Smog chamber studies on the influence of diesel exhaust on photosmog formation

Atmospheric Environment 36 (2002) 1737–1747

Smog chamber studies on the influence of diesel exhaust onphotosmog formation

Harald Geiger*, J .org Kleffmann, Peter Wiesen

Gesamthochschule Wuppertal/Fachbereich 9-Physikalische Chemie, Bergische Universit .at Wuppertal/Fachbereich 9-Physikalische

Chemie, D-42097 Wuppertal, Germany

Received 28 November 2000; received in revised form 1 February 2001; accepted 7 February 2001

Abstract

In an outdoor smog chamber, volatile organic compounds (VOC)/NOx/air mixtures were irradiated by natural

sunlight in the presence and the absence of diesel exhaust. The VOC mixture contained n-butane, ethene and toluene

with a fixed mixing ratio. Diesel exhaust was generated by a diesel engine mounted on a motor test bed directly at the

chamber facility. Five different diesel fuel formulations were used. Each experiment was carried out under similar initial

conditions for VOC and NOx. In the presence of diesel exhaust, the formation of ozone was significantly increased.

Simulation of the experiments performed using a chemical box model yielded good agreement between measured and

calculated concentrations for all chamber runs. The increase in ozone formation observed on addition of diesel exhaust

was mainly caused by the exhaust concentrations of nitrous acid and formaldehyde, which serve as strong radical

sources in the initial phase of each exhaust experiment. A sensitivity analysis showed that the photooxidant formation

was not dependent on the formulation of the diesel fuel used. The different ozone formation rates observed for the

single exhaust experiments were clearly caused by deviations in initial reactant concentrations as well as photolysis

conditions. r 2002 Elsevier Science Ltd. All rights reserved.

Keywords: Chemical modelling; Diesel exhaust; Simulation chamber experiments; Tropospheric ozone; Vehicle emissions

1. Introduction

Emissions from the combustion of fossil fuels,

especially road traffic emissions, are major contributors

to air pollution. Though exhaust-cleaning techniques for

vehicles have been significantly improved during the last

years and the average fuel consumption per single

vehicle have been significantly decreased, the contribu-

tion of road traffic emissions to tropospheric photosmog

formation is still high, due to the increasing total

number of vehicles.

For the future, an increase in the number of diesel

engines is often anticipated. Since this engine type

consumes less fuel than a comparable gasoline engine,

the replacement of gasoline-powered vehicles by diesel-

fuelled cars would reduce CO2 emissions and therefore

global warming and save natural resources. In contrast,

possible negative influences of the relatively high

number of particles emitted by diesel-powered vehicles

in comparison to gasoline-fuelled cars on tropospheric

chemistry is a matter of grave health and environmental

concern.

At present, the effect of a long-term exchange of the

fuel type from gasoline to diesel on air quality is not

clear. It is well known that gasoline exhaust is

characterised by relatively high concentrations of

volatile organic compound(s) (VOC) and low NOx

concentrations, whereas the VOC/NOx ratio of diesel

exhaust is extremely low, due to very low concentrations

of unburned fuel (Marshall and Owen, 1995; Balek et al.,

1997). An effective replacement of gasoline by diesel as

the major fuel used in road traffic might therefore

*Corresponding author. Tel.: +49-202-439-3832; fax: +49-

2902-439-2757.

E-mail address: [email protected] (H. Geiger).

1352-2310/02/$ - see front matter r 2002 Elsevier Science Ltd. All rights reserved.

PII: S 1 3 5 2 - 2 3 1 0 ( 0 2 ) 0 0 1 7 5 - 9

significantly influence the photochemistry of the tropo-

sphere, e.g. ozone formation. Such effects can be studied

in simulation chamber experiments. A large number of

single atmospheric trace components have previously

been investigated with respect to their ozone formation

potential (Andersson-Sk .old and Holmberg, 2000; Jenkin

and Hayman, 1999; Carter, 1995; Carter et al., 1995).

However, to our knowledge, only a few studies on real

exhaust have been performed. Within the EC project

INFORMATEX (Becker, 1998), the ozone formation

generated by the photooxidation of the exhaust of a

gasoline-powered engine was investigated for different

fuel formulations. Palm and Kr .uger (1998, 1999) created

artificial gas mixtures representing the composition of

exhaust from combustion of a commercially available

diesel as well as rape oil methyl ester (biodiesel) and

investigated the influence of these mixtures on ozone

formation in indoor photoreactor experiments. Smog

chamber studies on the ozone formation potential of

real diesel exhaust have not yet been published.

