Carbon artifact adjustments for the IMPROVE and CSN speciated particulate networks Mark Green,...
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Carbon artifact adjustments for the IMPROVE and CSN speciated particulate networks Mark Green, Judith Chow, John Watson Desert Research Institute Ann Dillner
Carbon artifact adjustments for the IMPROVE and CSN speciated
particulate networks Mark Green, Judith Chow, John Watson Desert
Research Institute Ann Dillner University of California at Davis
Neil Frank and Joann Rice USEPA Office of Air Quality Planning and
Standards National Air Quality Conference, San Diego, CA March
2011
Slide 2
Introduction Organic aerosol is a major contributor to PM 2.5
concentration, typically accounting for 25-50% of reconstructed
fine mass Organic aerosol % of fine mass (2000-2004)
Statement of the problem Analysis of filter samples for carbon
analysis done by thermal optical reflectance (TOR) for both IMPROVE
and CSN networks TOR heats filter in stages without oxygen and
organic carbon volatilized and converted to CO2 Finally, 2% oxygen
is added to combust elemental carbon Because high temperatures are
needed for TOR analysis, Teflon filter cannot be used Quartz fiber
filters are used to collect the aerosol for analysis Quartz fiber
filters are known to react with organic gases causing sampling
artifacts Positive artifact from adsorption of organic gases
Negative artifact from volatilization of particles off filter (e.g.
as temperature increases during the day or after sample is
collected).
Slide 6
Organic Sampling Artifacts Positive sampling artifact:
gas-phase adsorption onto quartz Negative sampling artifact: SVOC
is volatilized after captured by filters Quartz- or other filter
material Backup fiber Particle (P) Particle and gas are in a
dynamic equilibrium! Gas Molecule CIG: Charcoal-impregnated
glass-fiber filter
Slide 7
Treatment of artifact Typically, positive artifact thought to
be greater than negative artifact SEARCH network uses denuders to
remove organic gases upstream of filter- use a backup filter to
capture gases volatilizing off front filter- negative artifact
However denuder approach add complexity and expense and also alters
gas-particle equilibrium IMPROVE network has used backup filters at
a few sites to characterize positive artifact IMPROVE has
subtracted monthly median backup filter OC concentrations at 6
sites to give a monthly correction to apply to all sites CSN
network is currently collecting back filters at all sites without
denuders but has not determined how to use them for artifact
correction Desire a method consistent between networks and that can
give continuity in time over >20 years of IMPROVE data
Slide 8
Average front filter (QF), backup filter (QBQ), and field blank
OC concentrations (Top 1% QF excluded) IMPROVE QBQ= 21% of QF,
bQF=11.8% of QF CSN QBQ= 15.8% of QF, bQF=6.7% of QF
Slide 9
Some possible methods for artifact adjustment 1)Ignore
potential positive and negative artifacts 2)Subtract representative
OC concentration on field blank 3)Subtract representative OC
concentration on backup filter 4)Use denuder to prevent positive
artifact and ignore any negative artifact 5)Use denuder and backup
filter to characterize negative artifact and field blanks for
positive artifact 6)Same as above, except without denuder 7)Add
quartz filter behind Teflon and subtract (recommended by McDow
& Huntzicker (1990) 1 Only 1-3, 6 can be done with existing
sampling set-ups/existing data 1 Atmos. Environ.,
24A,2563-2571
Slide 10
Data analysis methods Use only sample site days with front
filter (QF), blank filter (bQF), and backup (QBQ) available Look at
relationships between QF and bQF and QBQ and if they vary by
geographic location or season to see if regional or seasonal
artifact adjustments are called for Consider IMPROVE and CSN data
separately and then together (may expect differences because CSN
mainly urban, IMPROVE mainly rural Used 1839 CSN samples 2008-2009
Used 1387 IMPROVE samples Sep 2008- Feb 2010 Removed QBQ
OC>1.2*QF OC
Slide 11
CSN Average bQF and QBQ OC by site show little geographic
pattern (sites ordered from EPA Region 1 (left) to EPA Region 10
(right)
Slide 12
IMPROVE bQF and especially QBQ show seasonal pattern (higher in
summer) CSN shows subtle seasonal patterns in bQF and QBQ
Slide 13
Backup filter OC (QBQ) proportional to front filter OC (QF).
Logarithmic or power law fits work about equally well. QBQ scales
approximately with square root of QF. IMPROVE better fit than CSN.
Estimating backup filter OC from front filter OC
Slide 14
Combined data set power law fit slightly better than
logarithmic fit. Power law fit equations for CSN, IMPROVE, and
combined similar- suggests little adverse impact from using
combined equation for all data
Slide 15
Averaging the data clarifies the front/back filter OC
relationship
Slide 16
How to proceed? Use of curve fitting to estimate QBQ from QF
gives less error than using median QBQ so no good reason to
continue using median QBQ for IMPROVE adjustment or to apply to CSN
data BUT- What does the QBQ OC really represent? Alternate
explanation back filter collects positive and negative artifact fit
linear curve to QBQ vs QF slope represents negative artifact
proportional to QF concnetration intercept represents positive
artifact QF OC adjusted = QF + slope*QF - intercept Blank filters
represent a positive artifact independent of concentration QF OC
adjusted= QF+slope*QBQ-2*bQF (method gives small negative average
adjustment for IMPROVE, small positive for CSN) This is equivalent
to SEARCH approach, except no denuder is present to remove organic
vapors
Slide 17
Linear model for QBQ based on QF (highest 1% of data excluded
from figure and fit) OCback =.08*OCfront+0.13 Intercept about equal
to field blank- CSN linear model gives intercept of 0.23 compared
to bQF of 0.16 Linear model less satisfactory than power or ln for
CSN
Slide 18
Summary Method of artifact correction can affect OC
concentrations up to 20% or so Dont currently have enough
information to determine most appropriate correction Backup filter
OC concentration best represented by fit proportional to
concentration BUT We dont really know what backup filter represents
Use of field blanks (may adjust seasonally, monthly, etc.)
straightforward and consistent with artifact corrections for non-
reactive compounds Want consistent methodology among CSN and
IMPROVE networks for comparability and ability to calculate
urban/rural differences, etc. Conference call later this month to
try to discuss artifact correction approach for both networks