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Calculated emission and measured immission of air pollution related to traffic flow on a motorway
The Science of the Total Environment, 134 (1993) 139-146 Elsevier Science Publishers B.V., Amsterdam
139
Calculated emission and measured immission of air pollution related to traffic flow on a motorway Paul G. H6glund a and H~kan T6rnevik b aRo~'al Institute ot" Technology, S.10044 Stockholm, Sweden "Indic, P. O, Box 1514, S.600 45 Norrk@ing, Sweden
ABSTRACT Emissions of NO~ from the traffic on a three.lane motorway have been calculated by means of an emission model purely based on traffic flow data, Hourly mean emissions for February 1990 are presented. For the same period, measurements of NO as well as meteorological measurements were taken at and close to the motorway. A long path instru. ment, based on the Differential Optical Absorption Spectroscopy (DOAS) prir~cipleswas used for gas measurements in the ambient air. An atmospheric diffusion model was used in order to determine the traffic emissions that fully explained the concentration of the gas measured in the ambient air, Emission estimates based on these principles are presented as hourly values for an average day during February 1990. The emission estimates from the two mutually independent methods show striking similarities. It is concluded that a further developed model based on DOAS measurements, could be a flexible and cost effective method for tile estimation of traffic emissions, for several gases and for complex traffic scenarios, implying l~ewand better ways ofcomparing the environmental effects of different approaches to traffic planning solutions and infrastructural design,
Key words: traffic flow; immission model; emission; immission; ~ir poilution from traffic; emission model; immission measurement INTRODUCTION
To answer questions about ambient air quality close to a road, we normally simulate this by means of traffic flow data, traffic emission factors and meteorological dispersion models describing the diffusion of traffic exhaust gases into the atmosphere. Traffic emission factors are often crude estimates based on theoretical approximate models or laboratory experiments. If it were possible to measure emissions from road traffic in situ, i.e. during a specific period, in a specific traffic situation, then it would be possible to compare different road, street and intersection designs from an environmental point of view. Emission factors for different traffic design solutions could then be used at an early stage in the traffic planning process. 0048-9697/93/$06.00
© 1993 Elsevier Science Publishers BN. All
rights reserved
140
P.G. HOGLUNDAND H, TORNEVIK
Thus, from a practical point of view, we are interested in finding a nonexpensive commercially available solution for the in situ measurements of e~ssions. PILOT PROJECT DESIGN
It was decided that we should look for a measurement site where conditions could be regarded as ideal from the measuring point of view. That would include the practical arrangements needed for ambient air monitoring and meteorological monitoring as well as avoiding complicated disturbances from background emissions. We also looked for a rather simple traffic situation, i.e. a road with a fairly constant driving pattern in the tramc flow, For such conditions it would be possible to apply well known emission factors based on measured traffic flow data for comparison between the methods. Due to ~ n o m i c constraints the measurement period was limited to I month (February 1990) and only one long path ambient air measuring apparatus was used in combination with a meteorological mast. MEASUREMENTS
Measurements of ambient air quality (hereafter denoted: immissions) were performed with a long path measuring equipment, based on the DOAS technique (Differential Optical Absorption Spectroscopy). The IX)AS technique is based on the fact that all gases have unique spectral signatures. In the DOAS equipment developed by the OPSIS Company in Lurid, Sweden, a broadb~d light source with a wavelength of 200-1000 rim, is capable of transmitting a light beam 100-2000 m. After passing through the air, the light is collected and focused into a fibre optic cable and transmitted to a grating, which selects a specific part of the spectra. The analyser compares the received spectrum with reference spectra stored in a computer. This makes it possible to determine the concentration of a specific gas along the light beam. The DOAS technique makes it possible to determine mean gas concentra. tions within air volumes that are so large that several tens of conventional point measuring equipments would b~ needed to give the same information. The OPSIS/13~AS equipment was placed close to a motorway in the suburban city Naeka, southeast of Stockholm. For a description of the measuring site, see Fig. 2. Measuring characteristics: Subszances. NO, NO~, benzene, toluene and formaldehyde. Light beams. Two of ~ 100 m length, at 3.8 m height. One beam parallel to the motorway and the other diagonally crossing the road.
