Ozone Pollution Events Research Articles

Altered stomatal dynamics of two Euramerican poplar genotypes submitted to successive ozone exposure and water deficit

The impact of ozone (O3) pollution events on the plant drought response needs special attention because spring O3 episodes are often followed by summer drought. By causing stomatal sluggishness, O3 could affect the stomatal dynamic during a subsequent drought event. In this context, we studied the impact of O3 exposure and water deficit (in the presence or in the absence of O3 episode) on the stomatal closure/opening mechanisms relative to irradiance or vapour pressure deficit (VPD) variation. Two genotypes of Populus nigra x deltoides were exposed to various treatments for 21 days. Saplings were exposed to 80 ppb/day O3 for 13 days, and then to moderate drought for 7 days. The curves of the stomatal response to irradiance and VPD changes were determined after 13 days of O3 exposure, and after 21 days in the case of subsequent water deficit, and then fitted using a sigmoidal model. The main responses under O3 exposure were stomatal closure and sluggishness, but the two genotypes showed contrasting responses. During stomatal closure induced by a change in irradiance, closure was slower for both genotypes. Nonetheless, the genotypes differed in stomatal opening under light. Carpaccio stomata opened more slowly than control stomata, whereas Robusta stomata tended to open faster. These effects could be of particular interest, as stomatal impairment was still present after O3 exposure and could result from imperfect recovery. Under water deficit alone, we observed slower stomatal closure in response to VPD and irradiance, but faster stomatal opening in response to irradiance, more marked in Carpaccio. Under the combined treatment, most of the parameters showed antagonistic responses. Our results highlight that it is important to take genotype-specific responses and interactive stress cross-talk into account to improve the prediction of stomatal conductance in response to various environmental modifications.

Impact of Meteorological Factors on the Ozone Pollution in Hong Kong

Based on ozone monitoring and meteorological data from 2000 to 2015 in Hong Kong, the characteristics of ozone pollution and the influence of meteorological factors on the ozone pollution were analyzed. The results show that:① A seasonal variation of the ozone concentration in Hong Kong is notable:autumn > spring > winter > summer. Days of ozone exceeding the standard value are concentrated in summer and autumn and rarely occur in winter and spring. ② The annual mean ozone concentration of the maximum daily 8-h average (MDA8) in Hong Kong increases from 2000 to 2015, with an average growth rate of 0.77 μg·(m3·a)-1. The 90th percentile concentration of the ozone MDA8 also increases, with an average rate of 1.49 μg·(m3·a)-1. ③ Higher temperatures are necessary for ozone pollution in Hong Kong. The higher the temperature is, the more ozone pollution likely occurs. ④ In most cases, the ozone concentration is negatively correlated with the relative humidity. The higher the relative humidity is, the lower are the ozone and 90th percentile concentrations in Hong Kong. ⑤ When ozone pollution occurs in Hong Kong, prevailing winds tend to shift from northerly or easterly to westerly. In addition, with the increase of the wind speed, the average ozone concentration changes little, but the 90th percentile ozone concentration significantly decreases. ⑥ Precipitation and cloud cover are important factors affecting the ozone concentration. Weather conditions without or with little rain for many consecutive days are necessary for the occurrence of ozone pollution events. However, with the increase of the cloud cover, the average ozone and 90th percentile concentrations continue to decrease. ⑦ In the case of a total solar radiation ≤ 20 MJ·m-2 or sunshine duration ≤ 10 h, the ozone concentration is positively correlated with the solar radiation and sunshine duration. However, in the case of intense solar radiation (total solar radiation>20 MJ·m-2 or duration of sunshine>10 h), the ozone concentrations decrease with increasing solar radiation or duration because strong solar radiation often occurs in the background of sunny weather after rain. At the same time, southerly winds from the sea often prevail, making it difficult for ozone pollution to occur in Hong Kong. ⑧ Ozone excess days in Hong Kong are often accompanied by changes of a series of meteorological conditions including less rain on sunny days, stronger radiation, higher boundary layer height, lower relative humidity, smaller wind speeds, and higher temperatures. The end of the pollution process is accompanied by the opposite weather changes.

