1. 10th CMAS Conference, Chapel Hill, NC 2010 October 11-13
2006 Annual Operational Evaluation of the Environment Canada Air Quality Modelling System - AURAMS
Jack Chen, L.Boucher, S.Cousineau, D.Davignon, A.Duhamel, S.Gilbert, J.Racine, M.Sassi, M.Samaali
Air Quality Modelling Applications Section, Environment Canada, Montreal, QC
10th CMAS Conference, Chapel Hill, NC October 11-13

2. Outline Modelling platform for policy scenarios
Model configuration for 2006 annual simulation
Integrated model evaluation database
Preliminary annual model evaluation results
O3, PM2.5, NO2, Speciated PM2.5
Evaluation by geospatial attribute
Future work

3. Air Quality Modelling Platform
Comprehensive modelling platform for emission scenario simulations
Quantify air quality impacts across different regions and cities in Canada with respect to policy and regulatory proposals (e.g. Biodiesel fuel)
Results to be used for health impact assessments, and ecosystem impact analysis (e.g. acid deposition critical load)

4. AQ Modelling Framework
Model verification
Emission scenario comparisons
Health impact analysis
Ecosystem impact analysis
Canadian operational weather forecast model (GEM)
“off-line” sectional PM regional air-quality model (CTM)

5. AURAMS CTM / Emissions AURAMS v1.4 Emissions (SMOKE v2.4)
modified ADOM-II gas-phase and aqueous-phase chemical mechanism; ISORROPIA inorganic aerosol module
sectional representation of PM size distribution (12 bins from 0.01 to 41 µm diameter)
nine PM chemical components: SO4, NO3, NH4, EC, POM, SOM, CM, SS, H2O
Monthly varying O3 BCON with dynamic tropopause adjustment
Emissions (SMOKE v2.4)
Canada: 2006 NPRI
USA: 2005 NEI version 4 (EPA emissions clearinghouse)
Mexico: 1999 from (EPA emissions clearinghouse)
Biogenic with BEIS v3.09 integrated online

6. Domain and Simulation Setup
GEM meteorology (rotated lat/lon proj.): - variable resolution (575 x 641) - uniform core (432 x 565) at ~15km vertical layers
AURAMS CTM (polar stereo. proj.): - outer domain 45-km at 60oN - Inner domains: 22.5-km vertical layers
AURAMS run in 3 segments (1) to (2) to (3) to

7. Model Evaluation Database System
Goal: a systematic, comprehensive model evaluation tool that allows traceability, reproducibility and automation
Central storage of measured and modelled data in a relational database
Open source software:
PostgreSQL + PostGIS spatial extension
Visualization: Quantum GIS, Google Earth, or direct connection to DB
Dynamic data queries base on chemical species, time, location, obs. measurement methods, and any geospatial attributes

8. Measurement Data In DB
O3 – Hourly measurements from EC NAPS (194 stations) and EPA AQS (1147 stations)
NO2 – Hourly measurements from EC NAPS (136 stations) and from EPA AQS (399 stations)
PM2.5 – Hourly measurements from EC NAPS (173 stations) and from EPA AQS (520 stations)
Also hourly SO2, CO, NO, PM10
No 24-hr speciated PM2.5 yet
* For forecast model evaluation, the database is also ingesting realtime measurement feeds from AIRNOWa and from Canadian provinces. However, since these measurements were not validate, we only used results from EPA AQS and Canada NAPS.

9. Spatial Comparison – 45km domain
O3 Mean Bias (ppbv)
NO2 Mean Bias (ppbv)
% Station NO2
MB > 0
33%
MB < 0
67%
% Station O3
MB > 0
70%
MB < 0
30%
PM2.5 Mean Bias (μg/m3)
% Station PM2.5
MB > 0
20%
MB < 0
80%

10. Annual Evaluation – Hourly O3 (45km domain)
Similar NME in US abd Canada
Correlation: 0.5 – 0.7
Best NME in Spring, worse NME in Fall
CANADA
DJF
MAM
JJA
SON
YEAR
NMB
-16%
-9%
16%
24% 3%
NME
40%
32%
37%
47%
38% R
0.51
0.48
0.66
0.57
USA
DJF
MAM
JJA
SON
YEAR
NMB
-2% 3%
15%
19%
10%
NME
40%
29%
35%
41% R
0.57
0.63
0.68
0.65
avg. obs: 25 ppb
avg. obs: 35 ppb

