Transcript Relationship Between NOx Emissions and NO2 Columns

Improving Emission Inventories Using Space-Based
Measurements of Ultraviolet and Visible Radiation
Randall Martin
With contributions from:
Aaron Van Donkelaar, Rongming Hu (Dalhousie University)
Chris Sioris, Kelly Chance (Smithsonian Astrophysical Observatory)
Lyatt Jaeglé, Linda Steinberger (Univerisity of Washington)
Yongtao Hu, Armistead Russell (Georgia Tech)
Tom Ryerson (NOAA)
Ron Cohen (Berkeley)
Bill Brune (Penn State)
Major Challenges in Tropospheric Chemistry
More Accurate Emission Inventories
Understand Aerosol Sources and Properties
Global Surface NOx Emissions Uncertain to Factor of 2
Implications for Tropospheric Ozone, Aerosols, Indirect Effect, Nutrient Delivery
Here in Tg N yr-1 (based on)
Fossil Fuel 24 (GEIA)
Biomass Burning 6
(Duncan et al., 2003)
Soils 5
(Yienger and Levy, 1995)
NOx Emissions (Tg N yr-1)
Fossil Fuel (20-33)
Biomass Burning (3-13)
Soils (4-21)
Relative Uncertainty
Top-Down Information from the GOME and
SCIAMACHY Satellite Instruments
•Nadir-viewing solar backscatter instruments
including ultraviolet and visible wavelengths
• Low-elevation polar sun-synchronous orbit,
late morning observation time
•GOME 1995-2002
•Spatial resolution 320x40 km2
•Global coverage in 3 days
•SCIAMACHY 2002-present
Spatial resolution 60x30 km2
Global coverage in 6 days
Spectral Fit of NO2
Distinct NO2 Spectrum
Solar Io
Ozone
Backscattered
intensity IB
NO2
Scattering by
Earth surface
and by atmosphere
Albedo A
O2-O2
Nonlinear least-squares fitting
s

I B ( )  A( ) I 0 ( )e
 Ring
Also Weak H2O line

Based on Martin et al., 2002
Total NO2 Slant Columns Observed from SCIAMACHY
Dominant stratospheric background (where NO2 is produced from N2O oxidation)
Also see tropospheric hot spots (fossil fuel and biomass burning)
May-October 2004
Perform a Radiative Transfer Calculation to Account for
Viewing Geometry and Scattering
Cloud Radiance Fraction
IB,c / (IB,o + IB,c)
IB,o
IB,c
Io
•GOMECAT (Kurosu) &
FRESCO Clouds Fields
[Koelemeijer et al., 2002]
q
•Surface Reflectivity
[Koelemeijer et al., 2003]
Ro
•LIDORT Radiative Transfer
Model [Spurr et al., 2002]
•GEOS-CHEM NO2 &
aerosol profiles
Rc
Pc
d
Rs
Based on Martin et al., 2002, 2003
Cloud-filtered Tropospheric NO2 Columns Determined from
SCIAMACHY (Data  NASA)
May-Oct 2004
detection
limit
ICARTT: COORDINATED ATMOSPHERIC CHEMISTRY CAMPAIGN OVER
EASTERN NORTH AMERICA AND NORTH ATLANTIC IN SUMMER 2004
ERS
ERS-2
Envisat
Terra
Aqua
GOME
SCIAMACHY
AIRS, MODIS
MISR, MODIS, MOPITT
NOAA-P3
Canada Convair
DLR Falcon
NASA DC-8
NASA
Proteus
UK BAE-143
International, multi-agency collaboration targeted at regional air quality,
pollution outflow, transatlantic transport, aerosol radiative forcing
Promising Agreement Between Coincident Cloud-Free
SCIAMACHY and In-Situ Measurements
1:1
line
r = 0.74
slope = 0.86
Cohen NO2
•Coincident
measurements
•Cloud-radiance
fraction < 0.4
•In-situ measurements
below 1 km
