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My background
1 |
• Reactive Gases Team leader (CSIRO), Cape Grim Reactive Gases Joint Lead Scientist (2013-)
Main roles
• VOC insitu monitoring program at Cape Grim (2014-) • Dual channel GC-FID based on Uni York
• 2 years prelim hydrocarbon data (poster Thur)
• Australia’s first air monitoring study in region of coal seam gas (2015-) • Network 5 ambient air sites – 2 years (presentation Fri)
• Shipboard measurements of atmospheric VOCs (2012- present) • PTR-MS on NZ’s RV Tangaroa, Australia’s RV Investigator
Impact of marine and biomass burning emissions on reactive gas and aerosol composition at Cape Grim
Sarah Lawson, Senior Research Scientist
CSIRO CLIMATE SCIENCE CENTRE
10 November 2016
Unexplained organic trace gases over temperate southern hemisphere oceans….
1. shortlived (global lifetime of 3 and 1.6 hours), photolysis main sink (Fu 2008)
2. Intermediate oxidation products of isoprene, monoterpenes
3. highly water soluble – quickly diffuse into aerosol or cloud water
4. are significant source of secondary organic aerosol -organic acids (oxalic, pyruvic) and oligimers
3 |
glyoxal methylglyoxal
Oxalic acid
pyruvic acid
Evidence that glyoxal and methylglyoxal contribute to marine secondary organic aerosol
• Glyoxal and methylglyoxal found in marine aerosols over the Atlantic (van Pinxteren and Herrmann, 2013) and Pacific Ocean (Bikkina et al., 2014)
• mass in aerosols positively correlates with organic acids (including oxalic acid) and ocean biological activity
4 |
• Oxalic acid -Amsterdam Island (Claeys et al., 2010), Mace Head (Rinaldi et al., 2010), Cape Verde (Muller et al., 2010) and Cape Grim
Mysteries surrounding glyoxal and methylglyoxal in the marine boundary layer
• Recent DOAS and satellite observations suggest glyoxal is widespread in atmosphere over the ocean
• Glyoxal >> precursors??
• models cannot reproduce observed glyoxal
Knowledge gaps:
• no parallel measurement of precursors (isoprene, monoterpenes)
• Dominance of DOAS-based glyoxal studies
• low mixing ratios challenge (particularly in Southern Hemisphere)
• only one previous study reporting methlyglyoxal in the MBL (tropical NH). How widespread, importance to SOA unknown.
5 |
Glyoxal and methylglyoxal sampling locations
33 samples (24 hour) 5 ‘clean marine’ days Winter 2011 Chl a ~0.2 mg m-3
41º S
6 samples (24 hour) 2 ‘clean marine’ days Summer 2012 Chl a ~1 mg m-3
~43º S
Precursor (VOC) measurements via PTR-MS, flask data (INSTAAR, NOAA
HATS)
Cape Grim Baseline station
SOAP voyage
Lawson, S. J., Selleck, P. W., Galbally, I. E., Keywood, M. D., Harvey, M. J., Lerot, C., Helmig, D., and Ristovski, Z.: Seasonal in situ observations of glyoxal and methylglyoxal over the temperate oceans of the Southern Hemisphere, Atmos. Chem. Phys., 15, 223-240, doi:10.5194/acp-15-223-2015, 2015
Glyoxal, methylglyoxal derivatisation method
• Air is drawn through 2,4-DNPH cartridges using CSIRO custom-built ‘Sequencer’
