Modeled Ozone Concentrations Research Articles

Dynamic evaluation of modeled ozone concentrations in Germany with four chemistry transport models

Simulating the ozone variability at regional scales using chemistry transport models (CTMs) remains a challenge. We designed a multi-model intercomparison to evaluate, for the first time, four regional CTMs on a national scale for Germany. Simulations were conducted with LOTOS-EUROS, REM-CALGRID, COSMO-MUSCAT and WRF-Chem for January 1st to December 31st, 2019, using prescribed emission information. In general, all models show good performance in the operational evaluation with average temporal correlations of MDA8 O3 in the range of 0.77–0.87 and RMSE values between 16.3 μg m−3 and 20.6 μg m−3. On average, better models' skill has been observed for rural background stations than for the urban background stations as well as for springtime compared to summertime. Our study confirms that the ensemble mean provides a better model-measurement agreement than individual models. All models capture the larger local photochemical production in summer compared to springtime and observed differences between the urban and the rural background. We introduce a new indicator to evaluate the dynamic response of ozone to temperature. During summertime a large ensemble spread in the ozone sensitivities to temperature is found with (on average) an underestimation of the ozone sensitivity to temperature, which can be linked to a systematic underestimation of mid-level ozone concentrations. During springtime we observed an ozone episode that is not covered by the models which is likely due to deficiencies in the representation of background ozone in the models. We recommend to focus on a diagnostic evaluation aimed at the model descriptions for biogenic emissions and dry deposition as a follow up and to repeat the operational and dynamic analysis for longer timeframes.

Reductions in crop yields across China from elevated ozone

Exposure of crops to high concentrations of ozone can cause substantial reductions in yield that pose a serious threat to global food security. Here we provide comprehensive estimates of yield losses for key crops across China between 2014 and 2017 attributed to ozone using a number of new approaches. We use an air quality model at 5 km resolution and crop-specific dose-response functions developed for both concentration- and flux-based metrics. We bias correct modelled ozone concentrations and metrics using observations from more than 1000 locations. We find that on a 4-year average basis, production losses of key crops are 34–91 million metric tonnes (Mt/yr), dependent on the approach used, with highest losses in Henan province. At a national level, loss of winter wheat production derived using a China-specific dose-response function increased by 82% from 2014 to 2017, with large interannual variations in the North China Plain and in eastern China. Winter wheat losses estimated using flux-based functions, which require robust simulation of stomatal conductance and underlying vegetation physiology, are significantly lower, at 30 Mt/yr. We show that the definition of the growing season may have a greater impact on estimated losses than small biases in ozone surface concentrations. Although uncertainties remain, our findings demonstrate that increasing ozone concentrations have substantial adverse impacts on crop yields and threaten food security in China. It is important to control ozone concentrations to mitigate these negative impacts.

Air quality and source apportionment modeling of year 2017 ozone episodes in Albuquerque/Bernalillo County, New Mexico

ABSTRACT Albuquerque/Bernalillo County, New Mexico, is currently in attainment of the 2015 National Ambient Air Quality Standard (NAAQS) for ozone (70 ppb), but its ozone design values have increased in recent years. Air quality and source apportionment modeling with the Comprehensive Air Quality Model with Extensions (CAMx) was conducted for Albuquerque/Bernalillo County to develop a refined understanding of ozone source apportionment in the region, estimate ozone concentrations in the year 2025 based on projected changes in anthropogenic emissions, and evaluate the sensitivity of future ozone concentrations to various changes in local and non-local emissions. The study focused on two ozone episodes during June and July 2017 when 8-hr average ozone concentrations were greater than 70 ppb. Based on the modeling results, ozone during the June 2017 episode was found to be driven largely by contributions from non-local and regional emissions, whereas ozone during the July 2017 episode was driven more strongly by local emissions from within Albuquerque/Bernalillo County. On high ozone days, anthropogenic emissions from within Albuquerque/Bernalillo County contributed between 8% and 19% (6–14 ppb) of total ozone. Half of this local ozone contribution was from on-road mobile sources. Fire emissions contributed as much as 2 ppb of ozone on a given day. Contributions from large power plants in New Mexico were as large as 1 ppb on a given day but less than 0.5 ppb on most days. Modeled ozone concentrations in Albuquerque/Bernalillo County were also sensitive to emissions from oil and gas emissions in New Mexico. If projected emission reductions by 2025 materialize, these reductions could reduce future peak 8-hr average ozone concentrations by as much as 3–4% compared to 2017 values. Implications: The results of this study have important implications for air quality management in Albuquerque/Bernalillo County. Ozone in Albuquerque/Bernalillo County is the result of local and non-local emissions, is impacted by wildfires, and is sensitive to statewide oil and gas emissions. The magnitude of modeled contributions from anthropogenic emissions within Albuquerque/Bernalillo County is strongly influenced by meteorological conditions, transport pathways, and the presence of wildfire. This modeling is important for understanding the potential effectiveness of local emission controls in Albuquerque/Bernalillo County, and can serve as a basis for testing future regional and local emission control options.

