WP5: Regional and Global Atmospheric Composition

 

Coordinated by J. Kukkonen (FMI) and A. Stohl (NILU)

 

MEGAPOLI Partners involved: DMI, FORTH, MPIC, ARIANET, CNRS, FMI, NILU, TNO, MetO, UHam, UHel, UH-CAIR, UCam

Summary of progress toward objectives

The main overall objective of WP5 is to quantify the effects of megacities on air quality of the region that surrounds and includes the megacities, and on the downwind atmospheric composition on regional to global scales.  This will be achieved by combining regional and global Chemical Transport Models (CTMs) with ground-based and airborne measurements, including improved satellite observations. In particular, we will use the observations from the Paris field campaign (WP3). Specific objectives of WP5 are the following:

There has been substantial progress in developing and evaluating the satellite-based methods for the measurement of tropospheric gases and aerosols. The MPIC team has developed, e.g., a retrieval algorithm for tropospheric NO2 vertical column densities for GOME-2 on METOP, adapted and refined the satellite retrieval algorithms, validated tropospheric trace gas products, and correlated NO2 observations with wind data
(e.g., Chen et al., 2009; Hayn et al., 2009). The FMI and UHel teams have compared CALIOP level 2 aerosol subtypes to aerosol types derived from AERONET inversion data (Mielonen et al., 2009).
An extensive review article is in progress on operational chemical weather forecasting models on regional and continental scales, in collaboration with COST Action ES0602 and MEGAPOLI, coordinated by FMI (Kukkonen et al., 2010). Work has started at TNO to make improvements on the LOTOS-EUROS model to be better equipped to simulate the effect on air quality of megacities on the regional scale (Manders et al., 2009ab; Schaap et al., 2009). The DMI team is running the on-line Enviro-HIRLAM model for the European region with TNO emissions. The Fire Assimilation System is operational with improved spatial and temporal aggregation of multi-source fire information by FMI (Sofiev et al., 2009ab).
The major European fire episodes in 2006 were examined using both chemically speciated size-resolved aerosol measurements and dispersion model computations (Saarnio et al., 2010).
The ARIANET team has conducted long-term evaluations of air pollution in the Po Valley region. The chemistry schemes in the global models used at MPIC and MetO have been substantially improved and extended (e.g., Folberth et al., 2009ab) and, for instance, oxidation pathways have been studied (Butler, 2009). The effect of megacities on the chemistry of the global atmosphere has been determined (Butler and Lawrence, 2009).
The WP 5 regional model ensemble has been discussed and all its parameters decided. The first modellign data have arrived to FMI for testing and have been included into the ensemble creation software. The ensemble will cover the baseline year 2005 and two Paris campaigns in 2009 and 2010. All the models will perform the European-scale simulations using own meteodata but unified emission input. The ensemble construction and analysis will generally follow the setup of COST-728 but with substantially more sophisticated analytical part related to the ensemble handling algorithms and analysis of its representativeness.
 

Figure 5.1: Mean daily NO2 concentrations forecasted for 25.3.2010, SILAM model. Domain represents the MEGAPOLI regional ensemble area.

 

Summary details for each relevant WP deliverables, milestones, and tasks

Task 5.1: Application of satellite data to characterize the regional-to-global scale impact of megacities (lead: MPIC)

In October 2006 the first of a series of three GOME-2 instruments was launched on a board the METOP satellite. Based on the retrieval algorithms for GOME-1 and SCIAMACHY the MPIC team developed a spectral retrieval method for the analysis of the atmospheric NO2 absorption in the GOME-2 spectra. The one-year mean map of tropospheric NO2 shows the high sensitivity and consistency of the GOME-2 analysis.
The retrieval of tropospheric information from satellite observations is challenging, mainly because of the strong influence of aerosols and clouds. In addition, also the (relative) vertical concentration profile of the measured trace species has a large impact on the resulting tropospheric column density. A sophisticated cloud correction scheme (e.g. Chen et al., 2009) was developed by the MPIC team. This correction is based on simultaneously retrieved cloud information (effective cloud fraction and cloud top height) in combination with radiative transfer modelling.
Validation of tropospheric trace gas results from satellite observations is a complex task, because well suited ground-based observations are still sparse. Moreover, a large variability (in time and space) of tropospheric trace gas concentrations complicates the validation activities. The tropospheric trace gas product (from SCIAMACHY) of MPIC was successfully validated over strongly polluted areas (Shanghai, China; Chen et al., 2009).
In recent years several studies investigated the spatial-temporal variation of the global tropospheric NO2 distribution by fitting prescribed functions for linear trends, seasonal and/or weekly cycles to the satellite observations. We extended this method using a very flexible approach of generalised additive models (GAM). Using this tool set makes, in particular, possible to investigate the influence of wind fields on local distributions of tropospheric NO2 (Hayn et al., 2009).
The FMI and UHel teams have compared CALIOP level 2 aerosol subtypes to aerosol types derived from AERONET inversion data (Mielonen et al., 2009).

