EUROTRAC-2 

(A EUREKA Environmental Project) 

Limitation of Oxidant Production 

Final Report 

Editors 

Albrecht Neftel and Christoph Spirig 

Swiss Federal Research Station for Agroecology and Agriculture, 

Zurich, Switzerland 

International Scientific Secretariat (ISS), 

GSF - National Research Center for Environment and Health 

Munich, Germany 

2003 
Preface 

Retrospectively, the suggestion to investigate the limitation of oxidant production 

as a EUROTRAC-2 subproject was a naïve act. To focus a whole subproject on 

this aspect was difficult for both group of affiliates: while pure scientists found it 

hard to accept such a projection on one focal point, actors related to agencies had 

to accept that their treatments of the ozone problems required more detailed 

investigations. 

The idea of such a project arose in 1997 during a meeting in Bern and LOOP 

took off, driven by the enthusiasm of a small group of atmospheric scientists. 

During the course of LOOP, many of the first principal investigators were forced 

or deliberately chose to leave the field. As a consequence, some of the ideas 

originally proposed were omitted but, more importantly, quite a few have been 

realised and produced valuable scientific results. Throughout the whole project, 

LOOP was characterised by an open spirit, discussions that were sometimes 

controversial but always fair, and often unconventional ways of acting. 

Having an idea is not enough; its successful realisation depends on close 

collaborators who fully support the idea. During the initial phase of the project, I 

was very lucky to have Thomas Staffelbach as the trouble-shooter. When he 

became aware that our former institute, the Institute for Environmental Protection 

and Agriculture located in Liebefeld – Bern would be incorporated into the new 

Swiss Federal Research Station for Agroecology and Agriculture (FAL) in 

Zurich, he decided to leave the field, and began actively to do something for air 

quality. He is now leading a small company specialising in information systems 

for public transportation. If you happen to enjoy a friendly announcement during 

a pleasant trip in a Swiss train, it was most probably done by his company. 

Luckily, Christoph Spirig stepped in as his successor and became the new 

trouble-shooter. Without his efficiency in compiling information, this document 

most probably would not exist. 

I am grateful for the LOOP coordination credit from the Commission of 

Technology and Innovation (KTI). Hans Richner, the Swiss representative on the 

EUROTRAC-2 IEC continuously supported the LOOP activities with great 

enthusiasm. Last but not least, I would like to thank my superiors at the FAL for 

letting me lead the LOOP project even though it was not directly related to 

farmers' needs. 

Albrecht Neftel, LOOP Subproject coordinator 
Contents 

1 Introduction..................................................................................................... 1

1.1 EUROTRAC-2 and LOOP ............................................................................... 1 

1.2 Goals of LOOP ................................................................................................. 1 

1.3 LOOP activities................................................................................................. 2 

1.4 LOOP investigators........................................................................................... 3 

2 Scientific Background..................................................................................... 5 

2.1 Photo-oxidant production - NOX versus VOC sensitivity of P(O3).................. 5 

2.1.1 Ozone formation processes in the lower troposphere................................... 5 

2.1.2 Chemical ageing ........................................................................................... 5 

2.1.3 Expressions of P(O3)..................................................................................... 6 

2.1.4 Approximation for ODD-H radicals ............................................................. 7 

2.1.5 P(O3) derived from Leighton ratio................................................................ 8 

2.1.6 Approximate formulas for NOx/VOC dependence of P(O3) ........................ 9 

2.1.7 NOx and VOC sensitivity of P(O3) ............................................................. 10 

2.2 The dependence of ozone production on VOC reactivity and 

 oxidation mechanisms..................................................................................... 13 

2.2.1 Principles .................................................................................................... 13 

2.2.2 Hydroperoxides........................................................................................... 14 

2.2.3 Peroxyacetyl Nitrate (PAN)........................................................................ 15 

2.2.4 Ozonolysis of carbon double bonds............................................................ 16 

2.2.5 Radical measurements ................................................................................ 17 

2.3 From the local ozone production to the ozone concentration......................... 19 

2.3.1 Basic principles........................................................................................... 19 

2.3.2 Indicators .................................................................................................... 20 

2.3.3 Discussion of indicators.............................................................................. 22 

2.4 Photo-oxidants and aerosols ........................................................................... 23 

2.4.1 Inorganic aerosols ....................................................................................... 24 

2.4.2 Secondary organic aerosols ........................................................................ 24 

2.5 Performance of emission inventories – what can modellers expect? ............. 28 

2.5.1 Introduction................................................................................................. 28 

2.5.2 Steps of creating an emission inventories................................................... 28 

2.5.3 Types of input into emission inventories.................................................... 29 

2.5.4 Disaggregation of emission inventories...................................................... 30 

2.5.5 Methods for validation................................................................................ 31 

2.5.6 Recommendations and conclusions............................................................ 32 
 Contents 

3 Field Campaigns............................................................................................35 

3.1 BOCCALINO..................................................................................................35 

3.2 SLOPE.............................................................................................................36 

3.3 BERLIOZ ........................................................................................................38 

3.3.1 Scientific background..................................................................................39 

3.3.2 Experimental ...............................................................................................42 

3.3.3 Meteorological situation..............................................................................46 

3.3.4 Data Quality and Instrument Comparisons .................................................47 

3.3.5 Observational results...................................................................................50 

3.3.6 Model simulations.......................................................................................56 

3.3.7 Conclusions .................................................................................................58 

Acknowledgement...................................................................................................59 

3.4 PIPAPO ...........................................................................................................60 

3.4.1 The Milan basin as natural photoreactor .....................................................60 

3.4.2 Intensive observation periods......................................................................61 

3.4.3 QA/QC of PIPAPO. ....................................................................................62 

3.4.4 Emissions ....................................................................................................63 

3.4.5 Meteorology and photosmog episodes in the Milan area............................65 

3.4.6 Investigation of P(O3) based on observations .............................................67 

3.4.7 Aerosols.......................................................................................................70 

3.4.8 Model analysis.............................................................................................73 

3.4.9 Summary of scientific findings of the PIPAPO experiment .......................82 

Acknowledgements .................................................................................................84 

3.5 Atmospheric pollution over the Paris area: The ESQUIF project ...........85 

3.5.1 General introduction to the campaign .........................................................85 

3.5.2 Overview over results relevant for the LOOP project.................................86 

3.5.3 Climatology of the chemical regime in the Paris - 

 Ile de France region –a model simulation ...................................................88 

Acknowledgements .................................................................................................92 

3.6 ESCOMPTE....................................................................................................93 

3.6.1 General framework of the ESCOMPTE programme ..................................93 

3.6.2 The ESCOMPTE area and period ...............................................................93 

3.6.3 Experimental set-up.....................................................................................93 

3.6.4 The campaign progress................................................................................95 

3.6.5 Specific results: photochemical ozone production and chemical regime ...96 

Acknowledgements ...............................................................................................103 

4 Integration - scaling up...............................................................................105 

4.1 LOOP interactions with environmental policy..............................................105 
Contents 

4.2 The need for environmental agencies ........................................................... 105 

4.2.1 Peak ozone ................................................................................................ 106 

4.2.2 Ozone levels and cumulated indices (AOT-values) ................................. 107 

4.3 Influence of LOOP on environmental policy................................................ 107 

5 Synthesis: LOOP Messages in a Nutshell ................................................. 109 

5.1 Are the simulations of the efficiency of VOC versus NOx emission 

 reduction on the ozone production on a sound base? ................................... 109 

5.2 Do biogenic emissions influence the VOC – NOx sensitivity of the 

 ozone production?......................................................................................... 109 

5.3 Can indicators be used to characterize chemical regimes of 

 ozone production?......................................................................................... 109 

5.4 How does the grid resolution influence the model results? .......................... 110 

5.5 What is the influence of aerosols? ................................................................ 110 

5.6 How do photochemical models relate to the AOT concept ? ....................... 111 

5.7 What kind of activities are still needed?....................................................... 111 

6 References.................................................................................................... 113 
1. Introduction 

1.1 EUROTRAC-2 and LOOP 

The rationale for the EUROTRAC-2 project as a whole is “to support the further 

development of abatement strategies within Europe by providing an improved 

scientific basis for the quantification of source-receptor relationships for photooxidants, aerosols and acidifying substances.” 

EUROTRAC-2 aims to provide an integrated scientific evaluation of photooxidants, aerosols and acidifying substances in the troposphere over Europe, 

using the extended knowledge base and improved methodologies gained in the 

first phase of EUROTRAC. In particular advanced techniques in linking 

numerical atmospheric models and observational data are used to provide an 

unprecedented capability for understanding the complex interactions between the 

sources, transformations and deposition which determine the concentrations of 

trace substances appropriate to environmental impact. The work thus provides 

scientific support for future measures needed to control photo-oxidants and the 

deposition of acidifying substances and nutrients. 

Photo-oxidants is a key issue in EUROTRAC-2. The subproject LOOP 

(Limitation of Oxidant Production) focuses on the question which species or 

group of species limit the formation of photo-oxidants – it is thus directly 

addressing the objectives of the EUROTRAC-2 project. 

LOOP proposed to investigate the temporal behaviour and the spatial extent of 

VOC and NOx sensitive areas of photo-oxidant production. Special emphasis is 

given to the relative roles of VOC and NOx in the photo-chemical production of 

ozone and other photo-oxidants in polluted areas. 

In order to assess effective and cost-efficient ozone management strategies it is 

important to know the spatial extent of the different ozone production regimes as 

well as their temporal behaviour. LOOP promised to provide improved 

experimental and modelling tools for this task. 

1.2 Goals of LOOP 

An improved understanding of the temporal evolution and the spatial extent 

of the different photo-oxidant production regimes in the planetary boundary 

layer in order to assess the effectiveness of reduction strategies towards 

ground level ozone. 

An evaluation of the indicator concept to determine areas of NOx and VOC 

sensitive ozone production across Europe. The robustness of the indicator 

concept towards changes in chemical and meteorological parameters will be 

evaluated. 
2 Introduction 

1.3 LOOP activities 

A major component of LOOP is the production of joint publications in peer 

reviewed journals. This guarantees the maintenance of a high scientific level as 

well as the distribution of the experience to a wide audience. In order to support 

joint publications and to facilitate the exchange of information between the 

LOOP community in general, a series of workshops was held (Table 1). LOOP 

established close links to EMEP, the Co-operative Programme for Monitoring 

and Evaluation of the Long-Range Transmission of Air Pollutants in Europe, in 

order also to ensure the links between science and environmental policy. 

Table 1. Workshops within LOOP. 

Workshop Location Date Focal point 

Gerzensee March 20th to 22nd, 

1999 

Limitation of ozone production based on 

interpretation of field data (observationbased modelling) and on numerical models. 

Varese December 13-16, 

1999 

Scientific results of the BERLIOZ and 

PIPAPO field campaigns. Joint workshop of 

the Lombardy Region, LOOP and the 

German TFS / LT3 (BERLIOZ). 

Gerzensee December 3-6, 2001 Joint LOOP / EMEP workshop. Exchange 

of information between the LOOP and 

EMEP communities 

Activities within LOOP were centred on several field initiatives, each of them 

with its own characteristics and structure. SLOPE and BOCCALINO can be 

considered as “trigger initiatives” for LOOP. 

Table 2. Field activities with links to LOOP.

Project Name Duration Major focus 

SLOPE Sept 1992 and June 

1996 

Budgets of OH radicals and ozone in the 

plume of Freiburg 

BOCCALINO July-August 1994 Peroxides as indicators for chemical 

regimes. 

BERLIOZ July-Aug 1998 Development of the city plume, radical 

chemistry 

PIPAPO May and June 1998 NOx / VOC limitation of Ozone production 

in the Po Valley, Italy 

Secondary aerosol formation 

ESQUIF July, August 1998; 

June and July 1999; 

August 2000; 

Documentation of photochemical oxidant 

formation in the Greater Paris area 

ESCOMPTE June and July 2001 Build-up of an experimental data base 

allowing the thorough validation of air 

quality models 
LOOP Final Report 3

1.4 LOOP investigators 

Table 3. Original list of LOOP principal investigators (PIs). 

 Original P.I. Title of contribution 

1 Johanna Altenstedt, Swedish 

Environment Research Institute, 

IVL, Sweden 

Using the IVL model as chemical reference in a 

highly variable chemical environment 

2 Bertrand Calpini, Swiss Federal 

Institute of Technology, EPFL, 

Switzerland 

Characterisation of the PBL and the ozone 

development in the Milan - Ticino region. DIAL 

developments, field measurements and modelling 

case study analysis 

3 Josef Dommen, Paul Scherrer 

Institute, Department of General 

Energy Technology, Switzerland 

HCHO/NOy as an indicator of the photo-chemical 

state of an air mass 

4 Ugo Facchini, Istituto di Fisica 

Generale Applicata, Milan, Italy 

Ozone and Radon measurements in the Milan 

basin 

5 Jens Hjorth, JRC- Ispra, Italy VOC and peroxyradical field measurements to 

understand photo-chemical ozone formation 

6 Bruno Neininger MetAir AG, 

Applied Atmospheric Physics, 

Switzerland 

Aircraft measurements between Milan and the 

Alps 

7 Nicola Quaranta 

Regione Lombardia, Settore 

Ambiente ed Energia, Italy 

Chemical-physical model approach to determine 

the different photo-chemical regimes in the Milan 

aerologic basin 

8 Jana Slemr, Frauenhofer-Institut für 

Atmosphärische Umweltforschung, 

IFU, Germany 

Urban emissions and their impact on 

surroundings 

9 Johannes Staehelin, Atmospheric 

Science, Swiss Federal Institute of 

Technology, Switzerland 

Surface measurements of NOx, NOy, J(NO2), O3

and volatile hydrocarbons (C5-C11) and 

trajectory calculations 

10 Thomas Staffelbach, Institute for 

Environmental Protection and 

Agriculture, Switzerland 

Limitation of Oxidant Production in the Milan 

basin 

11 Gérard Toupance, LISA, Université 

Paris, France 

ESCOMPTE 

12 Bernhard Vogel, IMK, University 

Karlsruhe, Germany 

Numerical Simulation of the Temporal and 

Spatial Distribution of Indicator Species 

13 Gerard Ancellet and Pascal Perros, 

Université Paris, France 

Aircraft studies of the ozone 3 dimensional field 

and of the nitrogen oxides partitioning during the 

Milan experiment 

14 Andreas Volz-Thomas, 

Forschungszentrum Jülich, Germany 

Investigation of Photo-oxidant Precursor 

Relations and the in situ Formation Rate from the 

TOR-Schauinsland Data 

15 Wilfried Winiwarter, Austrian 

Research Centre Seibersdorf, Austria

Development of a High Performance Emission 

Inventory for Assessing Urban Plumes 

16 Ulrich Joss, Meteotest, Bern, 

Switzerland 

Photochemical regimes simulated with 

Berphomod 
4 Introduction 

17 John Burrows, University of 

Bremen, Germany 

ROx measurements 

18 Ulrich Vogt, University of Stuttgart, 

Germany 

Balloon soundings 

19 Theo Brauers, Forschungszentrum 

Jülich, Germany 

Measurements of the OH and HO2 radical 

concentrations in polluted air masses 

20 Helga Kromp-Kolb, University of 

Vienna, Austria 

Vertical Ozone transports in the Alps II 

(VOTALP II) 

21 Ulrich Platt, University of 

Heidelberg 

Measurements of HONO, NO2 and HCHO by 

DOAS and investigation of the HONO formation 

mechanisms 

22 Matthias Beekmann, Service 

d’Aéronomie/ IPSL / France 

Chemical regime within the ESQUIF and 

ESCOMPTE campaigns 
2. Scientific Background 

2.1 Photo-oxidant production - NOX versus VOC 

sensitivity of P(O3) 

Albrecht Neftel 

Swiss Federal Research Station for Agroecology and Agriculture, Zurich, Switzerland 

Lawrence I. Kleinman 

Brookhaven Natl. Lab., Environmental Sciences Division, Upton, NY, USA 

2.1.1 Ozone formation processes in the lower troposphere 

Ozone is formed from the photochemical oxidation of volatile organic 

compounds (VOCs) in the presence of oxides of nitrogen (NOx = NO + NO2). 

The oxidation processes that lead to ozone production are initiated by photolysis 

of various molecules. Figure 1 shows a simplified representation of the complex 

pathway involved in producing ozone leaving out organic peroxy radicals. 

THE TROPOSPHERIC OZONE CYCLE

P(O3) = k[HO2 ][NO]

NO

HO2

OH

HO2 + NO OH + NO2

OH + CO H + CO2

H + O2 HO2

CO

CO2

P(O3) = k[OH][CO]

O3

hv

NO2 + hv NO + O

O + O2 O3

NO2

Figure 1. Scheme of ozone production with CO as a surrogate for VOCs. 

2.1.2 Chemical ageing 

Determining the relation between O3 and its precursors has been the object of 

more than 4 decades of research (NARSTO, 2000; NRC, 1991; Sillman et al., 
6 Scientific Background 

1990). It has been found that the production of ozone P(O3) depends on NOx and 

VOC emissions in a complicated and non-linear way. Sillman et al. (1990) 

presented approximations of P(O3) as function of NOx and VOCs. 

Figure 2 shows ozone production as function of NOx for various levels of VOCs.

Either of the two precursors may limit P(O3). For a given level of VOC, the rate 

of ozone production will increase with increasing NOx so long as NOx is low. 

Eventually the rate of ozone production reaches a maximum value as the 

chemistry undergoes a transition from low-NOx to high-NOx conditions. At 

higher NOx concentrations the rate of ozone production decreases with increasing 

NOx but would increase with increasing VOC. The transition from low-NOx to 

high-NOx chemistry is associated with a specific ratio of VOC to NOx. The exact 

transition depends on the speciation and reactivity of the VOC mix and not just 

on the absolute concentration of VOC. 

0

1

2

3

4

5

6

7

0 5 10 15 20

NOx (ppb)

VOC=20ppbC

VOC=50ppbC

VOC=100ppbC

lowNOx

transition

high-NOx

Figure 2. Net rates of ozone production (ppb per hour) as a function of NOx (ppb), for VOC = 20 ppbC 

(solid line), 50 ppbC (long dashed line) and 100 ppbC (short dashed line), based on calculations shown in 

Milford et al. (1994). 

2.1.3 Expressions of P(O3) 

Ozone production rates cannot be directly observed but instead has to be deduced 

in a more or less indirect way from observed concentrations. The least indirect 

way of obtaining P(O3) is from measurements of peroxy radicals and NO. The 

relevant chemistry is: 

HO2 + NO  OH + NO2 (R 1) 

RO2 + NO  RO + NO2 (R 2) 

1

2 

3 
LOOP Final Report 7

NO2 + hν  NO + O (R 3) 

O + O2  O3 (R 4) 

NO + O3  NO2 + O2 (R 5) 

Since O3 is formed with nearly 100% yield from NO2: 

P(O3) = (k1[HO2] + k2[RO2]) [NO] (1) 

The difficulty in using (1) is that peroxy radicals are difficult to measure and k2

(as the average rate constant of all species encompassed by the term ‘RO2’) is 

hard to determine. Therefore alternate methods of determining P(O3) are needed. 

2.1.4 Approximation for ODD-H radicals 

Peroxy and OH radicals react rapidly (characteristic lifetimes of 100 and 1 s, 

respectively) so it is expected that they are in a steady state equilibrium with 

other longer lived atmospheric trace gases. Only a few field measurements exist 

on ground stations. Routine and/or operational measurements are not existent. As 

a consequence indirect methods have been developed to characterise ODD-H 

levels and P(O3) and their dependence on NOx and VOC concentrations. If all of 

the stable reactants are measured then HO2, RO2, and OH can be calculated by 

solving a set of steady state equations. 

P [OH] k [S ] 0

dt

d[OH]

i

 OH   i i  ( 2) 

P [HO ] k [S ] 2k [HO ] 0

dt

d[HO ] 2

peroxid 2

j

HO 2 j j

2

2      ( 3) 

P [RO ] k [S ] 2k [RO ] 0

dt

d[RO ] 2

o_peroxid 2

j'

RO 2 j' j'

2

2     

 ( 4) 

where POH, PHO2 and PRO2 are the production rates of OH, HO2 and RO2, 

respectively. Si, Sj, and Sj’ denote (radical or non-radical) species that act as 

reaction partners in sink reactions of OH, HO2 and RO2, respectively. 

The radical production rates are determined from photolysis rate constants and 

the concentrations of radical precursors. A solution of (2-4) can be obtained by 

solving these equations algebraically or by integrating a coupled set of ordinary 

differential equations (e.g., for d[OH]/dt, d[HO2]/dt, d[RO2(i)]/dt) to steady state. 

In either case concentrations of stable compounds are fixed at their observed 

concentration. NO2 has a short lifetime and in both approaches it can either be 

constrained or calculated. The treatment of compounds such as PAN with an 

intermediate lifetime can be problematic. If PAN is measured then it can be 

included as a reactant on the right hand side of (2-4). If PAN is not measured, a 

steady state assumption can be made as best approximation. 

The accuracy of (2-4) will depend on the completeness and accuracy of the input 

variables, namely measured concentrations and kinetic parameters. A particular 

concern is the accurate quantification of HONO. Another concern is that 

observations of VOCs and their oxidation products be sufficiently complete, so 
8 Scientific Background 

as to give a realistic value of OH-reactivity and radical production. Ultimately 

the accuracy of (2-4), and indeed of any mechanism describing "fast" 

photochemistry, will have to be assessed by comparing measured and calculated 

values of free radicals. 

A large influence has the NO concentrations. NO2 is difficult to measure. 

Routine network data with conventional monitors that convert NO2 to NO using 

molybdenum converters systematically overestimate NO2 values. Such a set of 

measurement is not in a quasi equilibrium state and will lead to erroneous 

conclusions. This can easily be checked when the set of measurement is used as 

initial values in a box model. In case the NO / NO2 ratio shows a very fast 

change the set of measurement was not in equilibrium, either due to fresh 

emissions or due to an overestimation of NO2. 