TRArV~C FLOW-RELATED AIR POLLUTION O N A M O T O R W A Y
141
Integration time. 1 ndn. At the same time meteorological measurements were carried out using a 10-m mast in open terrain 1 km from the roadway. Measuring characteristics: Parameters. Horizontal wind at 10 m (mean value and standard deviation); vertical wind at 10 m (mean value and standard deviation); global radiation at 2 m; vertical temperature difference (8-2 m); absolute temperature at 2 m; precipitation at 2 m (yes/no). Integration time. 15 min (precipitation and radiation: 60 min) The data described above, are a subset of a larger data set described in the report [8]. DOAS data as well as meteorological data were collected for this study during February 1990. Traffic counts were carried out by the National Swedish Road Administration, Stockholm district (VF Stockholm) during 1 entire week, 20th April at 13:27 h to 27th April, at 13:45 h (1990), i.e. nearly 2 months after the immission data were collected. This data, which apart from the traffic counts, contained vehicle speed and vehicle classification (13 classes) information on an hourly basis. EMISSION ESTIMATION BASED ON TRAFFIC FLOW DATA
The TMS data measured in April was transformed to hourly variations for February. Correction factors for the relationship between weekday traffic in February 1990 and the measured data from I week in April 1990 were taken from Refs. 1 and 2.
Emiter Power unit
~
.tmttyser
Pflnter
Fig. I. The long path (DOAS) instrument. Typical distances between emitter and receiver could be 100-2000 m.
'~n,~qad u! s K ~ p q ~ o~t~aa~ aqt aoj ~ON jo UOl~ltUa u ~ m 4moq aq~.jo uo!l~m!~so .mj m~p mdu! s~ uoq~ am,~ (SOlO!qo^jo ~ I O o~t oq~ 'f-~: •~jo~ u! p~Ip~sop 'lopom OJ.~A P~II~ os oq~ 'om~!~Ul q a ~ O ~ l o ~ j . pure p~o~l qs!l~,~S ,~q l:mdoloAop l~pom • moaj uoq'~ am,~ s.mlo~j uo.~,zm3 '(sou#uo l~so!p) s;)plqoA l~lOods pu~ sosnq 's~mOl I1~ summoo SS~lO Olo!qo^ ~CAttaqoqj. 'SOlO~Cuo~om~oj XlOA!I~I~ oq~ se IIO~ ~ (~au#uo OU!lOS~) sago .mSuoss~d ~ u ! p , zo ~uos~doa SOlo!qoA lqS!'l '~Io!q~ R ~ q pu~ lq~!l 'soSSUlOo.~1 otu! pouuojsu~l OSl~ s ~ ~ p lunoo ot.l~l oq£
oqJ+ 'wloqqools oi punoqu? (dwm.t Sum+too oq, hlpnl~U?) OUml-,moj put+ WlOqqoots wo.u smowozns~+w Ol:)!qoASi41£ +qJ+ "pm)a +qt a+^o +(ImUOhlp pro+ ot l+ll.,nM ;no ImFmm m ~ sm+wmnst++w $¥0<3 +q,x,'mowd!nlm m~m~ns.w SVO(1 +q'.jo uo?t~aoi +qt pure,<+~otow oq~ a~o ~u!~'~l tonp~le, oqt s~oq~ am~ U oq£ "otis m ~ w a m ~ w jo m~!~ l ~ U ~ '~ '8!d
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TRAFFIC FLOW-RELATED AIR POLLUTION ON A MOTORWAY
14~
EMISSION ESTIMATION BASED ON DOAS AND METEOROLOGICAL DATA.
