uncertainties in pm2.5 gravimetric and speciation ... · pdf fileuncertainties in pm2.5...
TRANSCRIPT
Uncertainties in PM2.5 Gravimetric and Speciation Measurements and
What Can We Learn from Them
• William Malm• Cooperative Institute for Research in the Atmosphere, Colorado State University,
Fort Collins, CO 80523-1375
• Bret A. Schichtel • National Park Service-Air Resources Division, CIRA, Colorado State University,
Fort Collins, CO 80523-1375
• Marc L. Pitchford• National Oceanic and Atmospheric Administration-Air Resources Laboratory, c/o
Desert Research Institute, 755 E Flamingo Rd, Las Vegas, NV 89119-7363
Non-urban and urban PM2.5
networks
Non-urban and urban PM2.5
networksInteragency Monitoring of
PROtected Visual Environments
(IMPROVE) Network
Interagency Monitoring of
PROtected Visual Environments
(IMPROVE) Network
Chemical Speciation Network (CSN)
Chemical Speciation Network (CSN)
Virgin IslandsVirgin Islands
Neighborhood- and Urban-Scale
Monitoring Objectives
Neighborhood- and Urban-Scale
Monitoring Objectives
• Determine compliance with air quality
standards
• Validation of regional scale models
• Assess source/receptor relationships
• Evaluate health, radiative, and
ecological effects
• Determine compliance with air quality
standards
• Validation of regional scale models
• Assess source/receptor relationships
• Evaluate health, radiative, and
ecological effects
IMPROVE Monitoring ObjectivesIMPROVE Monitoring Objectives
• Tracking long term temporal changes in
visibility (extinction)
• Assess source/receptor relationships
• Serve as a regional backdrop for
special studies and understanding non
urban background
• Used for regional modeling validation
studies
• Tracking long term temporal changes in
visibility (extinction)
• Assess source/receptor relationships
• Serve as a regional backdrop for
special studies and understanding non
urban background
• Used for regional modeling validation
studies
OBJECTIVES
• Estimate average bias in gravimetric PM2.5 measurement
• Estimate average bias in reconstructed PM2.5 from measured aerosol species
• Estimate average bias in reconstructed extinction using standard IMPROVE algorithms
PM2.5 Federal Reference
Methods (FRMs)
PM2.5 Federal Reference
Methods (FRMs)
Andersen RAASThermo Fisher Scientific, formerly Andersen Instruments, Smyrna, GA
URG MASSURG Corp., Raleigh, NC
Partisol SamplerThermo Fisher Scientific, formerly Rupprecht & Patashnick, Albany, NY
BGI PQ-200BGI, Inc., Waltham, MA
Speciation Monitors (EPA Speciation Network)Speciation Monitors (EPA Speciation Network)
Mass Aerosol Sampling System (MASS)URG Corporation, Raleigh, NC
Reference Ambient Air Sampler (RAAS)Andersen Instruments, Smyrna, GA
Spiral Aerosol Speciation Sampler (SASS)Met One Instruments, Grants Pass, OR
Interagency Monitoring of Protected Visual Environments (IMPROVE) SamplerAir Resource Specialists, Ft. Collins, CO
Other Speciation MonitorsOther Speciation Monitors
Dual Channel Sequential Filter Sampler
and Sequential Gas SamplerDesert Research Institute, Reno, NV
Dichotomous Virtual ImpactorAndersen Instruments, Smyrna, GA
Paired MinivolsAirmetrics, Inc., Springfield, OR
Partisol 2300 Speciation SamplerRupprecht & Patashnick, Albany, NY
Dichotomous Partisol-Plus SamplerRupprecht and Patashnick, Albany, NY
URG 3000NSpeciation Sampler URG Corporation, Raleigh, NC
Sampler Design Characteristics
47mmWhatma47mmWhatma47mmWhatma47mmWhatma47mmWhatma25mmPallQuartz Filter Type
QFQFQFQFQFQ For
QBQQuartz Filter Pack
Configuration
3rd day/6th day3rd day/6th day3rd day3rd day3rd day3rd daySampling Frequency
23.6cm/sec14.2cm/sec23.7cm/sec9.5cm/sec10.3cm/sec107.2cm/s
ecFilter Face Velocity
16.7l/min10.0l/min16.7l/min6.7l/min7.3l/min22.7l/minFlow Rate
242544Number of Channels
2214617918181Number of Sites (2006)
R&P2025
sequential FRM
R&P2300URG MASSMet One SASSAndersenIMPROVESampler type
CSNCSNCSNCSNCSNIMPROVENetwork
Speciation
SamplerVariable
Sampler Intercomparison and
Artifact Correction
• 1) Comparison of carbon across samplers
– Warren H. White, 16 April 2008 EPA
workshop
• 2) Converting the CSN carbon concentrations to match IMPROVE on the average
– Accounting for positive additive and
multiplicative negative artifacts
– Accounting for different thermal optical
methods.
