development and assessment of traffic-related …oa.upm.es/37032/1/inve_mem_2014_198188.pdf ·...

EOI - MIGMA 08-09. Introducción a la simulación de la calidad del aire

DEVELOPMENT AND ASSESSMENT OF TRAFFIC-RELATED EMISSION ABATEMENT MEASURES FOR THE MADRID CITY

(SPAIN) THROUGH THE WRF-SMOKE-CMAQ MODELLING SYSTEM

28 March 2014

Rafael Borge, Julio Lumbreras, David de la Paz, Javier Pérez, Mª Encarnación Rodríguez

Laboratory of Environmental Modelling. Technical University of Madrid (UPM).

24-28 March 2014, Garmisch-Partenkirchen, Germany

Special session on "Air pollution in cities"

[email protected]

EOI - MIGMA 08-09. Introducción a la simulación de la calidad del aire

1. Introduction

2. Methodology

3. Scenarios / measures

4. Results

5. Conclusions

OUTLINE

9th International Conference on Air Quality – Science and Application. Special session on Air pollution in cities

Development and assessment of traffic-related emission abatement measures for the Madrid city (Spain) 3

1. Introduction

• As environmental standards become more stringent (e.g. European Directive2008/50/EC), more reliable modelling tools are needed to simulate measuresand plans that may effectively tackle air quality exceedances, common inlarge cities across Europe, particularly for NO2.

• This is the case ofMadrid (Spain), 3.4million inhabitants in thecity, more than 5 millionpeople in themetropolitan area



• Madrid enacted a local AQP in 2012 to meet the NO2 standards by the end of2014

• It included a package of 70 measures, most of them aimed at the roadtransport sector

The Madrid Air Quality Plan (AQP)

Figures from Borge et al., 2014 (STOTEN)



0

5000

10000

15000

20000

25000

30000

35000

40000

45000

50000

TOTAL RCI Industria Tráfico rodado

Emis

ione

s N

OX (t

/año

)2007

2014

• A global decrease of 31% in NOX

emissions is expected (40% in the roadtransport sector)

NO2 annual mean (Annual LV)

NO2 annual 1h 99.8th percentile (1-h LV)

• Annual NO2 levels reduced by34% as an average; approximately15 μg/m3 in the city center

• Important impact in themetropolitan area (-7 μg/m3 as anaverage in the modeling domain)


Development and assessment of traffic-related emission abatement measures for the Madrid city (Spain)

0

50

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0 10 20 30 40 50 60 70 80

Annual mean NO2 concentration (µg/m3)

19th

hig

hest

hou

rly N

O2 c

once

ntra

tion

(µ

g/m

3 )

0

50

100

150

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250

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400

0 10 20 30 40 50 60 70 80


19th

hig

hest

hou

rly N

O2 c

once

ntra

tion

(µ

g/m

3 )

6

Observed NO2 values (corresponding to the annual and hourly NO2 limit values defined in the European AQ Directive) in the Madrid air quality monitoring network for the years 2010-2013

0

50

100

150

200

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300

350

400

0 10 20 30 40 50 60 70 80

Annual mean NO2 concentration (µg/m 3)

19th

hig

hest

hou

rly N

O2 c

once

ntra

tion

(µ

g/m

3 )

0

50

100

150

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250

300

350

400

0 10 20 30 40 50 60 70 80


19th

hig

hest

hou

rly N

O2 c

once

ntra

tion

(µ

g/m

3 )

Traffic stations Urban background stations Suburban background stations

2010

2012

2011

2013



• According to the simulations performed, compliance may be expected by the endof 2014

• Although:- Additional microscale measures (and modelling) for particular points are

needed- Additional, temporal measures to be applied during high-pollution

episodes must be considered and assessed

• The effect of road trafficaccess restriction undera 10-day high pollutionepisode to the citycentre are modelled anddiscussed in this work



2. Methodology

Air quality modelling system

Meteorological model

Emission model

Chemcal-Transport model

WRF

SMOKE

CMAQ

Terrain & land use

data

Met data (gridded, obs.)

Emission Inventories

Ancillary information:-Temporal allocation-Spatial allocation-Chemical speciation

Large Point Source

parameters

Initial conditions

Boundary conditions

Photolysis rates

ConcentrationDepositionVisibility



• Four nested domains canconsistently describe air pollutionprocesses from continental tourban scale

• Suitable to estimatecontributions from differentgeographic areas (international,national, regional and local)

A

D

D1

D2

D3

D4



• The system is able to depict urban background levels (e.g. NO2)

NO2 uncertainty (MRDE)

Hourly VL = 23,7 %

Annual VL = 22,4 %

Relative Directive Error (RDE) Directive 2008/50/EC

*

*

0

40

80

120

160

200

240

280

320

0 40 80 120 160 200 240 280 320

Concentración observada NO2 (ug/m 3)

Con

cent

raci

ón s

imul

ada

NO

2 (ug

/m3 )

