o f t he t rue va lue fo rev er y sit e in clu de d in t he st ud y. G en er ally those sites i

n the W est are sli ghtly overestim

ated by usi ng average f(RH) values while tho se in t he East are underestim

ated. The type of av

erage f(RH) va

l ueus ed (m onth l y , y ea rl y , av era geof top 20% ext inctio n days, aver age of bo t t om 2 0% ext inctio n days) can ha ve a s ignifi cant impact on t he am ount o f error in

duced i n the cal cul ation of a y

early deci view i ndex based on the h

igh est 20% ( r es pe ct ive ly, lo we st 20 % ) ex t inc t io n d ays . I n mo st inst an ce s, t he us e o f a ye ar ly o rmo nt hly average f(RH) resul

ted in s im il ar percentage errors and both procedures resulted i n less error than usi ng average f(RH) val

ues deri ved f rom the worst o r best 20% days . Therefore, the si mpl er cli matological

appro ach i s used in

regional h

aze calcul ations. We as se ss ed t he ef

fe ct o f t he co rr ela t io n be t we en da ily f(RH) and SO4 and/or NO3 mass con centr ati ons . Th i s is prom pte d by the obs erv ati on th at, i n r ec ons tructi ng ex ti nc ti on f rom aerosol mass conc en trations, of

ten a n a verage v al ue is us ed f

or f(RH) due

to the unavai l ab i l i ty of on- site re lative hu midity measur ement s fro m which f(RH) va l ue s c an be cal cul ate d. Th

e e qua ti on for reconstructed extinction is an addi tive l in ear comb in

ation of contri

butions from various aerosol speci es. The contri bution to estim

ated atmospheri

c ex tin ction due to SO 4 and NO 3 ( int er pr et ed as ammo niu m su lfat e a nd nit r at e) o cc ur s in t he fo rm ef(RH) *SO 4 and ef(RH) *NO 3 , where e is an av

erage m ass scatterin

g eff ic ie ncy . Calc ula ting av erage exti nctions over a giv

en time period r esults in

averagin g of the pro ducts ef(RH) *SO 4 and ef(RH) *NO 3 . However, when an av erage f(RH) is u se d i n p lac e o f ada ily f(RH) , the contri bution to extin

ction due to SO 4 and/or NO 3 is es t imat ed by t he p ro du ct o f t he s ep ar at e a ver ag es o f f(RH) and SO4 , and, like

wis e, se pa ra t e a ver ag es o f

f(RH) and NO 3 . Le

t usdenote

the err ors i ntr oduc ed due to such su bs ti tution of av erages by dSO 4 and dNO 3 , r es pe ct ive ly.Guidance f or Tracking Progress Under the

Regional Haze R ule

B - 3 That is,

dSO 4 = average f(RH) *ave rage SO 4 –average [

f(RH) *SO 4 ] (1) and dNO 3 = average f(RH) *average NO 3 – average [ f(RH) *NO 3 ]. (2) These er ro rs w ill

be ze ro if, and o nly i

f, t he sa mple Pea rso n co rr elat ion bet wee n f(R H) and SO4 , r es pe ct ive ly f(RH) and NO 3 , i s z ero. More general

ly , suppose n pa ir s o f o bs er va t io ns , sa y (x 1 , y 1 ), (x 2 , y 2 ),. .. , (x n , y n

) ar e a va ilable on the va ri ab l e pai r (x, y) . I f the sample P ear so n co rr elat ion co efficient r bet wee n X and Y i s z ero, i t f oll ows th at th e a v erag e of th e prod uc t X*Y is equal to th e prod

uc t of th e s ep arate

ave ra ge s o f X and Y. Nam

el y ,

im pli es (3)

