NORTRIP: Kjeller meeting NILU: Generalised road dust emissions model (GRD-2) Bruce Rolstad Denby and...

NORTRIP: Kjeller meeting

NILU: Generalised road dust emissions model (GRD-2)

Bruce Rolstad Denby

andIngrid Sundvor

Contents (1)• Expectations from the meeting• Model overview

o Conceptso Road dust model (GRD-2)o Comparison between emission models (GRD-2/SMHI)o Surface moisture model (GRD-2)o Road dust and surface moisture linkageso Model documentation

• Some first resultso Hornsgatan (2009)o Hornsgaten (2010)o RV4 (2005)o NB (2002)

Contents (2)• Demonstrations

o Suspension factor sensitivity (Hornsgatan)o Comparison of evaporation schemes (Hornsgatan)o Demonstration of cleaning (Hornsgatan)o Demonstration of salting (RV4)

• Datasets• Plans

Expectations this meeting

• Demonstrate some aspects of the model• Improve the parameterisations in regard to

– wear parameters (VTI)– suspension parameters (DMU)– sanding and the sand paper effect (FMI)– impact of salting (NILU)– traffic induced turbulence parameterisation (DMU)– splash/spray parameterisation (SMHI)

• Plan and encourage– provision of data sets– inter-comparison (models and parameterisations)– develop application studies of the models

GRD-2 concept

• A structure within which road dust emission processes can be quantified and can interact

• Mass loading based on:– wear (road, tire and break)– addition of external mass

• Emissions based on:– direct wear– suspension

• Surface retention based on surface moisture process

• Described in documentation (v5)

Dust and salt surface mass balance

• Production through:– retained wear (road, tires, brakes) – ambient air deposition– salting and sanding– sand paper effect

• Removal through:– traffic induced suspension of surface mass– wind induced suspension of surface mass– drainage– spray/splash

• Distributed over road and shoulder surfaces

• Emission through direct wear– inhibited by surface moisture

• Emission through suspension– traffic induced suspension– wind induced suspension– inhibited by surface moisture

• Size fraction:– fixed size distributions of emissions

• Emitted from road and shoulder surfaces

Dust and salt emissions

GRD-2

Road dust (M)

Wear W(N,V) .f0,direct . fq . fPM10

PM101-f0,direct . fq

Direct emissions

fsuspend (V2,3).fq.fPM10

Suspended emissions

f0,direct = Fraction of wear emitted directly(0.5)f0,suspend = Fraction of mass suspended (Veh-1hr-1) (1x10-4)fq = Retention factor(0 – 1)fPM10 = PM fraction emitted as PM10 (0.2)

GRD-2

Removal

Road dust (l)

Wear + sanding

PM10ast

.fq . ewinter ref

Suspended emissions

ast = Fraction with studded tires(0.7)ewinter ref = Reference emission factor (g/km)(1200 )l = Normalised road dust loading (0 – 1)kdecay = Decay rate for road dust (Veh-1hr-1) (2x10-6)

Omstedt et al.

fq . kdecay

Mass loading and sanding are normalised quantities

Road dust removal not coupled to suspension

Surface moisture mass balance • Production through:

– precipitation (rain/snow)– snow melt– condensation (affected by salting)– wetting during salting/cleaning

• Removal through:– evaporation (affected by salting)– drainage– spray/splash

• Includes snow mass balance– removal by ploughing and by snow melt

Dust and moisture model linkages

• Surface moisture (and snow) retention:– retention of direct wear producing surface mass– retention of direct wear reducing emissions – retention of surface mass through inhibited suspension

• Drainage and spray of water, dust and salt– mixing of dust and salt in surface water– removal of mixed layer through drainage and spray

• Evaporation/condensation affected by salt– reduced vapour pressure

• Melting point affected by salt– reduced melting point

Retention based on surface moisture

• Surface moisture retention (fq) is given by

• gthresh is the threshold surface moisture above which full retention occurs (fq = 0) .– simple formulation– may be different for direct and suspended emissions– may be different for different wear sources– may be different for shoulder and road

• How wet is a dry road?

sourceemisthresh

surfsourceemisq g

gf

,, 1 ,0max

Documentation and model code

• All model processes are described in the documentation (v5.0)– still in development (v5.1)

• Model is coded in MatLab– easy visualisation and development possibilities– will be transferred to FORTRAN when complete– will be available to NORTRIP

• Input data and model input parameters– model parameter excel sheets (dust model only)– model input data excel sheets (RV4, NS, Hornsgaten)

• All code/data uploaded to the NORTRIP ftp site

Example of model output for Hornsgatan: (Daily means for winter 2009)

• Traffic data• Meteorological data• Mass balance and emissions• Surface wetness• Other factors• Energy balance• Concentrations

• 60% studded tires, 27 000 veh/day at 45 km/hr

Example of model output for Hornsgatan: (Daily means for 2010)

• Meteorological data• Mass balance and emissions• Surface wetness• Concentrations• 40% studded tires in winter, 2% in summer• 22 000 veh/day at 45 km/hr

Example of model output for RV4 (2004)

• Meteorological data missing– wind, radiation, cloud cover

• 27% studded tires• 44 000 veh/day• 80 km/hr• Known to have significant contributions from salt,

around 30% for the whole period.

