Transport and Chemistry Modeling in the Colorado Northern Front Range Metropolitan Area 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 and the FRAPPÉ and DISCOVER-AQ Science Teams .
FRAPPÉ and DISCOVER-AQ 15 July – 18 August 2014 PI: James Crawford PIs: Gabriele Pfister and Frank Flocke NASA Langley National Center for Atmospheric Research (NCAR) Funding Sources FRAPPÉ: State of Colorado / CDPHE The presented analysis has National Science Foundation (NSF) been funded by CDPHE DISCOVER-AQ: NASA Others: NOAA, GO 3 Project, NPS, EPA .
FRAPPÉ and DISCOVER-AQ The Front Range is an 8-hour Ozone NAAQS Non-Attainment Area W hat and w here are the relevant o sources? How do these emissions get o transported? How do they get chemically processed? o How m uch pollution com es into o Colorado? Which are the best ways to improve air o quality? .
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 .
Meteorological Evaluation Extensive Evaluation of modeled winds, temperature, rel. hum., PBL, and solar radiation with surface, aircraft, and sonde measurements. • 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. .
Emission evaluation strategy • 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 … - 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 .
Emission evaluation strategy Mobile Emissions OnG Emissions .
Emissions NO X A Priori (S0) NO X Posteriori (S05) NO X C-130 10-17LT < 1km agl Posteriori A Priori Ethyne • 2 Traffic outside Denver• 2 NO x • 2 VOCs• 2 (not ethane) .
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. .
Average Ozone MDA8 FRAPPÉ Average Posteriori Ozone MDA8 .
Zero-Out Scenarios FRAPPÉ Average Posteriori Ozone MDA8 NFRMA Anthropogenic Emission Contribution • Average 15-20ppb • On high ozone days 20-30 ppb • Maxima up to 40 ppb (28 July) .
Zero-Out Scenarios 28 July Posteriori Ozone MDA8 Anthropogenic Emission Contribution • Average 15-20ppb • On high ozone days 20-30 ppb • Maxima up to 40 ppb (28 July) .
Zero-Out Scenarios 3 August Posteriori Ozone MDA8 Anthropogenic Emission Contribution • Average 15-20ppb • On high ozone days 20-30 ppb • Maxima up to 40 ppb (28 July) .
Zero-Out Scenarios FRAPPÉ Mobile Contribution O&G Contribution Average Industrial Contribution CEM Contribution .
Zero-Out Scenarios 28 July Mobile Contribution O&G Contribution Industrial Contribution CEM Contribution .
Zero-Out Scenarios 3 August Mobile Contribution O&G Contribution Industrial Contribution CEM Contribution .
Box Model - Methodology Base-case calculated C-130 ozone production rates and Measurements ozone concentrations Aircraft Samples Difference indicates Relative emission emission sector Factors (S0.5) BOX Model contribution to (NCAR / U. Munich) ozone produced Steady State Model (NASA LaRC* ) Measurements Zero-out-case calculated adjusted / reduced ozone production rates and by emission sector ozone concentrations * Jason Schroeder, NASA Langley R.C. .
Box Model - Results Weld County : Oil and Gas emission dominated Denver : Mobile emission dominated Reduction of ~ 14 ppb of maximum Reduction of ~ 16 ppb of maximum ozone with O&G emissions removed ozone with mobile emissions removed .
Steady-State Box Model - Results Weld County : Oil and Gas emission dominated West Denver metro : Mobile/ Industrial O&G emissions are Mobile and industrial emissions responsible for more than contribute equally to ozone production 80% of ozone production in in the West Denver Metro area Weld County .
Steady-State- and Box Model - Results Commerce City : EGU emissions Commerce City : Industrial emissions EGU NOx emissions titrate Industrial emissions are the major ozone and slow production contribution to ozone production close to Commerce City downwind of Commerce City .
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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