11. Annual Evaluation – Hourly NO2 (45km domain)
Conc. variability decrease with increase temperature
Correlation: 0.5 – 0.6
Best NME in Winter, worse NME in Summer
CANADA
DJF
MAM
JJA
SON
YEAR
NMB
-35%
-32%
-20%
-28%
NME
57%
64%
66%
61%
62% R
0.48
0.47
0.49
USA
DJF
MAM
JJA
SON
YEAR
NMB
-24%
-18%
-6%
-15%
-16%
NME
51%
62%
69%
58%
59% R
0.59
0.56
0.51
0.58
avg. obs: 8 ppb
avg. obs: 10 ppb

12. Annual Evaluation – Hourly PM2.5 (45km domain)
Conc. variability increase with increase temperature
Poorer correlation: 0.1 – 0.4
Best NME in Summer, worse NME in Fall (Canada), Winter (US)
CANADA
DJF
MAM
JJA
SON
YEAR
NMB
-14%
-8%
-16% 9%
NME
77%
73%
65%
81% R
0.29
0.13
0.35
0.33
0.20
USA
DJF
MAM
JJA
SON
YEAR
NMB
-34%
-35%
-31%
-21%
NME
63%
57%
62%
61% R
0.39
0.34
0.40
0.35
0.38
avg. obs: 6 μg/m3
avg. obs: 8 μg/m3

13. Preliminary Speciated PM2.5 (22.5km domains)
Daily averaged measurements from EC NAPS
Sample once every two days
32-36 stations for PNO3, PSO4, PNH4
12 stations for PEC and POC
“No speciated PM2.5 from IMPROVE and EPA AQS”

14. Speciated PM2.5 – Ammonium (22.5km domains)
DJF
MAM
JJA
SON
YEAR N.
431
412
532
538
1868
Obs. Mean
1.0
0.8
0.7
Mod. Mean
0.6
0.9
NMB
-38%
-1%
17%
25% 0%
NME
57%
61%
66%
67%
62% R
0.70
0.73
0.68
0.64

15. Speciated PM2.5 – Sulfate (22.5km domains)
DJF
MAM
JJA
SON
YEAR N.
433
415
534
541
1923
Obs. Mean
1.7
1.8
2.4
1.9
Mod. Mean
0.8
1.0
2.2
1.3
1.4
NMB
-56%
-44%
-10%
-28%
-30%
NME
63%
56%
59%
55%
58% R
0.62
0.74
0.69
0.55
0.65

16. Speciated PM2.5 – Nitrate (22.5km domains)
DJF
MAM
JJA
SON
YEAR N.
409
366
455
509
1739
Obs. Mean
1.6
0.8
0.1
0.7
Mod. Mean
1.0
1.3
1.5
1.1
NMB
-40%
52%
457%
126%
43%
NME
67%
125%
511%
158%
122% R
0.63
0.55
0.23
0.54
0.43
High conc. variability in winter, model under-predicts but good correlation
Very poor performance as temperature increases
** There are known biases in NAPS PNO3 from sample loss

17. Speciated PM2.5 – Total EC2.5 (22.5km domains)
DJF
MAM
JJA
SON
YEAR N.
200
175
245
279
899
Obs. Mean
0.8
0.6
0.7
Mod. Mean
0.5
NMB
22%
32%
14%
59%
33%
NME
99%
100%
90%
138%
109% R
0.14
0.24
0.48
0.19
0.22

18. Speciated PM2.5 – Total OC2.5 (22.5km domains)
DJF
MAM
JJA
SON
YEAR N.
209
204
280
302
995
Obs. Mean
7.6
6.8
7.9
7.2
7.4
Mod. Mean
2.1
1.9
2.6
2.4
2.3
NMB
-73%
-67%
-69%
NME
75%
73%
67%
70%
71% R
0.10
0.28
0.47
0.37
0.26
Under prediction in all season, poor correlation
2 product SOA module, with constant yield
No semi volatile organic
Under represent biogenic SOA

19. Geospatial Evaluation by Population Density (22.5km domains)
Pop. Density (ppl./km2)
O3 Station
PM2.5 Station
NO2 Station
Urban
> 4,000 13 11
Suburban
4,000 – 1,000 51 50 43
Semirural
1,000 – 100 46 38
Rural
< 100 76 41

21. Current / Future work Continue with verification DB development
speciated PM2.5 from NAPS, IMPROVE, EPA AQS
additional measurements: wet/dry deposition (NADP, CAPMoN, CASTNet etc.)
Explore other geospatial criteria to examine measurement data and model performance (i.e. by distance from road network, LULC, etc.)
Emission scenario modelling with the model platform
Impacts of biodiesel fuels on air quality
Canadian AQ impacts from US Transport Rule

22. Thank you!