2.1.5 P(O3) derived from Leighton ratio 

P(O3) can alternatively be calculated by the deviation from the Leighton ratio, 

also named Photostationary State relation (PSS): 

   3 2 2 5 3 P(O )  jNO  NO k  NO  O ( 5) 

The PSS relations come from setting d[NO]/dt or d[NO2]/dt = 0. We can expand 

the set of processes to include sink reactions for NO and NO2. If we do this we 

also have to include an emission term, else [NO] and [NO2] will decrease. 

Suppose organic NO + RO2 has an organic nitrate yield of δ, i.e., 

k1[HO2] [NO] + k2[RO2][NO] = P(O3) + δ organic nitrate ( 6) 

then: 

d[NO]/dt = 0 = jNO2 [NO2] – k5[NO][O3] – P(O3) + E(NO) - δ P(O3) ( 7) 

yielding 

P(O3) = jNO2 [NO2] – k5[NO][O3] + E(NO) - δ P(O3) ( 8) 

δ has a value of about 0.03 for a typical mixture of VOCs, so it will be ignored. 

the NO2 equation gives us: 

d[NO2]/dt = 0 = - jNO2 [NO2] + k5[NO][O3] – k6[OH][NO2] + P(O3) ( 9) 

yielding 

P(O3) = jNO2 [NO2] – k[NO][O3] + k[OH][NO2] (10) 

In order for both equations to be correct E(NO) = k6[OH][NO2], which is the 

conservation equation for NOx. The NO2 sink term can be written in terms of an 

O3 production efficiency per NOx as 

k6[OH][NO2] = P(O3)/OPE (11) 

so if OPE is small (i.e., 2), then ignoring it can lead to a 100% under-estimate of 

P(O3), i.e., 

P(O3) with sinks = P(O3) without sinks / (1 - 1/OPE). (12) 

One could add dilution terms to these equations. Dilution does not interchange 

NO and NO2 but it's rate can be greater than chemical loss. 
LOOP Final Report 9

Suppose there are no NOx emissions and the air parcel is not in steady state 

because NOx is getting lost in the form of NO2. 

Then 

d[NOx]/dt = d[NO]/dt + d[NO2]/dt = -k6[OH][NO2] ( 13) 

and d[NO2]/dt > d[NOx]/dt (i.e.,, d[NO2]/dt is less negative than d[NOx]/dt) 

d[NOx]/dt = -k6[OH][NO2] < d[NO2]/dt ( 14) 

d[NO2]/dt = - j[NO2] + k5[NO][O3] + P(O3) – k6[OH][NO2] ( 15) 

-k6[OH][NO2] < - j[NO2] + k5[NO][O3] + P(O3) – k6[OH][NO2] ( 16) 

0 < - j[NO2] + k5[NO][O3] + P(O3) ( 17) 

P(O3) > j[NO2] – k5[NO][O3] ( 18) 

But since d[NOx]/dt is not too much smaller than d[NO2]/dt , the last Eq is almost 

the usual result. 

2.1.6 Approximate formulas for NOx/VOC dependence of P(O3) 

Sometimes it is useful to have an approximate formula for P(O3), especially if it 

can be evaluated from a limited set of measurements or if it has a functional form 

that can give insights into the relation between P(O3) and O3 precursors. Such 

formulas can be derived from a simplified set of photochemical equations 

organized as a chain reaction (Kleinman, 1994; Kleinman et al., 1997, Kleinman, 

2000; Kleinman et al., 2000): 

Initiation; Radical Production 

O3 + hν  O(1

D) (R 6) 

O(1

D) + H2O  2 OH (R 7) 

HCHO + hν  2 HO2 (R 8) 

Chain Propagation (schematic) 

OH + VOCi  HO2 (or RO2) + Carbonyl (R 9) 

HO2 (or RO2) + NO  OH (or Carbonyl + HO2) + NO2 (R 1 and R 2) 

NO2 + hν (+O2)  NO + O3 (R 3) 

Chain Termination 

LN (NOx + Radical) 

OH + NO2  HNO3 (R 10) 

LR (radical + radical) 

HO2 + HO2  H2O2 (R 11) 

RO2 + HO2  ROOH (R 12) 
10 Scientific Background 

Sources and sinks of free radicals must be in balance, yielding an odd-hydrogen 

budget equation: 

Q = LN + LR ( 19) 

where Q is the primary production rate of radicals and the removal terms LN and 

LR are approximated as above. 

At low NOx concentration, almost all radicals are removed by peroxide 

formation. The radical budget equation becomes Q = LR, which can be solved for 

[HO2]+[RO2], which gives P(O3) from (1). The low NOx formula for P(O3) is 

P(O3) = k1/(2 keff)

1/2 Q1/2 [NO] ( 20) 

where keff is an effective rate constant for peroxide formation that depends on the 

individual rate constants for HO2+HO2 and RO2+HO2 as well as the fraction 

[RO2]/[HO2]. 

A high NOx formula is derived in the limit that Q = LN with the additional 

assumption that propagation >> termination. The latter approximation gives us 

kOH+VOCi Yi [OH] [VOCi] = k1 ([HO2] + [RO2]) [NO] = P(O3) ( 21) 

where the summation is over all VOCs and Yi is a stoichiometric factor for the 

number of peroxy radicals produced from OH+VOC (for an individual VOC, Yi

is usually equal to 1 or 2) (Sillman, 1995a; Tonnesen and Dennis, 2000). [OH] is 

derived from the budget equation 

Q = kOH+NO2 [OH] [NO2]. ( 22) 

Combining (21) and (22), we obtain 

P(O3) = Q kOH+VOCi Yi [VOCi]/ (kOH+NO2 [NO2]) ( 23) 

Equation (23) shows that in the high NOx limit, P(O3) depends on a VOC to NO2

reactivity ratio. 

2.1.7 NOx and VOC sensitivity of P(O3) 

In a similar fashion to (23) we can derive a formula that is valid for intermediate 

NOx conditions where both LN and LR pathways are important: 

P(O3) = k1/(2 keff)

1/2 (Q- LN)1/2 [NO] ( 24) 

Equation (24) can be used to evaluate P(O3) based on the formula given below 

for LN/Q. The resulting expression is somewhat complicated and does not clearly 

show how P(O3) depends on NOx and VOCs. Instead, the utility of (24) is that 

relative sensitivities of P(O3) to NO and VOCs can be determined by 

differentiation with respect to [NO] or [VOC] (Kleinman et al., 1997). The 

derivation makes use of the approximations: 

LN = kOH+NO2 [OH] [NO2] ( 25) 

P(O3) = kOH+VOCi Yi [OH] [VOCi] ( 26) 

Relative sensitivities are given by 

dlnP(O3)/dln[NO] = (1 - 3/2 LN/Q)/(1 - 1/2 LN/Q) ( 27) 
LOOP Final Report 11

dlnP(O3)/dln[VOC] = (1/2 LN/Q)/(1 - 1/2 LN/Q) ( 28) 

The sensitivities are given in terms of a single independent variable, LN/Q; the 

fraction of radicals which are removed by reactions involving NOx. The utility of 

(27) and (28) is that they show very clearly the functional form of the solutions to 

a complex photochemical process and also provide a theoretical justification for 

one combination of indicator species (Sillman, 1995a). 

An explicit equation for LN/Q has been derived using the same type of 

approximations that were used to determine relative sensitivities (Kleinman et 

al., 2001). The derivation depends on radical balance as given in (19), with LR

expressed in terms of peroxide formation and LN expressed in terms of HNO3

formation (25). It is also assumed that chain propagation is more likely than 

termination. This is expressed in (21) and in a slightly different form below: 

 kOH+VOCi [OH] [VOCi] = k1 [HO2] [NO] ( 29) 

The desired equations are: 

LN/Q = - /2 + (2

 + 4)

1/2/2 ( 30) 

where 

= (kOH+NO2[NO2] k1[NO]/( kOH+VOCi [VOCi]))2

 (1/(2 Q keff)) ( 31) 

and 

 = [HO2]/[HO2 + RO2] ( 32) 

 

Figure 3. Dependence of LN/Q as function of Log(α) and NOx (Kleinman et al., 2001). 

The utility of (30-32), is that LN/Q can be shown to be a monotonic increasing 

function of [NOx]

4

/(Q*[VOC]2), which allows qualitative arguments to be made 

about the effects of chemistry and dilution on NOx and VOC sensitivity. There 
12 Scientific Background 

are interesting city to city differences in the dependence of LN/Q on NOx and 

VOCs which are helpful in understanding the conditions under which O3 is 

formed. 

These approximate formulas are tested by comparison with a CSS calculation 

and in general are reasonably accurate. This is more a test of internal consistency 

than a demonstration of absolute accuracy. For example, PAN is problematic 

because it is ignored in (25), but as long as PAN is ignored in the CSS 

calculation (i.e.,, assumed to be in steady state), no errors are detected in the 

approximate formulas. Some of the formulas can (and should) be revised to 

include PAN. 

Formulas such as (30-32) for LN/Q depend on most of the substances measured. 

With only a little extra effort, a CSS calculation could be done, in which no 

approximations need be made. Therefore the usefulness of some of the 

approximate formulas is for the insight that they provide, rather than for specific 

quantitative results. Figure 4 shows an example of a LN/Q analysis from the 

original paper by Kleinman et al. (1997). 

It is important to note that relative changes in [NOx] and [VOC] always result in 

smaller relative changes of P(O3). 

Figure 4. Relative sensitivities of local ozone production as determined from measurements. 
LOOP Final Report 13

2.2 The dependence of ozone production on VOC 

reactivity and oxidation mechanisms 

Jens Hjorth 

Institute for Environment and Sustainability (IES), European Commission 

Joint Research Centre, Ispra, Italy 

2.2.1 Principles 

Nearly all VOCs can contribute to photo-oxidant production, but the impact of 

the individual species on ozone formation depends on their reactivity 

(particularly the rate coefficient for their reaction with OH radicals) and their 

atmospheric degradation mechanism. The contribution to ozone formation of a 

VOC emitted in a certain quantity at a certain place depends significantly on the 

ambient conditions (meteorology and concentrations of trace gases, particularly 

NOx), as well as on the time scale over which the build up of ozone is followed. 

The question of interest from an environmental point of view is, how much a 

certain reduction of the emission of individual VOCs will influence ozone levels 

on relevant scales. This kind of information is, obviously, one of the prerequisites 

for developing the most cost-efficient VOC-reduction policy, but it is not a trivial 

problem to make a definition of the 'ozone production efficiency' of VOCs. The 

simplest approach is to use the rate coefficient of the first step in the OH-initiated 

degradation mechanism 

RH OH ROO H2O O2    (R 9) 

as an indicator, because the peroxy radicals produced subsequently can 

contribute to the oxidation of NO and thus to the production of ozone: 

ROO  NO  RO  NO2

  (R 2) 

RO  O2  HO2  R'O  (R 13) 

HO2  NO  NO2  OH (R 1) 

3

O NO2  h 2 O (R 3) 

However, this approach does not take into account the successive steps in the 

degradation mechanism where other peroxy radicals are formed and it does not 

take into account that for the larger alkyl peroxy radicals the formation of organic 

nitrates becomes a significant pathway for the reaction with NO 

ROO  NO  RONO2

 (R 14) 

This pathway does not lead to formation of ozone but to radical loss. 

The most important recent approaches to a quantification of the relative 

capability of individual VOCs to form ozone are both based on simulations by 

photochemical models. One example is the 'Maximum Incremental Reactivity' 

(MIR) scale (Carter, 1995; Carter et al., 1995), another is the 'Photochemical 

Ozone Creation Potentials' (POCP) (Derwent et al., 1998). The MIR scale is 
14 Scientific Background 

based on an urban air quality model developed on the basis of smog chamber 

experiments. The POCP scale is based on a trajectory model at regional, 

European scale and uses the Master Chemical Mechanism. In both cases the 

increase of ozone due to an increase in the emission of a certain VOC is 

estimated under conditions with relatively high NOx levels, where ozone levels 

are most sensitive to VOC emissions. 

Some important mechanistic aspects that influence the ozone forming potential 

of a VOC are: 

 The number of NO to NO2 conversions caused immediately by the initial 

attack of OH on the compound. 

 The reactivity of the primary degradation products with respect to the OH 

radical. 

 Formation of reaction products that by their photolysis can provide additional 

significant radical sources ( e.g., formaldehyde, glyoxal). 

 The degree of radical (and NOx) sequestering/removal through formation of 

organic nitrates or PAN-type compounds. 

 There is a relation between NOx vs. VOC limitation of ozone production and 

the ozone forming potential of individual VOCs: 

In VOC limited situations, an increase in the concentration of peroxy radicals 

will efficiently enhance the formation rate of ozone since the reaction with NO is 

important because of the (relatively) high concentrations of NO. Thus the 

capability of a VOC to produce ozone by its atmospheric degradation will 

depend strongly on the number of peroxy radicals that it forms. NOx-limited 

situations are characterised by low levels of NO; thus the peroxy radical 

reactions competing with the one with NO become important and the number of 

peroxy radicals formed by the oxidation of a certain VOC species has less impact 

on the formation of ozone. On the other hand, the amount of NOx that is 

sequestered through formation of nitrates or PAN-type compounds becomes 

more important for ozone production when it is limited by the availability of 

NOx. 

One of the approaches that have been used within the present project, is to 

estimate radical concentrations and ozone production rates have been based on 

the measured concentrations of the stable species and assuming a steady state 

concentration for the (short-lived) radicals, as described in section 2.1.4. In this 

case, only the instant radical and ozone production is calculated and thus the 

effect of reaction products and NOx-removal are not relevant. Only the 

consequences of reaction mechanisms for the immediate production of radicals 

and ozone must be taken into account 

2.2.2 Hydroperoxides 

Hydroperoxides are formed in the atmosphere by reactions between peroxy 

radicals: 

2 2 2

M, H O HO2  HO2 2 H O  2O (R 11) 
LOOP Final Report 15

RO2  HO2  ROOH  2O2

 (R 12) 

These reactions of the peroxy radicals are, obviously, competing with their 

reaction with NO (eventually leading to formation of ozone). At very low NO 

concentrations the photochemical formation of ozone becomes slower than the 

destruction of ozone by its photolysis and its reactions with HO2 and OH: 

2 3 2 HO  O OH  2O (R 15) 

HO  O3  HO2  O2 (R 16) 

In this case, tropospheric photochemistry becomes a sink for ozone. 

Hydroperoxides are destroyed by the gas phase reaction with OH radicals and by 

photolysis, the latter leading to formation of OH radicals. They are also taken up 

by liquid water (clouds, fog); the uptake of H2O2 is particularly favoured and it is 

an important oxidising species in the tropospheric aqueous phase. 

Since the concentration of hydrogen peroxide in the troposphere appears to be 

largely determined by photochemical reactions and since the formation of this 

species, as explained above, is favoured under conditions where ozone 

production is NOx-limited, it is intuitively understandable, that [H2O2], ratioed to 

the concentrations of other species is one of the parameters that has been used for 

the calculation of the indicators for NOx- or VOC-sensitive conditions, discussed 

in section 2.3.2. 

2.2.3 Peroxyacetyl nitrate (PAN) 

Several reactions of NO or NO2 with radicals lead to the formation of stable, 

non-radical species, that thus represent a sink for radicals and NOx. However, to 

some extent all of these species can regenerate NOx and radicals by their 

subsequent degradation in the atmosphere. This is the case for the organic 

nitrates mentioned earlier, which can form NOx by their photolytical degradation. 

It is also the case for nitric acid, e.g., formed by the reaction of NO2 with OH 

3

M NO  OH HNO (R 10) 

Nitric acid may subsequently be photolysed to form OH radicals and NO2, 

however it is a highly soluble strong acid and it has a high dry deposition 

velocity, thus it is likely to be removed by wet or dry deposition processes. 

The most important among the NOx and radical 'reservoir' species appear to be 

the peroxyacetyl nitrates, among which peroxyacetyl nitrate (PAN) is the most 

abundant. These compounds, with the general structure RC(O)OONO2, are 

formed by the degradation of VOC in the presence of NO2, e.g., by the OHreaction with aldehydes: 

CH3CHO  OH CH3CO  H2O  (R 17) 

  CH3CO  O2 CH3C(O)OO (R 18) 

3 2

M CH3C(O)OO  NO2   CH C(O)OONO  (R 19) 

The peroxyacyl nitrates have been found to be much more abundant in the 

atmosphere than the simple alkyl nitrates. While pernitric acid and simple 
16 Scientific Background 

alkylperoxynitrates are too unstable to be relevant at standard conditions (but 

stable at lower temperatures) PAN-type compounds are reasonably stable also at 

typical ground level temperatures: at room temperature the lifetime of PAN is 

appr. 1 hour and it increases to more than 1 year at upper troposphere 

temperatures. PAN is a strong eye irritant and has been found to be phytotoxic. 

The formation of nitric acid and the formation of PAN are competing 

atmospheric sinks for NOx. A model study by Meng et al. (1997) suggests that 

the relative importance of PAN-formation decreases with decreasing VOClevels. The implication of this hypothesis is that a reduction of VOC can lead to 

formation of more HNO3 and consequently, if enough ammonia is available, of 

more ammonium nitrate, meaning more particulate matter. This is an aspect that 

may need to be taken into account when evaluating the costs and benefits of NOx

or VOC reductions. 

2.2.4 Ozonolysis of carbon double bonds 

Ozonolysis of olefinic VOC, c.f. (Kroll et al., 2001; Paulson and Orlando, 1996; 

Siese et al., 2001) constitute a source of OH and peroxy radicals. The reaction 

pathways and the yields of ODD-H radical formation is not yet “common 

knowledge” and is very differently treated in models. 

The formation of OH radicals by photolysis of alkenes has been observed by 

several research groups by different techniques and it seems now to be a wellestablished fact that OH radicals are formed in yields that range from appr. 0.1 in 

the case of ethene to about unity for highly branched alkenes (Finlayson-Pitts and 

Pitts, 2000). The reactions leading to their generation must follow the initial 

formation of a Crigee intermediate. In the case of substituted alkenes, the most 

likely mechanism goes via the formation of an excited unsaturated hydroperoxide 

and leads eventually to the formation of an OH and a RO2 radical, as shown in 

the example in Figure 5 (Gutbrod et al., 1996). It should be noticed, that any 

reaction of a Criegee intermediate leading to the formation of an OH radical must 

necessarily also lead to the formation of a second radical species which normally, 

upon reaction with O2, will form a peroxy radical. 

Figure 5. Mechanism for the formation of OH and peroxy radicals by the ozonolysis of a substituted 

alkene (Gutbrod et al., 1996). 

+ O3 O +

O

O

O

OH O

+ O2

+ OH

O

O

O

O

*

O

O

* *
LOOP Final Report 17

Paulson and Orlando (1996) estimated that the ozonolysis of alkenes constitutes 

the most important radical formation pathway in the urban air masses of Los 

Angeles. 

2.2.5 Radical measurements 

OH, HO2 and organic peroxy radicals have a key role in tropospheric 

photochemistry and their measurement provide a critical test of the performance 

of atmospheric chemical models. These measurements are difficult because of 

the low concentrations of these species (OH peak concentrations appear to be 

about 107

 molecules/cm3 while peak concentrations of the sum of peroxy 

radicals, HO2 and RO2 have been found to be about 109

 molecules/cm3) and 

require advanced measurement techniques. 

OH radicals have been measured by several methods, often based on optical 

techniques. Long path absorption spectroscopy has been applied with a DOAS 

(Differential Optical Absorption Spectroscopy) technique, using the absorption 

lines of OH around 308 nm (e.g., Dorn et al. 1995). Another important optical 

method used for measurements of OH is based on Laser Induced Fluorescence 

(LIF) measurements (e.g., Holland et al., 1995), particularly the FAGE 

(Fluorescence Assay with Gas Expansion) technique (e.g., Hard et al., 1995; 

Creasey et al., 1997). 

An interesting mass spectrometric technique for determination of OH radicals 

was developed by Eisele and Tanner (1991). The principle of this method is that 

the OH radicals in the sampled air react with 34SO2 to form isotopically labelled 

sulphuric acid, which subsequently is determined by chemical ionisation mass 

spectrometry. 

Different methods have been applied also for the measurement of peroxy 

radicals: HO2 has been measured by converting it to OH which then was detected 

by LIF (e.g., Hard et al., 1995; Creasey et al., 1997). Another, but. very different, 

spectroscopical method for measurement of peroxy radicals is MIESR (Matrix 

Isolation - Electron Spin Resonance) where radicals in air are sampled in a 

matrix at low temperature and subsequently analysed by electron spin resonance 

(ESR) spectroscopy (Mihelcic et al., 1993). This method allows to distinguish 

between HO2 and organic peroxy radicals (RO2). 

A popular and relatively inexpensive method for measurement of the sum of HO2

and RO2 is the chemical amplifier technique, often named PERCA (PEroxy 

Radical Chemical Amplifier). The principle of this method is that NO and CO 

are added to the sampled air, whereby the OH and HO2 radicals take part in a 

chain reaction that for each radical generates several molecules of NO2, which 

eventually is measured (e.g., Hastie et al., 1991; Clemitshaw et al., 1997). 

Organic RO2 are to a large extent converted to HO2 by their reaction with NO in 

air and the PERCA does thus also measure these radicals. OH radicals are 

measured by the instrument also, but its concentration can be considered to be 

negligible compared to that of the peroxy radicals. 

The principle of 'chemical amplification' is also used in a recently developed 

instrument, where SO2 and NO are added to the sampled air, which leads to a 
18 Scientific Background 

chain reaction, where each HO2 or RO2 radical produce a certain number of 

sulphuric acid molecules that finally is measured by chemical ionisation mass 

spectrometry. By adding different mixtures of nitrogen and oxygen to the 

sampled air, this technique allows to switch between measurement of HO2 only 

and of the sum of all peroxy radicals (Hanke et al., 2002). 

Calibration of radical measurements is a complicated issue. The technique that 

probably is most frequently applied is based on the photolysis of water in air to 

create OH and HO2 

radicals (Schultz et al., 1995). 

