SMOGSTOP: a model for forecasting maximum daily ozone concentration in Belgium

被引:0
作者
Lissens, G
Debruyn, W
Mensink, C
Dumont, G
机构
[1] Vlaamse Instelling Technol Onderzoek, TAP, Ctr Remote Sensing & Atmospher Proc, B-2400 Mol, Belgium
[2] CELINE, IRCEL, B-1210 Brussels, Belgium
关键词
ozone forecasting; pattern matching; emission stratification;
D O I
10.1002/1099-095X(200009/10)11:5<511::AID-ENV415>3.0.CO;2-G
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Every summer, ground level ozone concentrations rise in Belgium and cause episodes of photochemical summer smog. This phenomenon is the cause of well recognised public health distress, especially for people suffering from respiratory diseases. To warn groups of sensitive people against forthcoming smog episodes, VITO (the Flemish Institute for Technological Research) and VMM (the Flemish Environmental Agency) have joined forces to create an ozone pollution forecasting model, called SMOGSTOP (Statistical Model Of Groundlevel Short Term Ozone Pollution). SMOGSTOP is used by Belgian government agencies to issue ozone reports and warnings in the media (TV, radio, internet, etc.). Ozone pollution levels, as well as concentrations of other air pollutants, are monitored in Belgium by the telemetric air quality measuring networks of the three Belgian regions: Flanders, Wallonia and Brussels. The major meteorological variables, such as the windvector, temperature, pressure, humidity and precipitation, are also monitored by the same networks. The historical time series of those variables, generated by the networks, are the source of input data for SMOGSTOP. Photochemical ozone pollution is the result of complex non-linear interactions between atmospheric pollutants and meteorology. As a consequence, it is extremely difficult to determine relationships between source emissions (ozone precursors) and ambient pollutant concentrations (ozone). To deal with this complexity, SMOGSTOP was constructed as an empirical model, applying a VITO tailor-made methodology called stratified pattern matching, to link meteorological and precursor information into ozone forecasts. In this paper, an overview of the process of ozone formation in Belgium is given, followed by the definition of the explanatory variables which will be used in the model. Then the methodology behind the model is reported and finally the results of the forecasting efforts in the period of 1.5.1995 till 31.8.1995 are presented. Copyright (C) 2000 John Wiley & Sons, Ltd.
引用
收藏
页码:511 / 521
页数:11
相关论文
共 17 条
[1]  
AMMAN M, 1998, 6 DG XI IIASA EUR CO
[2]  
[Anonymous], AIR QUALITY METEOROL
[3]  
BUILTJES PJH, 1996, 96274 TNO MEP R
[4]  
DEMUER D, 1993, RECENT DEV OZONE LAY
[5]  
DUMONT G, 1994, PHOTOCHEMICAL AIR PO
[6]   SURFACE OZONE AND METEOROLOGICAL PREDICTORS ON A SUBREGIONAL SCALE [J].
FEISTER, U ;
BALZER, K .
ATMOSPHERIC ENVIRONMENT PART A-GENERAL TOPICS, 1991, 25 (09) :1781-1790
[7]   METEOROLOGICAL AND ALTITUDINAL INFLUENCES ON THE CONCENTRATION OF OZONE AT GREAT DUN FELL [J].
GAY, MJ .
ATMOSPHERIC ENVIRONMENT PART A-GENERAL TOPICS, 1991, 25 (09) :1767-1779
[8]   CHEMISTRY AND PHYSIOLOGY OF LOS-ANGELES SMOG [J].
HAAGENSMIT, AJ .
INDUSTRIAL AND ENGINEERING CHEMISTRY, 1952, 44 (06) :1342-1346
[9]   MECHANISM OF SPRING HIGH OXIDANT EPISODE - A METEOROLOGICAL ANALYSIS IN AND AROUND THE HOKURIKU DISTRICT, JAPAN [J].
KATO, H ;
FUJITA, S ;
NISHINOMIYA, S .
ATMOSPHERIC ENVIRONMENT PART A-GENERAL TOPICS, 1990, 24 (08) :2023-2033
[10]  
KELLY NA, 1985, 78 ANN M AIR POLL CO