The studies presented here were part of the EC project

DIFUSO (Wiesen, 2000), which was focused on the

investigation of the impact of real diesel exhaust on

atmospheric chemistry. The experiments were carried

out in the European photoreactor EUPHORE in

Valencia, Spain (Becker, 1996). In a measurement

campaign in November 1999, a series of smog experi-

ments was performed in order to attain information

about the influence of diesel exhaust on photochemical

ozone formation. The following questions were ad-

dressed:

* Does the addition of diesel exhaust to a defined VOC

mixture lead to a significant increase in ozone

formation?* Does the influence of diesel exhaust on photosmog

formation depend on the formulation of the diesel

fuel used?

Within the present work, the experimental data

of the November 1999 campaign were analysed and

interpreted by chemical modelling and sensitivity

analyses.

2. Experimental

2.1. Smog chamber experiments

The experiments of the present work were carried out

in the outdoor simulation chamber EUPHORE in

Valencia, Spain. This facility and the analytical equip-

ment used for the measurement of selected trace gases is

described in detail by Becker (1996) as well as Barnes

and Wenger (1998).

Within the measurement campaign in November

1999, seven smog experiments were carried out. Two

reference experiments were focused on a VOC ‘‘only’’

mixture containing n-butane, ethene and toluene in the

presence of NO, representing the polluted troposphere.

Both experiments differed in the initial NO/NO2 ratio,

while the total amount of initial NOx was more or less

similar (about 200 ppb). For each of the five diesel fuels,

a smog experiment was performed, where diesel exhaust

was injected into the chamber up to a constant NOx

level. After exhaust injection, about 1 ppm of the VOC

mixture was added and the chamber was opened for

irradiation.

Diesel exhaust was generated by a diesel engine (1.8 l,

44 kW) mounted on a test bed including an eddy current

brake. For all smog chamber runs, similar test cycle

conditions were used (see Wiesen (2000) for details).

Five diesel fuels with different formulations were

tested, a commercial diesel (‘‘standard’’ diesel) available

at European gas stations, biodiesel (rape oil methyl

ester) and three sulphur-reduced diesel fuels containing

defined amounts of aromatic hydrocarbons. The de-

tailed compositions of the fuels used are summarised in

Table 1.

Table 2 gives an overview of the parameters relevant

to the computer simulations, such as temperature,

pressure, dilution and initial mixing ratios. Detailed

information about the analytical equipment applied is

given by Wiesen (2000). All studies were performed at

atmospheric pressure. A dilution factor was obtained

from the decay of inert SF6, added to the reaction

mixtures as leakage tracer. The start concentrations of

nitrous acid were not measured, since during the

November 1999 campaign, no suitable analytical tech-

nique for HONO detection was available. The initial

HONO values finally used for the present simulations

were estimated in order to give an optimum description

of the ozone concentrations. A comparison of these

estimates with [HONO]0 values, which were measured

during another campaign carried out in May 2000 under

almost identical motor-operating conditions, showed

that these estimates were reasonable. The HONO

concentrations obtained during the latter campaign

were in the range 1–2 ppb, which is very similar to the

Table 1

Contents of aromatic hydrocarbons and sulphur for the five

diesel fuels used in the present study

Fuel Aromatic HC

(weight%)

Sulphur

(weight%)

1 (standard diesel) 29.3 0.0425

2 (biodiesel) 0 0.0030

3 (5% aromatic HC) 4.3 0.0043

4 (15% aromatic HC) 14.2 0.0045

5 (25% aromatic HC) 24.4 0.0046

H. Geiger et al. / Atmospheric Environment 36 (2002) 1737–17471738

[HONO]0 data derived from the simulations (see Table

2). The studies carried out within the second campaign

are described in detail by Kleffmann et al. (2002). These

authors also measured HONO/NOx emission indices,

whose comparison with field data showed that the

HONO concentrations measured within the DIFUSO

project represent well the emissions of diesel cars in the

normal operation.

