Transport and Chemistry Modeling in the Colorado Northern Front - - PowerPoint PPT Presentation

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Gabriele Pfister, Frank Flocke, Sojin Lee and Jason Schroeder*

Atmospheric Chemistry and Modeling Laboratory (ACOM) National Center for Atmospheric Research (NCAR) *NASA Langley Research Center

Transport and Chemistry Modeling in the Colorado Northern Front Range Metropolitan Area

and the FRAPPÉ and DISCOVER-AQ Science Teams

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FRAPPÉ and DISCOVER-AQ

Funding Sources

FRAPPÉ: State of Colorado / CDPHE National Science Foundation (NSF) DISCOVER-AQ: NASA Others: NOAA, GO3 Project, NPS, EPA

PIs: Gabriele Pfister and Frank Flocke

National Center for Atmospheric Research (NCAR)

PI: James Crawford

NASA Langley

15 July – 18 August 2014 The presented analysis has been funded by CDPHE

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FRAPPÉ and DISCOVER-AQ

The Front Range is an 8-hour Ozone NAAQS Non-Attainment Area

• W hat and w here are the relevant

sources?

• How do these emissions get

transported?

• How do they get chemically processed?
• How m uch pollution com es into

Colorado?

• Which are the best ways to improve air

quality?

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Model Simulations

W RFV3 .9 / CMAQ v5 .2 beta

• 2 domains: 12 km x 12 km & 4 km x 4km
• Setup comparable to Colorado SIP
• Nudging of Operational and FRAPPÉ observations
• Chemical mechanisms: CB6r2

A Priori

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Extensive Evaluation of modeled winds, temperature, rel. hum., PBL, and solar radiation with surface, aircraft, and sonde measurements.

Meteorological Evaluation

• WRF/ CMAQ represent the transport quite

well, considering the challenging topography but underestimates clouds.

• The PBL characteristics are overall well

simulated, but small uncertainties could potentially lead to large errors when comparing (specifically) surface trace gas emission species.

• Surface sites often represent very localized

patterns that cannot be resolved even ay 4 km grid spacing.

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• Compare measurements with model predicted mixing

ratios - but select days and time periods when models represent transport well.

• Estimate source contribution to each sample from

surrounding grid cells using wind direction and speed

• Evaluate absolute concentrations and emission ratio

predictions versus measured ratios.

• Adjust individual emission sectors, based on data

selection.

Emission evaluation strategy

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Emission evaluation strategy

• Identify grid boxes for 10-17 LT < 1km ag where

(1) The contribution of the evaluated emission sector (mobile, O&G) is at least 50% (2) Observed and modeled winds are from same sector (10-17 LT, < 1km ag)

• Compare individual samples with modeled concentrations

averaged over each set of grid boxes

• Compare measured and modeled Emission Ratios

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Emission evaluation strategy

Mobile Emissions OnG Emissions

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Emissions

NOX C-130

10-17LT < 1km agl

NOX A Priori (S0) NOX Posteriori (S05)

Ethyne• 2 Traffic outside Denver• 2 NOx• 2 VOCs• 2 (not ethane)

Posteriori A Priori

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NFRMA Emission Comparison

• Priori estimates are on the low end

compared to EPA 2011, 2014 or 2017.

• Posteriori is lower in NOx and VOC than

EPA 2011 but higher compared to EPA 2014 (10% for NOx and 30% for VOC)

• Our Posteriori Emissions present a

"conservative" estimate for VOC emissions from O&G.

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Average Ozone MDA8

Posteriori Ozone MDA8

FRAPPÉ Average

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Zero-Out Scenarios

NFRMA Anthropogenic Emission Contribution

• Average 15-20ppb
• On high ozone days 20-30 ppb
• Maxima up to 40 ppb (28 July)

FRAPPÉ Average

Posteriori Ozone MDA8

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Zero-Out Scenarios

Anthropogenic Emission Contribution

• Average 15-20ppb
• On high ozone days 20-30 ppb
• Maxima up to 40 ppb (28 July)

28 July

Posteriori Ozone MDA8

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Zero-Out Scenarios

Anthropogenic Emission Contribution

• Average 15-20ppb
• On high ozone days 20-30 ppb
• Maxima up to 40 ppb (28 July)

3 August

Posteriori Ozone MDA8

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Zero-Out Scenarios

O&G Contribution Mobile Contribution Industrial Contribution CEM Contribution

FRAPPÉ Average

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Zero-Out Scenarios

O&G Contribution Mobile Contribution Industrial Contribution CEM Contribution

28 July

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Zero-Out Scenarios

O&G Contribution Mobile Contribution Industrial Contribution CEM Contribution

3 August

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Box Model - Methodology

C-130 Measurements BOX Model (NCAR / U. Munich) Steady State Model (NASA LaRC* ) Measurements adjusted / reduced by emission sector Base-case calculated

• zone production rates and
• zone concentrations

Zero-out-case calculated

• zone production rates and
• zone concentrations

Relative emission Factors (S0.5) Difference indicates emission sector contribution to

• zone produced

* Jason Schroeder, NASA Langley R.C. Aircraft Samples

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Weld County: Oil and Gas emission dominated Denver: Mobile emission dominated

Box Model - Results

Reduction of ~ 14 ppb of maximum

• zone with O&G emissions removed

Reduction of ~ 16 ppb of maximum

• zone with mobile emissions removed

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Weld County: Oil and Gas emission dominated West Denver metro: Mobile/ Industrial

Steady-State Box Model - Results

O&G emissions are responsible for more than 80% of ozone production in Weld County Mobile and industrial emissions contribute equally to ozone production in the West Denver Metro area

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Commerce City: EGU emissions Commerce City: Industrial emissions

Steady-State- and Box Model - Results

EGU NOx emissions titrate

• zone and slow production

close to Commerce City Industrial emissions are the major contribution to ozone production downwind of Commerce City

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Summary

• We employed an extensive range of modeling tools to analyze the FRAPPÉ data
• WRF/ CMAQ represent the transport quite well, considering the challenging
• topography. Ozone is biased high due to WRF underestimating clouds.
• Significant adjustments were needed to reported emissions from activities related

to oil and gas extraction.

• No strong biases in CMAQ chemistry caused by simplified chemistry.*
• Box model and WRF/ CMAQ source contribution estimates are largely in

agreement.

• Ozone is efficiently produced in the summer throughout the NFRMA and

transported into the mountains and sometimes across the Continental Divide driven by local upslope meteorology.

• We identify O&G and mobile emissions as the major contributors to ozone

production in the NFRMA. O&G emissions dominate the northern NFRMA; mobile (and, to a lesser extend, industrial) emissions dominate the southern NFRMA.

• Repeated measurements, especially aircraft-based would be beneficial to monitor

success of emission regulations and the influence of rapid population growth in the NFRMA.

• Download the full Report through the FRAPPE Website:

https: / / www2.acom.ucar.edu/ frappe

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Questions ?

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Questions ?