An exa m i nation of the

sam pl e correlation

betwee n SO 4 and f(RH) , as well as NO 3 and f(RH) , f or various si te/ye ar com

bi nations i n the IMPROV E da

ta ba se r ev ea ls t he pr es en ce o f st at ist ica lly significant corr elations b etween SO 4 and/or NO 3 and f(RH) , in so me insta nces , implyi ng t hat t he dif feren ces dSO 4 and dNO 3 , defi

ned i n equati ons (1) and (2) respectiv el y, are n ot zero. Therefore, to understand the practical im pli cations of the presence of

correlations between

f(RH) and SO4 /NO 3 , one nee ds to exam

i ne the m

agni tudes of d SO 4 and dNO 3 relati ve to the target quantities [average( f(RH) *SO 4 )] and [ave

rage( f(RH) *NO 3 )] . We have mad e t his assess me nt usi ng IMPROVE da ta fo rsit es /yea r s fo rwh ich da ily f(RH) data i s avail abl e. In add i tion to exa

m i ni ng dSO 4 and dNO 3 i nd i vi dua l l y , we ha ve also exa m i ne d the c om

bi ne d error dSO 4 +dNO 3 = average f(RH) *(ave rage of SO 4 +NO 3 ) – average [

f(RH) *(SO 4 +NO 3 )]. (4)Guidance f or Tracking Progress Under the

Regional Haze R ule

B - 4 In our calcul

ations we us ed the fol

lowi ng i nput quantities and data com ple teness cri teria:

• f(RH) is c o mp ut ed fr o m ho ur ly RH o bs er va t io ns . Ho ur ly f(RH) f actors a re deriv ed from Tang’s s moothed am

moni um s ulf ate growt h curves . For RH val ues greater t han

95%, the f(RH) val

ue i s f la gged as m

is si ng. Fi nal ly , the dail y a verage o f t he ho ur ly f(RH) observati ons i s obtain ed. Not e the daily

average f(RH) is

set t o miss ing o n d ays fo rwh ich t he r e a r e f ew er t ha n 1 6 h o ur ly f(RH) obse rva tions.

• SO 4 is

in terpret ed as am

moni um s ulf ate and NO 3 asam

moni um ni trate i n u ni ts of ng/m 3

.

• f(RH) M on th ly : Monthl y a verage f(RH) for each m

onth was computed f

or any gi ven si te by averagi ng f(RH) Daily f

or that m onth a crossal l years f or whi ch data we re available for t he sit e und er co nsider at ion.

• f(RH) Yearly = Yearl y a verage f(RH) for any given year and s ite w as c alculat ed by av er ag ing all d aily f(RH) val ues f or t he si te for the giv

en y ear. Days for whi ch f(RH) was“m

i ssi ng” were not i nc l uded i n the ca l cul ati on of thi s av erage . The us e of two di ff

erent av erages was considered: (1) f(RH) month ly and (2) f(RH) yearly . The f oll owin g %age errors we

re cal culated: (a) (Fi

gure 1 )
pSO 4 yearly = The

error dSO 4 , e xpr esse d as a % age , w hen f(RH) yearly is u se d in p lac e o f f(RH) dailyGuidance f or Tracking Progress Under the

Regional Haze R ule

B - 5 (b) (Figure 2) pSO 4 mon thly = The

error dSO 4 , e xpr esse d as a % age , w hen f(RH) month lyi s u se d i n p l ac e of f(RH) daily

(c) (Figure 3) pNO 3 yearly = The

error dNO 3 , e xpr esse d as a % age , w hen f(RH) yearly i s u se d i n p l ac e of f(RH) daily

(d) (Figure 4) pNO 3 mon thly = The

error dNO 3 , e xpr esse d as a % age , w hen f(RH) month lyi s u se d i n p l ac e of f(RH) daily

(e) (Figure 5) pSO 4 NO 3 yearly = The

error (dSO 4 + dNO 3

) , e xpr esse d as a % age , w hen f(RH) yearly is u se d in pla ce o f f(RH) dailyGuidance f or Tracking Progress Under the

