Airshed Model Research Articles

Optimal Control for Sustainable Intervention in a Coupled Socio-Climatic Model of Air Pollution

In this paper, technological interventions in a simple airshed model of emission propagation coupled with a social model of technology adoption are studied. An optimal control problem is introduced where a central planner aims to balance pollution concentration against intervention costs over an infinite time horizon. Interventions are classified into two types. Preventive interventions promote the adoption of low emission (green) technologies in the underlying population whereas dissipative interventions reduce the concentration of pre-existing pollutants in the air. Next, an infinite-horizon optimal control problem is set up and the notion of optimality is established. Applying Pontryagin's Minimum Principle, a sustainable equilibrium is derived and the existence of its stable manifold is explored. Imposition of green technology reduces both the steady-state pollutant concentration and dissipative Effort simultaneously but the planning variables induce a tradeoff between concentration and dissipative Effort. Lastly, the stable manifolds are simulated concluding with a discussion on policy implications for the system under consideration.

A review of gas-phase chemical mechanisms commonly used in atmospheric chemistry modelling

The atmospheric chemical mechanism is an essential component of airshed models used for investigating the chemical behaviors and impacts of species. Since the first tropospheric chemical mechanism was proposed in the 1960s, various mechanisms including Master Chemical Mechanism (MCM), Carbon Bond Mechanism (CBM), Statewide Air Pollution Research Center (SAPRC) and Regional Atmospheric Chemistry Mechanism (RACM) have been developed for different research purposes. This work summarizes the development and applications of these mechanisms, introduces their compositions and lumping methods, and compares the ways the mechanisms treat radicals with box model simulations. CBM can reproduce urban pollution events with relatively low cost compared to SAPRC and RACM, whereas the chemical behaviors of radicals and the photochemical production of ozone are described in detail in RACM. The photolysis rates of some oxygenated compounds are low in SAPRC07, which may result in underestimation of radical levels. As an explicit chemical mechanism, MCM describes the chemical processes of primary pollutants and their oxidation products in detail. MCM can be used to investigate certain chemical processes; however, due to its large size, it is rarely used in regional model simulations. A box model case study showed that the chemical behavior of OH and HO2 radicals and the production of ozone were well described by all mechanisms. CBM and SAPRC underestimated the radical levels for different chemical treatments, leading to low ozone production values in both cases. MCM and RACM are widely used in box model studies, while CBM and SAPRC are often selected in regional simulations.

Performance Evaluation of CCAM-CTM Regional Airshed Modelling for the New South Wales Greater Metropolitan Region

A comprehensive evaluation of the performance of the coupled Conformal Cubic Atmospheric Model (CCAM) and Chemical Transport Model (CTM) (CCAM-CTM) for the New South Wales Greater Metropolitan Region (NSW GMR) was conducted based on modelling results for two periods coinciding with measurement campaigns undertaken during the Sydney Particle Study (SPS), namely the summer in 2011 (SPS1) and the autumn in 2012 (SPS2). The model performance was evaluated for fine particulate matter (PM2.5), ozone (O3) and nitrogen dioxide (NO2) against air quality data from the NSW Government’s air quality monitoring network, and PM2.5 components were compared with speciated PM measurements from the Sydney Particle Study’s Westmead sampling site. The model tends to overpredict PM2.5 with normalised mean bias (NMB) less than 20%, however, moderate underpredictions of the daily peak are found on high PM2.5 days. The PM2.5 predictions at all sites comply with performance criteria for mean fractional bias (MFB) of ±60%, but only PM2.5 predictions at Earlwood further comply with the performance goal for MFB of ±30% during both periods. The model generally captures the diurnal variations in ozone with a slight underestimation. The model also tends to underpredict daily maximum hourly ozone. Ozone predictions across regions in SPS1, as well as in Sydney East, Sydney Northwest and Illawarra regions in SPS2 comply with the benchmark of MFB of ±15%, however, none of the regions comply with the benchmark for mean fractional error (MFE) of 35%. The model reproduces the diurnal variations and magnitudes of NO2 well, with a slightly underestimating tendency across the regions. The MFE and normalised mean error (NME) for NO2 predictions fall well within the ranges inferred from other studies. Model results are within a factor of two of measured averages for sulphate, nitrate, sodium and organic matter, with elemental carbon, chloride, magnesium and ammonium being underpredicted. The overall performance of CCAM-CTM modelling system for the NSW GMR is comparable to similar model predictions by other regional airshed models documented in the literature. The performance of the modelling system is found to be variable according to benchmark criteria and depend on the location of the sites, as well as the time of the year. The benchmarking of CCAM-CTM modelling system supports the application of this model for air quality impact assessment and policy scenario modelling to inform air quality management in NSW.