New insight of ozone pollution impact from flare emissions of chemical plant start-up operations

Flaring is a common and necessary operation for chemical industries, which is designed to manage dangerous process overpressure scenarios or to release and destroy off-spec products during chemical plant upsets or turnarounds. However, excessive flaring can emit large quantities of VOCs and NOx into the atmosphere, which will cause transient and localized ozone pollution events in the presence of sunlight. The objective of this study was to quantify the impact to regional air-quality due to flare emissions from chemical plant start-up operations through the coupling of dynamic process simulations via Aspen Plus and air-quality simulations via CAMx. Simulation results from case studies have indicated that the corresponding ozone increments can vary significantly from 0.2 ppb to 17.8 ppb under different temporal and spatial factors, including the start-up starting hour, starting day, and plant location. Additional ozone sensitivity simulations have also indicated that the corresponding ozone increments are higher when the plant is located in a VOC-limited area than that in a NOx-limited area. The results from this study have delivered a cost-effective air-quality control practice for plant start-ups with a minimum air-quality impact through selecting the optimal starting time within the allowable ranges. The practice has significant potential to benefit all stakeholders, including environmental agencies, chemical industries, and local communities.

Characteristics of Atmospheric Boundary Layer Structure during PM2.5 and Ozone Pollution Events in Wuhan, China

In this study, we investigated six air pollutants from 21 monitoring stations scattered throughout Wuhan city by analyzing meteorological variables in the atmospheric boundary layer (ABL) and air mass backward trajectories from HYSPLIT during the pollution events. Together with this, ground meteorological variables were also used throughout the investigation period: 1 December 2015 to 30 November 2016. Analysis results during this period show that the city was polluted in winter by PM2.5 (particulate matter with aerodynamics of less than 2.5 microns) and in summer by ozone (O3). The most polluted day during the investigation period was 25 December 2015 with an air quality index (AQI) of 330 which indicates ‘severe pollution’, while the cleanest day was 26 August 2016 with an AQI of 27 indicating ‘excellent’ air quality. The average concentration of PM2.5 (O3) on the most polluted day was 265.04 (135.82) µg/m3 and 9.10 (86.40) µg/m3 on the cleanest day. Moreover, the percentage of days which exceeded the daily average limit of NO2, PM10, PM2.5, and O3 for the whole year was 2.46%, 14.48%, 23.50%, and 39.07%, respectively, while SO2 and CO were found to be below the set daily limit. The analysis of ABL during PM2.5 pollution events showed the existence of a strong inversion layer, low relative humidity, and calm wind. These observed conditions are not favorable for horizontal and vertical dispersion of air pollutants and therefore result in pollutant accumulation. Likewise, ozone pollution events were accompanied by extended sunshine hours, high temperature, a calm wind, a strongly suspended inversion layer, and zero recorded rainfall. These general characteristics are favorable for photochemical production of ozone and accumulation of pollutants. Apart from the conditions of ABL, the results from backward trajectories suggest trans-boundary movement of air masses to be one of the important factors which determines the air quality of Wuhan.

A data mining framework for environmental and geo-spatial data analysis

Mining geo-spatial data is an important task in many application domains, such as environmental science, geographic information science, and social networks. In this paper, we introduce a data mining framework, which includes pre-processing of environmental and geo-spatial data, geo-spatial data mining techniques, and visual analysis of environmental and geo-spatial data. In particular, we propose new density-based clustering algorithms to identify interesting distribution patterns from geo-spatial data, a change pattern discovery technique to detect dynamic change patterns within spatial clusters, and a post-processing technique to extract interesting patterns and useful knowledge from geo-spatial data. Our density-based clustering algorithms are based on the well-established density-based shared nearest neighbor clustering algorithm, which can find clusters of different shape, size, and densities in high-dimensional data. The post-processing analysis technique allows automatic screening of interesting spatial clusters. The change pattern discovery algorithm is able to detect and analyze dynamic patterns of changes within spatial clusters. This paper focuses on developing a framework integrating a sequence of data mining process including clustering algorithm, analysis technique and pattern changing discovery algorithm. In contrast to previous works in this area, our approaches can cluster and analyze dynamically evolved complex objects, i.e., polygons. We evaluate the effectiveness of our techniques through a challenging real case study involving ozone pollution events in the Houston–Galveston–Brazoria area. The experimental results show that our approaches can discover interesting patterns and useful information from geo-spatial air-quality data.