2.2. Computer simulations

The chemical simulations were performed using a

simple chemical box model based on the regional

atmospheric chemistry mechanism (RACM) by Stock-

well et al. (1997). This condensed reaction scheme

includes a fairly complete set of reactions for inorganic

chemistry. Organic species are aggregated according to

their chemical structure and reactivity into 32 stable

organic species and 24 organic intermediates,

except methane, ethane, ethene and isoprene, whose

chemistry is treated explicitly. In total, the mechanism

comprises of 237 reactions including 23 photochemical

reactions.

Each experiment was modelled using the box model

described below, except that for diesel fuel 5 (see below).

All computer simulations and sensitivity analyses

were carried out using the box model SBOX

(Seefeld, 1997; Seefeld and Stockwell, 1999). This

FORTRAN program incorporating the Gear algorithm

(Gear, 1971) was operated on an SGI OCTANE

workstation (Silicon Graphics) running under IRIX

6.5. The program uses the public domain library VODE

(Brown et al., 1989) to integrate the ordinary differential

equations.

From the spectral radiant meter data, photolysis

frequencies, j; for several species were calculated

(Wiesen, 2000). Since the box model SBOX requires

photolysis frequencies in a fixed table format, the j

values obtained from the radiant meter data were

transformed into a suitable matrix. For the calculation

of the photolysis frequencies of the nine photosensitive

‘‘lumped’’ species of the RACM scheme, the program

‘‘photoRACM’’ (Seefeld, 1997; Seefeld and Stockwell,

1999) was used. This program generates photolysis

frequencies according to Madronich (1987).

3. Results and discussion

3.1. Preparation of the chemical model

For all the simulations performed, only gas-phase

chemistry was taken into account, the reason for which

will be discussed below in detail.

3.1.1. Modifications of the RACM

Since the experiments were carried out using simple

VOCs mixtures containing only n-butane, ethene and

toluene, a few modifications of the original RACM code

were necessary for better performance of the calcula-

tions. n-Butane is grouped in RACM into the surrogate

species HC3, which represents the class of ‘‘low’’

reactive alkanes, whereas toluene is grouped into the

aromatic class TOL, indicating aromatic compounds

with OH reactivities equal to or lower than toluene. For

the present calculations, the rate coefficients for the

reactions of OH radicals with HC3

(2.20� 10�12 cm3 s�1) and TOL (5.96� 10�12 cm3 s�1)

were replaced by the explicit literature values for

OH+n-butane (2.2� 10�12 cm3 s�1; Atkinson, 1994)

and toluene (6.6� 10�12 cm3 s�1; Becker, 1994), respec-

tively. No modifications were necessary with respect to

ethene, since this hydrocarbon is explicitly treated in

RACM.

3.1.2. Radical sources and sinks

The chemical modelling of smog chamber experiments

is generally complicated due to unknown sources of

radicals, which enable the initiation of the reaction chain

at the beginning of an experiment if no ‘‘reactive’’

Table 2

Initial conditions and mixing ratios used for the model calculations carried out for the smog chamber experiments

Experiment CO

(ppm)

SO2

(ppb)

C4H10

(ppb)

C2H4

(ppb)

C7H8

(ppb)

NO

(ppb)

NO2

(ppb)

NOx

(ppb)

HONO

(ppt)

HCHO

(ppb)

ALD

(ppb)

Dilution

(h�1)

Base mixture I (23 Nov. 1999) 3.50 — 437 433 109 184 21 205 150 — — 0.022

Base mixture II (24 Nov. 1999) 3.58 — 450 450 118 105.4 87.5 192.9 205 — — 0.022

Fuel 1 (15 Nov. 1999) 3.51 23 446 446 124 239 9.6 248.6 1500 9 8.7 0.018

Fuel 2 (18 Nov. 1999) 3.44 1.4 470 430 120 180 17.8 197.8 920 2.7 4.5 0.025

Fuel 3 (16 Nov. 1999) 3.45 2.7 460 452 115 196 13.9 209.9 900 2.8 5.9 0.020

Fuel 4 (19 Nov. 1999) 3.47 1.8 491 428 148 177 15.7 192.7 820 2 5.5 0.024

All runs were performed at average temperatures of about 305K in 760Torr air and 200ppm water (ALD: higher aldehydes).

—Below detection limit.