The measured concentration of a specific air pollutant in the ambient air, (the immission value) is the combined result of various complicated processes, namely: (i) the number, strength and behaviour of nearby air pollution sources (emissions); (ii) the efficiency of atmospheric transport and mixing (dispersion); (iii) the transformation of substances through chemical reactions and (iv) air pollutant sinks in the form of dry and wet deposition. The immission values close to a source are generally not proportional to the emission values. On the contrary, the processes of transmission, i.e. those named above in (ii), (iii) and (iv) can be regarded as non-linear processes giv. ing immission values within a broad range, even if the emissions are constant. For conditions close to the source of emission the gas concentration in the air is primarily determined by the first two processes. Rao and Keenan, [7] describe how immission data and meteorological data, measured in the vicinity of a highway, have been used for calibration of the EPA-HIWAY dispersion model. This model can be used for describing the relation between emissions and immissions in the vicinity of a highway and for different weather scenarios. The EPA-HIWAY model was used in this study to simulate hourly mean values of emissions, during the whole of February. For each hour, meteorological data were taken from the mast and the dispersion was simulated. The amount of emission in the model, that fully explained the ira. mission values on the OPSIS beam 1, was taken as *.heestimate of the traffic emission plus background values. Wind data as well as atmospheric stability data were taken from the mete,3rological mast. The atmospheric stabd'i ty classes used (local PasquillGifford classes) were determined from estimations of the Monin-Obukhovs length (L) based on the meteorological data from the mast. The following discrimination rules were applied: I/L -0.002
<-0.002 <0.003
P-G stability class: A,B,C P-G stability class: D P-G stability class: E,F
The Monin.Obukhov lengths were estimated using the methods described by Berkowics and Prahm [9]. The emission calculation was based on immission values of nitrogen monoxide (NO). The reason for this choice is that no other substantial source of NO was found in the vicinity. Background values of NO (mainly contribution from nearby traffic) have been estimated by using NO
144
P.O. HOGLUNDAND H. TORNEVIK
measurements at OP$I$ beam 2 at wind directions between 120° and 240°, i.e. in conditions when it is likely that this beam is not directly exposed to emission from the traffic on the motorway. Such conditions occurred during 40% of the total measuring period, evenly distributed throughout the day. As a mean, background values were found to be 16% of measured NO immissions across the motorway. The total emissions of,Jitrogen oxides (NO~) from the traffic are expected to consist of mainly (> 90%) NO [ 12]. Thus, by using the NO immission values at OPSIS beam 1 in the EPAHIWAY model to estimate the total emissions of NO~ from the traffic, we would expect a slight (5-10%) underestimation of NO~ emissions. For a single hour we would expect an error in the simulation model, that could ~ of the same magnitude as the estimated value. Rao and Keenan [7] report, that in - 70 cases of a total 594, the simulated values of immissions (EPA-HIWAY 04) differed more than 100% from measured values. But for the whole period those values p ~ n t e d a mean simulation value, that exc¢~ed the observed mean value with 15%. It is assumed that the inclusion of background values in the OPSIS path used for emission estimation, the approximation of NO~ from NO values and the use of the EPA=HIWAY model, would introduce three types of mutually independent errors. Therefore we expect, that long-term simulations with the EPA-HIWAY model, estimating traffic-induced NO~ emissions based on NO emission data, will result in a slight underestimation. The underestimation would probably be in the range 0-10% (when background values are included). RESULTS
For both methods, the emission estimates are presented as hourly values for the a v e n ~ day of February, Due to the uncertainties in the traffic flow corrections it would not be meaningful to present the data in more detail. Denoting the method of emission estimation based on traffic flow data as Veto model and the method based on immission data and meteorology for DOAS model, we notice: • The DOA$ model emissions are generally higher than VETO model emissions,
• The overall daily variations arc similar between the methods. • For the whole period the DOAS model emission is 23% higher than the VETO model emission, There is no variation in the relative difference between the methods when dividing the material into the diurnal periods 07:00-17:00 h and 18:00-06:00 h. • The absolute difference between the methods increases with traffic flow.
145
TRAFFIC FLOW-RELATED AIR POLLUTION O N A M O T O R W A Y
Emission(gram/km) 000
.
.
.
.
.
.
.
8OOO 70OO 6OOO
0 0 0
'
•
'
2OOO ~J
I~mi~ioa~ fromVe,o~mode! .
0
.......
!
I .......
2
1 .........
3
I ..........
4
1 .......... l ........
$
6
I ........
7
1 .......... O........
