U.S. EPA Office of Research & Development October 16, 2012
Prakash Bhave, Adam Reff, Alexis Zubrow, Venkatesh Rao
U.S. Environmental Protection Agency
CMAS ConferenceChapel Hill, NC
October 15 – 17, 2012
Evaluation of Urban PM2.5 Emission Inventories across the U.S.
U.S. EPA Office of Research & Development, Atmospheric Modeling & Analysis Division
2
Conclusions: CMAS 2010
• In the past decade, which modeling system refinements contributed most to PM2.5 performance improvement?→Meteorology inputs (2)→Emissions & deposition (4)→Atmospheric chemistry (2)
IMPROVE Observations (1996)
PM2.5 Components (μg m-3)
CM
AQ
v4.
1
NO3SO4
OC
IMPROVE Observations (1996)
PM2.5 Components (μg m-3)
CM
AQ
v4.
1
IMPROVE Observations (1996)
PM2.5 Components (μg m-3)
CM
AQ
v4.
1
NO3SO4
OC
PM2.5 Components (μg m-3)
IMPROVE Observations (2002 – 2006)
CM
AQ
v4.
7
NO3
SO4
OC
U.S. EPA Office of Research & Development, Atmospheric Modeling & Analysis Division
3
Background & Motivation• U.S. has most detailed national inventory for PM2.5
– Spatial resolution
– Source resolution
– Chemical resolution
• Inventory accuracy
very difficult to check– CTM is often used
– Can we find & fix gross
inventory errors without
running CMAQ? Reference: Reff et al. (ES&T, 2009)
U.S. EPA Office of Research & Development, Atmospheric Modeling & Analysis Division
4
• Cass & McRae (ES&T, 1983) demonstrated a simple approach for PM2.5 inventory evaluation• Compare emission rates
directly against ambient concentrations• Only works because,
*most trace elements are conserved*
• Results• Ti, Ni emissions too high• Zn too low• Ambient Cu data error
•We applied same method to 2001 NEI in 21 cities…
U.S. EPA Office of Research & Development, Atmospheric Modeling & Analysis Division
Secondary Species
Below MDL
Reff et al. (Intl Aerosol Conf. 2006)
Al Ca Fe KSi
Prior Evaluation: 2001 NEI
U.S. EPA Office of Research & Development, Atmospheric Modeling & Analysis Division
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Prior Evaluation: 2001 NEIEmissions Allotment of Si
Em
iss
ion
s (t
on
/yea
r)
Dallas Minneapolis St. Louis
Emissions Allotment of Si
Em
iss
ion
s (t
on
/yea
r)
Dallas Minneapolis St. Louis
Factor Dilutionc Atmospheri
ionConcentrat Ambient
• In many cities, we found positive biases in the emissions of– Agricultural soil– Unpaved road dust
Methodological Shortcomings• Limited number of sites (n = 21)• 36 km grid resolution• “old” version of NEI• Only able to identify gross
overestimates• Unable to quantify the emission
errors
U.S. EPA Office of Research & Development, Atmospheric Modeling & Analysis Division
Methodology• 2005ak NEI• Mobile emissions from 2005cr, output by MOVES• Spatial allocation: 12km ConUS grid• Temporal allocation: monthly
• 85 source categories with unique PM2.5 speciation profiles
• Aggregate to 159 Core-Based Statistical Areas (CBSA)
Result> 7×104 pairs of diluted emissions & ambient concentrations
• Multiply emissions by month-
& site-specific dilution ratio
U.S. EPA Office of Research & Development, Atmospheric Modeling & Analysis Division
Methodology• Apply principles of chemical mass balance (CMB)
correction factor
• Data in each city/month are fit separately
• Key result: source-specific F value for each site & month
U.S. EPA Office of Research & Development, Atmospheric Modeling & Analysis Division
MethodologyForce Fij to be positive
Account for measurement
error
Minimize this
Penalize fit for over-correcting the
emissions
U.S. EPA Office of Research & Development, Atmospheric Modeling & Analysis Division
Preliminary ResultsF values for Agricultural Burning
100
1
0.01J F M A M J J A S O N D
• PM2.5 from crop burning is biased high by ~10x
• Pouliot, McCarty, et al. have diagnosed the reason for these overestimates
• Revisions will be incorporated into 2008 NEI
U.S. EPA Office of Research & Development, Atmospheric Modeling & Analysis Division
Preliminary ResultsF values for Unpaved Road Dust
100
1
0.01J F M A M J J A S O N D
• PM2.5 from unpaved roads is biased high by ~30x
• Is this entirely due to emissions error?• see poster by Appel et al.
U.S. EPA Office of Research & Development, Atmospheric Modeling & Analysis Division
Preliminary ResultsF values for Unpaved Road Dust
100
1
0.01J F M A M J J A S O N D
Median of Monthly F values
U.S. EPA Office of Research & Development, Atmospheric Modeling & Analysis Division
Summary•Methodology to quantify source-specific biases in
PM2.5 inventory has been developed
•Preliminary results look quite promising!
• In process of assessing our results for other source
categories
