scholarly journals Evaluating the capability of regional-scale air quality models to capture the vertical distribution of pollutants

2013 ◽  
Vol 6 (3) ◽  
pp. 791-818 ◽  
Author(s):  
E. Solazzo ◽  
R. Bianconi ◽  
G. Pirovano ◽  
M. D. Moran ◽  
R. Vautard ◽  
...  
Keyword(s):  
Air Quality ◽  
Correlation Coefficient ◽  
Regional Scale ◽  
Model Performance ◽  
Correlation Coefficients ◽  
Surface Processes ◽  
Free Troposphere ◽  
Commercial Aircraft ◽  
Mixing Ratios ◽  
The North

Abstract. 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.

scholarly journals Impacts of different characterizations of large-scale background on simulated regional-scale ozone over the continental United States

2018 ◽  
Vol 18 (5) ◽  
pp. 3839-3864 ◽  
Author(s):  
Christian Hogrefe ◽  
Peng Liu ◽  
George Pouliot ◽  
Rohit Mathur ◽  
Shawn Roselle ◽  
...  
Keyword(s):  
Air Quality ◽  
Boundary Conditions ◽  
Large Scale ◽  
Surface Ozone ◽  
Regional Scale ◽  
Model Performance ◽  
Lower Troposphere ◽  
Substantial Impact ◽  
Mixing Ratios ◽  
Scale Models

Abstract. This study analyzes simulated regional-scale ozone burdens both near the surface and aloft, estimates process contributions to these burdens, and calculates the sensitivity of the simulated regional-scale ozone burden to several key model inputs with a particular emphasis on boundary conditions derived from hemispheric or global-scale models. The Community Multiscale Air Quality (CMAQ) model simulations supporting this analysis were performed over the continental US for the year 2010 within the context of the Air Quality Model Evaluation International Initiative (AQMEII) and Task Force on Hemispheric Transport of Air Pollution (TF-HTAP) activities. CMAQ process analysis (PA) results highlight the dominant role of horizontal and vertical advection on the ozone burden in the mid-to-upper troposphere and lower stratosphere. Vertical mixing, including mixing by convective clouds, couples fluctuations in free-tropospheric ozone to ozone in lower layers. Hypothetical bounding scenarios were performed to quantify the effects of emissions, boundary conditions, and ozone dry deposition on the simulated ozone burden. Analysis of these simulations confirms that the characterization of ozone outside the regional-scale modeling domain can have a profound impact on simulated regional-scale ozone. This was further investigated by using data from four hemispheric or global modeling systems (Chemistry – Integrated Forecasting Model (C-IFS), CMAQ extended for hemispheric applications (H-CMAQ), the Goddard Earth Observing System model coupled to chemistry (GEOS-Chem), and AM3) to derive alternate boundary conditions for the regional-scale CMAQ simulations. The regional-scale CMAQ simulations using these four different boundary conditions showed that the largest ozone abundance in the upper layers was simulated when using boundary conditions from GEOS-Chem, followed by the simulations using C-IFS, AM3, and H-CMAQ boundary conditions, consistent with the analysis of the ozone fields from the global models along the CMAQ boundaries. Using boundary conditions from AM3 yielded higher springtime ozone columns burdens in the middle and lower troposphere compared to boundary conditions from the other models. For surface ozone, the differences between the AM3-driven CMAQ simulations and the CMAQ simulations driven by other large-scale models are especially pronounced during spring and winter where they can reach more than 10 ppb for seasonal mean ozone mixing ratios and as much as 15 ppb for domain-averaged daily maximum 8 h average ozone on individual days. In contrast, the differences between the C-IFS-, GEOS-Chem-, and H-CMAQ-driven regional-scale CMAQ simulations are typically smaller. Comparing simulated surface ozone mixing ratios to observations and computing seasonal and regional model performance statistics revealed that boundary conditions can have a substantial impact on model performance. Further analysis showed that boundary conditions can affect model performance across the entire range of the observed distribution, although the impacts tend to be lower during summer and for the very highest observed percentiles. The results are discussed in the context of future model development and analysis opportunities.

scholarly journals Impacts of Different Characterizations of Large-Scale Background on Simulated Regional-Scale Ozone Over the Continental United States