H. Geiger et al. / Atmospheric Environment 36 (2002) 1737–1747 1739

species are present (e.g. base mixture I). Since ozone is

not present and the initial NO2 concentration is very

low, this composition cannot explain the rapid start of

the reaction chain observed immediately after irradia-

tion of the mixture.

It is now well known that the heterogeneous reaction

of NO2 on wet surfaces leads to HONO and HNO3

formation (see, e.g. Kleffmann et al., 1998). This

transformation allows the description of the sponta-

neous reaction start of even low-reactive smog mixtures.

Since VOC and NOx are injected almost 1 h before

opening the chamber, small amounts of NO2 will be

converted into nitrous acid on the chamber walls. The

subsequent photolysis of HONO is a fast process, which

instantaneously leads to significant amounts of OH after

opening the chamber. For modelling the base mixture

experiments, small initial HONO concentrations of

150 ppt (base mixture I) and 205 ppt (base mixture II)

were used. In the diesel exhaust experiments, the engine

directly emitted nitrous acid. The initial HONO

concentrations used in this case were in the range 820–

1500 ppt (see Section 2.1).

During the DIFUSO campaign, it was found that

HONO formation on the diesel soot surface was

generally small (o2� 1014 HONO cm�2) under the

experimental conditions applied and the formation of

HONO on the soot terminated after 2 min (Kleffmann

et al., 2002; Wiesen, 2000). Considering that the exhaust

was added about 1 h before opening the chamber, this

heterogeneous process did not interfere with the photo-

smog formation in the experiments performed. Since the

high initial concentrations of HONO and aldehydes

dominate the radical balance of each chamber run,

additional radical sources are not needed for the

successful simulation of the experimental data.

A small additional OH radical sink was defined in

order to achieve optimum agreement between calculated

and experimental concentration/time profiles. The reac-

tion OH-wall with a rate coefficient of 2.5 s�1 was

added to the chemical mechanism. The slow offgasing of

reactive substances, in particular HNO3 and NO2, from

the chamber walls might be an additional sink for OH in

the system. Another loss process for OH radicals may

also be its reaction on the chamber wall and on particles

present in the exhaust experiments. It is highly certain

that in a well-stirred reactor, OH radicals will be

removed from the system at a significant rate by

reaction on the chamber wall. In contrast, the surface

of soot particles present in the exhaust experiments

(0.02–0.8 m2; Wiesen, 2000) is negligible in comparison

to the chamber wall (about 170m2; Becker, 1996).

Therefore, the resulting loss rate must be a constant

number if the surface properties as well as the flow rate

of the ventilators are not changed during a series of

experiments.

3.2. General observations

The diesel exhaust added to the chamber in each

experiment mainly contained CO, NOx, HCHO and

higher aldehydes, SO2 and soot. The fraction of

hydrocarbons, e.g. from unburned fuel, was negligible

(Wiesen, 2000).

In all the experiments performed, significant forma-

tion of ozone was observed. Table 3 compares both the

ozone formation rates and the values for dð½O3� �½NO�Þ=dt for all runs, which provides a measure for

the ozone formation potential, derived from the experi-

mental data 2 h after opening the chamber. Both rates

are significantly smaller for the base mixture experi-

ments than for the exhaust runs.

The mean OH concentration, which can be estimated

from the experimental hydrocarbon degradation, was in

the range (1–3)� 106 cm�3 for all chamber runs per-

formed.

All exhaust/VOC studies have been compared to the

base mixture I experiment, since they were carried out at

an initial NO/NO2 ratio very similar to the first reference

run. The ozone formation rates for all other runs with

diesel exhaust added were in the range 46–83 ppb h�1,

which is a factor of about 7–13 higher than that

observed in the base mixture I experiment.

Due to significant deviations in the initial conditions

of each experiment, such as concentrations of NO, NO2,

aldehydes, etc. as well as different photolytic parameters

caused by the weather conditions, a direct interpretation

of the ozone data was not possible. Therefore, in order

to analyse the data, the smog chamber experiments were

simulated using the chemical box model described

above.