In the following, the activities so far  are described divided into three main parts:
a) the validation of satellite observations over Paris using mobile MAX-DOAS observations
b) the determination of emissions from Paris using satellite observations
c) the determination of emissions from Paris using mobile MAX-DOAS observations
All results are for NO2, because this gas can be analysed using spectroscopic techniques with comparably high accuracy. Also NO2 (or better NOx) has a rather short atmospheric lifetime (in the order of several hours); thus emissions from Megacities are usually confined to the surrounding regions.
In this report we describe two novel techniques for the quantification of megacity emissions, based on observational data from satellite instruments or car MAX-DOAS. In principle these techniques can also be applied to other trace gases (or aerosols), but this might not be possible for some regions (e.g. Paris) because of the rather small signals and/or the vicinity of other strong emission sources. Additionally, the MPIC team used GOME-2 data to continue our investigations of the weekly cycle in different parts of the world. Depending on the religious orientation, minima on different days of the week are observed.
 
Validation of satellite observations over Paris using mobile MAX-DOAS observations
The validation of tropospheric trace gas distributions obtained from satellite observations is a very important task, because of the rather large uncertainties of these data products. However, such validation exercises are still a great challenge, mainly because of the coarse spatial resolution of satellite observations. Several validation attempts have so far been carried out (e.g. Heland et al., 2002; Chen et al., 2009), but their significance is generally limited, because of the strong spatial gradients of pollutants close to emission sources, which can usually not be resolved by the satellite observation (Chen et al., 2009).
Within the Megapoli project we performed extensive MAX-DOAS measurements using an instrument mounted on a car thus covering areas of about the size of up to several satellite pixel. In the two Megapoli campaigns we performed car MAX-DOAS observations on circles around Paris on about 50 days. Spectra of scattered sun light were measured every 30 to 60 seconds leading to a spatial resolution of the order of 500-1000m. From the measured spectra the vertically integrated tropospheric NO2 concentration (tropospheric vertical column density, VCD) can be derived (Wagner et al., 2010), which can be directly compared to the satellite observations. In Figure 5.2 such a comparison with observations from the OMI instrument is shown for 20.07.2009 (DOMINO product (version 3) from the temis website (www.temis.nl), see Boersma et al., 2007). It is obvious that strong spatial gradients at sub-pixel scales can not be resolved by the satellite observations. Nevertheless, a rather  good quantitative agreement with the car MAX-DOAS observations was found for that day. It should be noted that on other days also substantial differences were found, which should be investigated in more detail in the future. 
    

Figure 5.2: Comparison of the tropospheric NO2 VCD measured from OMI (OMI overpass: 13:13) and car MAX-DOAS during the summer campaign.

 

Determination of emissions using satellite observations
Satellite observation offer a unique possibility to quantify emissions of tropospheric pollutants (trace gases and aerosols) due to their spatial coverage. In particular, they allow to observe extended regions around selected emission sources (e.g. megacities). Emission strengths can for example be determined from the comparison of the satellite observations with model results (e.g. Bergamschi et al., 2007). However, especially for species with short atmospheric lifetimes (hours to days) it becomes also possible to apply an inversion approach which is independent from model results. This approach is described and used in the following. 
For species with short atmospheric lifetimes it is possible to select areas around the emission source which contain all accumulated emissions (or at least the major fraction). From the total number of observed molecules, the emission strength can be determined by dividing by the atmospheric lifetime of NO2. We estimated also the atmospheric lifetime from the satellite observations in combination with meteorological information. After grouping of the satellite observations for different wind directions, the decay along the outflow regions is quantified and divided by the average wind speed. Examples for the average tropospheric NO2 VCD around Paris for different wind directions are shown in Figure 5.3. 
The total emissions for Paris determined in this way range between 5x1025molec/s and 11x1025molec/s.

 

 

Figure 5.3: Average tropospheric NO2 VCD for the area around Paris depending on the wind direction and speed. The figure in the center is for wind speeds < 2m/s; the figures at the left and right describe the measurements for easterly and westerly winds, respectively /scale * 1015 molec/cm2/.


