My background

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• 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

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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