At first it was checked whether the differences

between the reference system and the exhaust system

could generally account for the significant increase in

ozone formation observed for the exhaust/VOC experi-

ments. The exhaust runs were characterised by the

Table 3

Comparison of d½O3�=dt and dð½O3� � ½NO�Þ=dt derived from

the experimental data 2 h after opening the smog chamber

Experiment d½O3�=dt

(ppbh�1)

dð½O3� � ½NO�Þ=dt

(ppbh�1)

Base mixture I 6.2 48.5

Base mixture II 13.1 46.2

Standard diesel (fuel 1) 66.9 116.6

Biodiesel (fuel 2) 82.7 106.9

Diesel containing 5%

aromatic HC (fuel 3)

48.8 108.2



52.8 58.1



46.0 74.3


presence of particles (soot) and relatively high initial

concentrations of nitrous acid, formaldehyde and higher

aldehydes.

It is expected that the initial concentrations of HONO

and aldehydes lead to higher ozone concentrations in the

exhaust experiments, due to fast photolysis and genera-

tion of radicals. In order to check this possibility, a

series of simulations with the initial concentrations of

base mixture I plus several initial concentrations of

nitrous acid or formaldehyde was carried out and the

peak ozone concentration was calculated. The results

exhibit a strong increase of peak ozone with increasing

initial concentrations of HONO or HCHO, which

supports the expectation that the strong ozone forma-

tion in the exhaust/VOC experiments is due to photo-

lysis of initial nitrous acid and formaldehyde. This is

also confirmed by modelling the ozone profiles of the

exhaust experiments (see Section 3.3 for details). As an

example, Fig. 1 illustrates the experimental ozone

concentration for the standard diesel run together with

calculated data. Using the data summarised in Table 2

(‘‘full simulation’’), the model fits well to the experi-

mental ozone data. For either [HONO]0=0 or

[HCHO]0=0, the calculations yield significantly lower

ozone concentrations. If both initial values are set to

zero, the ozone formation is decreased by a factor of

about 10.

Another interesting result was obtained from the

model calculations discussed above. It was possible to

find pairs of initial HONO and HCHO concentrations,

which yield very similar ozone profiles in the simulation,

as demonstrated in Fig. 2.

Considering the way, how OH radicals are formed

from the photolysis of HONO and HCHO as well as the

initial conditions of the system, this observation can be

explained as follows. The photofragmentation of nitrous

acid directly leads to OH radicals:

HONO þ hn-OH þ NO; ðR1Þ

whereas the photodissociation of formaldehyde primar-

ily yields HCO radicals and H atoms. Both reactive

species are transformed by molecular oxygen to HO2,

which finally reacts with NO to OH radicals and NO2:

HCHO þ hn-HCO þ H; ðR2Þ

H þ HCO ðþ2O2Þ-2HO2þCO; ðR3Þ

HO2 þ NO-OH þ NO2: ðR4Þ

Since the NO concentration is high at the beginning of

the experiment, both reactions do not influence the NOx

balance of the system. Accordingly, the photolysis of

HONO as well as HCHO serves as a pure OH radical

source in the initial phase of each chamber run.

Consequently, initial concentrations of HONO or

HCHO, which produce similar amounts of OH radicals

in the system, will yield similar ozone profiles, such as

shown in Fig. 2.

Fig. 1. Experimental (E) and simulated ozone profiles for

different initial concentrations of nitrous acid and formalde-

hyde for the smog chamber run of 15 November 1999 (fuel 1).

Initial conditions for the calculations are given in Table 2.

Fig. 2. Simulated ozone profiles for different initial concentra-

tions of nitrous acid (symbols) and formaldehyde (solid lines)

for the conditions of the base mixture I experiment.


3.3. Chemical modelling of the experiments

The experiments performed were modelled using the

parameters summarised in Table 2. The chamber run on

17 November 1999 (fuel 5) was terminated about 2 h

after the opening of the chamber, because strong wind

endangered the stability of the chamber foil. Further-

more, no photolytic parameters were measured on this

particular day. Accordingly, this experiment was not

taken into account in the data interpretation.

For all runs modelled, a systematic overestimation of

NO2 by the model was observed, even when the

calculated concentrations of other species were excel-

lently fitted to the measured data. The disparity

occurred only for reaction times X2 h and further

increased with increasing time. Since the measured NO2

data were corrected with respect to PAN and HNO3

interferences (Wiesen, 2000), this observation must be

explained by a general lack of mechanistic information

about the tropospheric degradation of toluene. It is well

known that the OH-initiated degradation of aromatic

hydrocarbons in smog chambers leads to a significant

loss of NOx in the reaction system (see, e.g. Calvert et al.,

2002), which at present cannot be explained by current

chemical models. Also, the RACM mechanism used for

the present investigations does not account for this NOx

loss. Accordingly, the simulation of a reaction system

including significant amounts of toluene must lead to an

overestimation of NOx, as observed in each calculation

performed in the present study.

