Fully-coupled air-quality models running in “feedback” and “no-feedback” configurations were compared against each other and observation network data as part of Phase 2 of the Air Quality Model ...Evaluation International Initiative. In the “no-feedback” mode, interactions between meteorology and chemistry through the aerosol direct and indirect effects were disabled, with the models reverting to climatologies of aerosol properties, or a no-aerosol weather simulation, while in the “feedback” mode, the model-generated aerosols were allowed to modify the models' radiative transfer and/or cloud formation processes. Annual simulations with and without feedbacks were conducted for domains in North America for the years 2006 and 2010, and for Europe for the year 2010. Comparisons against observations via annual statistics show model-to-model variation in performance is greater than the within-model variation associated with feedbacks. However, during the summer and during intense emission events such as the Russian forest fires of 2010, feedbacks have a significant impact on the chemical predictions of the models.
The aerosol indirect effect was usually found to dominate feedbacks compared to the direct effect. The impacts of direct and indirect effects were often shown to be in competition, for predictions of ozone, particulate matter and other species. Feedbacks were shown to result in local and regional shifts of ozone-forming chemical regime, between NOx- and VOC-limited environments. Feedbacks were shown to have a substantial influence on biogenic hydrocarbon emissions and concentrations: North American simulations incorporating both feedbacks resulted in summer average isoprene concentration decreases of up to 10%, while European direct effect simulations during the Russian forest fire period resulted in grid average isoprene changes of −5 to +12.5%. The atmospheric transport and chemistry of large emitting sources such as plumes from forest fires and large cities were shown to be strongly impacted by the presence or absence of feedback mechanisms in the model simulations. Summertime model performance for ozone and other gases was improved through the inclusion of indirect effect feedbacks, while performance for particulate matter was degraded, suggesting that current parameterizations for in- and below cloud processes, once the cloud locations become more directly influenced by aerosols, may over- or under-predict the strength of these processes. Process parameterization-level comparisons of fully coupled feedback models are therefore recommended for future work, as well as further studies using these models for the simulations of large scale urban/industrial and/or forest fire plumes.
The calculation of aerosol optical properties from aerosol mass is a process subject to uncertainty related to necessary assumptions on the treatment of the chemical species mixing state, density, ...refractive index, and hygroscopic growth. In the framework of the AQMEII-2 model intercomparison, we used the bulk mass profiles of aerosol chemical species sampled over the locations of AERONET stations across Europe and North America to calculate the aerosol optical properties under a range of common assumptions for all models. Several simulations with parameters perturbed within a range of observed values are carried out for July 2010 and compared in order to infer the assumptions that have the largest impact on the calculated aerosol optical properties. We calculate that the most important factor of uncertainty is the assumption about the mixing state, for which we estimate an uncertainty of 30–35% on the simulated aerosol optical depth (AOD) and single scattering albedo (SSA). The choice of the core composition in the core–shell representation is of minor importance for calculation of AOD, while it is critical for the SSA. The uncertainty introduced by the choice of mixing state choice on the calculation of the asymmetry parameter is the order of 10%. Other factors of uncertainty tested here have a maximum average impact of 10% each on calculated AOD, and an impact of a few percent on SSA and g. It is thus recommended to focus further research on a more accurate representation of the aerosol mixing state in models, in order to have a less uncertain simulation of the related optical properties.
•We calculate optical properties from several aerosol models using same assumptions.•We test choices on mixing state, refractive index, density and hygroscopicity.•The most sensitive parameter is the aerosol mixing state.•The related uncertainty on calculated AOD and SSA is 30–35%.
The Air Quality Model Evaluation International Initiative (AQMEII) has now reached its second phase which is dedicated to the evaluation of online coupled chemistry-meteorology models. Sixteen ...modeling groups from Europe and five from North America have run regional air quality models to simulate the year 2010 over one European and one North American domain. The MACC re-analysis has been used as chemical initial (IC) and boundary conditions (BC) by all participating regional models in AQMEII-2. The aim of the present work is to evaluate the MACC re-analysis along with the participating regional models against a set of ground-based measurements (O3, CO, NO, NO2, SO2, SO42−) and vertical profiles (O3 and CO). Results indicate different degrees of agreement between the measurements and the MACC re-analysis, with an overall better performance over the North American domain. The influence of BC on regional air quality simulations is analyzed in a qualitative way by contrasting model performance for the MACC re-analysis with that for the regional models. This approach complements more quantitative approaches documented in the literature that often have involved sensitivity simulations but typically were limited to only one or only a few regional scale models. Results suggest an important influence of the BC on ozone for which the underestimation in winter in the MACC re-analysis is mimicked by the regional models. For CO, it is found that background concentrations near the domain boundaries are rather close to observations while those over the interior of the two continents are underpredicted by both MACC and the regional models over Europe but only by MACC over North America. This indicates that emission differences between the MACC re-analysis and the regional models can have a profound impact on model performance and points to the need for harmonization of inputs in future linked global/regional modeling studies.
