understanding fine particle episodes in the upper midwest during the 2009 ladco winter nitrate study...

Understanding fine particle episodes in the Upper Midwest during the 2009 LADCO Winter Nitrate Study using CMAQ and CAMx: model performance, processes,

and response to emissions controls

Charles Stanier – University of Iowa

[email protected]

319-335-1399CENTER FOR GLOBAL AND REGIONAL ENVIRONMENTAL RESEARCH

mailto:[email protected]

IDNR Workgroup - Stanier 2Sept 9, 2010

Co-authors and Acknowledgements• University of Iowa

– Scott Spak– Gregory Carmichael– Charles Stanier– Jaemeen Baek– Sang Rin Lee– Yoo Jung Kim– Timothy Rohlf– Sinan Sousan– Ashish Singh

• University of Illinois– Nicole Riemer

• EPRI– Stephanie Shaw– Naresh Kumar

• Measurements– Eric Edgerton (ARA Inc)– Mike Caughey (ISWS)– Wisconsin DNR staff – Joe Leair, Jerry Medinger, Dan Nickolie,

Mary Mertes, Bruce Rodger, and Bart Sponseller

– Site operators by John Hillery, Janel Hanrahan, Laura Carnahan

• LADCO (Lake Michigan Air Directors Consortium)– Michael Koerber– Donna Kenski– Mark Janssen– Abigail Fontaine

• Wisconsin DNR– Michael Majewski– Bill Adamski

• Funding– LADCO– Electric Power Research Institute

3

Motivation?• Recurrent cold weather PM2.5

episodes greatly influence air quality in this region.

• Similarities to California’s Central Valley (Pun and Seigneur 1999; McMurry, Shepherd et al. 2004) and to Northwestern Europe and the Po Valley of Italy (Schaap, van Loon et al. 2004; Putaud, Van Dingenen et al. 2010).

DJF MAM

JJA SON

Figure 2-2. Eight year average of PM episode activity divided by season. Quantified by an episode indicator (see note ii).

• What is known? – Episodes are tightly coupled with meteorological conditions.– Ammonium nitrate comprises a large fraction of the PM2.5 during episodes.

– Chu 2004; McMurry, Shepherd et al. 2004; Blanchard and Tanenbaum 2008; Klatzman, Rutter et al. 2009; LADCO 2009; Pitchford, Poirot et al. 2009.

4

LADCO Winter Nitrate Study(Jan 1 – Mar 31, 2009)

SpeciesAveraging time (hr) Species

Averaging time (hr)

PM2.5 1hr PM2.5 24hr 1 in 3days

SO4 1hr NH4 24hr 1 in 3days

NO3 1hr NO3 24hr 1 in 3days

NH4 1hr SO4 24hr 1 in 3days

HNO3 1hr OC 24hr 1 in 3days

NH3 1hr EC 24hr 1 in 3days

NOy 1hr O3 1hr

NOx (note 6) 1hr Relative Humidity

1hr

SO2 (note 7) 1hr Surface pressure

1hr

Temperature 1hr Visibility 1hrWind Speed 1hr Precipitation 1hrWind direction 1hr HNO3 24hr

NH3 24hr H2SO3, H2SO4 24hr

6

Science Questions for the Study

Composition: Typical chemical composition during episodes and non-episodes?

Urban-rural contrast: Differences in PM2.5 concentrations (frequency and severity), chemical composition, and source regions?

Meteorology: What meteorological conditions favor winter-time episodes? How can we best use this information to improve wintertime episode forecasting?

Nitrate formation chemistry: What do the data tell us the nitrate formation chemistry leading to events?

Sensitivity of episodes:• How sensitive are concentrations to hypothetical changes in total nitrate,

total ammonia, and total sulfate?• What sources categories have leverage on episodes? Do local sources

have influence?

3D Model skill: Can photochemical modeling accurately predict PM2.5 concentrations during the observed winter-time episodes?