Regional Haze R ule

B - 6 (f) (Figure 6) pSO 4 NO 3 mon thly = The

error ( dSO 4 + dNO 3 ), expr esse d as a % age , w hen f(RH) month lyis used in pla ce o f

f(RH) daily

The resul ts are displ

ay ed graphi cally in Figures 1 through 6. In each f igure, b ox-andwh i sker p l ots of

the an nu al vi si bi l i ty i nd i ce s a re d i sp l ay ed f or ea ch si te. The nu m be r of yea rs of data used in

any giv en b ox-and-whisker plot ranges f rom 3 to 11 years, dependi ng on the si

te, based on data com

ple teness f or t he si te. Each box-and-wh

is ker plot has a rectangul

ar part called t he bo x. Lines ext ending o ut fro m the t op and bo t t om ed ges of t he bo x ar e ca lled whiske rs. The box represen

ts the mi ddle 50% of the di stribution of the y early in dic es and the posi

tion of the horizontal li ne b etween the top and bott om edges of the box represen

ts the position of

the me dia

n value. The re d do t on t he bo x-a nd- whiske r p lot indicat es t he po sitio n of t he mean va lue fo r t he %age error. The val

ue bel ow the lab el

for each s ite sh

own along the horizontal

axis i s the average “true” f(RH) daily SO 4 i

n n g/m 3 for that site across the y ears of data i

ncl uded the study. The v

ertical li nes (wh is kers) are drawn f

rom the box to the most extreme poi nt withi n 1.5 i nterquartil e ranges (an i nterquartil e range is the di stance be tween the 25th and the 75th sa mpl e %il es). Any val ue m ore ex trem e tha n th i s i s considered

a poten tia l outli er an d m arked wi th a p l ot sy

m bol

. Id en ti f i ca ti on of such da ta v al ue s is d on e to ass i st th

e data an al y st i n ca rry i n g ou t ex pl ora tory da ta analyses a nd ga ining a bet t er unde rst anding o f the dat a and do es no t imply t hat t her e is so mething wron g w i th s uc h d ata va l ue s. O f ten reasons c an

be f oun d that hel p e xp l ai n th e “ ex trem en es s” of pot ential out li ers. An exam in ation of F igures

1 through 6 shows that, in ge neral , the average an

d/or median error is typi

cally bel ow ± 10% . G ener ally tho se sit es in t he West ar e o ver est imated by using average f(RH) val

ues whi le those in the East are underestim

ated.Guidance f or Tracking Progress Under the

Regional Haze R ule

B - 7 Effect of f(RH) value on Year

ly Visibility Index A se con d s tudy wa s c arr i ed out to ex am i ne the ef f ec t on y ea rl y vi si bi l i ty i nd i ce s of diffe re nt cho ice s o f

f(RH) va l uesthat m

ay be sub sti tuted f or f(RH) daily . Fi

ve can didateswere consi dered f or such s ubstitution :

• f(RH) daily = d aily f(RH) val ue

• f(RH) monthly = m onthly average f(RH) val

ues computed as ex

pla in ed earli er

• f(RH) yearly = y early average f(RH) val

ues computed as ex

pla in ed earl i er.

• f(RH) high20 = a ver ag e o f f(RH) daily val

ues computed fro m the hi ghest 20% extin

ction day s f or a given ye ar. These hi

ghest 20% ext inctio n days w er e de t er mined by compu t ing reconstructed extinction usi ng f(RH) daily values , t hen so rt ing the se ex ti nc ti ons an d i denti f y i ng the hi ghes t 20%ex

ti nc ti on day s.

• f(RH) low20 = a ver ag e o f f(RH) daily val

ues computed fro m the l

owest 20% extin

ction day s f or a given ye ar. These lowest 20% ext inctio n days w er e de t er mined by compu t ing reconstructed extinction usi ng f(RH) daily values , t hen so rt ing the se ex ti nc ti ons an d i denti f y i ng the l owe st 2 0% exti

nc ti on days. A sampling da y was includ ed in t he ana lysis o nly when f(RH) daily an d al l of the aeros ol concentrations n

eeded to calcul

ate the reconstruct ed exti nction were avai

la ble for that day. Such a day i s ref er re d to h ere a s a “ com pl ete da y .”Re ca l l th at f(RH) daily is

avai la ble for a day

only if at lea st 16 o f t he ho ur ly f(RH) avera ge s w ere avai l ab l e f or that day

i n th e IM PROVE da

tab as e. F or an y gi v en si te, yea rswi th f ew er th an 50“ com pl ete da y s” weren ot co n si

dere d i n th i s stud y . N ote that ex tin cti on i s com

puted h ere i n i nv erse kil ome ters (1/ km ).Guidance f or Tracking Progress Under the

Regional Haze R ule

B - 8 The foll owing quantities were computed for t he hi ghest 20% ext in

ction days.