• Glyoxal methyglyoxal trapped on silica adsorbent coated with 2,4-DNPH, and converted to the hydrazone derivatives
• derivatives are analysed by HPLC with diode array detector (EPA Method TO11A)
• Detection limits: 1-2 ppt glyoxal and methyl glyoxal (24 hour sample)
Optimising analytical method
Absorption spectra and retention times used to identify glyoxal and methylglyoxal
Quantifying glyoxal and methylglyoxal using absorption at 435nm increases peak height and reduces co-elutions from monocarbonyls
Glyoxal, methylglyoxal in clean marine air
9 |
Site Season Glyoxal
(ppt)
Methylglyoxal
(ppt)
CO2 (ppm) CN>10nm
(particles cm-3)
Radon
(mBq m-3)
Cape
Grim
n=5
Winter/Spring
(Aug-Sep)
7 ± 2 28 ± 11 388.8 ± 0.1 194 ± 110 43± 14
SOAP
voyage
n=2
Summer
(Feb-Mar)
23 ± 8 10 ± 10 388.5 ± 0.8 328 ± 1591 n/a
Comparison with other marine sites 1
Temperate ocean (ppt)
Tropical ocean (ppt)
Southern Ocean (Cape Grim)
This work
South West
Pacific (Chatham
Rise) This work
South West
Pacific (Chatham
Rise)a
North Pacific
& Atlantic
a
Tropical Pacific
& Atlantic
a
Eastern Tropical Pacific
b
Tropical Pacific
c
Caribbean and
Sargasso Sea
d
Glyoxal
All
data
10 ± 6
30 ± 12
23 ± 10
25 ± 13
24 ± 12 (SH)
26 ± 15 (NH)
43 ± 9 (SH)
32 ± 6 (NH)
63 ± 21
80
Methyl- glyoxal
All data
57 ± 32
19 ± 14
-
-
-
-
-
~10
2 3
4
10 |
a Mahajan et al. 2014 b Coburn et al. 2014 c Sinreich et al. 2010 dZhou and Mopper 1990
Good agreement between DNPH and MAX-DOAS glyoxal observations over Chatham Rise despite low mixing ratios
Precursor precursor mixing ratios
(ppt) glyoxal yield (ppt)
methylglyoxal yield
(ppt)
Chatham
Rise
Cape
Grim
Chatham
Rise
Cape
Grim
Chatham
Rise
Cape
Grim
acetylene 3a 39
a 0.02 0.08 n/a n/a
ethene 51b 31
b 0.22 0.06 n/a n/a
propene 17b 8
b n/a n/a 0.04 0.03
propane 33c 35
c n/a n/a 0.02 0.02
alkanes >C3^ 54
c 52
c n/a n/a 0.02 0.02
isoprene 17 14d 1.03 0.43 2.30 1.97
benzene 10 9a 0.03 0.01 n/a n/a
toluene 9 9* 0.08 0.03 0.03 0.03
xylenes sum 10 9* 0.27 0.10 0.22 0.19
monoterpenes 34 17e 0.89 0.44 0.73 0.48
acetone 125 118d n/a n/a 0.02 0.02
sum yield (ppt) 2.5 1.2 3.4 2.8
% explained 11 17 28 10
1 aCape Grim flasks (NOAA HATS analysis) bKivlighon thesis cCape Grim flasks (INSTAAR analysis) dGalbally et al. 2007 (upper estimate Cape Grim summer) eLawson et al. 2011 ^ sum of C4 and C5 *upper estimate based on benzene
At most 3 ppt glyoxal and methylglyoxal can be explained from oxidation of precursors!
Suggests significant additional source!
Glyoxal comparison with GOME-2 Satellite retrieval (2007-2012)
12 |
• Mixing ratios converted into Vertical Column Densities (VCD) assuming all glyoxal observed is well mixed within boundary layer (850m)
• Satellite sees much higher VCD than surface observations
• Assumption that all observed glyoxal is in boundary layer may be incorrect
• aircraft campaigns - glyoxal between 2-10 km over tropical, temperate oceans (including SH) (Volkamer et al 2016)
• If glyoxal is in free troposphere over temperate ocean, satellite columns would be higher than boundary layer measurements
Additional sources of glyoxal and methyl glyoxal?