Determination of emissions from Paris using mobile MAX-DOAS observations
Total urban NO2 emissions can be determined from Auto DOAS observations performed on driving routes around complete cities (Wagner et al., 2010, Ibrahim et al., 2010). For that purpose also the knowledge of the wind speed and direction is required.
Within the MEGAPOLI project we carried out Auto MAX-DOAS measurements along closed driving routes of various radii around Paris in summer 2009 and winter 2010 (in total on more than 50 days. One example is shown in Figure 5.4. From preliminary analyses we found emissions for Paris ranging from about 2x1025 molec/s in summer to about 7x1025 molec/s in winter. If these emission estimates are compared the results from the satellite observations, rather good agreement is found for winter, but large disagreement is found for summer (with the satellite results being higher by about a factor of 4). Part of these discrepancies might be related to the smaller lifetime in summer, which can cause a systematic underestimation of the true emission strength. This aspect should be investigated and corrected in future analyses of the car MAX-DOAS observations (see also Ibrahim et al., 2010).


 

        

 Figure 5.4: Tropospheric NO2 VCD determined from car MAX-DOAS observations around Paris on 11.02.2010 (left). High values are found in the south-west, which corresponds well with the prevailing wind direction on that day (right, data obtained from NOAA air research laboratory).

Task 5.2: Improvement of the regional and global CTMs to simulate megacities and their effects (lead: FORTH)

An extensive review article is in progress on operational chemical weather forecasting (CWF) models on regional and continental scales (acknowledged: COST Action ES0602 and MEGAPOLI), coordinated by FMI and MEGAPOLI scientists are also coauthors. This article will contain an evaluation of the physical and chemical treatments of most of the regional scale models to be used in MEGAPOLI (Kukkonen et al., 2010).
Work has started at TNO to make improvements on the LOTOS-EUROS model to be better equipped to model the effect on air quality of megacities on the regional scale (Manders et al., 2009ab; Schaap et al., 2009).
Using the operational evaluation of MACC project and a set of re-analysis simulations, FMI has improved the SILAM modeling system in several directions. Firstly, the advection algorithm has been reviewed and the utilization of the subgrid information has been increased 6-fold. The modification sharply improved the representation of mountainous and complex-weather situations. Secondly, the boundary condition algorithm has been reconsidered and more accurate procedure introduced, which allowed smoother fields in case of high Courant numbers near the borders. Finally, the new model version 5 has been outlined with an explicit implementation of the single-atmosphere principle, newly designed aerosol dynamics module and much better integration between the chemical sub-modules. The UH-CAIR team is working on the CMAQ model to include a specific approach for BC on London area (sensitivity test); improvement on emissions inventory (time modulation and vertical profiles); operationalize the system, and satellite and ground based dataset integration (focus on vertical profiles of aerosol species). The MPI team works on the box modelling experiments using MECCA, with focus on hydrocarbons chemistry and ozone production potentials.
The chemistry schemes in the global models used at MPIC and MetO have been substantially improved and extended (e.g., Folberth et al., 2009ab) and, for instance, oxidation pathways have been studied (Butler, 2009). The effect of megacities on the chemistry of the global atmosphere has been determined (Butler and Lawrence, 2009). FLEXPART, used at NILU, has been extended to allow treatment of simple aerosol-like tracers, which in addition to pure transport, are subject to removal processes (dry and wet deposition). The work on the FLEXPART simulations at NILU has been started very recently.

 

Task 5.3: Evaluation of the current capability of regional CTMs to predict megacity plumes (lead: FMI).

Regarding ensembles, we will use the recent experience from GEMS regarding a similar (although operational) ensemble. We will also use the outcomes from the above mentioned extensive model review article (Kukkonen et al., 2010), and COST 728 reporting.

 

Task 5.4: Determination of the impact of megacities on regional and global atmospheric composition (lead: FMI, MPIC, NILU)

The configuration of the regional ensemble has been decided and is being implemented in the participating models.
Main features of the ensemble simulations:
All models in the ensemble perform two-scale simulations: European ones and zoomed regional. Some of the models can go to the third zooming and further on. Extra zooming is "voluntary" but two-scale runs - "Europe" and "regiona" - are mandatory for all.
Computed period for the European and regional runs: baseline year 2005 and Paris campaigns.
No data assimilation is expected.
The predicted fields are to be transferred to FMI for the ensemble construction using the Ensemble Creation Tool (developed within the scope of COST-728).
Steps:
  • The first Paris campaign (July 2009) as a test case. One run, Europe, July 2009,
  • Confirmation of the results readability and compatibility
  • Simulation of the baseline year 2005
  • Generation of the ensemble
  • Results presentation; second MEGAPOLI annual meeting
  • Regional ensemble: emission top-down, 7km. Second set: merge the bottom-up emissions from MC to 7km Eur map.