Parameter Milwaukee(Urban)

Mayville(Rural)

PM2.5 (µg m-3) 17.1 11.7

Total nitrate (µg m-3) 5.6 4.8Total ammonia (µg m-3) 3.3 3.3Gas ammonia (ppb) 2.3 2.4Nitrate aerosol / total nitrate 78% 69%NOy (ppb) 27 6.3

Temperature (°C) -3 -5Ozone (ppb) 22 31OC (µg m-3) 3.6 3.2EC (µg m-3) 0.5 0.3Gas Ratio (d’less) 1.5 1.7

0

10

20

30

40

50

60

70

1/1/

09

1/8/

09

1/15

/09

1/22

/09

1/29

/09

2/5/

09

2/12

/09

2/19

/09

2/26

/09

3/5/

09

3/12

/09

3/19

/09

3/26

/09

PM

2.5

(µg

m-3

)

Mil PM2.5 (h) Mil PM2.5 (d) May PM2.5 (h) May PM2.5 (d) Mil epi May epi

J-I J-II J-III J-IV F-I F-II F-III F-IV M-I M-II III M-IV

60

40

20

0

PM

2.5

(µg

m-3)

Jan Feb Mar

PM

2.5

(μg

m-3

)

Jan III episode

A. Milwaukee, WI

B. Mayville, WI

Ozo

ne (

ppb

)

NO

, N

O2, N

Oy,

NO

3, H

NO

3(p

pb

)

Jan III episode

C. Milwaukee, WI

D. Mayville, WI

Detailed view of an episode

Agreement between multiple

independent measurements

12% 19% 11% 17% 12% 19%

26%

38%31%

45%

23%

37%12%

17%

13%

19%

12%

17%50%

26%44%

20%

53%

27%

0%

20%

40%

60%

80%

100%

Other

NH4

NO3

SO4

0

10

20

30

40

Other

NH4

NO3

SO4

Composition

Gas ratios (ammonia availability) ranges 1.0-1.7. Lowest at the rural site during episodes. Evidence of gas ratio ↓ during episodes at multiple sites in the region.

PM

2.5 (

µg

m-3)

PM

2.5 fr

actio

n

Urban-Rural Contrast During Episodes

Some excess in total nitrate, but nitrate and ammonium appear predominantly regional.

For aerosol species, urban excess of OC during episodes is significant.

0

10

20

30

40

0 15 30 45 60 75 90

Snow

wat

er e

quiv

alen

t (m

m) a

nd s

now

subl

imati

on

and

mel

t in

mm

d-1

SWE

Julian Day

Episode indicator

Snow amount

Snow melt

Snow sublimation

Fog index

J-I J-II J-III J-IV F-I F-III F-IV M-I M-II M-IVJ-V F-II M-III

A

Meteorology

• Episodes began under similar synoptic conditions – arrival of a surface low pressure system.

• Episodes were marked by inversions with warm, moist air and low wind speeds. • Snow cover and fog were both correlated with episode occurrence. • Regional snow cover was present over southeastern Wisconsin and northern

Illinois at the onset of late winter episodes and usually melted by episode end.

Model Configuration• Community Multiscale Air Quality Model

(CMAQ) v4.7.1– CB05 gas phase / AERO5 aerosol module – ACM2 PBL closure– Mass-conserving advection– 14 vertical layers

• LADCO’s 12 km regional modeling grid– Hourly boundary conditions from a 36 km simulation

(with the same configuration) covering the continental United States.

• Meteorology– WRF 3.1.1 with the RPO configuration selected by Iowa

DNR, SESARM, and LADCO– ACM2 PBL closure– Pleim-Xu land surface module– RRTM radiation– Morrison microphysics– Kain-Fritsch cumulus– Boundary meteorology from the North American

Regional Reanalysis 3-hourly – Analysis nudging on NARR above the PBL (no direct

observational nudging)

• Emissions– LADCO’s 2008 emissions inventory used for 12km

domain.– Day-specific biomass burning emissions from MODIS

fire detection products. – NEI with day- specific biomass burning will be used for

36 km continental simulations.