8
9
~............ t .........
t=I
..... 1 ............. t ............ 4
+
....
i ............ + ......... t ............ t
............
t ........... t
........... t
I0 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Hoursof the day
Fig. 3. Comparison of emission estimates. Hourly values for an average day in February 1990. The x-axis is divided into hours from 00:00-24:00 h. The y-axis gives the average emission levels (fo~"both road directions) in g/km based on 28 hourly mean values, l VETO model; DOAS data.
CONCLUSIONS
Two different methods for estimating traffic emissions of NOx have been compared. The VETO model, based purely on traffic flow parameters and the DOAS model based on measurements of traffic exhaust g;~:s (NO) and meteorological information in the vicinity of the road. The two methods have been compared during February 1990 for a segment of a motorway in Nacka. The mean diurnal variations during February 1990, estimated with the two methods, show a very close resemblance (see Fig. 3). The DOAS method estimates the emissions 23% higher than the VETO model although a vice versa relation of 0-10% lower was expected. We expect that the DOAS model is capable of describing the emissions from the traffic in a more realistic way than the VETO model by using real time data of meteorology and measurement of exhaust gases from traffic in the vicinity of the road. The full scale experiment described in Ref. (6), where emissions were controlled, give further evidence that the long path instrument (DOAS) is a suitable technique for the estimation of nearby emissions. Therefore it is suggested, that the DOAS method should be further
146
P.G. HOGLUNDAND H. TORNEVIK
developed and applied for future investigations together with careful measurements of traffic flow parameters. The emission factors for the VETO model or other emission estimation models could thereafter be updated and possibly coupled to t ~ m c parameters such as driving patterns, that are not included in the ~ s s i o n factors at present. By using the DOAS method it will also be possible to extend the number of emission factors to include specific hydrocarbons, that can be detected by the IX)AS m ~ s u r i n g method. In s u ~ ~ , it is concluded that an estimation of traffic emissions based on the DOAS technique is a flexible and cost effective method that gives us the possibility of comparing the environmental effects of different approaches to tramc planning. REFERENCES
I Schande~n Rein, Trafikensveckodagsvariationunder ~rct(Weekly variationof traffic flow during the year), Swedish Road and Traffic Research Institute (VTi), VT! Notat T 73, 1989, 11-30, 2 SwedishNational Road Administration (VV), Biltrafikens tidsndissiga variationer 1988 (Traffic count time variations 1988). Trafikdatasektionen, 1989-07. Publ 1989:36. 3 SwedishNational Road Administration (VV), Berakning av avgasutslipp (Calculations of air pollution exhaust), 1989-06, Publ 1989:16 B, 4 U. Hamn~rstr0m and B, Karlsson, VETO-ett datorprogram fOr berikning av transportkostnader sore funtion av v~gstandard (VETO - a computer program for calculation of transport coats as a function of road standard), Swedish Road and Traffic Research lnstitute (VTI). 1987, VII meddelande 501, $ U, Hammarstr6m, Avgasmodel! fOr biltraflk (Exhaust model for car traffic), VTI., Trafikavdelningen (Traffic department). 1989. 12- ! 7, 6 Indic AB, Emission experiment based on DOAS monitoring of toluene al',d sulphur dioside, Indic Technical Report no, I. 1990, 7 $,T, Rao and M,T, K~nan, Suggestions for improvement of the EPA-HIWAY Model. IAPCA. 30 (1980) 60-69, 8 IndicAB, Lufit~0roreningsm~tning~ri Nacka vintern 1990 (Measurements of air pollution in Nacka during winter 1990), 1990, 9 R, Berkowicsand L,P, Prahm, Evaluation of the profile method for estimation of surface fluxes of momentum and heat, Almos, Environ,. 16 (1982) 2809-2819, 10 SwedishEnvironment Protection Agency, Berakning av avgashalter rid gator och v/igar (Calculation of air pollution along streets and roads), SNV mcdde!ande 8/1984. II K,.E, Epb~ick, HMtighet, FOroreningsutsl~ipp. Bcnsindrivna bilar (Speed, Pollution. Gasoline motor cars), Swedish Environment Protection Agency, SNV report 3276, 1987. 12 NorwegianInstitute for Air Research, No,disk beregningsmetode for bilavgaser(Nordic calculation method for ~hicle exhaust), NILU report O-8216, 1984.