Impacts of flare emissions from an ethylene plant shutdown to regional air quality

Critical operations of chemical process industry (CPI) plants such as ethylene plant shutdowns could emit a huge amount of VOCs and NOx, which may result in localized and transient ozone pollution events. In this paper, a general methodology for studying dynamic ozone impacts associated with flare emissions from ethylene plant shutdowns has been developed. This multi-scale simulation study integrates process knowledge of plant shutdown emissions in terms of flow rate and speciation together with regional air-quality modeling to quantitatively investigate the sensitivity of ground-level ozone change due to an ethylene plant shutdown. The study shows the maximum hourly ozone increments can vary significantly by different plant locations and temporal factors including background ozone data and solar radiation intensity. It helps provide a cost-effective air-quality control strategy for industries by choosing the optimal starting time of plant shutdown operations in terms of minimizing the induced ozone impact (reduced from 34.1 ppb to 1.2 ppb in the performed case studies). This study provides valuable technical supports for both CPI and environmental policy makers on cost-effective air-quality controls in the future.

A regional air quality forecasting system over Europe: the MACC-II daily ensemble production

Abstract. This paper describes the pre-operational analysis and forecasting system developed during MACC (Monitoring Atmospheric Composition and Climate) and continued in the MACC-II (Monitoring Atmospheric Composition and Climate: Interim Implementation) European projects to provide air quality services for the European continent. This system is based on seven state-of-the art models developed and run in Europe (CHIMERE, EMEP, EURAD-IM, LOTOS-EUROS, MATCH, MOCAGE and SILAM). These models are used to calculate multi-model ensemble products. The paper gives an overall picture of its status at the end of MACC-II (summer 2014) and analyses the performance of the multi-model ensemble. The MACC-II system provides daily 96 h forecasts with hourly outputs of 10 chemical species/aerosols (O3, NO2, SO2, CO, PM10, PM2.5, NO, NH3, total NMVOCs (non-methane volatile organic compounds) and PAN+PAN precursors) over eight vertical levels from the surface to 5 km height. The hourly analysis at the surface is done a posteriori for the past day using a selection of representative air quality data from European monitoring stations. The performance of the system is assessed daily, weekly and every 3 months (seasonally) through statistical indicators calculated using the available representative air quality data from European monitoring stations. Results for a case study show the ability of the ensemble median to forecast regional ozone pollution events. The seasonal performances of the individual models and of the multi-model ensemble have been monitored since September 2009 for ozone, NO2 and PM10. The statistical indicators for ozone in summer 2014 show that the ensemble median gives on average the best performances compared to the seven models. There is very little degradation of the scores with the forecast day but there is a marked diurnal cycle, similarly to the individual models, that can be related partly to the prescribed diurnal variations of anthropogenic emissions in the models. During summer 2014, the diurnal ozone maximum is underestimated by the ensemble median by about 4 μg m−3 on average. Locally, during the studied ozone episodes, the maxima from the ensemble median are often lower than observations by 30–50 μg m−3. Overall, ozone scores are generally good with average values for the normalised indicators of 0.14 for the modified normalised mean bias and of 0.30 for the fractional gross error. Tests have also shown that the ensemble median is robust to reduction of ensemble size by one, that is, if predictions are unavailable from one model. Scores are also discussed for PM10 for winter 2013–1014. There is an underestimation of most models leading the ensemble median to a mean bias of −4.5 μg m−3. The ensemble median fractional gross error is larger for PM10 (~ 0.52) than for ozone and the correlation is lower (~ 0.35 for PM10 and ~ 0.54 for ozone). This is related to a larger spread of the seven model scores for PM10 than for ozone linked to different levels of complexity of aerosol representation in the individual models. In parallel, a scientific analysis of the results of the seven models and of the ensemble is also done over the Mediterranean area because of the specificity of its meteorology and emissions. The system is robust in terms of the production availability. Major efforts have been done in MACC-II towards the operationalisation of all its components. Foreseen developments and research for improving its performances are discussed in the conclusion.

