Some Thoughts on the Current State of Emissions-Based PM Air Quality Modelling Michael Moran Air Quality Research Branch Meteorological Service of Canada Toronto, Ontario, Canada EMEP Workshop on PM Measurement & Modeling New Orleans, Louisiana, U.S.A. 20-23 April 2004
Talk Outline Workshop objectives and emissions-based AQ modelling: How well are we doing? What new insights have we gained? What do we need to do better? What are some “low-hanging fruit”?
How well are we doing? Encouragingly well. Models are improving, and current models have some predictive skill for episodic and seasonal simulations. AURAMS examples
AURAMS Overview regional emissions processing system; A Unified Regional Air-quality Modelling System Episodic, Eulerian, regional, size-resolved, chemically-characterized particulate-matter (PM) modelling system intended initially for research and policy support “unified’ in that it considers multiple air pollutants and can be applied to multiple AQ issues (PM, O3, acid deposition) for integrated AQ management consists of three main components: regional emissions processing system; prognostic regional meteorological model; regional sectional PM air-quality model current PM resolution: 12 size bins (0.01-40.96 m) and 8 chemical components (SO4=, NO3-, NH4+, BC, OC, CM, SS, H2O) Slide 10.
Time Series, Feb. 7–14, 1998 PM2.5 PM2.5 PM2.5 O3
24-Hour PM2.5 Species Scatterplots: Feb. 7-14, 1998, IMPROVE & GAViM SO4 NH4 NO3
What are some new insights that we have gained to date? Atmospheric responses to emission reductions may vary by season These responses may also be significantly nonlinear
2020P - 2020B Scenario “Deltas” for SO2 and NOx Emission Reductions, July 1995 & Feb. 1998 Cases PM2.5 SO4 PM2.5 NO3 PM2.5 NH4 July 8-18 Feb. 7-15
Change in PM2.5 Nitrate Due to Reductions in SO2 and NOx Emissions July 8-18, 1995 Feb. 7-15, 1998
What do we need to do better? Everything. There is room for improvements related to: emissions meteorology PM process representations ambient measurements numerics
Iterative Improvement Process emissions, meteorology air-quality models ambient AQ measurements
Treatment of Emissions Treatment of primary PM emissions need PM speciation profiles need size disaggregation profiles for PM2.5 need better transport factors (AQ model?) need wind-blown dust & wildfires Treatment of NH3 emissions need monthly and diurnal variation need subgrid-scale removal
Some Less Certain AQ Process Representations cloud and precipitation properties condensable p-OC and SOA formation PM dry deposition PM cloud processing (how good is SO4?) subgrid-scale vertical cloud transport PM wet removal
A Few Evaluation Issues 1. Consideration of comprehensive data sets meteorological measurements PM mass, composition, size distribution gaseous co-pollutants deposition measurements optical measurements (visibility, optical depth) 2. Frequency (1/1 vs. 1/3 or 1/6 or 2/7)
What are some “low-hanging fruit”?
Inexpensive Non-Technical Actions to Improve Source- Based PM Modelling (1) Include a reading list in report from this workshop (list some papers and reports that are important and recent) Organize a focussed PM modelling workshop (current mtgs such as AMS-APM, AMS-AC, NATO-CCMS, AAAR, AGU, EGU are not focussed; NARSTO? EMEP? CMAS?)
Inexpensive Non-Technical Actions to Improve Source- Based PM Modelling (2) Expedite access to field study data (e.g., encourage early modelling participation) Describe model evaluation“good practice”: identify useful data sets, techniques, metrics Encourage model confidence-building initiatives, such as joint studies, detailed evaluations, model intercomparisons, collaborations with receptor models and data analysts, …
Inexpensive Non-Technical Actions to Improve Source- Based PM Modelling (3) Develop WMO GTS exchange code (BUFR?) for transmission of air concentration measurements Rely on evidence-based research prioritization instead of intuition-based or interest-based (e.g., model performance for different PM components) Build data “warehouses” for input data sets