1. Measurement Needs for AQ Models
Paul Makar
Air Quality Research Branch, Meteorological Service of Canada, Environment Canada
Environment Environnement
Canada Canada

2. What kind of data have been used in the past (by MSC)
Points to be covered:
What kind of data have been used in the past (by MSC)
for model evaluation?
How have these data been used?
What are their limitations / benefits?
Some ideas on what would be useful for future work.
Environment Environnement
Canada Canada

3. AQ Model/Measurement Comparisons:
Three types of data for comparisons:
Laboratory / Process Studies
Monitoring Networks
Measurement Intensives
Environment Environnement
Canada Canada

4. Laboratory / Process Studies
Represent transition between “pure” and “applied” science.
Fundamental basis for every component of an AQ model.
Some examples:
Smog chamber
data for
gas-phase
mechanism
evaluation
Environment Environnement
Canada Canada

5. Laboratory / Process Studies
Represent transition between “pure” and “applied” science.
Fundamental basis for every component of an AQ model.
Slope = 0.46
R2 = 0.98
Slope = 0.64
R2 = 0.90
Slope = 0.85
R2 = 0.72
Some examples:
Comparison
of laboratory
water uptake
on organics to
absorptive
partitioning
model results.
Environment Environnement
Canada Canada

6. Laboratory / Process Studies Last example: 1-D column model of
Isoprene emissions
and chemistry.
Sensitivity of isoprene
emissions measurements
to chemical loss: 30%
underestimate in
emission possible.
Environment Environnement
Canada Canada

7. Laboratory and Process Studies are necessary for
improvements to science in regional AQ models!
Test the model components as stand-alone processes,
if possible.
(2) Test them in the complete AQ model and compare to
monitoring and measurement intensive data.
Environment Environnement
Canada Canada

8. Monitoring Networks:
Multiple locations across a wide spatial domain. 
Long time periods available. 
Limited chemical speciation. 
Limited time intervals (24 hr averages,
1 day in 3 or 1 day in 6) 
Evaluation of model over a wide range
of locations, hence over a wide range
of conditions.
The “depth” of the evaluation is limited
by the lack of detail (speciation and time interval).
Environment Environnement
Canada Canada

9. Example: An AURAMS model grid showing measurement
intensive (Pacific2001) and Monitoring sites:
Intensive
Monitoring
Networks
Very detailed data, but
only at a few sites,
Better representation
over domain, but less
detailed data.
Environment Environnement
Canada Canada

10. Useful for different things:
Monitoring
networks can
be used to get
scatterplots.
e.g. this shows that
the model is
over-predicting
particle nitrate – it
doesn’t tell you why.
Environment Environnement
Canada Canada

11. Measurement Intensives:
Highly speciated
High time-resolution
Data only available at
small number of sites.
Measurements are for
a limited total time.
e.g. measurement intensive data showed precursor
to particle nitrate was being over-predicted.
The point: if you want to determine the cause of an
inconsistency between model and measurements,
you need the highest amount of speciation and time
resolution possible.
Environment Environnement
Canada Canada

12. AQ Measurement - Model Interactions: Monitoring Networks:
New Directions for
AQ Measurement - Model Interactions:
Monitoring Networks:
Provide real-time data for AQ forecast evaluation and data assimilation. Continuous monitoring of some species at high time resolution starting.
Adjoint models under construction for data assimilation of air quality variables (to improve AQ model forecast skill).
Environment Environnement
Canada Canada

13. AQ Measurement - Model Interactions: Measurement Intensives:
New Directions for
AQ Measurement - Model Interactions:
Measurement Intensives:
On-site model-measurement links: AQ models are being used to drive measurement intensive programs. E.g. MSC contribution to ICARTT
MSC contribution: study on cloud processes and cloud chemistry.
Resulted from the research staff being asked, “What measurements could be made that would provide the most useful data for model improvement.”
AQ Model simulations used to help determine site location.
AQ Model forecasts to be run to determine aircraft flight plans.
Environment Environnement
Canada Canada

14. Some thoughts on “user needs”:
What suite of measurements are needed to support model evaluation?
How much money do you have to spend?
I want measurements of everything,
on 5 minute time intervals,
every 3 km,
over the entire planet.
Failing that…
The monitoring networks currently in place
across North America are sufficient to evaluate
an AQ model’s performance. (Operational Evaluation)
The monitoring networks currently in place
across North America are NOT sufficient to
evaluate the causes behind an AQ model’s
performance. (Diagnostic Evaluation)
Environment Environnement
Canada Canada