139
Calculated emission and measured immission of air pollution related to traffic flow on a motorway Paul G. H6glund a and H~kan T6rnevik b aRo~'al Institute ot" Technology, S.10044 Stockholm, Sweden "Indic, P. O, Box 1514, S.600 45 Norrk@ing, Sweden
ABSTRACT Emissions of NO~ from the traffic on a three.lane motorway have been calculated by means of an emission model purely based on traffic flow data, Hourly mean emissions for February 1990 are presented. For the same period, measurements of NO as well as meteorological measurements were taken at and close to the motorway. A long path instru. ment, based on the Differential Optical Absorption Spectroscopy (DOAS) prir~cipleswas used for gas measurements in the ambient air. An atmospheric diffusion model was used in order to determine the traffic emissions that fully explained the concentration of the gas measured in the ambient air, Emission estimates based on these principles are presented as hourly values for an average day during February 1990. The emission estimates from the two mutually independent methods show striking similarities. It is concluded that a further developed model based on DOAS measurements, could be a flexible and cost effective method for tile estimation of traffic emissions, for several gases and for complex traffic scenarios, implying l~ewand better ways ofcomparing the environmental effects of different approaches to traffic planning solutions and infrastructural design,
Key words: traffic flow; immission model; emission; immission; ~ir poilution from traffic; emission model; immission measurement INTRODUCTION
To answer questions about ambient air quality close to a road, we normally simulate this by means of traffic flow data, traffic emission factors and meteorological dispersion models describing the diffusion of traffic exhaust gases into the atmosphere. Traffic emission factors are often crude estimates based on theoretical approximate models or laboratory experiments. If it were possible to measure emissions from road traffic in situ, i.e. during a specific period, in a specific traffic situation, then it would be possible to compare different road, street and intersection designs from an environmental point of view. Emission factors for different traffic design solutions could then be used at an early stage in the traffic planning process. 0048-9697/93/$06.00
© 1993 Elsevier Science Publishers BN. All
rights reserved
140
P.G. HOGLUNDAND H, TORNEVIK
Thus, from a practical point of view, we are interested in finding a nonexpensive commercially available solution for the in situ measurements of e~ssions. PILOT PROJECT DESIGN
It was decided that we should look for a measurement site where conditions could be regarded as ideal from the measuring point of view. That would include the practical arrangements needed for ambient air monitoring and meteorological monitoring as well as avoiding complicated disturbances from background emissions. We also looked for a rather simple traffic situation, i.e. a road with a fairly constant driving pattern in the tramc flow, For such conditions it would be possible to apply well known emission factors based on measured traffic flow data for comparison between the methods. Due to ~ n o m i c constraints the measurement period was limited to I month (February 1990) and only one long path ambient air measuring apparatus was used in combination with a meteorological mast. MEASUREMENTS
Measurements of ambient air quality (hereafter denoted: immissions) were performed with a long path measuring equipment, based on the DOAS technique (Differential Optical Absorption Spectroscopy). The IX)AS technique is based on the fact that all gases have unique spectral signatures. In the DOAS equipment developed by the OPSIS Company in Lurid, Sweden, a broadb~d light source with a wavelength of 200-1000 rim, is capable of transmitting a light beam 100-2000 m. After passing through the air, the light is collected and focused into a fibre optic cable and transmitted to a grating, which selects a specific part of the spectra. The analyser compares the received spectrum with reference spectra stored in a computer. This makes it possible to determine the concentration of a specific gas along the light beam. The DOAS technique makes it possible to determine mean gas concentra. tions within air volumes that are so large that several tens of conventional point measuring equipments would b~ needed to give the same information. The OPSIS/13~AS equipment was placed close to a motorway in the suburban city Naeka, southeast of Stockholm. For a description of the measuring site, see Fig. 2. Measuring characteristics: Subszances. NO, NO~, benzene, toluene and formaldehyde. Light beams. Two of ~ 100 m length, at 3.8 m height. One beam parallel to the motorway and the other diagonally crossing the road.
