At the 2014 annual Dispersion Modellers user group meeting guest speaker Duncan Laxen spoke on the topic: 'Linking ADMS with micro-simulation models'

1. Linking ADMS with
Microsimulation Models
Prof. Duncan Laxen
and
Dr Ben Marner

2. Outline of Presentation
• Will look at a study AQC carried out for Reigate
and Banstead Borough Council to test options to
address NO2 concentrations in a small AQMA at a
road junction in the north of the borough
• The study used a microsimulation traffic model to
provide emission factors taking into account
vehicle acceleration

3. AQMA
 AQMA is a single property
in the north of the Borough
 At the junction of two main
roads Reigate Road and Fir
Tree Road

4. Benefits of Microsimulation
Traffic Models
• A conventional traffic model produces
 Link-average speeds and flows
• A microsimulation traffic model
 Can provide details of flows, speeds and
acceleration for individual lanes in great spatial
detail
 But resource intensive, so mainly applied to
smaller sets of links and usually to peak hours

5. Traffic Models
Saturn-Type Model Microsimulation Model

6. Acceleration is a Key Benefit
Instantaneous Emission
Factors (from David Carslaw)
Average Speed Emission
Factors
NOx from Diesel Cars – remote sensing
20mph
30mph

7. This Study
 S-Paramics Microsimulation Traffic Model (run by SIAS)
+ AIRE Instantaneous Emission Model (maintained by SIAS
for Transport Scotland)
+ ADMS-Roads Dispersion Model
(Annual mean NO2 from predicted annual mean road-NOx to Annual mean NO2
using Defra background maps and NOx to NO2 calculator)
 Traffic and emissions models run for 3 x 24hr periods:
typical weekday, Saturday and Sunday
 Emissions were extracted for each 2m section of road
network for each 5-minute period and for each for 1-hour
period and then input to ADMS Roads

8. AQMA at Junction of 2 Roads
26 mg/m3
46 mg/m3
41 mg/m3
Annual Mean NO2
concentrations in 2012

9. Network broken down into 3,500
2m line sources
High degree of automation,
taking the data from S-Paramics
to AIRE to
ADMS, and then collating
the results
In ADMS, all emissions set
to 1g/km/s, and then the
AIRE data entered as .hfc
files
Also modelled the same network using 1-hour
link-average speeds for each 2m link but using
EFT emissions for comparison

10. Modelled Roads
58 road lane sections modelled
S-Paramics:
•Traffic counts
•Traffic speeds
•Vehicle mix
AIRE:
•1-hour emission profiles
•5-minute emission profiles

11. AIRE vs EFT Comparison
Predicted Annual Mean Road-NOx Based on AIRE vs EFT
(EFT used 2m link speeds)
 Modelled 109
receptors
 Much Greater
Range in AIRE-Based
Predictions
than in EFT-Based
Predictions
EFT
AIRE

12. Results on One Link (EFT vs AIRE)
 Different Movements Compare Differently
 Large Variation in Concentrations Along a
Relatively Short Road-Section (depend on
acceleration and idle time)

13. Modelled Concentrations
2007 Further Assessment
(2010 concentrations)
This Study

14. Difference in Concentrations
Standard EFT assessment
(redone) vs
Microsimulation AIRE
assessment
Red shows EFT>AIRE
Blue shows EFT<AIRE

15. Traffic Management Scenarios
Option 1 – Introduce a 20 mph
speed limit
Option 2 – Remove southbound
left-hand lane of A240 (N)
Option 3 – Extended green traffic light

16. Scenario Testing – Option 3
• Option 3 – extended
green traffic light
Up to 0.2 mg/m3
reduction in AQMA
Up to 0.7 mg/m3 increase
in locations with no
relevant exposure
Change in Predicted Annual Mean
NO2 (μg/m3) between Option 3 and
Do Nothing

17. Scenario Testing – Option 2
Change in Predicted Annual Mean NO2
(μg/m3) between Option 2 and Do
Nothing
• Option 2 – removal of
the southeast-bound
left-hand lane on
junction approach
Up to 0.9 mg/m3 reduction
in AQMA
Up to 1.0 mg/m3 increase
in locations with no
relevant exposure

18. Scenario Testing – Option 1
• Option 1 – 20 mph
speed limit (reduced
from 30 mph)
Up to 4.4 mg/m3
reduction in AQMA
Up to 13.1 mg/m3
increase in locations
with no relevant
exposure
Change in Predicted Annual Mean
NO2 (μg/m3) between Option 1 and
Do Nothing

19. Traffic Management Option 1
Option 1 – Introduce a 20 mph
speed limit
Base Option 1
Predicted NO2 Concentrations (μg/m3) Predicted NO2 Concentrations (μg/m3)

20. Study Limitations
 The local monitoring was insufficient to fully verify
the findings of the microsimulation modelling
 The findings depend on the accuracy of the
microsimulation model especially how acceleration
is presented (it is understood that there are differences
between microsimulation models and that S-Paramics
handles acceleration more accurately)

21. Other Observations
 2m links potentially over-kill for emissions
subdivision, but facilitated automated link with ADMS
source-geometry
 Automation meant that a larger study area could
have been modelled in ADMS relatively easily once
systems in place
 Even with this small network, volume of emissions
data made QA onerous (1/4 million different emissions
values per scenario)

22. Key Observations
 Use of average speed emission factors would
predict an adverse effect of implementing a 20mph
speed limit
 Use of microsimulation model shows that 20mph
limit can reduce emissions by reducing
accelerations, i.e. smoothing flows. There is support
for this view from a recent study in London

23. Similar Findings for 20mph
• Used floating car on routes in
London with 20 and 30mph limits
• Used drive-cycle profiles with
AIRE emission factors
• Found reduction in NOx
emissions on 20mph roads
Concluded: “.. it would be incorrect to
assume a 20mph speed restriction would
be detrimental to local air quality …”

24. Wide-scale Rollout of 20mph Zones

25. Thanks to
• Dr Leon Hibbs at Reigate and Banstead BC
• SIAS Transport Planners
• Defra (for grant funding)
• and Dr Austin Cogan at AQC

26. Head Office
23 Coldharbour Road, Bristol BS6 7JT
Tel: 0117 974 1086
London Office
12 Airedale Road, London SW12 8SF
Tel/Fax: 020 8673 4313