• Process Analysis– Chemical and process rates stored for all layers up to

550 m, with focus on NOy processing and N2O5 heterogeneous chemistry

Model Skill

1-Ja

n

8-Ja

n

15-J

an

22-J

an

29-J

an

5-F

eb

12-F

eb

19-F

eb

26-F

eb

5-M

ar

12-M

ar

19-M

ar

26-M

ar

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

Mil PM2.5(h)_obs Mil PM2.5(h)_model Mil epi

PM

2.5

(µ

g m

-3)

J-I J-II J-III J-IV F-I F-II F-III F-IV M-I M-II III M-IV

Network Species Observed Model

AQS Ozone 29.8 35.0

Improve PM2.5 7.0 8.6

SO4 1.8 2.6

STN PM2.5 12.1 15.4

NO3 3.0 3.0

NH4 1.7 2.0

SO4 2.4 3.6

30

20

10

0

Con

cent

ratio

n (µ

g m

-3)

Mil a

ll hou

rs

May

all h

ours

Mil e

pisod

es

May

epis

odes

Mil n

on e

pisod

es

May

non

epis

odes

Other (obs) NH4 (obs) NO3 (obs) SO4 (obs) NH3(g) as NH4 (obs) HNO3(g) NO3 (obs)

Other (mod) NH4 (mod) NO3 (mod) SO4 (mod) NH3(g) NH4 (mod) HNO3(g)NO3 (mod)

Model Skill

• Total ammonia underprediction during almost all periods and sites.• Shows as deficit in gas phase ammonia.• Nitrate underprediction during episodes.• Systematic OC underprediction (not shown) but offset by CMAQ other inorganics

15

Reaction Reactants ProductsR1 NO2 + hν NO + OR3 O3 + NO NO2

R4 O + NO2 NOR5 O + NO2 NO3

R6 O + NO NO2

R7 NO2 + O3 NO3

R14 NO3 NO2 + OR15 NO3 NOR16 NO2 + NO 2 NO2

R17 NO3 + NO2 NO + NO2

R18 NO3 + NO2 N2O5

R19 N2O5 + H2O 2 HNO3

R20 N2O5 + H2O + H2O 2 HNO3

R21 N2O5 NO3 + NO2

R22 NO + NO + O2 2 NO2

R23 NO + NO2 + H2O HONOR24 NO + OH HONOR25 HONO NO + OHR26 OH + HONO NO2

R27 HONO + HONO NO + NO2

R28 NO2 + OH HNO3

R29 OH + HNO3 NO3

R30 HO2 + NO OH + NO2

R31 HO2 + NO2 PNAR32 PNA HO2 + NO2

R33 OH + PNA NO2

R46 NO3 + O NO2

R47 NO3 + OH HO2 + NO2

R48 NO3 + HO2 HNO3

R49 NO3 + O3 NO2

R50 NO3 + NO3 2 NO2

R51 PNA 0.61HO2 + 0.61NO2 + 0.39OH + 0.39NO3

R52 HNO3 OH + NO2

R53 N2O5 NO2 + NO3

R89 PAN C2O3 + NO2

R90 PAN C2O3 + NO2

IntegratedReaction Rate Analysis

Nitrate formation analysis by process analysis

NO2 + OH HNO3 (R1)

NO2 + O3 NO3 + O2 (R2)

NO3+NO2 ↔ N2O5 (R3)

N2O5 NO2 + NO3 (R4)

NO3 + VOC organic products (R5)

N2O5 + H2O 2HNO3 (R6)

RH and composition dependent accommodationcoefficient, uncertain

Daytime

Averages 0.075 ppb/hr in surface layer

Nighttime

Averages0.044 ppb/hrin surface layer

Understanding PM Iowa - Stanier 17Jan 9, 2009

10

8

6

4

2

-0.010 0.010 0.030 0.050 0.070 0.090 0.110 0.130 0.150

Milwaukee

hom. hydrol.OH+NO2het. hydrol.

