AIRPACT-3 & CMAQ Evaluation. Eric Smith, Pierre Wong, Ying Xie, Jen Hinds, Joe Vaughan, Tom Jobson, & Brian Lamb
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1 AIRPACT-3 & CMAQ Evaluation Eric Smith, Pierre Wong, Ying Xie, Jen Hinds, Joe Vaughan, Tom Jobson, & Brian Lamb
2 Recent evaluation efforts Wintertime PM2.5 evaluation (MM5- AIRPACT-3) (Eric Smith) MM5 to WRF conversion AIRPACT-3 evaluation (Pierre Wong) Photochemical indicator species and evaluation (Ying Xie)
3 Wintertime PM2.5 Evaluation Employ paired hourly PM2.5 observed and predicted concentrations from the automated AIRPACT-AIRNOW retrieval Model period approximately Jan-Feb, 2008 All reporting stations in the Airpact domain
4 Seattle Queen Anne Hill 1/15/2008 1/17/2008 Observed Values vs. Predicted Values of PM Observed Values of PM2.5 Predicted Values of PM PM2.5 (µg/m³) Model Run Hour (Starting at 12:00am on 1/15/2008)
5 Seattle Queen Anne Hill Model Run 1/15/2008 1/17/2008 Mean Bias PM Model Run Starting 1/15/2008 Model Run Starting 1/16/2008 Model Run Starting 1/17/ Mean Bias (µg/m³) Model Run Hour (Starting at 12:00am on 1/15/2008)
6 Tacoma- Port Area 1/15/2008 1/17/2008 Observed Values vs. Predicted Values of PM Observed Values of PM2.5 Predicted Values of PM PM2.5 (µg/m³) Model Run Hour (Starting at 12:00am on 1/15/2008)
7 Tacoma- Port Area Model Run 1/15/2008 1/17/2008 Mean Bias PM Model Run Starting 1/15/2008 Model Run Starting 1/16/2008 Model Run Starting 1/17/ Mean Bias (µg/m³) Model Run Hour (Starting at 12:00am on 1/15/2008)
8 Spokane- Ferry Street 1/15/2008 1/17/2008 Observed Values vs. Predicted Values of PM Observed Values of PM2.5 Predicted Values of PM PM2.5 (µg/m³) Model Run Hour (Starting at 12:00am on 1/15/2008)
9 Spokane- Ferry Street Model Run 1/15/2008 1/17/2008 Mean Bias PM Model Run Starting 1/15/2008 Model Run Starting 1/16/2008 Model Run Starting 1/17/2008 Mean Bias (µg/m³) Model Run Hour (Starting at 12:00am on 1/15/2008)
10 Winthrop 1/15/2008 1/17/2008 Observed Values vs. Predicted Values of PM Observed Values of PM2.5 Predicted Values of PM PM2.5 (µg/m³) Model Run Hour (Starting at 12:00am on 1/15/2008)
11 Average Hourly PM2.5 Mean Bias for January With all stations included, the model under-estimates PM2.5 hourly. This is likely due to the number of stations in less densely populated areas where under-estimation is common. Mean Bias (µg/m³) Short Range Mean Bias (predictions made in previous 24 hours) Mid-Range Mean Bias (predictions made in previous 48 hours) Long Range Mean Bias (predictions made in previous 65 hours) Hour of Day
12 Trends in Bias of Wintertime PM2.5 Forecasts Over-estimates of PM2.5 in densely populated areas (Seattle, Tacoma) Degree of over-estimation is less in mid-size cities (Spokane, Ellensburg) Under-estimates of PM2.5 in rural towns and areas (Winthrop, Darrington) Results for the 2 nd 24 hrs are often slightly better than for the most recent model run Bias on an hourly basis, all stations, is negative and largest at night Interpretation: overestimation in large cities grids are completely filled with sources/population, but EI is too high (or PBL/mixing too low) Underestimation in rural areas grids are much larger than source area, so sources are diluted, while monitors are actually within the source area
13 MM5 to WRF Conversion MM5 and WRF Airpact simulations were evaluated during a short overlap period in April, 2008 The two model runs were compared in terms of PM2.5 performance
14 Time Line of Meteorology System AP3-MM5 Time period for evaluation AP3-WRF Past 3/14/08 3/28/08 4/15/08 4/28/08 Now
15 Model Performance Predicted and Observed Mean Mean Bias PM2.5 [ug/m^3] MM5 - Predicted Wrf - Predicted AIRNow - Observed Overall Rural Area Small Town Urban Area PM2.5 [ug/m^3] MM5 vs Obs WRF vs Obs MM5 vs WRF Overall Rural Area Small Town Urban Area Population Population Correlation Coefficient (r) MM5 vs Obs WRF vs Obs MM5 vs WRF Overall Rural Area Small Town Urban Area PM2.5 [ug/m^3] Mean Error MM5 vs Obs WRF vs Obs MM5 vs WRF Overall Rural Area Small Town Urban Area Population Population