Update and evaluation of the ozone dry deposition in Oslo CTM3 v1.0

Abstract. High concentrations of ozone in ambient air are hazardous not only to humans but to the ecosystem in general. The impact of ozone damage on vegetation and agricultural plants in combination with advancing climate change may affect food security in the future. While the future scenarios in themselves are uncertain, there are limiting factors constraining the accuracy of surface ozone modeling also at present: the distribution and amount of ozone precursors and ozone-depleting substances, the stratosphere–troposphere exchange, as well as scavenging processes. Removal of any substance through gravitational settling or by uptake by plants and soil is referred to as dry deposition. The process of dry deposition is important for predicting surface ozone concentrations and understanding the observed amount and increase of tropospheric background ozone. The conceptual dry deposition velocities are calculated following a resistance-analogous approach, wherein aerodynamic, quasi-laminar, and canopy resistance are key components, but these are hard to measure explicitly. We present an update of the dry deposition scheme implemented in Oslo CTM3. We change from a purely empirical dry deposition parameterization to a more process-based one which takes the state of the atmosphere and vegetation into account. We examine the sensitivity of the scheme to various parameters, e.g., the stomatal conductance-based description of the canopy resistance and the choice of ozone surface resistance, and evaluate the resulting modeled ozone dry deposition with respect to observations and multi-model studies. Individual dry deposition velocities are now available for each land surface type and agree generally well with observations. We also estimate the impact on the modeled ozone concentrations at the surface. We show that the global annual total ozone dry deposition decreases with respect to the previous model version (−37 %), leading to an increase in surface ozone of more than 100 % in some regions. While high sensitivity to changes in dry deposition to vegetation is found in the tropics and the Northern Hemisphere, the largest impact on global scales is associated with the choice of prescribed ozone surface resistance over the ocean and deserts.

The Variability of Ozone Sensitivity to Anthropogenic Emissions with Biogenic Emissions Modeled by MEGAN and BEIS3

In this study, we examined how modeled ozone concentrations respond to changes in anthropogenic emissions when different modeled emissions of biogenic volatile organic compounds (BVOCs) are used. With biogenic emissions estimated by the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and the Biogenic Emissions Inventory System Version 3 (BEIS3), the Community Multi-scale Air Quality with the High-order Direct Decouple Method (CMAQ-HDDM) simulations were conducted to acquire sensitivity coefficients. For the case study, we chose 17–26 August 2007, when the Southern Korean peninsula experienced region-wide ozone standard exceedances. The results show that modeled local sensitivities of ozone to anthropogenic emissions in certain NOx-saturated places can differ significantly depending on the method used to estimate BVOC emission, with an opposite trend of ozone changes alongside NOx reductions often shown in model runs using MEGAN and BEIS3. Findings of increased ozone concentrations with one model and decreased ozone concentrations with the other model implies that estimating BVOCs emissions is an important element in predicting variability in ozone concentration and determining the responses of ozone concentrations to emission changes, a discovery that may lead to different policy decisions related to air quality improvement. Quantitatively, areas in the 3-km modeling domain that experienced daily maximum one-hour ozone concentrations greater than 120 ppb (MDA1O3) showed differences of over 20 ppb in MDA1O3 values between model runs with MEGAN and BEIS3. For selected monitoring sites, the maximum difference in relative daily maximum eight-hour ozone concentrations (MDA8O3) response between the methods to model BVOCs was 4.2 ppb in MDA8O3 when we adopted a method similar to the Relative Reduction Factor used by the US Environmental Protection Agency (EPA).