H2O + h H + OH (R 20) 

H + O2  HO2 (R 21) 

A more detailed discussion of radical measurement techniques can be found in 

the book by Finlayson-Pitts and Pitts, (2000). 
LOOP Final Report 19

2.3 From the local ozone production to the ozone 

concentration 

Christoph Spirig, Albrecht Neftel 

Swiss Federal Research Station for Agroecology and Agriculture, Zurich, Switzerland 

Sanford Sillman 

Department of Atmospheric, Oceanic and Space Sciences, University of Michigan, 

Ann Arbor, Michigan, USA 

2.3.1 Basic principles 

The ozone concentration at a given point in time and space is the result of the 

chemical and meteorological processes integrated over the lifetime of ozone. 

This lifetime is in the order of days and is determined mainly by deposition 

processes and chemical loss processes. 

 





0

3

3 dt

dt

d O O ( 33) 

The change of ozone concentration in an air parcel is given by: 

 d O

dt

PO LO O 3     33 3 ( ) ( 34) 

P(O3) : Chemical production 

L(O3): Chemical losses and deposition 

	(O3): Changes due to advection and mixing 

P(O3) and the NOx/VOC sensitivity derived from field measurements 

characterise the local P(O3). As stated above the ozone concentration itself is 

only marginally related to the local production at the same place. The integration 

back in time has to be done with numerical models in order to get a source - 

receptor relationship. 

A general feature of the chemical aging of an air mass with a high load of 

pollutants ( e.g., taken up over a large urban area) is demonstrated within Figure 

2. Air with fresh emissions very often starts in the high-NOx region (label 1). As 

the air mass travels downwind from an urban area to a region with lower 

emissions, dilution and chemical reactions reduce the precursor concentrations. 

NOx concentrations typically decrease more rapidly than VOC as the air mass 

ages, because NOx has a relatively short photochemical lifetime. Thus, the ratio 

of VOC to NOx increases as air masses age, and the air mass undergoes a 

transition from high-NOx to low-NOx chemistry (label 2). The process of 

transition is hastened if the downwind region includes high emission rates of 

biogenic VOC, which also shift the VOC-NOx ratio in the direction of low-NOx

chemistry (label 3). Individual situations vary greatly and there are many 
20 Scientific Background 

exceptions to this rule, but it frequently happens that air undergoes a transition 

from high-NOx to low-NOx chemistry as fresh emissions from an urban plume 

move downwind. Frequently an aged urban air mass will be recharged with 

emissions causing a flipping back from NOx sensitive to VOC sensitive ozone 

production as symbolised in Figure 6. This typical pattern of the VOC / NOx

sensitivity of the ozone production of an urban air mass transported into a region 

with lower emission densities is symbolized in the LOOP logo. 

Downtown Downwind:

Transition from VOC sensitivity (red) to NOx sensitivity (yellow)

Wind direction

Figure 6. Ozone production in city plumes and the LOOP logo. 

Box models are sufficient to describe and analyse the chemical production for an 

ideally mixed case, typically a smog chamber. Sensitivity studies with such 

models show the basic features of the non-linear dependence of P(O3) on NOx

and VOC concentrations. 1-D Lagrangian models are best suited for sensitivity 

studies in isolated air masses. 3-D models are needed to describe the spatial and 

temporal evolution of ozone and other photo-oxidants. The resolution of the 

chosen model must be adapted to the target that has to be investigated. The 

occurrence of a city plume is likely to occur on a relative small scale a few tens 

of kilometres, whereas the inflow conditions will depend on larger scale. Ideally 

grid nested models should be used that are capable of linking scales from 

thousands of kilometres down to 1 km. 

Observation based answers to emission control questions ideally should rely on 

simple approaches that can be based on routine data. A seminal contribution to 

this topic has been the idea to use indicators to distinguish between VOC and 

NOx sensitivity of the integrated O3 production (Milford et al., 1994; Sillman, 

1995a). 

2.3.2 Indicators 

Sillman (1995a) suggested that NOx-VOC sensitivity could be evaluated from 

measurements by using a series of "indicator ratios" which were linked to NOxVOC sensitivity in 3-D models. The species involved shared two characteristics: 

they were relatively long-lived, so that their concentrations provided evidence 

concerning the photochemical history of the air mass. The species were also 
LOOP Final Report 21

directly related to the chemistry of OH radicals that drives the separation into 

low-NOx and high-NOx regimes. In particular, they are related to the Ln/Q 

formula discussed above. In a ratio such as O3/NOy, the NOy is related to the rate 

of removal of NOx (Ln) over the history of the air mass, while O3 is related to the 

source of radicals (Q). These ratios thus provide an analogue to the formula for 

instantaneous ozone chemistry discussed above, but for ozone concentrations. 

The NOx-VOC indicators proposed by Sillman (1995a) included the following: 

O3/NOy (where NOy represents total reactive nitrogen); O3/NOz (where NOz

represents summed NOx reaction products, or NOy-NOx); O3/HNO3; H2O2/HNO3; 

H2O2/NOz; and the equivalent ratios with summed H2O2 and organic peroxides 

Figure 7 shows how the indicator ratios are related to O3-NOx-VOC sensitivity in 

3-D models. 

-60

-40

-20

0

20

40

60

0 5 10 15 20

O3/NOy

O3 reduction (ppb)

VOC controls

NOx controls

Figure 7. Predicted reduction in peak O3 (ppb) resulting from a 35% reduction in the emission rate for 

anthropogenic ROG (crosses) and from a 35% reduction in the emission rate for NOx (circles), plotted 

against predicted O3/NOy concurrent with the ozone peak, in simulations for Chicago/Lake Michigan. 

From Sillman (1995a). 

The figure (representing a model for the Chicago area in the U.S.) shows the 

predicted change in O3 resulting from a 35% decrease in region-wide VOC 

emissions and from a 35% decrease in NOx-emissions. Each point represents a 

different model location. In some of these locations, reduced VOC results in 

reduced O3, but reduced NOx results in either unchanged or increased O3 (highNOx chemistry). In other locations, reduced VOC has little impact on O3, but 

reduced NOx results in lower O3 (low-NOx region). The locations with predicted 

high-NOx chemistry almost always have predicted low values for the "indicator" 

ratio O3/NOy, while the locations with predicted low-NOx chemistry have 

predicted high values for the same ratio. Thus, measured values of the indicator 

ratios might be used as an indirect test of the accuracy of the model predictions 

concerning O3-NOx-VOC sensitivity. 
22 Scientific Background 

Previously Sillman (1995a) associated NOx-sensitive and VOC-sensitive 

conditions with high and low values of indicator ratios (O3/NOy, etc.) and 

identified transition values that separated NOx-sensitive and VOC-sensitive 

locations (O3/NOy=6-8, O3/NOz=8-10, O3/HNO3=12-15). A careful examination 

of Figure 8 shows that the NOx-VOC transition does not correspond exactly to 

these transition values. It can also be shown that the transition values of indicator 

ratios decrease with increasing O3. The change in indicator transition values is 

especially noticeable for O3 less than 80 ppb (with NOx-VOC transitions at 

O3/NOy=11-15, O3/NOz=15-20). For O3 greater than 100 ppb the NOx-VOC 

transition corresponds to the ratio values previously identified by Sillman 

(1995a). By contrast, NOx-VOC transition for ratios involving peroxides 

(H2O2/HNO3=0.2-0.3; total peroxides/HNO3=0.3-0.45) do not appear to vary for 

the range of clean and polluted conditions shown here. 

2.3.3 Discussion of indicators 

The NOx-VOC transition values for some indicator ratios can vary significantly. 

However, this does not appear to be just a random variation among different 

models or locations. Rather, it is part of a systematic variation from relatively 

clean to highly polluted conditions, which is imperfectly captured by the 

indicator ratios. This variation can be explained in terms of the radical chemistry 

that drives the split into NOx-sensitive and VOC-sensitive conditions. 

As was done in Sillman et al. (1998), the indicator results for individual 

simulations are summarised by recording the 5th, 50th and 95th percentile 

indicator values for NOx-sensitive and VOC-sensitive locations. A NOx-VOC 

indicator is successful if the 95th percentile value for VOC-sensitive locations is 

equal to or less than the 5th percentile value for NOx-sensitive locations, and if 

the transition values remain similar in models for different locations and 

assumptions. These 95th percentile and 5th percentile values identify the 

transition from NOx-sensitive to VOC-sensitive conditions. 
LOOP Final Report 23

2.4 Photo-oxidants and aerosols 

Jean-Philippe Putaud 

European Commission Joint Research Centre, Ispra, Italy 

Christoph Spirig 

Swiss Federal Research Station for Agroecology and Agriculture, Zurich, Switzerland 

A very large part (generally >40%, often more) of the fine aerosol mass consists 

of secondary components such as non sea salt sulphate (nssSO4

2-), nitrate (NO3-

) 

and a fraction of the particulate organic matter (POM). These components result 

from the oxidation of SO2, NO2 and certain VOCs by OH, O3, peroxides, etc.... 

Some of these reactions represent a sink of photo-oxidants. The formation of 

particulate NO3

-

 and the formation of secondary POM also represent a sink of 

NOx and VOCs, which are precursors of ozone. The net production of ozone and 

the formation of secondary aerosol are therefore intimately coupled (Figure 8). 

This leads to difficulties in conceiving efficient abatement strategies for both 

ozone and particulate matter (PM). 

OH

HO2

HNO3

NH3

POMNH4 NO3

NO h 2

O3

NO

condensable

products

VOCs

RCOO2

Other

volatile

products

PAN

Figure 8. Chemical coupling in the production of ozone and secondary aerosol. Some termination 

reactions in the ozone cycle lead to the production of particulate species. 

For instance, in a VOC rich area where the net production of ozone is limited by 

the availability of NOx, a reduction in NOx concentrations (to reduce O3 level) 

would leave more OH radicals available for the oxidation of VOCs, which might 

lead to an increase in secondary POM concentration. In contrast, in a NOx rich 

area, the reduction in VOC would be efficient to decrease ozone levels, but 
24 Scientific Background 

would favour the production of nitric acid (HNO3) and then the formation of 

NH4NO3 when enough ammonia (NH3) is available. 

2.4.1 Inorganic aerosols 

The inorganic fraction of the aerosol consists mainly of SO4

2-, NO3-

, NH4

+

, and 

often minor amounts of other ions and elements. These latter are primary aerosol 

components (sea spray, soil dust, etc...) whereas NssSO4

2-, NO3-

, and NH4

+

are 

secondary components, the precursors of which are the gaseous species SO2, NO2

and NH3, respectively. 

NssSO4

2- can be produced by the gas phase oxidation of SO2: 

SO2 + OH + (O2, H2O)  H2SO4 + HO2 (R 22) 

The lifetime of SO2 relative to this reaction is > a few days at typical atmospheric 

levels of OH. Sulphuric acid (H2SO4) reacts with NH3 to produce condensable 

NH4HSO4 and (NH4)2SO4 when enough NH3 is available. This mechanism can 

lead to the formation of new particles (nucleation process). 

However, a large fraction of nssSO4

2- is formed by oxidation of SO2 in cloud 

droplets or at the surface of pre-existing particles: 

(SO2 , H2O) + ROOH  SO4

2- +2 H+

 + ROH (R 23) 

(R = H or alkyl group) 

(SO2 , H2O) + O3  SO4

2- + 2 H+

 + O2 (R 24) 

These processes are generally more efficient than the gas phase oxidation. They 

lead to the growth of particles (when clouds evaporate in the case of cloud 

droplets) but not to the formation of new particles. 

HNO3 is formed according to the reaction: 

NO2 + OH + (M)  HNO3 + (M) (R 10) 

The lifetime of NO2 with respect to this reaction is about one day. HNO3 and 

NH3 are in equilibrium with the particulate compounds NH4NO3: 

HNO3 + NH3 
 NH4NO3 (R 25) 

The equilibrium constant depends on the temperature, the state of NH4NO3

(solid/liquid) and its concentration in solution when NO3

-

 and NH4

+

 are mixed 

with SO4

2- in the aqueous phase (Seinfeld and Pandis, 1998). NH4NO3 cannot 

exist in the particulate phase if the amount alkaline species is not sufficient to 

neutralise at least the first acidity of H2SO4. 

2.4.2 Secondary organic aerosols 

Particle measurements in both urban and rural areas have shown that a major 

fraction of particulate mass consists of organic matter. Both primary and 

secondary sources contribute to organic matter in aerosols. Numerous smog 

chamber studies have proven the potential of certain VOC to form particles 

(Forstner et al., 1997; Grosjean and Seinfeld, 1989; Hoffmann et al., 1997; Koch 

et al., 2000; Wang et al., 1992). 
LOOP Final Report 25

While the formation of new particles is still poorly understood, there is a 

framework of theory available for the transfer of gaseous organic compounds 

onto existing particles. In urban areas, this is expected to be the major pathway in 

terms of mass transfer from gaseous to particulate phase, as high aerosol surface 

areas suppress the formation of new particles (Aalto et al., 2001). 

Once VOC are released into the atmosphere, they react with oxidizing agents like 

OH, O3 or NO3. Some of the products formed in these reactions exhibit vapour 

pressures low enough so that they readily condense onto existing particles. 

Among the VOC found to be potentially important for secondary organic aerosol 

formation are compounds from both anthropogenic and biogenic origin: 

aromatics, alkanes, alkenes, and carbonyls from anthropogenic sources, while 

biogenic VOCs include organics such as mono- and sesquiterpenes as well as a 

series of oxygen-containing compounds. As the volatility of oxidation products is 

one of the most determining factors, a rule of thumb says that only hydrocarbons 

with more than six carbon atoms contribute to secondary organic aerosol under 

atmospheric conditions. Figure 9 shows the aerosol forming potential of selected 

VOCs, determined as the sum of their condensable oxidation products (Seinfeld 

and Pandis, 1998). 

0

200

400

600

800

1000

Cyclohexan

C11

Cycloparaffine

Isopren

Benzol

m/o-Xylen

1,3,5-

Trimethylbenzol

Nitrophenole

(gm-3 ppm-1)

Figure 9. Secondary organic aerosol yields of selected VOCs (Seinfeld and Pandis, 1998). 

The aerosol yield (Y) is a measure for the particle forming potential of a certain 

compound: 



















  



3

3

 [ ]

( )

gm

gm

VOC

M Aerosol Y



 ( 35) 

with DM: Organic aerosol mass produced 

 DVOC amount of VOC reacted 

As different experiments showed a big variety of aerosol yields for a certain 

compound it has been recognized that these yields cannot be constant, but rather 

depend on the properties of existing aerosol. Oxidation products partition into the 
26 Scientific Background 

organic fraction of the aerosol before they reach saturation vapour pressure. As a 

result, aerosol yields depend strongly on the organic aerosol mass. Partitioning 

models considering this dependency have been described by Pankow (1994) and 

Odum et al. (1996). 

In this framework the partitioning of each oxidation product is described by a 

partitioning coefficient (Ki) as 

0

i o O L,i

i

i MW p

RT

G M

A K

   ( 36) 

Ai concentration of product i in the absorbing organic aerosol phase 

Gi gas phase concentration of product i

Mo absorbing organic aerosol mass concentration with mean molecular weight MWO, 

R universal gas constant 

T temperature 

 activity coefficient of product i in the organic phase 

pL,i vapour pressure of product i as a pure liquid 

Partitioning coefficients therefore strongly depend on the liquid vapour pressure 

of the compound and on the organic aerosol mass. Experimentally found aerosol 

yields from various VOCs could be reasonably described with a model assuming 

two oxidation products: 





















  	

 

o o

o K M

K

K M

K M

VOC

A A Y

2

2 2

1

1 2 1 1

[ ] 1 1

  ( 37) 

where 1 and 2 are the mass-based stoichiometric coefficients for the reaction 

generating products 1 and 2 from the parent VOC. 

Figure 10 illustrates the dependency of aerosol yields on organic aerosol mass in 

the example of some aromatic compounds (Odum et al., 1997). 

0 40 80 120 160 200

Momg m-3)

0

2

4

6

8

10

12

Yield (%)

xylenes

toluene

ethyltoluene

ethylbenzene

1=0.038, 2=0.167

K1=0.042 , K2=0.0014

1=0.071, 2=0.138

K1=0.053 , K2=0.0019

Figure 10. Secondary organic aerosol yields of aromatics as a function of organic aerosol mass 

concentration. Curves are fits to data using the two-product model of equation (37) (Odum et al., 1997). 
LOOP Final Report 27

In the context of a project devoted to photo-oxidant production it should be noted 

that most VOCs of importance for secondary aerosol production exhibit higher 

aerosol yields through reaction with O3 as compared to their reaction with OH. It 

is therefore expected that regimes with high concentrations of photo-oxidants and 

VOCs effectively produce secondary organic aerosols. 
28 Scientific Background 

2.5 Performance of emission inventories – what can 

modellers expect? 

Wilfried Winiwarter 

ARC Seibersdorf Research, Seibersdorf, Austria 

2.5.1 Introduction 

Emission inventories traditionally have been created from a regulatory 

perspective. Available information was centrally collected, and attributed to 

certain grid cells or polygon areas. Requirements for emission inventories 

quickly increased. Some of these requirements could be settled by installing 

additional measurements. Especially as long as point source emissions accounted 

for the major part of total emissions, this approach proved very sensible. Later, 

the success of air pollution regulation decreased the contribution of large point 

sources. Minor sources relatively gained in importance. Small industry, traffic 

(despite the immense success of emission reductions by introducing catalytic 

converters in cars) and small-scale combustion processes as in domestic heating 

started to dominate the field. 

This small sketch shows that the technique in emission assessment has always 

lagged behind the actual situation. As soon as novel approaches have been 

implemented (in terms of additional measurements, in terms of improving 

emission factors), the emission situation itself also had changed due to new 

requirements and technologies. Moreover, it proved very difficult to retrospectively apply techniques that were developed for a certain situation. 

Still the regulatory approach made it possible to develop inventories, such that 

data were accessible as soon as atmospheric modellers required them. However, 

the focus on data quality was not fully identical. While a regulatory approach 

aimed at full assessment (“completeness”) of all sources, and on the possibility of 

assessing prescribed changes of emissions (“comparability”), an approach 

towards the “true value” (“accuracy”) only very recently has become an explicit 

aim of the regulatory type inventory (Lim et al., 1999). 

Consequently, emission data were never fully satisfactory for input to 

atmospheric modelling. Nevertheless they are still used because creating new 

emission inventories from scratch is a huge effort. In the following section, the 

possibilities and the limitations of emission inventories are discussed in some 

more detail, in order to limit frustrations and false expectations of atmospheric 

modellers. Potentials for improvements are also suggested. 

2.5.2 Steps of creating an emission inventories 

When creating an emission inventory, efforts are concentrated in obtaining as 

much information as possible within a limited time frame or project volume. The 

amount of work required is normally not defined, but depends – in addition to 

local circumstances of data availability – on the specific interrelation between a 
LOOP Final Report 29

contractor and a client. Only in few cases the exact extent of the emission 

inventory or the detailed parameters to be assessed are defined independently, 

and thus a quality criterion is defined beforehand. Such examples are the 

Austrian standard on emission inventories (ON, 2000), or the international 

activities on the European scale (CORINAIR: EEA, 2001) and on the global 

scale (UNFCCC / IPCC: Penman et al., 2000). The latter examples are on a 

country scale only, however. 

2.5.3 Types of input into emission inventories 

Emission inventories typically comprise information from a multitude of data 

sources. Best in quality are data based on operational emission measurements 

available from very large sources. Continuous measurements, as required in the 

regulatory process, provide a good temporal resolution, while the place of 

emissions likewise is well known. The only difficulty may lie in the accessibility 

of data: point source emission information may be considered confidential and 

thus not freely enter emission inventories. 

Next in quality are existing emission measurements for a specific emission 

source. Again, for certain industrial installations data from prescribed 

measurement programs may be obtained. Measurements usually tend to represent 

stable operation conditions of the respective installation. It is however well 

possible that emissions from instable conditions dominate. Additionally, the 

relation of emission measurements to the activity rates of parameters that are 

publicly available may be difficult. Such activity rates are required for the period 

of measurement in order to derive an emission factor, but then also for the time 

period that the emission inventory is valid for (usually a year). Emissions in this 

case, as generally, are calculated as the product of emission factor times activity 

rate (E = EF x A). 

Activity rates are usually statistical data or other forms of accessible quantitative 

information, for bottom-up inventories this may also include the results of 

specific counts as well as evaluation of questionnaires. 

In a still more general way, emission factors available from literature are applied 

to activity rates describing a specific emission source. It is evident that the 

appropriateness of an emission factor to a certain activity, as wells as the 

precision of this emission factor can be very different from case to case. The 

same is true for applicability and magnitude of activity rates. Consequently the 

quality of the resulting emission data depends on very subtle differences and 

variations of input choices. 

Many emission inventories, which are not required to undergo a standardized 

protocol of quality control, may consequently not fully reflect reality. There are 

too many possibilities to choose input data incorrectly. Still, such an inventory 

can provide very valuable information to establish a useful air quality program. 

The main requirement for an inventory to be valuable in this direction is 

consistency. Consistency is however not sufficient to provide externally useful 

emission data. Even standardized protocols do not guarantee a general validity of 

data, but at least they provide another important aspect, comparability. 
30 Scientific Background 

Comparable emission inventories allow for judging the same mistakes between 

different inventory regions or regimes. Emission inventories for use in air quality 

modelling however require high precision information, which only can be 

achieved when emissions are validated (see section 2.5.5 “methods for 

validation”). 

2.5.4 Disaggregation of emission inventories 

Certain input data to be used for the inventory may be available at a scale that is 

larger than the inventory scale itself. This may be in terms of spatial resolution as 

well as in temporal resolution. Examples are statistical information which may be 

available for an administrative unit rather than for the grid chosen to represent 

the inventory, or for a year rather than for the hourly information required by air 

quality models. 

The general way to resolve this kind of top-down information onto smaller units 

is to apply surrogate statistics. This information is available at the desired scale, 

and sufficiently related to the process or activity to be investigated. The most 

characteristic example for anthropogenic emissions is the population density, 

which is widely available at a very high resolution, much higher than common 

statistical information. Emissions calculated for a certain type of anthropogenic 

activity may consequently be distributed in space according to population. 