Reactive uptake of ammonia by secondary organic aerosols: Implications for air quality

Reactions between ammonia (NH3) and organic compounds containing carbonyl functional groups in aerosol particles can form organic products that are less basic than NH3 and are thus unable to neutralize efficiently nitric and sulfuric acids. In this exploratory study, the University of California, Irvine - California Institute of Technology (UCI-CIT) model is used to investigate the potential air quality impacts of including of the chemical uptake of NH3 by secondary organic aerosols (SOA) in a regional airshed model. A surface reaction of NH3 with SOA is implemented into the model to determine the impact of this process on NH3 and PM2.5 concentrations in the South Coast Air Basin of California (SoCAB). Air quality simulations are conducted using uptake coefficients ranging from 10−5 to 10−2 to explore the sensitivity of changes in NH3 and PM2.5 concentrations to the magnitude of the uptake coefficient. Results indicate that the chemical uptake of NH3 by SOA can potentially deplete gaseous NH3 concentrations, causing indirect reductions in the amount of ammonium nitrate and ammonium sulfate in particulate matter. The magnitude of the impact on NH3 and PM2.5 concentrations exhibits a strong but non-linear dependence on the value of the uptake coefficient, with evidence for small but notable impacts on air quality even with the lowest assumed uptake coefficient of 10−5.

Secondary organic aerosol from atmospheric photooxidation of indole

Abstract. Indole is a heterocyclic compound emitted by various plant species under stressed conditions or during flowering events. The formation, optical properties, and chemical composition of secondary organic aerosol (SOA) formed by low-NOx photooxidation of indole were investigated. The SOA yield (1. 3 ± 0. 3) was estimated from measuring the particle mass concentration with a scanning mobility particle sizer (SMPS) and correcting it for wall loss effects. The high value of the SOA mass yield suggests that most oxidized indole products eventually end up in the particle phase. The SOA particles were collected on filters and analysed offline with UV–vis spectrophotometry to measure the mass absorption coefficient (MAC) of the bulk sample. The samples were visibly brown and had MAC values of ∼ 2 m2 g−1 at λ = 300 nm and ∼ 0. 5 m2 g−1 at λ = 400 nm, comparable to strongly absorbing brown carbon emitted from biomass burning. The chemical composition of SOA was examined with several mass spectrometry methods. Direct analysis in real-time mass spectrometry (DART-MS) and nanospray desorption electrospray high-resolution mass spectrometry (nano-DESI-HRMS) were both used to provide information about the overall distribution of SOA compounds. High-performance liquid chromatography, coupled to photodiode array spectrophotometry and high-resolution mass spectrometry (HPLC-PDA-HRMS), was used to identify chromophoric compounds that are responsible for the brown colour of SOA. Indole derivatives, such as tryptanthrin, indirubin, indigo dye, and indoxyl red, were found to contribute significantly to the visible absorption spectrum of indole SOA. The potential effect of indole SOA on air quality was explored with an airshed model, which found elevated concentrations of indole SOA during the afternoon hours contributing considerably to the total organic aerosol under selected scenarios. Because of its high MAC values, indole SOA can contribute to decreased visibility and poor air quality.

Sub-Grid Scale Plume Modeling

Multi-pollutant chemical transport models (CTMs) are being routinely used to predict the impacts of emission controls on the concentrations and deposition of primary and secondary pollutants. While these models have a fairly comprehensive treatment of the governing atmospheric processes, they are unable to correctly represent processes that occur at very fine scales, such as the near-source transport and chemistry of emissions from elevated point sources, because of their relatively coarse horizontal resolution. Several different approaches have been used to address this limitation, such as using fine grids, adaptive grids, hybrid modeling, or an embedded sub-grid scale plume model, i.e., plume-in-grid (PinG) modeling. In this paper, we first discuss the relative merits of these various approaches used to resolve sub-grid scale effects in grid models, and then focus on PinG modeling which has been very effective in addressing the problems listed above. We start with a history and review of PinG modeling from its initial applications for ozone modeling in the Urban Airshed Model (UAM) in the early 1980s using a relatively simple plume model, to more sophisticated and state-of-the-science plume models, that include a full treatment of gas-phase, aerosol, and cloud chemistry, embedded in contemporary models such as CMAQ, CAMx, and WRF-Chem. We present examples of some typical results from PinG modeling for a variety of applications, discuss the implications of PinG on model predictions of source attribution, and discuss possible future developments and applications for PinG modeling.

