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STATUS OF GRD-2:Model development within NORTRIP
Bruce Rolstad DenbyIngrid Sundvor
Linkoping (26.10.2011)
The Norwegian Institute for Air Research (NILU). PO BOX 100, Kjeller 2027, Norway. [email protected]
Presentation
• Aim• Major changes• Overview of concept
• Some details on the road dust model• Some details on surface moisture model• Some examples• Demonstration• Way forward
Aim of NORTRIP
“The ultimate aim is to develop a process based emission model, that can be applied in any city without site specific empirical factors, for management and evaluation of abatement strategies and
that is able to describe the (non-exhaust) emissions on an hourly or at least daily
basis with satisfactory accuracy.”
GRD-2 major changes since last meeting
Removal of ‘shoulder’ concept• Not found to be beneficial and doubled the complexity
Introduction of ‘non-suspendable’ dust loading• Typically the major part of sanding• Impacts on abrasion (sandpaper effect)• Can be crushed to form ‘suspendable’ dust at a defined (unknown) rate
Impact of salting on surface humidity and melt temperature• Reduces the surface humidity and tends to keep the surface wetter• Has been shown to improve some datasets but not all
New datasets• A number of new datasets are available from Copenhagen, Helsinki and
many from Hornsgatan
User interface executable version of the model available
NORTRIP model concept and processes Emissions• Direct emissions of wear (road/tyre/brake)• Suspended emissions (traffic /wind blown)• Both inhibited by surface moisture
Dust mass balance model • Production through wear, abrasion, deposition, salting and sanding• Removal through suspension, cleaning, ploughing, spraying and drainage
Moisture balance model for water and ice• Production through precipitation, condensation, wetting• Removal through drainage, evaporation, spraying, ploughing
Assessment • Comparison with observations using NOX as a dispersion indicator
• Comparison with observed road moisture and temperature
NORTRIP model concept and processes
Surface moisture conditions
Salting
Wearroad, brake
and tyre
Sanding
Clea
ning
Melting and
freezing
Meteorological conditions Particles
TSP PM10PM2.5
Deposition Dra
inag
e
Sandpaper
Retainedwear
Road dustand salt
load
Dra
inag
e
Spra
ySp
ray
Plou
ghin
gPl
ough
ing
Prec
ipita
tion
Impact of salting
Salti
ngCrushing
Wetting
Evap
orati
on
cond
ensa
tion
Wind suspension
Direct emissions
Traffic suspension
Moisture retention
Temperature, humidity and radiation
Emissions are the sum of direct wear emissions and suspended emissions in the size fraction x
Suspended emissions are the sum of traffic induced and windblown emissions
Emissions
xsuspension
xdirect
x EEE
xroadwind
xroadsus
xsuspension EEE
tyre
suwistt
vehicle
lihev
vtxroadsusPM
vtroadsus
susroad
xroadsus fRME
,, ,
,,,
,
Dust and salt
loadingSuspension
rate
Proportion in size fraction x
Suspension rate for both dust and salt depends on suspension factor and moisture retention
Suspension factor per vehicle is dependent on speed
Suspension rate
Traffic volume
Suspension factor per vehicle
Moisture retention factor
roadroadsuspensionqvehvtj
suspensionvt
suspensionvtvt
suspension gsfVffNR ,),( ,,,
,0,,,
2
,,0
,
ref
vehvtsuspension
vtsuspension V
Vff
Tabulated suspension
factor
Vehicle speed
Tabulated suspension factors
1. Suspension factors are based on model fitting to data. Could be calculated independently if dust loading was measured. Relative rates for different tyre types could be based on SNIFFER or road simulator data
2. Removal rates of non-suspendable dust can be based on SNIFFER or other measurement campaigns where dust is applied.
3. Is quadratic speed dependence correct?
Road suspension
f0,suspension(veh-1) Studded tyres (st) Winter tyres (wi) Summer tyres (su)Non-suspendable
removal
Heavy (he) 4.00E-06 8.00E-06 2.00E-05 4.00E-04
Light (li) 1.00E-06 2.00E-06 2.00E-06 1.00E-04
Tabulated size fractions (direct and sus)
4. Size fractions for road wear and suspension are based on VTI information. Will direct emitted and suspended size fractions be different?