Similarly, parameters to adequately describe temporal behaviour may be derived. 

Temporal behaviour can mostly be described using three sets of cycles: a 

seasonal cycle, a weekly cycle and a diurnal cycle. It is interesting to note that 

these three cycles are applicable to anthropogenic emissions, while the weekly 

cycle is not relevant for natural emissions. 

Clearly, each step of disaggregation adds more uncertainty to the emission 

figures presented. Surrogate statistics are per se not activity statistics, and their 

applicability is limited. Even if such a disaggregation always may be considered 

an improvement over just applying an average value (which is the alternative), it 

may be misunderstood as the representation of a real value. 

This becomes extremely evident when the third application of disaggregation 

commonly used is discussed, the application of split data to total non-methane 

volatile organic compound (NMVOC) emissions. Generally, total NMVOC is 

measured using an apparatus consisting of a Flame Ionization Detector (FID) and 

a GC column which is flushed backwards after the methane peak passed. 

Consequently no information on the actual NMVOC species is available for the 

vast majority of emission measurements. Species information, which is required 

as an input to air chemistry, is available for a small set of data and for a specific 

area or region. A widely used set has been published for UK (Derwent et al., 

1996). Now there is no indication that solvents, processes, fuels, or even general 

temperature conditions in, say, Italy, are sufficiently similar to warrant using the 

same split. Even worse, there are data on the composition of a refinery plume 

indicating drastic variations within days in the plume of a single refinery (Sexton 

and Westberg, 1983). 
LOOP Final Report 31

Again, this indicates that, while performing a split into VOC species is easily 

possible, resulting numbers need to be treated with great care. Not many 

sensitivity studies are available that would allow to assess the results in terms of 

ozone chemistry when using alternate speciation sets. Instead, VOC splits are 

used as a fixed input parameter. These splits however rather represent an expert’s 

guess (or a model in terms of an expert system), and their ease in computation 

must not misinterpreted as a real result. Still, also in this case, a guessed VOC 

split will allow a far better representation than if no split at all were provided. 

2.5.5 Methods for validation 

In the development of emission inventories, only very recently quality 

considerations also have gained in weight. A number of approaches is available 

to assess and validate data quality of emission inventories. Not only the absolute 

magnitude of emissions may be validated, but methods have been developed that 

also allow to assess and compare the spatial variability of data sets. 

A detailed assessment of quality requirements in terms of urban emissions 

inventories has been developed by Sturm et al. (1999) in the framework of the 

EUROTRAC SATURN and GENEMIS subprojects with contributions for six 

different European cities. While developing the spreadsheets as shown in Figure 

11, information was also spread to the LOOP inventory community. The 

availability of all specific information required for the quality sheets was 

discussed and confirmed by all participating institutions. However, no 

completely filled sheet ever appeared. 

Figure 11. Quality assessment sheets for emission inventories. 

Element Parameters 

Emissions choice of

indicator

value of

indicator

(activity)

emission factor model structure surrogate for

spatial

disaggregation

surrogate for

temporal

disaggregation

choice of

VOC-split

Public power plants

District heating plants

Petroleum refining plants

Solid fuel transform. plants

......

Completeness analysis emission covered ?

(Y/N)

(If emission not covered: Comment why considered irrelevant)

Public power plants

District heating plants

Petroleum refining plants

Solid fuel transform. plants

......

Uncertainty applicability

of indicator

uncertainty of

indicator

(activity)

uncertainty of

emission factor

representativity

of emission

factor

model

structure

uncertainty of

spatial

disaggregation

uncertainty of

temporal

disaggregation

Public power plants

District heating plants

Petroleum refining plants

Solid fuel transform. plants

......

Element Approaches

Retrospective analysis relative contribution of

source groups

sensitivity analysis

(optional)

overall uncertainties

Validation (at least

one approach is

required)

Alternative emission

assessment

Emission trends vs.

ambient air concentration

trends

Flux estimations from

downwind

measurements

Atmospheric

models

Fingerprints and

receptor modelling
32 Scientific Background 

2.5.6 Recommendations and conclusions 

In a purely scientific context, the above-mentioned shortcomings of inventories 

call for an improvement of procedures. Especially, this needs to facilitate well 

documented updates, as soon as new information becomes available. However, 

emission data used for policy purposes can not easily be altered or adapted. They 

represent a precondition for negotiations, and even small changes may undermine 

the confidence in the inventory (also as the term "inventory" implies an actual 

counting). Also, the robustness of information and the reliability of the measures 

set upon may be more important to negotiation partners than the closeness to the 

real world - see the diverging concepts of "truth" set forth by different 

professions as discussed by Pulles (1999). Consequently, environment agencies 

are extremely reluctant to update their estimations. Moreover, an adaptation 

would require to also adjust a chain of other data (e.g., emissions form previous 

years), often causing efforts beyond the resources available. 

It poses a considerable challenge to atmospheric modellers to apply good 

emission data under these preconditions. The following procedures should 

however help doing so: 

 Select an emission database that fulfils as much of the requirements shown in 

Figure 11. Especially, validation of the inventory and verification through 

field data are extremely beneficial to the inventory. It cannot be expected that 

a full verification of the inventory is available, but quality assurance must be 

considered from the beginning. 

 Choose a local emissions expert. Many of the questions arising from 

applying an inventory can only be solved by the persons familiar with the 

instances in the respective area in their daily lives. Also, the availability of 

certain data is best assessed by people who are aware of local habits. 

 Assess the confidence range of emission information. This may require an 

outside expert, who again may need to contact the local emissions expert. 

Uncertainty or confidence ranges are often difficult to obtain. One reason is 

that the input data are of unknown quality, another is that the applicability of 

a certain emission calculation method, an emission factor or of a surrogate 

statistic is simply not known. Still, there always remain possibilities to 

estimate this. In contrast to models, emission inventories should be seen as 

open systems, where the influence of the respective data sources also needs 

to be considered. 

 Do a sensitivity analysis of model results. Those input parameters which 

severely affect the outcome of the model should be flagged and checked with 

double care. 

 Mark these inconsistencies and refer them back to the compiler of the 

inventory, and/or the local expert. In many cases there may be simple 

explanations, but experience shows that too often large discrepancies remain. 

This discussion should however bear in mind that the inventory relies on a 

substantial amount of external data, which do not allow further checks. 
LOOP Final Report 33

 An adaptation of the emission information according to model results should 

be avoided as much as possible. Only when considerable further evidence is 

available ( e.g., atmospheric measurements), the changes may be performed 

but need to be very well documented. Emission data should never be used to 

tune a model in order to fit the atmospheric concentration (unless a validated 

model is used for inverse modelling) 

While emission inventories are far from producing optimised results to 

atmospheric modellers, they still remain to be a very important source of 

information. As all purpose in atmospheric modelling is to improve the air 

quality, emission inventories are indispensable. They describe the main 

anthropogenic influence to the atmosphere, and consequently the only control to 

change air quality. Consequently, emission data are required for any attempt to 

design a reduction measure. Using the approach described above, the reliability 

of the model can be assessed in relation to the confidence in the inventory. This 

is what ultimately is needed when applying results of models to improve the air 

quality. 
3. Field Campaigns 

Activities within LOOP were centred on several field initiatives, each of them 

with its own characteristics and structure. BOCCALINO and SLOPE can be 

considered as “trigger initiatives” for LOOP. They are shortly described below 

before the actual LOOP projects are presented in more detail. 

3.1 BOCCALINO 

Albrecht Neftel 

Swiss Federal Research Station for Agroecology and Agriculture, Zurich, Switzerland 

The BOCCALINO (= Biogenic Organic Carbon Compounds as Leading 

Indicators of Non – H2O2 Peroxides) study was performed in July and August 

1994 in the southern part of Switzerland. The region is adjacent to the Po Valley 

and exhibits the highest ozone concentrations in Switzerland. 

The main results are summarised below: 

Elevated O3 concentrations are generally influenced by the “Milan urban 

plume” and often are accompanied by elevated SO2 concentrations 

An estimation of the isoprene emissions shows roughly a five times higher 

emission rate as predicted by the inventories used at that time. As 

consequence, isoprene dominates the VOC reactivity towards OH at the 

ground 

The dominant peroxide is H2O2. It accounts for 64% of the total mean 

peroxide concentrations. HMHP concentrations were below 0.3 ppbv. 

Maximum concentrations of 10 ppbv were measured for HCHO. It was 

estimated that isoprene oxidation accounts for 30% to 70% of the HCHO 

production. 

HONO concentrations were around 0.2 ppbv in the afternoon and cannot be 

explained by homogeneous gas phase photochemistry. The measured HONO 

concentration would account for about 30% of the radical production in air 

close to the ground. 

Comparison of radical production and NOx emissions show that the air 

masses are in the low NOx chemical regime. Those calculations are based on 

data that are not influenced by the plume. 

Indicators for NOx or VOC sensitivity calculated from the measurements 

from August 1994 show that reduction of NOx emissions would be most 

efficient in reducing O3 in the Ticino region. 

Detailed results are described in Prévôt et al. (1997), Staffelbach and Neftel 

(1996a,b), Staffelbach and Neftel (1997) and Staffelbach et al. (1997a,b). 
36 Field Campaigns 

3.2 SLOPE 

Andreas Volz-Thomas 

FZJ Research Center Jülich, Institut für Chemie und Dynamik der Geosphäre; 

IUP, Germany 

SLOPE (Schauinsland Ozone Precursor Experiment) was conducted in 1996 and 

aimed at studying the chemical and physical development of the plume of the 

city of Freiburg during transport to the TOR station Schauinsland. The 

experiment was designed in a semi-Lagrangian fashion, by using the valley that 

descends from Schauinsland towards Freiburg as a flow reactor. A large suite of 

chemical species and meteorological parameters was measured at Schauinsland 

and at the entrance to the valley. Transport path and time, as well as the mixing 

with air from aloft were constrained by a dispersion experiment with SF6. 

Several tethered balloons, LIDAR and SODAR systems were distributed in the 

valley in order to provide information on the vertical structure of and a small 

research aircraft provided detailed information on VOCs and NOx within the 

valley and on the residual layer above. The setting of SLOPE was based on the 

experience gained in an earlier experiment with much simpler logistics that was 

conducted in 1992 as part of TOR and TRACT. 

The major scientific findings of SLOPE are: 

Given the large prevailing NO2 mixing ratios (between 3 and 15 ppb), a 

relatively large OH concentration of (72)x106

 cm-3 was estimated from 

the degradation of reactive hydrocarbons in the plume of Freiburg during 

transport to Schauinsland. The thus derived OH concentration was almost 

a factor of two larger than what was calculated with a chemical box model 

(EURO-RADM) constraint by the measured trace gas concentrations and 

photolysis rates. The conclusion was that current model results on the 

basis of RADM2, which is quite similar to EURO-RADM, would tend to 

under predict OH radical concentrations and, hence, the ozone formation 

rate in polluted air masses. 

It was possible to close the radical budget within the experimental 

uncertainties, when an upper limit was adopted for the radical production 

from photolysis of nitrous acid, in addition to that from photolysis of 

ozone and carbonyl compounds as well as ozonolysis of unsaturated 

VOCs. 

From the ground based VOC measurements (C2-C15), it was found that the 

total VOC concentration was dominated by anthropogenic hydrocarbons 

(alkanes and aromatics). The contribution of biogenic VOCs to the total 

VOC reactivity (VOCi]·kOHi), however was already about 30% in the 

polluted air masses at the entrance to the valley and about 70% at 

Schauinsland. 
LOOP Final Report 37

The results of SLOPE basically confirmed the conclusions from an earlier 

experiment made during the TRACT campaign in 1992 at the same 

location. 

Detailed findings are described in Fiedler et al. (2000), Kalthoff et al. (2000), 

Kramp and Volz-Thomas (1997), Pätz et al. (2000), Volz-Thomas and 

Kolaghar (2000), Volz-Thomas et al.((2000). 
38 Field Campaigns 

3.3 BERLIOZ 

Andreas Volz-Thomas 

FZJ Research Center Jülich, Institut für Chemie und Dynamik der Geosphäre; IUP, 

Germany 

The Berlin Ozone Experiment (BERLIOZ) was conducted as part of the German 

Tropospheric Research Focus (TFS) between July 5 and August 7, 1998 near the 

city of Berlin. 

The overall aim was to analyse the transport and chemical processes responsible 

for photo-oxidant formation and the contribution of groups of precursor 

substances to the ozone formation in the Berlin area. For this purpose, speciated 

hydrocarbons and carbonyl compounds, O3, PAN, NO, NO2, HNO2, HNO3, and 

NO3 radicals (e.g., JNO2 and JO1

D) were measured at different ground based sites 

by in situ techniques, along with measurements of meteorological parameters and 

photolysis frequencies. A map of the area around Berlin with the BERLIOZ sites 

is shown in Figure 12. The sites had been lined up along an axis extending from 

ca. 70 km south-east to 80 km north-west of Berlin, according to the predicted 

main wind direction during episodes with large photochemical activity. In 

addition to the surface sites, which were operational during the whole BERLIOZ 

period, 6 ozone LIDAR systems, 5 tethered balloons and 6 aircraft were 

deployed during intensive operational periods (IOPs). Some of the ground based 

measurements, i.e., carbonyl compounds, carboxylic acids, and the 

measurements of peroxy radicals by MIESR (see below) were also confined to 

the IOPs. 

The Photochemistry Experiment in BERLIOZ (PHOEBE), which was conducted 

at Pabstthum, about 50 km NW of Berlin, aimed at a quantitative understanding 

of the fast radical chemistry in rural and suburban air by simultaneous 

measurements of the major free radicals (OH, HO2, RO2, NO3) and the chemical 

compounds and physical parameters that control the radical concentrations (NO, 

NO2, NOy, non-soluble NOy, PAN, hydrocarbons and oxygenated organic 

compounds, peroxides, ozone, CO, photolysis frequencies and meteorological 

parameters). Interpretation of the measurements involved models of different 

complexity. 

Specific questions addressed by PHOEBE were: 

How do the concentrations of free radicals depend on the primary 

production, i.e., JO1

D, and on the concentrations of, e.g., NOx, VOC? 

What is the influence of other sources (e.g., HONO photolysis, ozonolysis) 

on the radical concentrations? 

How well do state of the art photochemical models reproduce the measured 

radical concentrations? 

Is the photo-stationary state (PSS) approach (see section 2.1.5) a suitable tool 

to determine the local ozone production rate PO3? 
LOOP Final Report 39

What are the main sources of free radicals at night and how large is the 

influence of NO3 radicals on the oxidation capacity of the atmosphere? 

Figure 12. Map of the area around Berlin with the surface sites of BERLIOZ indicated by the red dots 

and the airfield Schönhagen by the yellow dot. The red lines denote motorways and major roads. 

The methods deployed in BERLIOZ and the results are discussed in a special 

section in J. Atmos. Chem. 42, 2002, (Corsmeier et al., 2002; Junkermann et al., 

2002; Moortgat et al., 2002; Platt et al., 2002; Winkler et al., 2002). The 

scientific results from PHOEBE are published as a separate special section in 

J. Geophys. Res. and are summarised in the following. 

3.3.1 Scientific background 

The transition region between urban and rural areas is important in understanding 

the fast photo-chemistry that leads to the build up of high concentrations of 

ozone and other photo-oxidants during so-called summer smog episodes. As is 

schematically outlined in reactions R26 to R30, hydrocarbon oxidation by 

hydroxyl radicals (OH) leads to formation of peroxy radicals (RO2 and HO2), 

which oxidise NO to NO2, thereby regenerating the OH. Photolysis of the NO2

then generates the oxygen atoms required to produce ozone (Chameides and 

Walker, 1973; Crutzen, 1979). In this simplified view, the net effect of the 

radical chain in the presence of sufficient NO is that hydrocarbons are oxidised to 
40 Field Campaigns 

carbonyl compounds (CARB, i.e., aldehydes and ketones) and O3, c.f. 

(Chameides et al., 1992). 

R-H + OH + O2 (+ M)  RO2 + H2O (+ M) (R 26) 

RO2 + NO  RO + NO2 (R 27) 

RO + O2  HO2 + CARB (R 28) 

HO2 + NO  OH + NO2 (R 29) 

(2x)NO2 + h + O2 (+ M)  NO + O3 (+ M) < 420nm (R 30)

net: R-H + 3 O2 + h  CARB + 2 O3 + H2O 

Additional HO2 is produced from the oxidation of CO: 

CO + OH + O2 (+M) CO2 + HO2 (+M) (R 31) 

Production of OH radicals in the troposphere occurs mainly via photolysis of O3

(R32 and R33) (Levy, 1971) 

O3 + h  O1

D + O2  < 340nm (R 32) 

O1

D + H2O  2 OH (R 33) 

Another potentially important source for OH, particularly in polluted air, is the 

photolysis of HONO which is formed either in the tail pipe of motor vehicles 

(Kessler and Platt, 1984) or upon emission in the atmosphere via heterogeneous 

reactions (Stockwell and Calvert, 1983). 

HONO + h  OH + NO  < 405nm (R 34) 

Since R34 occurs at much longer wavelengths than R33, it can produce OH 

during the early morning, when R33 is still rather ineffective. Thereby, HONO 

photolysis is thought to provide an important trigger for photochemical smog 

formation in the urban and sub-urban environment (Calvert et al., 1994; Harris et 

al., 1982; Harrison et al., 1996; Jenkin et al., 1988; Platt, 1986; Volz-Thomas 

and Kolahgar, 2000). Other sources of OH and peroxy radicals include the 

ozonolysis of olefinic VOC, c.f. (Kroll et al., 2001; Paulson and Orlando, 1996; 

Siese et al., 2001), and the reaction of NO3 radicals with organic compounds at 

night (Carslaw et al., 1997; Mihelcic et al., 1993; Platt and Volz-Thomas, 2000; 

Salisbury et al., 2001; Wayne et al., 1991). 

During daytime, the concentration of OH and the production rate of ozone both 

depend on the UV-flux (i.e., on the photolysis frequencies JO1

D, JNO2, JHONO, 

JHCHO,...) and on the concentrations of H2O, O3, CO, NOx and VOCs. The role of 

NOx in the budgets of HOx (OH and HO2) and ozone is ambivalent: At low NOx

concentrations, where recombination reactions of the peroxy radicals (R35 + 

R36) constitute the major radical loss, NO controls the recycling of HOx and is 

the rate limiting factor in ozone production (Crutzen, 1979). 

HO2 + HO2 + M  H2O2 + M (R 35) 

HO2 + RO2 + M  ROOH + M (R 36) 
LOOP Final Report 41

At high NOx levels, radical losses by recombination of peroxy radicals become 

insignificant and HO2 is almost completely recycled to OH in reaction R29. Due 

to photolysis of the carbonyl compounds formed in reaction R28, more radicals 

can be produced from the hydrocarbon oxidation mechanism than are initially 

consumed in R26, depending on the VOC to NOx ratio and VOC reactivity 

(Jeffries and Tonnesen, 1994). 

CARB + h  HO2 + ....... (R 37) 

This effect is counteracted by the reaction of OH with NO2, which becomes the 

predominant sink of HOx in the high-NOx regime and thus effectively limits the 

production of RO2 and HO2. 

NO2 + OH + M  HNO3 + M (R 38) 

The net effect of NOx on the radical balance and ozone formation depends on the 

NO/NO2 ratio, which is controlled by the photolysis rate of NO2 (R30) and by the 

concentrations of peroxy radicals and O3 via reactions (R27, R29, and R39). 

NO2 + O3  NO + O2 (R 39) 

The radical chemistry in the high-NOx regime is further complicated by the 

photolysis of HONO (R34). Another complication in the understanding of the 

radical budget is the formation of alkyl nitrates and peroxyacyl nitrates, e.g., 

PAN. Alkyl nitrates are formed as by-products in R27. The branching ratios tend 

to increase with the size of the organic rest and are higher for secondary and 

tertiary RO2 (Atkinson et al., 1982; Atkinson et al., 1984; Atkinson et al., 1987; 

Atkinson et al., 1983; Becker and Wirtz, 1989). The net effect is a decrease in the 

local ozone formation rate. Similarly, the production of peroxyacteyl nitrate 

(PAN) and its homologues by reaction of acylperoxy radicals with NO2 (R40) 

removes peroxy radicals and NOx from the active pool. Thermal decomposition 

of the PAN compounds establishes equilibrium, but the net effect on the local 

radical balance depends on temperature and history of the air mass. 

R-C(O)-OO + NO2 + M 	 R-C(O)-OO-NO2 + M) (R 40) 

Because of their short chemical lifetimes, free radicals (OH, HO2 and RO2) are 

largely de-coupled from transport processes and can thus be investigated with 

zero dimensional chemistry models, provided that the chemical and physical 

parameters which control the local radical concentration, e.g., UV radiation, NOx

and VOC, are quantified. This is strictly the case only if the radicals and other 

parameters are measured with a time resolution given by the atmospheric 

lifetimes of the radicals, e.g., between less than one second for OH and a few 

seconds to minutes for the peroxy radicals. Until now this is an unsolved 

challenge for many atmospheric trace gases, in particular for hydrocarbons which 

in urban air can constitute of more than 100 different compounds (Ciccioli et al., 

1992). The interpretation of the radical measurements thus relies on assumptions 

about stationarity and homogeneity of the investigated air masses. These 

conditions are best achieved if the measurements are made at sufficient distance 

from sources or sinks and if the different measurements are made as close 

together as possible. 
42 Field Campaigns 

The fast photochemistry of the troposphere has been investigated by 

measurements of the concentrations of the free radicals (OH, HO2, RO2) and of 

those chemical and physical parameters that are thought to control the radical 

concentrations. Besides airborne missions in the free troposphere (Brune et al., 

1998; Mauldin III et al., 1998; Wennberg et al., 1998), a strong emphasis has 

been on ground based studies, mostly in the planetary boundary-layer (PBL), c.f., 

(Armerding et al., 1997; Brandenburger et al., 1998; Brauers et al., 2001; 

Cantrell et al., 1997; Cantrell et al., 1996; Carpenter et al., 1997; Carroll et al., 

2001; Carslaw et al., 1999; Ehhalt, 1999; Eisele et al., 1994; Eisele et al., 1997; 

Eisele et al., 1996; Hauglustaine et al., 1999; Holland et al., 1998; Jefferson et 

al., 1998; Kanaya et al., 2000; Kanaya et al., 1999; McKeen et al., 1997; Mount 

and Williams, 1997; Penkett et al., 1997; Perner et al., 1987; Platt et al., 1988; 

Poppe et al., 1994; Savage et al., 2001; Volz-Thomas and Kolahgar, 2000). 

