CFD Modeling of Reactive Pollutants in an Urban Street Canyon using Different Chemical Mechanisms

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Amos Oliver
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Mechanisms B Sanchez a,b, JL Santiago a, A

for Energy, Environment and Technology (CIEMAT),

transport (INECO), Madrid, Spain c GAIASENS

1 CFD Modeling of Reactive Pollutants in an Urban Street Canyon using Different Chemical Mechanisms B Sanchez a,b, JL Santiago a, A Martilli a, M Palacios a, F Kirchner c a Center for Energy, Environment and Technology (CIEMAT), Madrid, Spain b Engineering and Economy of transport (INECO), Madrid, Spain c GAIASENS Technologies. Sarl, Switzerland beatriz.sanchez@externos.ciemat.es

Introduction At microscale the atmosphere and urban distributions interaction generates a complex flow and heterogeneous dispersion of pollutants within the canopy An accurate understanding of Urban

2 Introduction At microscale the atmosphere and urban distributions interaction generates a complex flow and heterogeneous dispersion of pollutants within the canopy An accurate understanding of Urban Air Quality requires considering a coupled behavior between dispersion of reactive pollutants and atmospheric dynamics Urban Air Pollution Traffic emissions VOCs NO NO 2 - Nitrogen Oxide (NO) - Nitrogen dioxide (NO 2 ) - Volatile Organic Compounds (VOCs) 2

Limitations In a real and complex geometry, the required computational time is large Implementing chemical reactions in a CFD model increase the CPU time considerably due to the coupling of pollutant

3 Limitations In a real and complex geometry, the required computational time is large Implementing chemical reactions in a CFD model increase the CPU time considerably due to the coupling of pollutant transport equations Objectives To simulate the pollutants dispersion considering chemistry: To reproduce reactive pollutant distribution using the simplest chemical mechanism minimizing CPU time Analyze the conditions in which the implementation of a complex chemical mechanism is necessary 3

Structure To model in 2D and 3D idealized urban geometries: The chemical and dynamic coupling under different chemical approaches: (a) Passive tracer (non-reactive) (b) NOx-O 3 photostationary state

4 Structure To model in 2D and 3D idealized urban geometries: The chemical and dynamic coupling under different chemical approaches: (a) Passive tracer (non-reactive) (b) NOx-O 3 photostationary state (PSS) (c) Complex chemical mechanism (CCM) Evaluation of the influence of atmospheric parameters (wind speed and ozone concentration) Quantify the variation on NO and NO 2 concentration with the use of chemical mechanism 4

Chemical Mechanisms Passive Tracer Considering NO and NO 2 non-reactive Photostationary State Complex Chemical Mechanism 23 chemical species 25 chemical reactions

5 Chemical Mechanisms Passive Tracer Considering NO and NO 2 non-reactive Photostationary State Complex Chemical Mechanism 23 chemical species 25 chemical reactions Due to the limitation of CPU time, CCM has been reduced based on Regional Atmospheric Chemistry Mechanism (RACM) using CHEMATA program software (Kirchner, 2005) 5

6 Study scenarios Ozone Geometry Wind Speed O 3 = 10 ppb O 3 = 40 ppb 2D 3D Passive tracer (non-reactive) NOx-O 3 photostationary state (PSS) Complex chemical mechanism (CCM) u z = 2H = 2 m s 1 u z = 2H = 4 m s 1 Different ratios of VOCsto-NOx emission: VOCs/NOx=1/5 VOCs/NOx=1/2 6

chemical species Computational domains 2D-geometry: Street-Canyon

7 CFD Model description Reynolds-averaged Navier-Stokes (RANS) equations with a k-ε turbulence model Transport equations of chemical species Computational domains 2D-geometry: Street-Canyon 24x40x64 m 3D-geometry: Staggered Array of cubes: 64x64x64 m λ p =

Simulation Set up Boundary conditions for momentum

y-direction zero gradient boundary conditions

2D-Geometry P x = ρ u τ 2 4H 3D-Geometry u τ :