13 |
• Oxidation of unknown gas phase precursors
• Flux from organic-rich sea surface microlayer • Photolysis of fatty acids (Rossignol et al 2016, Ciuraru et al 2015, Zhou et al
2014)
• Positive flux from SH tropical oceans, but too low to explain atmospheric concs (Coburn et al 2014)
• Photochemical reactions involving organic aerosols
To summarise
• First insitu glyoxal, methyl glyoxal measurements over SH emperate oceans
• Yield of glyoxal and methyl glyoxal and glyoxal cannot be explained by precursors highlighting significant additional source
• Satellite VCD glyoxal exceed surface obs – may be due to distribution of glyoxal in FT (source unknown)
Robbins Island fire -opportunity for plume characterisation
Plume took 20 minutes to reach Cape Grim Wide variety of measurements (trace gases and aerosols), including VOCs via PTR-MS
Unique set of trace gas emission factors calculated for coastal heathland fires (33 species)
Highest observed methyl halide EF worldwide, attributed to high halogen levels in coastal vegetation
Lawson, S. J., Keywood, M. D., Galbally, I. E., Gras, J. L., Cainey, J. M., Cope, M. E., Krummel, P. B., Fraser, P. J., Steele, L. P., Bentley, S. T., Meyer, C. P., Ristovski, Z., and Goldstein, A. H.: Biomass burning emissions of trace gases and particles in marine air at Cape Grim, Tasmania, Atmos. Chem. Phys., 15, 13393-13411, 2015
Emission factors (g/kg fuel burned) are used by models in simulating air quality and climate impacts
Rainfall drives changes in emissions
VOC/CO ER increase by factor of 3, BC to CO decreased by factor 2 attributed to rainfall – first study to show large response of meteorology to biomass burning emissions
Testing chemical transport model –ozone simulation
17 |
Modelled production or destruction of ozone highly dependant on meteorology and emission factors!
Lawson, S.J., Cope, M., Lee., S., Keywood, M.D., Galbally, I.E and Ristovski. Z (2016): Biomass burning at Cape Grim: exploring photochemistry using multiscale modelling, Atmos Chem. Phys. Discuss., (submitted)
What are relative contributions to ozone production?
Most of the ozone is urban air transported
from Melbourne ~
300km to north
Model predicts plume age = 2 days (urban air)
Biomass burning conclusions
• Chance biomass burning event at Cape Grim lead to • Unique trace gas emission factors derived
• Rainfall lead to major change in emissions -highlights need for emission factors in models to respond dynamically to meteorology
• Biomass burning data set used to test chemical transport models • Highly sensitive to meteorology, biomass emission factors
• Most of ozone observed during fire events was from urban air from Melbourne, from precursors emitted 2 days prior
20 |
Impact of changing meteorology and emission factors
21 |
TAPM carbon monoxide CCAM carbon monoxide
Meteorological models determine the duration and timing of plume strikes and concentrations Emission factors (corresponding to low, medium or high combustion efficiency) drive simulated concentrations
Measurements – P2P campaign Measurement Instrument
Particle size distribution (14 – 700 nm) TSI SMPS
Particle number >10 nm TSI 3010 CN Counter
Particle number > 3 nm TSI 3025a UCN Counter
Black Carbon Aethalometer
Cloud Condensation Nuclei (CCN) DMT CCN counter
VOCs (10 minute) Proton Transfer Reaction –Mass Spectrometer
Ozone TECO ozone analyser
CH4 AGAGE GC FID
CO, H2 AGAGE GC-MRD
CO2 LoFlo NDIR
N2O CHCl3, CH3CCl3, CCl4 AGAGE GC-ECD system
Ethane, methyl halides AGAGE Medusa GCMS
The Centre for Australian Weather and Climate Research
A partnership between CSIRO and the Bureau of Meteorology
Higher CCN/CN during particle growth period
The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology
Higher CCN/CN during particle growth due to changing composition rather than size
Plume dilution leads to particle growth, ozone
A. Fresh plume B. Particle growth
period C. Air from mainland
Australia D. Air from
Melbourne E. Air from Ocean F. Air from Mainland
Australia
Ozone enhancement driven by biomass burning or Melbourne air?