Average HNO3 production in ppb/hr

laye

r

10

8

6

4

2

-0.010 0.010 0.030 0.050 0.070 0.090 0.110 0.130 0.150

Mayville

hom. hydrol.OH+NO2het. hydrol.

Average HNO3 production in ppb/hr

laye

r

Emissions Sensitivity: Emissions Scenarios

• 30% NOx from base case

• 30% NH3 from base case

• 2015 Proxy Case– Simulate near-term changes in mobile NOx & simulate

approximation of implementation of Cross State Air Pollution Rule (CSAPR) effect on coal-fired power plant NOx & SOx emissions

-70% EGU SO2

-10% EGU NOx

-30% mobile NOx

• Additional scenarios: add all-sector reductions to the 2015 Proxy Case- 30% NH3

- 30% NOx

- 30% NH3 & - 30% NOx

Emissions Sensitivity Methods

• Direct Sensitivity

• Hybrid Box Model Sensitivity

– Input to sensitivity case box model?– Measured T and RH– Measured total sulfate, ammonia, and nitrate x fractional

reduction in these species predicted by CMAQ model

Thermodynamic Sensitivity / Model Skill

30%

NO

x

30%

NH

3

2015

Pro

xy

2015

Pro

xy +

30

% N

Ox

2015

Pro

xy +

30

% N

H3

2015

Pro

xy +

30

% N

Ox,

30

% N

H3

0

5

10

15

20

25

Direct CMAQ Sensitivities to Emissions versus ISORROPIA Model Hybrid of Modeled and Measured Values

(During hours with > 27 µg m-3 measured PM2.5)

Milwauk CMAQ

Milwauk Hybrid

Mayville CMAQ

Mayville Hybrid

Re

du

cti

on

in

In

org

an

ic P

M (

%)

30% NOx Cut only reduces TNO3 by less than 12%

30% NH3 Cut reduces TNH3 by 22% or more

30% NH3 Cut reduces PM2.5 by 10-15%

PM ↓

PM ↑

Graphing % Reduction TNO3 Case: 30% NOx Cut

Graphing % Reduction TNH3 Case: 30% NH3 Cut

Graphing % Reduction PM2.5

Case: 30% NOx CutGraphing % Reduction PM2.5

Case: 30% NH3 Cut

22

Conclusions – A refined conceptual model of wintertime episodes in the Upper Midwest

Composition: Confirming results from past studies. Database of time-resolved concentrations now available.

Urban-rural contrast: More episodes recorded at urban site. Urban primary pollutant enhancement quantified. Urban secondary enhancement <20% of inorganic total on average.

Primary sources? Local primary OC important. Role of primary local NOx under investigation with CMAQ.

Meteorology: Meteorology critical to episode occurrence and prediction. Stagnant low pressure systems, warmer than average temperatures, low wind speeds, low mixing heights. Snow cover, snow melt, and fog correlated with episodes.

Nitrate formation chemistry: Both daytime and nighttime pathways important.

Sensitivity of episodes: Direct modeled sensitivity from CMAQ is fairly accurate despite low NH3 bias. System responds to either reductions in total nitrate or total ammonia, but NOx controls inefficient at delivering total nitrate reduction in NOx source regions. Impact of local vs. regional NOx reductions under investigation.

3D Model skill: Fairly skilled, especially on average. Mixed skill for timing and intensity of individual episodes.

Thank You!

Full reports on LADCO Winter Nitrate Study available at

ladco.org and on Stanier group website

Questions?