3.3.1. Base mixture I

Figs. 3 and 4 illustrate the comparison of experi-

mental and calculated concentration–time profiles for

VOC, HCHO, NO, NO2 and ozone for the experiment

performed with the base VOC mixture in the presence of

NOx (NO/NO2 ratio=8.8) on 23 November 1999. All

data (except NO2, see above) are in excellent agreement

within the experimental errors, which are in the range of

75–715% for the different species. The good model-

ling results indicate that the RACM mechanism

describes the system with sufficient accuracy.

3.3.2. Base mixture II

Fig. 5 illustrates the comparison of experimental and

calculated concentration–time profiles for HCHO, NO,

NO2 and ozone for the experiment performed with the

base VOC mixture in the presence of NOx (NO/NO2

ratio=1.2) on 24 November 1999. The simulation

results are of similar high quality with respect to the

experiment on 23 November 1999. The modelled NO2

profile here fits somewhat better, since the initial

concentration of NO2 is much higher than in the base

mixture I run and the overall amount of NO2 formed is

lower.

It should be noted that the concentrations of NO and

NO2 changed rapidly by a few ppb after opening the

smog chamber. This effect is always observed when a

smog system is started with high initial NO2 concentra-

tions and is caused by the fast adjustment of the

photochemical equilibrium. The model did not precisely

fit this ‘‘jump’’ in the concentrations, because the

Fig. 3. Comparison of simulated (—) and experimental con-

centrations of n-butane (�), ethene (&) and toluene� 3 (E) for

the smog chamber run of 23 November 1999 (base mixture I).


centrations of NO (�), NO2 (&), ozone (J) and formaldehyde

(m) for the smog chamber run of 23 November 1999 (base

mixture I).


photolysis in the model started at zero with the full

intensity, whereas the chamber was slowly opened

within 3min. As a consequence, even the modelled

ozone concentration increased rapidly by a few ppb in

the beginning of the simulation. However, this small

artefact is compensated during the further simulation.

The modelled data for the VOC are similar in quality

to those of the base mixture I experiment and are not

shown here. The same is valid for all other runs

discussed below.

3.3.3. Standard diesel (fuel 1)

Fig. 6 shows a comparison of experimental and

calculated concentration–time profiles for NO, NO2

and ozone for the experiment performed with exhaust

from the standard diesel fuel together with the base

VOC mixture in the presence of NOx on 15 November

1999. Only the initial formaldehyde concentration was

measured. Time-resolved data for HCHO were not

available for this run. Calculated and experimental

concentration–time profiles are in good agreement and

the system is well described by the model.

3.3.4. Biodiesel (fuel 2)



NO2 and ozone for the experiment performed with

exhaust from the biodiesel fuel together with the base

VOC mixture in the presence of NOx on 18 November

1999. The concentration of formaldehyde is slightly

underestimated by the model for reaction times after

13:00 GMT. However, this deviation reaches only a few

ppb and is within the experimental error of the HCHO

concentration (typically 720%). In total, the calculated

and experimental concentration–time profiles are in

good agreement.


centrations of NO (E), NO2 (&), ozone (J) and formalde-

hyde/2 (m) for the smog chamber run of 24 November 1999

(base mixture II).


centrations of NO (E), NO2 (&) and ozone (J) for the smog

chamber run of 15 November 1999 (fuel 1).


centrations of NO (E), NO2 (&) ozone (J) and formaldehyde

(m) for the smog chamber run of 18 November 1999 (fuel 2).


From Table 3 it is evident that the ozone formation

rate of 82.7 ppb h�1 in the biodiesel experiment is the

highest value of all runs. It should be pointed out that

this is not specific for the combustion of biodiesel. The

observation of Palm and Kr .uger (1998, 1999) that the

combustion of biodiesel leads to higher formaldehyde

emissions than the burning of a conventional diesel was

not confirmed within the DIFUSO project (Wiesen,

2000). The formaldehyde concentrations measured in

the biodiesel exhaust were not higher than for all other

diesel fuels tested. Accordingly, the high ozone forma-

tion observed in the biodiesel experiment on 18

November 1999 was due to the experimental conditions.