Lumping, testing, tuning: The invention of an artificial chemistry in atmospheric transport modeling

Since the late 1950s computer simulation has been used to investigate the transport of pollutants in the atmosphere. About 20 years later also the chemical transformation of atmospheric pollutants was included in computer models of photochemical smog formation. Due to limited knowledge of atmospheric chemistry and due to limited computer capacity, chemical processes in the atmosphere were modeled with the help of simplified chemical models. In these models chemical substances are lumped together forming artificial virtual compounds with virtual characteristics. The paper aims at studying the practices developed in chemical model building and the creation of confidence in these models. Core of the paper will be the analysis of the Urban Airshed Model (UAM) for the Los Angeles region, a pioneering development in the early 1970s. The construction of the UAM involved the “lumping” of chemical processes and extensive testing and tuning. These practices led to a consistent model representation, in which diverse pieces of information fitted and were mutually stabilized. The pragmatic achievement of consistency created confidence, even though empirical tests of the models remained ambiguous and problematic.

Reactive Organic Gas Emissions from Livestock Feed Contribute Significantly to Ozone Production in Central California

The San Joaquin Valley (SJV) in California currently experiences some of the highest surface ozone (O(3)) concentrations in the United States even though it has a population density that is an order of magnitude lower than many urban areas with similar ozone problems. Previously unrecognized agricultural emissions may explain why O(3) concentrations in the SJV have not responded to traditional emissions control programs. In the present study, the ozone formation potentials (OFP) of livestock feed emissions were measured on representative field samples using a transportable smog chamber. Seven feeds were considered: cereal silage (wheat grain and oat grain), alfalfa silage, corn silage, high moisture ground corn (HMGC), almond shells, almond hulls, and total mixed ration (TMR = 55% corn silage, 16% corn grain, 8% almond hulls, 7% hay, 7% bran + seeds, and 5% protein + vitamins + minerals). The measured short-term OFP for each gram of reactive organic gas (ROG) emissions from all livestock feed was 0.17-0.41 g-O(3) per g-ROG. For reference, OFP of exhaust from light duty gasoline powered cars under the same conditions is 0.69 +/- 0.15 g-O(3) per g-ROG. Model calculations were able to reproduce the ozone formation from animal feeds indicating that the measured ROG compounds account for the observed ozone formation (i.e., ozone closure was achieved). Ethanol and other alcohol species accounted for more than 50% of the ozone formation for most types of feed. Aldehydes were also significant contributors for cereal silage, high moisture ground corn, and total mixed ration. Ozone production calculations based on feed consumption rates, ROG emissions rates, and OFP predict that animal feed emissions dominate the ROG contributions to ozone formation in the SJV with total production of 25 +/- 10 t O(3) day(-1). The next most significant ROG source of ozone production in the SJV is estimated to be light duty vehicles with total production of 14.3 +/- 1.4 t O(3) day(-1). The majority of the animal feed ozone formation is attributed to corn silage. Future work should be conducted to reduce the uncertainty of ROG emissions from animal feeds in the SJV and to include this significant source of ozone formation in regional airshed models.

Development of a condensed SAPRC-07 chemical mechanism

Abstract The development of a condensed version of the SAPRC-07 mechanism, designated CS07A, is described. It is comparable in size to CB05 and was derived directly from detailed SAPRC-07, which serves as the basis for its predictive capability and evaluation against chamber data. It incorporates the more condensed and approximate peroxy radical lumped operator method employed in SAPRC-99, and condensations involving removing or lumping less reactive compounds, lumping some product species in isoprene or aromatic mechanisms with other species with similar mechanisms using reactivity weighting, removing some compounds and reactions that are rapidly reversed, and using fewer model species to represent emitted alkanes and similar species. It gives predictions of O 3 , total PANs and OH radicals that are very close to the standard SAPRC-07 mechanism for airshed models used as the starting point, but predicts about 15% more H 2 O 2 . Use of CS07A is suitable for models where the priority is O 3 formation, while the less condensed version should be used if more accurate hydroperoxide predictions are a priority.