2017 ◽  
Author(s):  
Christian Hogrefe ◽  
Peng Liu ◽  
George Pouliot ◽  
Rohit Mathur ◽  
Shawn Roselle ◽  
...  
Keyword(s):  
Air Quality ◽  
Boundary Conditions ◽  
Large Scale ◽  
Surface Ozone ◽  
Regional Scale ◽  
Model Performance ◽  
Lower Troposphere ◽  
Substantial Impact ◽  
Mixing Ratios ◽  
Scale Models

Abstract. This study analyzes simulated regional-scale ozone burdens both near the surface and aloft, estimates process contributions to these burdens, and calculates the sensitivity of the simulated regional-scale ozone burden to several key model inputs with a particular emphasis on boundary conditions derived from hemispheric or global scale models. The Community Multiscale Air Quality (CMAQ) model simulations supporting this analysis were performed over the continental U.S. for the year 2010 within the context of the Air Quality Model Evaluation International Initiative (AQMEII) and Task Force on Hemispheric Transport of Air Pollution (TF-HTAP) activities. CMAQ Process Analysis (PA) results highlight the dominant role of horizontal and vertical advection on the ozone burden in the mid-to-upper troposphere and lower stratosphere. Vertical mixing, including mixing by convective clouds, couple fluctuations in free tropospheric ozone to ozone in lower layers. Hypothetical bounding scenarios were performed to quantify the effects of emissions, boundary conditions, and ozone dry deposition on the simulated ozone burden. Analysis of these simulations confirms that the characterization of ozone outside the regional-scale modeling domain can have a profound impact on simulated regional-scale ozone. This was further investigated by using data from four hemispheric or global modeling systems (Chemistry – Integrated Forecasting Model (C-IFS), CMAQ extended for hemispheric applications (H-CMAQ), GEOS-Chem, and AM3) to derive alternate boundary conditions for the regional-scale CMAQ simulations. The regional-scale CMAQ simulations using these four different boundary conditions showed that the largest ozone abundance in the upper layers was simulated when using boundary conditions from GEOS-Chem, followed by the simulations using C-IFS, AM3, and H-CMAQ boundary conditions, consistent with the analysis of the ozone fields from the global models along the CMAQ boundaries. Using boundary conditions from AM3 yielded higher springtime ozone columns burdens in the mid- and lower troposphere compared to boundary conditions from the other models. For surface ozone, the differences between the AM3-driven CMAQ simulations and the CMAQ simulations driven by other large-scale models are especially pronounced during spring and winter where they can reach more than 10 ppb for seasonal mean ozone mixing ratios and as much as 15 ppb for domain-averaged daily maximum 8-hr average ozone on individual days. In contrast, the differences between the C-IFS, GEOS-Chem, and H-CMAQ driven regional-scale CMAQ simulations are typically smaller. Comparing simulated surface ozone mixing ratios to observations and computing seasonal and regional model performance statistics revealed that boundary conditions can have a substantial impact on model performance. Further analysis showed that boundary conditions can affect model performance across the entire range of the observed distribution, although the impacts tend to be lower during summer and for the very highest observed percentiles. The results are discussed in the context of future model development and analysis opportunities.

Examination of the Physical Atmosphere in the Great Lakes Region and Its Potential Impact on Air Quality—Overwater Stability and Satellite Assimilation

2018 ◽  
Vol 57 (12) ◽  
pp. 2789-2816 ◽  
Author(s):  
Richard T. McNider ◽  
Arastoo Pour-Biazar ◽  
Kevin Doty ◽  
Andrew White ◽  
Yuling Wu ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Air Quality ◽  
Land Surface ◽  
Lake Michigan ◽  
Model Performance ◽  
Meteorological Model ◽  
Mixing Ratios ◽  
Chemical Models ◽  
Improve Model ◽  
Model Mixing

AbstractHigh mixing ratios of ozone along the shores of Lake Michigan have been a recurring theme over the last 40 years. Models continue to have difficulty in replicating ozone behavior in the region. Although emissions and chemistry may play a role in model performance, the complex meteorological setting of the relatively cold lake in the summer ozone season and the ability of the physical model to replicate this environment may contribute to air quality modeling errors. In this paper, several aspects of the physical atmosphere that may affect air quality, along with potential paths to improve the physical simulations, are broadly examined. The first topic is the consistent overwater overprediction of ozone. Although overwater measurements are scarce, special boat and ferry ozone measurements over the last 15 years have indicated consistent overprediction by models. The roles of model mixing and lake surface temperatures are examined in terms of changing stability over the lake. From an analysis of a 2009 case, it is tentatively concluded that excessive mixing in the meteorological model may lead to an underestimate of mixing in offline chemical models when different boundary layer mixing schemes are used. This is because the stable boundary layer shear, which is removed by mixing in the meteorological model, can no longer produce mixing when mixing is rediagnosed in the offline chemistry model. Second, air temperature has an important role in directly affecting chemistry and emissions. Land–water temperature contrasts are critical to lake and land breezes, which have an impact on mixing and transport. Here, satellite-derived skin temperatures are employed as a path to improve model temperature performance. It is concluded that land surface schemes that adjust moisture based on surface energetics are important in reducing temperature errors.

