Evaluating the capability of regional-scale air quality models to cature the vertical distribution of pollutants

This study is conducted in the framework of the Air Quality Modelling Evaluation International Initiative (AQMEII) and aims at the operational evaluation of an ensemble of 12 regional-scale chemical transport models used to predict air quality over the North American (NA) and European (EU) continents for 2006. The modelled concentrations of ozone and CO, along with the meteorological fields of wind speed (WS) and direction (WD), temperature (T), and relative humidity (RH), are compared against high-quality in-flight measurements collected by instrumented commercial aircraft as part of the Measurements of OZone, water vapour, carbon monoxide and nitrogen oxides by Airbus In-service airCraft (MOZAIC) programme. The evaluation is carried out for five model domains positioned around four major airports in NA (Portland, Philadelphia, Atlanta, and Dallas) and one in Europe (Frankfurt), from the surface to 8.5 km. We compare mean vertical profiles of modelled and measured variables for all airports to compute error and variability statistics, perform analysis of altitudinal error correlation, and examine the seasonal error distribution for ozone, including an estimation of the bias introduced by the lateral boundary conditions (BCs). The results indicate that model performance is highly dependent on the variable, location, season, and height (e.g. surface, planetary boundary layer (PBL) or free troposphere) being analysed. While model performance for T is satisfactory at all sites (correlation coefficient in excess of 0.90 and fractional bias ≤ 0.01 K), WS is not replicated as well within the PBL (exhibiting a positive bias in the first 100 m and also underestimating observed variability), while above 1000 m, the model performance improves (correlation coefficient often above 0.9). The WD at NA airports is found to be biased in the PBL, primarily due to an overestimation of westerly winds. RH is modelled well within the PBL, but in the free troposphere large discrepancies among models are observed, especially in EU. CO mixing ratios show the largest range of modelled-to-observed standard deviations of all the examined species at all heights and for all airports. Correlation coefficients for CO are typically below 0.6 for all sites and heights, and large errors are present at all heights, particularly in the first 250 m. Model performance for ozone in the PBL is generally good, with both bias and error within 20%. Profiles of ozone mixing ratios depend strongly on surface processes, revealed by the sharp gradient in the first 2 km (10 to 20 ppb km−1). Modelled ozone in winter is biased low at all locations in the NA, primarily due to an underestimation of ozone from the BCs. Most of the model error in the PBL is due to surface processes (emissions, transport, photochemistry), while errors originating aloft appear to have relatively limited impact on model performance at the surface. Suggestions for future work include interpretation of the model-to-model variability and common sources of model bias, and linking CO and ozone bias to the bias in the meteorological fields. Based on the results from this study, we suggest possible in-depth, process-oriented and diagnostic investigations to be carried out next

Seasonal ozone vertical profiles over North America using the AQMEII3 group of air quality models: model inter-comparison and stratospheric intrusions

This study evaluates simulated vertical ozone profiles produced in the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3) against ozonesonde observations in North America for the year 2010. Four research groups from the United States (US) and Europe have provided modeled ozone vertical profiles to conduct this analysis. Because some of the modeling systems differ in their meteorological drivers, wind speed and temperature are also included in the analysis. In addition to the seasonal ozone profile evaluation for 2010, we also analyze chemically inert tracers designed to track the influence of lateral boundary conditions on simulated ozone profiles within the modeling domain. Finally, cases of stratospheric ozone intrusions during May–June 2010 are investigated by analyzing ozonesonde measurements and the corresponding model simulations at Intercontinental Chemical Transport Experiment Ozonesonde Network Study (IONS) experiment sites in the western United States. The evaluation of the seasonal ozone profiles reveals that, at a majority of the stations, ozone mixing ratios are underestimated in the 1–6&thinsp;km range. The seasonal change noted in the errors follows the one seen in the variance of ozone mixing ratios, with the majority of the models exhibiting less variability than the observations. The analysis of chemically inert tracers highlights the importance of lateral boundary conditions up to 250&thinsp;hPa for the lower-tropospheric ozone mixing ratios (0–2&thinsp;km). Finally, for the stratospheric intrusions, the models are generally able to reproduce the location and timing of most intrusions but underestimate the magnitude of the maximum mixing ratios in the 2–6&thinsp;km range and overestimate ozone up to the first kilometer possibly due to marine air influences that are not accurately described by the models. The choice of meteorological driver appears to be a greater predictor of model skill in this altitude range than the choice of air quality model.</p

Modeling intercontinental transport of ozone in North America with CAMx for the Air Quality Model Evaluation International Initiative (AQMEII) Phase 3