Validation of gas phase chemistry in the WRF-Chem model over Europe

Abstract. This work presents the evaluation of the WRF-Chem model applied for a European domain over the year 2008 and employing two different chemical modules. Airbase European station data and E-OBS database are used for validation of the simulated meteorological conditions as well as concentrations of NO2, SO2 and ozone. In both experiments, underestimation of the amplitude of temperature daily cycle (by about 1 °C) and precipitation overestimation (by about 25 %) were found, with possible impact on chemistry processes due to increased removal via wet deposition. The modelled ozone concentrations match the observations quite well, while the simulated concentrations of other gases show highly negative bias.

Influence of Different Foreign Emissions Inventories on Simulated, Ground-Level Ozone in the Seoul Metropolitan Area during May 2014

ABSTRACTThis study examines the effects of different foreign anthropogenic emissions inventories on predicted ozone concentrations in the Seoul Metropolitan Area (SMA), South Korea, and estimates changes in ozone due to emissions reductions. We ran the Community Multi-Scale Air Quality (CMAQ) model using the High-Order Decoupled Direct Method with three inventories of foreign anthropogenic emissions: (1) the Intercontinental Chemical Transport Experiment, Phase B (INTEX-B) 2006; (2) the Comprehensive Regional Emissions inventory for Atmospheric Transport Experiment (CREATE) 2010; and (3) the Model Inter-Comparison Study (MICS)-Asia 2010. All three inventories have different spatial distributions of emissions, yielding different modeled ozone concentrations. However, the ozone concentrations modeled for the SMA differ less than those modeled for large, foreign cities in the modeling domain. The simulations using INTEX-B 2006 and CREATE 2010 suggested greater reduction in ozone with NOx control than with VOCs control. All simulations show that (1) simultaneous reduction in NOx and VOCs leads to less ozone reduction than the sum of ozone reductions for individual NOx and VOCs controls and (2) ozone reductions are stronger for high ozone days than for low ozone days. Comparing the modeled reductions in the relative sense yields smaller differences between high and low ozone days than comparing the modeled reductions in the absolute sense. With a 20% reduction in only NOx emissions, the differences in MDA1O3 among the three inventories were between 0.3 and 0.7 ppb. Because air-quality planning often leads to defined tonnage reductions, we examined the model’s response to such a defined emissions reduction. Using the NOx reduction in China estimated by Zhao et al. (2013), we estimated that the differences in MDA1O3 among the three inventories were between 1.50 and 1.78 ppb. Based on these results, we recommend using different foreign anthropogenic emissions inventories to test future scenarios for air-quality control

A Bayesian model for quantifying the change in mortality associated with future ozone exposures under climate change.

Climate change is expected to have many impacts on the environment, including changes in ozone concentrations at the surface level. A key public health concern is the potential increase in ozone-related summertime mortality if surface ozone concentrations rise in response to climate change. Although ozone formation depends partly on summertime weather, which exhibits considerable inter-annual variability, previous health impact studies have not incorporated the variability of ozone into their prediction models. A major source of uncertainty in the health impacts is the variability of the modeled ozone concentrations. We propose a Bayesian model and Monte Carlo estimation method for quantifying health effects of future ozone. An advantage of this approach is that we include the uncertainty in both the health effect association and the modeled ozone concentrations. Using our proposed approach, we quantify the expected change in ozone-related summertime mortality in the contiguous United States between 2000 and 2050 under a changing climate. The mortality estimates show regional patterns in the expected degree of impact. We also illustrate the results when using a common technique in previous work that averages ozone to reduce the size of the data, and contrast these findings with our own. Our analysis yields more realistic inferences, providing clearer interpretation for decision making regarding the impacts of climate change.