Ryerson NO2
Assume constant
mixing ratio below
lowest measurement
Chris Sioris
In situ errorbars show 17th & 83rd percentiles
USE RETRIEVED NO2 COLUMNS TO MAP NOx EMISSIONS
GOME
SCIAMACHY
Tropospheric NO2
column ~ ENOx
NO/
NO2
  NO
NO2
BOUNDARY
LAYER
W ALTITUDE
lifetime ~hours
HNO3
Emission
NITROGEN OXIDES (NOx)
Conduct a Chemical Inversion & Combine Top-Down
and Bottom-up Inventories with Error Weighting
A Priori NOx Emissions
SCIAMACHY NO2 Columns
NO/
NO2

W ALTITUDE
1011 molec N cm-2 s-1
1015 molec cm-2
GEOS-CHEM
model
Top-Down Emissions
Error
weighting
A posteriori emissions
Interpret Satellite Observations Using
GEOS-CHEM Chemical Transport Model
•
•
•
•
•
•
•
•
Assimilated Meteorology (GEOS)
2ox2.5o horizontal resolution, 30 vertical layers
O3-NOx-VOC chemistry
SO42--NO3--NH4+-H2O, dust, sea-salt, organic & elemental carbon aerosols
Interactive aerosol-chemistry
Anthropogenic and natural emissions
Cross-tropopause transport
Deposition
Calculated Mean Surface Ozone for August 1997
Global Optimal Emission Inventory Reveals
Major Discrepancy in NOx Emissions from Megacities
48 Tg N yr-1
May-Oct 2004
48 – 39 Tg N yr-1
GEIA
r2=0.82 vs a priori
Large Change in NOx Emissions Near New York City
A priori
r2 = 0.92
7.2 Tg N
1011 atoms N cm-2 s-1
A posteriori
A posteriori – A priori
8.3 Tg N
1011 atoms N cm-2 s-1
1.1 Tg N
1011 atoms N cm-2 s-1
Evaluate Each Inventory By Conducting GEOS-CHEM Simulation &
Sampling Model Along Aircraft Flight Tracks
Simulation with A Posteriori – Simulation with A Priori
NOx (ppbv)
HNO3 (ppbv)
In Situ Airborne Measurements Support Top-Down
Inventory
New England
New England + Gulf
Remote
GEOS-CHEM
(A posteriori)
In Situ
GEOS-CHEM
(A priori)
P-3 Measurements from Tom Ryerson (NOAA)
EMIS: Emissions Mapping Integration Science
Optimize NOx Emissions
SCIAMACHY NO2 Columns
NOx Emissions (SMOKE/G.Tech)
Aug 2004
May-Oct 2004
1011 molec N cm-2 s-1
1015 molecules cm-2
CMAQ
Top-Down Emissions
Error
weighting
A posteriori emissions
Algorithm for partitioning top-down NOx inventory (2000)
1
2
GOME NOx emissions
1. Spatial location of FFdominated regions in a priori
(>90%)
2. Spatiotemporal
distribution of fires used to
separate BB/soil
Fuel Combustion
Biomass Burning
VIRS/ATSR fire counts
Soils
No fires + background
Algorithm tested using synthetic retrieval
Jaeglé et al., 2005
Biomass Burning (2000)
A priori
A posteriori
1010atoms N cm-2 s-1
r2 = 0.72
(±200%)
(±80%)
N. Eq. Africa:
50% increase
SE Asia/India
N. Eq. Africa
SE Asia/India:
46% decrease
S. Eq. Africa
Line: A priori
(BB)
A posteriori total
Bars: A posteriori
(BB)
Good agreement with BB seasonality from Duncan et al. [2003]
Jaeglé et al., 2005
Speciated Inventory for Soil emissions
A posteriori 70% larger than a priori!
A priori
(±200%)
A posteriori
r2 = 0.62
(±90%)
Largest soil emissions: seasonally dry tropical + fertilized cropland ecosystems
North Eq. Africa
Soils
East Asia
Soils
Onset of rainy season: Pulsing of soil NOx!