Ground-level ozone in urban Beijing over a 1-year period: Temporal variations and relationship to atmospheric oxidation

Regional ozone pollution has become a major environmental concern in China, especially in densely populated and economically vibrant regions such as North China, including Beijing. To address this issue, surface ozone and its precursors (CO, NO, and NO2) from December 2012 to November 2013 at 12 sites in urban Beijing and 2 sites in suburban Beijing were analyzed. The annual average concentrations of O3, CO, NO, and NO2 in urban Beijing were 45.5±50.2μgm−3, 1.5±1.3mgm−3, 27.3±42.7μgm−3, and 58.3+32.0μgm−3, respectively. The concentration of ozone was highest during summer, whereas concentrations of its precursors were highest during winter. Diurnal variations in ozone presented as a single-peak curve, with the peak appearing at about 15:00–16:00. Diurnal variations in most ozone precursors showed bimodal curves; the first peak appeared at about 08:00–09:00, and the second peak appeared at night. Hourly concentrations of ozone on the weekend were higher than those on weekdays between 11:00 and 24:00 in urban Beijing, which was suggestive of a significant weekend effect. This may be because NO inhibition on the weekend is weaker than that on weekdays during the ozone formation phase. Diurnal variations in OX (NO2+O3) showed a single peak, which appeared at 15:00 or 16:00. The results of correlation analysis among OX, O3, and NO2 suggested that OX was mainly controlled by O3 during the day and by NO2 during the night throughout the year. OX was controlled by NO2 during both the day and night during winter due to the low concentration of O3. The regional transport of ozone along the upwind direction was found in a typical ozone pollution event in summer in Beijing.

Projecting policy‐relevant metrics for high summertime ozone pollution events over the eastern United States due to climate and emission changes during the 21st century

AbstractOver the eastern United States (EUS), nitrogen oxides (NOx) emission controls have led to improved air quality over the past two decades, but concerns have been raised that climate warming may offset some of these gains. Here we analyze the effect of changing emissions and climate, in isolation and combination, on EUS summertime surface ozone (O3) over the recent past and the 21st century in an ensemble of simulations performed with the Geophysical Fluid Dynamics Laboratory CM3 chemistry‐climate model. The simulated summertime EUS O3 is biased high but captures the structure of observed changes in regional O3 distributions following NOx emission reductions. We introduce a statistical bias correction, which allows derivation of policy‐relevant statistics by assuming a stationary mean state bias in the model, but accurate simulation of changes at each quantile of the distribution. We contrast two different 21st century scenarios: (i) representative concentration pathway (RCP) 4.5 and (ii) simulations with well‐mixed greenhouse gases (WMGG) following RCP4.5 but with emissions of air pollutants and precursors held fixed at 2005 levels (RCP4.5_WMGG). We find under RCP4.5 no exceedance of maximum daily 8 hour average ozone above 75 ppb by mid‐21st century, reflecting the U.S. NOx emissions reductions projected in RCP4.5, while more than half of the EUS exceeds this level by the end of the 21st century under RCP4.5_WMGG. Further, we find a simple relationship between the changes in estimated 1 year return levels and regional NOx emission changes, implying that our results can be generalized to estimate changes in the frequency of EUS pollution events under different regional NOx emission scenarios.

