U. Shankar1, B. Henderson2, S. Arunachalam1,

Z. Adelman1, N. Davis1, L. Ran1, E. Adams1, M. Barna3, and

M. Rodriguez3

8th Annual CMAS Conference

Chapel Hill, NC, October 19-21, 20091 UNC – Institute for the Environment

2 UNC Department of Environmental Sciences and Engineering

3 National Park Service

● RoMANS Field Campaign Overview● Context for Modeling Study● Model Setup● Current Results ● Conclusions● Next Steps

● Goal: To reduce deleterious effects on sensitive ecosystems due to atmospheric sulfur and nitrogen compounds

●Current estimate of inorganic N wet dep + dry dep of HNO3, NO3 and NH4 ≈ 4 kg/ha/yr

●20-fold increase since Western pre-industrial values● Objectives

● Identify S/N mix, ambient and deposited, on both sides of Continental Divide

● Identify important sources and transport pathways within and outside Colorado responsible for the S/N in Rocky Mountain National Park

● Identify relative contributions of different source types within Colorado to S/N species observed

● Observation period was aimed at capturing the seasonality in meteorology, and understanding S/N source contributions and chemistry

●Spring 2006: March 25 – April 30 (season for upslope, synoptic storms)

●Summer 2006: July 6 – August 12 (convective precip)

● Measurements at high temporal frequency to resolve changes in pollutant transport patterns and identify source types

RoMANS Measurements- Chemistry

Measured daily at 8 sites in spring, 6 sites in summer, and sub-hourly at core site, collocated w/ IMPROVE monitor; PM size measured at core site

Gore Pass

Lyons CrestCore Site 10-m Tower

Larimer CountyJackson County

Grand County Boulder County

Routt County

Wyoming

Colorado

Meteorology Monitoring Locations - ROMANS Study

Radar Profiler

Granby Sodar

Distances from Core Site:

to Estes Park Radar Profiler = 12 Km to Lyons = 24 Km

to Granby SODAR = 37 Km

to Gore Pass = 86 Km

Measured winds, precip, temperature, RH and light scattering

● Initial modeling of RoMANS by NPS using CAMx found severe underprediction of (gas and particulate) ammonia● Suspected emissions, dry dep of NH3

● Under a NASA ROSES UNC needed a demo application of the pyPA tool soon that it would port to VIEWS (End users: WRAP, NPS, …)

● Opportunity for a diagnostic evaluation of CMAQ against RoMANS and an inter-model comparison

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

ALVC BEME BRUS DINO GOPA GRAN LYCR ROMO SPRI TICR

Site

Me

an

Fra

ctio

na

l Err

or

Spring

Summer

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

ALVC BEME BRUS DINO GOPA GRAN LYCR ROMO SPRI TICR

Site

Mea

n Fr

actio

nal B

ias

Spring

Summer

NH4 Mean Fractional Error NH4 Mean Fractional Bias

CMAQ Simulation Setup ● Nested runs at

36- , 12- and 4-km ● 19 vertical levels ● CMAQ v4.7: CB05

w/ aero5 and Cl ●BCs from GEOS-Chem for ConUS domain●Soil NH3 correction to 2002 RPO EI

Initial focus of analyses is high wet dep event during strong upslope flow April 23-25 ’06

CMAQ Spring ’06: Inorganic PMat 12-km

ConclusionsPreliminary results indicate that CMAQ is

underbiased w.r.t. observations in both oxidized and reduced PM nitrate constituents and comparable to that in CAMx

The % mean bias is somewhat lower for ammonium than for nitrate

The agreement is better in the daily data (secondary and satellite sites) than in the sub-hourly (core site)

Next StepsCompare NH3 and HNO3 concentrations and

deposition amounts against observed concentrations, depositions and met data

Compare against satellite data of NO2, AOD

Run pyPACompare with CAMx pyPA results to identify

the processes contributing to the biases in each model

AcknowledgementsNASA Grant # NNX08AL28G