European run setup
:
Input meteorology and physiography: up to the model
Input emission: MEGAPOLI emission data, plus embedded dynamic modelled emission, if any. Stack height, time: COST-728 (somewhat close to EMEP), time resolution: EMEP disaggregation.
Boundary conditions:
  •  MATCH-MPIC for 2005 (gases), TM5 (aerosols)
  • GEMS/MACC MOZART global fields for 2009-2010 (gases) + IFS aerosols.
Output file format: NetCDF, convention to be agreed
Output domain: GEMS/MACC (15W-35E, 35N-70N)
Output grid resolution: (0.30  0.20)
Output vertical levels: screen level (2m/10m above the surface), 100m, 500m, 1000m, 3000m

Output variables:
Output temporal resolution: 1 hour
Computational domain: covering the output domain
Computational resolution: up to the model; re-project to the output grid if differs from it
Computational vertical: up to the model, project the fields to the output vertical levels
 
Nested regional setup:
Input meteorology and physiography: up to the model
Input emission: MEGAPOLI emission data, plus embedded dynamic modelled emission, if any, plus Paris refined emission
Boundary conditions: The European run of the corresponding model
Output file format: NetCDF, convention to be agreed, same as for the European run
Output domain: (5W:15E, 40N:57N)
Output grid resolution: ~7km (same as emission), 0.125x0.0625
Output vertical levels: screen level (2m/10m above the surface), 100m, 500m, 1000m, 3000m

Output variables:

Output temporal resolution: 1 hour
Computational domain: covering the output domain
Computational resolution: up to the model; re-project to the output grid if differs from it
Computational vertical: up to the model, project the fields to the output vertical level

    Global modelling

Concerning global modelling, some key steps (Butler and Lawrence 2009) have already been completed. The MPI-C component of this task will be performed using two different global models: MATCH-MPIC and EMAC. MATCH-MPIC is a semi-offline CTM (Chemical Transport Model) which uses input fields (wind speed and surface fluxes) to compute the hydrological cycle and the transport and chemistry of atmospheric trace constituents. MATCH-MPIC has already been used for two different studies of the global impacts of emissions from megacities (Lawrence et al. 2007, Butler and Lawrence 2009). EMAC (the ECHAM5/MESSy1 Atmospheric Chemistry general circulation model, (Jockel et al. 2006) is a fully coupled, highly modular, global three dimensional chemistry-climate model, which will be used in addition to MATCH-MPIC in the suite of models performing global simulations under the MEGAPOLI project. Output from MATCH-MPIC as boundary conditions to the ensemble of regional models involved has already been provided.
Prior to MEGAPOLI, Lawrence et al. (2007) performed idealised simulations using passive tracers and found that the degree of vertical transport of trace constituents away from megacities plays a crucial role in both the amount of pollutants in the cities themselves, as well as their amounts in regions downwind of the cities.  We are now following up this study examining the regional transport of aerosol pollution tracers using the EMAC model.
Simulation with a full suite of gas phase chemical reactions, using the emissions from megacities described by Butler et al. (2008), within WP5 has been performed (Butler and Lawrence, 2009). We found that the influences of megacities on global oxidising capacity (through the OH radical) and ozone mixing ratios were generally in proportion to or smaller than the total percentage of global emissions which are due to megacities. The effects of megacities on the reactive nitrogen cycle, however, were generally larger than the percentage of the emissions of reactive nitrogen due to megacities, with potentially important consequences for deposition of reactive nitrogen onto terrestrial and oceanic ecosystems (Figure 5.5).

 


 Figure 5.5: Percentage change in NOx mixing ratios due to emissions from megacities in MATCH-MPIC.