Nitrate formation analysis by process analysis

NO2 + OH HNO3 (R1)

NO2 + O3 NO3 + O2 (R2)

NO3+NO2 ↔ N2O5 (R3)

N2O5 NO2 + NO3 (R4)

NO3 + VOC organic products (R5)

N2O5 + H2O 2HNO3 (R6)

RH and composition dependent accommodationcoefficient, uncertain

Daytime

Averages 0.075 ppb/hr in surface layer

Nighttime

Averages0.044 ppb/hrin surface layer

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

Mil allhours

May allhours

Milepisodes

Mayepisodes

Mil nonepisodes

May nonepisodes

Gas

Rati

o

GR (obs)

GR (mod)

Model Skill Continued… Gas Ratio Prediction Skill

• Measurements 1.0 – 1.7. Model low on ammonia, but also low on sulfate and nitrate. Model range 1.1 – 1.5.

Model Skill … Additional Evaluation Using Diurnal Patterns

Model Observations

Tem

p.N

itrat

eS

ulfa

te

All Sites Gas Ratio

0

0.5

1

1.5

2

2.5

Gas Ratio

All hours Episodes Non-episodes

Figure 4-13. Gas ratio for the four sites during episode and non episode periods.

NH3 rich

NH3 poor

Ammonia Availability


Approach

• Run ISORROPIA for every hour of the study using 400 different cases with varying reductions in– Total ammonia (10), total sulfate (4), and total

nitrate (10)• Make contour plots showing ammonia vs.

nitrate sensitivity for constant sulfate cases.


We propose operational definitions of sensitivity based on RSM as follows:

∞ > RSM > 8 Nitrate sensitive / ammonia insensitive

8 > RSM > 2 More sensitive to nitrate than to ammonia

2 > RSM > 0.5 Nitrate and ammonia sensitivity approximately balanced

0.5> RSM > 0.125 More sensitive to ammonia than to nitrate

0.125 > RSM Ammonia sensitive / nitrate insensitive

Symbol in this work Name Formula

SNO3-f Sensitivity to a fractional reduction in

total nitrate 33,5.2,5.2

TNOTNO

PMPM inorginorg

SNH3-f Sensitivity to a fractional reduction in

total ammonia 33,5.2,5.2

TNHTNH

PMPM inorginorg

RSf Relative sensitivity (on fractional

basis)

SNO3-f / SNH3-f

SNO3-M Sensitivity to a mass reduction in total

nitrate 3,5.2

TNO

PM inorg

SNH3-M Sensitivity to a mass reduction in total

ammonia 3,5.2

TNH

PM inorg

RSM Relative sensitivity (on mass basis) SNO3-M / SNH3-M


Table 7-4 summarizes the sensitivities to 30% total nitrate reductions, 30% total ammonia

reductions, and combined 30/30 nitrate and ammonia reductions.

Mayville Milwaukee Variable or Case Hours

with no episode

All study hours

All episode hours

Hours with no episode

All study hours

All episode hours

BASE CASE - ISORROPIA inorganic PM with 0% / 0% reductions in TNO3 and TNH3 (μg m-3)

ISORROPIA inorganic PM with 30% / 0% reductions in TNO3 and TNH3 (μg m-3)

10.4

9.1

11.2

9.7

31.2

26.9

13.5

12.6

16.8

15.4

34.5

31.1


8.6 9.2 24.6 12.0 14.7 29.4


9.5 10.1 25.5 12.6 15.5 31.3

Total nitrate (µg m-3) 4.52 4.79 12.35 4.55 5.62 12.04

Total ammonia (µg m-3) 3.15 3.24 5.79 2.77 3.30 6.24

RSf 1.47 1.34 0.74 1.04 1.04 1.03

RSM 1.03 0.91 0.35 0.63 0.61 0.54

Classification balanced balanced More NH3

sensitive

balanced balanced balanced

Median gas ratio (from section 4) 1.69 1.66 0.98 1.59 1.50 1.35

Expected sensitivity based on gas ratio (see table 7-3)

More sensitive to nitrate

than to ammonia


than to ammonia

More NH3

sensitive


than to ammonia


than to ammonia


than to ammonia

32

Comparison to Blanchard Midwest Ammonia Monitoring Project

33

Nitrate sensitivity vs. PM - This study and Blanchard 2008

0.00

0.50

1.00

1.50

2.00

2.50

0.0 10.0 20.0 30.0 40.0 50.0 60.0

PM2.5 (ug/m3)