5. Size fractions for tyre and brake wear are literature based. Are these appropriate?
Fractional size distribution emissions
Wear parameter PMTSP PM10 PM2.5
fPM,dir-roadwear 0.5 0.12 0.006
fPM,dir-tirewear 0.5 0.1 0.01
fPM,dir-brakewear 1 0.8 0.5
fPM,sus-road 0.5 0.12 0.006
Mass balance on the road surface for suspendable and non-suspendable dust (j) and salt
Mass balance of dust and salt
dustdust
jdust SPt
M
saltsalt
jsalt SPt
M
Production terms for suspendable dust
Production terms for non-suspendable dust
Production of road dust
crushing
sandpaper
sussandingsanding
deposition
retentionwearsusdust
P
P
fP
P
PP
fugitive
sussandingsanding
nonsusdust
P
fPP
1
Retained wear
Deposition from ambient air
Suspendable fraction of applied sand
Road wear due to non-suspendable dustCrushing of non-suspendable dust
Non-suspendable fraction of sanding
Other fugitive sources
tire
suwistt
vehicle
lihevroadq
vtroadweardir
vtroadwear
vtroadwearretention ffWNP
,, ,,
,,0
,, 1
Production through the retention of road wear
Wear rates
Road wear: equations
Road wetness
Wear rates
Traffic volume
Fraction not
directly emitted
roadroadsnowppave
roadwearref
vehvtroadwear
vtroadwear sfh
V
VWW ,
,
,,0
,
Linear dependence on speed
Dependence on pavement
type
Dependence on snow depth
Tabulated wear rates
Road wearW0,roadwear (g km-1 veh-1) Studded tyres (st) Winter tyres (wi) Summer tyres (su)
Heavy (he) 24 2 2Light (li) 6 0.5 0.5
Tire wearW0,tirewear (g km-1 veh-1) Studded tyres (st) Winter tyres (wi) Summer tyres (su)
Heavy (he) 0.4 0.4 0.2Light (li) 0.1 0.1 0.1
Brake wearW0,brakewear (g km-1 veh-1) Studded tyres (st) Winter tyres (wi) Summer tyres (su)
Heavy (he) 0.04 0.04 0.04Light (li) 0.01 0.01 0.01
Tabulated wear rates
6. Need update of tyre and brake wear rates.
7. Summer tyre road wear needs to be set very high to simulate summer concentrations. Why? What is the summer wear source? Tyre, gravel abrasion? True for both Stockholm and Copenhagen data
Crushing of the non-suspendable dust (sand)
Abrasion (sandpaper effect) almost exactly the same
Crushing and abrasion of sand
Snow depth dependence
Tabulated
crushing factor
Traffic volume
Speed dependenc
e
tyre
suwistt
vehicle
lihevroadroadsnow
crushingref
vehvtcrushing
vtnonsusdustcrushing sf
V
VfNMP
,, ,,
,
,,0
,
Non-suspendabl
e dust loading
tyre
suwistt
vehicle
lihevroadsnow
ppave
roadwearref
vehvtsandpaper
vtnonsusdustsandpaper fh
V
VfNMP
,, ,,
,
,,0
,
8. In the model formulation there is little difference between crushing and abrasion. Chemical analysis of emissions or dust loaded needed
9. Should we include enhanced abrasion of tyres with sanding?
Removal of road dust and salt
Sink terms for suspendable dust and salt
jspray
jploughing
jcleaning
jdrainage
jwindblown
jsuspension
jsaltdust
S
S
S
S
S
SS
/ Traffic induced suspension of dust and salt
Wind blown suspension of dust and saltRemoval through drainage
Removal by cleaning
Removal through snow ploughing
Removal through splash and spray
All sink terms (except cleaning) are dependent on the surface moisture mass balance
Suspension sink uses the same suspension rate as for suspended emissions
Suspension sinks
tyre
suwistt
vehicle
lihev
vtsuspension
jsaltdust
jsuspension RMS
,, ,
,/
Traffic volume
Suspension factor per vehicle
Moisture retention factor
roadroadsuspensionqvehvtj
suspensionvt
suspensionvtvt
suspension gsfVffNR ,),( ,,,
,0,,,
Wind blown dust sink
)(, ,0,/ FFRgsfMS windroadroadsuspensionqsaltdustsuswindblown
3
,0
1)(
ref
thresh
windwind FF
FFFFFFR
Based on moisture removal rates (Rg from moisture model) and an efficiency factor heff
Drainage and spray
jeffdraindraing
jsaltdust
jdrainage hRMS ,/
jeffspraysprayg
jsaltdust
jspray hRMS ,/
Efficiency factors for dust and saltEfficiency parameter Dust(suspendable) Dust (non-suspendable) Salt