 Task 5.5: The influence of non-urban pollution sources in megacities, and intercontinental transport (lead: DMI, NILU, FMI)

Fire Assimilation System is operational with improved spatial and temporal aggregation of multi-source fire information by FMI (Sofiev et al., 2009ab). Global inventories of fire emissions have been generated for the time period of 24.02.2000 - 31.12.2008 using 0.25 by 0.25 deg grid resolution. European fire emissions have been generated with finer, 0.1 by 0.1 deg, resolution.
The DMI team is working on the influence of non-urban pollution sources in megacities, and intercontinental transport. This work is only on the preparation stage (domain, emissions, model specification, tests, etc.). DMI is considering to use or off-line CAC model or online Enviro-HIRLAM model for this study. One of the possible case studies is the Moscow forest fires summer 2002 episode, the other one is the effects of the ship emissions in Bosporus on the Istanbul megacity. For the first case study cooperation with Russian daughter project MEGAPOLIS has started (including satellite data for forest fires).
Sea salt emission model of the FMI has been improved and evaluated against experimental data. A modelling system has been developed for the exhaust emissions of marine traffic and it has been applied in the Baltic Sea area (Jalkanen et al., 2009). The new ship emission model will be applied to Istanbul region to study the air quality effects of marine traffic to Bosporus strait area, in collaboration with DMI, FMI, KNMI, TNO and the Istanbul Technical University. Birch pollen emission and dispersion modeling has been refined, using data in the Baltic countries and their environment (Veriankaite et al., 2010).
The efforts at the MetO in connection with WP5 Task 5.6 (with relevance also to WP5 Task 5.4.2 and WP6 Tasks 6.1-6.2) and the WP5 deliverables during the first year have been closely correlated to the efforts of our partner group in Mainz (MPIC) and Oslo (NILU). The focus is on improving the representation of the chemistry (following discussions with MPIC and NILU partners at the MEGAPOLI kick-off meeting and at the 7th International Conference on Air Quality - Science and Application, Istanbul earlier this year). The HadGEM2 model has been extended by a comprehensive tropospheric chemistry model, a simple interactive SOA scheme accounting for both anthropogenic and biogenic precursors and an interactive BVOC emission model which has been coupled to the vegetation and land use scheme in HadGEM2.

Deliverable 5.1: Characterization of megacity impact on regional and global scales using satellite data (lead: MPIC) was written and available from the MEGAPOLI public website.

Thomas Wagner, Steffen Beirle, Reza Shaiganfar (2010): Characterization of Megacity Impact on Regional and Global Scales Using Satellite Data. Deliverable D5.1, MEGAPOLI Scientific Report 10-09, MEGAPOLI-12-REP-2010-03, 25p;

Deliverable 5.2: Provision of global and regional concentrations fields from initial baseline runs (lead: FMI) was written and available from the MEGAPOLI internal website (http://megapoliforum.dmi.dk)
 Sofiev M., Prank M., Vira J., and MEGAPOLI Modelling Teams (2010): Provision of Global and Regional Concentrations Fields from Initial Baseline Runs. Deliverable D5.2, MEGAPOLI Technical Note 10-12, MEGAPOLI-15-REP-2010-03, 10p.

Deliverable 5.3Evaluation and Improvement of Regional Model Simulations for Megacity Plumes (lead: FMI) was written and available from the MEGAPOLI public website.
Sofiev M., M. Prank, J. Kukkonen (Eds) (2011): Evaluation and Improvement of Regional Model Simulations for Megacity Plumes. Deliverable D5.3, MEGAPOLI Scientific Report 11-04, MEGAPOLI-30-REP-2011-03, 88p.

Deliverable 5.4: Prediction of Megacities Impact on Regional and Global Atmospheric Composition (lead: NILU) was written and available from the MEGAPOLI public website.
Cassiani M., Stohl S., Eckhardt S., Sovief M., Prank M., Butler T., Lawrence M., Collins W.J., Folberth G.A., Rumbold S., Pyle J.A., Russo M.R., Stock Z., Siour G., Coll I., D’Allura A., Finardi S., Radice P., Silibello C. (2011): Prediction of Megacities Impact on Regional and Global Atmospheric Composition. Deliverable D5.4, MEGAPOLI Scientific Report 11-11, MEGAPOLI-37-REP-2011-06, 55p.

Deliverable 5.5: Influence of Regional Scale Emissions on Megacity Air Quality (lead: FMI, DMI) was written and available from the MEGAPOLI public website.
Sofiev M., M. Prank, A. Baklanov (Eds) (2011): Influence of Regional Scale Emissions on Megacity Air Quality. Deliverable D5.5, MEGAPOLI Scientific Report 11-12, MEGAPOLI-38-REP-2011-06, 60p, ISBN: 978-87-92731-16-6, http://megapoli.dmi.dk/publ/MEGAPOLI_sr11-12.pdf

Deliverable 5.6: Influence of North American Megacities on European Atmospheric Composition (lead: NILU) was written and available from the MEGAPOLI public website.
Eckhardt S., M. Cassiani, A. Stohl (2011): Influence of North American Megacities on European Atmospheric Composition. Deliverable D5.6, MEGAPOLI Scientific Report 11-10, MEGA-POLI-36-REP-2011-06, 28p.

