Evaluation of several PM_2.5 forecast models using data collected during the ICARTT/NEAQS 2004 field study

Abstract

[1] Real-time forecasts of PM 2.5 aerosol mass from seven air quality forecast models (AQFMs) are statistically evaluated against observations collected in the northeastern United States and southeastern Canada from two surface networks and aircraft data during the summer of 2004 International Consortium for Atmospheric Research on Transport and Transformation (ICARTT)/New England Air Quality Study (NEAQS) field campaign. The AIRNOW surface network is used to evaluate PM 2.5 aerosol mass, the U.S. EPA STN network is used for PM 2.5 aerosol composition comparisons, and aerosol size distribution and composition measured from the NOAA P-3 aircraft are also compared. Statistics based on midday 8-hour averages, as well as 24-hour averages are evaluated against the AIRNOW surface network. When the 8-hour average PM 2.5 statistics are compared against equivalent ozone statistics for each model, the analysis shows that PM 2.5 forecasts possess nearly equivalent correlation, less bias, and better skill relative to the corresponding ozone forecasts. An analysis of the diurnal variability shows that most models do not reproduce the observed diurnal cycle at urban and suburban monitor locations, particularly during the nighttime to early morning transition. While observations show median rural PM 2.5 levels similar to urban and suburban values, the models display noticeably smaller rural/urban PM 2.5 ratios. The ensemble PM 2.5 forecast, created by combining six separate forecasts with equal weighting, is also evaluated and shown to yield the best possible forecast in terms of the statistical measures considered. The comparisons of PM 2.5 composition with NOAA P-3 aircraft data reveals two important features: (1) The organic component of PM 2.5 is significantly underpredicted by all the AQFMs and (2) those models that include aqueous phase oxidation of SO 2 to sulfate in clouds overpredict sulfate levels while those AQFMs that do not include this transformation mechanism underpredict sulfate. Errors in PM 2.5 ammonium levels tend to correlate directly with errors in sulfate. Comparisons of PM 2.5 composition with the U.S. EPA STN network for three of the AQFMs show that sulfate biases are consistently lower at the surface than aloft. Recommendations for further research and analysis to help improve PM 2.5 forecasts are also provided.

Organic Aerosols in the Earth’s Atmosphere

“…Many chemistry-transport models underestimate the mass loadings of OA in the polluted atmosphere (16,31). However, the discrepancy is rarely an order of magnitude as suggested in the previous paragraph.…”

An evaluation of real‐time air quality forecasts and their urban emissions over eastern Texas during the summer of 2006 Second Texas Air Quality Study field study

“…One possibility is a collective misrepresentation of nighttime planetary boundary layer (PBL) dynamics and depositional loss. For NEAQS-2004, McKeen et al [2007 showed that the diurnal trends for urban and suburban locations were not reproduced adequately, and that the 24-h model averages were heavily skewed toward nighttime concentrations for most models, while the observations were not. This does not appear to be a factor for TexAQS II, since statistics based only on midday 8-h averages (not shown) are nearly identical to those shown in Figure 5 for TexAQS II, but were significantly different (much improved skill with an 11% median ensemble low bias) for NEAQS-2004.…”

“…Comparisons with aircraft data given below (sections 4 and 5) suggest that highly reactive anthropogenic VOC emissions (ethylene in particular) are significantly underpredicted relative to NO x emissions in the Houston region, whereas inferred ethylene/NO x emission ratios for the Dallas/Forth Worth region (based on only one available upwind/downwind transect pair) are more consistent between all of the AQFMs and observations. Figure 1c, and compared with equivalent statistics for the ICARTT/NEAQS study period in the northeast United States and southeastern Canada during the summer of 2004 [McKeen et al, 2007]. Current regulatory interest is focused on 24-h average concentrations, which are used in the AIRNow comparisons here (0400 UTC to 2800 UTC model forecasts) for the 13 August to 30 September 2006 period.…”

“…Current regulatory interest is focused on 24-h average concentrations, which are used in the AIRNow comparisons here (0400 UTC to 2800 UTC model forecasts) for the 13 August to 30 September 2006 period. McKeen et al [2007] used log-transformed concentrations in the analysis of the AIRNow PM 2.5 data within the 2004 study based on the probability distribution functions (and chi-square analysis) of that data set. For consistency in the comparisons, log-transformed concentrations are also applied to the 2006 AIRNow PM 2.5 analysis, and used to determine r coefficients and ratio-equivalent RMSE, and model bias is viewed in terms of model to observed ratios.…”

“…To our knowledge, these were the first PM 2.5 ensemble, bias-corrected and Kalmanfilter ensemble AQ forecasts ever available in real time. Previous versions of these same models provided the basis for multimodel evaluations and ensemble studies specific to the summer of 2004 New England Air Quality Study International Consortium for Atmospheric/Research on Transport and Transformation (ICARTT/NEAQS) field study in the northeast United States and southern Canada Pagowski et al, 2005;Pagowski et al, 2006;McKeen et al, 2007;Wilczak et al, 2006;Delle Monache et al, 2008]. Model performance statistics derived from that 2004 study are compared and contrasted with the 2006 forecast results for surface O 3 and PM 2.5 using observations from the U.S. Environmental Protection Agency (EPA) AIRNow (Aerometric Information Retrieval Now) network within section 3.…”