Climate-forced air-quality modeling at the urban scale: sensitivity to model resolution, emissions and meteorology

Abstract. While previous research helped to identify and prioritize the sources of error in air-quality modeling due to anthropogenic emissions and spatial scale effects, our knowledge is limited on how these uncertainties affect climate-forced air-quality assessments. Using as reference a 10-year model simulation over the greater Paris (France) area at 4 km resolution and anthropogenic emissions from a 1 km resolution bottom-up inventory, through several tests we estimate the sensitivity of modeled ozone and PM2.5 concentrations to different potentially influential factors with a particular interest over the urban areas. These factors include the model horizontal and vertical resolution, the meteorological input from a climate model and its resolution, the use of a top-down emission inventory, the resolution of the emissions input and the post-processing coefficients used to derive the temporal, vertical and chemical split of emissions. We show that urban ozone displays moderate sensitivity to the resolution of emissions (~ 8 %), the post-processing method (6.5 %) and the horizontal resolution of the air-quality model (~ 5 %), while annual PM2.5 levels are particularly sensitive to changes in their primary emissions (~ 32 %) and the resolution of the emission inventory (~ 24 %). The air-quality model horizontal and vertical resolution have little effect on model predictions for the specific study domain. In the case of modeled ozone concentrations, the implementation of refined input data results in a consistent decrease (from 2.5 up to 8.3 %), mainly due to inhibition of the titration rate by nitrogen oxides. Such consistency is not observed for PM2.5. In contrast this consistency is not observed for PM2.5. In addition we use the results of these sensitivities to explain and quantify the discrepancy between a coarse (~ 50 km) and a fine (4 km) resolution simulation over the urban area. We show that the ozone bias of the coarse run (+9 ppb) is reduced by ~ 40 % by adopting a higher resolution emission inventory, by 25 % by using a post-processing technique based on the local inventory (same improvement is obtained by increasing model horizontal resolution) and by 10 % by adopting the annual emission totals of the local inventory. The bias of PM2.5 concentrations follows a more complex pattern, with the positive values associated with the coarse run (+3.6 μg m−3), increasing or decreasing depending on the type of the refinement. We conclude that in the case of fine particles, the coarse simulation cannot selectively incorporate local-scale features in order to reduce its error.

Investigating the impact on modeled ozone concentrations using meteorological fields from WRF with an updated four–dimensional data assimilation approach

The four–dimensional data assimilation (FDDA) technique in the Weather Research and Forecasting (WRF) meteorological model has recently undergone an important update from the original version. Previous evaluation results have demonstrated that the updated FDDA approach in WRF provides more accurate wind fields aloft than the original approach, particularly during the nocturnal period when low level jets are a common feature in the Eastern United States. Due to the importance of WRF/FDDA meteorological fields in retrospective air quality applications, a modeling study with the Community Multiscale Air Quality (CMAQ) model was undertaken to ascertain if the improved wind flow fields translate into better performance for ozone. To undertake this objective, separate CMAQ model simulations were performed with meteorological inputs generated by WRF using the original and the updated FDDA approaches for a three month summer period. The evaluation effort focused on observed and modeled surface ozone from a mid–morning hour (10 local daylight time (LDT)). Comparisons of modeled results against concentrations aloft from an instrumented tall tower and from available morning vertical profile measurements were also examined. Surface concentrations near 10 LDT are desirable for evaluating the transport process since they are often representative of ozone that has been transported aloft overnight and has undergone downward entrainment in response to convective mixing the following morning. Statistical results from surface observed and modeled concentration pairs indicated modeled ozone from the CMAQ simulation using the updated FDDA meteorology displayed smaller biases and lower absolute errors at 88% and 80% of monitoring sites, respectively, in the Eastern United States. The CMAQ results with the updated FDDA generally exhibited smaller biases and lower absolute errors at monitoring sites across the northern states than in the southeastern states. The results provide evidence that the more accurate wind flows generated with the updated WRF/FDDA approach improved CMAQ model performance based on the statistical results from 10 LDT ozone concentrations.