Effects of 10% biofuel substitution on ground level ozone formation in Bangkok, Thailand

The Thai Government's search for alternatives to imported petroleum led to the consideration of mandating 10% biofuel blends (biodiesel and gasohol) by 2012. Concerns over the effects of biofuel combustion on ground level ozone formation in relation to their conventional counterparts need addressing. Ozone formation in Bangkok is explored using a trajectory box model. The model is compared against O 3, NO, and NO 2 time concentration data from air monitoring stations operated by the Thai Pollution Control Department. Four high ozone days in 2006 were selected for modeling. Both the traditional trajectory approach and a citywide average approach were used. The model performs well with both approaches but slightly better with the citywide average. Highly uncertain and missing data are derived within realistic bounds using a genetic algorithm optimization. It was found that 10% biofuel substitution will lead to as much as a 16 ppb peak O 3 increase on these four days compared to a 48 ppb increase due to the predicted vehicle fleet size increase between 2006 and 2012. The approach also suggests that when detailed meteorological data is not available to run three dimensional airshed models, and if the air is stagnant or predominately remains over an urban area during the day, that a simple low cost trajectory analysis of O 3 formation may be applicable.

Effects of anthropogenic emission sources on maximum ozone concentrations over Greece

The impacts of anthropogenic emissions from the maritime transport and from the countries neighboring Greece on the maximum ground-level ozone concentrations over Greece were studied. Ozone concentrations were simulated across a part of the Eastern Mediterranean during a summer period using a modeling system that consisted of the photochemical Urban Airshed Model known as UAM-V coupled with the meteorological mesoscale model known as MM5. Simulated, maximum hourly ozone concentrations were higher over continental and maritime areas of Greece influenced by the emissions of the large urban agglomerations. When air quality simulations were performed assuming zero maritime transport emissions, the greater part of Greece experienced reductions in maximum ozone levels. Over the continental part of the country, the largest ozone reductions occurred along the coastline of southern and western Greece and were approximately 20 ppb. Over maritime areas, the decreases in maximum ozone concentrations were more pronounced. However, in the regions influenced by high amounts of nitrogen oxides emitted from the sea transport activities, the O 3 concentrations were increased. The impact of anthropogenic emissions from all continental areas within the modeling domain, other than Greece, on the maximum ozone concentrations over Greece was small. Considering that the emission inventory for Greece was more detailed, while the official emission data for some of the countries in the modeling domain were generally poor, the assessed impact might have been underestimated.

Mining and modeling for a metropolitan Atlanta ozone pollution decision-making framework

In this paper, we present a Decision-Making Framework (DMF) for reducing ozone pollution in the metropolitan Atlanta region. High ground-level concentrations of ozone continue to be a serious problem in several US cities, and Atlanta is one of the most serious of these cases. In contrast to the “trial and error” approach utilized by state government decision-makers, our DMF searches for dynamic and focused control strategies that require a lower total reduction of emissions than current control strategies. Our DMF utilizes a rigorous stochastic dynamic programming formulation and includes an Atmospheric Chemistry Module to represent how ozone concentrations change over time. This paper focuses on the procedures within the Atmospheric Chemistry Module. Using the US EPA's Urban Airshed Model for Atlanta, we use mining and metamodeling tools to develop a computationally efficient representation of the relevant ozone air chemistry. The proposed approach is able to effectively model changes in ozone concentrations over a 24-hour period.

Influence of dense surface meteorological data assimilation on the prediction accuracy of ozone pollution in the southeastern coastal area of the Korean Peninsula

In order to clarify the influence of surface meteorological data assimilation with various resolutions on the photochemical ozone concentration in the southeastern Korean Peninsula, several numerical experiments were conducted. The meteorological and photochemical reaction models used in this study are the fifth-generation mesoscale model (MM5) and the three-dimensional photochemical urban airshed model (UAM-V), respectively. Dense meteorological data make it easier to obtain accurate estimates and surface characteristics than coarse-resolution data. As a result, the estimated temperature obtained from high resolution surface data assimilation in the Busan and Ulsan metropolitan areas is higher than that obtained from coarse resolution surface data assimilation. These high temperatures resulted in strong winds from the sea and a significant dispersion of ozone. In analyses involving an index of agreement (IOA) and root mean square deviation (RMSD), the temperature and wind speed estimated with dense surface data assimilation agreed well with those obtained from observations. However, the influence of dense surface data assimilation tends to be stronger in the flat Ulsan metropolitan area than in the mountainous Busan metropolitan area. This is caused by the heterogeneity of the surface characteristics, including the topography. If the surface parameters induced by regional circulation, such as the topography and land use, are complex and heterogeneous, the efficiency of observational data on data assimilation has to be verified before air pollution is assessed.

Air Quality Modeling in the South Coast Air Basin of California: What Do the Numbers Really Mean?

