Transactions on Ecology and the Environment vol 15, © 1997 WIT Press, www.witpress.com, ISSN 1743-3541
Comparison of dispersion model predictions and
the results from an urban air quality measurement
network
A. Karppinen,* J. Kukkonen,* M. Konttinen,* E. Rantakrans,*
E. Valkonen/ J. Harkonen^ T. Koskentalo,* T. Elolahde*
^Finnish Meteorological Institute, Air Quality Research
Sahaajankatu 20 £, FIN - 00810 Helsinki, Finland
Fox +3J2 P 7P2P J^OJ
Email: AriXarppinen@fmi.fi
^Helsinki Metropolitan Area Council
6,4,
Abstract
We have developed a modelling system for predicting the emissions,
dispersion and chemical transformation of nitrogen oxides in an urban area.
The system takes into account of all source categories, including stationary
point and area sources, and vehicular sources. This paper describes a
comparison of the predicted NO% and NOi concentrations with the results of an
urban air quality measurement network. The comparison included four
monitoring stations in the Helsinki metropolitan area in 1993. The predicted
and measured NOi concentrations agreed well at all the stations considered.
The agreement of model predictions and measurements for NOx and NC>2 was
better for the two suburban measurement stations, compared with the two
stations located in downtown Helsinki
1 Introduction
The dispersion modelling system is based on a combined application of the
Urban Dispersion Modelling system UDM-FMI [1,2] and the road network
dispersion model CAR-FMI [3,4,5] of the Finnish Meteorological Institute
(FMI). The integrated modelling system includes also a meteorological pre-
Transactions on Ecology and the Environment vol 15, © 1997 WIT Press, www.witpress.com, ISSN 1743-3541
406
Air Pollution Modelling, Monitoring and Management
processing model [1,2], emission models for stationary and vehicular sources
[6,7] and a statistical analysis of the computed time series of concentrations.
The modelling system is depicted in Figure 1. The programs were executed on
the Cray C94 supercomputer.
EMME
IJISA
MP]P-FMI
Trail ic volumes
Itaffic missions
Metecnxriogical
pre-pinocessing
UDM-FMI
Dispersion
from stationsury sources
G\R-FM
Dispersion
fromnDbile sources
Statistical analysis and
graphical presentatioin
Figure 1: An overview of the modelling system.
The dispersion models include a treatment of the chemical transformation
of nitrogen oxides. A new model has been developed for evaluating the
chemical interaction of pollution from a large number of individual sources.
This model allows for the interdependence of urban background NO, NO% and
Os concentrations and NO and NO% emissions from various source categories.
The model predictions are compared against the results of the air quality
monitoring network of the Helsinki Metropolitan Area Council (YTV).
2 The spatial concentration distributions
Figure 2 shows the computed yearly mean NOi concentrations at the ground
level. The legend in the top left-hand corner shows the absolute values of the
pollutant concentration.
Clearly, the traffic emissions have a larger relative influence on the
ground-level concentrations, compared to the stationary emissions, which are
mostly released from higher altitudes. It can be shown numerically that
Transactions on Ecology and the Environment vol 15, © 1997 WIT Press, www.witpress.com, ISSN 1743-3541
Air Pollution Modelling, Monitoring and Management
407
although the contribution of traffic on the total emissions is less than a half, the
ground level concentrations mostly originate from traffic sources.
The concentrations of NO] are strongly concentrated in the vicinity of the
main roads and streets, and in the downtown area of Helsinki. The figure
clearly shows the influence of the ring roads and the junctions of major roads
and streets.
ABOVE 40.
35. TO 40.
30 TO 36.
EH 26 TO 30.
D 20.TO25.
D 15.TO20.
15. & BBJOW
Figure 2: Predicted spatial distribution of the yearly mean of NC>2
concentrations (jig/m*) in the Helsinki metropolitan area in 1993. The location
of the urban monitoring stations (Tbolo, Vallila, Leppavaara and Tikkurila) has
also been indicated. The size of the depicted area is 35 km x 25 km.
The computed results include also the spatial distributions of the statistical
concentration parameters, which can be compared to national air quality
guidelines.
3 Comparison with the data of an urban monitoring network
We have compared the model predictions against the air quality measurements
at four YTV stations in the Helsinki metropolitan area. The monitoring
network and the methods have been described by Aarnio et al. [8]. The
concentrations of nitrogen oxides were measured at two urban and two
suburban stations in 1993.
Transactions on Ecology and the Environment vol 15, © 1997 WIT Press, www.witpress.com, ISSN 1743-3541
408
Air Pollution Modelling, Monitoring and Management
,<x
.0-0
U f r '-r , T ¥ ' "¥ f ? ? , 1
1 2 3 4 5 6 7 8 9 10 11 12
Leppavaara
"°"'*
NO^
t— ,— ,— ,— i "4' 4 ~4— 4— -i— i— i
2 3 4 56 78 9 1 0 1 1 1 2
Month
ValliUI
- 250 E 200 - NO%
...^....Obserwd
— •— Predicted
— * Background
Concentration
D 8 8 H
NO,
,_—o<> 1 1 i _i —
Concentration (pg/m3)
%
0.,
„- 250 E 200 I
c 150 "*o"
I 100 H^-*-^_ J^"^*^
^Sr
oI 0J
1 2 3 4 5 6 78 9101112
Month
Toolo
Concentration (pg/m ')
-* -* ro ro
) 8 8 8 8 8
The urban monitoring stations, Toolo and Vallila, are located in the
Helsinki downtown area. The station of Toolo is at the center of a densely
trafficed junction, surrounded by several major buildings. The station of Vallila
is situated in a small park, at a distance of 23 m from a busy street.