동북아 장거리 수송 과정에서 적운 모수화 및 미세물리과정이 오존 모사농도에 미치는 영향 연구

This study has been carried out to analyze the sensitivity of ozone concentrations by employing different options of cumulus parameterization schemes (CPSs) and microphysics schemes in MM5 models. These sensitivity tests were applied to long-range transport case of higher ozone over Northeast Asia. Employed CPS schemes are Betts-Miller (BM), Grell (GR), Kain-Fritsch2 (KF2), Anthes-Kuo (AK), None scheme (grid scale physics only), and four microphysics used here are Simple ice, Reisner1, Reisner2, Schultz scheme in MM5. We chose two cases of high ozone long range transport case by employing both concentrations ozone level and backward trajectory model. The results showed that modeled ozone concentrations indicated about 10% differences among CPSs. Of the all options, GR and KF2 (for CPS), and Rersiner-1 and Resiner-2 (for microphysics) showed relatively good and stable variations against ensemble mean values. For both CPS and microphysics schemes, the difference of precipitation arising from different parameterization schemes was significant by itself, but the resultant ozone variations showed only marginal. But the cloud fraction differences arising from different parameterization schemes showed better correlation with ozone variations than precipitation differences, indicating that the photochemical ozone generation variations is more dominant by cloud fraction than wet removal process for high and long-ranged transported ozone cases over Northeast Asia.

Uncertainty Analysis of Ozone Formation and Response to Emission Controls Using Higher-Order Sensitivities

Understanding ozone response to its precursor emissions is crucial for effective air quality management practices. This nonlinear response is usually simulated using chemical transport models, and the modeling results are affected by uncertainties in emissions inputs. In this study, a high ozone episode in the southeastern United States is simulated using the Community Multiscale Air Quality (CMAQ) model. Uncertainties in ozone formation and response to emissions controls due to uncertainties in emission rates are quantified using the Monte Carlo method. Instead of propagating emissions uncertainties through the original CMAQ, a reduced form of CMAQ is formulated using directly calculated first- and second-order sensitivities that capture the nonlinear ozone concentration-emission responses. This modification greatly reduces the associated computational cost. Quantified uncertainties in modeled ozone concentrations and responses to various emissions controls are much less than the uncertainties in emissions inputs. Average uncertainties in modeled ozone concentrations for the Atlanta area are less than 10% (as measured by the inferred coefficient of variance [ICOV]) even when emissions uncertainties are assumed to vary between a factor of 1.5 and 2. Uncertainties in the ozone responses generally decrease with increased emission controls. Average uncertainties (ICOV) in emission-normalized ozone responses range from 4 to 22%, with the smaller being associated with controlling of the relatively certain point nitrogen oxide (NOx) emissions and the larger resulting from controlling of the less certain mobile NOx emissions. These small uncertainties provide confidence in the model applications, such as in performance evaluation, attainment demonstration, and control strategy development.

Regional‐Scale Ozone Deposition to North‐East Atlantic Waters

A regional climate model is used to evaluate dry deposition of ozone over the North East Atlantic. Results are presented for a deposition scheme accounting for turbulent and chemical enhancement of oceanic ozone deposition and a second non‐chemical, parameterised gaseous dry deposition scheme. The first deposition scheme was constrained to account for sea‐surface ozone‐iodide reactions and the sensitivity of modelled ozone concentrations to oceanic iodide concentration was investigated. Simulations were also performed using nominal reaction rate derived from in-situ ozone deposition measurements and using a preliminary representation of organic chemistry. Results show insensitivity of ambient ozone concentrations modelled by the chemical‐enhanced scheme to oceanic iodide concentrations, and iodide reactions alone cannot account for observed deposition velocities. Consequently, we suggest a missing chemical sink due to reactions of ozone with organic matter at the air‐sea interface. Ozone loss rates are estimated to be in the range of 0.5–6 ppb per day. A potentially significant ozone‐driven flux of iodine to the atmosphere is estimated to be in the range of 2.5–500 M molec cm−2 s−1, leading to a mixing‐layer enhancement of organo‐iodine concentrations of 0.1–22.0 ppt, with an average increase in the N.E. Atlantic of around 4 ppt per day.