These field experiments qualitatively confirmed fundamental aspects of the free 

radical chemistry, such as the principal dependencies of OH on the ozone 

photolysis frequency JO1

D and the concentration of NOx. 

There is a general tendency of photochemical models to overestimate OH and 

peroxy radicals. Exceptions are, e.g., the ALBATROSS, POPCORN, and 

SCATE campaigns, and the MLOPEX-2 campaign in spring, where modelled 

and measured OH were found to agree within the experimental uncertainties for 

clean air conditions (Brauers et al., 2001; Ehhalt, 1999; Eisele et al., 1996; 

Jefferson et al., 1998), and some campaigns conducted in forested areas (e.g., 

AEROBIC, PROPHET, and SLOPE) where OH was found to be significantly 

underestimated by the models (Carslaw et al., 2001; Creasey et al., 2001; Tan et 

al., 2001; Volz-Thomas and Kolahgar, 2000). It is also noted that in some of the 

earlier studies, the comparison was somewhat limited by the lack of 

measurements for several trace gases that are of importance to OH formation or 

loss, e.g., part of the VOC. Very little information exists so far on the behaviour 

of OH radicals in highly polluted atmospheres, except of the LAFRE campaign 

(George et al., 1999). 

3.3.2 Experimental 

The PHOEBE site (12°56'25" E, 52°51'15" N, 50 m above sea level) was 

established about 400 m east of the small village Pabstthum at the western border 

of a flat grassland of 7.5 x 4.5 km2 extension (Figure 13). Selection criteria were 

the distance from Berlin in order to obtain a good representation of the plume 

development in conjunction with the other BERLIOZ sites (see Figure 12), as 

well as the absence of local anthropogenic sources, reasonably flat terrain with 

unrestricted flow from the direction of Berlin, and logistical requirements such as 

electrical power and road access for supplying liquid nitrogen and gases. 

The area around Pabstthum, which itself consists of only 5 residences, is 

extremely sparsely populated. Local emissions from traffic, industry and 

residences in the vicinity of Pabstthum are negligible, except for the motorway 

A24 in the west about 10 km away. The nearest villages Wall and Radensleben 

located about 5 km and 7 km to the south east and north west, respectively, have 

less than 500 inhabitants. The closest city is Neuruppin, 12 km in the north west, 
LOOP Final Report 43

with 38000 inhabitants. Berlin (3.4 million inhabitants) is located in south 

easterly direction (140°) at a distance of about 50 km (city centre). A mixed 

forest dominated by Scots pine (pinus sylvestris) extends from the station in 

westerly and northerly direction. About fifty meters in westerly direction of the 

station is a line of Holm oaks (quercus ilex) along the trail to the site. The grass 

land is used for cattle farming, except for an area of about 100 m in westerly 

direction which was kept clear during the campaign. 

Figure 13. Location of the PHOEBE observational site at Pabstthum. Forested areas are shown in green 

colour. 

The instrumentation deployed at Pabstthum is summarised in Table 4 together 

with information on the time resolution of the measurements and the responsible 

institutions. More detailed information is found in the special section PHOEBE. 

In order to keep the influence of local surface emissions and deposition at a 

minimum, the instruments were placed as close together as possible at a height of 

approximately 10m (Figure 14). 

The instruments for odd nitrogen compounds, O3, CO, PAN, HCHO and 

speciated hydrocarbons were housed inside an air conditioned mobile laboratory. 

The inlets were mounted 10-11 m above ground on a pneumatic mast which also 

carried a photometer for the measurement of JNO2. The gold converter for NOy

was mounted directly at the inlet. Details are given in Konrad et al. (2003) and 

Volz-Thomas et al. (2002). Air temperature, wind direction and wind speed were 

also measured at 11 m height on the same mast. 

The cryogenic sampler of the MIESR (Matrix Isolation ESR-spectroscopy) was 

also operated on a pneumatic mast, 11 m above ground, about 10 m north east of 

the mobile laboratory. The samples were collected over 30 min intervals and 

analysed after the campaign at the laboratory in Jülich (Mihelcic et al., 2003). 
44 Field Campaigns 

The LIF (Laser Induced Resonance Fluorescence) instrument for the 

measurement of OH and HO2 radicals was mounted inside a laboratory container 

which was placed on a 5 m high scaffolding platform. The inlet of the LIF 

instrument was 10 m above ground. Measurements of photolysis frequencies 

were made on the LIF container using a scanning spectral radiometer and two 

filter radiometers (JNO2 and JO1

D). Another container on the platform housed the 

sampling devices for the measurement of peroxides, carbonyl compounds and 

carboxylic acids (Großmann et al., 2003) and a chemical amplifier for the 

measurement of peroxy radicals, i.e., the sum of HO2 and RO2 (Volz-Thomas et 

al., 2002). 

Figure 14. The PHOEBE site viewed from east. 

A DOAS (Differential Optical Absorption Spectroscopy) system for the 

measurement of NO2, NO3, O3, HCHO and SO2 was also mounted on the 

platform. It had a folded light path of a total length of more than 2 km (Alicke et 

al., 2003). A second DOAS system for the measurement of NO3, NO2, HONO, 

HCHO, SO2, O3, and aromatic VOC pointed in easterly direction from a height 

of 1.5 m at the station to a retro-reflector mounted 36 m above the ground at a 

distance of 6.3 km (Geyer et al., 2003). 

Vertical soundings of O3, NOx, and meteorological parameters were conducted 

with a tethered balloon. A second tethered balloon carried four automatic 

sampling units for hydrocarbons (Glaser et al., 2003). 
LOOP Final Report 45

Table 4. Instrumentation deployed at Pabstthum. 

Parameter Instrument Timeres. Inst. Ref. 

Odd nitrogen compounds 

NO Chemiluminescence (770 Alppt, EcoPhysics) 1 min FZJ A 

NOx CLD 770 Alppt + PLC 760 (EcoPhysics) 1 min FZJ A 

NO2 Differential optical absorption spectroscopy (DOAS 1 and 2) 30 min IUP F 

NO2 

*

 Matrix isolation and ESR-spectroscopy (MIESR) 30 min FZJ C 

NOy CLD 770 ALppt + Au-converter 1 min FZJ A 

NOy-HNO3 CLD 770 ALppt + Au-converter + Denuder 1 min FZJ A 

HNO2 DOAS 1 30 min IUP F 

PAN GC-ECD (Meteorologieconsult) 6 min FZJ A 

Other

O3 DOAS 30 min IUP F 

O3 UV-Absorption (TE-49) 1 min FZJ A 

H2O2, ROOH Enzyme catalysed fluorescence 23 min MPI E 

CO IR-Absorption (TE-48) 1 min FZJ A 

CN Condensation Nuclei Counter (TSI) 1 min FZJ A 

SO2 DOAS 30 min IUP F 

Organic compounds 

NMHC: C5 – C10 In situ-GC (Airmotec HC1010) 20 min FZJ B 

NMHC: C2 – C10 In situ-GC (HPGC/Cryogenic sampling) 85 min FZJ B 

H2CO Fluorescence (AeroLaser, AL4001) 1 min FZJ A 

H2CO DOAS 30 min IUP F 

Carbonyl comp. * Derivatisation, GC/ECD 1 h TUD E 

Carboxylic acids*

 Capillary Electrophoresis-LIF 1 h TUD E 

Aromatics, Phenols DOAS 30 min IUP F 

Free Radicals 

OH Laser induced fluorescence (LIF) 90 s FZJ D 

HO2 LIF 90 s FZJ D 

HO2

*

 MIESR 30 min FZJ C 

RO2

*

 MIESR 30 min FZJ C 

ROx (HO2+RO2) Chemical Amplifier (CA) 72 s MPI-C A 

NO3 DOAS 30 min IUP G 

NO3

*

 MIESR 30 min FZJ C 

Meteorology and Radiation 

T, rH, P, wind vector Psychrometer, wind vane, cup anemometer (Thiess) 1 min FZJ A 

Global radiation Pyranometer (Kipp&Zonen) 1 min FZJ A 

JO1

D, JNO2 2 sr Filter radiometers 10 s FZJ D 

JNO3 2 sr Filter radiometer 10 s IUP G 

Ji,j (actinic flux) 2 sr spectral radiometer (Bentham) 90 s FZJ D 

Vertical Profiles (tethered balloon) 

O3 Chemiluminescence (GFAS, OS-B-2) 10 s IVD H 

NO2 and NOx Luminol chemiluminescence (Scintrex, LMA-4) 10 s IVD H 

NMHC Adsorption tubes, GC/FID 3 h IVD H 

T, rH, P, wind vector Meteorological Sonde (Atmos. Instr. Res. Inc.) 10 s IVD H 

A: (Volz-Thomas et al., 2002), B: (Konrad et al., 2003), C: (Mihelcic et al., 2003), D: (Holland et al., 2003), E: 

(Großmann et al., 2003), F: (Alicke et al., 2003), G: (Geyer et al., 1999; 2003), H: (Glaser et al., 2003). 

FZJ:Research Center Jülich, Institut für Chemie und Dynamik der Geosphäre; IUP: University of Heidelberg, Institut 

für Umweltphysik; IVD: University of Stuttgart, Institut für Dampfkesselwesen; MPI-C: Max Planck Institute for 

Chemistry, Mainz; TUD: Technical University of Darmstadt, Institut für Chemie 
46 Field Campaigns 

The site was in operation from July 13th to August 8th. Most of the continuous in 

situ measurements, including DOAS, LIF and the GCs, were conducted over the 

entire period and were interrupted only for calibration and maintenance, or 

during rain fall. The vertical soundings and some other experiments 

(i.e., MIESR, peroxides, carbonyl compounds and carboxylic acids) were 

concentrated on the intensive observational periods (IOPs) on July 20th - 21st and 

August 4th - 5th. 

3.3.3 Meteorological situation 

The meteorological situation during BERLIOZ was dominated by a westerly 

monsoon regime, which lasted unusually long. Winds between 180° and 360° 

prevailed more than 80% of the time. The city plume of Berlin with was only 

observed on a few occasions, i.e., on July 20, 21and 23. 

On July 20, surface wind at Pabstthum (10 m above ground) was calm during the 

night, increased after sunrise, and turned to south-easterly directions between 5 

and 5:30 UTC. During the day the wind direction remained at about 160 degrees 

until 18 UTC allowing the advection of air from the south-western part of the 

greater Berlin area. 

Local profiles of potential temperature at Pabstthum (Glaser et al., 2003) and the 

analysis of aircraft data (Corsmeier et al., 2002) for the entire BERLIOZ area 

showed the vertical development of the mixing layer from < 100 m in the early 

morning to 900 m at 12 UTC. South easterly winds directions prevailed in the 

boundary layer with a sharp transition to south westerly winds aloft. In the late 

afternoon, the vertical extent of the southerly wind regime decreased again to 

approx. 1 km around 18 UTC. In the evening, the westerly wind regime 

proceeded downwards by the combined action of the diurnal change in the heat 

balance and the shear induced turbulence at the top of the PBL. Due to the latter, 

transport conditions were not as well defined as intended for the BERLIOZ 

experiment. 

Advection of warm air ahead of a low pressure system that moved slowly northeast ward from Scotland lead to temperatures well above 30 0

C in Berlin on the 

21st. Starting sunny in the morning, clouds developed during the day while a 

frontal system that had originated in the morning west of Berlin moved eastward 

creating some precipitation in isolated showers and thunderstorms. Ahead of the 

convergence the wind direction turned towards south-east. During the day the 

winds moved on to westerly directions just behind the frontal system bringing in 

slightly dryer and colder air masses than before. The wind speed was generally 

lower than on 20th and decreased further except for some isolated gusts in the 

greater Berlin area. At Pabstthum, wind from south east was observed shortly 

after 6 UTC for about two hours. After 8 UTC, the wind turned to south west and 

west throughout the whole boundary layer. Wind speed at the surface was low 

with 2-4 m/s. In contrast wind speeds at 200 m above ground were much higher 

reaching more than 10 m/s. A mixing layer depth of only 200 m was observed in 

the morning increasing to about 500 m at 12 UTC (Glaser et al., 2003). 

Cloudiness increased after 11 UTC diminishing gradually the insolation. 
LOOP Final Report 47

3.3.4 Data quality and instrument comparisons 

Quality assurance was a major focus in TFS. Photolysis frequency instruments, 

which participated in BERLIOZ, were compared in advance against reference 

techniques during the field experiment JCOM97 in summer 1997 at Jülich (Kraus 

et al., 2000). Most other in situ instruments (VOC, NOx, CO, O3, PAN, HCHO) 

were brought together one week before the campaign at the airfield Schönhagen, 

where the measurements of all participants were formally calibrated against 

certified standards and compared to reference instruments in ambient air (Kanter 

et al., 2002; Volz-Thomas et al., 2002). Besides putting all the different 

measurements deployed in BERLIOZ on the same level of known data quality, 

these activities also helped to improve the data quality in the other European 

experiments in which several groups participated. This concerns in particular the 

instrumentation aboard the MetAir aircraft, which participated in most of the 

LOOP campaigns (SLOPE, PIPAPO, BERLIOZ and ESQUIF), was successfully 

quality assured during the TFS QA activities. 

Additional instrument comparisons were made at Pabstthum where most of the 

free radicals (HO2, HO2+RO2, NO3) and longer lived compounds (O3, NOx, 

HCHO) were measured with more than one technique (Geyer et al., 1999; Platt et 

al., 2002; Volz-Thomas et al., 2002). 

3.3.4.1 Radical measurements 

Hydroxyl and hydroperoxy radicals were measured at Pabstthum by laserinduced fluorescence (LIF) (Holland et al., 2003). The 2
-calibration error was 

estimated to 20% for both OH and HO2. The LIF instrument was previously 

found to be in good agreement for OH with an absolute laser-absorption 

spectrometer (DOAS) (Hofzumahaus et al., 1998). On 20-21 July, HO2 was also 

measured by MIESR, an absolute technique with an estimated accuracy of 5% 

(Mihelcic et al., 2003). The correlation of the temporally overlapping 

measurements was linear (R2

=0.88) and showed a good agreement with a slope 

of 1.03, well within the combined uncertainty of both instruments (Platt et al., 

2002). 

The MIESR also provided measurements of the organic peroxy-radicals 

(CH3COO2, and the sum of all other RO2) and of NO3 (Mihelcic et al., 2003). In 

addition, the sum of all peroxy-radicals (HO2 + RO2) was measured with a 

chemical amplifier with a calibration uncertainty of 20% (Volz-Thomas et al., 

2002). The comparison of both techniques showed good agreement, the chemical 

amplifier data being about 7% lower than the MIESR measurements, again well 

within the estimated calibration errors. 

Simultaneous NO3 measurements were achieved in the night of August 4 to 5 by 

MIESR and a DOAS instrument, which was operated with a single-folded lightpath over a distance of 6.3 km. Despite of relatively low concentrations, the 

comparison of the DOAS and MIESR data sets showed a tight linear correlation 

(R2

=0.98). The systematic deviation of 17% was within the combined systematic 

errors of both measurement techniques (Geyer et al., 1999). 
48 Field Campaigns 

3.3.4.2 Photolysis frequencies 

A scanning spectro-radiometer was deployed at Pabstthum to measure absolute 

spectra of the solar actinic flux from which photolysis frequencies of different 

species (O3, NO2, HCHO, H2O2, HONO, CH3OOH, CH3CHO) were derived. A 

filter radiometer was also deployed for JO1

D and was calibrated against the 

spectro-radiometer measurements. For JNO2, two independently calibrated filter 

radiometers and a spectro-radiometer measured simultaneously at Pabstthum. 

The agreement was on average within 2.5% for solar zenith angles less than 70° 

(Holland et al., 2003). 

3.3.4.3 NOx, O3, CO, PAN 

As outlined in Kanter et al. (2002), the O3 monitor deployed at Pabstthum agreed 

within 5% with a reference instrument that was calibrated against the NIST 

traceable primary standard of the Eidgenössische Materialprüfungs- und 

Forschungsanstalt (EMPA, Dübendorf, CH). For quality assurance of CO, two 

canister samples were collected at Pabstthum and measured against certified 

standards traceable to NOAA CMDL, Boulder (3-8% disagreement with the 

reference). The dynamic PAN calibration systems (Pätz et al., 2002) used by the 

different investigators agreed within 10% (Kanter et al., 2002). 

For NO2, NOy and PAN, the instruments deployed at Pabstthum served as the 

reference in BERLIOZ. The NO standard used at Pabstthum for calibration of all 

four CLDs agreed within 1% with the BERLIOZ reference standard (NIST 

traceable via EMPA). The data quality of the NO2 measurements was 

investigated by comparison of the simultaneous measurements made at 

Pabstthum by CLD/PLC, DOAS, MIESR, and with the balloon borne LMA-4 

instrument. Although the comparison was not organised in a strictly blind 

fashion, the different instruments had been calibrated independently and the data 

were not harmonised before the comparison. As shown in Figure 15, the 

deviation between the four techniques was, on average, less than 5% with 

slightly higher values determined by the spectroscopic methods (Volz-Thomas et 

al., 2003). 

The agreement for NOx (NO and NO2), between the balloon borne LMA4 

instrument employing conversion of NO to NO2 on Cr2O6 and the ground based 

CLD/PLC instrument was similarly good as for the NO2 measurements. A direct 

comparison of the NO concentrations was not possible as the LMA4 on the 

tethered balloon measured NOx and NO2 sequentially and thus at different 

heights. 
LOOP Final Report 49

0 5 10 15 20

0

5

10

15

20

0 5 10 15 20

0

5

10

15

20

0 5 10 15 20 25

0

5

10

15

20

25

 NO2 CLD-PLC [ppb]

Ao = 0.18 ppb

m = 1.05

R = 0.996

NO2 [ppb] MIESR

 NO2 CLD-PLC [ppb]

Ao = 0.53 ppb

m = 1.0

NO

R = 0.975

2 [ppb] LMA-4 

0 5 10 15 20

0

5

10

15

20

 NO2 CLD-PLC [ppb]

Ao = 0.06 ppb

m = 1.01

NO

R = 0.990

2 [ppb] DOAS 

Ao = 0.38 ppb

m = 0.94

NO

R = 0.976

x LMA-4 [ppb]

NOx CLD/PLC [ppb]

Figure 15. Correlation between the four NO2 measurements deployed at Pabstthum (CLD/PLC, DOAS, 

MIESR, LMA-4) and for NOx between CLD/PLC and LMA-4. 

3.3.4.4 VOC 

Hydrocarbons were determined at Pabstthum by in situ gas chromatography with 

two different systems similar to those deployed during the SLOPE campaign (see 

above), namely an Airmotec HC1010 and a custom made system built around a 

HP5890 (referred to as HP-GC). The HC1010 is appropriate for measuring C5 – 

C10 HC with a time resolution of 20 min, whereas the HP-GC is suitable for C2 – 

C10 HC with a 80-90 min measuring cycle. The HP-GC had been elected as the 

reference instrument for the overall quality assurance in BERLIOZ (Volz-Thomas 

et al., 2002). A comparison of the two GCs and tests performed with the inlet 

system are described in Konrad et al. (2003) and Konrad and Volz-Thomas 

(2000). The characterisation and harmonisation of the different in situ GC 

systems (10 different laboratories with almost 20 instruments) deployed in 

BERLIOZ was a major task of the quality assurance activities. Because of the 

many new systems deployed and the involvement of groups with varying 

experience in field measurements, the activities involved several comparisons of 

standard mixtures before a final assessment of instrument performance was made 

by a comparison in ambient air at Schönhagen (Volz-Thomas et al., 2002). 

A DOAS system was also set up to measure several aromatic hydrocarbons, as 

well as phenols and cresols. While some of these compounds were indeed found 

at significant levels at Eichstädt, the concentrations at Pabstthum remained 

always below the detection limit. 
50 Field Campaigns 

3.3.4.5 Formaldehyde 

Several commercial monitors (AeroLaser) that utilise fluorescence for detection 

of HCHO following the Hantzsch reaction were deployed at the different 

BERLIOZ sites. Calibration of the monitors was based on a common liquid 

standard provided by the University of Wuppertal. The comparison at 

Schönhagen (Kanter et al., 2002) was formally satisfying, although somewhat 

hampered by very low concentrations. At Pabstthum, HCHO was also measured 

by DOAS (Alicke et al., 2003). The mixing ratios measured by DOAS (max. 7.7 

ppb) were systematically larger by a factor 1.3 on average and by a factor 1.7 

during high photochemical activity (Großmann et al., 2003). An even larger 

discrepancy between Hantzsch and DOAS was observed at the BERLIOZ sites 

Eichstädt and Blossin. Großmann et al. (2003) discuss the possible reasons for 

the discrepancy in the light of results from other comparisons and conclude that 

none of the two measurements at Pabstthum can be proven wrong on the basis of 

the existing information and that the unresolved discrepancy of about a factor of 

two must be included in the uncertainty of (HCHO) for model simulations of the 

radical budgets (see below). Further comparison of the different methods for the 

measurement of HCHO under atmospheric conditions certainly remains an 

important task. 

