Transcript Inventory of WEEE in Latvia

February 10, 2009
Preparation of the guidelines
for vehicle non-exhaust
emission modelling of PM10
and PM2.5 in Latvia
Aiga Kāla, Valts Vilnītis
SIA Estonian, Latvian & Lithuanian
Environment
Outline
• Main tasks of the project
• Work programme:
– field work,
– evaluation and modelling
• Results of the project
The project
• Started in 2007
• In line with new requirements of
CAFE directive on exceedances
attributable to winter-sanding or salting of roads
• Co-financed by Latvian
Environmental Protection Fund,
Latvian Environment, Geology, and
Meteorology Agency and ELLE
Main tasks of the project
• To indentify and compare the
existing emission factors attributable
to vehicle non-exhaust emissions
• To perform the field measurements
• To compare dispersion modelling
results to the monitored values
• To prepare guidelines
PM contributions to an urban
agglomeration*
* Source: Marcus Pesch, 2008. Source apportionment of PM
Method for estimating
resuspension
Assumptions:
– PM2.5 is solely attributable to vehicular exhaust
sources
– Coarse fraction PM2.5–10 – to non-exhaust sources
ETOTAL = ETYRE + EBRAKE + ERESUSP
ETOTAL
EBRAKE
ETYRE
ERESUSP
- the total non-exhaust PM emission,
- the PM emission due to brake ware,
- the PM emission due to tyre ware,
- the PM emission corresponding to resuspension
Field work
• PM10 and PM2.5 measurements
in the two measurement sites
(GRIMM-EDM107):
– traffic station;
– urban background.
• Continuous traffic counts
(RTMS model K3)
Measurement sites
Monthly average concentrations PM2.5
and PM10 , µg/m3
60
50
ONK PM-10
40
30
ONK PM-2.5
20
MEZC PM-10
10
0
MEZC PM-2.5
Daily traffic average
12000.0
Volume
10000.0
8000.0
6000.0
4000.0
2000.0
0.0
Volume
Hourly traffic average
800.00
700.00
600.00
500.00
400.00
300.00
200.00
100.00
0.00
STL – Heavy duty vehicles, VTL – Light duty vehicles
STL
VTL
Estimation of emission factor
• Based on measured roadside
increments of PM10 and PM2.5 and
traffic counts
• Contribution of abrasion sources (tyre,
brake) – according to
EMEP/CORINAIR Emission
Inventory Guidebook (2007)
• Resuspension emission factor
estimated using dispersion modelling
(ADMS)
Non-exhaust PM emission
factors/models
• EMEP/CORINAIR Emission
Inventory Guidebook – 2007
• RAINS (Regional Air Pollution INformation
and Simulation)
• CEPMEIP (Co-ordinated European
Programme on Particulate Matter Emission
Inventories, Projections and Guidance)
• MOBILE 6.2
Advantages of
EMEP/CORINAIR methodology
• Emission factor depends on:
– Vehicle speed,
– Load correction factor (heavy-duty
tracks),
– Truck size.
• In all cases provide emission
factor for PM10 and PM2.5
Emission factor for resuspension
Vehicle category
Litgh-duty vehicle
Heavy-duty vehicle
Emission factor,
g/km
0.9
2.7
Emission factors reported for
other countries
UK
Emission factor for
ressusspension, mg/km
3.47 (LDV) 134 (HDV)
Italy
41 (54)
USA
Sweden
410 (540)
230 – 7800
205
Dispersion modelling for traffic
monitoring sites
Traffic monitoring sites
Average concentrations of PM10
(μg/m3)
(without/with resuspension)
Monitoring site
Monitored
value
K.Valdemāra iela
45.02
Brīvības iela
52.55
S. Eizenšteina iela
32.49
* Ratio of modelled to observed concentration
Modelled
value,
(ratio*)
26.21
(0.58)
26.56
(0.51)
21.73
(0.53)
Modelled
value,
(ratio*)
34.96
(0.78)
41.14
(0.78)
26.94
(0.83)
Source apportionment of PM10 results
Brīvības street
Resuspension
Exhaust emissions
Urban background
Valdemāra street
Tyre ware
Brake ware
Further work
• Relationship of emission factor
with meteorological factors
(precipitation level, wind speed
and direction)
• Source apportionment of urban
background (62 – 77%):
– Transboundary part,
– Natural sources....