Applications of satellite remote sensing data for estimating dry deposition in eastern Texas

The sensitivity of dry deposition velocities and air quality model predictions to land use/land cover (LULC) is examined. Four LULC data sets are employed; three of the data sets are derived from recent satellite imagery and the fourth data set is the LULC database currently used in air quality models by the State of Texas. Effects of the land cover data on estimates of dry deposition velocities and modeled ozone concentrations are examined using the Comprehensive Air Quality Model with extensions (CAMx) during an 22 August 2000–6 September 2000 episode developed for the Houston/Galveston area. All land cover data sets showed good general agreement with a few significant differences in classification and spatial extent of certain land cover categories. Dry deposition decreased in urban areas with the new land cover data during peak hours on some days, leading to ozone concentrations that were approximately 2 ppb higher in the Houston area. Ozone concentrations were lower west of Houston due to increased stomatal uptake by increased agricultural land coverage in the new data sets. These results indicate that the satellite-based LULC data, specifically the data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, can be used to provide periodic updates to land cover information used in CAMx and similar photochemical models.

Evaluation of long-term ozone simulations from seven regional air quality models and their ensemble

Long-term ozone simulations from seven regional air quality models, the Unified EMEP model, LOTOS-EUROS, CHIMERE, RCG, MATCH, DEHM and TM5, are intercompared and compared to ozone measurements within the framework of the EuroDelta experiment, designed to assess air quality improvement at the European scale in response to emission reduction scenarios for 2020. Modelled ozone concentrations for the year 2001 are evaluated. The models reproduce the main features of the ozone diurnal cycle, but generally overestimate daytime ozone. LOTOS-EUROS and RCG have a more pronounced diurnal cycle variation than observations, while the reverse occurs for TM5. CHIMERE has a large positive bias, which can be explained by a systematic bias in boundary conditions. The other models and the “ensemble model”, whose concentrations are by definition averaged over all models, represent accurately the diurnal cycle. The ability of the models to simulate day-to-day daily ozone average or maxima variability is examined by means of percentiles, root mean square errors and correlations. In general, daily maxima are better simulated than daily averages, and summertime concentrations are better simulated than wintertime concentrations. Summertime correlations range between 0.5 and 0.7 for daily averages and 0.6 and 0.8 for daily maxima. Two health-related indicators are used, the number of days of exceedance of the 120 μ g m - 3 threshold for the daily maximal 8-h ozone concentration and the SOMO35. Both are well reproduced in terms of frequency, but the simultaneity of occurrence of exceedance days between observations and simulations is not well captured. The advantage of using an ensemble of models instead of a single model for the assessment of air quality is demonstrated. The ensemble average concentrations almost always exhibit a closer proximity to observations than any of the models. We also show that the spread of the model ensemble is fairly representative of the uncertainty in the simulations.

Preliminary assessment of risk of ozone impacts to maize ( Zea mays) in southern Africa

Surface ozone concentrations in southern Africa exceed air quality guidelines set to protect agricultural crops. This paper addresses a knowledge gap by performing a preliminary assessment of potential ozone impacts on vegetation in southern African. Maize ( Zea mays L.) is the receptor of interest in the main maize producing countries, i.e. South Africa, Zambia and Zimbabwe. Surface ozone concentrations are estimated for the growing season (October to April) using photochemical modelling. Hourly mean modelled ozone concentrations ranged between 19.7 and 31.2 ppb, while maximums range between 28.9 and 61.9 ppb, and are near 30 ppb over South Africa and Zambia, while in Zimbabwe, they exceed 40 ppb and translate into monthly AOT40 values of over 3000 ppb h in five of the seven months of the growing season. This study suggests that surface ozone may pose a threat to agricultural production in southern African, particularly in Zimbabwe.

Measurement of actinic flux and the calculation of photolysis rate parameters for the Central California Ozone Study

The field measurement program of the Central California Ozone Study (CCOS) was conducted during the summer of 2000 with an overall goal of improving the understanding of ozone formation over central and northern California. Measurements of actinic flux were made as part of the study using spectroradiometers located at University of California, Davis; Sunol, California, and the Desert Research Institute in Reno, Nevada. The measured actinic flux was compared with the standard Peterson flux for a high ozone episode that occurred at the end of July. The standard Peterson flux was found to be greater than the measured flux across the spectral range. The measured actinic flux was used, along with standard quantum yields and absorption cross-section data to calculate the photolysis rate parameters for nitrogen dioxide, ozone and formaldehyde, and a radiative transfer model was used to simulate these same photolysis rate parameters. The simulated photolysis rate parameters for nitrogen dioxide could be up to 56% greater than the photolysis rate parameters derived from the measured actinic flux; for ozone the difference was as great as 160%; for the molecular reaction of formaldehyde the difference was as great as 89%; and for the radical producing channel the difference was as great as 126%. A simple atmospheric chemistry box-model was used to estimate the significance of these differences for air quality assessment. For a typical high ozone episode day 31 July, differences between modeled ozone concentrations based on photolysis rate parameters versus those derived from measured actinic flux were less than 7% change in concentration, while differences in HO concentrations were as high as 15%.