8 Simulation Set up Boundary conditions for momentum equations Simulating an infinite number of streets y-direction zero gradient boundary conditions x-direction Periodic Conditions: Flow field: 2D-Geometry P x = ρ u τ 2 4H 3D-Geometry u τ : Reference velocity H: Buildings height u τ = 0.45 m s 1 u τ = m s 1 8

9 Simulation Set up Traffic Emissions Located at the bottom NOx fixed emissions: S NO = 112 μg m 1 s 1 S NO2 = 17 μg m 1 s 1 VOCs emissions For all emissions cases Complex Chemical Mechanism VOCs-to-NOx emissions : VOCs/NOx = 1/5 VOCs/NOx = 1/2 (CCM5) (CCM2) 9

Simulation Set up Top Conditions Constant concentration at the top Important role within the canyon VOCs concentration at the top change with emission ratio O 3 is computed using

10 Simulation Set up Top Conditions Constant concentration at the top Important role within the canyon VOCs concentration at the top change with emission ratio O 3 is computed using photostationary equilibrium and is dependent on zenith angle (θ) θ = 45 θ = 78 θ NO NO2 16 ppb 35 ppb J NO2 = A exp B/cos(θ) O 3 = J NO 2 NO 2 k NO (A and B are constant) O 3 = 40 ppb O 3 = 10 ppb 10

11 Evaluation of Atmospheric Parameters Study scenarios Ozone Geometry Wind Speed O 3 = 10 ppb (Low O 3 ) O 3 = 40 ppb (High O 3 ) 2D 3D Passive tracer (non-reactive) (P) NOx-O 3 photostationary state (PSS) Complex chemical mechanism (CCM) u z = 2H = 2 m s 1 (Ut0225) u z = 2H = 4 m s 1 VOCs/NOx=1/5 VOCs/NOx=1/2 (Ut045) VOCs-to-NOx emission (CCM5) (CCM2) 11

12 Evaluation of Atmospheric Parameters In order to compare the scenarios, the concentration is normalized: C norm = C u τ W Q C norm = C u 2 τ A Em Q W: Street width L: Street length Q: Source emission rate μg m 1 s 1 (Street Canyon) (Staggered Array of cubes) The difference with respect to Passive tracer is quantify using: δc (%) = C norm C norm (P) C norm (P)

13 Evaluation of Atmospheric Parameters Study scenarios Geometry Wind Speed 2D 3D Passive tracer (non-reactive) (P) NOx-O 3 photostationary state (PSS) Complex chemical mechanism (CCM) u z = 2H = 2 m s 1 (Ut0225) u z = 2H = 4 m s 1 VOCs/NOx=1/5 VOCs/NOx=1/2 (Ut045) VOCs-to-NOx emission (CCM5) (CCM2) 13

14 Wind Speed δc (%) = C norm C norm (P) C norm (P) 100 δ[no] PSS CCM5 CCM2 δc Ut045 > δc Ut0225 Bigger differences with higher VOCs emissions Ut045 C norm Ut0225 δc (%)

15 Wind Speed δ[no] C norm More ventilation implies less differences between chemical mechanisms PSS CCM5 CCM2 Ut045 Ut0225 δc (%) = C norm C norm (P) C norm (P) 100 δc (%) 15

16 Wind Speed δ[no 2 ] δc (%) = C norm C norm (P) C norm (P) PSS CCM5 CCM2 100 δc Ut045 > δc Ut0225 Differences between all chemical systems Ut045 C norm Ut0225 δc (%) 16

17 Wind Speed C norm δ[no2] PSS CCM5 CCM2 Ut045 Ut0225 δc (%) = C norm C norm (P) C norm (P) 100 δc (%) 17

18 Wind Speed Vertical profiles Horizontal spatial averaged of [NO] N and [NO 2 ] N δc Ut045 > δc Ut0225 Lower velocity implies more differences between chemical systems (solid line): Ut045 (dashed line): Ut0225 C norm = C u τ W Q 2D Geometry C norm = C u τ A 2 Em Q 3D Geometry 18