Jaeglé et al., 2005
SCIAMACHY Shows Elevated NOx Export from North America
SCIAMACHY NO2 (1015 molec cm-2)
May-Oct 2004
GEOS-CHEM NO2 (1015 molec cm-2)
May-Oct 2004
Explained by Model Bias in Upper Tropospheric NOx
West of -60 degrees lon, “land”
East of -60 degrees lon, “ocean”
GEOS-CHEM NO2
Cohen NO2
GEOS-CHEM
low by factor of
2 in column
GEOS-CHEM low
by 7.5% in column
GEOS-CHEM NO
Brune NO
Errorbars Show 17th and 83rd percentiles
EMISSION CONTROL STRATEGY FOR OZONE POLLUTION:
ARE NOx OR VOCs THE LIMITING PRECURSORS?
Use GOME observations of
HCHO/NO2 ratio to determine
ozone production regime
[Sillman, 1995]
HCHO/NO2 < 1 (blue)
a VOC-limited
HCHO/NO2 > 1 (green-red)
a NOx-limited
Martin et al. [2004]
Aerosol Single Scattering Albedo Major Source of
Uncertainty in Global Radiative Forcing Estimates
IPCC [2001]
Maximum Sensitivity to Aerosol Optical Thickness Over Dark Surfaces
More Sensitive to Single Scattering Albedo Over Bright Surfaces
Saharan Dust Plume
Staten Island Refinery Fire
King et al.,
BAMS, 1999
TOMS Aerosol Index Measures Absorbing Aerosols In Ultraviolet
Where Rayleigh Scattering Acts as Bright Surface
AI  100{log10 [(I331 / I360 )meas ]  log10 [(I331 / I360 ) Rayleigh]}
July 2000
Reflectivity
0.6
TOA spectral albedo
measured by GOME
0.4
0.2
0.0
300
400
500
600
Wavelength [nm]
700
800
MODIS Aerosol Optical Depth Includes Both
Scattering and Absorbing Aerosols
1.5
MODIS
1.1
0.8
July 2000
0.4
0
3.0
2.2
1.6
0.8
July 2000
0
TOMS
Retrieval of Aerosol Single Scattering Albedo
Determined with radiative transfer calculation as SSA that reproduces
TOMS Aerosol Index when constrained by MODIS aerosol optical depth
July 2000
Correlation with AERONET = 0.8
Rongming Hu
Modeled Organic Carbon Too Low in Southeast in July
Ground-Based
Measurements from
IMPROVE (ug m-3)
GEOS-CHEM model
calculation (ug m-3)
Aaron Van Donkelaar
Summer Organic Carbon Bias
GEOS-CHEM already accounts for primary and secondary
sources of organic aerosol
IMPROVE minus GEOS-CHEM OC [ug/m3], 2001
Aaron Van Donkelaar
Distribution of Isoprene Emissions Similar to OC Bias
Mounting Field and Laboratory Evidence of OC Yield from Isoprene
Oxidation Products
2001 Isoprene Emission (1012 moles C cm-2 s-1)
Aaron Van Donkelaar
Organic Carbon from Isoprene Oxidation Products
Largely Corrects Bias
IMPROVE minus GEOS-CHEM OC [ug/m3], 2001
Aaron Van Donkelaar
Conclusions
•Growing confidence in top-down constraint on NOx
emissions
•Gross-underestimate in NOx emissions from megacities
•Soil NOx emissions underestimated, especially from
Northern Equatorial Africa
•North American lightning NOx emissions underestimated
•Promise for global retrieval of aerosol single scattering
albedo
•Low yield of organic carbon from isoprene oxidation
products reduces model bias
Acknowledgements
Aaron Van Donkelaar, Rongming Hu (Dalhousie U.)
Chris Sioris, Kelly Chance (Smithsonian)
Lyatt Jaeglé, Linda Steinberger (U. of Washington)
Yongtao Hu, Armistead Russell (Georgia Tech)
Arlene Fiore (GFDL)
Tom Ryerson (NOAA)
Ron Cohen (Berkeley)
Bill Brune (Penn State)
Funding:
• National Aeronautics and Space Administration (NASA)
• Canadian Foundation for Innovation (CFI)
• Canadian Foundation for Climate and Atmospheric Sciences (CFCAS)
• Natural Sciences and Engineering Research Council of Canada (NSERC)
• Nova Scotia Research and Innovation Trust (NSRIT)