Intercontinental ozone (O3) transport extends the geographic range of O3 air pollution impacts and makes local air pollution management more difficult. Phase 3 of the Air Quality Modeling Evaluation International Initiative (AQMEII-3) is examining the contribution of intercontinental transport to regional air quality by applying regional-scale atmospheric models jointly with global models. We investigate methods for tracing O3 from global models within regional models. The CAMx photochemical grid model was used to track contributions from boundary condition (BC) O3 over a North American modeling domain for calendar year 2010 using a built-in tracer module called RTCMC. RTCMC can track BC contributions using chemically reactive tracers and also using inert tracers in which deposition is the only sink for O3. Lack of O3 destruction chemistry in the inert tracer approach leads to overestimation biases that can exceed 10 ppb. The flexibility of RTCMC also allows tracking O3 contributions made by groups of vertical BC layers. The largest BC contributions to seasonal average daily maximum 8 h averages (MDA8) of O3 over the US are found to be from the mid-troposphere (over 40 ppb) with small contributions (a few ppb) from the upper troposphere–lower stratosphere. Contributions from the lower troposphere are shown to not penetrate very far inland. Higher contributions in the western than the eastern US, reaching an average of 57 ppb in Denver for the 30 days with highest MDA8 O3 in 2010, present a significant challenge to air quality management approaches based solely on local or US-wide emission reductions. The substantial BC contribution to MDA8 O3 in the Intermountain West means regional models are particularly sensitive to any biases and errors in the BCs. A sensitivity simulation with reduced BC O3 in response to 20 % lower emissions in Asia found a near-linear relationship between the BC O3 changes and surface O3 changes in the western US in all seasons and across the US in fall and winter. However, the surface O3 decreases are small: below 1 ppb in spring and below 0.5 ppb in other seasons

Modeling Europe with CAMx for the Air Quality Model Evaluation International Initiative (AQMEII)

The CAMx photochemical grid model was used to model ozone (O 3) and particulate matter (PM) over a European modeling domain for calendar year 2006 as part of the Air Quality Model Evaluation International Initiative (AQMEII). The CAMx base case utilized input data provided by AQMEII for emissions, meteorology and boundary conditions. Sensitivity of model outputs to input data was investigated by using alternate input data and changing other important modeling assumptions including the schemes to represent photochemistry, dry deposition and vertical mixing. Impacts on model performance were evaluated by comparisons with ambient monitoring data. Base case model performance for January and July 2006 exhibited under-estimation trends for all pollutants both in winter and summer, except for SO 2. SO 2 generally had little bias although some over-estimation occurred at coastal locations and this was attributed to incorrect vertical distribution of emissions from marine vessels. Performance for NOx and NO 2 was better in winter than summer. The tendency to under-predict daytime NOx and O 3 in summer may result from insufficient NOx emissions or overstated daytime dilution (e.g., too deep planetary boundary layer) or monitors that are located near sources (e.g., roadside monitors). Winter O 3 was biased low and this was attributed to a low bias in the O 3 boundary conditions. PM 10 was widely under-predicted in both winter and summer. The poor PM 10 was influenced by under-estimation of coarse PM emissions. Sensitivities of O 3 concentrations to precursor emissions are quantified using the decoupled direct method in CAMx. The results suggest that O 3 production over the central and southern Europe during summer is mostly NOx-limited but for a more northerly city, London, O 3 production can be limited either by NOx or VOC depending upon daily meteorological conditions. © 2011 Elsevier Ltd

Investigating impacts of chemistry and transport model formulation on model performance at European scale

The CAMx and CHIMERE chemistry and transport models were applied over Europe for the year 2006 in the framework of the AQMEII inter-comparison exercise. Model simulations used the same input data set thus allowing model performance evaluation to focus on differences related to model chemistry and physics. Model performance was investigated according to different conditions, such as monitoring station classification and geographical features. An improved evaluation methodology, based on the Wilcoxon statistical test, was implemented to provide objectivity in the comparison of model performance.The models demonstrated similar geographical variations in model performance with just a few exceptions. Both models displayed great performance variability from region to region and within the same region for NO 2 and PM 10. Station type is relevant mainly for pollutants directly influenced by low level emission sources, such as NO 2 and PM 10.The analysis of the differences between CAMx and CHIMERE results revealed that both physical and chemical processes influenced the model performance. Particularly, differences in vertical diffusion coefficients (Kz) and 1st layer wind speed can affect the surface concentration of primary compounds, especially for stable conditions. Differently, differences in the vertical profiles of Kz strongly influenced the impact of aloft sources on ground level concentrations of both primary pollutants such as SO 2 as well as PM 10 compounds. CAMx showed stronger photochemistry than CHIMERE giving rise to higher ozone concentrations that agreed better with observations. Nonetheless, in some areas the more effective photochemistry showed by CAMx actually compensated for an underestimation in the background concentration.Finally, PM 10 performance was rather poor for both models in most regions. CAMx performed always better than CHIMERE in terms of bias, while CHIMERE score for correlation was always higher than CAMx. As already mentioned, vertical mixing is one cause of such discrepancies in correlation. Differently, the stronger underestimation experienced by CHIMERE was mainly influenced by temporal smoothing of the boundary conditions, underestimation of low level emissions (mainly related to fires) and more intense depletion by wet deposition. © 2012 Elsevier Ltd

Investigating impacts of chemistry and transport model formulation on model performance at European scale