TRArV~C FLOW-RELATED AIR POLLUTION O N A M O T O R W A Y
141
Integration time. 1 ndn. At the same time meteorological measurements were carried out using a 10-m mast in open terrain 1 km from the roadway. Measuring characteristics: Parameters. Horizontal wind at 10 m (mean value and standard deviation); vertical wind at 10 m (mean value and standard deviation); global radiation at 2 m; vertical temperature difference (8-2 m); absolute temperature at 2 m; precipitation at 2 m (yes/no). Integration time. 15 min (precipitation and radiation: 60 min) The data described above, are a subset of a larger data set described in the report [8]. DOAS data as well as meteorological data were collected for this study during February 1990. Traffic counts were carried out by the National Swedish Road Administration, Stockholm district (VF Stockholm) during 1 entire week, 20th April at 13:27 h to 27th April, at 13:45 h (1990), i.e. nearly 2 months after the immission data were collected. This data, which apart from the traffic counts, contained vehicle speed and vehicle classification (13 classes) information on an hourly basis. EMISSION ESTIMATION BASED ON TRAFFIC FLOW DATA
The TMS data measured in April was transformed to hourly variations for February. Correction factors for the relationship between weekday traffic in February 1990 and the measured data from I week in April 1990 were taken from Refs. 1 and 2.
Emiter Power unit
~
.tmttyser
Pflnter
Fig. I. The long path (DOAS) instrument. Typical distances between emitter and receiver could be 100-2000 m.
'~n,~qad u! s K ~ p q ~ o~t~aa~ aqt aoj ~ON jo UOl~ltUa u ~ m 4moq aq~.jo uo!l~m!~so .mj m~p mdu! s~ uoq~ am,~ (SOlO!qo^jo ~ I O o~t oq~ 'f-~: •~jo~ u! p~Ip~sop 'lopom OJ.~A P~II~ os oq~ 'om~!~Ul q a ~ O ~ l o ~ j . pure p~o~l qs!l~,~S ,~q l:mdoloAop l~pom • moaj uoq'~ am,~ s.mlo~j uo.~,zm3 '(sou#uo l~so!p) s;)plqoA l~lOods pu~ sosnq 's~mOl I1~ summoo SS~lO Olo!qo^ ~CAttaqoqj. 'SOlO~Cuo~om~oj XlOA!I~I~ oq~ se IIO~ ~ (~au#uo OU!lOS~) sago .mSuoss~d ~ u ! p , zo ~uos~doa SOlo!qoA lqS!'l '~Io!q~ R ~ q pu~ lq~!l 'soSSUlOo.~1 otu! pouuojsu~l OSl~ s ~ ~ p lunoo ot.l~l oq£
oqJ+ 'wloqqools oi punoqu? (dwm.t Sum+too oq, hlpnl~U?) OUml-,moj put+ WlOqqoots wo.u smowozns~+w Ol:)!qoASi41£ +qJ+ "pm)a +qt a+^o +(ImUOhlp pro+ ot l+ll.,nM ;no ImFmm m ~ sm+wmnst++w $¥0<3 +q,x,'mowd!nlm m~m~ns.w SVO(1 +q'.jo uo?t~aoi +qt pure,<+~otow oq~ a~o ~u!~'~l tonp~le, oqt s~oq~ am~ U oq£ "otis m ~ w a m ~ w jo m~!~ l ~ U ~ '~ '8!d
! t
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m^SN~OJL"Xany aNnaC~x o'a
I ,
,
!
~td
TRAFFIC FLOW-RELATED AIR POLLUTION ON A MOTORWAY
14~
EMISSION ESTIMATION BASED ON DOAS AND METEOROLOGICAL DATA.
