scholarly journals Impact of a new condensed toluene mechanism on air quality model predictions in the US

2010 ◽  
Vol 3 (4) ◽  
pp. 2291-2314
Author(s):  
G. Sarwar ◽  
K. W. Appel ◽  
A. G. Carlton ◽  
R. Mathur ◽  
K. Schere ◽  
...  
Keyword(s):  
Air Quality ◽  
Los Angeles ◽  
Production Efficiency ◽  
Sensitivity Study ◽  
Chemical Mechanism ◽  
Ozone Production ◽  
Daily Maximum ◽  
Air Quality Model ◽  
Quality Model ◽  
Mixing Ratios

Abstract. A new condensed toluene mechanism is incorporated into the Community Multiscale Air Quality Modeling system. Model simulations are performed using the CB05 chemical mechanism containing the existing (base) and the new toluene mechanism for the western and eastern US for a summer month. With current estimates of tropospheric emission burden, the new toluene mechanism increases monthly mean daily maximum 8-h ozone by 1.0–3.0 ppbv in Los Angeles, Portland, Seattle, Chicago, Cleveland, northeastern US, and Detroit compared to that with the base toluene chemistry. It reduces model mean bias for ozone at elevated observed ozone mixing ratios. While the new mechanism increases predicted ozone, it does not enhance ozone production efficiency. Sensitivity study suggests that it can further enhance ozone if elevated toluene emissions are present. While changes in total fine particulate mass are small, predictions of in-cloud SOA increase substantially.

scholarly journals Impact of a new condensed toluene mechanism on air quality model predictions in the US

2011 ◽  
Vol 4 (1) ◽  
pp. 183-193 ◽  
Author(s):  
G. Sarwar ◽  
K. W. Appel ◽  
A. G. Carlton ◽  
R. Mathur ◽  
K. Schere ◽  
...  
Keyword(s):  
Air Quality ◽  
Los Angeles ◽  
Production Efficiency ◽  
Sensitivity Study ◽  
Chemical Mechanism ◽  
Ozone Production ◽  
Daily Maximum ◽  
Air Quality Model ◽  
Quality Model ◽  
The Us

Abstract. A new condensed toluene mechanism is incorporated into the Community Multiscale Air Quality Modeling system. Model simulations are performed using the CB05 chemical mechanism containing the existing (base) and the new toluene mechanism for the western and eastern US for a summer month. With current estimates of tropospheric emission burden, the new toluene mechanism increases monthly mean daily maximum 8-h ozone by 1.0–3.0 ppbv in Los Angeles, Portland, Seattle, Chicago, Cleveland, northeastern US, and Detroit compared to that with the base toluene chemistry. It reduces model mean bias for ozone at elevated observed ozone concentrations. While the new mechanism increases predicted ozone, it does not enhance ozone production efficiency. A sensitivity study suggests that it can further enhance ozone if elevated toluene emissions are present. While it increases in-cloud secondary organic aerosol substantially, its impact on total fine particle mass concentration is small.

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

2017 ◽  
Author(s):  
Emmanouil Oikonomakis ◽  
Sebnem Aksoyoglu ◽  
Giancarlo Ciarelli ◽  
Urs Baltensperger ◽  
André S. H. Prévôt
Keyword(s):  
Air Quality ◽  
Surface Ozone ◽  
High Surface ◽  
Mitigation Strategies ◽  
Ozone Production ◽  
Air Quality Model ◽  
Quality Model ◽  
Mixing Ratios ◽  
Modelling Studies ◽  
Regional Air Quality

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 modelling 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, 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 (

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

2018 ◽  
Author(s):  
Marina Astitha ◽  
Ioannis Kioutsoukis ◽  
Ghezae Araya Fisseha ◽  
Roberto Bianconi ◽  
Johannes Bieser ◽  
...  
Keyword(s):  
United States ◽  
Air Quality ◽  
North America ◽  
Vertical Profiles ◽  
Lateral Boundary ◽  
Air Quality Model ◽  
Quality Model ◽  
Mixing Ratios ◽  
Lateral Boundary Conditions ◽  
Stratospheric Intrusions

Abstract. 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 (U.S.) and Europe have provided 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 under-estimated in the 1–6 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 hPa for the lower tropospheric ozone mixing ratios (0–2 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 km range and overestimate ozone up to the first km 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.