This study evaluates air quality model sensitivity to input and to model components. Simulations are performed using the California Institute of Technology (CIT) airshed model. Results show the impacts on ozone (O3) concentration in the South Coast Air Basin (SCAB) of California because of changes in: (1) input data, including meteorological conditions (temperature, UV radiation, mixing height, and wind speed), boundary conditions, and initial conditions (ICs); and (2) model components, including advection solver and chemical mechanism. O3 concentrations are strongly affected by meteorological conditions and, in particular, by temperature. ICs also affect O3 concentrations, especially in the first 2 days of simulation. On the other hand, boundary conditions do not significantly affect the absolute peak O3 concentration, although they do affect concentrations near the inflow boundaries. Moreover, predicted O3 concentrations are impacted considerably by the chemical mechanism. In addition, dispersion of pollutants is affected by the advection routine used to calculate its transport. Comparison among CIT, California Photochemical Grid Model (CALGRID), and Urban Airshed Model air quality models suggests that differences in O3 predictions are mainly caused by the different chemical mechanisms used. Additionally, advection solvers contribute to the differences observed among model predictions. Uncertainty in predicted peak O3 concentration suggests that air quality evaluation should not be based solely on this single value but also on trends predicted by air quality models using a number of chemical mechanisms and with an advection solver that is mass conservative.

Simulation and analysis of secondary organic aerosol dynamics in the South Coast Air Basin of California

The dynamics of secondary organic aerosol (SOA) formation are analyzed using a species‐resolved SOA model for the South Coast Air Basin of California (SoCAB). Updated versions of the Caltech Atmospheric Chemistry Mechanism (CACM) and the Model to Predict the Multiphase Partitioning of Organics (MPMPO) are integrated with the CIT airshed model. The simulations are performed using input data from the 8–9 September 1993 episode. Results show that urban areas with major volatile organic compound (VOC) emission sites experience peaks in SOA levels during morning hours. Downwind locations, such as Azusa and Claremont, experience sustained levels of high SOA concentrations in comparison with coastal areas such as central Los Angeles and Long Beach. Concentrations of condensible organics are higher in inland locations compared to those in coastal locations because of high oxidation capacity and transport of pollutants. Furthermore, SOA constitutes up to 30% of simulated organic particulate matter at inland locations, with maximum contributions occurring during afternoon hours. Anthropogenic sources contribute over 90% of simulated SOA at most locations in the basin. Oxidation products of aromatic compounds from anthropogenic sources constitute over 70% of total simulated SOA. Sensitivity runs indicate strong dependence of SOA on VOC emissions and temperature. Overall, model predictions are in qualitative agreement with recent observations in the SoCAB.

Measurement and modelling of air pollution and atmospheric chemistry in the U.K. West Midlands conurbation: Overview of the PUMA Consortium project

The PUMA (Pollution of the Urban Midlands Atmosphere) Consortium project involved intensive measurement campaigns in the Summer of 1999 and Winter of 1999/2000, respectively, in which a wide variety of air pollutants were measured in the UK West Midlands conurbation including detailed speciation of VOCs and major component analysis of aerosol. Measurements of the OH and HO 2 free radicals by the FAGE technique demonstrated that winter concentrations of OH were approximately half of those measured during the summer despite a factor of 15 reduction in production through the photolysis of ozone. Detailed box modelling of the fast reaction chemistry revealed the decomposition of Criegee intermediates formed from ozone–alkene reactions to be responsible for the majority of the formation of hydroxyl in both the summer and winter campaigns, in contrast to earlier rural measurements in which ozone photolysis was predominant. The main sinks for hydroxyl are reactions with NO 2, alkenes and oxygenates. Concentrations of the more stable hydrocarbons were found to be relatively invariant across the conurbation, but the impacts of photochemistry were evident through analyses of formaldehyde which showed the majority to be photochemical in origin as opposed to emitted from road traffic. Measurements on the upwind and downwind boundaries of the conurbation revealed substantial enhancements in NO x as a result of emissions within the conurbation, especially during westerly winds which carried relatively clean air. Using calcium as a tracer for crustal particles, it proved possible to reconstruct aerosol mass from the major chemical components with a fairly high degree of success. The organic to elemental carbon ratios showed a far greater influence of photochemistry in summer than winter, presumably resulting mainly from the greater availability of biogenic precursors during the summer campaign. Two urban airshed models were developed and applied to the conurbation, one Eulerian, the other Lagrangian. Both were able to give a good simulation of concentrations of both primary and secondary pollutants at urban background locations.