• So rt ing was do ne bas ed o n re co nst ru ct ed d aily extinct ion co mput ed u sing f(RH) daily . T he av er ag e e xt inc t io n a nd de civ iew fo rt he hig he st 20 % o f d ays we r e c o mp ut ed

. T he se ar e d en o t ed by ext high, daily and dv high, daily , r es pe ct ive ly.

• So rt ing was do ne bas ed o n re co nst ru ct ed d aily extinct ion co mput ed u sing f(RH) month ly . T he av er ag e e xt inc t io n a nd de civ iew fo rt he hig he st 20 % o f d ays we r e c o mp ut ed

. T he se ar e d en o t ed by ext high, month lyand dv high, month ly , r es pe ct ive ly.

• So rt ing was do ne bas ed o n re co nst ru ct ed d aily extinct ion co mput ed u sing f(RH) yearly . T he av er ag e e xt inc t io n a nd de civ iew fo rt he hig he st 20 % o f d ays we r e c o mp ut ed

. T he se ar e d en o t ed by ext high, yearly and dv high, yearly , r es pe ct ive ly.

• So rt ing was do ne bas ed o n re co nst ru ct ed d aily extinct ion co mput ed u sing f(RH) high20 . T he av er ag e e xt inc t io n a nd de civ iew fo rt he hig he st 20 % o f d ays we r e c o mp ut ed

. T he se ar e d en o t ed by ext high20and dv high20 , r es pe ct ive ly. The foll owing quantities were computed for t he lowest 20% extinction days:

• So rt ing was do ne bas ed o n re co nst ru ct ed d aily extinct ion co mput ed u sing f(RH) daily . The

av erage ex tin cti on an d dec i vi ew f or the l owest 20 % of d

ays we re co mp ut ed

. T he se ar e d en o t ed by ext low,daily and dv low,daily , r es pe ct ive ly.

• So rt ing was do ne bas ed o n re co nst ru ct ed d aily extinct ion co mput ed u sing f(RH) month ly . T he av er ag e e xt inc t io n a nd de civ iew fo rt he hig he st 20 % o f d ays we r e c o mp ut ed

. T he se ar e d en o t ed by ext low,mo nthly and dv low,mo nthly , r es pe ct ive ly.

• So rt ing was do ne bas ed o n re co nst ru ct ed d aily extinct ion co mput ed u sing f(RH) yearly . T he av er ag e e xt inc t io n a nd de civ iew fo rt he hig he st 20 % o f d ays we r e c o mp ut ed

. T he se ar e d en o t ed by ext low,year lyand dv low,year ly , r es pe ct ive ly.

• So rt ing was do ne bas ed o n re co nst ru ct ed d aily extinct ion co mput ed u sing f(RH) high20 . T he av er ag e e xt inc t io n a nd de civ iew fo rt he hig he st 20 % o f d ays we r e c o mp ut ed

. T he se ar e d en o t ed by ext low20 and dv low20 , r es pe ct ive ly. As ment ioned ear lier, o nly “co mplet e da ys,” i. e. , d ays for which da t a we re available for eac h and ever y compo nent of t he eq uat ion fo r r eco nst ru ct ing ext inctio n, w er e us ed in t he abo ve calcul ations.Guidance f or Tracking Progress Under the

Regional Haze R ule

B - 9 The ext inctio n index ( re spe ct ively, dec iview index) base d o n f(RH) daily was t ake n as t he "true " or “cor rect” val

ue. Relative errors, in %, for t he other t hree methods ( f(RH) yearly , f(RH) month ly , a nd o ne o f

f(RH) high20and f(RH) low20 , de pend i ng on w he the r th e h i ghes t 20%ex

ti nc ti on da y s or the l owe st 2 0% exti

nc ti on d ay s a re of i nte res t) of com puti ng rec ons tructed ex ti nc ti on were calculated as fol

lows:

(11) Vis ual sum ma ries of these %age errors are provided i n Fi gures 7 and 8 f

or extinction and Fi

gures 9 and 10 f or decivi ew. We observ

ed that, for extinc

tion or deciv

ie w representi

ng the l owest 20% ext inctio n days, t he index c omp ut ed w ith f(RH) low20 tends to underestim ate the true index , whereas t he indices co mput ed w ith f(RH) month lyor f(RH) yearly ten d to overe sti

matei t. F or ex ti nc ti on or dec iview rep re sent ing t he highes t 20% ext inctio n days, t he index c omp ut ed w ith f(RH) high20tends t o o ver est imate t he t ru e index, wher eas t he indices co mput ed w ith f(RH) month ly or f(RH) yearly ten d to und erestim ate i t. Conclusions: (a) The e ff

ect of an y correl ation

that may exist between

SO 4 and/or NO 3 and f(RH) appe ar s to induce er ro rs t hat ar e, on a ver age , w ithin 10 % o f the t ru e value for ever y site includ ed in t he study. Positi

ve %age errors in

dic ate that t he true in

dex is overestim

ated by the me thod under co nsider at ion. Tha t is, t he met hod re sult s in a po sitive bias . T his will oc cur when t he corresponding c orrelation coef fi ci ent is negati ve. Li kewi se, negati

ve %age errors in

dic ate a ne gati ve bi as. Th i s si tuati on wi

l l occur w hen the corres

pondi ng c orrelati on coef

f i cien t is posi tiv e. The se i m pli cations f

oll ow f rom th e def i ni tion of these %age e rrors. (b) The type

of average f(RH) val

ue used (monthly, yearly

, average o f top 20% extinction day s, avera geof bottom 20%ex ti nc ti on d ay s) ca n h ave a si gn i f i ca nt i m pa ct on the am oun t of err or ind uc ed in t he ca lcu lat io n o f ayea r ly d ec ivie w in de x ba se d o n t he hig he st 20 % ( r es pe ct ive ly, lowest 20%) extin

ction day s. In m ost instance s, the use of a y early or monthl

y a veragef(RH) resul ted in s im il ar %age errors and both procedures resulted i n less error than usi

ng average f(RH) val ues deri ved f rom the worst o r best 20% days . Therefore, the si mpl er cli ma to logical appro ach i s used in

regional h

aze calcul ations.Guidance f or Tracking Progress Under the

Regional Haze R ule

B - 10 Figure B-1 Boxpl ots of yearly %age errors pSO4 yea rly f or 20 se le cted

IM PR OVE s ite s. Thered

do t ind ic ate s t he mean of the %age errors fo r a site computed b ased on y ears of data for that site included in th e study . The value sh own bel ow th e sit e n am e al ong th e h ori zon ta l a xi s is th e mea n of a ver ag e[f( RH) daily *SO4] (ng/m 3 ) for th at si te, av erage d ac

ros s y ea rs. An e xpl anation o f how

to inte rpret the b ox-and-w

his ke r plo t is giv en i n the b od y o f the pap er.Guidance f or Tracking Progress Under the

Regional Haze R ule

B - 11 Figure B-2 Boxpl ots of pSO4 mo nth lyfo r 20 selected IMPROVE site s. The red dot indicates the mean of the %age errors f or a site co mputed b ased o

n ye ars of data fo r that site include d in the study. The value show n belo w the s ite na me a lon g t he hor iz ont al ax is i s th e mea n of a ver ag e[f( RH) daily *SO4] ( ng/m 3 ) f or that s ite, a

ve raged acro ss y

ears. An e xpl anation o f how

to inte rpret the b ox-and-w

his ke r plo t is giv en i n the b od y o f the pap er.Guidance f or Tracking Progress Under the

Regional Haze R ule

B - 12 Figure B-3 Boxpl ots of pNO3 yea rly fo r 20 selected IMPROVE site s. The red dot indicates the mean of the %age errors f or a site co mputed b ased o

n ye ars of data fo r that site include d in the study. The value show n belo w the s ite na me a lon g t he hor iz ont al ax is i s th e mea n of a ver ag e[f( RH) daily *NO3] ( ng/m 3 ) f or that s ite, a

ve raged acro ss y

ears. An exp lan ati on of how to in terp ret t he box-an d-whi sker p lot is gi ven in th e body of the pap er .Guidance f or Tracking Progress Under the