scholarly journals Eta-CMAQ air quality forecasts for O<sub>3</sub> and related species using three different photochemical mechanisms (CB4, CB05, SAPRC-99): comparisons with measurements during the 2004 ICARTT study

2010 ◽  
Vol 10 (6) ◽  
pp. 3001-3025 ◽  
Author(s):  
S. Yu ◽  
R. Mathur ◽  
G. Sarwar ◽  
D. Kang ◽  
D. Tong ◽  
...  
Keyword(s):  
Air Quality ◽  
Production Efficiency ◽  
Gulf Of Maine ◽  
Ozone Production ◽  
Eastern United States ◽  
Forecast Performance ◽  
Transport And Transformation ◽  
Mixing Ratios ◽  
Upper Limits ◽  
The Impact

Abstract. A critical module of air quality models is the photochemical mechanism. In this study, the impact of the three photochemical mechanisms (CB4, CB05, SAPRC-99) on the Eta-Community Multiscale Air Quality (CMAQ) model's forecast performance for O3, and its related precursors has been assessed over the eastern United States with observations obtained by aircraft (NOAA P-3 and NASA DC-8) flights, ship and two surface networks (AIRNow and AIRMAP) during the 2004 International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) study. The results show that overall none of the mechanisms performs systematically better than the others. On the other hand, at the AIRNow surface sites, CB05 has the best performance with the normalized mean bias (NMB) of 3.9%, followed by CB4 (NMB=−5.7%) and SAPRC-99 (NMB=10.6%) for observed O3≥75 ppb, whereas CB4 has the best performance with the least overestimation for observed O3<75 ppb. On the basis of comparisons with aircraft P-3 measurements, there were consistent overestimations of O3, NOz, PAN and NOy and consistent underestimations of CO, HNO3, NO2, NO, SO2 and terpenes for all three mechanisms although the NMB values for each species and mechanisms were different. The results of aircraft DC-8 show that CB05 predicts the H2O2 mixing ratios most closely to the observations (NMB=10.8%), whereas CB4 and SAPRC-99 overestimated (NMB=74.7%) and underestimated (NMB=−25.5%) H2O2 mixing ratios significantly, respectively. For different air mass flows over the Gulf of Maine on the basis of the ship data, the three mechanisms have relatively better performance for O3, isoprene and SO2 for the clean marine or continental flows but relatively better performance for CO, NO2 and NO for southwesterly/westerly offshore flows. The results of the O3-NOz slopes over the ocean indicate that SAPRC-99 has the highest upper limits of the ozone production efficiency (εN) (5.8), followed by CB05 (4.5) and CB4 (4.0) although they are much lower than that inferred from the observation (11.8), being consistent with the fact that on average, SAPRC-99 produces the highest O3, followed by CB05 and CB4, across all O3 mixing ratio ranges

The Impact of Nudging in the Meteorological Model for Retrospective Air Quality Simulations. Part I: Evaluation against National Observation Networks

2008 ◽  
Vol 47 (7) ◽  
pp. 1853-1867 ◽  
Author(s):  
Tanya L. Otte
Keyword(s):  
Air Quality ◽  
Meteorological Conditions ◽  
Daily Maximum ◽  
Air Quality Model ◽  
Quality Model ◽  
Meteorological Model ◽  
Model Simulations ◽  
Dynamic Analyses ◽  
The Impact ◽  
Over Time

Abstract It is common practice to use Newtonian relaxation, or nudging, throughout meteorological model simulations to create “dynamic analyses” that provide the characterization of the meteorological conditions for retrospective air quality model simulations. Given the impact that meteorological conditions have on air quality simulations, it has been assumed that the resultant air quality simulations would be more skillful by using dynamic analyses rather than meteorological forecasts to characterize the meteorological conditions, and that the statistical trends in the meteorological model fields are also reflected in the air quality model. This article, which is the first of two parts, demonstrates the impact of nudging in the meteorological model on retrospective air quality model simulations. Here, meteorological simulations are generated by the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) using both the traditional dynamic analysis approach and using forecasts for a summertime period. The resultant fields are then used to characterize the meteorological conditions for emissions processing and air quality simulations using the Community Multiscale Air Quality (CMAQ) Modeling System. As expected, on average, the near-surface meteorological fields show a significant degradation over time in the forecasts (when nudging is not used), while the dynamic analyses maintain nearly constant statistical scores in time. The use of nudged MM5 fields in CMAQ generally results in better skill scores for daily maximum 1-h ozone mixing ratio simulations. On average, the skill of the daily maximum 1-h ozone simulation deteriorates significantly over time when nonnudged MM5 fields are used in CMAQ. The daily maximum 1-h ozone mixing ratio also degrades over time in the CMAQ simulation that uses MM5 dynamic analyses, although to a much lesser degree, despite no aggregate loss of skill over time in the dynamic analyses themselves. These results affirm the advantage of using nudging in MM5 to create the meteorological characterization for CMAQ for retrospective simulations, and it is shown that MM5-based dynamic analyses are robust at the surface throughout 5.5-day simulations.