Chemical processes in a young biomass‐burning plume

The photochemistry in young biomass‐burning plumes depends on the emissions from the fire and their mixing with the background atmosphere as well as on the actinic flux. In the present study a three‐dimensional plume model is used to investigate the photochemical evolution of a biomass‐burning plume during the first tens of minutes after the fire emissions have been released into the atmosphere. The model results represent the evolution of the plume from the Quinault prescribed fire conducted during the Smoke, Cloud, and Radiation‐C (SCAR‐C) experiment. The modeled ozone concentrations of about 70 ppb are close to observations. The main nitrogen reservoir species downwind of the fire are HNO3and peroxyacetyl nitrate, accounting for about ∼60% and ∼30% of the total nitrogen reservoir species, respectively. Photolysis of formaldehyde, which is emitted from the fire, is the primary source of radicals in the plume. Omitting the emissions of oxygenated volatile organic compounds in the modeled fire plume leads to unrealistically low ozone concentrations in the simulations. A nonabsorbing aerosol as well as the lower emission of NOxin the simulations enhance the radical concentration, the photochemical ozone formation, and the oxidation efficiency, at least at the timescales considered here. Further investigations of the atmospheric processes in young biomass‐burning plumes will increase our understanding of the interaction of transport and chemical processes not only in biomass‐burning plumes but also in other convective systems.

Data assimilation of ozone in the atmospheric transport chemistry model LOTOS

Modelled ozone concentrations often differ from measured concentrations quite substantially, partly due to measurement errors, but mainly due to uncertainties in the model. Modelling studies would therefore benefit highly from more reliable model simulations. One way to achieve this is the application of data assimilation, a technique that uses measurement information within the model simulation in a way that is consistent with the model itself. This aim of this paper is to show that this is indeed one way to go with atmospheric transport chemistry models (ATCMs) by presenting results of data assimilation simulations of ozone with the model LOTOS. The assimilation technique used in this study is the Ensemble Kalman Filter. A simulation for a period of 4 weeks has been performed in which ground-level ozone measurements have been assimilated. The necessary noise input consisted of uncertainties in the emissions of NO x, SO x, VOC and CO in 17 groups of countries. The main conclusion is that it is possible to improve ATCM simulations of ozone by data assimilation, but that noise inputs other than emissions only are essential for the reduction of the differences between measured and modelled concentrations to acceptable margins.

Airborne observations of dust aerosol over the North Atlantic Ocean during ACE 2: Indications for heterogeneous ozone destruction

Aerosol size distribution measurements have been performed in the free troposphere during the Second Aerosol Characterization Experiment (ACE 2) near Tenerife, Canary Islands, in July 1997. During one measurement flight, on July 8, a uniform aerosol layer was encountered between 2.5 and 5.5 km altitude, characterized by a relatively low Aitken mode particle number concentration and high concentrations of accumulation and coarse mode particles, resulting in a relatively large aerosol surface area and mass, which is estimated to be about 400 μg m−3. Five‐day backward trajectories indicate that the aerosol in this layer was mineral dust originating from arid regions on the North African continent. The dust layer was associated with reduced ozone mixing ratios. Model simulations have been performed with a photochemical box model including different heterogeneous removal reactions to study the interaction between gas phase chemistry and mineral aerosol. The best agreement between the observed and modeled ozone concentrations was obtained when heterogeneous removal of ozone and precursor gases on dust aerosol were taken into account. Heterogeneous O3 loss is estimated at 4 ppbv O3 per day. Although uncertainties concerning heterogeneous ozone removal remain, in particular related to the reactive uptake coefficient of O3, it is likely that the loss of O3 and precursor gases on mineral dust aerosol significantly reduces the O3 abundance in large‐scale dust plumes.