11
Comparison of IMPROVE and CSN Carbon
at Collocated Sites
Anderson Met One R&P URG
urban collocations of CSN and IMPROVE carbon measurements
12
• The EC difference between CSN and IMPROVE shows little dependence on the
CSN sampler, suggesting that it is mainly analytical.
•IMPROVE:TOR (DRI) – CSN: TOT(NIOSH)
13
0
5
10
15
20
0 5 10 15 20
CSN TC, ug/m3
IMP
RO
VE
TC
+, ug/m
3MetOne 6.7 lpm
Anderson 7.3 lpm
R&P 16.7 lpm
URG 16.7 lpm
2005
For TC, unlike EC,
different CSN
samplers show
different biases
relative to
IMPROVE.
Note that the CSN offset is not determined simply by flow rate.
14
0
5
10
15
20
0 5 10 15 20
MetOne TC, ug/m3
IMP
RO
VE
TC
+, ug/m
3
Dec, Jan, Feb
Mar, Apr, May
Jun, Jul, Aug
Sep, Oct, Nov
2005
The CSN offset
shows no obvious
seasonality. In that
respect it behaves
more like IMPROVE
field blanks than
IMPROVE backup
filters.
15
0
5
10
15
20
0 5 10 15 20
MetOne TC, ug/m3
IMP
RO
VE
TC
+, ug/m
3
Birmingham
Detroit
Fresno
Phoenix
Pittsburgh
Rubidoux
2005
Relating IMPROVE and CSN TCMaking CSN look like IMPROVE
• Recall - Measured TC has a positive OC artifact.
- IMPROVE corrects for the artifact but CSN does not
- IMPROVE TC has a negative multiplicative artifact due loss of OCfrom high face velocities (FV)
- IMPROVE FV = 107.2 cm/s
- CSM MetOne FV = 9.5 cm/s
- Assume CSN negative artifact is 0
• Then[TC]IMP = [TC] – BIMP[OC] B - multiplicative artifact
[TC]CSN = [TC] + ACSN/VMetOne A/V – additive artifact
• Combine[TC]CSN = [TC]IMP + BIMP[OC] + ACSN/VMetOne
The multiplicative artifact (1+bOC) and the monthly positive additive organic artifact (a) used to relate CSN and IMPROVE carbon
concentrations. The units for the positive artifacts are µg/m3 and 1+bOC
is unitless.
1.1aDec
1.0aNov
1.2aOct
1.5aSep
1.9aAug
1.8aJul
1.7aJun
1.6aMay
1.4aApr
1.2aMar
1.3aFeb
1.1aJan
1.21+bOC
MetOne
Correction Factors
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
1+bO
C
Jan
Feb Mar
Apr
ilM
ayJu
ne
July
Aug Sep Oct
Nov Dec
Fac
tor
OFFSET
Comparison of CSN and adjusted
CSN to IMPROVE Carbon
Governing equations[ ]
))))lablablablab(RH(RH(RH(RHssssssss''''SSfSSfSSfSSfSoilSoilSoilSoil LACLACLACLACstuff)stuff)stuff)stuff) ofofofof (lots(lots(lots(lotsococococOCROCROCROCR))))lablablablab(RH(RH(RH(RHffff 3333NONONONO4444NHNHNHNH4444xSOxSOxSOxSOPMPMPMPM ''''inorginorginorginorg2.52.52.52.5
+
++++=
• x=(NH4)2SO4/H2SO4<=1.35 – lowest in summer – acidic aerosol
• highest in summer (D/Do)3≈1.3
• FM biased low because of volatilization (nitrate, SVOC, etc?)
• Roc(lots of stuff) probably highest in summer months
• f‘ss(RHlab) ≈ 1.3
• LAC may have a multiplier
• Soil may be have some seasonal and spatial dependence
3333))))lablablablab(RH(RH(RH(RH
ooooDDDDDDDD
3333
speciesspeciesspeciesspeciesρρρρspeciesspeciesspeciesspeciesmix,mix,mix,mix,ρρρρ
))))lablablablab(RH(RH(RH(RH''''ffff
=
Bias Between Estimated Fine Mass
and Gravimetric Fine Mass and
Bias as function of massPM2.5 = 1.375*SO4 +1.29*NO3+1.8*OC+Other
Temporal plot of PM2.5-PM2.5avg and the percent difference between reconstructed
and gravimetric mass (Brigantine WR) %DM=[(PM2.5-RPM2.5)/PM2.5]*100 = b1+b2(cos(f(T))
Average percent seasonal variability between reconstructed and gravimetric
mass for the IMPROVE monitoring network
%DM=[(PM2.5-RPM2.5)/PM2.5]*100 = b1+b2(cos(f(T))
Average percent bias between reconstructed and
gravimetric mass for the IMPROVE monitoring
network. The red or green color indicates that
reconstructed mass is an over or underestimate of
gravimetric mass respectively.