scholarly journals Simulation of Snow Water Equivalent (SWE) Using Thermodynamic Snow Models in Québec, Canada

2009 ◽  
Vol 10 (6) ◽  
pp. 1447-1463 ◽  
Author(s):  
A. Langlois ◽  
J. Kohn ◽  
A. Royer ◽  
P. Cliche ◽  
L. Brucker ◽  
...  
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Meteorological Data ◽  
Regional Scale ◽  
Correlation Coefficients ◽  
Reanalysis Data ◽  
Regional Variability ◽  
The North ◽  
Snow Water ◽  
Regional Reanalysis

Abstract Snow cover plays a key role in the climate system by influencing the transfer of energy and mass between the soil and the atmosphere. In particular, snow water equivalent (SWE) is of primary importance for climatological and hydrological processes and is a good indicator of climate variability and change. Efforts to quantify SWE over land from spaceborne passive microwave measurements have been conducted since the 1980s, but a more suitable method has yet to be developed for hemispheric-scale studies. Tools such as snow thermodynamic models allow for a better understanding of the snow cover and can potentially significantly improve existing snow products at the regional scale. In this study, the use of three snow models [SNOWPACK, CROCUS, and Snow Thermal Model (SNTHERM)] driven by local and reanalysis meteorological data for the simulation of SWE is investigated temporally through three winter seasons and spatially over intensively sampled sites across northern Québec. Results show that the SWE simulations are in agreement with ground measurements through three complete winter seasons (2004/05, 2005/06, and 2007/08) in southern Québec, with higher error for 2007/08. The correlation coefficients between measured and predicted SWE values ranged between 0.72 and 0.99 for the three models and three seasons evaluated in southern Québec. In subarctic regions, predicted SWE driven with the North American Regional Reanalysis (NARR) data fall within the range of measured regional variability. NARR data allow snow models to be used regionally, and this paper represents a first step for the regionalization of thermodynamic multilayered snow models driven by reanalysis data for improved global SWE evolution retrievals.

Two models and two emission databases – evaluation of the PM10 and PM2.5 concentrations modelled with WRF-Chem and EMEP4PL

2020 ◽  
Author(s):  
Małgorzata Werner ◽  
Maciej Kryza ◽  
Justyna Dudek
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Model Performance ◽  
Correlation Coefficients ◽  
Chemical Transport ◽  
Population Exposure ◽  
Transport Models ◽  
Local Database ◽  
Chemical Transport Models ◽  
Pm10 And Pm2.5

<p>Some European countries in Eastern or Central Europe, such as Poland, have serious problems with air quality. High concentrations of particulate matter (PM) in winter are often related to high coal and wood combustion for residential heating. Meteorological conditions, i.e. low air temperature and anticyclones, provide favourable conditions for the accumulation of air pollution, rendering it harmful to people.  PM concentrations during the warmer period are much lower, however there are episodes with elevated concentrations related to e.g. long-range transport of pollutants from biomass burning areas. Policy makers in Poland put a lot of effort to improve air quality as well as inform and aware people on harmful effects of air pollution. One of the relevant tools which provides information on the past, current and future state of the air pollution are chemical transport models.</p><p>In this study we aim for validation of PM10 and PM2.5 concentrations from two different chemical transport models – WRF-Chem and EMEP4PL and two different emission databases – a) a regional EMEP database, and b) a local database provided by the Chief Inspectorate of Environmental Pollution. Modelled PM10 and PM2.5 concentrations were compared with observations from Polish stations for the year 2018. The results show a clear seasonal variation of the models performance with the lowest correlation coefficients in summer. Higher seasonal variability is observed for WRF-Chem than EMEP, which is probably related to differences in calculations of boundary layer height. Application of local database improves the results for both models. For several months, the performance of WRF-Chem and EMEP is clearly different, which shows that an ensemble approach with an application of these two models could improve the modelling results. The differences in the model performance significantly influence the results of the population exposure assessment.</p><p> </p>