Deliverable 5.7: Estimate of Megacity Impacts in a Future Climate (lead: UK MetO) was written and available from the MEGAPOLI public website.
Folberth G.A., S. Rumbold, W.J. Collins, T. Butler (2011): Estimate of Megacity Impacts in a Future Climate. Deliverable D5.7, MEGAPOLI Scientific Report 11-09, MEGAPOLI-35-REP-2011-06, 21p.

Milestone 5.1: Selecting key improvements to undertake for regional and global models for megacities plumes (lead: NILU, FMI; month 18) has been achieved. The key improvement areas have been reviewed. The following fields were considered to be the most urgent ones: the evaluation of the boundary conditions for the CWF models, the integration of numerical weather prediction and atmospheric chemical transport models, the data assimilation of the various chemical species, the understanding of several chemical and physical processes, the construction of model ensembles, the scientific evaluation of the CWF models, including their evaluation against data, and the statistical post-processing of the model results.

 

Significant results: Methodologies and scientific achievements related to WP including partners' contributions

 The WP 5 regional model ensemble has been designed and all its parameters decided. The first modelling data have been compiled by the FMI, tested and included to the ensemble creation software. The ensemble will cover the baseline year 2005 and two Paris campaigns, both in 2009 and 2010. All the models will perform the European-scale simulations using harmonised emissions, although their own meteorological datasets. A substantial number of reviewed articles have been already published.

 

Socio-economic relevance and policy implications

A new PM2.5 limit value has been proposed though the CAFE process to strengthen the current PM10 limit value (COM(2005) 446 final). In our opinion, the improved and better evaluated modeling methods that will result from MEGAPOLI will be crucial in the implementation of this directive. The changes of limit values and for instance, the physical measures to be selected in the future directives for particulate matter (e.g., PM2.5, PM0.1, particle number concentrations, etc.), should evidently rely on a sound understanding of emissions of aerosols and precursors as well as atmospheric processes over a range of scales.

 

Discussion and conclusion

There has been substantial progress in developing and evaluating the satellite-based methods, especially for the measurement of tropospheric gases, and also progress in case of aerosols. An extensive review is in progress on operational chemical weather forecasting models on regional and continental scales; the aim of this activity is to evaluate and analyze the advantages and limitations of individual models used.
Substantial progress has been achieved regarding the development of individual models towards an improved evaluation of the impacts of megacities. Several participants have collaborated closely on various aspects of model development.
The representation of chemical processes has been improved substantially in the global models. It was planned to use the EDGAR v4.0 emission database for a joint modeling effort and intercomparison. Because the emission data set is delayed, discussions are now under way how to replace this emission data set.

 

List of WP5 reports, publications, presentations

Baklanov, A., Mestayer, P., Clappier, A., Zilitinkevich, S., Joffre, S., Mahura, A., Nielsen, N.W., (2008): Towards improving the simulation of meteorological fields in urban areas through updated/advanced surface fluxes description. Atmos. Chem. Phys., 8, 523-543.

Bergamaschi, P., C. Frankenberg, J.F. Meirink, M. Krol1, F. Dentener, T. Wagner, U. Platt, J.O. Kaplan, S. Korner, M. Heimann, E.J. Dlugokencky, A. Goede, (2007): Satellite chartography of atmospheric methane from SCIAMACHY onboard ENVISAT: (II) Evaluation based on inverse model simulations, J. Geophys. Res., 112, D02304, doi:10.1029/2006JD007268.

Boersma, K.F., H.J. Eskes, J.P. Veefkind, E.J. Brinksma, R.J. van der A, M. Sneep, G.H.J. van den Oord, P.F. Levelt, P. Stammes, J.F. Gleason and E.J. Bucsela, (2007) Near-real time retrieval of tropospheric NO2 from OMI, Atm. Chem. Phys./, 2013-2128, sref:1680-7324/acp/2007-7-2103.

Butler, T. M., and M. G. Lawrence, -(2009): The influence of megacities on global atmospheric chemistry: a modelling study, Environ. Chem. 6, 291-225.

Butler, T. M., (2009): Automated sequence analysis of atmospheric oxidation pathways: SEQUENCE version 1.0, Geosci. Model Dev. Discuss. 2, 1001-1021.

Butler T.M. and Lawrence M.G. and Gurjar B.R. And van Aardenne J. and Schultz M. and Lelieveld J., (2008): The representation of emissions from megacities in global emission inventories, Atmospheric Environment 42, 703-716.