hploughing-eff 0.01 0.1 0.01
hcleaning-eff 0.01 0.1 0.1
hdrainage-eff 0.01 0.1 1
hspraying-eff 0.01 0.1 1
10. Any information available to define these efficiency parameters?
Suspendable dust loading
Example of mass balance
Non-suspendable dust loading
Studded tyre season
Daily mean emission and dust loading example Hornsgatan 2010-2011
11. Measurement of dust and salt loading (size specific) needed to validate the model!
Moisture balance for water (g) and ice/snow (s) on the road surface
Production terms
Moisture model
Sink terms
roadgroadgroad SPt
g,,
roadcondensgroadwettinggroadsnowmeltgroadraingroadg PPPPP ,,,,,
roadfreezegroadevapgroadspraygroaddraingroadg SSSSS ,,,,,
Surface energy balance model
roadsroadsroad SPt
s,,
Energy balance model to determine latent heat flux (Ls)
Energy balance model
trafficsssnetlongsnetshorts HLHRRG ,,
Ls
Rshort-net
Rlong-net
HsGs
Energy balance: average daily cycle
Htraffic
Energy balance model predicts the surface temperature
Energy balance model
ModelledObserved
Predicts the surface moisture
ObservedModelled
Drainage problem
Drainage rate given as constant time scale
Drainage and spray removal processes
Spray dependent on traffic volume and spray factor
mindrainableroadroad
mindrainableroadroaddrainroad
roadroaddraing
gg
gggS
,
,,
for 0
for 1
12. Drainage may not be fast enough. Needs adjustment based on available moisture data from HBAC and Hornsgatan. Update numerics
minsprayableroadroad
minsprayableroadroad
vehicle
lihev
vveh
vspray
lanes
v
roadroadsprayg
gg
ggVfn
NgS
,
,,
,
for 0
for )(
13. Spray factor is lower than indicated by VTI. Needs an expert assessment!
Moisture retention
Observed and modelled moisture
Too dry
Just rightToo wet
Dry
Wet
Moisture retention factor (fq)
Dry Wet
No dust retention
Dust retention
Impact of salt surface on moistureReduces the surface vapour pressure and as a result the freezing point. Use Antoine equation to determine the saturated vapour pressure
TC
BAe
)(10log
Saturated NaCl solution reduces RH by 25%
Reduces freezing point to -21 C
Impact of salt on moisture: ExampleNo impact of salt on vapour pressure
Impact of salt on vapour pressure included
Model too dry
Impact of salt on moisture14. Need observational data concerning freezing point and salt concentrations on the road. HCAB data and Hornsgatan data? Other data that is available?
15. Need improved activity data. Quantity and timing of salting, salt solution. Any cleaning associated with salting.
16. In regard to salt also need measured ambient air concentrations of salt. This is available for Oslo but not assessed yet.
Example applications: Oslo RV4
PM10
PM2.5
Cold wet period Dry period
Salt
Close to exhaust emissions
Net daily mean concentration including salting
Studded tyre season
Salting
Example applications: Hornsgatan
Using modelled moisture r2 = 0.47
Summer
Cold and wet
Using observed moisture r2 = 0.83
Much better
Studded tyre season
Net daily mean concentration without salting
Dry spring
Example applications: Hornsgatan
Using modelled moisture r2 = 0.47
Using observed moisture r2 = 0.83
Net daily mean concentration
Model too dry
Example applications: Hornsgatan
Using modelled moisture r2 = 0.35
Using observed moisture r2 = 0.71
Net hourly mean concentration
Too dryToo
wet
A brief summary
• Dust loading and surface moisture approach can provide very good results (Omstedt et al., 2005)
• Road surface moisture impacts on both the timing and the total emissions
• Modelling both dust loading and moisture is essential
• Salt can make a significant contribution to the emissions (observed in Oslo)
• Shoulder contribution not found to be significant
NORTRIP future model development• Go through the list presented today• Improve vehicle speed dependence of suspension, based on
experimental data • Improve data concerning road maintenance activities• Direct comparison of the road surface moisture model with
surface moisture measurements• Apply to non-Nordic countries to assess its applicability in
other environments (interested?)• Apply to road and air quality management applications
Development needs
• Summer time emissionsTo reproduce the summer time emissions a significantly higher wear rate has been employed than is expected from laboratory studies of summer tyres. Why?
• Many processes, too many parameters, too many unknownsA number of the parameters used in the model are currently poorly defined. Further measurements of processes, such as road dust/salt loading and suspension rates, are required for improving these.
• Activity data is required but is seldom available
Input data requirements
• MetadataRoad configuration, pavement type, surface albedo, etc.
• Traffic dataVolume, tyre type, vehicle type, vehicle speed
• Meteorological dataWind, temperature, humidity, global radiation (cloud cover)
• Activity dataSalting, sanding, cleaning, ploughing, wetting
• Model parametersWear rates, suspension rates, etc.
NORTRIP future model applications
• Implementation in AQ modelling systemsUrban scale modelsRegional scale models
• Management applicationsImpact of salting and dust bindingQuantification of salt contribution to PMQuantification of sanding contribution to PMImpact of studded tyresImpact of cleaningImpact of traffic speedImpact of meteorological conditions