The measured concentration of a specific air pollutant in the ambient air, (the immission value) is the combined result of various complicated processes, namely: (i) the number, strength and behaviour of nearby air pollution sources (emissions); (ii) the efficiency of atmospheric transport and mixing (dispersion); (iii) the transformation of substances through chemical reactions and (iv) air pollutant sinks in the form of dry and wet deposition. The immission values close to a source are generally not proportional to the emission values. On the contrary, the processes of transmission, i.e. those named above in (ii), (iii) and (iv) can be regarded as non-linear processes giv. ing immission values within a broad range, even if the emissions are constant. For conditions close to the source of emission the gas concentration in the air is primarily determined by the first two processes. Rao and Keenan, [7] describe how immission data and meteorological data, measured in the vicinity of a highway, have been used for calibration of the EPA-HIWAY dispersion model. This model can be used for describing the relation between emissions and immissions in the vicinity of a highway and for different weather scenarios. The EPA-HIWAY model was used in this study to simulate hourly mean values of emissions, during the whole of February. For each hour, meteorological data were taken from the mast and the dispersion was simulated. The amount of emission in the model, that fully explained the ira. mission values on the OPSIS beam 1, was taken as *.heestimate of the traffic emission plus background values. Wind data as well as atmospheric stability data were taken from the mete,3rological mast. The atmospheric stabd'i ty classes used (local PasquillGifford classes) were determined from estimations of the Monin-Obukhovs length (L) based on the meteorological data from the mast. The following discrimination rules were applied: I/L -0.002
<-0.002 <0.003
P-G stability class: A,B,C P-G stability class: D P-G stability class: E,F
The Monin.Obukhov lengths were estimated using the methods described by Berkowics and Prahm [9]. The emission calculation was based on immission values of nitrogen monoxide (NO). The reason for this choice is that no other substantial source of NO was found in the vicinity. Background values of NO (mainly contribution from nearby traffic) have been estimated by using NO
144
P.O. HOGLUNDAND H. TORNEVIK
measurements at OP$I$ beam 2 at wind directions between 120° and 240°, i.e. in conditions when it is likely that this beam is not directly exposed to emission from the traffic on the motorway. Such conditions occurred during 40% of the total measuring period, evenly distributed throughout the day. As a mean, background values were found to be 16% of measured NO immissions across the motorway. The total emissions of,Jitrogen oxides (NO~) from the traffic are expected to consist of mainly (> 90%) NO [ 12]. Thus, by using the NO immission values at OPSIS beam 1 in the EPAHIWAY model to estimate the total emissions of NO~ from the traffic, we would expect a slight (5-10%) underestimation of NO~ emissions. For a single hour we would expect an error in the simulation model, that could ~ of the same magnitude as the estimated value. Rao and Keenan [7] report, that in - 70 cases of a total 594, the simulated values of immissions (EPA-HIWAY 04) differed more than 100% from measured values. But for the whole period those values p ~ n t e d a mean simulation value, that exc¢~ed the observed mean value with 15%. It is assumed that the inclusion of background values in the OPSIS path used for emission estimation, the approximation of NO~ from NO values and the use of the EPA=HIWAY model, would introduce three types of mutually independent errors. Therefore we expect, that long-term simulations with the EPA-HIWAY model, estimating traffic-induced NO~ emissions based on NO emission data, will result in a slight underestimation. The underestimation would probably be in the range 0-10% (when background values are included). RESULTS
For both methods, the emission estimates are presented as hourly values for the a v e n ~ day of February, Due to the uncertainties in the traffic flow corrections it would not be meaningful to present the data in more detail. Denoting the method of emission estimation based on traffic flow data as Veto model and the method based on immission data and meteorology for DOAS model, we notice: • The DOA$ model emissions are generally higher than VETO model emissions,
• The overall daily variations arc similar between the methods. • For the whole period the DOAS model emission is 23% higher than the VETO model emission, There is no variation in the relative difference between the methods when dividing the material into the diurnal periods 07:00-17:00 h and 18:00-06:00 h. • The absolute difference between the methods increases with traffic flow.
145
TRAFFIC FLOW-RELATED AIR POLLUTION O N A M O T O R W A Y
Emission(gram/km) 000
.
.
.
.
.
.
.
8OOO 70OO 6OOO
0 0 0
'
•
'
2OOO ~J
I~mi~ioa~ fromVe,o~mode! .
0
.......
!
I .......
2
1 .........
3
I ..........
4
1 .......... l ........
$
6
I ........
7
1 .......... O........