Understanding high wintertime ozone pollution events in an oil- and natural gas-producing region of the western US

Abstract. Recent increases in oil and natural gas (NG) production throughout the western US have come with scientific and public interest in emission rates, air quality and climate impacts related to this industry. This study uses a regional-scale air quality model (WRF-Chem) to simulate high ozone (O3) episodes during the winter of 2013 over the Uinta Basin (UB) in northeastern Utah, which is densely populated by thousands of oil and NG wells. The high-resolution meteorological simulations are able qualitatively to reproduce the wintertime cold pool conditions that occurred in 2013, allowing the model to reproduce the observed multi-day buildup of atmospheric pollutants and the accompanying rapid photochemical ozone formation in the UB. Two different emission scenarios for the oil and NG sector were employed in this study. The first emission scenario (bottom-up) was based on the US Environmental Protection Agency (EPA) National Emission Inventory (NEI) (2011, version 1) for the oil and NG sector for the UB. The second emission scenario (top-down) was based on estimates of methane (CH4) emissions derived from in situ aircraft measurements and a regression analysis for multiple species relative to CH4 concentration measurements in the UB. Evaluation of the model results shows greater underestimates of CH4 and other volatile organic compounds (VOCs) in the simulation with the NEI-2011 inventory than in the case when the top-down emission scenario was used. Unlike VOCs, the NEI-2011 inventory significantly overestimates the emissions of nitrogen oxides (NOx), while the top-down emission scenario results in a moderate negative bias. The model simulation using the top-down emission case captures the buildup and afternoon peaks observed during high O3 episodes. In contrast, the simulation using the bottom-up inventory is not able to reproduce any of the observed high O3 concentrations in the UB. Simple emission reduction scenarios show that O3 production is VOC sensitive and NOx insensitive within the UB. The model results show a disproportionate contribution of aromatic VOCs to O3 formation relative to all other VOC emissions. The model analysis reveals that the major factors driving high wintertime O3 in the UB are shallow boundary layers with light winds, high emissions of VOCs from oil and NG operations compared to NOx emissions, enhancement of photolysis fluxes and reduction of O3 loss from deposition due to snow cover.

High winter ozone pollution from carbonyl photolysis in an oil and gas basin.

The United States is now experiencing the most rapid expansion in oil and gas production in four decades, owing in large part to implementation of new extraction technologies such as horizontal drilling combined with hydraulic fracturing. The environmental impacts of this development, from its effect on water quality to the influence of increased methane leakage on climate, have been a matter of intense debate. Air quality impacts are associated with emissions of nitrogen oxides (NOx = NO+NO2) and volatile organic compounds (VOCs), whose photochemistry leads to production of ozone, a secondary pollutant with negative health effects. Recent observations in oil- and gas-producing basins in the western United States have identified ozone mixing ratios well in excess of present air quality standards, but only during winter. Understanding winter ozone production in these regions is scientifically challenging. It occurs during cold periods of snow cover when meteorological inversions concentrate air pollutants from oil and gas activities, but when solar irradiance and absolute humidity, which are both required to initiate conventional photochemistry essential for ozone production, are at a minimum. Here, using data from a remote location in the oil and gas basin of northeastern Utah and a box model, we provide a quantitative assessment of the photochemistry that leads to these extreme winter ozone pollution events, and identify key factors that control ozone production in this unique environment. We find that ozone production occurs at lower NOx and much larger VOC concentrations than does its summertime urban counterpart, leading to carbonyl (oxygenated VOCs with a C = O moiety) photolysis as a dominant oxidant source. Extreme VOC concentrations optimize the ozone production efficiency of NOx. There is considerable potential for global growth in oil and gas extraction from shale. This analysis could help inform strategies to monitor and mitigate air quality impacts and provide broader insight into the response of winter ozone to primary pollutants.

Skill in forecasting extreme ozone pollution episodes with a global atmospheric chemistry model

Abstract. From the ensemble of stations that monitor surface air quality over the United States and Europe, we identify extreme ozone pollution events and find that they occur predominantly in clustered, multiday episodes with spatial extents of more than 1000 km. Such scales are amenable to forecasting with current global atmospheric chemistry models. We develop an objective mapping algorithm that uses the heterogeneous observations of the individual surface sites to calculate surface ozone averaged over 1° by 1° grid cells, matching the resolution of a global model. Air quality extreme (AQX) events are identified locally as statistical extremes of the ozone climatology and not as air quality exceedances. With the University of California, Irvine chemistry-transport model (UCI CTM) we find there is skill in hindcasting these extreme episodes, and thus identify a new diagnostic using global chemistry–climate models (CCMs) to identify changes in the characteristics of extreme pollution episodes in a warming climate.