16 Model Evaluation by Population Mean (Overall) Mean (Rural Area) 120% 100% 80% 60% 40% 20% 0% -20% -40% MM5 vs Obs WRF vs Obs MM5 vswrf NMB NME FB FE 100% 50% 0% -50% -100% MM5 vs Obs WRF vs Obs MM5 vswrf NMB NME FB FE 100% 50% Mean (Small Town) MM5 vs Obs WRF vs Obs MM5 vswrf 200% 150% 100% Mean (Urban Area) MM5 vs Obs WRF vs Obs MM5 vs WRF 0% 50% NMB NME FB FE 0% -50% -50% NMB NME FB FE
17 Conclusion There was no significant difference between AP3- MM5 and AP3-WRF in overall model performance, although AP3-MM5 appeared to yield slightly better results. The AIRPACT-3 PM2.5 levels were underestimated in rural areas and overestimated in urban areas for both systems. Sources of error may be related to emission inventory and/or grid size
18
19 Evaluation of CMAQ model predicted O3-NOx-VOC sensitivity using field measurements from PNW2001 Objective Evaluate model predicted sensitivity and ozone chemistry by comparing to observed indicator values (O 3 /NO y ) Evaluate the emission inventory using observed compounds versus NO y ratios in the morning urban profile Compare observed and model predicted VOC reactivity. Two modeling scenarios : The standard scenario based on the original run from Rob Elleman (Elleman, 2007; Elleman et al., 2008) The reduced VOC scenario developed based on comparisons of observations with the emission inventory.
20 Observed and predicted O3, NOy
21 Observed and predicted photochemical indicator values (O 3 /NO y ) Base run Reduced VOC run
22 Emission inventory evaluation compound/no y reactivity weighted compound/no y
23 VOC reactivity comparison Morning Afternoon
24 Conclusion Photochemical indicator values: Model predicted O 3 /NO y ratios are closely related to VOC-NO x sensitive conditions. Peak O 3 is associated with VOC sensitive conditions, but not far from the transitional regime. The standard modeling scenario overpredicted peak O 3 and O 3 /NO y slope, indicating an overestimation of sensitivity to NO x, probably due to too much VOC in the emission inventory. The reduced VOC scenario resulted in better agreement with measurements in terms of peak O 3 as well as O 3 /NO y correlations. Emission inventory: Substantial overestimation of CO emissions by 80%, Overestimation of anthropogenic and the total VOC reactivity by 30% Large underpredictions of oxygenated compounds, ranging from a factor of 3 for formaldehyde to a factor of 30 for methanol. VOC reactivity: Anthropogenic VOC and CO are the major contributors to odd oxygen photochemistry in the morning urban profile, while CO and oxygenated compounds account for two thirds of the measured reactivity in the afternoon aged plume. The standard modeling scenario substantially overestimated the reactivity from CO. The reduced VOC scenario shows generally good agreement with observations of the relative contributions to the total VOC reactivity.
25 Ellensburg 1/15/2008 1/17/2008 Observed Values vs. Predicted Values of PM Observed Values of PM2.5 Predicted Values of PM PM2.5 (µg/m³) Model Run Hour (Starting at 12:00am on 1/15/2008)
26 Ellensburg Model Run 1/15/2008 1/17/2008 Mean Bias PM Model Run Starting 1/15/2008 Model Run Starting 1/16/2008 Model Run Starting 1/17/2008 Mean Bias (µg/m³) Model Run Hour (Starting at 12:00am on 1/15/2008)
27 Darrington 1/15/2008 1/17/2008 Observed Values vs. Predicted Values of PM Observed Values of PM2.5 Predicted Values of PM2.5 PM2.5 (µg/m³) Model Run Hour (Starting at 12:00am on 1/15/2008)
28 Darrington Model Run 1/15/2008 1/17/2008 Mean Bias PM Mean Bias (µg/m³) Model Run Starting 1/15/2008 Model Run Starting 1/16/2008 Model Run Starting 1/17/2008 Model Run Hour (Starting at 12:00am on 1/15/2008)
29 Winthrop Model Run 1/15/2008 1/17/2008 Mean Bias PM Model Run Starting 1/15/2008 Model Run Starting 1/16/2008 Model Run Starting 1/17/2008 Mean Bias (µg/m³) Model Run Hour (Starting at 12:00am on 1/15/2008)
30 Method Compare each set of model results to the observed results by using data from 82 sites Calculate model performance statistics for each pair of comparisons: AP3-MM5 versus AIRNow AP3-WRF versus AIRNow AP3-MM5 versus AP3-WRF
31 Map
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