understanding fine particle episodes in the upper midwest during the 2009 ladco winter nitrate study...
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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
319-335-1399CENTER FOR GLOBAL AND REGIONAL ENVIRONMENTAL RESEARCH
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
Understanding PM Iowa - Stanier 25Jan 9, 2009
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
Understanding PM Iowa - Stanier 29Jan 9, 2009
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.
Understanding PM Iowa - Stanier 30Jan 9, 2009
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
Understanding PM Iowa - Stanier 31Jan 9, 2009
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
ISORROPIA inorganic PM with 30% / 30% reductions in TNO3 and TNH3 (μg m-3)
8.6 9.2 24.6 12.0 14.7 29.4
ISORROPIA inorganic PM with 0% / 30% reductions in TNO3 and TNH3 (μg m-3)
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
More sensitive to nitrate
than to ammonia
More NH3
sensitive
More sensitive to nitrate
than to ammonia
More sensitive to nitrate
than to ammonia
More sensitive to nitrate
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
Understanding PM Iowa - Stanier 37Jan 9, 2009
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
Understanding PM Iowa - Stanier 38Jan 9, 2009
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
Understanding PM Iowa - Stanier 39Jan 9, 2009
Understanding PM Iowa - Stanier 40Jan 9, 2009
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.
Understanding PM Iowa - Stanier 41Jan 9, 2009
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
Understanding PM Iowa - Stanier 43Jan 9, 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
Understanding PM Iowa - Stanier 44Jan 9, 2009
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
Understanding PM Iowa - Stanier 48Jan 9, 2009
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
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 51
Figure 7-5. Sensitivity of PM2.5 to reductions in total nitrate and total ammonia.
SITE: MILWAUKEE
PERIOD: ALL EPISODE HOURS ONLY
SULFATE LEVEL: 100% OF MEASURED VALUE
Jan 9, 2009 52
Figure 7-6. Sensitivity of PM2.5 to reductions in total nitrate and total ammonia.
SITE: MAYVILLE
PERIOD: ALL EPISODE HOURS ONLY
SULFATE LEVEL: 100% OF MEASURED VALUE
Jan 9, 2009 53
54Jan 9, 2009
Monthly mean emissions (2001 NEI)BC NH3
55Jan 9, 2009
Monthly mean emissions (2001 NEI)NOx SO2