A Forward and Adjoint Neighborhood Scale Air Quality Model

Eduardo P. OlaguerDirector, Air Quality Research

Houston Advanced Research Center

Moving knowledge to action.

Science and Policy Issues at Stake

• Nonlinear ozone chemistry near large sources may require very fine resolution to address.

• Coarse models may bias regulatory decisions by misrepresenting the efficacy of controls.

• Industrial point source emissions are uncertain by 1-2 orders of magnitude.

• Near source human exposure to ozone and air toxics may be large during emission events.

HARC Air Quality Model• Neighborhood scale 3D Eulerian chemistry transport

model customized for near source applications.• Parameterized clear sky photolysis rates.• Very high temporal (10-20 s) and spatial (100-400 m

horizontal, 50 m vertical) resolution.• Forward and inverse (adjoint) model.• Coded in MATLAB to facilitate adjoint model.• Documented in 3 peer-reviewed publications (Atmos.

Environ. and J. Air & Waste Manage. Assoc.).• Two manuscripts on chemical adjoint in review.

HARC Model Transport

• Piecewise Parabolic Method for advection• Explicit scheme for horizontal diffusion• Uniform horizontal diffusion coefficient (can

be adjusted by inverse model)• Semi-implicit (Crank Nicholson) scheme for

vertical diffusion• Height-dependent vertical diffusion coefficient

from similarity theory (3 stability classes)

HARC Chemical Mechanism• Total of 47 gas phase reactions (compared to 150 for

CB05 and 260 for SAPRC07)– Detailed mechanisms for HCHO and highly reactive VOCs (ethene,

propene, 1,3-butadiene, 1-butene, 2-butene, isobutene)– Truncated mechanisms for isoprene, toluene, xylenes– Less reactive (“background”) organics lumped together and assigned a

total OH reactivity (rBVOC), where BVOC + OH HO2 + XO2.

• Simplified chemical solver – Chemical equilibrium assumed for OH and HO2 (OK for NO > ~0.5 ppb)

– EBI scheme (Hertel et al., 1993) for NO-NO2-O3

– Euler backward scheme for longer lived species (HONO, HCHO, CO, 6 olefins, ISOP, TOL, XYL, RNO3)

Mixing ratios of OH (left) and HO2 (right) at 10:00 – 15:00 CST, 9/14/2006 for rBVOC=0 (black), rBVOC=observed (blue), and TRAMP measurements (red), where rBVOC=total OH reactivity of unresolved organic species.

Note: The HARC model performs similarly to standard mechanisms also compared against TRAMP data (Chen et al., 2012). As chemical interferences have been found in the Laser Induced Fluorescence (LIF) method used to measure HOx (Mao et al., 2012), the discrepancy between model predictions and true HOx concentrations are not as large as they appear.

Mixing ratios of O3, NO2, NO and olefin predicted by OZIPR model for the CB05 (black), SAPRC97 (red), and

HARC (blue) mechanisms, with an initial 100 ppb olefin plume. Initial CO and NOx set at 200 ppb and 10 ppb.

NOx + propene

NOx + ethene

NOx + ethene

NOx + propene

Ozone

NO

NO2

Olefin

NOx + propene

NOx + propene

NOx + ethene

NOx + ethene

Forward Modeling ofHouston Ship Channel Flare

• 10-hr flare release of >14,000 lbs of ethene• Nearest downwind monitor 12 km away• Simulation resolution: 200 m x 200 m

(horizontal) x 50 m (vertical) x 20 s (temporal)• Domain: 12 km x 12 km (horiz) x 1 km (vert)• Time period: 9:30 am – 12:30 am CST• Hourly varying uniform horizontal wind• Molar HCHO:CO = ~8% (TCEQ Flare Study)

200 m resolution

1 km resolution

No primary HCHO

Flare only

Flare + Routine

Flare + Routine

Observations

200 m resolution

200 m resolution

Inverse Modeling of TexAQS IIFlare Emission Event

• HCHO at Lynchburg Ferry (LF) peaked at 52 ppb on Sep 27, 2006 (Eom et al., 2008).

• HCHO peak occurred during an olefin flare accompanying an 18-day sequential shutdown of a petrochemical facility ~8 km upwind of LF.

• Performed 4Dvar inverse modeling of flare event emissions of CO, HCHO, olefins based on LF observations of NOx, O3, HCHO, olefins.

Horizontal Resolution: 400 mHorizontal Domain Size: 8 km × 8 km

(BC and met obs)

Inverse Model Assumptions• Annual mean routine point source emissions• Link-based mobile emissions from MOVES

courtesy of Houston Galveston Area Council• Inverse modeling for two cases of the HCHO

upwind boundary condition:– Control: 4 ppb (typical in Houston urban air)– Sensitivity: 31.5 ppb (max at HRM-3 monitor)

• Sensitivity run simulates transport of secondary HCHO from outside model domain

Inverse Modeling Results

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tion H

CH

O (

ppb)

LF observations

control

sensitivity run Inferred HCHO event emissions:

Control: 282 kg/hrSensitivity run: 239 kg/hr

Note:

This is about 50 times larger than flare HCHO emissions from routine operations inferred during the 2009 SHARP campaign (Wood et al., 2012).

Conclusion: Substantial event emissions of primary HCHO are required in addition to olefin emissions to explain LF observations.

Computer Aided Tomography (CAT) + DOAS

4.1 km 5.08 km5.15 km

70 m

300

m13

0 m

20 m

MoodyTower

LP-DOAS

DowntownHouston

LP-DOAS light paths

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3-hr forward model results with “true” parameter values

E = 10 g/sKh =13.2 m2/s

Neutral stability

Optimized:E = 9.3 g/sKh =16.2 m2/sCAT-4Dvar

reconstruction based on 2T90°

CAT reconstruction using Algebraic Reconstruction Technique and 2T90° DOAS configuration with 20 light rays.

Error of improved reconstruction

U=2 m/s

30 min assimilation window

Single point source

First Guess:E = 1 g/sKh =132 m2/s

Future Work• Link to micro-scale CFD or WRF LES model to

simulate air flow with realistic buildings.• Combine with chemical fingerprinting tools

(e.g., Positive Matrix Factorization).• Perform short-range (~2 km) CAT-DOAS for

reactive HAPs (e.g., toluene and xylenes) during BEE-TEX field study in Houston in 2014.

• Apply CAT-DOAS to longer-range (~10 km) measurements of HCHO, HONO, NO2, SO2, O3.