SEUGI 194

STRASBOURG (FRANCE) 14-17 JUIN 1994

"ATMOSFERA: un Systeme Informatique, realise sous SAS,. dedie it la gestion, prevision et analyse de donnees meteorologiques et de

pollution atmospherique sur territoire urbain"

P. Fedelel , G. Grandoni1, M.e. Mammarella1, G. Marcon2 et M. Sanarico2

Resume. Les activites conduites par ENEA ("Ente per Ie Nuove Tecnologie, I'Energia e l'Ambiente") SUI la pollution urbaine ont mis en evidence la necessite de disposer d'un InstrUment Infonnatique qui puisse pennettre une meilleure connaissance des phenomenes complexes regissant la pollution atrnospherique, afin soit de prevoir et definir les situations les plus critiques, soit de permettre all" decideurs de mieux evaluer l'efficacire des mesures de limitation du trafic ou de route autre action necessaire. Dans ce but ENEA a realise ATMOSFERA, un Systeme Infonnatique sous SAS (Statistical Analysis System): la structure logique de ce Systeme permet la gestion de series historiques de donnees soit de concentrations dans l'air de polluants que de parametres meteorologiques. et en paniculier l'application sur ces memes donnees des modeles stochastiques pour la prevision de la tendance des niveaux de pollution atmospherique. ATMOSFERA est ainsi utilisable de Ia pan des Administrations Publiques pour repondre a leur propres necessites; en particuHer la Municipalite de Rome utilisera ce Systeme pour faire front avec une certaine anticipation aux situations critiques de pollution atmospherique, surtout a cause des emissions dues au trafic automobile (vehicules a essence et diesel) et aux foyers fixes de combustion (installations de chauffage individuel et collectif. chaudieres industrielles, etc.), en presence de conditions atmospheriques defavorables a la dispersion de la pollution.

La presentation sera divisee en trois parties:

a) projet et realisation d' ATMOSFERA. instrument de support pour les Administrations Publiques, dedie it la gestion, l'analyse et la prevision d'episodes aigus de pollution (Dr M.C. Mammarella, en fran~ais);

b) application d'ATMOSFERA a la pollution atmospherique de la ville de Rome: analyse et resultats sur la qualite de l'air relativement aux periodes 1992/93 et 1993/94 (Dr. G. Grandoni, en anglais);

c) particularites d'ATMOSFERA hardware et software et application pratique par ordinateur (Dott. M. Sanarico, en anglais).

I "ENEA, Dipartimento Ambiente - Casaccia, via AnguiUarese nO '301. Roma (Italia)

2 "NOUSTAT". via Campanoni n04. Milano (Italia)

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ATMOSFERA: premiere partie

t'Projet et realisation d'ATMOSFERA, instrument de support pour les Administrations Publiques, dedie it la gestion, l'analyse et la

prevision d'episodes aigus de pollution"

Dr M.C. Mammarella

1. Presentation des activite de I'ENEA

ENEA: Ente per Ie nuove tecnologie, l'energia e l'ambiente (Commissariat pour les technologies nouvelles, l'energie et l'environnement)

La structure pour la realisation des activites, dont l'ENEA est investi en tant

qu'organisation pUblique,est subdivisee en trois Departements:

Depart. Nouvelles Technologies Depart. Energie Depart. Environnement

A son tour Ie Departement de I 'Environnement comprend differentes subdivisions

en Secteurs, finalises soit a la recherche sur l'environnement (chimie et physique

de l'environnement, geologie, hydrogeologie, informatique. etc.), soit a l'etude

des installations industrielles dont on suppose un impact sur l'environnement.

La recherche presentee ici a ete effectuee par un groupe qui s' occupe de

l'informatique appliquee aux problemes d'impact des differents effluents sur

l'environnement. Les activites de ce groupe peuvent etre ainsi schematisees:

- realisation de Banque de Donnees alphanumeriques et cartographiques;

- traitement statistique des donnees sur l'environnement;

- modeles informatises pour impact des differents effluents sur l'environnement;

- reseau informatique et res sources de calcul distribuees.