Chen, D., Zhou, B., Beirle, S., Chen, L. M., and Wagner, T., (2009): Tropospheric NO2 column densities deduced from zenith-sky DOAS measurements in Shanghai, China, and their application to satellite validation, Atmos. Chem. Phys., 9, 3641-3662.

Folberth, G. A., Abraham, N. L., Collins, W. J., Johnson, C. E., Morgenstern, O, O'Connor, F. M., Young, P., (2009)a: The Hadley Centre Earth-System-Model HadGEM2 - Outline, Evaluation. 7th Intl. Conference on Air Quality - Science and Application, Istanbul 25.III.2009 (Istanbul, Turkey, 24-27 March 2009).

Folberth, G. A., Abraham, N. L., Collins, W. J., Johnson, C. E., Morgenstern, O., O’Connor F. M., Young, P., -(2009b)-: Evolution of SOA formation and budget over the 21(st) century with implications for air quality. in abstracts to the 19th Annual VM Goldschmidt Conference, 22-26 June 2009, Davos, Switzerland, published in Geochimica et Cosmochimica Acta, Vol 73, Iss 13, p. A387.

Hayn, M., Beirle, S., Hamprecht, F. A., Platt, U., Menze, B. H., and Wagner, T.,, (2009): Analysing spatio-temporal patterns of the global NO2-distribution retrieved from GOME satellite observations using a generalized additive model, Atmos. Chem. Phys., 9, 1-19.

Heland, J., Schlager, H., Richter, A., Burrows, J. P., (2002): First comparison of tropospheric NO2 column densities retrieved from GOME measurements and in situ aircraft profile measurements, GRL, doi:10.1029/2002GL015528.

Ibrahim, O., Shaiganfar, R., Sinreich, R., Stein, T., Platt, U., and Wagner, T., (2010): Auto MAX-DOAS measurements around entire cities: quantification of NOx emissions from the cities of Mannheim and Ludwigshafen (Germany), Atmos. Meas. Tech. Discuss., 3, 469-499.

Jalkanen J.-P., Brink A., Kalli J., Pettersson H., Kukkonen J. and Stipa T., (2009): A modelling system for the exhaust emissions of marine traffic and its application in the Baltic Sea area, Atmos. Chem. Phys., 9, 9209-9223.

Jockel P., Tost H., Pozzer A., Bruhl C. Bucholz J., Ganzeveld L., Hoor P., Kerkweg A,., Lawrence M.G., Sander R., Steil B., Stiller G., Tanarhte M., Taraborrelli D., Van Aardenne J., Lelieveld J.,, (2006): The atmospheric chemistry general circulation model ECHAM5/MESSy1: consistent simulation of ozone from the surface to the mesosphere, Atmos. Chemistry and Physics, 6, 5067-5104.

Kukkonen, J., T. Klein, K. Karatzas, K. Torseth, A. Fahre Vik, R. San Jose, T. Balk, and M. Sofiev, (2009). COST ES0602: towards a European network on chemical weather forecasting and information systems, Adv. Sci. Res., 3, 27-33, www.adv-sci-res.net/3/27/2009/, Contributions of the 8th EMS Annual Meeting and 7th European Conference on Applied Climatology, 2008.

Kukkonen, J., Balk, T., Schultz, D., Baklanov, A., Klein, T., Miranda, A.I., Monteiro, A., Hirtl, M., Lehtinen, K., Karatzas, K., San Jose, R., Astitha, M., Kallos, G., Schaap, M., Reimer, E., Jakobs, H., Tarvainen, V., Boy, M., Peuch, V.-H., Poupkou, A., Kioutsioukis, J., Finardi, S., Sofiev, M. and Sokhi, R., (2010): Operational chemical weather forecasting models on a regional scale in Europe. Manuscript submitted for publication.

Lawrence M.G, Butler T.M., Steinkamp J., Gurjar B.R. and Lelieveld J., (2007): Regional pollution potentials of megacities and other major population centres, Atmospheric Chemistry and Physics 7, 3969-3987.

Manders, A.M.M., Schaap, M., Hoogerbrugge, R., (2009a). Testing the capability of the chemistry transport model LOTOS-EUROS to forecast PM10 levels in the Netherlands, Atmospheric Environment, 43 (26), pp. 4050-4059. DOI: 10.1016/j.atmosenv.2009.05.006.

Manders, A.M.M., M. Schaap,  M. Jozwicka, (2009b). Sea salt concentrations over Europe, measurements and modelling, Goldschmidt Conference, Davos Zwitserland, 21-26 May 2009.