C5

M = 29,5 μg/m3

O = 28,3 μg/m3

0

40

80

120

160

200

240

280

320

0 40 80 120 160 200 240 280 320


Con

cent

raci

ón s

imul

ada

NO

2 (ug

/m3 )

C5

M = 29,5 μg/m3M = 29,5 μg/m3

O = 28,3 μg/m3O = 28,3 μg/m3

0

40

80

120

160

200

240

280

320

0 40 80 120 160 200 240 280 320


Con

cent

raci

ón s

imul

ada

NO

2 (ug

/m3 )

A2

M = 34,8 μg/m3

O = 37,4 μg/m3

0

40

80

120

160

200

240

280

320

0 40 80 120 160 200 240 280 320


Con

cent

raci

ón s

imul

ada

NO

2 (ug

/m3 )

A2

M = 34,8 μg/m3M = 34,8 μg/m3

O = 37,4 μg/m3O = 37,4 μg/m3

• Acceptableperformance

• (MB = -2.2 μg/m3;r = 0.63; MFB = -14.1%...)



v. 4.10

Emission modelling

- 1h intensity and speed from the traffic model

- Zone-specific fleet composition and age from field campaigns

• Integration with the regional traffic model (TDM) for emission computation atlink level (15 000 aproximately)

Borge et al., 2012 (AE)

Emission modelling



• A 10-day period with high stability and low ventilation (winter) was selected,typical of high-pollution episodes (2007 meteorology)

• Restriction measures to be applied inside M30 (ring road)• Only for working days

Calle 30

50,6 km2

Temporal and spatial scope of traffic restrictions

• Reference scenario =2014 (expected situationfrom the Madrid AQP)

• Same initial and boundaryconditions and emissionsfor non-traffic sources(corresponding period of2014) for all scenarios



A - 20 % reduction of passenger carsB - 20 % reduction of passenger cars + restrictions for taxisC - 50 % reduction of passenger carsD - 50 % reduction of passenger cars + restrictions for taxis

13

3. Scenarios

• In a first stage 4 scenarios were considered:

-

+Restriction

level

• None of these restrictions apply to residents, emergency and public servicevehicles, duty vehicles, etc.

• An additional, more restrictive scenario was considered in a second stage:

E - 50 % reduction of passenger cars (including residents) + restrictions for taxis



4. ResultsScenarios A-D

• Emission summary



• These measures mayachieve improvements of 2-3 µg/m3 for the 20%reduction and up 6 µg/m3

for the 50% reductionscenario

• Roughly 7% decrease in theinnermost area for the mostrestrictive scenario

Decrease of average NO2 (µg/m3) in the 10-day period

• Air quality summary



• Concentration peaks may bereduced in the central areaof Madrid by 5-7 % (up to 12ug/m3) under the mostrestrictive scenario

• The effect of taxi restrictionsis broadly 1 ug/m3

Decrease of maximum 1-h NO2(µg/m3) in the 10-day period




• Analysis of concentration variations in time

A B C D

Mean concentration

by hour

Maximum concentration

by hour

Daily means

Daily 1-h maximum

concentration

Weekend



• Global emission reduction of nearly 8% in themodelling domain

• Strong emission reduction inside M-30 (despitemobility reduction an increase of 10 km/h inaverage speed is expected)

• Slight increase of NOX emissions in the ring road(3,3%) due to traffic redistribution

• Very small increase of distance travelled outsideM-30 and decrease of average speed (< 1 km/h)

Scenario E • Emission summary




• Average decrease of 12% inaverage NO2 concentrationwithin M-30

• Maximum reductions up to17 µg/m3 (Castellana area)

NO2 ( µg/m3 )

Decrease of average NO2 (µg/m3) in the 10-day period

E

Base E




• Peak concentration values vary ina similar percentage

• Reductions between 10 and 25µg/m3 inside M-30

• Small increments in particularspots outside M-30

E

Decrease of maximum 1-h NO2(µg/m3) in the 10-day period

Base E



• The effect decreasesstrongly with distance andbecomes highly dependenton wind patterns

• NO2 reductions growslowly in time but the effectceases to exist soon afterthe restriction is removed

1

2

3



5. Conclusions• Road traffic is the main responsible of air quality issues in Madrid

• Improving air quality with temporal measures under unfavourablemeteorological conditions is very hard

• Temporal traffic restrictions may help to avoid very high pollution levels, andtherefore hourly NO2 limit value exceedances, but only if strong measuresare applied in relatively large areas of the city

• Significant improvements in the city centre (reductions of 10-15 µg/m3 and15-25 µg/m3 for average and maximum NO2 concentration respectively) canbe achieved by applying a 50% restriction to passenger cars inside M-30,including residents in that area

• A minimum of 2-3 days of application is needed

• The effect of the restriction measures diminishes rapidly with distance, sothe reduction in the city outskirts may be negligible depending onmeteorological conditions



THANK YOU FOR YOUR ATTENTION!

Laboratory of Environmental Modelling. Technical University of Madrid (UPM)

[email protected]

• The Madrid City Councilprovided the traffic modeloutputs and funded this study.

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