Summary table of the percent seasonal variability and average bias of
reconstructed versus gravimetric mass
16822.7-17.77.003.4AVG BIAS (CSN)
1589.4-17.94.44-3.9AVG BIAS (IMPROVE)
16819.00.04.517.6% Seasonal
Variability (CSN)
15826.70.06.1414.9% Seasonal
Variability (IMPROVE)
NMaxMinStd DevMeanVariable
AssumptionsAssumptions
• Do not account for volatilization of SVOC’s
• SVOC loss on Teflon and quartz substrates are
the same
• Gravimetric mass of soil dust, seasalt, and non
volatilized POM are measured without bias
• Nitrate and sulfates are measured without loss
on nylon substrate and nitrate and sulfates are
fully ammoniated
IMPROVE
0
5
10
15
20
All Winter Spring Summer Fall
Co
nc
en
tra
tio
n (
ug
/m3
)
STN Suburban
0
5
10
15
20
All Winter Spring Summer Fall
Co
nc
en
tra
tio
n (
ug
/m3
)
STN Urban
0
5
10
15
20
All Winter Spring Summer Fall
Co
nc
en
tra
tio
n (
ug
/m3
)
LAC
POM
SEAS
SOIL
NO3
SO4
Stacked bar charts showing average concentrations of each species for all and seasonal data for IMPROVE, CSN suburban, and CSN urban.
Center City
Inorganic water retention, nitrate loss
and Roc factor
Water Fraction for Sulfate
1.00
1.05
1.10
1.15
1.20
1.25
1.30
Average Winter Spring Summer Fall
Fra
ction
Nitrate Loss (corrected for water)
0.00
0.10
0.20
0.30
0.40
0.50
0.60
Average Winter Spring Summer Fall
Fra
ction N
itra
te L
oss
Roc Factor
1.00
1.10
1.20
1.30
1.40
1.50
1.60
1.70
1.80
1.90
Average Winter Spring Summer Fall
Ro
c F
acto
r
PM2.5 = a1*1.375*SO4 +a2*1.29*NO3+a3*OC+a4*Other
Center City
Suburban
IMPROVE
Comparison of regression and ratio
method for estimating Roc
Comparison of Regression and Ratio Roc Derivation
0.00
0.50
1.00
1.50
2.00
2.50
3.00
Average W inter Spring Summer Fall
Ro
c
Center City (Reg)
Suburban (Reg)
IMPROVE (Reg)
Center City (Ratio)
Suburban (Ratio)
IMPROVE (Ratio)
• Other= (NH4)2SO4+NH4NO3+Soil+LAC+SS
• POM = FM-Other
• Roc=(FM-Other)/OC
SUM of Bias IMPROVE
-0.40
-0.20
0.00
0.20
0.40
0.60
Average Winter Spring Summer FallConcen
tration
(ug/m
3)
Bias (Center City)
-2.00
-1.50
-1.00
-0.50
0.00
0.50
1.00
1.50
2.00
Average Winter Spring Summer Fall
Co
nc
en
tra
tio
n (
ug
/m3
)
Bias (Suburban)
-2.00
-1.50
-1.00
-0.50
0.00
0.50
1.00
1.50
2.00
Average Winter Spring Summer FallCo
nc
en
tra
tio
n (
ug
/m3
)PM2.5-RPM2.5= ))))RFMRFMRFMRFM(FM(FM(FM(FM iiiiiiii iiii −∑
= (PM2.5SO4-1.375*SO4)+( PM2.5NO3-1.29*NO3)+
(PM2.5POM-1.8*OC)+(PM2.5other-Other)
FMNO3-1.29*NO3
FMPOM-1.8*OC
FMSO4-1.375*SO4
FMother-Other
SUM
Assumptions for estimating gravimetric
and reconstructed mass bias sans
accounting for SVOC loses
Assumptions for estimating gravimetric
and reconstructed mass bias sans
accounting for SVOC loses• Weighing of Teflon filter includes retained water on sulfate and nitrate
aerosols
• Nitrate and sulfates are measured without loss on nylon substrate
• Organic volatilization from Teflon and quartz substrates are the same
• Gravimetric mass of total carbon, soil dust, and sea salt determined
without bias
Gravimetric:
PM2.5 Bias = (a1 -1)*1.375 *SO4
+(a2-1)1.29*NO3Reconstructed:
RPM2.5 Bias=(1.8-a3)*OC+(1-a4)*Other
Average bias in gravimetric and reconstructed
PM2.5 mass concentration for the IMPROVE
and CSN datasets
FM Bias on Teflon filter
-0.20
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
Winter Spring Summer Fall AVG
Concentration (ug/m
3)
Reconstructed Mass Bias
-0.50
0.00
0.50
1.00
1.50
2.00
Winter Spring Summer Fall AverageConcentration (ug/m
3)
IMPROVE
Suburban
City Center
Seasonal and spatial variability in fine gravimetric mass bias for the CSN monitoring network
PM2.5measured-PM2.5ambient
Seasonal and spatial variability in fine gravimetric mass bias for the IMPROVE monitoring network
PM2.5measured-PM2.5ambient
Seasonal and spatial variability in reconstructed mass bias for the CSN monitoring network.