8
9
~............ t .........
t=I
..... 1 ............. t ............ 4
+
....
i ............ + ......... t ............ t
............
t ........... t
........... t
I0 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Hoursof the day
Fig. 3. Comparison of emission estimates. Hourly values for an average day in February 1990. The x-axis is divided into hours from 00:00-24:00 h. The y-axis gives the average emission levels (fo~"both road directions) in g/km based on 28 hourly mean values, l VETO model; DOAS data.
CONCLUSIONS
Two different methods for estimating traffic emissions of NOx have been compared. The VETO model, based purely on traffic flow parameters and the DOAS model based on measurements of traffic exhaust g;~:s (NO) and meteorological information in the vicinity of the road. The two methods have been compared during February 1990 for a segment of a motorway in Nacka. The mean diurnal variations during February 1990, estimated with the two methods, show a very close resemblance (see Fig. 3). The DOAS method estimates the emissions 23% higher than the VETO model although a vice versa relation of 0-10% lower was expected. We expect that the DOAS model is capable of describing the emissions from the traffic in a more realistic way than the VETO model by using real time data of meteorology and measurement of exhaust gases from traffic in the vicinity of the road. The full scale experiment described in Ref. (6), where emissions were controlled, give further evidence that the long path instrument (DOAS) is a suitable technique for the estimation of nearby emissions. Therefore it is suggested, that the DOAS method should be further
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developed and applied for future investigations together with careful measurements of traffic flow parameters. The emission factors for the VETO model or other emission estimation models could thereafter be updated and possibly coupled to t ~ m c parameters such as driving patterns, that are not included in the ~ s s i o n factors at present. By using the DOAS method it will also be possible to extend the number of emission factors to include specific hydrocarbons, that can be detected by the IX)AS m ~ s u r i n g method. In s u ~ ~ , it is concluded that an estimation of traffic emissions based on the DOAS technique is a flexible and cost effective method that gives us the possibility of comparing the environmental effects of different approaches to tramc planning. REFERENCES
I Schande~n Rein, Trafikensveckodagsvariationunder ~rct(Weekly variationof traffic flow during the year), Swedish Road and Traffic Research Institute (VTi), VT! Notat T 73, 1989, 11-30, 2 SwedishNational Road Administration (VV), Biltrafikens tidsndissiga variationer 1988 (Traffic count time variations 1988). Trafikdatasektionen, 1989-07. Publ 1989:36. 3 SwedishNational Road Administration (VV), Berakning av avgasutslipp (Calculations of air pollution exhaust), 1989-06, Publ 1989:16 B, 4 U. Hamn~rstr0m and B, Karlsson, VETO-ett datorprogram fOr berikning av transportkostnader sore funtion av v~gstandard (VETO - a computer program for calculation of transport coats as a function of road standard), Swedish Road and Traffic Research lnstitute (VTI). 1987, VII meddelande 501, $ U, Hammarstr6m, Avgasmodel! fOr biltraflk (Exhaust model for car traffic), VTI., Trafikavdelningen (Traffic department). 1989. 12- ! 7, 6 Indic AB, Emission experiment based on DOAS monitoring of toluene al',d sulphur dioside, Indic Technical Report no, I. 1990, 7 $,T, Rao and M,T, K~nan, Suggestions for improvement of the EPA-HIWAY Model. IAPCA. 30 (1980) 60-69, 8 IndicAB, Lufit~0roreningsm~tning~ri Nacka vintern 1990 (Measurements of air pollution in Nacka during winter 1990), 1990, 9 R, Berkowicsand L,P, Prahm, Evaluation of the profile method for estimation of surface fluxes of momentum and heat, Almos, Environ,. 16 (1982) 2809-2819, 10 SwedishEnvironment Protection Agency, Berakning av avgashalter rid gator och v/igar (Calculation of air pollution along streets and roads), SNV mcdde!ande 8/1984. II K,.E, Epb~ick, HMtighet, FOroreningsutsl~ipp. Bcnsindrivna bilar (Speed, Pollution. Gasoline motor cars), Swedish Environment Protection Agency, SNV report 3276, 1987. 12 NorwegianInstitute for Air Research, No,disk beregningsmetode for bilavgaser(Nordic calculation method for ~hicle exhaust), NILU report O-8216, 1984.