scholarly journals Effects of halogens on European air-quality

2017 ◽  
Vol 200 ◽  
pp. 75-100 ◽  
Author(s):  
T. Sherwen ◽  
M. J. Evans ◽  
R. Sommariva ◽  
L. D. J. Hollis ◽  
S. M. Ball ◽  
...  
Keyword(s):  
Air Quality ◽  
Stratospheric Ozone ◽  
Mixing Ratios ◽  
The North ◽  
Halogen Chemistry ◽  
The North Sea ◽  
Regional Air Quality ◽  
The Uk ◽  
The Impact ◽  
Quality Policy

Halogens (Cl, Br) have a profound influence on stratospheric ozone (O3). They (Cl, Br and I) have recently also been shown to impact the troposphere, notably by reducing the mixing ratios of O3 and OH. Their potential for impacting regional air-quality is less well understood. We explore the impact of halogens on regional pollutants (focussing on O3) with the European grid of the GEOS-Chem model (0.25° × 0.3125°). It has recently been updated to include a representation of halogen chemistry. We focus on the summer of 2015 during the ICOZA campaign at the Weybourne Atmospheric Observatory on the North Sea coast of the UK. Comparisons between these observations together with those from the UK air-quality network show that the model has some skill in representing the mixing ratios/concentration of pollutants during this period. Although the model has some success in simulating the Weybourne ClNO2 observations, it significantly underestimates ClNO2 observations reported at inland locations. It also underestimates mixing ratios of IO, OIO, I2 and BrO, but this may reflect the coastal nature of these observations. Model simulations, with and without halogens, highlight the processes by which halogens can impact O3. Throughout the domain O3 mixing ratios are reduced by halogens. In northern Europe this is due to a change in the background O3 advected into the region, whereas in southern Europe this is due to local chemistry driven by Mediterranean emissions. The proportion of hourly O3 above 50 nmol mol−1 in Europe is reduced from 46% to 18% by halogens. ClNO2 from N2O5 uptake onto sea-salt leads to increases in O3 mixing ratio, but these are smaller than the decreases caused by the bromine and iodine. 12% of ethane and 16% of acetone within the boundary layer is oxidised by Cl. Aerosol response to halogens is complex with small (∼10%) reductions in PM2.5 in most locations. A lack of observational constraints coupled to large uncertainties in emissions and chemical processing of halogens make these conclusions tentative at best. However, the results here point to the potential for halogen chemistry to influence air quality policy in Europe and other parts of the world.

scholarly journals Airborne observations and modeling of springtime stratosphere-to-troposphere transport over California

2013 ◽  
Vol 13 (4) ◽  
pp. 10157-10192 ◽  
Author(s):  
E. L. Yates ◽  
L. T. Iraci ◽  
M. C. Roby ◽  
R. B. Pierce ◽  
M. S. Johnson ◽  
...  
Keyword(s):  
Air Quality ◽  
Free Troposphere ◽  
Air Mass ◽  
Air Masses ◽  
Airborne Measurements ◽  
Mixing Ratios ◽  
Stratospheric Intrusion ◽  
Tropospheric O3 ◽  
Carbon Dioxide Co2 ◽  
The Impact

Abstract. Stratosphere-to-troposphere transport (STT) results in air masses of stratospheric origin intruding into the free troposphere. Once in the free troposphere, O3-rich stratospheric air can be transported and mixed with tropospheric air masses, contributing to the tropospheric O3 budget. Evidence of STT can be identified based on the differences in the trace gas composition of the two regions. Because ozone (O3) is present in such large quantities in the stratosphere compared to the troposphere, it is frequently used as a tracer for STT events. This work reports on airborne in situ measurements of O3 and other trace gases during two STT events observed over California, USA. The first, on 14 May 2012, was associated with a cut-off low, and the second, on 5 June 2012, occurred during a post-trough, building ridge event. In each STT event, airborne measurements identified high O3 within a stratospheric intrusion which was observed as low as 3 km above sea level. During both events the stratospheric air mass was characterized by elevated O3 mixing ratios and reduced carbon dioxide (CO2) and water vapor. The reproducible observation of reduced CO2 within the stratospheric air mass supports the use of non-conventional tracers as an additional method for detecting STT. A detailed meteorological analysis of each STT event is presented and observations are interpreted with the Realtime Air Quality Modeling System (RAQMS). The implications of the two STT events are discussed in terms of the impact on the total tropospheric O3 budget and the impact on air quality and policy-making.