Ces activites ont pennis de realiser des systemes informatiques integres, finalises

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a revaluation de rimpact sur l'environnement et sur la population des effluents

provenants:

- d'installations industrielles de grandes dimensions (centrales thenniques,

incinerateurs, depots de dechets, etc.);

- du trafic routier (soit sur simple autoroute, soit sur zone urbaine);

- du chauffage collectif ou individuel (zone urbaine).

2. Le Projet ATMOSFERA

Afin de disposer d 'un instrument scientifique pour r etude de la pollution dans un

environnement urbain, il a ete mis a point un prototype qui est I' objet de cette

relation.

Les buts du Systeme Informatique, denomme ATMOSFERA (Analyse et

Traiternent de donnees Meteorologiques et de pollution avec l'Objectif

d'identifier sur base Statistique les PHEnomenes Relatifs a la pollution de

r Atmosphere), a partir des niveaux de pollution releves sur les stations de mesure

du reseau de surveillance du PMP (organisation regionale de sante) qui

repn!sentent I' agglomeration sont les suivants:

- presentation dynamique, intuitive et de synthese, de la qualite de l'air dans

l' agglomerat urbain pour informer les decideurs et Ie public;

- comprehension des phenomenes complexes regissant la pollution atmospherique;

- prevision des tendances des niveaux de pollution pour Ie jour courant et Ie

Iendemain et leur comparaison avec les differentes normes de qualite de l' air

existantes pour aider les decideurs a prendre les actions necessaires;

- evaluation a posteriori de I'efficacite des mesures entreprises par r Autorite,

telles que la limitation du trafk individuel dans Ie centre de la ville:· ceci sera un

des objets de la relation du Dr. Grandoni;

- programmation de l' amelioration de la qualite de l' air dans l' environnement

urbain.

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3. Structure logique d' ATMOSFERA

La structure logique de ATMOSFERA se compose de deux modules centraux

contenants:

- une Base des Donnees meteorologiques et de pollution de l' air;

- une librairie de modeles statistiques de prevision (ARMAX et autoregressifs).

Un module d'entree du Systeme permet l'acquisition des donnees, leuf validation

et Ie stockage dans la Base des Donnees.

Le module de sortie du Systeme est compose d 'un interface graphique evolue qui

gere Ie dialogue avec r exterieur.

Tout ceci represente la version 1.1 de ATMOSFERA; par ailleurs il est deja en

COUfS d'elaboration la version 2.0, qui est foumie d'une librairie de modeles

statistiques beaucoup plus etendue que celIe contenue dans la version precedente,

comprenant des modeles qui pennettent d 'utiliser des infonnations heterogenes

entre elles, en particulier celles provenantes de sondages effectues par un SODAR

(direction et vitesse du vent it differentes hauteurs dans l'atmosphere, et presence

de zones stables dans la couche limite, entre 0 et 1000 m environ de hauteur sur

Ie niveau du sol).

Ce demier aspect sera illustre dans la relation suivante tenue par Ie Dr. Sanarico.

La version finale de ATMOSFERA prevoit des stations multimediales dediees a l'information du public sur la qualite de rair en temps reel.

4. Presentation directe it l'ordinateur des applications d' ATMOSFERA

La presentation d' ATMOSFERA a l'ordinateur a ete realisee oralement pendant t }

f. l'exposition au Congres; a titre d'exemple on reporte ici quelques uns des ecrans i ~ projectes.

! Le premier (Fig. 1) montre Ie plan de la ville de Rome avec l'animation sur base i f r ~:-:

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Dans Ie deuxieme (Fig. 2) on peut voir les valeurs moyennes jouralieres des

concentrations dans l'air de N02; la couleur rouge montre les donnees qui

depassent Ie se'Uil d'attention, et Ie noir Ie seuil d'alanne, d'apres la

reglementation italienne.