The photolysis intensity here was the highest of all the

days of the campaign and the NO/NO2 ratio is the

smallest of all the exhaust experiments performed. Both

the factors promote ozone formation in the system and

are obviously the reasons for the remarkably high ozone

formation observed.

3.3.5. Diesel containing 5% aromatic HC (fuel 3)



NO2, and ozone for the experiment performed using

exhaust from the fuel with 5% aromatic HC content

together with the base VOC mixture in the presence of

NOx on 16 November 1999. While the ozone concentra-

tion is excellently modelled, the simulation system-

atically underestimates the concentration of

formaldehyde. It seems that the radical concentration

in the model is somewhat lower than in the experimental

system, indicated by the slight shift of the NO/NO2

crossing point to higher reaction times. The reason for

these small deviations is not clear. Nevertheless, the

description of the experiment by the model is still

reasonable.

3.3.6. Diesel containing 15% aromatic HC (fuel 4)



NO2, and ozone for the experiment performed using

exhaust from the fuel with 15% aromatic HC content

together with the base VOC mixture in the presence of

NOx on 19 November 1999. The calculated formalde-

hyde concentrations and the NOx data are in reasonable

agreement with the experiment, apart from the over-

estimation of NO2 by the model after 13:15GMT. The

modelled ozone concentration after 13:15GMT is

clearly higher than the measured data. The reason for

this large discrepancy is probably the weather situation

on this day. The spectral radiation was not continuous

due to numerous clouds. As a consequence, the

photolysis data were frequently changing between high

and low values. It was not possible to adapt the model to

this difficult photolysis situation. Accordingly, the

photolysis rates in the calculations did not exactly

reflect the experimental scenario and this resulted in

larger errors in the model results. This can be seen in the

ozone concentration in Fig. 9. While the experimental

ozone shows clear ‘‘dents’’ at 12:50 and 13:20GMT due

to extensive cloud coverage at these times, the simulated

ozone profile exhibits a smooth shape. In spite of the


centrations of NO (E), NO2 (&), ozone (J) and formalde-

hyde (m) for the smog chamber run of 16 November 1999 (fuel

3).

Fig. 9. Comparison of simulated (solid lines) and experimental

concentrations of NO (E), NO2 (&), ozone (J) and

formaldehyde/2 (m) for the smog chamber run of 19 November

1999 (fuel 4).


complex photolysis situation, the model gives a reason-

able picture of the chemical system.

3.4. Sensitivity analysis with respect to ozone formation

In order to identify the most important steps in the

initial phase of the smog chamber runs leading to ozone

formation and for further interpretation of the results,

sensitivity analyses were carried out using the direct

decoupled method of Dunker (1984). The sensitivities of

ozone towards all rate coefficients of the chemical

mechanism were calculated. For this purpose, rate

parameter sensitivity coefficients, SK ; were calculated

as described by Stockwell et al. (1995). These rate

parameter sensitivity coefficients depend on the concen-

trations of all reactants and, therefore, on the reaction

time. Thus time-dependent relative sensitivities can be

calculated from the SK values. Fig. 10 shows the relative

sensitivities at t ¼ 30 min (representing the initial phase

of each experiment) of ozone towards selected reaction

rate coefficients. These nine reactions are the most

sensitive for ozone formation and account for X90% of

the total sensitivity in the initial phase of each run. A

positive sensitivity indicates that an increase in the rate

coefficient will cause an increase in the ozone concen-

tration, while increasing the rate constants with a

negative sensitivity will lead to a smaller concentration

of ozone. The plot illustrates the typical situation for a

smog system: The photolysis of NO2 is the most

important reaction leading to ozone formation, whereas

the reaction of O3 with NO is the most significant sink

for ozone in the system.

Fig. 10 clearly indicates that compared to the base

mixture I experiment, the formation of ozone in the

exhaust studies is significantly promoted by the photo-

lysis of the initial concentrations of nitrous acid and

formaldehyde. For all diesel experiments, the relative

sensitivities for these reactions are about a factor of 2

higher, whereas the importance of the NO2 photolysis

and the reaction O3+NO is lowered by a factor of about

2. The photolysis of higher aldehydes is of minor

importance regarding ozone formation.