scholarly journals Sensitivity of the Community Multiscale Air Quality (CMAQ) model v4.7 results for the eastern United States to MM5 and WRF meteorological drivers

2010 ◽  
Vol 3 (1) ◽  
pp. 169-188 ◽  
Author(s):  
K. W. Appel ◽  
S. J. Roselle ◽  
R. C. Gilliam ◽  
J. E. Pleim
Keyword(s):  
United States ◽  
Air Quality ◽  
Mesoscale Model ◽  
Model Performance ◽  
Wrf Model ◽  
Total Carbon ◽  
Eastern United States ◽  
Model Simulations ◽  
Mixing Ratios ◽  
Vegetation Fraction

Abstract. This paper presents a comparison of the operational performances of two Community Multiscale Air Quality (CMAQ) model v4.7 simulations that utilize input data from the 5th-generation Mesoscale Model (MM5) and the Weather Research and Forecasting (WRF) meteorological models. Two sets of CMAQ model simulations were performed for January and August 2006. One set utilized MM5 meteorology (MM5-CMAQ) and the other utilized WRF meteorology (WRF-CMAQ), while all other model inputs and options were kept the same. For January, predicted ozone (O3) mixing ratios were higher in the Southeast and lower Mid-west regions in the WRF-CMAQ simulation, resulting in slightly higher bias and error as compared to the MM5-CMAQ simulations. The higher predicted O3 mixing ratios are attributed to less dry deposition of O3 in the WRF-CMAQ simulation due to differences in the calculation of the vegetation fraction between the MM5 and WRF models. The WRF-CMAQ results showed better performance for particulate sulfate (SO42−), similar performance for nitrate (NO3−), and slightly worse performance for nitric acid (HNO3), total carbon (TC) and total fine particulate (PM2.5) mass than the corresponding MM5-CMAQ results. For August, predictions of O3 were notably higher in the WRF-CMAQ simulation, particularly in the southern United States, resulting in increased model bias. Concentrations of predicted particulate SO42− were lower in the region surrounding the Ohio Valley and higher along the Gulf of Mexico in the WRF-CMAQ simulation, contributing to poorer model performance. The primary causes of the differences in the MM5-CMAQ and WRF-CMAQ simulations appear to be due to differences in the calculation of wind speed, planetary boundary layer height, cloud cover and the friction velocity (u∗) in the MM5 and WRF model simulations, while differences in the calculation of vegetation fraction and several other parameters result in smaller differences in the predicted CMAQ model concentrations. The performance for SO42−, NO3− and NH4+ wet deposition was similar for both simulations for January and August.

scholarly journals Low modeled ozone production suggests underestimation of precursor emissions (especially NO<sub><i>x</i></sub>) in Europe

2018 ◽  
Vol 18 (3) ◽  
pp. 2175-2198 ◽  
Author(s):  
Emmanouil Oikonomakis ◽  
Sebnem Aksoyoglu ◽  
Giancarlo Ciarelli ◽  
Urs Baltensperger ◽  
André Stephan Henry Prévôt
Keyword(s):  
Air Quality ◽  
Surface Ozone ◽  
Model Performance ◽  
Ozone Production ◽  
Nox Emissions ◽  
Air Quality Model ◽  
Quality Model ◽  
Voc Emissions ◽  
Mixing Ratios ◽  
The Impact