The suburban stations are located in Leppavaara, Espoo and in Tikkurila,
Vantaa. The station of Leppavaara is in the city of Espoo in a shopping and
residence area; the distance of the station to two major roads is approximately
200 m. The station of Tikkurila is located in a park near the centre of the city
of Vantaa.
The measurement height is 4 m at the stations of Toolo, Vallila and
Leppavaara, and 6 m at the station of Tikkurila.
Figures 3 and 4 present the seasonal variation of the predicted and
measured NO* and NOi concentrations at the monitoring stations. At the
station of Toolo, the modelling system clearly underpredicts the measured
concentrations. At the other three stations, the predicted NO% concentrations
agree fairly well with the measured data. The variation in time of the predicted
and observed NOx concentrations is similar at all four stations.
^
^
^
_
^
4
^
1 2 3 45 67 8 9 1 0 1 1 1 2
Tikkurila
"*"*
Figures 3a-d: The predicted and measured monthly averages of NO%
concentration at the four monitoring stations considered, together with the
regional background concentrations.
Transactions on Ecology and the Environment vol 15, © 1997 WIT Press, www.witpress.com, ISSN 1743-3541
Air Pollution Modelling, Monitoring and Management
409
At all the stations, the predicted NO] concentrations agree fairly well with the
measured data. The variation in time of the predicted and observed
concentrations is similar, except for the station of Vallila.
1 2 345
T6616
67 8 9 1 0 1 1 1 2
Month
1 2 3 4 56 7 8 9 1 0 1 1 1 2
Leppavaara
Month
-,
i— i— i— i T i— i
1 2 3 4 5 66 77 88 99 10 11 12
Month
Vallila
1 2 3 4 5 6 7 8 9101112
Tikkurila
Month
Figures 4a-d: The predicted and measured monthly averages of NO:
concentration at the four monitoring stations considered, together with the
regional background concentrations.
Conclusions
We have conducted an emission inventory of the mobile and stationary sources
in the Helsinki metropolitan area in 1993. Atmospheric dispersion was
subsequently evaluated, resulting in hourly time series of concentrations of
NOx and NO]. These time series were utilised for presenting the spatial
concentration distributions of the yearly mean values and statistical
concentration parameters.
We have compared the model predictions against the measurements of the
Helsinki Metropolitan Area Council. Both the measured and predicted data
includes hourly time series of the NOx and NO] concentrations for a year at
four measurement stations. This data set is sufficiently extensive in order to
draw statistically reliable conclusions on the model performance. The
Transactions on Ecology and the Environment vol 15, © 1997 WIT Press, www.witpress.com, ISSN 1743-3541
410
Air Pollution Modelling, Monitoring and Management
comparison included data from two measurement stations in an urban
environment (in downtown Helsinki), and two suburban stations (in the cities
of Espoo and Vantaa).
The predicted and measured NC>2 concentrations agree well at all
monitoring stations. However, the variation in time of the measured and
predicted concentrations is slightly different for at the station of Vallila,
located in downtown Helsinki.
The comparison of the NOx concentrations shows also a good agreement
for the stations of Vallila, Leppavaara and Tikkurila. However, the measured
concentration values are clearly underpredicted at the station of T6616. This
station is located in downtown Helsinki at a densely trafficked junction, in the
vicinity of several large buildings. One reason for these differences is the
underestimation of the NOx emissions from traffic in a junction.
The computations indicated that the national air quality guideline of the
daily NO2 concentration was exceeded at the stations of Toolo and Vallila in
1993. The monitoring data also shows that the guideline value was exceeded at
these two stations, together with the exceedence at the station of Leppavaara.
In general, the agreement of model predictions and measurements was
better for the two suburban measurement stations, compared with the two
stations located in downtown Helsinki. This is to be expected, taking into
account the inherent limitations of the modelling system in urban conditions
(e.g., the influence on dispersion of the buildings and other obstacles).
In conclusion, the modelling system was surprisingly successful in
predicting the urban NO% and NO% concentrations. The computational methods
and the results will be utilised by the municipal authoritites in urban planning.
The predicted spatial concentration distributions can also be used for
estimating the representativity of the urban measurement network.
Acknowledgements
We would like to thank our coworkers in this study, Ms. Paivi Aarnio
(Helsinki Metropolitan Area Council) and Mr. Juhani Laurikko (VTT Energy).
This work is part of the national research programme "MOBILE - Energy and
the environment in transportation". The funding from Technology
Development Centre (TEKES) is gratefully acknowledged.
Key words: dispersion model, urban air quality, model testing, NOx, NO%,
References
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