Sen

siti

vity

to

nit

rate

rel

ativ

e to

am

mo

nia

(m

ass

bas

is)

This study

Blanchard 2008

1A

2A

3A4A

5A1E

3E 4E 5E

1 Great River Bluffs MN (A=DJF avg; E=Feb 3, 2005 episode)2 Mayville WI (A=DJF avg) 3 Lake Sugema IA (A=DJF avg; E=Feb 3, 2005 episode) 4 Bondville IL (A=DJF avg; E=Feb 3, 2005 episode) 5 Allen Park MI (A=DJF avg; E=Feb 3, 2005 episode) a Mayville (JFM avg; no episodes)b Mayville (JFM avg; all hours)c Mayville (JFM avg; episodes)d Milwaukee (JFM avg; no episodes)e Milwaukee (JFM avg; all hours)f Milwaukee (JFM avg; episodes)

a

bd

e

cf

Milwaukee (d-e-f)

Lake Sugema

Mayville study-study comparison

Mayville episodes

34

Nitrate sensitivity vs. PM - This study and Blanchard 2008

0.00

0.50

1.00

1.50

2.00

2.50

0.0 10.0 20.0 30.0 40.0 50.0 60.0

PM2.5 (ug/m3)

Sen

siti

vity

to

nit

rate

rel

ativ

e to

am

mo

nia

(m

ass

bas

is)

This study

Blanchard 2008

1A

2A

3A4A

5A1E

3E 4E 5E

1 Great River Bluffs MN (A=DJF avg; E=Feb 3, 2005 episode)2 Mayville WI (A=DJF avg) 3 Lake Sugema IA (A=DJF avg; E=Feb 3, 2005 episode) 4 Bondville IL (A=DJF avg; E=Feb 3, 2005 episode) 5 Allen Park MI (A=DJF avg; E=Feb 3, 2005 episode) a Mayville (JFM avg; no episodes)b Mayville (JFM avg; all hours)c Mayville (JFM avg; episodes)d Milwaukee (JFM avg; no episodes)e Milwaukee (JFM avg; all hours)f Milwaukee (JFM avg; episodes)

a

bd

e

cf

Milwaukee (d-e-f)

Lake Sugema

Mayville study-study comparison

Mayville episodes

I

II

IIIIV

I nitrate sens > ammonia sensII balanced sensitivityIII ammonia sens > nitrate sensIV only sensitive to ammonia

35

Future Work

• Modeling episodes at 12 km with CMAQ• Look at sensitivity in model versus

measured sensitivity• Look at skill for total ammonia and total

nitrate• Investigate skill for total nitrate (and NOx

and NOy) temporal and spatial patterns• Investigate link between O3 and nitrate

formation

Supporting slides


Table 3-1 Species measured at MILWAUKEE and Mayville site

Measurement Time average Units Source Method PM2.5

SO4 NO3 NH4 HNO3 NH3 NOx

1 SO2

2 TEMP Wind Speed Wind direction NH3 HNO3 SO2 PM2.5 NH4 NO3 SO4 OC NOy O3 Relative Humidity3 Surface pressure3 Visibility3 Precipitation3

1hr 1hr 1hr 1hr 1hr 1hr 1hr 1hr 1hr 1hr 1hr 24hr 24hr 24hr 24hr 1 in 3days 24hr 1 in 3days 24hr 1 in 3days 24hr 1 in 3days 24hr 1 in 3days 1hr 1hr 1hr 1hr 1hr 1hr

µg m-3 µg m-3 µg m-3 µg m-3 ppbv ppbv ppbv ppb Deg F

mph

Comp Deg ppbv ppbv ppbv µg m-3 µg m-3 µg m-3 µg m-3 µg m-3 ppb ppb % mbar km mm

WDNR ARA ARA ARA ARA ARA WDNR WDNR WDNR WDNR WDNR ISWS ISWS ISWS WDNR WDNR WDNR WDNR WDNR ARA WDNR NWS NWS NWS NWS

FDMS EPA Param 88101 See text See text See text See text See text EPA Param 42603 EPA Param 42401 Denuder Denuder Denuder FRM EPA Param 88101 FRM EPA Param 88101 FRM EPA Param 88301 FRM EPA Param 88401 FRM EPA Param 88350 See text

1.hourly NOx is only available at MILWAUKEE

2.hourly SO2 is only available at Mayville


Table 3-2 Species available at SEARCH network. All variables provided by ARA.