Abstract. High surface ozone concentrations, which usually occur when photochemical ozone production takes place, pose a great risk to human health and vegetation. Air quality models are often used by policy makers as tools for the development of ozone mitigation strategies. However, the modeled ozone production is often not or not enough evaluated in many ozone modeling studies. The focus of this work is to evaluate the modeled ozone production in Europe indirectly, with the use of the ozone–temperature correlation for the summer of 2010 and to analyze its sensitivity to precursor emissions and meteorology by using the regional air quality model, the Comprehensive Air Quality Model with Extensions (CAMx). The results show that the model significantly underestimates the observed high afternoon surface ozone mixing ratios (≥ 60 ppb) by 10–20 ppb and overestimates the lower ones (< 40 ppb) by 5–15 ppb, resulting in a misleading good agreement with the observations for average ozone. The model also underestimates the ozone–temperature regression slope by about a factor of 2 for most of the measurement stations. To investigate the impact of emissions, four scenarios were tested: (i) increased volatile organic compound (VOC) emissions by a factor of 1.5 and 2 for the anthropogenic and biogenic VOC emissions, respectively, (ii) increased nitrogen oxide (NOx) emissions by a factor of 2, (iii) a combination of the first two scenarios and (iv) increased traffic-only NOx emissions by a factor of 4. For southern, eastern, and central (except the Benelux area) Europe, doubling NOx emissions seems to be the most efficient scenario to reduce the underestimation of the observed high ozone mixing ratios without significant degradation of the model performance for the lower ozone mixing ratios. The model performance for ozone–temperature correlation is also better when NOx emissions are doubled. In the Benelux area, however, the third scenario (where both NOx and VOC emissions are increased) leads to a better model performance. Although increasing only the traffic NOx emissions by a factor of 4 gave very similar results to the doubling of all NOx emissions, the first scenario is more consistent with the uncertainties reported by other studies than the latter, suggesting that high uncertainties in NOx emissions might originate mainly from the road-transport sector rather than from other sectors. The impact of meteorology was examined with three sensitivity tests: (i) increased surface temperature by 4 ∘C, (ii) reduced wind speed by 50 % and (iii) doubled wind speed. The first two scenarios led to a consistent increase in all surface ozone mixing ratios, thus improving the model performance for the high ozone values but significantly degrading it for the low ozone values, while the third scenario had exactly the opposite effects. Overall, the modeled ozone is predicted to be more sensitive to its precursor emissions (especially traffic NOx) and therefore their uncertainties, which seem to be responsible for the model underestimation of the observed high ozone mixing ratios and ozone production.

scholarly journals Evaluation and Error Apportionment of an Ensemble of Atmospheric Chemistry Transport Modelling Systems: Multi-variable Temporal and Spatial Breakdown

2016 ◽  
Author(s):  
Efisio Solazzo ◽  
Roberto Bianconi ◽  
Christian Hogrefe ◽  
Gabriele Curci ◽  
Ummugulsum Alyuz ◽  
...  
Keyword(s):  
Air Quality ◽  
Atmospheric Chemistry ◽  
Model Comparison ◽  
Regional Scale ◽  
Model Development ◽  
Model Performance ◽  
Strong Impact ◽  
Air Quality Model ◽  
Quality Model ◽  
Transport Modelling

Abstract. Through the comparison of several regional-scale chemistry transport modelling systems that simulate meteorology and air quality over the European and American continents, this study aims at i) apportioning the error to the responsible processes using time-scale analysis, ii) helping to detect causes of models error, and iii) identifying the processes and scales most urgently requiring dedicated investigations. The analysis is conducted within the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII) and tackles model performance gauging through measurement-to-model comparison, error decomposition and time series analysis of the models biases for several fields (ozone, CO, SO2, NO, NO2, PM10, PM2.5, wind speed, and temperature). The operational metrics (magnitude of the error, sign of the bias, associativity) provide an overall sense of model strengths and deficiencies, while apportioning the error to its constituent parts (bias, variance and covariance) can help to assess the nature and quality of the error. Each of the error components is analysed independently and apportioned to specific processes based on the corresponding timescale (long scale, synoptic, diurnal, and intra-day) using the error apportionment technique devised in the former phases of AQMEII. The application of the error apportionment method to the AQMEII Phase 3 simulations provides several key insights. In addition to reaffirming the strong impact of model inputs (emissions and boundary conditions) and poor representation of the stable boundary layer on model bias, results also highlighted the high inter-dependencies among meteorological and chemical variables, as well as among their errors. This indicates that the evaluation of air quality model performance for individual pollutants needs to be supported by complementary analysis of meteorological fields and chemical precursors to provide results that are more insightful from a model development perspective. The error embedded in the emissions is dominant for primary species (CO, PM, NO) and largely outweighs the error from any other source. The uncertainty in meteorological fields is most relevant to ozone. Some further aspects emerged whose interpretation requires additional consideration, such as, among others, the uniformity of the synoptic error being region and model-independent, observed for several pollutants; the source of unexplained variance for the diurnal component; and the type of error caused by deposition and at which scale.

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