3.3.5 Observational results 

3.3.5.1 Radicals 

The variability of OH was mainly controlled by changes in the solar UV 

responsible for the photochemical formation of OH (Holland et al., 2003). Daily 

maxima of OH were usually observed at midday and showed values in the range 

of (4-8) x 106

 cm-3. The shape of the diurnal OH profiles followed closely the 

variations of JO1

D with a linear correlation-coefficient of R~ 0.9. During the early 

morning and late evening hours, however, OH concentrations as high as 1.5 x 106

cm-3 were measured even when JO1

D was essentially zero, due to the radical 

production by photolysis of HONO and HCHO. These precursors were found to 

be efficient photochemical sources of OH under polluted conditions like in the 

morning of 20 and 21 July (Alicke et al., 2003). At sunset the observed OH may 

be explained as a result of reactions of O3 and NO3 radicals with alkenes. (Geyer 

et al., 1999; Geyer et al., 2003) 

NOx was found to be another important parameter that controls OH. The JO1

Dnormalised OH data exhibited a non-linear NOx dependence with a maximum 

around 3 ppb NOx (Holland et al., 2003). Towards lower NOx levels the OH 

concentrations decline due to the decreasing conversion of HO2 into OH by 

reaction with NO (R29), whereas towards higher NOx levels the OH 

concentrations decrease due to increasing depletion of OH by reaction with NO2 

(R38). In comparison to an earlier field campaign (POPCORN), which took place 

in a clean rural environment (Plass-Dülmer et al., 1998), the OH data from 

BERLIOZ are about a factor of 2 lower for the same values of JO1

D and NOx

(Holland et al., 2003). 
LOOP Final Report 51

At night, OH concentrations were usually below the detection limit of the LIF 

when short integration times (90 s) were applied. Averaging the data over timeintervals of 20 minutes yielded significant OH concentrations of (1.9 ± 0.8) x 105

cm-3 in the night of July 20-21, which could be explained by the nocturnal 

production of OH from the reactions of biogenic monoterpenes with O3 and NO3

radicals (Geyer et al., 2003). Averaging all nocturnal OH data measured at 

Pabstthum between 21:00 UT and 3:00 UT, yielded an experimental upper limit 

of 5 x 104

 cm-3 for nocturnal OH (Holland et al., 2003). 

The highest HO2 concentration (8 x 108

 cm-3, i.e., 32 ppt) was observed at noon 

on July 21, a day which was characterised by exceptionally high VOC mixing 

ratios (Konrad et al., 2003). On the other days, the daily maxima were in the 

range of (2-4) x 108

 cm-3 (8-16 ppt). HO2 exhibited a much less pronounced 

dependence on the solar UV then OH and was strongly influenced by NO which 

efficiently converts the peroxy radicals into OH by reaction R29. In the morning 

hours (4:00 - 10:00 UT) when NO usually exhibited a morning peak, the HO2

concentration was typically close to or below the detection limit. 

After sunset HO2 usually remained at significant levels above the detection limit 

(1x107

 cm-3) and had an average night-time value of 3 x 107 cm-3 (~ 1 ppt). On 

some occasions HO2 even increased after sunset as a result of HO2 production by 

the reaction of biogenic VOC's with NO3 and O3 (Geyer et al., 2003). The highest 

nocturnal HO2 value (1 x 108

 cm-3, i.e., 4 ppt) was observed in the night from 

20 - 21 July when very high mixing ratios of organic compounds were 

encountered (e.g., up to ~ 0.5 ppb -pinene). From midnight to sunrise the HO2

concentrations usually decayed and reached values near the detection limit in the 

early morning as mentioned above. 

The diurnal profiles of the organic peroxy radicals (RO2) showed a great 

similarity to HO2. RO2 radicals were often close to the detection limit in the 

morning due to elevated NO mixing ratios. The daily maxima of RO2 occurred 

typically 1 to 2 hours after local noon and reached the highest value, about 20 ppt 

(i.e., ~55 ppt of HO2+ RO2), on 21 July 1998 (Mihelcic et al., 2003; VolzThomas et al., 2003). The concentration of CH3COO2 never exceeded the limit of 

detection (2 ppt) of the MIESR. The sum of other organic peroxy radicals during 

daytime was about the same as the concentration of HO2. 

At night RO2 concentrations were much higher than HO2. During many nights a 

significant increase of HO2+ RO2 was observed after sunset as a result of the 

reaction of NO3 radicals with biogenic monoterpenes (Geyer et al., 2003). 

Night-time maxima of NO3 were usually of the order of 10 ppt (Geyer et al., 

2003). In one night the NO3 mixing ratio reached 70 ppt due to an exceptional 

high production rate of nitrate radicals by the reaction of NO2 with O3. Similar 

time series of NO3 were measured at the BERLIOZ sites Lindenberg, Blossin, 

and Eichstädt, where other DOAS instruments were operated. A correlation of 

the night-time levels of NO3 was observed among all four measurement sites 

(Platt et al., 2002). 

At Pabsttum the average night-time profile of NO3 started to rise above the 

detection limit around sunset and reached a maximum between 20:00 and 22:00 
52 Field Campaigns 

UT, followed by a continuous decay reaching levels below the detection limit at 

sunrise (Geyer et al., 2003). This time profile was found to have a positive, linear 

correlation with the concentration of HO2+ RO2 which also exhibited a nighttime maximum before midnight. For example, in the night of 4-5 August the 

correlation coefficient was R2

 = 0.83. The observed correlation can be described 

generally by a chemistry model showing that the night-time HO2 and RO2

radicals were largely formed by the reaction of NO3 with biogenic VOC's at 

Pabstthum (Geyer et al., 2003). 

3.3.5.2 VOC 

More than 60 hydrocarbons (NMHC) in the range of C2 – C10 were identified and 

quantified with the two GC systems deployed at Pabstthum (Konrad et al., 2003). 

The data sets from both GC systems were combined to join the high time 

resolution of the HC1010 with the high precision and the larger number of 

measurable compounds on the HP-GC. This was achieved by interpolation 

between two data points of the HP-GC with the pattern given by the HC1010. 

For compounds that could not be reliably measured with the HC1010, patterns of 

compounds with similar reactivity were used. 

Air masses with the lowest photochemical age as estimated from the 

toluene/benzene ratio and the highest hydrocarbon mixing ratios were observed 

on July 20th and 21st when air was advected from the direction of Berlin. Alkanes 

were the most abundant hydrocarbons (~ 60%) on a molecular basis, followed by 

alkenes and aromatics. The reactivity of the hydrocarbons towards OH, however, 

was dominated by the alkenes (> 60%), with the biogenic hydrocarbons isoprene 

and -pinene constituting the major fraction even during the time when the site 

was under the influence of air from the greater Berlin area. 

3.3.5.3 Oxygenated VOC 

Up to 30 different aldehydes and ketones ( C2) were identified and quantified at 

Pabstthum during the IOPs using a novel analytical technique (derivatisation 

with PFBHA on cartridges, followed by GC-ECD analysis in the laboratory, 

(Schlomski et al., 1997). HCHO was measured continuously by both, DOAS and 

a commercial Hantzsch monitor (see above). 

Carboxylic acids (C1 – C9) were sampled with a new optimised scrubber system. 

The samples were analysed by sequential reaction with 

dicyclohexylcarbodiimide and 4-aminofluoresceine, followed by capillary zone 

electrophoresis (CEP) and detection by LIF (Kibler et al., 1999). These 

measurements were made during the IOPs only. 

Großmann et al. (2003) discuss the diurnal variation of the oxygenated 

compounds and the correlation between primary and the secondary species that 

were observed at Pabstthum. The C2-C10 aldehydes, which originate primarily 

from anthropogenic hydrocarbon degradation processes, showed maximum 

mixing ratios from 0.6 ppb (C2) to 0.1 ppb (C5). The C6, C9 and C10 alkanals 

exhibited strong fluctuations, thus giving evidence of biogenic emissions. The 

primary unsaturated carbonyl compounds (methylvinylketone and methacrolein) 
LOOP Final Report 53

and the secondary oxidation products of isoprene (hydroxyacetone and 

glycolaldehyde) showed excellent correlation. Also, diurnal profiles of glyoxal, 

methylglyoxal, biacetyl, benzaldehyde and pinonaldehyde were obtained. 

Formic and acetic acid varied between 0.6 and 2.6 ppb. The mixing ratio of the 

other acids decreased from 0.1-0.2 ppb for C3 to a few ppt for the C9-

monocarboxylic acids. The measurements highlight the importance of carbonyl 

compounds for accurately determining the total VOC reactivity. In some cases, 

important information on the chemical mechanism is derived from the observed 

correlation between precursors and oxidation products. 

3.3.5.4 PAN 

The PAN concentrations measured at Pabstthum were similar as on the other 

BERLIOZ sites, with maximum mixing ratios around 1 ppb observed on the 

afternoon of July 20 and 21. Because of the high temperatures on these days, 

PAN was an important source of peroxy radicals (Konrad et al., 2003) despite the 

low concentrations. On the other days with westerly winds, PAN usually 

remained around a few hundred ppt (Volz-Thomas et al., 2003). 

3.3.5.5 Peroxides 

The hydroperoxides show pronounced diurnal variations with peak mixing ratios 

in the early afternoon. The maximum mixing ratios were observed on July 21st

(1.4 ppb H2O2, 0.64 ppb methylhydroperoxide, and 0.22 ppb hydroxymethylhydroperoxide). The increase of H2O2 in the morning originated mainly from 

vertical transport from the residual layer and changes in advection. A secondary 

maximum sometimes observed in the late afternoon indicates the formation from 

ozonolysis of biogenic alkenes. The H2O2/HNO3 ratio is used as indicator for 

distinguishing between NOx and VOC limitation of photochemical ozone 

production at Pabstthum (Großmann et al., 2003). 

3.3.5.6 Odd nitrogen compounds and photo stationary state 

(PSS) 

The ozone production rates P(O3) as calculated from PSS and from the radical 

concentrations provided by the CA are shown in Figure 16. P(O3) from PSS 

reached daily maxima of approximately 30 ppb/h, except on July 20, 21, and 23 

when air was advected from the greater Berlin area. Then the maximum 

production rates are 80-120 ppb/h. The ozone production calculated from ROx 

and NO show a similar pattern with the highest values on July 20, 21, 23. The 

absolute values, however, are on average by a factor of 3-5 lower. On the days 

with the highest production rates, the ozone concentration also exhibited 

significantly larger daily maxima than the 50 ppb observed during the rest of the 

campaign. Figure 16 also compares the radical measurements made by MIESR 

and by CA with those calculated from PSS. Clearly, PSS overestimates the 

peroxy radical concentrations by a factor of 4. 
54 Field Campaigns 

0

50

100

0

20

40

P(O3) [ppb/h] PSS

 CA

 MIESR

0

10

20

30

NOx

RO2+HO2 [ppt]

 PSS :4

 CA

 MIESR

0

2

4

6

8 JNO2*1000

0

50 PAN

Ozone

0.0

0.4

0.8

1.2

0

10

20

30

rh [%]

T [°C]

0

50

0

90

180

270

 wind direction [deg]

06 08 10 12 14 16 0

2

4

6 wind speed [m/s]

 UT 21.7.1998

0

50

100

0

20

40

 PSS

 CA

 MIESR

0

10

20

30

NOx [ppb]

RO2+HO2

 [ppt]

 PSS :4

 CA

 MIESR

0

2

4

6

8

JNO2*1000 [s-1]

0

50

PAN [ppb]

Ozone [ppb]

0.0

0.4

0.8

1.2

0

10

20

30

rh [%]

T [°C]

0

50

0

90

180

270 wind direction [deg]

06 08 10 12 14 16

0

2

4

6

wind speed [m/s]

 UT 20.7.1998

Figure 16. Comparison of P(O3) and total peroxy radical concentrations as determined by PSS, MIESR 

and Chemical Amplifier (from Volz-Thomas et al. (2003)). 

In several of the published data sets data quality issues were discussed as 

potential causes for the large values of PSS derived P(O3) or RO2, particularly 

concerning the accuracy of the NO2 measurements (e.g., Davis et al., 1993). We 

also note that in many of the published data sets, JNO2 was inferred from model 

calculations with adjustments for cloudiness made by flat plate radiometers. As 

noted above, the contributions from imprecision can always be sufficiently 

reduced by selecting data well above the instrumental detection limits and for 

relatively homogeneous atmospheric conditions as well as by averaging over 

long enough time periods. The contributions from accuracy, however, remain. 

At Pabstthum, the accuracy of the NO2 measurements is confirmed by the 

comparison of four independent methods. In fact, when taking the spectroscopic 

NO2 measurements as the true values and correcting the CLD/PLC 

measurements accordingly, the deviation between P(O3) from (2) and (3) would 

become slightly larger. For NO, a direct independent method was not available at 

Pabstthum. However, problems with the NO measurement are difficult to 

conceive because the NO2 measurement by CLD/PLC is based on the 
LOOP Final Report 55

measurement of NO which should thus have a similar or better accuracy than 

NO2. The NO calibration agreed with the certified standard within 1%. Finally, 

NOx measured by the balloon borne LMA4 instrument employing conversion of 

NO to NO2 on Cr2O6 (fourth panel of Figure 15 agreed with the CLD/PLC data 

as well as the NO2 measurements. A direct comparison of the NO concentrations 

was not possible as the LMA4 on the tethered balloon measured NOx and NO2

sequentially and thus at different heights. The ozone monitor agreed with the 

primary ozone standard within < 5% and the two independently calibrated JNO2

instruments agreed within < 3%. Therefore, the uncertainty in the rate coefficient 

(8%, Atkinson et al. (1997)) represents the largest uncertainty. 

01234

0

30

60

90

01234

0

30

60

90

0.0 0.1 0.2 0.3 0.4 0.5

0

5

10

15

20

25

30

BERLIOZ 1998

PO3 [ppb/h]

NO [ppb]

 PSS, JNO2>0.006 s-1

 CA

 Ox -Budget aircraft

 MIESR

 PSS, JNO2>0.006 s-1

 MIESR

Schauinsland 1994

PO3 [ppb/h]

PO3_vs_NOx_mal_J: PabSchauza

Izana 1993

PO3 [ppb/h]

 PSS

 CA

 MIESR

Figure 17. Comparison of P(O3) determined by PSS and from RO2 measurements at Izana, Schauinsland 

and Pabstthum. The values of P(O3) calculated from the radical measurements in BERLIOZ are in 

excellent agreement with the ozone budget obtained from airborne measurements of the ozone fluxes 

(lower panel). 
56 Field Campaigns 

The result from BERLIOZ is similar to observations made at Schauinsland 

(Figure 17), whereas in clean air at Izana good agreement between PSS and 

radical measurements was observed. It was thus concluded that the PSS approach 

severely overestimates the local ozone formation rate in the continental boundary 

layer (Volz-Thomas et al., 2003). In none of the radical measurements made by 

MIESR, values of P(O3) greater than 10 ppb/h were found (Mihelcic et al., 

2003). Faster rate coefficients for the reaction of RO2 with NO, as discussed by, 

e.g., Frost et al. (1998), are not considered a likely explanation, because the 

discrepancy exists also at high NO concentrations where the peroxy radical 

concentrations are at or below the detection limit of the MIESR. Moreover, the 

budget of ozone in the plume as derived from the aircraft measurements in 

BERLIOZ (Corsmeier et al., 2002) does not allow for much larger formation 

rates than those calculated from the measured RO2 concentrations and the 

accepted rate coefficients. Therefore, an unknown oxidation process must exist in 

the atmosphere for NO. While similar suggestions have been made before 

(Carpenter et al., 1998; Parrish et al., 1986; Volz-Thomas et al., 1997), the high 

data quality achieved in PHOEBE precludes the possibility of analytical errors 

being responsible for the observed discrepancy. Furthermore, the comparison 

with the ozone budget gives evidence that the unknown process does not lead to 

a net formation of O3. The MIESR data from BERLIOZ and several other 

campaigns conducted at Schauinsland in Southern Germany and at Tenerife 

suggest that ozone formation rates do not exceed values of 10 ppb/h (Mihelcic et 

al., 2003). 

3.3.6 Model simulations 

The measurements were used to calculate the radical concentrations with 

photochemical box models of different complexity, i.e., the Master Chemical 

Mechanism (MCM, (Jenkin et al., 1997)) and the condensed mechanism RACM 

(Stockwell et al., 1997). As is seen in Figure 18, both models predict the 

concentrations of OH, HO2 and RO2 quite well in the high NOx regime (Konrad 

et al., 2003; Mihelcic et al., 2003). An important conclusion was that the 

photolysis of HONO accounted for most of the HOx production in these air 

masses during early morning (Alicke et al., 2003). 

On the other hand, both models significantly overestimated the OH 

concentrations at low NOx (< 5 ppb). The disagreement was up to 60% for the 

MCM and 80% for RACM. The agreement for HO2 and RO2 was better. 

Ozonolysis of mostly biogenic olefins was an important source of RO2 and HO2

in the late afternoon. 

Qualitatively, the results from Pabstthum confirmed earlier exercises, in which 

constrained models were also found to over predict OH concentrations (e.g., 

Carslaw et al., 1999; Eisele et al., 1994, 1996; George et al., 1999; Hauglustaine

et al., 1999; McKeen et al., 1997; Poppe et al., 1994; Perner et al., 1987; Platt et 

al., 1988; Savage et al., 2001). The sensitivity studies conducted in PHOEBE 

demonstrated that missing hydrocarbon reactivity, as argued in several earlier 

studies, was not the sole reason for the overestimation of OH. This conclusion 

was possible from the specific RO2 measurements made in PHOEBE (Mihelcic
LOOP Final Report 57

et al., 2003). Increasing the VOC reactivity lead to a pronounced over prediction 

of the RO2 concentration by the model. The concentrations of all radicals was 

brought into reasonable agreement with the measurements by introducing a sink 

term in the models, corresponding to a first order loss of approximately 1 s-1 for 

OH or 0.02 s-1 for HO2, and by increasing the total biogenic VOC reactivity by 

approximately 20% (Konrad et al., 2003). 

0

20

40

60

80

0

2

4

6

0

5

10

15

0

200

400

600

06 09 12 15 18 21

0

10

20

RO2 [ppt] HO2 [108 cm-3] OH [106 cm-3] HO2/OH NOx [ppb]

UT 20.7.98

J(O1D)*106 [s-1]

Figure 18. Diurnal variation of simulated and measured concentrations of free radicals (OH, HO2 and the 

sum of all organic peroxy radicals RO2) on July 20th at Pabstthum (open circles: LIF (OH and HO2); 

squares: MIESR (HO2 and RO2); solid lines: RACM simulation; broken lines: RACM with 500 ppt of 

limonene added. The dotted lines: MCM simulation. The lowest panel shows the NOx mixing ratio, 

condensation nuclei (CN), and the photolysis frequency J(O1

D). (from Konrad et al. (2003)). 

3.3.6.1 Night time chemistry 

The simultaneous observations of NO3, RO2, HO2, and OH during several nights 

were interpreted with a chemical box model by Geyer et al. (2003). For most of 

the nights the model results and ambient observations of RO2 and HO2 are in 
58 Field Campaigns 

good agreement, whereas the modelled OH concentrations are just within the 

upper limit of the measurements (5 x 104 

cm-3). In one night (20-21 July), when 

very high mixing ratios of VOCs were encountered, the model yielded a 

maximum nocturnal OH level of (4.1 ± 0.7) x 105

cm-3, significantly higher than 

the measured value of (1.60 ± 0.85) x 105

 cm-3. The overestimation by the model 

could point to a missing nocturnal sink of OH. 

Reactions of NO3 with VOCs, mainly with biogenic monoterpenes, were shown 

to constitute a considerable source of organic peroxy radicals at night. 

Generally a positive linear correlation of the mixing ratios of RO2 and NO3 was 

observed and modelled during the campaign. The model analysis shows that this 

dependence can be attributed to the role of NO as a sink for both radicals. In 

addition, the production rate of RO2 increased with increasing NO3 concentration 

during nights, when VOCs were of minor importance for the NO3 removal. 

While Carslaw et al. (1997) also found a positive correlation of RO2 and NO3 at 

the eastern coast of England, Mihelcic et al. (1993) observed a negative 

correlation for a clean, forested site where the NO3 losses were dominated by 

reactions with VOCs. 

The contribution of OH to the nocturnal oxidation of VOCs, CO, and CH4 was 

modelled to be 15% of that of NO3 for the situation at Pabstthum. This 

corresponds to a contribution of 2.6% by night time OH to the 24h integral of the 

total atmospheric oxidation capacity. Since the model tends to overestimate the 

measured OH levels at night, the contribution is even smaller and therefore 

negligible during BERLIOZ. 

3.3.7 Conclusions 

The measurements made during BERLIOZ at Pabstthum comprise the most 

complete data set collected so far in the PBL on the chemistry of free radicals. 

Most radicals, i.e., HO2, RO2 and NO3, were measured with two different 

analytical techniques. The good agreement gives high confidence in the accuracy 

of the data. The situation is similar for the stable compounds, e.g., excellent 

agreement (<5%) was observed between four different methods for the 

measurement of NO2, more than 50 hydrocarbons and 30 carbonyl compounds 

were identified and quantified, and quantitative experimental information was 

obtained on the relevant photolysis rates that control radical production. For the 

concentration of HCHO, significant differences of up to a factor of two were 

observed between DOAS and the in situ measurement, which could not be 

resolved. 

Although the city plume was observed only for a few hours, the measurements 

covered the entire range of chemical conditions from continental background (< 

1 ppb NOx) to suburban air with up to 30 ppb of NOx. The interpretation of the 

data set in the accompanying papers leads to important conclusions regarding our 

understanding of the radical chemistry: 

The NO/NO2 ratio is 25% lower than predicted by photochemical models 

and by the PSS approach. 
LOOP Final Report 59

The photochemical ozone production rate does not seem to exceed values of 

10 ppb/h. The production rates derived from PSS are much larger and must 

be regarded with great caution. 

The large overestimation of OH by the models at low NOx mixing ratios 

suggest a yet unidentified loss process for HOx radicals. The RO2 data show 

that missing VOC reactivity is not the sole reason. 

Night time chemistry initiated by NO3 radicals and ozonolysis plays an 

important role in the degradation of many VOCs and is an important source 

for peroxy radicals at night. 

HONO is an important source for OH in polluted air in the morning. 