Regional Haze R ule

B - 13 Figure B-4 Boxpl ots of pNO3 mo nth lyfo r 20 selected IMPROVE site s. The red dot indicates the mean of the %age errors f or a site co mputed b ased o

n ye ars of data fo r that site include d in the study. The value show n belo w the s ite na me a lon g t he hor iz ont al ax is i s th e mea n of a ver ag e[f( RH) daily *NO3] ( ng/m 3 ) f or that s ite, a

ve raged acro ss y

ears. An e xpl anation o f how

to inte rpret the b ox-and-w

his ke r plo t is giv en i n the b od y o f the pap er.Guidance f or Tracking Progress Under the

Regional Haze R ule

B - 14 Figure B-5 Boxpl ots of pSO4NO3 yea rly f or 20 se le cted

IM PR OVE s ite s. Thered

do t ind ic ate s t he m ea n o f the %a ge er ror s for a si te com put ed ba sed on year s of da ta for t ha t si te i nc lu ded in th e stu dy. T he val ue sh own bel ow th e sit e n am e al ong th e h ori zon ta l a xi s is th e mea n of a ver ag e[f( RH) daily *(SO4+NO3)] (ng/m 3 ) for th at si te, av erage d ac

ros s y ea rs. An e xpl anation o f how

to inte rpret the b ox-and-w

his ke r plo t is giv en i n the b od y o f the pap er.Guidance f or Tracking Progress Under the

Regional Haze R ule

B - 15 Figure B-6 Boxpl ots of pSO4NO3 mo nth lyf or 20 se le cted

IM PR OVE s ite s. Thered

do t ind ic ate s t he m ea n o f the %a ge er ror s for a si te com put ed ba sed on year s of da ta for t ha t si te i nc lu ded in th e stu dy. T he val ue sh own bel ow th e sit e n am e al ong th e h ori zon ta l a xi s is th e mea n of a ver ag e[f( RH) daily *(SO4+NO3)] (ng/m 3 ) for th at si te, av erage d ac

ros s y ea rs. An e xpl anation o f how

to inte rpret the b ox-and-w

his ke r plo t is giv en i n the b od y o f the pap er.Guidance f or Tracking Progress Under the

Regional Haze R ule

B - 16 Figure B-7 Co

mpa ris on of %ag e e rro rs in average

ex tinc tio n f or LOW ES T 2 0% extin ction days. Th ese values ar e comp ut ed u sin g f(RH) yearl y (r ed p oin ts) , f(RH) mo nth ly(gr een poi nt s), an d f(RH) low20 (blue poin ts). For an y given site, thes e values w

ere c ompute d by

ave raging the %age errors ac ross tho se y

ears f or the site that were

included in the study . The value

show n belo w a s ite name alo

ng the horizontal axis is the mean acros s y ears o f the y

early aver ag e lowes t 2 0% ext in cti on va lu es for th at sit e cal cul at ed u sin g f(RH) daily .Guidance f or Tracking Progress Under the

Regional Haze R ule

B - 17 Figu re B-8 Com pa ri son of

%a ge er ror s in aver ag e ext in cti on f or HIGHE ST 20 % ex

tinc tio n day s. The se v alues are computed usi ng f(RH) yearl y (r ed p oin ts) , f(RH) mo nth ly(green points), an d f(RH) high20 (b lue poi nts). For an y given site, these value s were c ompute d by ave raging the %age errors ac ross tho se y

ears f or the site that were included in t h e s t ud y. The value sh own below

a site na me along t he hor izonta l axis is th e mean acr oss y ears of the yearly average high est 20% ext in cti on va lu es for th at sit e cal cul at ed u sin g f(RH) daily .Guidance f or Tracking Progress Under the

Regional Haze R ule

B - 18 Figure 9. Co

mpa ris on of %ag e e rro rs in average

de civi ew f or LOW ES T 2 0% ex

tinc tio n day s. The se v alues are computed us ing f(RH

) yearl y (r ed p oin ts) , f(RH) mo nth ly(gr een poi nt s), an d f(RH) low20 (blue poin ts). For an y given site, the se v alues w ere co mpu te d b y averaging

the %ag e e rro rs a cro ss

tho se y ea rs f or the site that w ere inc lud ed in the study . The value show

n below a site name along the h orizontal axis is the mean across y ears of the ye arly average lowest 20% deci view va lu es for th at sit e cal cul at ed u sin g f(RH) daily .Guidance f or Tracking Progress Under the