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ATMOSFERA: second part

Air pollution in the city of Rome: air quality analysis and results given by Atmosfera within 1992/93 and 1993/94

Dr. G. Grandoni

1. Introduction

For the sake of humankind future, socioeconomic development within each Country should be carried out through achievement of environmental compatibility major goal. ENEA, Italian National Agency, plays an active role in environment monitoring and safeguard through supporting of Public Administrators and Private Companies by means of consultancies and operative proposals during stages concerning analysis, monitoring and prevention of both urban and industrial pollution. Within years, atmosphere has been considered as a container inside which dispose more or less hazardous gaseous waste: air quality acts as an index that points out a not correct relationship of man with environment. In the past years insufficient attention hase been dedicated to this resource and no relevant' intervention to reduce gaseous emission has been predisposed. Due to the lack of planning policies, the few carried out interventions gave insufficient results as they were operated in a emergency and immediateness situation. Informative system ATMOSFERA has been carried out to support a programme both to heal urban environment and to manage interventions. ATMOSFERA will be used by Rome Municipality to face and to prevent environmental emergency situations due above all to traffic pollution.

2.Meteorologic data base

To better understand problems linked to atmosphere. our attention is above all directed to understanding of atmosphere behaviour within layers next to the soil as transport and dispersion of atmospheric gaseous substances takes place within this zone. Studies concerning atmosphere diffusivity features, represent the major step for a correct interpretation of atmospheric physicochemical processes. It is then necessary to have at disposal an adeguate historic series both of

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meteorologic data and of atmospheric low layers vertical structure, organized within opportune and easy consultation data base. Climatology within a particular site acts on air quality level, and infonnations coming from low troposphere give indications concerning diffusive behaviour of atmosphere: in fact with the same emission factors, a stable atmospheric situation, with low wind speed and negligible vertical thermal exchange, lead to high concentrations of air pollutants; em instable atmosphere, i.e. strong wind and strong solar irradiance. means appreciable aloft dispersion of gases; a neutral atmosphere, i.e. strong wind speed, appreciable sky coverage and poor radiative exchanges, means dispersive features intermediate between the two above mentioned. SAS environment potentiality pennitted to realize a meteorologic data base that is able to handle data heterogeneous typologies as hourly anemologic and pluviometric data as well as SODAR remotely sensed data concerning vertical structure of atmospheric low layers, that permits to characterize different atmospheric features.

3. Pollutants concentrations data base

Italian prescriptions, as well as in other COl,lntries, consider two different typologies for what concern air quality levels for the various pollutants within urban areas: attention levels and alarm levels. Characterization of attention and alarm situations is a basic issue to be able to adopt measures to prevent extreme pollution episodes as well as to avoid environmental and sanitary risk situations. Utilization of ATMOSFERA informative system make possible forecast of air pollutants concentration trends on short and medium term, giving Municipalities a tool to manage and to prevent extreme pollution episodes. Validity of urban pollution management policies can be estimated by ATMOSFERA by means of procedures that are able to evaluate efficacy of interventions operated according to legislation, for example traffic restrictions, checking possible benefits.

S. An operative example:Rome

We used informative system ATMOSFERA to study and to analyze air pollutants concentration levels (measured by means of monitoring stations spread over urban territory) within Rome, comparing last two winter seasons .

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Data series relative to various pollutants have been analyzed with the aim to find a possible systematic difference between pollutants concentrations within considered two winter seasons. Results·coming from this study showed that during winter 1993-1994, CO levels were significantly lower than those measured during winter 1992-1993 above all for what concern late evening hours. As air quality within considered periods showed significative differences, a further analysis has been carried out taking into account also meteorologic parameters to assess to what amount air quality variation is attributable to reduced pollutants emissions (from vehicular traffic as well as, eventually, reduced condominial heating) or to a reduced frequency of atmospheric diffusivity meteorologic situations. Analysis of meteorologic conditions showed that rainfalls grew during second period of time (this means an enhanced wash-out of air pollutants), while atmospheric stability dropped (note that a stable atmosphere produce alarm levels above all during late evening hours, i.e. from 18 to 22). The study showed that difference between number of concentration peaks (for CO) is significantly correlated to dropping of stable atmosphere situations during 1993-94 within hours 18 and 22 (Saturdays and Sundays excluded). Furthermore it has been reported some preliminar data obtained by means of an ARMAX like predictive statistical model, to evaluate efficacy of interventions aimed to traffic restrictions; two basic cases have been considered showing significative differences between interventions on urban pollution.