PM2.5measured-PM2.5reconstructed
Seasonal and spatial variability in reconstructed mass bias for the IMPROVE monitoring network
PM2.5measured-PM2.5reconstructed
SUMMARY
• Approximately 20% of OC is volatilized in the IMPROVE sampling system
• The Roc factor (POM/OC) has a seasonal dependence that varies from about 1.4 in the winter to 1.6-1.8 in the summer
• Urban/suburban Roc factors may be marginally higher than rural factors
• Nitrate volatilization from the Teflon substrates vary from about 10% in the winter to 35-40% in the summer
• There doesn’t appear to be a systematic difference in nitrate volatilization between CSN and IMPROVE monitoring sites
• About 20% of inorganics species mass is retained water
SUMMARY (Cont)
• Bias between PM2.5 gravimetric and reconstructed mass is lowest (negative) in winter and highest (positive) in summer
• This bias is primarily driven by assuming a constant Roc factor and retained water by inorganic species
• Gravimetric PM2.5 in CSN network is biased high by one to two ug/m3 in most the east and during the summer biased low by about two ug/m3 in southern California
• IMPROVE reconstructed mass is biased high during all seasons but highest in winter. During summer it is biased low in the desert southwest
END
0
5
10
15
20
25
30
35
0 5 10 15 20 25 30 35
IMPROVE TC, ug/m3
CS
N-S
TN
TC
, ug/m
3
MetOne
Anderson
R&P
URG0
5
10
15
20
0 5 10 15 20
CSN TC, ug/m3
IMP
RO
VE
TC
+, ug/m
3
MetOne 6.7 lpm
Anderson 7.3 lpm
R&P 16.7 lpm
URG 16.7 lpm
2005
42
0.1
1
10
0.1 1 10
routine MetOne EC, ug/m3
collo
cate
d M
etO
ne E
C, ug/m
3 2003-4
2005
2006
Considerably
more scatter is
observed in
routine CSN
measurements by
collocated
MetOne
samplers,
particularly in the
earlier years.
Data are from Bakersfield,* Boston,* Cleveland,* New Brunswick* and
Rubidoux. * Not collocated with IMPROVE
43
EXPECTATION:
[TC]CSN = [EC]IMP + (1+BIMP*)[OC]IMP + ACSN/VMetOne
OLS REGRESSION:
[TC]CSN = (1+bEC)[EC]IMP + (1+bOC)[OC]IMP + a1 +…+ a12 + e
2005-6 observations at 7 MetOne sites (excluding Phoenix):
bEC = 0.008 (+/-0.05)
no sampling artifact for IMPROVE EC
bOC = 0.22 (+/-0.03)
~ 20% sampling loss for IMPROVE OC
rms(e) = 0.9 ug/m3 (r2 = 0.94, n = 728)
amm � next slide
44
EC – the short story:
-
-
-
- EC has little to no positive artifact for both
IMPROVE and CSN
-Multiplicative bias between CSN and IMPROVE
that is sampler independent
0,IMPε ≅ _IMP artifact adjε =
,newIMP CSNα≅ 1α >
,CSN CSNφ ϕ≅ φ ϕ≠ samplers
45
TC – the short story:
_IMP artifact adjε =
( ) ,newIMP CSNλ θ≅ − 1,λ <
,CSN CSNφ ϕ≠ φ ϕ≠ samplers
0θ >
Relating IMPROVE and CSN ECMaking CSN look like IMPROVE
• Recall - EC has little to no positive artifact for both IMPROVE
and CSN
- CSN and IMPROVE have a multiplicative bias that is sampler independent
• ECIMP = α * ECCSN
• α ~ 1.3
Non-urban and urban PM2.5
networks
Non-urban and urban PM2.5
networks
Interagency Monitoring of
PROtected Visual Environments
(IMPROVE) Network
Interagency Monitoring of
PROtected Visual Environments
(IMPROVE) Network
Chemical Speciation Network (CSN)
Chemical Speciation Network (CSN)
Virgin IslandsVirgin Islands
Ammonium Sulfate
Ammonium Nitrate
Organic Carbon
Fine Soil