Ozone pollution: What can we see from space? A case study

Due to its impact on environment, tropospheric ozone received particular attention since several decades. Ground-based networks associated with regional chemical transport models are used to monitor and forecast surface ozone concentrations, but coverage, representativeness, and accuracy issues remain important. Recent satellite observations have demonstrated the capacity to probe tropospheric ozone, but there has been no explicit attempt to quantify their ability to measure ozone pollution near ground. We propose here to assess the ability of ozone sounders to detect a photochemical ozone pollution event that is supposed to be a favorable situation for satellite detection. We have chosen ozone pollution event over Europe associated with a warm conveyor belt that efficiently transports photochemically produced ozone upward. Ozone satellite products from Global Ozone Monitoring Experiment-2, Infrared Atmospheric Sounding Interferometer (IASI), and Ozone Monitoring Instrument are analyzed here for their capacity to capture such an event. Also, in situ observations and regional chemical-transport models show increasing ozone concentrations in the continental and Mediterranean boundary layer and further transport to central Europe and Scandinavia associated with upward transport. Satellite observations do not detect high ozone concentrations within the boundary layer due the weak sensitivity near the surface. Nevertheless, we have shown that the IR sounder IASI was able to detect, qualitatively and quantitatively, the ozone plume transported upward by the warm conveyor belt, suggesting that a quantification of upward transport of ozone pollution could be possible using current satellite observations. This should encourage us to further explore approaches more sensitive to surface ozone (such as the multispectral approach) and to prepare the next generation of still more sensitive spaceborne instruments.

Regional scale ozone data assimilation using an ensemble Kalman filter and the CHIMERE chemical transport model

Abstract. An ensemble Kalman filter (EnKF) has been coupled to the CHIMERE chemical transport model in order to assimilate ozone ground-based measurements on a regional scale. The number of ensembles is reduced to 20, which allows for future operational use of the system for air quality analysis and forecast. Observation sites of the European ozone monitoring network have been classified using criteria on ozone temporal variability, based on previous work by Flemming et al. (2005). This leads to the choice of specific subsets of suburban, rural and remote sites for data assimilation and for evaluation of the reference run and the assimilation system. For a 10-day experiment during an ozone pollution event over Western Europe, data assimilation allows for a significant improvement in ozone fields: the RMSE is reduced by about a third with respect to the reference run, and the hourly correlation coefficient is increased from 0.75 to 0.87. Several sensitivity tests focus on an a posteriori diagnostic estimation of errors associated with the background estimate and with the spatial representativeness of observations. A strong diurnal cycle of both these errors with an amplitude up to a factor of 2 is made evident. Therefore, the hourly ozone background error and the observation error variances are corrected online in separate assimilation experiments. These adjusted background and observational error variances provide a better uncertainty estimate, as verified by using statistics based on the reduced centered random variable. Over the studied 10-day period the overall EnKF performance over evaluation stations is found relatively unaffected by different formulations of observation and simulation errors, probably due to the large density of observation sites. From these sensitivity tests, an optimal configuration was chosen for an assimilation experiment extended over a three-month summer period. It shows a similarly good performance as the 10-day experiment.

