A semi-empirical model for urban PM10 concentrations, and its evaluation against data from an urban measurement network

被引:44
作者
Kukkonen, J
Härkönen, J
Karppinen, A
Pohjola, M
Pietarila, H
Koskentalo, T
机构
[1] FMI, Air Qual Res, Helsinki 00810, Finland
[2] Helsinki Metropolitan Area Council, YTV, Helsinki 00520, Finland
基金
芬兰科学院;
关键词
particulate matter; PM10; NOx; modelling; urban pollution;
D O I
10.1016/S1352-2310(01)00254-0
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
We have developed a model for evaluating the mass-based concentrations of urban particulate matter. The basic model assumption is that local vehicular traffic is responsible for a substantial fraction of the street-level concentrations of both PM10 and NOx either due to primary emissions or resuspension from street surfaces. The modelling system utilises the data from an air quality monitoring network in the Helsinki Metropolitan Area. We have determined linear relationships between the measured urban PM10 data against those of NOx in various urban surroundings, based on continuously measured hourly concentration values. The data was obtained from two stations in central Helsinki and one suburban station in the Helsinki Metropolitan Area during a period of 3 yr, from 1996 to 1998. The model also includes a treatment of the regional background concentrations, and resuspended particulate matter. The model performance was evaluated against the measured PM10 data from the above-mentioned three stations and from two other stations, using data that was measured in 1999. We used two alternative model versions, one based on separate correlation parameters (PM10 vs. NOx) for each station, and another based on parameters averaged over the stations considered. We analysed the agreement between the measured and predicted hourly concentration time series, utilising the values of the fractional bias (FB) and the so-called index of agreement (IA). As expected, the model predicts relatively well the yearly mean concentrations of PM10: the FB values range from -0.05 to +0.09. Model performance is also relatively good when predicting the yearly mean values that are classified separately for each hour of the day: the corresponding IA values range from 0.85 to 0.96. However, model performance is substantially worse in predicting the hourly time series of the year: the IA values using the station-specific parameters range from 0.46 to 0.65. The model was applied in evaluating the yearly average spatial concentration distribution of PM10 in central Helsinki, based on the corresponding modelled NOx concentrations. With re-evaluation of a few parameters that can be determined empirically, the model could be evaluated, and most probably applied, in other urban areas as well. (C) 2001 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:4433 / 4442
页数:10
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