a multi-scale approach to evaluate the impact of urban

A multi-scale approach to evaluate the impact of urban mobility policies in emission and air quality in Barcelona

01/12/21 POLIS 21

Daniel Rodriguez Rey1, Marc Guevara1, Mari Paz Linares2, Josep Casanovas1,2, Jaime Benavides1, Jan Mateu1, Oriol Jorba1, Albert Soret1, Carlos Pérez García-Pando1,3.

(1) Barcelona Supercomputing Centre – Centro Nacional de Supercomputación (BSC-CNS) Earth Sciences division

(2) inLab FIB, Universitat Politècnica de Catalunya, Facultat d’Informàtica de Barcelona

(3) ICREA, Catalan Institution for Research and Advanced Studies, Barcelona, 08010, Spain

Motivation

• Urban air pollution as a major health issue

• Vehicle emissions as largest contributor to theregistered urban NO2 levels

• Traffic management strategies as the main foccus in Air Quality Plans

• Barcelona does not comply withthe EU AQD for NO2→

Application of Air Quality Plans

1

NO2 registered values in Barcelona

• Superblocks

Traffic Management Strategies applied in Barcelona

Aj. de Barcelona – “Pla d’Acció de l’àmbit de Superilles de St. Antoni.” December2017

• Tactical Urban Planning

NEW IMAGEWhat’s the impact of these measures on the emissions and the air quality levels?

• Low Emission Zone

2

Multi-Scale AQ modelling tool

VML: Traffic simulation

VML-HERMESv3

WRF – Meteorological model

CMAQ - Chemistry model

Hourly Origin-Destination matrix

COPERT V emission factors

Vehicle fleet compositionHourly Static Traffic

Assignment simulation

R-Line model

Urban geometry

HERMESv3 – Emission model

HERMESv3: Traffic emissions

CALIOPE

Hourly traffic volume and speed

per link

CALIOPE-UrbanTraffic emissions

Meteorological and chemical boundary conditions

Per road link

Per grid cell

Rodriguez-Rey et al. (2021) Benavides et al. (2019)

Pay et al. (2014)

Montero et al. (2018) Guevara et. Al (2020)

3

Eixample Station

Gràcia Station

1. Base Case- Pollution episodein November 2017

2. Tactical Urban Planning and Superblocks- 8 Superblocks- 32 km removed

TUP

Superblock

3. Low EmissionZone- Diesel vehicles < Euro 4 - Gasoline vehicles< Euro 3

4. Traffic demanddecrease of -25%

Scenarios performed

LEZ

4

Emission results (NOx)

Scenario 2

(1)

(2)

(3)

(4) (5)

TUP + SPBScenario 3

TUP + SPB + LEZ

Scenario 4

TUP + SPB + LEZ + Demand reduction

5

Superblocksrebound effect

Concentration results [NO2]

Scenario 2

CALIOPE-Urban CALIOPEStation Daily mean average Daily mean average

Scenario 2 (Diff. %)Gràcia -19% 0%Eixample -4% 0%Scenario 3 (Diff. %)Gràcia -29% -10%Eixample -15% -11%Scenario 4 (Diff. %)Gràcia -38% -18%Eixample -27% -18%

CALIOPE (1km x 1km) CALIOPE – Urban (20m x 20m)

TUP + SPBTUP + SPB + LEZ

Scenario 3

TUP + SPB + LEZ + Demand reduction

Scenario 4

6

Conclusions

• LEZ (-13%) and the demand reduction (-30%) are the measures with highest overall impact on emissions.

• Measures aiming at reducing vehicle space (SPB, TUP) show negligible effects on overall emissions (+0.1% NOx) but they imply important street gradient variations (+/-17% NOx).

• Expected daily mean NO2 reductions of -38% and -27% at the two traffic stations in the city under the most restrictive scenario (scenario 4).

• The mesoscale system miss the street-gradient variations and halves simulated NO2 peak reductions

7

Impact on media

El País, 23 Nov 2021

TV3, 23 Nov 2021

El Periódico, 23 Nov 2021

Europapress, 23 Nov 20218

01/12/2021

Daniel Rodríguez ReyBarcelona Supercomputing CenterEarth Sciences department

daniel.rodriguez@bsc.es

Thank you for your attention

Acknowledgements:Daniel Rodriguez-Rey work is funded with the grant BES-2016-078116 from the FPI program by the Spanish Ministry ofEconomy and Competitiveness. The authors acknowledgeCARNET-The Future Mobility Research HUB to allow the usageand work on the BCN-VML network, as well as PTV VISUM forthe traffic software license.The authors acknowledge the support from the Agencia Estatalde Investigación (AEI) as part of the VITALISE project (PID2019-108086RA-I00 / AEI /10.13039/501100011033)

FAC2: 0,77; MB: -12; RMSE: 33; r: 0,55FAC2: 0,76; MB: -16; RMSE: 36; r: 0,58

Evaluation of the system

Multi-Scale results: Base Case

a)

1km x 1km NOx

Emissions forCALIOPE

1km x 1km NO2

concentrationfrom CALIOPE

Street-level NOx

Emissions forCALIOPE-Urban

20m x 20m NO2

concentration fromCALIOPE-Urban

6/10

Model description and validation

• HERMESv3: Traffic Emissions• Estimation of link-level vehicle emissions

• Emission factors speed and meteorological dependent

• Exhaust (hot and cold-start) and non-exhaust emissions (wear, evaporative, resuspension)

• 491 vehicle categories considered

• Validated against RSD study.

Spee

d[K

m/h

]

• VML: Traffic simulation• Model Based on PTV-VISUM

• Traffic Flow calibration with 138 local loopdetectors

• RMSE: 35%; R2: 0,77; mean relative error: 27%

• Vehicle speed calibration with historicalTomTom GPS hourly speeds.

• 24-Hourly Static Traffic Assignment

Montero et al. (2018)Guevara et. Al (2020)