Page 1 An Integrated Measurement-Modeling Approach to Quantify Contribution of Washington Dulles...

An Integrated Measurement-Modeling Approach to Quantify Contribution of Washington Dulles Airport

Emissions to Local Air Quality

Saravanan Arunachalam

Institute of the EnvironmentUniversity of North Carolina at Chapel Hill

October 11-13, 20109th Annual CMAS User’s Conference, Chapel Hill, NC

Project Team

• N. Davis, B.H. Baek, D. Yang, U. Shankar, M. Omary, K. Talgo, G. Arora, A. Hanna, UNC Chapel Hill

• Brian Kim, ESA• Jawad Rachami, Wyle Labs• Roger Wayson, U.S. DOT Volpe Center• Steven Cliff and Yongjing Zhao, University of California at Davis• Phil Hopke, Clarkson University

Motivation

• Aviation activities release emissions of CO, NOx, VOC, SOx, PM2.5, and numerous hazardous air pollutants

• Aviation emissions vary in 4-D (in space and time) and undergo complex chemical transformation in atmosphere– Need to properly characterize emissions, their transformation and

atmospheric impacts • Compared to all other sources that impact air quality, aviation

emissions are usually small– For e.g. in the U.S., NOx from aviation contributes < 1% in 77% of counties, PM2.5

contributes < 1% in 94% of counties– However, in some counties, the airport contribution could be significant

• Limited research on relative contribution of airport emissions to ambient air quality

Statement of Objectives

Provide guidance for airport operators on effective tools and techniques for measuring airport contributions to ambient AQ

– Evaluate existing and potential monitoring strategies and forecasting techniques that airports can use to measure airport-related AQ impacts on local jurisdictions

– Identify gaps in existing models and model inputs, and identify research needed to fill gaps and improve the predictive capabilities of available models

– Provide detailed recommendations for implementing an optimal emissions monitoring and forecasting strategy, and guidance to airport operators on how to select and carry out that strategy.

Project Overview

• Washington Dulles International Airport (IAD) chosen after extensive screening process– 428,482 operations in 2007 (TAF, 2007)– Located in non-attainment area (8h O3 and PM25)– Willingness of airport authority to work with us– Strong seasonality– Less interference issues from non-airport sources, and Easy Access

• Conduct measurement campaigns for three seasons– Apr 2009 (Spring), Jan 2010 (Winter), July 2010 (Summer)

• Air quality modeling using – Source-oriented models (CMAQ and AERMOD)– Receptor-oriented models (PMF)

Pollutant Intensive Period (1 week)

Less-intensive Period (1 week)

Base station gas analyzers: SO2, NO/NO2/NOx, CO, O3

Continuous measurements

MiniVol Tedlar bag samples: SO2, NO/NO2/NOx, CO, O3

1-hr samples, 4/day at 5 locations

MiniVol PM filters: elemental composition, BC, NO3, SO4

24-hr integrated samples, once/day at 5 locations

24-hr integrated samples, once/day at 5 locations

RDI: size-segregated PM and elemental composition

3-hr integrated samples at 3 locations

Mobile lab gas analyzers: SO2, NO/NO2/NOx, CO, O3

Continuous measurements,approx. 2-3 sites


Mobile lab SMPS: PM sizedistributions



Mobile lab Summa canisters and cartridges: VOCs and Aldehydes

1-3-hr integrated samples, 3/day at 2-3 sites

1-3-hr integrated samples, 3/day at 2-3 sites

Monitoring Locations

Spring: April 2009 Winter and Summer: Jan, July 2010

Other Important Data Collected

• Meteorology Wind speed, direction, temperature, pressure and RH Downloaded National Weather Service Data

• Additional Needs Extensive Field Notes Pictures, Maps, Coordinates Airline Services Quality Performance (AQSP) Data Detailed Operations Data Enhanced Traffic Management System (ETMS) Data Data for Runway Usage / Flight Paths Background Concentrations From AIRNOW/AQS

Airport Operations Data

• Data derived from PASSUR/Radar • Daily runway use varies

Departures Arrivals

Comparison of PM from on-site measurements to AQS

Direct Comparison

Average Comparison

Multiscale Modeling System

12-km

4-km

CMAQ Modeling Domains

Modeling Tools

• Weather Research Forecast (WRF) Model Version 3.1– Used NCEP 40-km NAM analysis data for initialization, boundary conditions and

FDDA– Run for 2.5 day durations starting each day, to obtain 12-hour and 36-hour

forecasts• Emissions Dispersion and Modeling System (EDMS) Version 5.0

– Radar data used as primary inputs for commercial flight activity– Average statistics and/or general use assumptions for other airport sources

• SMOKE Version 2.6– Anthropogenic Emissions from NEI-2005 projected to 2009

• CMAQ Version 4.7– IC/BC from NCEP CMAQ simulations for ConUS at 12-km

• AERMOD

Evaluation against AIRNOW data: Apr 2009

Max 8h O3

24-hr Ave PM2.5

12-km 4-km

MB: -3.6NMB: -6.6NME: 10.1

MB: -4.5NMB: -7.9NME: 10.4

MB: 0.05NMB: 2.0NME: 26.4

MB: 1.6NMB: 17.7NME: 30.1

CMAQ Model Performance – April 2009

CMAQ evaluated against other gas-phase species (AQS) and STN- High error for SO2, and ASO4, ANO3 and TC

Comparison of CMAQ to Dulles Apr-2009 Data

NOx

O3

EC

PM2.5OC

SO4

Incremental AQ Contribution from Dulles Airport – Apr 2009

% DiffAerosol EC

Abs Diff PM2.5Abs DiffAerosol EC

% Diff PM2.5

Dulles airport contributes upto 40% of EC and 4% of PM2.5, compared to background

Average Elemental Size Distribution of RDI Samples

•178 RDI Samples from 3 sites•27 Chemical Elements by XRF•8 Size Fractions

Size resolved PM measurements from RDI

CMAQ predicts PM chemical components in 3 modes

Tools being developed to convert CMAQ’s modal size distribution to compare with 8 size bins measured

Ref: Liu and Bowman (2004)

Discussion

• Successful measurement campaign conducted for three different seasons at Washington Dulles airport– Air quality, meteorological and on-site flight activity data collected

• Near Real-time Meteorological and Air Quality forecast system developed at multiple resolutions of 12-km and 4-km for IAD– Model performance evaluated against both routine measurements from

AIRNOW/AQS and STN, and from on-site field measurements at Dulles– CMAQ performance for Apr-2009 marginally better than for Jan-2010– Additional evaluation ongoing using on-site measurements

• Airport contribution to local AQ being assessed using 3 approaches, and corroborated by on-site measurements– CMAQ and AERMOD modeling– Receptor modeling

Acknowledgements

• This project was conducted with funding from the Transportation Research Board (TRB) and developed under the Airport Cooperative Research Program (ACRP) Project 02-08

• We would like to thank the ACRP 02-08 panel for guidance and directions

Evaluation against AIRNOW data: Jan 2010

Max 8h O3

24-hr Ave PM2.5

12-km 4-km

MB: 3.8NMB: 13.9NME: 17.9

MB: 5.9NMB: 20.2NME: 21.0

MB: 1.9NMB: 17.9NME: 31.8

MB: 5.9NMB: 20.2NME: 21.0

CMAQ Model Performance – January 2010

CMAQ evaluated against other gas-phase species (AQS) and STN- High error for SO2, OC and TC

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