Air Quality Model Evaluation Data for Organics. 2. C1−C14Carbonyls in Los Angeles Air

1996 ◽  
Vol 30 (9) ◽  
pp. 2687-2703 ◽  
Author(s):  
Eric Grosjean ◽  
Daniel Grosjean ◽  
Matthew P. Fraser ◽  
Glen R. Cass
Keyword(s):  
Air Quality ◽  
Los Angeles ◽  
Model Evaluation ◽  
Air Quality Model ◽  
Quality Model ◽  
Evaluation Data

scholarly journals Insights into the deterministic skill of air quality ensembles from the analysis of AQMEII data

2016 ◽  
Vol 16 (24) ◽  
pp. 15629-15652 ◽  
Author(s):  
Ioannis Kioutsioukis ◽  
Ulas Im ◽  
Efisio Solazzo ◽  
Roberto Bianconi ◽  
Alba Badia ◽  
...  
Keyword(s):  
Air Quality ◽  
Deterministic Model ◽  
Ensemble Methods ◽  
Ground Level ◽  
Chemical Mechanism ◽  
Second Phase ◽  
Air Quality Model ◽  
Quality Model ◽  
Deterministic Models ◽  
Ensemble Mean

Abstract. Simulations from chemical weather models are subject to uncertainties in the input data (e.g. emission inventory, initial and boundary conditions) as well as those intrinsic to the model (e.g. physical parameterization, chemical mechanism). Multi-model ensembles can improve the forecast skill, provided that certain mathematical conditions are fulfilled. In this work, four ensemble methods were applied to two different datasets, and their performance was compared for ozone (O3), nitrogen dioxide (NO2) and particulate matter (PM10). Apart from the unconditional ensemble average, the approach behind the other three methods relies on adding optimum weights to members or constraining the ensemble to those members that meet certain conditions in time or frequency domain. The two different datasets were created for the first and second phase of the Air Quality Model Evaluation International Initiative (AQMEII). The methods are evaluated against ground level observations collected from the EMEP (European Monitoring and Evaluation Programme) and AirBase databases. The goal of the study is to quantify to what extent we can extract predictable signals from an ensemble with superior skill over the single models and the ensemble mean. Verification statistics show that the deterministic models simulate better O3 than NO2 and PM10, linked to different levels of complexity in the represented processes. The unconditional ensemble mean achieves higher skill compared to each station's best deterministic model at no more than 60 % of the sites, indicating a combination of members with unbalanced skill difference and error dependence for the rest. The promotion of the right amount of accuracy and diversity within the ensemble results in an average additional skill of up to 31 % compared to using the full ensemble in an unconditional way. The skill improvements were higher for O3 and lower for PM10, associated with the extent of potential changes in the joint distribution of accuracy and diversity in the ensembles. The skill enhancement was superior using the weighting scheme, but the training period required to acquire representative weights was longer compared to the sub-selecting schemes. Further development of the method is discussed in the conclusion.

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

2018 ◽  
Vol 18 (19) ◽  
pp. 13925-13945 ◽  
Author(s):  
Marina Astitha ◽  
Ioannis Kioutsioukis ◽  
Ghezae Araya Fisseha ◽  
Roberto Bianconi ◽  
Johannes Bieser ◽  
...  
Keyword(s):  
United States ◽  
Air Quality ◽  
North America ◽  
Vertical Profiles ◽  
Lateral Boundary ◽  
Air Quality Model ◽  
Quality Model ◽  
Mixing Ratios ◽  
Lateral Boundary Conditions ◽  
Stratospheric Intrusions

Abstract. 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 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 hPa for the lower-tropospheric ozone mixing ratios (0–2 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 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.

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