Chemical Transport Modelling methodology
• Meteorological models coupled to chemical transform model – simulates the emission, transport and reaction, deposition of atmospheric trace gases and aerosols
• 400m grid cell, hourly resolution
Fire emissions scaled to wind speed
Modelling domains used (large to fine scale processes)
Model output – black carbon
Model simulates narrow plume which intermittently strikes Cape Grim Close proximity of fire to observation site is stringent test of model
Spatial variability of ozone
Presentation title | Presenter name 27 |
Presentation title | Presenter name 28 |
Expected glyoxal & methylglyoxal mixing ratios using parallel precursor measurements
29 |
Global average glyoxal and methylglyoxal lifetimes (Fu et al 2008)
Yield from oxidation of precursor (Fu et al 2008)
Lifetime of precursor calculated from seasonal [OH] and [O3]
Mixing ratio of precursors: *PTR-MS data *flask data (GC MS FID)
Mixing ratio of glyoxal and methylglyoxal expected
SOAP measurement summary Measurement Organisation
Air Sea Exchange CO2/ DMS flux NIWA, NUIG Ireland, UC Irvine US, IFM-G Germany, U Chapman US, SUNY US
Ocean Biology/ biogeochemistry
SST, Diss. DMS, DMSP, pH, DOM characterisation
NIWA, U Laval Canada
Chlorophyll-a, bacterial & phytoplankton density/ composition, bacterial enzyme activity, nutrients
NIWA
Atmospheric chemistry Aerosol nuclei production Aerosol chemical composition (filters) Aerosol size distribution/count Black carbon Cloud condensation nuclei (CCN)
UEF Finland NIWA QUT NIWA CSIRO CMAR
Atmospheric DMS UC Irvine, NIWA, CSIRO CMAR
Halocarbons, I2, halogen oxides NIWA University Cambridge
Volatile organic compounds CSIRO CMAR
SOAP Voyage track
The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology
Chatham Rise:
subtropical front:
Mixing of water
bodies (nutrient
rich sub-Antarctic
and nutrient
depleted sub-
tropical)
Bloom 2 Bloom 1
Bloom 3
Voyage obs compared to other sites
Protonated Mass
Most Probable Compound
SOAP Chatham Rise Oceanic
Bloom transects ppt
10-90 percentile
Cape Grim Oceanic [1] -
[3]
Southern Hemisphere Mid-Latitude
Oceanic [4]- [7]
Subtropical/ Tropical Oceanic
[8]- [14]
33 Methanol 229 - 1067 476-633 595-727 575-890
42 Acetonitrile 27- 55 25-32 20 111-142
45 Acetaldehyde 19 - 91 nd- 53 120 204-500
59 Acetone 109 - 410 61-118 100 - 450 350-630
63 DMS 55 - 484 ~80-95 140-250 50-270
69 Isoprene 9 - 43 14-21 30-187 2-120
81/137 Monoterpenes 14 - 32 nd-25 5-125 2-80
DNPH/HPLC Formaldehyde 154 - 729 ~350 ~300 211-550
The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology
[1] Galbally et al (2007), [2] Lawson et al (2011), [3] Ayers et al (1997), [4] Colomb et al (2009), [5] Williams et al (2010),
[6] Weller and Schrems (2000), [7] Yassaa et al 2008, [8] Singh et al (2004), [9] Williams et al (2004), [10] Warneke et al
(2009), [11] Sinreich et al (2010), [12] Zhou and Mopper (1990ab), [13] Zhou and Mopper (1993) [14] Bonsang (1992)
DMS emissions and the sulphur cycle
The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology
bloom 1 bloom 2 bloom 3
Atmospheric DMS influenced by seawater concs
The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology
UCI atmospheric and seawater data courtesy of Eric Saltzman and
Tom Bell
DMS and acetone – common biological source?
The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology
Locally high concentrations of isoprene, monoterpenes
The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology