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Title: Modeling the Atmospheric Transport and Deposition of Mercury


1
Modeling the Atmospheric Transport and
Deposition of Mercury
Dr. Mark Cohen NOAA Air Resources Laboratory 1315
East West Highway, R/ARL, Room 3316 Silver
Spring, Maryland, 20910 301-713-0295
x122 mark.cohen_at_noaa.gov http//www.arl.noaa.gov/
ss/transport/cohen.html
Materials assembled for Mercury in Maryland
Meeting, Appalachian Lab, Univ. of Maryland
Center for Environmental Science 301 Braddock
Road, Frostburg MD, Nov 2-3, 2005
2
  • What do atmospheric mercury models need?
  • Atmospheric mercury modeling
  • Why do we need atmospheric mercury models?
  • Some preliminary results
  • Model evaluation
  • Source Receptor Information

2
3
  • What do atmospheric mercury models need?
  • Atmospheric mercury modeling
  • Why do we need atmospheric mercury models?
  • Some preliminary results
  • Model evaluation
  • Source Receptor Information

3
4
Atmospheric Mercury Fate Processes
4
5
NOAA HYSPLIT MODEL
5
6
6
7
  • What do atmospheric mercury models need?
  • Atmospheric mercury modeling
  • Why do we need atmospheric mercury models?
  • Some preliminary results
  • Model evaluation
  • Source Receptor Information

7
8
Why do we need atmospheric mercury models?
  • to get comprehensive source attribution
    information ---
  • we dont just want to know how much is
    depositing at any given location, we also want to
    know where it came from
  • to estimate deposition over large regions,
  • because deposition fields are highly spatially
    variable,
  • and one cant measure everywhere all the time
  • to estimate dry deposition
  • to evaluate potential consequences of alternative
    future emissions scenarios

9
But modelsmust have measurements
Modeling needed to help interpret measurements
and estimate source-receptor relationships
Monitoring required to develop models and to
evaluate their accuracy
10
  • What do atmospheric mercury models need?
  • Atmospheric mercury modeling
  • Why do we need atmospheric mercury models?
  • Some preliminary results
  • Model evaluation
  • Source Receptor Information

10
11
What do atmospheric mercury models need?
Emissions Inventories
Meteorological Data
Scientific understanding of phase partitioning,
atmospheric chemistry, and deposition processes
Ambient data for comprehensive model evaluation
and improvement
11
12
12
13
Why is emissions speciation information critical?
Logarithmic
Hypothesized rapid reduction of Hg(II) in plumes?
If true, then dramatic impact on modeling
results
13
14
14
15
15
16
Atmospheric Chemical Reaction Scheme for Mercury
16
17
17
18
Some Additional Measurement Issues (from a
modelers perspective)
  • Data availability
  • Simple vs. Complex Measurements

19
Some Additional Measurement Issues (from a
modelers perspective)
  • Data availability
  • Simple vs. Complex Measurements

20
Data availability
21
Some Additional Measurement Issues (from a
modelers perspective)
  • Data availability
  • Simple vs. Complex Measurements

22
Simple vs. Complex Measurements 1. Wet
deposition is a very complicated phenomena...
?
  • many ways to get the wrong answer incorrect
    emissions, incorrect transport, incorrect
    chemistry, incorrect 3-D precipitation, incorrect
    wet-deposition algorithms, etc..

?
?
23
Simple vs. Complex Measurements 2. Potential
complication with ground-level monitors...
(fumigation, filtration, etc.)...
24
  • Simple vs. Complex measurements - 3. Urban areas
  • Emissions inventory poorly known
  • Meteorology very complex (flow around buildings)
  • So, measurements in urban areas not particularly
    useful for current large-scale model evaluations

25
Simple vs. Complex Measurements 4 extreme
near-field measurements
Sampling site?
Ok, if one wants to develop hypotheses regarding
whether or not this is actually a source of the
pollutant (and you cant do a stack test for some
reason!).
  • Sampling near intense sources?
  • Must get the fine-scale met perfect

26
Complex vs. Simple Measurements 5 Need some
source impacted measurements
  • Major questions regarding plume chemistry and
    near-field impacts (are there hot spots?)
  • Most monitoring sites are designed to be
    regional background sites (e.g., most Mercury
    Deposition Network sites).
  • We need some source-impacted sites as well to
    help resolve near-field questions
  • But not too close maybe 20-30 km is ideal (?)

27
  • What do atmospheric mercury models need?
  • Atmospheric mercury modeling
  • Why do we need atmospheric mercury models?
  • Some preliminary results
  • Model evaluation
  • Source Receptor Information

27
28
Participants
D. Syrakov .. Bulgaria. NIMH A.
Dastoor, D. Davignon Canada...... MSC-Can J
. Christensen . DenmarkNERI G.
Petersen, R. Ebinghaus ...... GermanyGKSS J.
Pacyna . Norway.. NILU J. Munthe,
I. Wängberg .. Sweden.. IVL R. Bullock
USAEPA M. Cohen, R. Artz, R.
Draxler USANOAA C. Seigneur, K. Lohman
.. USA... AER/EPRI A. Ryaboshapko, I.
Ilyin, O.Travnikov EMEP MSC-E
28
29
Intercomparison Conducted in 3 Stages
  • Comparison of chemical schemes for a cloud
    environment
  • Air Concentrations in Short Term Episodes
  • Long-Term Deposition and Source-Receptor Budgets

29
30
Participating Models
30
31
Anthropogenic Mercury Emissions Inventoryand
Monitoring Sites for Phase II(note only showing
largest emitting grid cells)
31
32
Total Gaseous Mercury (ng/m3) at Neuglobsow June
26 July 6, 1995
32
33
Total Particulate Mercury (pg/m3) at Neuglobsow,
Nov 1-14, 1999
33
34
Reactive Gaseous Mercury at Neuglobsow, Nov 1-14,
1999
34
35
35
36
  • What do atmospheric mercury models need?
  • Atmospheric mercury modeling
  • Why do we need atmospheric mercury models?
  • Some preliminary results
  • Model evaluation
  • Source Receptor Information

36
37
Example of Detailed Results 1999 Results
for Chesapeake Bay
37
38
Geographical Distributionof 1999 Direct
Deposition Contributions to the Chesapeake Bay
(entire domain)
38
39
Geographical Distribution of 1999 Direct
Deposition Contributions to the Chesapeake Bay
(regional close-up)
39
40
Geographical Distribution of 1999 Direct
Deposition Contributions to the Chesapeake Bay
(local close-up)
40
41
Largest Regional Individual Sources Contributing
to1999 Mercury Deposition Directly to the
Chesapeake Bay
41
42
Largest Local Individual Sources Contributing
to1999 Mercury Deposition Directly to the
Chesapeake Bay
42
43
Emissions and Direct Deposition Contributions
from Different Distance Ranges Away From the
Chesapeake Bay
43
44
Top 25 Contributors to 1999 Hg Deposition
Directly to the Chesapeake Bay
44
45
Preliminary Results for other Maryland Receptors
45
46
Maryland Receptors Included in Recent Preliminary
HYSPLIT-Hg modeling (but modeling was not
optimized for these receptors!)
46
47
Largest Modeled Atmospheric Deposition
Contributors Directly to Deep Creek Lake based
on 1999 USEPA Emissions Inventory (national view)
47
48
Largest Modeled Atmospheric Deposition
Contributors Directly to Deep Creek Lake based
on 1999 USEPA Emissions Inventory (regional view)
48
49
Largest Modeled Atmospheric Deposition
Contributors Directly to Deep Creek Lake based
on 1999 USEPA Emissions Inventory (close-up view)
49
50
Some Next Steps
50
51
Conclusions
51
52
Thanks
52
53
EXTRA SLIDES
53
54
Why might the atmospheric fate of mercury
emissions be essentially linearly independent?
  • Hg is present at extremely trace levels in the
    atmosphere
  • Hg wont affect meteorology (can simulate
    meteorology independently, and provide results
    to drive model)
  • Most species that complex or react with Hg are
    generally present at much higher concentrations
    than Hg
  • Other species (e.g. OH) generally react with many
    other compounds than Hg, so while present in
    trace quantities, their concentrations cannot be
    strongly influenced by Hg
  • Wet and dry deposition processes are generally
    1st order with respect to Hg
  • The current consensus chemical mechanism
    (equilibrium reactions) does not contain any
    equations that are not 1st order in Hg

54
55
Spatial interpolation
Impacts from Sources 1-3 are Explicitly Modeled
1
RECEPTOR
2
3
55
56
  • Perform separate simulations at each location for
    emissions of pure Hg(0), Hg(II) and Hg(p)
  • after emission, simulate transformations
    between Hg forms
  • Impact of emissions mixture taken as a linear
    combination of impacts of pure component runs on
    any given receptor

56
57
Chemical Interpolation
Impact of Source Emitting Pure Hg(0)
0.3 x
Impact of Source Emitting 30 Hg(0) 50
Hg(II) 20 Hg(p)


Impact of Source Emitting Pure Hg(II)
0.5 x

Impact of Source Emitting Pure Hg(p)
0.2 x
57
58
58
59
Standard Source Locations in Maryland region
during recent simulation
59
60
60
61
Eulerian grid models givegrid-averaged estimates
difficult to compare against measurement at
a single location
62
Geographic Distribution of Largest Anthropogenic
Mercury Emissions Sources in the U.S. (1999) and
Canada (2000)
62
63
63
64
  • In principle, we need do this for each source in
    the inventory
  • But, since there are more than 100,000 sources in
    the U.S. and Canadian inventory, we need
    shortcuts
  • Shortcuts described in Cohen et al Environmental
    Research 95(3), 247-265, 2004

64
65
Cohen, M., Artz, R., Draxler, R., Miller, P.,
Poissant, L., Niemi, D., Ratte, D., Deslauriers,
M., Duval, R., Laurin, R., Slotnick, J.,
Nettesheim, T., McDonald, J. Modeling the
Atmospheric Transport and Deposition of Mercury
to the Great Lakes. Environmental Research
95(3), 247-265, 2004. Note Volume 95(3) is a
Special Issue "An Ecosystem Approach to Health
Effects of Mercury in the St. Lawrence Great
Lakes", edited by David O. Carpenter.
65
66
  • For each run, simulate fate and transport
    everywhere,
  • but only keep track of impacts on each selected
    receptor
  • (e.g., Great Lakes, Chesapeake Bay, etc.)
  • Only run model for a limited number (100) of
    hypothetical, individual unit-emissions sources
    throughout the domain
  • Use spatial interpolation to estimate impacts
    from sources at locations not explicitly modeled

66
67
0.1o x 0.1o subgrid for near-field analysis
67
68
0.1o x 0.1o subgrid for near-field analysis
68
69
69
70
70
71
71
72
72
73
Hypothesized rapid reduction of Hg(II) in plumes?
If true, then dramatic impact on modeling
results
74
Why is emissions speciation information critical?
Linear
74
75
Why is emissions speciation information critical?
Logarithmic
Linear
75
76
Emissions and Chemistry
  • The form of mercury emissions (elemental, ionic,
    particulate) is often very poorly known,
  • but is a dominant factor in estimating
    deposition (and associated source-receptor
    relationships)
  • Questions regarding atmospheric chemistry of
    mercury may also be very significant
  • The above may contribute more to the overall
    uncertainties in atmospheric mercury models than
    uncertainties in dry and wet deposition
    algorithms

77
77
78
Total Gaseous Mercury at Neuglobsow June 26
July 6, 1995
78
79
Total Gaseous Mercury (ng/m3) at Neuglobsow June
26 July 6, 1995
The emissions inventory is a critical input to
the models
Using default emissions inventory
79
80
Some Additional Measurement Issues (from a
modelers perspective)
  • Data availability
  • Simple vs. Complex Measurements
  • Process Information

81
Process Information 1. Dry Deposition -
Resistance Formulation
  • 1
  • Vd --------------------------------- Vg
  • Ra Rb Rc RaRbVg
  • in which
  • Ra aerodynamic resistance to mass transfer
  • Rb resistance of the quasi-laminar sublayer
  • Rc overall resistance of the canopy/surface
    (zero for particles)
  • Vg the gravitational settling velocity (zero
    for gases).

82
Dry Deposition
  • depends intimately on vapor/particle partitioning
    and particle size distribution information
  • resistance formulation Ra, Rb, Rc...
  • for gases, key uncertainty often Rc (e.g.,
    reactivity factor f0)
  • for particles, key uncertainty often Rb
  • How to evaluate algorithms when phenomena hard to
    measure?

83
Particle dry deposition phenomena
Atmosphere above the quasi-laminar sublayer
Ra
Very small particles can diffuse through the
layer like a gas
Very large particles can just fall through the
layer
Quasi-laminar Sublayer ( 1 mm thick)
In-between particles cant diffuse or fall easily
so they have a harder time getting across the
layer
Rb
Wind speed 0 (?)
Rc
Surface
84
Vd settling velocity
Diffusion low Settling velocity low Vd
governed by Rb
Diffusion high Vd governed by Ra
85
Process information needed1. For particle dry
deposition, must have particle size distributions!
86
ATMOSPHERE
Particle-Phase Pollutant
Gas-Phase Pollutant
PROCESS INFORMATION 2. The gas-exchange flux at
a water surface depends on the concentration of
pollutant in the gas-phase and the
truly-dissolved phase (but these are rarely
measured)
Pollutant Truly Dissolved in Water
Pollutant on Suspended Sediment
LAKE
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