Acknowledgement 

The financial support by the German Ministry for Research and Education 

(BMBF) as part of the Tropospheric Research Focus (TFS, LT 3) is gratefully 

acknowledged. 
60 Field Campaigns 

3.4 PIPAPO 

Christoph Spirig, Albrecht Neftel 

Swiss Federal Research Station for Agroecology and Agriculture, Zurich,. Switzerland 

Josef Dommen 

Paul Scherrer Institute, Laboratory of Atmospheric Chemistry, Villigen, Switzerland 

Rita Van Dingenen, Jean-Philippe Putaud 

European Commission Joint Research Centre, Ispra, Italy 

3.4.1 The Milan basin as natural photoreactor 

The PIPAPO (Pianura Padana Produzione di Ozono) campaign took place May 

to mid June 1998 in the northern part of the Po Valley (information about air 

quality in the Lombardy region on the web: 

http://www.ambiente.regione.lombardia.it 

This region offers many interesting aspects with respect to air pollution problems 

and reduction strategies: 

Frequent episodes with very high photo-oxidant levels. 

Re-circulation of air masses over the Po Valley due to the topographic 

situation. 

Presumably rapid changeover from VOC to NOx limited ozone production. 

Large production of secondary aerosol with a major influence from 

biogenic VOC and NH3 emission due to intensive farming and high 

emissions of isoprene and terpenes in the pre-Alps. 

The PIPAPO field campaign was basically set up as a Lagrangian experiment 

with several stations within the so-called Milan plume, i.e., downwind of Milan. 

During two intensive observation periods (IOP’s, May 12 and 13, June 1 to 10, 

1998), surface station and aircraft measurements were performed. Observational 

stations at Bresso, Seregno and Verzago were established downwind of Milan, 

hypothetically located in different chemical regimes according to earlier 

investigations with a one-dimensional Lagrangian model (Staffelbach et al., 

1997b) (Figure 19). 

Aerosol issues, especially concentration of fine particles (PM2.5), gained 

increasing attention from environmental agencies, because air quality guidelines 

for PM2.5 and/or PM10 are now generally being established. As for ozone, 

development of reduction strategies to meet the newly established guidelines 

needs a quantitative source – receptor relationship. Reduction strategies for 

aerosols might interfere with ozone reduction strategies (Meng et al., 1997). It 

was therefore a logical step to start a close cooperation with the Eurotrac-2 

subproject AEROSOL. In fact it was the steering committee of the AEROSOL 

subproject that offered to actively participate in the PIPAPO field experiment. 
LOOP Final Report 61

Milano

Como

Bergamo

Verzago

Seregno

Bresso

680 700 720 740 760 780

x [km]

0

20

40

60

80

100

120

140

y [km]

Figure 19. PIPAPO – an experiment with a Lagrangian approach. Colours of the LOOP logo (see section 

2.3) indicate different ozone production regimes of the Milan Plume as found in 1-D Lagrangian model 

runs. 

3.4.2 Intensive observation periods 

The PIPAPO experiment was organised as a pure bottom-up project without 

central funding. A close co-operation with local authorities was established from 

the beginning. 

During two intensive observation periods (IOP’s) (May 12th and 13th, June 1st to 

June 10th), measurements at the ground stations were intensified and air plane 

measurements completed the field activity. 

Meteorological criteria for an IOP were i) a high pressure situation lasting for 

several consecutive days, ii) high insolation producing strong thermally driven 

circulations and intensive photochemical activity, iii) weak synoptic winds aloft 

and southerly winds near the surface, and iv) absence of precipitation. Because 
62 Field Campaigns 

ozone episodes often occur in spring and early summer, this time of the year was 

selected over the better-known mid-summer episodes. 

The first IOP lasted from May 12 to 13, 1998, and was embedded in a period of 

exceptionally warm, dry and sunny weather. The Po Basin was free of clouds on 

both days, while in the afternoon of the second day convective clouds developed 

in the mountains east of the Lake of Como, which led to thunderstorms that 

terminated the IOP. A heat low over the Alps was well established on both days. 

The pressure gradient induced a weak south-to-north flow over the study area, 

and the ideal flow configuration for PIPAPO was realized on May 13. High 

insolation and high temperatures were very favourable for photochemistry in the 

planetary boundary layer (PBL), and the winds supported the transport of 

polluted air from the basin towards the Alps. Ozone concentrations reached 

values of 190 ppb during this IOP. 

The second IOP took place from June 1 to 10, 1998. A consistent southwesterly 

flow across the Alps existed for the whole period, while the surface charts exhibit 

various frontal systems, which remained north of the Alpine crest. 

Winds aloft were mostly southwesterly, while surface winds showed variable 

directions. Very frequently thunderstorms and scattered intermittent heavy 

showers developed during the second IOP. In contrast to the first IOP, Milan 

always reported moderate cloudiness around noon. The ideal flow situation for 

the second IOP lasted from June 2 to 4, before a cold front approached the area. 

In this period, maximum ozone concentrations increased from day to day, 

reaching peak values of 140 ppb on June 4. 

May 12th and 13th have been chosen as the ideal days for the application of the 

Eulerian models. 

3.4.3 QA/QC of PIPAPO 

The quality assurance, quality control (QA/QC) within PIPAPO is based 

primarily on the conscientiousness of the individual contributors. The data have 

been compiled on an MS ACCESS database, including tools for extracting and 

visualizing of data1

. Figure 20 shows an example for the representation of the 

flight data. The user can e.g. scan the flight for any measured species, and then 

the height above ground, the geographical location and the concentration are 

shown. 

 

1

 The CD can be ordered at FAL, P.O. Box, CH 8046 Zürich 
LOOP Final Report 63

Figure 20. Visualization tool for the PIPAPO database. 

3.4.4 Emissions 

3.4.4.1 Development of the emission inventory for the LOOP 

domain 

An emission inventory was developed for the Lombardy region and Southern 

Switzerland. The resolution is 3 x 3 km in space and 1 hour in time. It contains 

anthropogenic and biogenic area emissions and a few large point sources. The 

available information on emissions in Italy and Switzerland was different and 

had to be combined. 

In the Italian part of the domain, a bottom-up approach was used to derive the 

emission inventory from statistical data. Emissions of SO2, NOx, CO and volatile 

organic compounds were considered. For the VOCs eleven different speciation 

profiles (eight anthropogenic and three biogenic) were used. Statistical data were 

available on a municipality level. The emissions calculated for a municipality 

were then allocated to each grid cell using land-use data. 

For the Swiss part of the region an emission inventory of high spatial (5x5 km2

) 

and temporal (1 hour) resolution with base year 1995 existed. It was an updated 

version of the emission inventory developed during the Swiss Pollumet project 

(BUWAL, 1996). The inventory is divided into the two categories traffic and 

industry, and includes emissions of SO2, nitrogen oxides (NOx), CO and volatile 

organic compounds (VOC). This inventory was spatially re-sampled to match the 

3x3 km2

 grid resolution. The VOC-species profile was also adapted to the 

profiles used for the Italian part of the domain. A detailed description of the 
64 Field Campaigns 

preparation of the emission inventory is given in Maffeis et al. (1999) and 

Dommen et al. (2003). 

Finally, the emission inventory was provided to the modellers with different 

lumping schemes of the VOCs. 

Figure 21 shows the daily average emissions for NOx. The Milan area with its 

high emissions is clearly seen. There are many peaks scattered throughout the 

domain, which are from smaller cities and power plants. Highways and main 

roads are also clearly seen as line emission sources. 

8.5 9 9.5 10

Longitude

45.5

46

46.5

Latitude

 V

 M 

NOx

 0 to 1

 1 to 10

 10 to 100

 100 to 500

 500 to 1000

 1000 to 2000

 2000 to 4000

Figure 21. Average-day NOx emissions (kg/day) in LOOP domain for all source categories. V = Verzago, 

M = Milano. 

Figure 22 shows the magnitude of the domain total hourly NOx emissions. NOx

emissions from traffic and stationary sources are roughly equal. Point sources 

add about 10% to the total NOx emissions. 

-

2

4

6

8

10

12

14

16

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Human activities

Linear traffic

Urban traffic

Figure 22. Diurnal variation of domain total NOx emissions (without point sources) in tons of 

NO2-eq /hour (from Dommen et al. (2003)). 
LOOP Final Report 65

Besides the advantages of this bottom-up methodology, there are also limitations 

to this approach as mentioned above (section 2.5). This inventory used a 

statistical method based on industrial plants declarations in which CO emissions 

are underestimated. Another weakness is that more point sources, beyond the 

seven considered here, need to be known in more detail. The use of UK annual 

detailed emission profiles (Derwent et al., 1996) to speciate VOCs is also a rough 

approximation; in fact, no alternative information is at disposal on a local base. 

This could cause an inadequate VOC speciation with consequence on the 

reactivity of the emitted pollutants, playing an important role in photochemical 

modelling. Finally, it should be underlined that both national inventories are 

based on indicators and emission factors referenced to the year 1995. 

An update of this inventory should include: 

newly realized important infrastructure (e.g., Malpensa airport and connected 

to this additional transportation); 

the strong car fleet renewal over the last years; 

the change in industrial processes and their decentralisation out of the main 

cities. 

3.4.4.2 Comparison of the emission inventory with 

measurements 

A comparison of emission ratios of CO/NOx and CO to various hydrocarbon 

classes have been performed between the emission inventory and measurements 

in rural and urban environment (Dommen et al., 2003). Measurements yield 

CO/NOx ratios between 11 and 27. The higher values are related to situations of 

dense traffic in the centre of a city with traffic jams. The inventory-based ratios 

are 5.5-7 for the urban area and 2-3 elsewhere. The measurements do not show a 

pronounced difference of the CO/NOx ratio between urban and non-urban 

regions as given by the inventory. Model studies of the urban plume show a clear 

underestimation of the modelled CO mixing ratio compared to measurements 

(Martilli et al., 2002; Bärtsch-Ritter et al., 2003b). From these model calculations 

it was concluded, that CO emissions are underestimated by about a factor of 1.8 

(Bärtsch-Ritter et al., 2003b). 

Ratios of some classes of hydrocarbons to CO were also inter-compared between 

emission inventory and measurements. The emission inventory underestimates 

CO/VOC-class ratios by factors of 1.3 - 8. Bärtsch-Ritter et al. (2003b) evaluated 

the influence of such discrepancies on the photo-oxidant formation (see section 

3.4.8). 

3.4.5 Meteorology and photosmog episodes in the Milan area 

Occurrences of elevated ozone concentration in the region between Milan and the 

Alps are strongly related to the meteorological conditions. As an example, Figure 

23 shows the variability of late afternoon concentrations in Verzago as a function 

of the prevailing meteorological conditions. Daily average global radiation and 

daily temperature maximums were taken from representative ground stations. 
66 Field Campaigns 

The prevailing wind conditions were derived from wind profiler measurements at 

Seregno, which is located between Milan and Verzago. The best correlation is 

found between temperature and ozone concentrations at Verzago in the late 

afternoon (17.30 Central European Daylight Time, = LST + 1h = UTC + 2h) 

during the PIPAPO campaign. Ozone increases from around 45-70 ppb at 20°C 

to 80-145 ppb at 30°C. The main reasons for this relationship are higher biogenic 

emissions, higher chemical reaction rates, and usually higher global radiation at 

higher temperatures, yielding higher ozone production. However, taking only 

temperature into account, a great part of the variability in the ozone concentration 

remains unexplained. Ozone does not exhibit a consistent dependence on global 

radiation. Model simulations show that ozone concentrations have a large 

temperature dependence (Bärtsch-Ritter et al., 2003a). On days with low 

radiation (lower than 2/3 of typical clear days), ozone concentrations do not 

exceed 80 ppb (crosses in Figure 23). Assuming the wind profiler data to be 

representative for the region around Milan, we can deduce the influence of the air 

mass origin on the ozone concentrations in Verzago. The highest concentrations 

in a particular temperature range are found for the cases when southerly winds 

prevail, transporting the Milan plume to Verzago (large circles in Figure 23). In 

the case of strong winds (several hundred kilometres transport distance within 10 

hours) and no development of thermally induced winds towards the Alps, low 

ozone concentrations are found in the according temperature range (squares in 

Figure 23). On days with thermally induced winds not originating from Milan 

(usually southwesterly or southeasterly wind directions), the ozone 

concentrations were close to the linear correlation fit (diamonds in Figure 23). 

Small circles denote days with incomplete or missing data from the wind profiler. 

15 20 25 30 35

0

50

100

150

temperature (°C)

O

z

o

n

e (p

p

b) ni Verz

a

g

o

at 17:3

0

Air from Milano

Strong winds, no thermally induced winds

Low radiation

Figure 23. Variability of ozone levels at Verzago as function of meteorological parameters. 
LOOP Final Report 67

In summary, the ozone concentrations in Verzago in the late afternoon typically 

increase by around 6 ppb ozone per 1 °C daily maximum temperature. On days 

with low global radiation ozone concentrations do not exceed 80 ppb. When the 

air originates from Milan, we find around 20-30 ppb higher ozone concentrations 

than the concentration typical for the prevailing temperature. This is similar to 

what was found in cross-sections of the plumes, where the maximum ozone 

concentrations are often 20-40 ppb higher than in the adjacent air masses 

(Dommen et al., 2002). For conditions with strong winds or no development of 

southerly thermally induced winds, ozone concentrations are 20-30 ppb lower 

than typical for the prevailing temperature. 

3.4.6 Investigation of P(O3) based on observations 

3.4.6.1 PSS versus ODD-H approximation 

For the comprehensive data sets at the site of Verzago, radical concentrations and 

local ozone productions (P(O3)) were determined by steady state calculations. 

Peroxy radical levels as determined by steady state calculations were usually 

lower than concentrations measured with a chemical amplifier at this site (Spirig 

et al., 2002). Part of this difference can be explained by the negligence of O3-

alkene reactions as a radical source (see section 2.2.4). Based on VOCmeasurements at Verzago, we estimated the importance of this radical source 

during the passage of the plume at the station on May 13 1998. This is 

considered to be an extreme case and likely to represent an upper limit of VOC 

levels for this location. Ozonolysis of alkenes contributed 25% to odd-H 

production in this case, a smaller percentage than Paulson and Orlando (1996) 

found for an urban ground station in the Los Angeles area. 

Calculations of P(O3) by using either equation (5) or (1) frequently results in 

significant discrepancies. For sunny conditions with well mixed conditions, 

P(O3) calculated with the Leighton ratio (5) is higher than with the formation 

over R1-R4. 

local time

-20

-10

0

10

20

30

40

50

P(O3) [ppb/h]

Equation (1)

PSS

9:00 11:00 13:00 15:00 17:00 19:00

Figure 24. Comparison of P(O3) calculated by the Leighton ratio (PSS) and (1) for May 13th 1998 at 

Verzago. (Data from the PIPAPO field experiment). 
68 Field Campaigns 

Figure 24 shows a comparison of P(O3) calculated by equation (1) and the PSS 

based on measurements of the PIPAPO campaign in Verzago (May 13th). There 

is a clear tendency - during the afternoon, when the boundary layer height is 

constant - that P(O3) derived from PSS is higher than calculated via the radical 

steady state approximation. 

3.4.6.2 Investigation of NOx / VOC sensitivity of P(O3) 

For datasets gathered during the two IOP’s, the relative change of the ozone 

production rate due to a small change (5%) in the concentrations of NOx and 

VOC (including CO, biogenics and CH4) was calculated. In Figure 25, these 

relative ozone production sensitivities (dlnP(O3)/dln [NOx] and 

dlnP(O3)/dln[VOC]) are plotted against the parameter LN/Q. 

Figure 25. Relative sensitivities of local ozone production as determined from measurements between 

1000 and 1800 LT at Bresso and Verzago. 

The LN/Q values calculated from observations (circles and squares) follow the 

theoretical pattern (lines) quite well, except at higher LN/Q values, where the 

“observed” relative sensitivity of VOC-changes is somewhat lower than in 

theory. The transition between NOx and VOC sensitive O3 production occurs 

almost exactly at the theoretical LN/Qvalue of 0.5. Calculated LN/Q values for the 

sites of Bresso and Verzago reveal that ozone production at the urban site of 

Bresso is VOC sensitive, while Verzago exhibited both VOC and NOx sensitive 

conditions. The VOC sensitivity at Bresso is not surprising due to the various 

strong emission sources nearby. The situation in Verzago is more complex. 

Ozone production and its sensitivity are influenced by the diurnal variation of 

radiation, vertical mixing and horizontal transport processes. 

The results of the LN/Q-approach for Verzago and Bresso agree with analyses of 

the ozone production regimes by other methods. Empirical ozone isopleths 

(Thielmann et al., 2001) and measurements of indicator species (Thielmann et 

al., 2002) both suggest VOC-sensitive ozone production at Bresso and mainly 

0 0.2 0.4 0.6 0.8 1

LN/Q

-1

-0.5

0

0.5

1

dlnPO3/dln[X]

dlnPO3/dln[HC]

dlnPO3/dln[NOx]

NOxsensitive

VOCsensitive
LOOP Final Report 69

NOx sensitive ozone production at Verzago (Figure 26). Cases of VOC-sensitive 

ozone production at Verzago occurred during situations with direct advection of 

air masses from Milan. 

Figure 26. Ozone isopleths from measurements at Bresso and Verzago (Thielmann et al., 2001): VOC (as 

propene-equivalents) versus NOx and NOz concentrations. 

3.4.6.3 Measurements of indicator species 

May 12 and May 13 1998 were ideal days to compare ozone sensitivities at the 

site of Verzago: Although temperature and radiation conditions were similar, two 

distinct situations were observed. On May 12, no direct advection of air masses 

from Milan occurred, whereas on May 13, a distinct plume arrived at the 

Verzago site. The analyses above and 3-D model studies (see 0) suggest VOCsensitive ozone concentrations within the Milan plume and NOx sensitivity in 

areas not affected by the plume. The indicator values registered at Verzago on 

these two days show different levels during the passage of the plume (grey area 

in Figure 27) and the afternoon on May 12. The transition values of the indicators 

deviated from these specific events are in agreement with the values proposed by 

Sillman (1995a), i.e., 6-8 for O3/NOy, and 0.2 –0.3 for H2O2/HNO3. 

12:00 15:00 18:00

May 12

100

120

140

160

180

200

O3 [ppb]

2

4

6

8

O3/NOy 0.2

0.4

0.6

H

O2 2/HNO3

12:00 15:00 18:00

May 13

10

20

30

40

50

NOy[ppb]

0.2

0.4

0.6

H

O2 2/HNO3

12:00 15:00 18:00

2

4

6

8

O3/NOy

12:00 15:00 18:00

Ozone

NOy

Figure 27. Measurements of indicators at the site of Verzago during May 12 and May 13 1998. The grey 

area indicates the passage of the VOC-sensitive Milan plume. 
70 Field Campaigns 

3.4.6.4 Results from aircraft observations 

Measurements of VOC, NOx, peroxides and O3 aboard an aircraft were also used 

to characterize ozone production rates in the Milan area (Dommen et al., 2002). 

These analyses focused on heavily polluted air masses, i.e. the so-called ‘Milan 

plume’. Steady state calculations (similar to those described in section 2.1.4) 

showed that the core of the Milan plume is VOC sensitive. The plume showed a 

downwind extension of about 40 km and a width of 10 to 20 km. Most of the 

measurements in the Milan plume fulfil the high NOx formula for the ozone 

production rate, as given by eq. 23 (see Figure 28). Peroxide and ozone 

productions rates were calculated from the measurements and also deduced from 

a local steady state photochemical analysis. The intercomparison of these two 

approaches yielded reasonable agreement for peroxide but lower ozone 

production rates for the steady state analysis. 

0 5 10 15 20 25

ki[VOCi]Q)/(kN[NO2])

0

4

8

12

16

P(O

3) (ppb/h)

Figure 28. Calculated values of P(O3) from the high NOx formula eq. 23. Circles are values 

with LN/Q < 0.7. 

3.4.7 Aerosols 

3.4.7.1 Number size distributions 

Aerosol number size distributions in Bresso (urban background) and Verzago 

(rural, regional background) have quite different shapes. Figure 29 shows 6-

hourly averages (over the whole PIPAPO measurement period) of the size 

distributions for both sites. The total number concentration in Bresso is always 

higher than in Verzago. Bresso size distributions are clearly bi-modal with a very 

pronounced peak in the Aitken mode (around 20 - 25 nm diameter size). In 

Verzago, the modes appear to be merged into a single broader mode, with a 

strongly reduced number concentration compared to Bresso. 

The high number concentration of small particles in Bresso is obviously due to 

traffic emissions, and most pronounced during morning rush hours (06:00 - 

12:00). 
LOOP Final Report 71

0000-0600

0

5000

10000

15000

20000

25000

30000

35000

40000

1 10 100 1000 10000

Dp (nm)

dN/dlog(Dp) 

(#/cm3)

Bresso Verzago

0060-1200

0

5000

10000

15000

20000

25000

30000

35000

40000

1 10 100 1000 10000

Dp (nm)

dN/dlog(Dp) 

(#/cm3)

Bresso Verzago

1200-1800

0

5000

10000

15000

20000

25000

30000

35000

40000

1 10 100 1000 10000

Dp (nm)

dN/dlog(Dp) (#/cm3)

Bresso Verzago

1800-2400

0

5000

10000

15000

20000

25000

30000

35000

40000

1 10 100 1000 10000

Dp (nm)

dN/dlog(Dp) (#/cm3)

Bresso Verzago

Figure 29. Averaged size distributions for different periods of the day in Bresso (urban background) and 

Verzago (rural, regional background). 

Apart from the lower number concentration, Verzago also shows larger mode 

diameters, indicating that a growth process has taken place during air mass 

transport. We investigated with a sectional aerosol box model in how far the 

coagulation process can explain the observed changes in number and mode 

diameter. It appears that coagulation only can not explain the particle number 

reduction in a realistic time period (3 - 6 hours), and that the observed mode 

diameters in Verzago are larger than the modelled one, in particular for the 

Aitken mode. This provides some evidence that other growth processes 

(condensation of secondary aerosol) has contributed to the Verzago aerosol 

volume. 