15. The monitoring networks currently in place across North America
are sufficient to evaluate an AQ model’s performance.
(Operational Evaluation)
Why?
Already measuring O3, PM2.5, PM10 mass at high time resolution,
PM speciation at low time resolution.
Sufficient to “evaluate” a forecast of these species.
Not sufficient to explain the reason for a poor forecast.
The monitoring networks currently in place across North America
are NOT sufficient to evaluate the causes behind an AQ model’s
performance.
Why?
High time resolution, simultaneous measurements of
PM, O3 and precursors are not available in the networks.
Need: speciated VOCs, HNO3, NH3, NOx, SO2 at high
time resolution, ditto for PM speciation.
Environment Environnement
Canada Canada

16. (1) Is the measurement location representative of the grid-square?
How do we treat point-measurement versus grid-prediction incommensurability?
(1) Is the measurement location representative of the grid-square?
This is a model grid-square.
0.85
Its concentration is valid at the point
in the centre. Assumed to represent
the entire square.
0.82
0.78
0.35
0.85
0.75
This is a measurement site.
0.61
0.65
Is its concentration representative
of the entire grid-square?
0.99
Make ten simultaneous measurements.
Calculate the slope and correlation
between the proposed site and the others.
If the correlation is high, the slope is 1, and the intercept is small:
the within-grid-square variability is low, and one site will be sufficient to characterize the grid square.
Some grid squares may be better than others!
Environment Environnement
Canada Canada

17. (2) Is the measurement location representative of the region?
Use the same strategy as above; how do the sites correlate across the region?
(3) Is the model grid-square representative of the larger region?
Use a similar strategy:
are the model results
at the grid-square
well correlated with others
in the surrounding region?
The point: some statistics
on measurements and
model results across
the domain will quantify
“incommensurability”.
Environment Environnement
Canada Canada

18. But, if you want to know why the control programs are working
What suite of measurements are needed to establish that we have met
the requirements of the control programs in terms of achieving the
target reductions in air concentrations?
Depends:
If the target reductions are for total PM, you measure total PM.
O O3
PM PM2.5
But, if you want to know why the control programs are working
or not, or if they’re working for the reasons you think they
are, you need to look at other species, more detailed
time resolution (Diagnostic level – wish list coming).
Environment Environnement
Canada Canada

19. How does measurement error affect model evaluation? Depends:
Measurement limitations or bias, if unreported, will result in a lot of
(possibly) wasted effort on model “improvements”.
In the absence of information to the contrary, the
measurements will be assumed to have no errors,
no bias, and to be an exact representation of reality.
What are model evaluation goals?
Operational (forecast): Is it giving the right result?
Diagnostic (Control strategy): Is it giving the right
result for the right reason?
Environment Environnement
Canada Canada

20. Wish list for Control Strategy / Diagnostic Model Development:
Process-Specific Studies at multiple sites with:
Size-resolved PM: SO4, NO3, NH4, Na, Cl, H, Ca, Si, OC, EC,
other elemental cations, anions, metals, at high time resolution.
VOCs:
(1) High time resolution on reactive O3 precursor classes.
(2) SOA precursor classes speciated (detailed speciation
for members of Aromatics, Alkenes, Monoterpenes, etc.).
(3) Oxygenated first and second level products for the above.
OC PM speciation:
PM measurements analyzed using New Directions methods
(see yesterday’s talks) to get Humic-Like Substances,
polymer chains, and their precursors identified.
Transport:
Aircraft as well as surface-based measurements,
Lidar for determining aerosol layering structure.
How well does the met. model simulate local
as well as synoptic meteorology?
Meteorology:
Environment Environnement
Canada Canada

21. Wish list for Process Studies:
Three studies that would help reduce uncertainties in AQ models:
Multi-species (VOC and organic) gas deposition flux and
deposition velocities.
(2) Hulis and polymer formation – lab and ambient, with
New Directions instrumentation.
(3) Detailed emissions speciation for the top 80% of mass
of primary PM, VOC, inorganic gas emissions.
Environment Environnement
Canada Canada

22. Fundamental process measurements are necessary for
Summary:
Fundamental process measurements are necessary for
model construction and evaluation of components.
Monitoring networks: good for forecasting/operational use
and identifying broad-scale problems, but still limited in
terms of time and speciation, hence limited for diagnostic
evaluation.
Measurement Intensives / diagnostic measurements:
necessary to work perform diagnostic evaluations for
control strategy runs.
Environment Environnement
Canada Canada