International audienceThe CAMx and CHIMERE chemistry and transport models were applied over Europe for the year 2006 in the framework of the AQMEII inter-comparison exercise. Model simulations used the same input data set thus allowing model performance evaluation to focus on differences related to model chemistry and physics. Model performance was investigated according to different conditions, such as monitoring station classification and geographical features. An improved evaluation methodology, based on the Wilcoxon statistical test, was implemented to provide objectivity in the comparison of model performance. The models demonstrated similar geographical variations in model performance with just a few exceptions. Both models displayed great performance variability from region to region and within the same region for NO2 and PM10. Station type is relevant mainly for pollutants directly influenced by low level emission sources, such as NO2 and PM10.The analysis of the differences between CAMx and CHIMERE results revealed that both physical and chemical processes influenced the model performance. Particularly, differences in vertical diffusion coefficients (Kz) and 1st layer wind speed can affect the surface concentration of primary compounds, especially for stable conditions. Differently, differences in the vertical profiles of Kz strongly influenced the impact of aloft sources on ground level concentrations of both primary pollutants such as SO2 as well as PM10 compounds. CAMx showed stronger photochemistry than CHIMERE giving rise to higher ozone concentrations that agreed better with observations. Nonetheless, in some areas the more effective photochemistry showed by CAMx actually compensated for an underestimation in the background concentration. Finally, PM10 performance was rather poor for both models in most regions. CAMx performed always better than CHIMERE in terms of bias, while CHIMERE score for correlation was always higher than CAMx. As already mentioned, vertical mixing is one cause of such discrepancies in correlation. Differently, the stronger underestimation experienced by CHIMERE was mainly influenced by temporal smoothing of the boundary conditions, underestimation of low level emissions (mainly related to fires)and more intense depletion by wet deposition

Modeling Europe with CAMx for the Air Quality Model Evaluation International Initiative (AQMEII)

International audienceThe CAMx photochemical grid model was used to model ozone (O3) and particulate matter (PM) over a European modeling domain for calendar year 2006 as part of the Air Quality Model Evaluation International Initiative (AQMEII). The CAMx base case utilized input data provided by AQMEII for emissions, meteorology and boundary conditions. Sensitivity of model outputs to input data was investigated by using alternate input data and changing other important modeling assumptions including the schemes to represent photochemistry, dry deposition and vertical mixing. Impacts on model performance were evaluated by comparisons with ambient monitoring data. Base case model performance for January and July 2006 exhibited under-estimation trends for all pollutants both in winter and summer, except for SO2. SO2 generally had little bias although some over-estimation occurred at coastal locations and this was attributed to incorrect vertical distribution of emissions from marine vessels. Performance for NOx and NO2 was better in winter than summer. The tendency to under-predict daytime NOx and O3 in summer may result from insufficient NOx emissions or overstated daytime dilution (e.g., too deep planetary boundary layer) or monitors that are located near sources (e.g., roadside monitors). Winter O3 was biased low and this was attributed to a low bias in the O3 boundary conditions. PM10 was widely under-predicted in both winter and summer. The poor PM10 was influenced by underestimation of coarse PM emissions. Sensitivities of O3 concentrations to precursor emissions are quantified using the decoupled direct method in CAMx. The results suggest that O3 production over the central and southern Europe during summer is mostly NOx-limited but for a more northerly city, London, O3 production can be limited either by NOx or VOC depending upon daily meteorological conditions

Air quality simulations for North America - MM5–CAMx modelling performance for main gaseous pollutants

In the scope of the Air Quality Model Evaluation International Initiative (AQMEII) the air quality modelling system MM5eCAMx was applied to the North American (NA) domain for calendar year 2006. The simulation domainwas defined according to the spatial resolution and the coordinate system of the emission databases provided and the common grid required by AQMEII for ensemble analysis. A Lambert Conformal Projection grid of around 5500 km by 3580 km with 24 24 km2 horizontal resolution was defined. Emissions available through AQMEII have been prepared to feed the CAMx model. Meteoro- logical inputs were developed by the application of the meteorological model MM5, which was initial- ized by 1 resolution NCEP-FNL global data and run for the whole year of 2006. A spatial and temporal analysis of results based on the 2D surface fields and time series for regional monitoring stations was performed for the main gaseous pollutants. A detailed statistical analysis and evaluation against observations was carried out, considering three different sub-domains over North America, in order to comprehend the differences between the East, West and Central part. The exploitation of modelling results was based on the capabilities and analysis tools available through the ENSEMBLE software, developed and upgraded for AQMEII. Results have shown a good agreement between observed and modelled concentrations of O3 (especially regarding peaks) and NO2 and a weaker performance of the air quality model for CO and SO2. However, the model tends to underestimate O3 and overestimate NO2 and CO at night as a consequence of meteorology (weak vertical mixing due to underestimation of the Planetary Boundary Layer (PBL) height). This paper intends to be a valuable contribution to the overall AQMEII exercise since it aims to evaluate the performance of individual models to be used in the ensemble approach for the areas of interest