Example of model output for NB (2002)

• Meteorological data missing– radiation, cloud cover

• No PM2.5 data• Only daily mean average background PM10• 32% studded tires• 35 000 veh/day at 94 km/hr

Suspension concepts/questions

• Suspension is the combined effect of grinding and emission.– creates ‘suspendable’ particle sizes from larger particles ( V?)– ejects these particles mechanically or through turbulence ( V?)

• Is it necessary to divide the surface mass into >TSP and <TSP size distributions? – better suspension description– better road cleaning description– better sanding and sand paper effect description

• How to determine suspension parameters from measurements?– road dust loading under dry conditions– fitting the model to observed concentrations

f0,direct = 1.0f0,suspend = 1x10-4

f0,direct = 0.0f0,suspend = 1x10-4

f0,direct = 0.5f0,suspend = 1x10-5

f0,direct = 0.5f0,suspend = 1x10-4

(default)

Suspension factor sensitivity

Stop

Surface moisture mass balance • Production through:

– precipitation (rain/snow)– snow melt– condensation (affected by salting)– wetting during salting/cleaning

• Removal through:– evaporation (affected by salting)– drainage– spray/splash

• Includes snow mass balance– removal by ploughing and by snow melt

• Basis for Penman and energy balance equations

• Penman does not know the surface flux but requires as input. Also uses parameterisation of net long wave radiation.

• Energy balance solves for surface temperature and outgoing radiation using

snets RG ,2.0

Surface energy balance

sssnets LHRG ,

soutsinroadsinsnet RLRLRSR ,,,, )1(

ssnet GR ,

s

s

ss

s

z

G

ct

T

1

Penman modified

Energy balance

Comparison of evaporation/condensation

1. Fixed evaporation time scale (48 hours)2. Penman-Omstedt (surface RH = 100%)

– potential evaporation from a wet surface– evaporation reduced with a fixed factor (fevap= 0.075, 0.3)

– no information on surface heat flux

3. Penman modified (surface RH = gsurf/gthresh)– no information on surface heat flux– reduces surface relative humidity for gsurf < 0.2 mm

4. Bulk energy balance method (surface RH)– prognoses surface temperature and surface heat flux– reduces surface relative humidity for gsurf < 0.2 mm

1. Constant time scale (48 hr)

2. Penman - Omstedt (f=0.075)

4. Penman – modified (G=0.2*net rad)

5. Energy balance

3. Penman - Omstedt optimised (f=0.3)

Evaporation demonstration

Surface moisture mass balance • Drainage– Drainage time scale (4 hours)– Drainage stops at a threshold value (1 mm)– Also removes mass, assuming a well mixed layer

• Splash and spray– not implemented– should remove significant amounts, down to a threshold of

X mm?

• Snow mass balance– degree hour model for snow melt (can also use EB model)– removal by ploughing

1. Without road cleaning

2. With road cleaning

Road cleaning demonstration

Road salting demonstration

1. Without salting

2. With dry salting(3 days, -10 < T < 0)

• Road surface moisture– Meteo data, surface temperature, surface moisture, salt content, cleaning

and salting activities, splash and spray data

• Concentration data– Street level and background for PM and NOx

• Activity data– Salting activities– Cleaning activities– Ploughing activities– Sanding activities

• Mass balance data– Road dust and salt loading– Concentrations in surface water and drainage water

Data sets required

• Model development– Implementation of new parameterisations– Develop code and interface using excel sheets (executable)– Division of road dust into > TSP and < TSP size categories?

• Database– Add Kirkeveien and RV4 2005, 2006 to database (Other?)– Supplement with other meteorological data

• Apply the models– Use a range of input data sources for model inter-comparisons– Speed reduction studies– Salting impact on surface moisture– Contribution of salting and sanding to PM concentrations

Plans for 2011 (1)

• Reports– Complete and QC model documentation– Model users guide

• Possible publications– A review of road dust emission data– GRD-2 description and validation – Inter-comparison of road dust emission models– Impact of speed reduction, salting on road dust emissions– Model applications to road surface management

Plans 2011 (2)