6. Future developments

ENEA realized ATMOSFERA, an informative system relative to chemical (air pollution) and meteorologic data concerning Rome urban basin; the system is supplied both with a set of statistical models for medium range forecast of pollutants concentration levels and with a module for synthetic dysplay of infonnations. The system is aimed to: - display both to decision makers and to citizens information concerning air pollution. - forecast pollutants concentration close to measurement points. at short time. - evaluate efficacy on air quality of traffic restriction interventions (or other interventions) with the aim to improve decision makers policies. Within urban pollution Programmes, ATMOSFERA will be supplied with real time connection to acquire: - Rome monitoring station pollution data;

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- hourly meteorologic data; - remote sensing data; _ weather centre medium range forecast within Rome area.

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ATMOSFERA: third part

ATMOSFERA hardware and software features and practical computer application; future developments

Dr. M. Sanarico

ATMOSFERA 1.1 is the first version of a SAS-based system developed to cope with the need to help monitoring, understanding and forecasting the quality of the air in a large urban area. In the present case the interested area~ as already said, is that corresponding to the municipality of Rome. The current version of ATMOSFERA runs under Windows 3.1 with SAS System 6.08 and requires the BASE, STAT, FSP.GRAPH and ETS modules. ATMOSFERA 2.0 will run also under the UNIX operating system and the IML module will also be necessary. The keywords we would use to summarize the main features of ATMOSFERA are the following: object-oriented, visualization-based, user-friendly and forecasting aimed. ATMOSFERA is organized into four modules: Data Management, Statistical Analysis, Graphical Analysis, and Forecasting. The Data Management module is to be used to import. edit and check the data from both the pollution measurement stations and the meteorological stations. A number of data checks have been automated in order to guarantee consistency of units of measurements through time and removal of certain machine-detectable errors. The original data are kept to allow further in-deep checking. The Statistical Analysis module allows to carry-out a wide range of descriptive and exploratory statistical analysis. The focus is on characterizing the distributions of the relevant quantities adopting different points of views. For, instance displaying the monthly distribution of an airborne chemical in a given year by means of box-and-whisker plots or the cumulative distribution of the same in a selected time interval. A further capability is to perform a "tailored-for-the-problem" cluster analysis by applying the Modeclus procedure on specially pre-treated data. The Graphical Analysis module is dedicated to the data visualization and the difference with the Statistical Analysis module is that the data more than the results of a statistical analysis are generally presented. A very noticeable capability contained in this latter module is the dynamic visualization of the joint pollution and meteorological data on a schematized map of the urban area of

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interest. The last module presented is the Forecasting module. Two classes of forecasting models have been included within this module: simple autoregressive models and transfer function models. Autoregressive models are an extension of the standard multiple linear regression model. The key difference between such models is the error structure which in the former is assumed to be independently and identically distributed an a zero­mean normal distribution, whereas in the latter can be an autoregressive process of whatever order. Transfer function models are much more sophisticated ad treat both the predictors and the dependent variable as stochastic processes whose realization is given by the observed time series. They are equivalent to the so-called ARMAX (Auto Regressive Moving Average with eXogenous variables) models. The possibility given in ATMOSFERA to define multiple scenarios for the weather forecasts gives the ability to perfonn simulations concerning different meteorological conditions, which may correspond to a range of situations between the worst and best possible departure from the official weather forecasts. The forecasting tools provided with ATMOSFERA 1.1, although useful, are quite limited with respect to the complexity of the problem. ATMOSFERA 2.0 will be endowed of a much more powerful set of forecasting tools embedded into a different strategy_ In particular the forthcoming new Forecasting module will make available to the use a class of dynamic models (that is, time-varying coefficient models, see Harrison and West, 1989). One ambitious objective we are also pursuing is to achieve the ability of the joint modeling and forecasting for the chemicals of interest, integrating the simultaneous measurements from all the different stations. The idea is to adopt models similar to the Dynamical Graphical Models (Queen and Smith, 1992, 1993). This kind of models allows the inclusion of a priori information, the integration of information from heterogeneous sources and the modeling of dependence of both correlation and causal type (according to the definition of causality given by Granger, 1969). Moreover, such models may account for nonlinear behaviour and non Gaussian distributions. This enhancement is specially important in view of the systematic gathering of measurements with the SODAR, which we think will make available new valuable data.

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