Atmospheric emission inventories are important tools for studying air quality and to set up possible remediation plans in areas characterised by nonattainment of the limit values established by ...legislation. In industrialised countries a considerable fraction of the emissions is due to road traffic, in particular in urban areas. For this reason emissions from road traffic must be estimated as accurately as possible, a task that can be performed, for the European vehicle fleet, thanks to the availability of the COPERT III methodology. This methodology is powerful and accurate, even if its algorithms can be difficult to apply in a regional emission inventory; moreover the collection of the necessary input data requires a lot of resources and time. This paper describes the road traffic emission inventory estimated for Region Sardinia (Italy) with a bottom-up approach. The estimation has been done by means of a software tool (EMITRA—EMIssions from road TRAnsport) which implements the COPERT III methodology. The resulting emission inventory has been compared against another emission inventory for Sardinia and against emission inventories for other Italian regions, to evaluate its reliability.
The complexity of air quality modeling systems, air quality monitoring data make ad-hoc systems for model evaluation important aids to the modeling community. Among those are the ENSEMBLE system ...developed by the EC-Joint Research Center, and the AMET software developed by the US-EPA. These independent systems provide two examples of state of the art tools to support model evaluation. The two systems are described here mostly from the point of view of the support to air quality model users or developers rather than the technological point of view. While ENSEMBLE is a web based platform for model evaluation that allows the collection, share and treatment of model results as well as monitoring data, AMET is a standalone tool that works directly on single model data. The complementarity of the two approaches makes the two systems optimal for operational, diagnostic and probabilistic evaluations. ENSEMBLE and AMET have been extended in occasion of the AQMEII two-continent exercise and the new developments are described in this paper, together with those foreseen for the future.
APOLLO2 is a new version of the long range Lagrangian particle dispersion model integrated into ARIES (Accidental Release Impact Evaluation System), the system that I.S.P.R.A. (Italian National ...Institute for Environmental Protection and Research) developed to provide prognosis about the dispersion of radioactive clouds in case of nuclear accidents. In this paper the theoretical aspects of the APOLLO2 formulation are briefly described. Moreover, the model performances have been evaluated qualitatively and quantitatively against the observations of the first release of the European Tracer Experiment (ETEX). The global analysis showed a FA2 = 56%, a FA5 = 78%, and a good agreement for intermediate values within the Q–Q plot. Considering a total of 126 stations, the number of locations where NMSE < 10, PCC > 0.7 and FMT > 20% is respectively 91, 65 and 86. The number of stations where the Chang and Hanna (2004) performance evaluation criteria are satisfied is 33. The capability of APOLLO2 to predict arrival time, cloud duration and time of peak is comparable to the one shown by similar models.
Finally, the sensitivity of the model to some input variables has also been investigated.
► We present the APOLLO2 long range atmospheric Lagrangian particle model. ► Qualitative comparison of APOLLO2 predictions and ETEX1 observations is good. ► Quantitative comparison is also of good quality (e.g. FA2 = 56%, FA5 = 78%). ► Sensitivity analysis has given hints to improve the model performances.
In this paper we describe an advanced database for the site characterization of seismic stations, named “CRISP—Caratterizzazione della RIsposta sismica dei Siti Permanenti della rete sismica” (
...http://crisp.ingv.it
, quoted with
https://doi.org/10.13127/crisp
), designed for the Italian National Seismic Network (Rete Sismica Nazionale, RSN, operated by Istituto Nazionale di Geofisica e Vulcanologia). For each site, CRISP collects easily accessible station information, such as position, type(s) of instrumentation, instrument housing, thematic map(s) and descriptive attributes (e.g., geological characteristics, etc.), seismic analysis of recordings, and available geophysical investigations (shear-wave velocity
V
S
profile, non-linear decay curve). The archive also provides key proxy indicators derived from the available data, such as the time-averaged shear-wave velocity of the upper 30 m from the surface (V
S30
) and site and topographic classes according to the different seismic codes. Standardized procedures have been applied as motivated by the need for a homogenous set of information for all the stations. According to European Plate Observing System infrastructural objectives for the standardization of seismological data, CRISP is integrated into pre-existing INGV instrument infrastructures, shares content with the Italian Accelerometric Archive, and complies map information about the stations, as well as local geology, through web services managed by Istituto Superiore per la Protezione e la Ricerca Ambientale. The design of the CRISP archive allows the database to be continually updated and expanded whenever new data are available from the scientific community, such as the ones related to new seismic stations, map information, geophysical surveys, and seismological analyses.