Measurement Time average Units PM2.5

SO4

NO3 NH4 HNO3 NH3

O3

CO SO2

NO/NO2/NOx NOy

BC TC OC Wind Speed Wind direction TEMP Relative Humidity Station pressure Precipitation Solar radiation

1hr 1hr 1hr 1hr 1hr 1hr 1hr 1hr 1hr 1hr 1hr 1hr 1hr 1hr 1hr 1hr 1hr 1hr 1hr 1hr 1hr

µg m-3

µg m-3

µg m-3

µg m-3

ppb ppb ppb ppb ppb ppb ppb ppb µg m-3

µg m-3

ms-1

Compass Deg deg C % mbar mm Wm-2


Milwaukee Concentrations

0.00

10.00

20.00

0.00 10.00 20.00 30.00 40.00 50.00 60.00

PM2.5

Sp

ecie

s C

on

cen

trat

ion

s (u

g/m

3)

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

1.80

TNO3

TNH3

OC

GR

Linear (GR)

Linear (TNO3)

Linear (TNH3)

Figure 4-14. Total nitrate, total ammonia, OC, and gas ratio as a function of PM2.5 for various periods in the Milwaukee dataset. Top figure has outlier gas ratio and OC/EC values, while bottom figure has these excluded. Lines are linear fits. Gas ratio decreases slightly with increasing PM2.5, reflecting greater enhancement of nitrate than of ammonia.


Mayville Concentrations

0

2

4

6

8

10

12

14

16

18

0 10 20 30 40

PM2.5

Sp

ecie

s C

on

cen

trat

ion

s (u

g/m

3)

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

1.80

Gas

Rat

io

TNO3

TNH3

OC

GR

Linear (GR)

Linear (TNO3)

Linear (TNH3)

Figure 4-15. Total nitrate, total ammonia, OC, and gas ratio as a function of PM2.5 for various periods in the Mayville dataset. Gas ratio decreases slightly with increasing PM2.5, reflecting greater enhancement of nitrate than of ammonia.

Jan 9, 2009 42

January 22 (11 am) January 24 (11 am)2009 2009


](mol)[NO](mol)[HNO

](mol)[NO](mol)[NH

TN

DSNxTSTA

nitrate total

ammonia freedjGR

-33

-33

A

](mol)[SO

](mol)[NO](mol)[NHDSN

-4

-34

Two additional measures of ammonia availability are the gas ratio GR and Excess Ammonia

(EA) (Blanchard, Roth et al. 2000).

TN

2xTSTA

nitrate total

tionneutraliza full of assumptionunder ammonia freeGR

](mol)[NO](mol)[HNO

](mol)[NO](mol)[NH

TN

DSNxTSTA

nitrate total

ammonia freedjGR

-33

-33

A

](mol)[SO

](mol)[NO](mol)[NHDSN

-4

-34

Two additional measures of ammonia availability are the gas ratio GR and Excess Ammonia

(EA) (Blanchard, Roth et al. 2000).