Model simulation of meteorology and air quality during the summer PUMA intensive measurement campaign in the UK West Midlands conurbation

The Regional Atmospheric Modeling System (RAMS) and Urban Airshed Model (UAM IV) have been implemented for prediction of air pollutant concentrations within the West Midlands conurbation of the United Kingdom. The modelling results for wind speed, direction and temperature are in reasonable agreement with observations for two stations, one in a rural area and the other in an urban area. Predictions of surface temperature are generally good for both stations, but the results suggest that the quality of temperature prediction is sensitive to whether cloud cover is reproduced reliably by the model. Wind direction is captured very well by the model, while wind speed is generally overestimated. The air pollution climate of the UK West Midlands is very different to those for which the UAM model was primarily developed, and the methods used to overcome these limitations are described. The model shows a tendency towards under-prediction of primary pollutant (NO x and CO) concentrations, but with suitable attention to boundary conditions and vertical profiles gives fairly good predictions of ozone concentrations. Hourly updating of chemical concentration boundary conditions yields the best results, with input of vertical profiles desirable. The model seriously underpredicts NO 2 / NO ratios within the urban area and this appears to relate to inadequate production of peroxy radicals. Overall, the chemical reactivity predicted by the model appears to fall well below that occurring in the atmosphere.

A GIS framework for Traffic Emission Information System

A coefficient-based vehicular exhaust emission model is being developed jointly with the variable-grid urban airshed model (UAM-V) of Systems Applications International (SAI), and integrated within a GIS (ArcInfo) framework. When coupled with a road network, traffic features and meteorological as well as geographical databases, this framework produces a Traffic Emission Information System (TEIS). With this TEIS, the emission coefficients of CO, NOx and VOC for Sydney in the calendar year 2000 are derived; and the emission rates of the pollutants are then estimated using sample traffic profile data for the Sydney metropolitan area. Finally, ongoing improvements to the system are presented.

The BOND project: Biogenic aerosols and air quality in Athens and Marseille greater areas

The role of Secondary Biogenic Organic Aerosol in aerosol budget is examined using the Atmospheric Dispersion of Pollutants over Complex Terrain–Urban Airshed Model–Aerosols (ADREA‐I/UAM‐AERO) modeling system in two representative Mediterranean areas. The areas have been selected, because of their elevated biogenic emission levels and the sufficient degree of meteorological and land use diversity characterizing the locations. Comparison of the model results with and without biogenic emissions reveals the significant role biogenic emissions play in modulating ozone and aerosol concentrations. Biogenic emissions are predicted to affect the concentrations of organic aerosol constituents through the reactions of terpenes with O3, OH and NO3. The ozonolysis of terpenes is predicted to cause an increase in OH radical concentrations that ranges from 10% to 78% for Athens, and from 20% to 95% for Marseilles, depending on the location, compared to the predictions without biogenic emissions. The reactions of this extra hydroxyl radical with SO2 and NOx have as final products increased concentrations of sulfates and nitrates in the particulate phase. As a result, biogenic emissions are predicted to affect the concentrations not only of organic aerosols, but those of inorganic aerosols as well. Thus biogenic emissions should be taken into consideration when models for the prediction and enforcement of abatement strategies of atmospheric pollution are applied.

Model study with UAM-V in the Milan area (I) during PIPAPO: simulations with changed emissions compared to ground and airborne measurements

Abstract The three-dimensional photochemical Urban Airshed Model with variable grid (UAM-V) is used to investigate the temporal and spatial dynamics of the photooxidant production in the highly polluted Milan area (Italy). A simulation of the 13 May 1998 event is presented, when peak ozone levels of 190 ppb were measured in the urban plume. A large field campaign provided data of numerous chemical species and meteorological quantities from ground based and airborne platforms. The highest measured ozone mixing ratios occurred in the urban plume, where a local peroxide decrease was found simultaneously. The model base case is able to reproduce the ozone concentration but more peroxide is formed in the centre of the plume than in the adjacent areas. This can be interpreted as a tendency of the model towards a stronger NOx sensitivity compared to observation. Modification of the emission inventory, which is based on observed discrepancies between inventory and measurements, lead to a better agreement with respect to peroxide formation and NOx removal in the urban plume. It seems that the different rearrangement of the emissions in urban and non-urban areas are important for the improved response of the model. Ozone levels did not differ much between the base case simulation and those with a modified emission inventory, while peroxide formation and NOx concentrations in the urban plume did.