High-Resolution Air Quality Modelling in the Oil Sands

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1 High-Resolution Air Quality Modelling in the Oil Sands Paul Makar, Ayodeji Akingunola, Philip Cheung, Balbir Pabla, Junhua Zhang, Qiong Zheng, Mike Moran, George Marson, Craig Stroud and Heather Morrison Environment Canada

2 Satellite NO 2 Monitoring over the Oil Sands Region (video) Oils Sands Region Refineries Edmonton 4 Power Plants

3 Satellite Measurements of Change in SO 2 between 2005 and 2013 Absolute units Oil Sands Area Flin Flon Smelter Closure in 2011 Red Increase Blue - Decrease

4 High-Resolution Air Quality Model (GEM-MACH) Emission Inventory and Model Description: Joint Oil Sands Emissions Inventory Compilation Report, EC/AESRD (In prep.) Model Description and Evaluation: Delivery of Environment Canada GEM-MACH 2.5 km Annual Simulation Results to AESRD: Description of Model, Evaluation and Shapefiles (Feb. 10, 2015) Moran et al (2010) Particulate-matter forecasting with GEM-MACH15, a new Canadian air-quality forecast model. In: Steyn DG, Rao ST (eds) Air Pollution Modelling and Its Application, Springer, Dordrecht, pp Im et al. (2014), Evaluation of operational online-coupled regional air quality models over Europe and North America in the context of AQMEII phase 2. Part I: Ozone. Atmospheric Environment Im et al (2014), Evaluation of operational online-coupled regional air quality models over Europe and North America in the context of AQMEII phase 2. Part 2: Particulate Matter. Atmospheric Environment Makar et al (2014) Feedbacks between air pollution and weather, Part 1: Effects on weather. Atmospheric Environment, in press. Makar et al (2014) Feedbacks between Air Pollution and Weather, Part 2: Effects on Chemistry. Atmospheric Environment, in press. 4

5 Purpose To evaluate and apply a comprehensive, highresolution air quality forecast model to the oil sands region as a tool to quantify the relationship between air pollutant emissions, air quality and the condition of the environment 5

6 Integration Emissions Current Air Quality Air Quality Forecast Model Near Future Air Quality New Science Emission Scenarios Past and Future Air Quality NAPS CAPMoN 6

7 Integration Observations GEM-MACH 7

8 Cumulative Effects Assessment Environmental and human exposure is continuous in time and space 8

9 Science Questions What are the levels of and trends in ambient air pollutants and acid deposition in the region? Where should monitoring sites be located? What is the relative contribution of emissions from oil sands activities to air quality in the region? transport, transformation, fate 9

10 JOSM Implementation Plan Activities #1 Develop an improved emissions inventory for the oil sands region and use this to drive the model Set-up a high-resolution (2.5 km grid square) version of EC s air quality forecast model, GEM-MACH, for the oil sands region Evaluate the model 10

11 Air quality model output for SO 2 plume dispersion and deposition during 2013 AQ Oil Sands Measurement Intensive Campaign (video) Emissions: Oil Sands Region, 2010; Rest of Canada, 2006; U.S., 2010 Page #22 11

Air Quality Health Index output from the air quality model during the 2013 AQ Oil Sands Measurement Intensive Campaign (video) Very High Health Risk (10+) High Health Risk (7-10)

12 Air Quality Health Index output from the air quality model during the 2013 AQ Oil Sands Measurement Intensive Campaign (video) Very High Health Risk (10+) High Health Risk (7-10) Moderate Health Risk (4-6) Low Health Risk (1-3) Based on integration of levels of ozone, PM 2.5 and NO 2 Emissions: Oil Sands Region, 2010; Rest of Canada, 2006; U.S., 2010 Page #23 12

13 JOSM Implementation Plan Activities #2 Use the model to determine levels of and trends in ambient air pollutants and acid deposition in the region 13

14 Model-estimated total annual deposition of sulphur and nitrogen (wet and dry, eq/ha/yr) Total S Total N Total S+N + = September 2013 to October 2014 min. to max log 10 scale This information will be used to evaluate critical load exceedances for acid deposition for the region 14

15 JOSM Implementation Plan Activities #3 Support assessments to determine where air quality monitoring sites should be located 15

analyzed in time and space to determine how closely

16 Air Quality Network Assessment Methodology: Long-term air quality model output is statistically analyzed in time and space to determine how closely correlated the measurements would be at different locations 16

17 Investigate possible location of monitoring sites 17

18 Measurements at Pinehouse Lake and Flat Valley well represent regional air quality in the vicinity of Buffalo Narrows. Ex. Dry Particle Nitrate Deposition Green Line: Buffalo Narrows Blue: Pinehouse Lake Red: Flat Valley An additional regionally representative station at this location would not add a lot of new information about air quality in the region 18

19 Next Steps: JOSM Work Plan Continue to develop best-available model-ready emissions dataset for use in oil sands model simulations Use the model output to support assessments and future designs of air quality networks Comparative analyses of model output with comprehensive air quality datasets from the Oil Sands Summer Intensive Field Campaign Improve the model where necessary Use the model to support the assessment of cumulative environmental impacts of oil sands-related activities 19

20 Questions? 20

21 Appendix 21

5 (below) 10 to 30 µg/m 3 @ 4pm. Observed: 36 µg/m 3.

22 Characterization of air pollution events Event recorded by AQHI site in Fort McMurray. Model predicted PM 2.5 (below) 10 to 30 µg/m 4pm. Observed: 36 µg/m 3. AQHI comparison: Observed: 5 GEM-MACH10: 2 GEM-MACH2.5: 4 to 225

Impacts of Aerosol Direct/Indirect Effect Feedbacks and Forest Shading/Turbulence on Urban Air Quality Forecasts

Impacts of Aerosol Direct/Indirect Effect Feedbacks and Forest Shading/Turbulence on Urban Air Quality Forecasts Paul A. Makar, Ayodeji Akingunola, Craig Stroud, Junhua Zhang, Wanmin Gong, Michael D. Moran,