Regional Haze R ule

B - 19 Figure B-10 Co

mpa ris on of %ag e e rro rs in average

de civi ew f or HI GHE ST20 % extin ction days. Th ese values ar e comp ut ed u sin g f(RH) yearl y (r ed p oin ts) , f(RH) mo nth ly(gr een poi nt s), an d f(RH) high20 (blue poin ts). For an y given site, thes e values w

ere c ompute d by

ave raging the %age errors ac ross tho se y

ears f or the site that were

included in the study . The value

show n belo w a s ite name alo

ng the horizontal axis is the mean acros s y ears o f the y

early aver ag e h ig he st 2 0% deci view va lu es for th at sit e cal cul at ed u sin g f(RH) daily .TECHNICAL REPORT DATA (Pl ease read Instructions on reverse before completing)
1. RE PORT NO. EPA-454/B-03-004 2. 3. RECI PIENT' S AC CESS IO

N NO.

4. TITLE AND SUBT ITLE Gu ida nc e fo rT r ac kin g P r o gr es s U nd er t he Re gio na l Ha ze Ru le 5. R EPO RT DA

TE Septembe

r 2003
6. PE RFORMI NG ORGA

NIZATION

CODE
7. AUTHOR( S) U. S. EP A/OAR /OAQ PS /E MAD/ AQT AG 8. PERFORMING ORGANIZ ATION REPORT

NO.

9. PERFO

RMING ORG

ANIZ ATI ON NAME

AND ADDRESS Offic e of A

ir Quality Planning and Standards Emi ss ion s, Mon it ori ng an d Ana lysi s Di vis ion U.S . En viron ment al P rote ction Agency Research Triangle Park, NC 27711 10. PROGRAM ELEME NT NO.

11. CONT

RACT/GRANT NO. 68- D-02- 0261 Work Ord er

No. 1- 06 12. S PONSORING

AGENCY

NAME AN

D ADDRESS Dir ect or Offic e of A

ir Quality Planning and Standards U.S . En viron ment al P rote ction Agency Research Triangle Park, NC 27711 13. TY PE OF REPOR T AND PERIOD COVER ED Guidance doc

ument
14. SPONSORING AGENCY CODE EPA/200/04

15. SUPPLEMENTARY NOTES

16. ABS TRA

CT The pu rp ose of this document is to p rovide guida nce to the St at es in implemen ting the r egional haz e progr am under t he Cle an A ir A ct. Aspart o f th

e pro gram

, th is do cum en t pro vide s g ui dan ce toEPA Re gioal, St

ate, and Tribal air quality man agem ent a uth orit ies an d th e gener al pu blic, on how EPA in tend s to exerci se its di screti on in impl emen tin g Clea n Ai r Act prov isio ns and EPA

regul ations, co

ncerning the

tracki ng of prog ress under the

regio nal haze pro gram.

17. KEY WORDS AND D OCUMENT ANALYSIS

a. DESCRI PT ORS b. IDENTIFI ERS/OPEN ENDED TE

RMS c. COS AT I Fi eld/ Group Regio nal Haze, Haze

I ndex Air Pol lu ti on cont rol

18. D ISTRIBU

TION STATEME

NT Unlimited 19. SECU RITY CL

ASS (Report) Unclassified 21. NO . OF PAGES

20. SECU

RITY CL

ASS (Page) Unclassified 22. PRICE

EPA Form 2220 -1 (Rev . 4-77) PREVI OUS E DITION IS OBSOLE

TEUnit ed Stat es Off ice o f Air Quality P lann ing an d Standar ds Publication No . EPA-454/B-03-004 En vir onm en ta l Pr otect ion Em iss ion s, M oni tor in g a nd An al ysis D ivi sion Septembe r 2003 Agen cy Research Tr iangle Park, NC

Postal inf ormatio n in this sec

tion wh ere appro priate.