TN

2xTSTA

nitrate total

tionneutraliza full of assumptionunder ammonia freeGR


Symbol in this work Name Formula

SNO3-f Sensitivity to a fractional reduction in

total nitrate 33,5.2,5.2

TNOTNO

PMPM inorginorg

SNH3-f Sensitivity to a fractional reduction in

total ammonia 33,5.2,5.2

TNHTNH

PMPM inorginorg

RSf Relative sensitivity (on fractional

basis)

SNO3-f / SNH3-f

SNO3-M Sensitivity to a mass reduction in total

nitrate 3,5.2

TNO

PM inorg

SNH3-M Sensitivity to a mass reduction in total

ammonia 3,5.2

TNH

PM inorg

RSM Relative sensitivity (on mass basis) SNO3-M / SNH3-M

The conversion between RS f and RSM is simply:

3

3

TNH

TNORSRS Mf and

3

3

TNO

TNHRSRS fM

45

AmmoniaPM

NOx

Local ReactionNOx → Nitric Acid

Reacted NOxNitric Acid

Regionally Transported Pollutants

Emissions from Local Counties

PM NOx Ammonia

GasesNOxAmmoniaNitric Acid

Nitrogen Leaving the Balance as Gas

AmmoniumNitrate PM

Facility SpecificEmissions Within ~3 km

Human Exposure to Mixed PM

Regional “Other” PM – Ammonium Sulfate, Organics

Local Primary PM – e.g. Vehicle & Industry Emissions

weather

amm

onia

Nitric acid

46

Each winter is very different

IDNR Workgroup - Stanier 47Sept 9, 2010

Species Ox State Compound Class

N2O5 +5 NOy

HNO3 +5 NOy

NO3- ion +5 NOy

PAN +5 NOy

NO3 radical +5 NOy

HONO +3 NOy

NO2 +4 NOx & NOy

NO +2 NOx & NOy

NH4+ ion -3 RN

NH3 -3 RN


0

2

4

6

8

10

Mil

wau

kee

TN

O3

May

vill

e T

NO

3

Mil

wau

kee

TN

H3

May

vill

e T

NH

3

Mil

wau

kee

SO4

May

vill

e SO

4

Mil

wau

kee

NO

3(p)

May

vill

e N

O3(

p)

Mil

wau

kee

NH

4(p)

May

vill

e N

H4(

p)

Mil

wau

kee

NH

3(g)

May

vill

e N

H3(

g)

Mil

wau

kee

HN

O3(

g)

May

vill

e H

NO

3(g)

ug m

-3 o

r pp

b

Integrated

Original ARA

Revised ARA

Good

Goo

d

Nee

dsIm

prov

e

Goo

d

Goo

d

Poo

r VeryGood Good

Good Good

Nee

dsIm

prov

e

Poo

r

At / Near Detection

Limit

Figure 4-1. Comparison of 24 hour and hourly datasets. Y axis is the mean of the paired samples. Aerosols (labeled as (p) for particulate), total nitrate, and total ammonia as μg m-3, and gases as ppb. Error bars show 95% confidence interval on an individual ARA measurement at the mean concentration. Qualitative rating is based on two factors: bias relative to 24 hour average measurement in the original ARA data, and size of confidence interval in the revised ARA data. See table A2-4.

Jan 9, 2009 49

Figure 7-3. Sensitivity of PM2.5 to reductions in total nitrate and total ammonia.

SITE: MILWAUKEE

PERIOD: ALL STUDY HOURS

SULFATE LEVEL: 100% OF MEASURED VALUE

Jan 9, 2009 50


SITE: MILWAUKEE

PERIOD: ALL STUDY HOURS


Jan 9, 2009 51


SITE: MILWAUKEE

PERIOD: ALL EPISODE HOURS ONLY


Jan 9, 2009 52


SITE: MAYVILLE

PERIOD: ALL EPISODE HOURS ONLY


Jan 9, 2009 53

54Jan 9, 2009

Monthly mean emissions (2001 NEI)BC NH3

55Jan 9, 2009

Monthly mean emissions (2001 NEI)NOx SO2

understanding fine particle episodes in the upper midwest during the 2009 ladco winter nitrate study...

Documents

total nitrate g

sensitivity of episodes

total ammonia g

observed wintertime

ammonium nitrate

ladco winter nitrate

nitrate formation chemistry

fine particle episodes