This study is conducted in the framework of the Air Quality Modelling Evaluation International Initiative (AQMEII) and aims at the operational evaluation of an ensemble of 12 regional-scale chemical ...transport models used to predict air quality over the North American (NA) and European (EU) continents for 2006. The modelled concentrations of ozone and CO, along with the meteorological fields of wind speed (WS) and direction (WD), temperature (T), and relative humidity (RH), are compared against high-quality in-flight measurements collected by instrumented commercial aircraft as part of the Measurements of OZone, water vapour, carbon monoxide and nitrogen oxides by Airbus In-service airCraft (MOZAIC) programme. The evaluation is carried out for five model domains positioned around four major airports in NA (Portland, Philadelphia, Atlanta, and Dallas) and one in Europe (Frankfurt), from the surface to 8.5 km. We compare mean vertical profiles of modelled and measured variables for all airports to compute error and variability statistics, perform analysis of altitudinal error correlation, and examine the seasonal error distribution for ozone, including an estimation of the bias introduced by the lateral boundary conditions (BCs). The results indicate that model performance is highly dependent on the variable, location, season, and height (e.g. surface, planetary boundary layer (PBL) or free troposphere) being analysed. While model performance for T is satisfactory at all sites (correlation coefficient in excess of 0.90 and fractional bias less than or equal to 0.01 K), WS is not replicated as well within the PBL (exhibiting a positive bias in the first 100 m and also underestimating observed variability), while above 1000 m, the model performance improves (correlation coefficient often above 0.9). The WD at NA airports is found to be biased in the PBL, primarily due to an overestimation of westerly winds. RH is modelled well within the PBL, but in the free troposphere large discrepancies among models are observed, especially in EU. CO mixing ratios show the largest range of modelled-to-observed standard deviations of all the examined species at all heights and for all airports. Correlation coefficients for CO are typically below 0.6 for all sites and heights, and large errors are present at all heights, particularly in the first 250 m. Model performance for ozone in the PBL is generally good, with both bias and error within 20%. Profiles of ozone mixing ratios depend strongly on surface processes, revealed by the sharp gradient in the first 2 km (10 to 20 ppb km super(-1)). Modelled ozone in winter is biased low at all locations in the NA, primarily due to an underestimation of ozone from the BCs. Most of the model error in the PBL is due to surface processes (emissions, transport, photochemistry), while errors originating aloft appear to have relatively limited impact on model performance at the surface. Suggestions for future work include interpretation of the model-to-model variability and common sources of model bias, and linking CO and ozone bias to the bias in the meteorological fields. Based on the results from this study, we suggest possible in-depth, process-oriented and diagnostic investigations to be carried out next.
The paper presents an approach to the treatment and analysis of long-range transport and dispersion model forecasts. Long-range is intended here as the space scale of the order of few thousands of ...kilometers known also as continental scale. The method is called multi-model ensemble dispersion and is based on the simultaneous analysis of several model simulations by means of ad-hoc statistical treatments and parameters. The models considered in this study are operational long-range transport and dispersion models used to support decision making in various countries in case of accidental releases of harmful volatile substances, in particular radionuclides to the atmosphere. The ensemble dispersion approach and indicators provide a way to reduce several model results to few concise representations that include an estimate of the models’ agreement in predicting a specific scenario. The parameters proposed are particularly suited for long-range transport and dispersion models although they can also be applied to short-range dispersion and weather fields.
A system is presented that allows the centralised real-time acquisition, analysis, and redistribution of the results produced by a community of atmospheric long-range transport and dispersion models. ...The models are used operationally by national authorities in different countries in Europe and around the world to forecast the long-range (100–2000 km) dispersion of accidental releases of radioactive material in the atmosphere. The ENSEMBLE system is conceived to allow decision makers and scientific advisors to decision makers to consult in real-time several atmospheric predictions produced during and after the release. The availability of several model predictions through the system allows collating several results into few concise representations and the use of the multi-model ensemble technique to determine the degree of agreement of model results in the absence of monitoring data. The paper presents the technical concepts behind the ENSEMBLE system, the methodology adopted to acquire several model predictions in real-time and to produce the multi-model analysis. Some examples of application to fictitious releases are also presented. ENSEMBLE has been specifically designed for the management of long-range atmospheric releases as a consequence of nuclear accidents but its concept is applicable to several other fields of environmental sciences.
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