A polygon-based clustering and analysis framework for mining spatial datasets

Polygons provide natural representations for many types of geospatial objects, such as countries, buildings, and pollution hotspots. Thus, polygon-based data mining techniques are particularly useful for mining geospatial datasets. In this paper, we propose a polygon-based clustering and analysis framework for mining multiple geospatial datasets that have inherently hidden relations. In this framework, polygons are first generated from multiple geospatial point datasets by using a density-based contouring algorithm called DCONTOUR. Next, a density-based clustering algorithm called Poly-SNN with novel dissimilarity functions is employed to cluster polygons to create meta-clusters of polygons. Finally, post-processing analysis techniques are proposed to extract interesting patterns and user-guided summarized knowledge from meta-clusters. These techniques employ plug-in reward functions that capture a domain expert's notion of interestingness to guide the extraction of knowledge from meta-clusters. The effectiveness of our framework is tested in a real-world case study involving ozone pollution events in Texas. The experimental results show that our framework can reveal interesting relationships between different ozone hotspots represented by polygons; it can also identify interesting hidden relations between ozone hotspots and several meteorological variables, such as outdoor temperature, solar radiation, and wind speed.

The effect of using limited scene-dependent averaging kernels approximations for the implementation of fast observing system simulation experiments targeted on lower tropospheric ozone

Abstract. Practical implementations of chemical OSSEs (Observing System Simulation Experiments) usually rely on approximations of the pseudo-observations by means of a predefined parametrization of the averaging kernels, which describe the sensitivity of the observing system to the target atmospheric species. This is intended to avoid the use of a computationally expensive pseudo-observations simulator, that relies on full radiative transfer calculations. Here we present an investigation on how no, or limited, scene dependent averaging kernels parametrizations may misrepresent the sensitivity of an observing system. We carried out the full radiative transfer calculation for a three-days period over Europe, to produce reference pseudo-observations of lower tropospheric ozone, as they would be observed by a concept geostationary observing system called MAGEAQ (Monitoring the Atmosphere from Geostationary orbit for European Air Quality). The selected spatio-temporal interval is characterised by an ozone pollution event. We then compared our reference with approximated pseudo-observations, following existing simulation exercises made for both the MAGEAQ and GEOstationary Coastal and Air Pollution Events (GEO-CAPE) missions. We found that approximated averaging kernels may fail to replicate the variability of the full radiative transfer calculations. In addition, we found that the approximations substantially overestimate the capability of MAGEAQ to follow the spatio-temporal variations of the lower tropospheric ozone in selected areas, during the mentioned pollution event. We conclude that such approximations may lead to false conclusions if used in an OSSE. Thus, we recommend to use comprehensive scene-dependent approximations of the averaging kernels, in cases where the full radiative transfer is computationally too costly for the OSSE being investigated.

Surface ozone variability and the jet position: Implications for projecting future air quality

Changes in the variability of surface ozone can affect the incidence of ozone pollution events. Analysis of multi‐century simulations from a chemistry climate model shows that present‐day summertime variability of surface ozone depends strongly on the jet stream position over eastern North America. This relationship holds on decadal time scales under projected climate change scenarios, in which surface ozone variability follows the robust poleward shift of the jet. The correlation between ozone and co‐located temperature over eastern North America is also closely tied to the jet position, implying that local ozone‐temperature relationships may change as the circulation changes. Jet position can thus serve as a dynamical predictor of future surface ozone variability over eastern North America and may also modulate ozone variability in other northern midlatitude regions.

Changes in the frequency and return level of high ozone pollution events over the eastern United States following emission controls