It is remarkable that for all the reactions displayed in

Fig. 10, the corresponding sensitivities for the diesel

exhaust runs are more or less equal, demonstrating that

the different but significant higher ozone formation rates

observed in comparison to the reference experiment are

not specific for the diesel fuel formulation. They are

clearly the results of more or less different initial

parameters such as start concentrations or photolysis

frequencies during the single experiments.

4. Summary and conclusions

The experiments performed in the EUPHORE smog

chamber in November 1999 were simulated using a

simple box model, including only gas-phase chemistry.

The model described all experiments with high accuracy.

Sensitivity analyses were carried out in order to explain

the observations.

The addition of diesel exhaust to a well-defined simple

VOC mixture caused a significant increase in the ozone

formation after irradiation, in comparison to smog

experiments with a similar VOC/NOx ratio in the

absence of exhaust gas. The increase of ozone observed

in the exhaust runs was mainly caused by the high initial

concentrations of nitrous acid and formaldehyde

emitted by the diesel engine. Higher aldehydes were of

minor importance. The ozone formation was not

dependent on the formulation of the diesel fuel.

Differences in ozone formation rates for the single

experiments were due to deviations in initial start

concentrations as well as photolysis conditions.

Further studies within the DIFUSO project studies

exhibited that the influence of diesel soot on the ozone

formation is negligible under the conditions of the

smog chamber experiments performed. The present

Fig. 10. Relative sensitivities of ozone towards the rate

coefficients of selected elementary reactions of the chemical

mechanism used at t ¼ 30min. The results for all diesel exhaust

experiments are shown in comparison with those for the

reference experiment on 23 November 1999 (base mixture I);

DCB=unsaturated dicarbonyls. For the calculation of the total

fraction for the other reactions, the signs of the single

sensitivities were not considered.


simulations using a simple gas-phase model leading to

good agreement of experimental and calculated data

confirmed this observation.

For the future, detailed measurements of NOx,

HONO and aldehydes in diesel exhaust for typical

motor conditions should be considered. The use of such

data as input parameters for the calculation of ozone

formation potentials (e.g. incremental reactivities by the

method of Carter et al., 1995) can contribute to a better

estimation of the influence of diesel exhaust on tropo-

spheric ozone formation.

5. Atmospheric implications

The high NOx levels emitted by diesel engines in

contrast to gasoline-fuelled engines have to be consid-

ered for atmospheric air pollution, especially if the

number of diesel-fuelled vehicles might increase in the

future. The amounts of nitrous acid emitted will not

probably influence the formation of photosmog, since

similar emission indices have been reported in the

literature (Kurtenbach et al., 2001). In addition, in the

atmosphere, much higher HONO/NOx ratios compared

to direct emissions have been observed during nighttime

(see, e.g. Harrison et al., 1996). Accordingly, a partial

replacement of gasoline by diesel as energy source for

vehicles, probably, will not significantly affect the

tropospheric HONO/NOx ratio.

The emissions of hydrocarbons and unburned fuel

from diesel engines are negligible and consequently also

their contribution to the anthropogenic hydrocarbon

budget. In contrast, the emissions of formaldehyde and

other photosensitive carbonyl compounds might play a

role in tropospheric ozone formation, since the photo-

lysis of these compounds leads to radicals, which

enhance the atmospheric oxidation capacity. In conclu-

sion, if the number of diesel-powered vehicles is

increased, which is expected in the near future, their

emissions in comparison to those of gasoline vehicles

must be considered for air pollution control strategies.

From the technological point of view, the develop-

ment of more efficient exhaust gas cleaning techniques,

such as catalytic converters, for diesel engines should be

strongly advocated. Fuel formulation might not be first

choice to achieve a further emission reduction, since the

present study has shown that the formulation of the

diesel has no significant influence on exhaust composi-

tion and, therefore, on photosmog formation.

Acknowledgements

Financial support of this work by the European

Commission, Contract No. EV4V-CT97-0390 (DIFU-

SO), is gratefully acknowledged. The authors are deeply

indebted to K. Wirtz, CEAM, Valencia (Spain), for

kindly providing the experimental data, which were used

for the model calculations performed in this study.

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