Mielonen, T., A. Arola, M. Komppula, J. Kukkonen, J. Koskinen, G. de Leeuw and K. E. J. Lehtinen, (2009). Comparison of CALIOP level 2 aerosol subtypes to aerosol types derived from AERONET inversion data. Geophysical Research Letters, Geophys. Res. Lett., 36, L18804.

Morcrette, J.-J., O. Boucher, L. Jones, D. Salmond, P. Bechtold, A. Beljaars, A. Benedetti, A. Bonet, J. W. Kaiser, M. Razinger, M. Schulz, S. Serrar, A. J. Simmons, M., Sofiev, M. Suttie, A. M. Tompkins, and A. Untch, (2009): Aerosol analysis and forecast in the ECMWF Integrated Forecast System. Part I: Forward modelling, J. Geophys. Res., 114, D06206,, doi:10.1029/2008JD011235

Saarnio, K., Aurela, M., Timonen, H. Saarikoski, S., Teinila, K., Makela, T.,  Sofiev, M., Koskinen, J., Aalto, P.P., Kulmala, M., Kukkonen, J. and Hillamo, R., (2010): Fine particles in fresh smoke plumes from boreal forest-fires, Science of the Total Environment, 10.1016/j.scitotenv.2010.03.010, in press.

Schaap, M., E.Hendriks, H. Denier van der Gon., (2009). Constraining the potential source strength of various soil dust sources contributing to atmospheric PM10 concentrations in Europe,  Goldschmidt Conference, Davos Zwitserland, 21-26 May 2009.

Sofiev, M., Genikhovich, E., Keronen, P., Vesala, T., (2010): Boundary layer diagnostic for dispersion applications as part of meteo-to-dispersion modelling interface, J. of Appl. Meteorol. and Climatology, DOI: 10.1175/2009JAMC2210.1

Sofiev M., V.Sofieva, Elperin, T., Kleeorin, N., Rogachevski, I., Zilitnkevich, S., (2009): Turbulent Diffusion and Turbulent Thermal Diffusion of Aerosols in Stratified Atmospheric Flows, J. Geophys. Res., 114, D18209, doi:10.1029/2009JD011765.

Sofiev, M., R. Vankevich, M. Lotjonen, M. Prank, V. Petukhov, T. Ermakova, J. Koskinen and J. Kukkonen, (2009b). An operational system for the assimilation of satellite information on wild-land fires for the needs of air quality modelling and forecasting, Atmos. Chem. Phys., 9, 6833-6847.

Wagner, T., Ibrahim, O., Shaiganfar, R., and Platt, U., (2010): Mobile MAX-DOAS observations of tropospheric trace gases, Atmos. Meas. Tech., 3, 129-140.

Zilitinkevich, S.S., Elperin, T., Kleeorin, N., Rogachevskii, I., Esau, I., Mauritsen, T., and Miles, M. W., (2008): Turbulence energetics in stably stratified geophysical flows: strong and weak mixing regimes. Quart. J. Roy. Met. Soc. 134, 793-799.

Zilitinkevich, S.S., Mammarella, I., Baklanov, A.A., and Joffre, S.M., (2008): The effect of stratification on the aerodynamic roughness length and displacement height. Boundary-Layer Meteorol. 129, 179-190.

Zilitinkevich, S.S., and Esau, I.N., (2009): Planetary boundary layer feedbacks in climate system and triggering global warming in the night, in winter and at high latitudes. Submitted to Geography, Environment and Sustainability.

Zilitinkevich, S.S., Elperin, T., Kleeorin, N., L'vov, V., and Rogachevskii, I., (2009):  Energy- and flux-budget (EFB) turbulence closure model for stably stratified flows. Part II: The role of internal gravity waves. Boundary-Layer Meteorol. DOI: 10.1007/s10546-009-9424-0

Zilitinkevich, S.S., Esau, I.N., T., Kleeorin, and Rogachevskii, I., (2009):  Alternative similarity theory formulations in searching for the dissipation length scale in the stably stratified sheared turbulence. Submitted to Boundary-Layer Meteorol.

Veriankaitė, L., Siljamo, P., Sofiev, M., Sauliene, I., and Kukkonen, J., (2010): Modelling analysis of source regions of long-range transported birch pollen that influences allergenic seasons in Lithuania, Aerobiologia, International Journal of Aerobiology, Vol. 26, Number 1, 47-62.


FP7 EC MEGAPOLI, 2008-2011