In order to quantify the impact of recent efforts to abate surface ozone (O3) pollution, we analyze changes in the frequency and return level of summertime (JJA) high surface O3 events over the eastern United States (US) from 1988–1998 to 1999–2009. We apply methods from extreme value theory (EVT) to maximum daily 8-hour average ozone (MDA8 O3) observed by the Clean Air Status and Trends Network (CASTNet) and define O3 extremes as days on which MDA8 O3 exceeds a threshold of 75 ppb (MDA8 O3>75). Over the eastern US, we find that the number of summer days with MDA8 O3>75 declined on average by about a factor of two from 1988–1998 to 1999–2009. The applied generalized Pareto distribution (GPD) fits the high tail of MDA8 O3 much better than a Gaussian distribution and enables the derivation of probabilistic return levels (describing the probability of exceeding a value x within a time window T) for high O3 pollution events. This new approach confirms the significant decline in both frequency and magnitude of high O3 pollution events over the eastern US during recent years reported in prior studies. Our analysis of 1-yr and 5-yr return levels at each station demonstrates the strong impact of changes in air quality regulations and subsequent control measures (e.g., the ‘NOx SIP Call’), as the 5-yr return levels of the period 1999–2009 correspond roughly to the 1-yr return levels of the earlier time period (1988–1998). Regionally, the return levels dropped between 1988–1998 and 1999–2009 by about 8 ppb in the Mid-Atlantic (MA) and Great Lakes (GL) regions, while the strongest decline, about 13 ppb, is observed in the Northeast (NE) region. Nearly all stations (21 out of 23) have 1-yr return levels well below 100 ppb and 5-yr return levels well below 110 ppb in 1999–2009. Decreases in eastern US O3 pollution are largest after full implementation of the nitrogen oxide (NOx) reductions under the ‘NOx SIP Call’. We conclude that the application of EVT methods provides a useful approach for quantifying return levels of high O3 pollution in probabilistic terms, which may help to guide long-term air quality planning.

North Atlantic Oscillation and tropospheric ozone variability in Europe: model analysis and measurements intercomparison

Abstract. Ozone pollution represents a serious health and environmental problem. While ozone pollution is mostly produced by photochemistry in summer, elevated ozone concentrations can also be influenced by long range transport driven by the atmospheric circulation and stratospheric ozone intrusions. We analyze the role of large scale atmospheric circulation variability in the North Atlantic basin in determining surface ozone concentrations over Europe. Here, we show, using ground station measurements and a coupled atmosphere-chemistry model simulation for the period 1980–2005, that the North Atlantic Oscillation (NAO) does affect surface ozone concentrations – on a monthly timescale, over 10 ppbv in southwestern, central and northern Europe – during all seasons except fall. The commonly used NAO index is able to capture the link existing between atmospheric dynamics and surface ozone concentrations in winter and spring but it fails in summer. We find that the first Principal Component, computed from the time variation of the sea level pressure (SLP) field, detects the atmosphere circulation/ozone relationship not only in winter and spring but also during summer, when the atmospheric circulation weakens and regional photochemical processes peak. Given the NAO forecasting skill at intraseasonal time scale, the first Principal Component of the SLP field could be used as an indicator to identify areas more exposed to forthcoming ozone pollution events. Finally, our results suggest that the increasing baseline ozone in western and northern Europe during the 1990s could be related to the prevailing positive phase of the NAO in that period.

Transport of Asian ozone pollution into surface air over the western United States in spring

Many prior studies clearly document episodic Asian pollution in the western U.S. free troposphere. Here, we examine the mechanisms involved in the transport of Asian pollution plumes into western U.S. surface air through an integrated analysis of in situ and satellite measurements in May–June 2010 with a new global high‐resolution (∼50 × 50 km2) chemistry‐climate model (GFDL AM3). We find that AM3 with full stratosphere‐troposphere chemistry nudged to reanalysis winds successfully reproduces observed sharp ozone gradients above California, including the interleaving and mixing of Asian pollution and stratospheric air associated with complex interactions of midlatitude cyclone air streams. Asian pollution descends isentropically behind cold fronts; at ∼800 hPa a maximum enhancement to ozone occurs over the southwestern U.S., including the densely populated Los Angeles Basin. During strong episodes, Asian emissions can contribute 8–15 ppbv ozone in the model on days when observed daily maximum 8‐h average ozone (MDA8 O3) exceeds 60 ppbv. We find that in the absence of Asian anthropogenic emissions, 20% of MDA8 O3exceedances of 60 ppbv in the model would not have occurred in the southwestern USA. For a 75 ppbv threshold, that statistic increases to 53%. Our analysis indicates the potential for Asian emissions to contribute to high‐O3episodes over the high‐elevation western USA, with implications for attaining more stringent ozone standards in this region. We further demonstrate a proof‐of‐concept approach using satellite CO column measurements as a qualitative early warning indicator to forecast Asian ozone pollution events in the western U.S. with lead times of 1–3 days.