19 Evaluation of Atmospheric Parameters Study scenarios Ozone Geometry O 3 = 10 ppb (Low O 3 ) O 3 = 40 ppb (High O 3 ) 2D 3D Passive tracer (non-reactive) (P) NOx-O 3 photostationary state (PSS) Complex chemical mechanism (CCM) VOCs-to-NOx emission VOCs/NOx=1/5 VOCs/NOx=1/2 (CCM5) (CCM2) 19

20 Ozone δ[no] δc (%) = C norm C norm (P) C norm (P) PSS CCM5 CCM2 100 δc High O 3 > δc Low O 3 Differences between all chemical systems with high O 3 High O 3 C norm Low O 3 δc (%) 20

21 Ozone δc (%) = C norm C norm (P) C norm (P) 100 δ[no2] PSS CCM5 CCM2 δc High O 3 > δc Low O 3 Differences between all chemical systems with high O 3 High O 3 C norm Low O 3 δc (%) 21

22 Ozone Vertical profiles (solid line): High Ozone (dashed line): Low Ozone 2D Geometry 3D Geometry Horizontal spatial average of [NO] N and [NO 2 ] N The same vertical profile: PSS and CCM5 High O 3 : Importance of NOx/VOCs emission ( NO 2 N ) Low O 3 : the difference between chemical mechanism is insignificant 22

23 2D Geometry The average of δc below the canopy δc = C norm C norm (PS) C norm (PS) 23

24 Conclusions The biggest change in [NO] and [NO 2 ] is obtained between chemical mechanisms and tracer (non-reactive) In the case of high [O 3 ], the errors induced by the use of PSS are lager when the VOCs-to-NOx emission ratio increases Lower [NO] Higher [NO 2 ] With lower [O 3 ] at the top of the domain, [NO] and [NO 2 ] can be simulated by a simple or complex chemical mechanisms due to the differences between mechanisms are negligible. The influence of a complex chemical mechanism is slightly smaller in 3D than 2D geometry since major ventilation is produced within the street. 24

25 Thank you for your attention 25

26 26

27 Aditional Slides 27

28 Simulation Set up Top Conditions Constant concentration at the top NO 16 ppb NO2 35 ppb CO 200 ppb SO2 2 ppb Important role within the canyon Ozone concentration is computed using photostationary equilibrium and is dependent on zenith angle (θ) θ = 45 θ = 78 J NO2 = A exp B/cos(θ) O 3 = J NO 2 NO 2 k NO (A and B are constant) O 3 = 39.8 ppb O 3 = 10.2 ppb 28

29 Simulation Set up Top Conditions VOCs concentration at the top change with emission ratio Emission scenarios VOCs-to-NOx=1/5 VOCs-to-NOx=1/2 NO 16 ppb 16 ppb NO2 35 ppb 35 ppb VOCs 10.2 pbb 25.5 pbb Volumetric proportion within VOCs group are: OLE 28.6 % ARO 23.1 % ALK 38.6% ALD 4.0 % HCHO 5.6 % 29

chemical groups VOCs-to-NOx emissions : VOCs/NOx = 1/5 VOCs/NOx = 1/2 (in ppb) (in ppb)

30 Simulation Set up Traffic Emissions NOx fixed emissions: VOCs emissions S NO = 112 μg m 1 s 1 S NO2 = 17 μg m 1 s 1 Complex Chemical Mechanism Some VOCs are joined in specific chemical groups VOCs-to-NOx emissions : VOCs/NOx = 1/5 VOCs/NOx = 1/2 (in ppb) (in ppb) Volumetric proportion within VOCs group are: OLE 28.6 % ARO 23.1 % ALK 38.6% ALD 4.0 % HCHO 5.6 % 30

31 Validation CFD Model Validated previously with tunnel measurements in: o Papers Complex Chemical Mechanism Validated previously with results of box model Experimental measurements 31

Evaluation of a CFD modeling approach by means of an intensive experimental campaign using passive samplers in an urban area of Madrid

Evaluation of a CFD modeling approach by means of an intensive experimental campaign using passive samplers in an urban area of Madrid Jose Luis Santiago 1, Rafael Borge 2, Fernando Martin 1, David de