Further evidence for secondary aerosol formation is given by the volatile aerosol 

fraction, which was obtained by measuring the residual size distribution after 

heating the aerosol up to 280°C. At this temperature, sulphuric acid, ammonium 

sulphate, ammonium nitrate and semi-volatile organic compounds are 

evaporated, which are making up most of the secondary aerosol. The refractory 

aerosol can be attributed to primary emitted black carbon, low-volatility organic 

compounds and dust. Figure 30 shows the average diurnal trend of the volatile 

aerosol fraction at both sites. It appears that most of the aerosol mass (50 - 80%) 

consists of semi-volatile (secondary) compounds for both sites, but Verzago has 

a systematic higher fraction than Bresso. Note that both sites show a significant 

increase in non-volatile compounds during the morning rush hour, consistent 

with traffic-related emissions of black carbon and primary organic compounds. 
72 Field Campaigns 

Fraction volatile volume (280°C), average diurnal trend

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

00:00 03:00 06:00 09:00 12:00 15:00 18:00 21:00 00:00

Verzago Bresso

Figure 30. Average diurnal trend of the volatile aerosol volume fraction in Bresso and Verzago 

(sub-μm particles only). 

3.4.7.2 Chemical composition 

The comparison of the fine aerosol chemical composition at Verzago (near-city 

site) and Bresso (urban site) shows that the concentration of ammonium nitrate 

normalized to elemental carbon (NH4NO3/EC) was on average 10% larger at the 

near-city site compared to the urban site. Although it is difficult to determine 

whether this difference was significant or not, it might be explained by the 

conversion of NO2 to HNO3 (and then to NH4NO3-, NH3 being present in excess 

in the PiPapO area) during the transport of the photo-chemical smog plume. The 

normalized concentration of POM (POM/EC) was in turn 70% larger at the nearcity site compared to the urban site. The contribution of biogenic sources to the 

POM collected at the near-city site could not be investigated with the analytical 

methods we applied. Another source for the POM observed at this site could be 

the oxidation in condensable species of anthropogenic VOCs emitted upwind, in 

urban areas. To examine this hypothesis, we looked for changes in ratios between 

reactive species and stable tracers of pollution such as CO and EC. Variations in 

such normalized concentrations are independent of dilution and reflect mainly 

chemical processes. We observed for instance that the toluene/CO ratio was 2 

lower at the near-city site compared to the urban site (Thielmann et al., 2002). 

The oxidation of toluene can lead to condensable species, which would 

contribute to POM concentration (Pandis et al., 1992), and to ozone formation. 

We actually observed a correlation between afternoon average O3/EC and 

POM/EC ratios (R3=0.53, n=18, Figure 31). These observations indicate that the 

high POM concentrations observed at the near-city site were at least partly due to 

the gas-particle conversion of VOCs’ oxidation products. 
LOOP Final Report 73

R2 = 0.53

0

2

4

6

8

10

12

14

16

18

0 50 100 150 200 250 300

Normalized ozone concentration (μg m-3 O3 / μg m-3 EC)

Normalized POM concentration (μg m-3 OC / μg m-3 EC)

Figure 31. Correlation between POM/EC and O3/EC afternoon concentrations at the near-city site of 

Verzago during PiPaPO (Putaud et al., 2002). 

3.4.8 Model analysis 

Environmental policy to manage regional ozone problems has strongly relied on 

the use of photochemical air quality models (PAQM). These models contain 

representations of dynamics, emission rates and photochemistry. The differences 

between the models lie in the numerical routines, detail in the description of the 

physical and chemical processes, and how they use or develop meteorological 

fields. There is great concern about the uncertainties of such model predictions 

for ozone management strategies. Uncertainties may be due to model 

formulation, model inputs, or lack of a comprehensive set of measurements for 

model evaluation. There is no direct way to test whether a models prediction is 

accurate. It was the central theme of the LOOP project to determine the uncertain 

nature of model predictions concerning the response of ozone to reductions in 

NOx and VOC emissions and to improve the basis on how to evaluate a model. 

Sillman et al. (1995b) showed that 25% changes in anthropogenic emissions, 

wind speeds and mixing heights could alter the size of the reductions in peak 

ozone resulting from reduced VOC or NOx by a factor of two to ten. The biggest 

concern associated with model performance is the possibility of bias in 

predictions for the impact of NOx versus VOC. 

Emissions uncertainties are one of the limiting factors to accurately predict the 

dynamics of ozone over urban and regional scales, as well as the impact of 

control strategies. Evaluation of models with respect to meteorological 

parameters and comparison with ambient measurements other than ozone are 

also crucial. In recent years, different diagnostic tests have been proposed which 

should help in judging a model's predictive behaviour. Russell and Dennis (2000) 

summarized these in the following way: 
74 Field Campaigns 

a) comparisons of predicted and measured outcome variables across many 

species, including predicted and observed correlational structure 

among/between species 

b) comparisons of in situ indicators or ratios of species that probe or illuminate 

chemical processes 

c) indicator tests that probe the dynamic response surface of model sensitivity, 

such as the NOx -VOC sensitivity measures 

d) model sensitivity and uncertainty analyses. 

3.4.8.1 Photochemical model simulations - What has been 

done? 

On May 13 thermally induced southerly winds developed transporting the urban 

plume of Milan to the north towards the Alps. The highest peak ozone values of 

the observation period were reached with 190 ppb, measured at the ground 

station Verzago 30 km north of Milan. This situation was chosen as the test case 

for the model community in the project. Table 5 gives some parameters of the 

different model systems, which were used to simulate May 13. The European Air 

Pollution Dispersion Model (EURAD) group of the Institute for Geophysics and 

Meteorology, University of Cologne, simulated the same period on a larger 

European scale to provide boundary conditions for the smaller regional models. 

However, some model groups used other approaches. 

Table 5. Photochemical models which simulated the situation in the Po Valley on May 13, 1998. 

Model name Meteorological module Chemical module 

 Vertical 

layers 

(lowest 

layer) 

boundary 

conditions; 

nudging 

Vertical 

layers 

Chemical 

Mechanism 

Species 

boundary 

conditions 

Ref. 

KAMM/DRAIS 25 (20 m) Const. 

Geostrophical 

wind 

 RADM2 Derived 

from 

averaged 

emissions 

(Hammer 

et al., 

2002) 

TVM 24 (25 m) Vertical 

sounding 

Linate airport 

15 LCC 1-D model 

calc. over 

8 days 

with av. 

emissions 

south of 

Milan 

(Martilli 

et al., 

2002) 

TVM 25 (25 m) ECMWF 15 LCC EURAD 

aircraft 

data 

(Dosio et 

al., 2002) 

UAM-V variable SM; Ground 

stations, 

windprofiler 

8 CBM-IV EURAD (BärtschRitter et 

al., 

2003b) 

MM5-TAPOM 31 (30 m) ECMWF 16 RACM Measurem

ents 

(Thunis, 

2001) 
LOOP Final Report 75

The following gives a short summary of the work done by the various groups. A 

comparison and discussion on some aspects is then given below. 

KAMM/DRAIS (Hammer et al., 2002). 

The work deals with the usefulness of the indicator H2O2/HNO3 to separate 

NOx-sensitive and VOC-sensitive regions. They performed model 

simulations for two regions in Germany (Baden-Württemberg, Berlin) and 

the PIPAPO domain and developed a new procedure to derive the transition 

value. 

TVM (Martilli et al., 2002) 

A simulation for May 13, 1998 was performed. Model results and 

measurements were compared for several monitoring stations. The sensitivity 

of the ozone formation toward the reduction of VOCs and/or NOx is 

investigated and transition values for indicator species were determined. 

TVM (Dosio et al., 2002) 

A simulation for May 13, 1998 was performed. Model results and 

measurements were compared for several monitoring stations and aircraft 

measurements. A focus is put on the complex circulation patterns of air 

masses in this region and their influence on air pollution. 

UAM-V (Bärtsch-Ritter et al., 2003b) 

A simulation for May 13, 1998 was performed. Model results and 

measurements were compared for several monitoring stations and aircraft 

measurements. The influence of the emission inventory on ozone production 

and ozone formation sensitivity is studied. 

UAM-V (Bärtsch-Ritter et al., 2003a) 

A sensitivity study of the base case simulation of May 13, 1998 was 

performed. The influence of the meteorological parameters temperature, 

humidity, mixing height and wind speed on NO2 and photo-oxidant mixing 

ratios as well as on the ozone formation sensitivity was investigated. 

Furthermore, the effect of the spatial resolution of the emission inventory on 

ozone concentrations and the limitation question was addressed. 

MM5-TAPOM (Thunis, 2001) 

A simulation for May 13, 1998 was performed. The influence of the grid size 

and two different emission inventories on ozone mixing ratios and ozone 

formation sensitivity was studied. 

3.4.8.2 Photochemical model simulations - Evaluation with 

respect to: 

a) Meteorology 

There are two pollutant transport terms, an advection term, in which pollutants 

are carried along with the time-averaged mean wind flow, and a dispersion term 

representing transport due to turbulence. The advection term determines the 

amount of pollutants captured over an emitting region and the distance an urban 
76 Field Campaigns 

plume is transported. The turbulent mixing and the so-called mixing depth are 

critical to the vertical transport of pollutants, the horizontal plume dispersion and 

dry deposition in the PBL. 

Dosio et al. (2002) compared various ground stations and aircraft measurements 

with modelled wind velocities and direction as well as temperature. The stations 

were grouped into two classes (stations in Po Basin, stations in pre-alpine and 

alpine areas) and a statistical analysis was performed. The bias and the root mean 

square error were determined as functions of time. For the stations in the Po 

Basin good agreement was found for the wind velocity and direction. 

Martilli et al. (2002) and Bärtsch-Ritter et al. (2003b) compared the arrival time 

of the high ozone urban plume at Verzago with the model result. Both models 

showed such an urban plume transit near Verzago by about one hour delay. Thus, 

wind direction seems to be well captured by the models and at measured wind 

velocities of 2-3 m/s in this region the delay is still within an uncertainty of 20%, 

which can be rated as good. 

The development of the mixing height, which strongly influences the dilution of 

the emissions, was compared with measured 222Rn concentrations. On a time 

scale of days a constant ground emission rate of 222Rn can be assumed. Figure 14 

shows a comparison of the measured 222Rn activity and the mixing ratio of an 

inert tracer, which is emitted at a constant rate. This indicates, that the UAM-V 

model simulates the increase of the mixing height quite well for that day. 

Figure 32. A simulation of 222Rn (Bq m-3) on May 13 with measurements at the ground station Brera 

(crosses). (from Bärtsch-Ritter (2002). A constant surface emission of 72 Bq m-2 h-1 was assumed for the 

simulations. 

b) Emissions 

A comparison between the emission inventory and measurements yielded some 

discrepancies, as for instance the CO/NOx emission ratio in the urban and nonurban areas (see above). From a comparison between measurements and model 

calculated CO mixing ratios in the urban plume it was concluded, that the CO 

emission rate of the inventory must be underestimated by at least a factor of 1.8 

Time (CET)
LOOP Final Report 77

(Bärtsch-Ritter et al., 2003b). These authors then modified the emission 

inventory based on observations described by Dommen et al. (2003). A 

simulation with this modified emission inventory predicted similar peak ozone 

values in the urban plume and only small differences in the ozone distribution in 

the domain. However, better agreement was obtained for hydrogen peroxide, 

which is one of the test species for diagnostic evaluations of model performance 

(see paragraph c). Thus, there is evidence, that a discrepancy between the 

emission inventory and real emissions might be the reason for the incompatible 

behaviour of H2O2 between model and measurements. Sensitivity analyses of 

meteorological parameters showed, that their influence on peroxide formation is 

lower (Bärtsch-Ritter et al., 2003a). 

c) Chemistry 

Martilli et al. (2002) and Bärtsch-Ritter et al. (2003b) compared many species 

between model and measurements. Both models predict an urban ozone plume of 

similar magnitude near the Verzago station, where it was observed. However, 

other species did not show such a good agreement. This is a good example, 

which shows that a comparison of ozone alone may be misleading. Martilli et al. 

(2002) obtained agreements with measurements for O3, NOy and VOCs, an 

underestimation of NO, NO2, CO and an overestimation of PAN, HNO3 and 

H2O2. Bärtsch-Ritter et al. (2003b) obtained agreements with measurements for 

O3, NOy, HCHO and PAN, CO was strongly underestimated. Two features, 

which are good indicators of the photochemical processes in an urban plume 

were not modelled correctly; hydrogen peroxide concentrations increased in the 

plume concurrent with the ozone while observations showed a decrease and NO2

did not increase during the plume event in Verzago as observed. These 

discrepancies might indicate a bias of the models toward NOx sensitivity. One of 

the reasons for these discrepancies could be the differences observed between 

emission inventory and measurements (see 3.4.4.2). Therefore, these authors 

performed simulations with an emission inventory modified according to 

observations. These simulations showed only small differences in the ozone 

distribution in the domain and predicted similar peak ozone values in the urban 

plume, but no elevated peroxide mixing ratios anymore (see Figure 33). 

The response on the VOC-NOx sensitivity using either the original or the 

modified emission inventory shows only marginal differences in the NOx

sensitive areas outside the urban plume, whereas the ROG sensitivity of the 

plume is enhanced there using the modified emissions. 
78 Field Campaigns 

Figure 33. H2O2 mixing ratio simulated with the UAM-V. The circle points to the position of the urban 

plume. Simulation with the original emission inventory (a) and with the modified emission inventory (b), 

(from Dommen and Ritter (2002)). 

3.4.8.3 Comparison of photochemical model simulations 

Figure 34 shows the spatial distribution of the ozone mixing ratio at 4 p.m. (LT) 

on May 13 simulated by three models, TVM, UAM-V and TAPOM. The first 

two models used a grid size of 3x3 km2

 compared to 4x4 and 10x10 km2 of the 

last one. Predicted and observed ozone values are high in the Po Basin with over 

100 ppb. The TVM, UAM-V models simulate an ozone peak of more than 180 

ppb about 30 km north of Milan close to Verzago, where a peak ozone value of 

195 ppb was observed on that day. The TAPOM model predicts an ozone plume 

a) 

b) 
LOOP Final Report 79

of 170 ppb only 15 km to the west/north-west of Milan. This model has problems 

to represent the wind field correctly. 

Figure 34. Ozone mixing ratio for May 13, 1998, 4 p.m. simulated with the TVM (a) (Martilli et al., 

2002), UAM-V (b) (Bärtsch-Ritter et al., 2003b), TAPOM (Thunis, 2001) for (c) a 10x10 km 2

 and (d) 

4x4 km 2

 grid size. TVM and UAM-V have a grid size of 3x3 km 2. 

Reduction scenarios were calculated with all three models, whereby 35% of NOx

or VOC emissions were reduced. Figure 35 presents the difference of the ozone 

mixing ratios (O3) between those simulations, i.e., O3(VOC-reduction) minus 

O3(NOx-reduction). Thus, a positive value of O3 represents a NOx-sensitive 

chemistry and a negative value a VOC-sensitive chemistry. The TVM calculates 

a small VOC-sensitive region of about 15 km width north of Milan while the 

UAM-V predicts a large area north of Milan from Lake Maggiore to the right 

domain boundary as being VOC-sensitive. The TVM and TAPOM did not 

consider point emission sources. In the UAM-V simulations point sources have a 

pronounced effect on the extension of this VOC-sensitive area. The TAPOM 

simulation shows no VOC-sensitive region in the domain for 10x10 km 2

 grid 

resolution. It has a VOC sensitive region in the case of a 4x4 km 2

 grid size, 

whereby for this calculation VOCs and NOx where reduced by 40% each. There 

are various facts which could explain the weaker VOC sensitivity of the TAPOM 

a) b)

c) d) 
80 Field Campaigns 

e.g., a) the emissions downwind of Milan are important, which might be smaller 

along the urban plume trajectory to the north-west of this model; b) the lower 

grid resolution; c) since the model domain of TAPOM is larger than that of the 

other two models, emissions are also reduced on a larger scale, while boundary 

conditions were kept constant in the TVM and UAM-V. 

 

Figure 35. VOC control minus NOx control ozone mixing ratio for May 13, 1998, 4 p.m. simulated by 

TVM (a) (Martilli et al., 2002), UAM-V (b) (Bärtsch-Ritter et al., 2003b) and TAPOM (Thunis, 2001) for 

(c) a 10x10 km 2

 and (d) 4x4 km 2 grid size. TVM and UAM-V have a grid size of 3x3 km 2. (a)-(c) 

calculated a 35% reduction, (d) a 40% reduction of NOx or VOCs. 

3.4.8.4 Sensitivity analyses of photochemical model 

simulations 

A sensitivity analysis by Bärtsch-Ritter et al. (2003a) assessed how changing 

various parameters would impact predictions of ozone mixing ratios and the 

VOC-NOx sensitivity of the ozone production. Sensitivity analysis aids in the 

development of uncertainty estimates about a models predictions due to 

uncertainties in the inputs. It may also help to generalize the model results to a 

certain degree. 

a) b)

c) d)
LOOP Final Report 81

 The following parameters or combinations of them were varied: mixing 

height, temperature, humidity, temperature and humidity, wind speed. The 

following trends were obtained: 

 The VOC-sensitive areas increase with higher temperatures, mostly because 

of lower PAN formation at higher temperatures. 

 Increased humidity leads to increase of the NOx sensitive areas. 

 An increase of humidity and temperature also leads to more NOx sensitive 

conditions. 

 With increasing wind speed, emissions get more evenly distributed in the 

whole modelling area and the situation also becomes more influenced by the 

boundary conditions. VOC sensitive areas increase with elevated wind 

speeds, while simulations without point sources tend to increase NOx

sensitive areas. 

In summary, for each of the meteorological variations performed in this 

sensitivity study, the modelled ozone plume remains VOC sensitive. The 

variations were fairly large and should well cover uncertainties of these 

meteorological parameters. 

3.4.8.5 Influence of the spatial resolution of the emission 

inventory 

Spatial resolution in air pollution and meteorology modelling has always been a 

crucial issue. Ideally, simulations should use a resolution as fine as possible and a 

domain as large as possible to capture all processes. Unfortunately, this is 

prevented by CPU limitations. Therefore a compromise must be found between 

the resolution and the extent of the domain we want to simulate. The key issue 

consists thus in identifying the size of the relevant processes to determine the 

optimal scale and resolution. Thunis (2001) and Bärtsch-Ritter et al. (2003a) 

investigated which resolution is necessary to simulate the relevant processes in 

air quality modelling around cities. It might well happen that a coarse resolution 

leads to the prediction of a different emission reduction strategy. This could have 

fatal implications on ozone abatement strategies. 

Peak ozone values were similar for a resolution up to 10 x 10 km2

. At lower 

resolution peak ozone decreased by as much as 20% at a resolution of 50 x 50 

km 2

 while it increased in the urban areas and the Po Basin area of the model 

domain. 

When the grid size is increased the ozone reducing effect in VOC sensitive areas 

strongly decreases. The TAPOM model has already no VOC sensitive area at a 

grid resolution of 10x10 km2

 (Figure 35c). The UAM-V shows only a slight 

increase of the number of NOx sensitive grid cells up to 27x27 km2

. At 54x54 

km2

 only a small area remains VOC sensitive (Figure 36a). Without point 

emission sources no VOC sensitive area is predicted for a grid size of 54x54 km2

(Figure 36b). 
82 Field Campaigns 

Figure 36. VOC control minus NOx control ozone mixing ratio for May 13, 1998, 4 p.m. simulated by 

UAM-V (Bärtsch-Ritter et al., 2003b) with a grid size of 54x54 km2

; (a) with (b) without point emission 

sources. 

3.4.9 Summary of scientific findings of the PIPAPO experiment 

The main goal of the PIPAPO field campaign was to describe the spatial and 

temporal dynamics of the NOx/VOC sensitivity in the plume of the Milan 

metropolitan area. This can only be reached with models that have been proven 

not only to reproduce well the ozone distribution in space and time, but also the 

correct sensitivity to changed emission rates. However, a comparison with 

experimental data can be based on the base case model run only. Sensitivity runs 

are thus simulating situations that do not correspond to the real situation, and can 

a) 

b) 
LOOP Final Report 83

therefore not be validated with measurements. This situation is a dilemma, as a 

validation of sensitivity runs with field data cannot be performed. Reasons for 

deviations between modelled and measured values must be assessed, and it must 

be evaluated whether the causes for the deviations are affecting the sensitivity. 

GCMs need not only correctly predict ozone concentrations but also other 

secondary pollutants, such as PAN, peroxides, and HNO3. 

3.4.9.1 Indicators 

The comparison of measured indicator values with ozone concentration 

sensitivities at Verzago (see section 3.4.6.3) suggests that the transition values 

were in agreement with those defined by Sillman (1995a). However, the data 

base is small and should not be generalized. Analyses with 3D-models revealed 

that the transition values for the indicators are very sensitive to the chosen 

boundary conditions, especially for the small domain. It could well be that 

transition values in the real world are close to those suggested by Sillman 1995. 

In the simulations however, the transition values show a larger scatter due to 

systematic differences between individual models (e.g., how inflow peroxide 

concentrations are determined etc). Recently, a suggestion for adapting the 

original indicator concept has been made (Sillman and He, 2002). It is 

recommended to use the changes of indicator values during a given transport 

time rather than absolute values. 

3.4.9.2 Influence of aerosols 

Photochemical smog episodes are accompanied by high aerosol loads, with an 

important contribution from secondary aerosols. The high radical level associated 

with photochemical smog favours the formation of secondary aerosols, both 

inorganic and organic. The aerosol measurements have confirmed the large 

contribution from secondary aerosols (see section 3.4.7). However, a simple 

description of the aerosol in a kind of a flow reactor downwind of Milan cannot 

be expected due to the patchy emissions. Fresh emissions are always mixed into 

chemically aged air masses. The NH3 emissions are one of the driving forces for 

the inorganic aerosol formation. However, an adequate spatially and temporally 

resolved emission inventory was not available, and atmospheric NH3

concentration measurements to validate the plausibility of such an inventory do 

not exist. Aerosol formation in the model world has a very minor influence on 

ozone formation. The two most important processes that couple the photooxidant and aerosol formation are not yet in the models: there is no feedback of 

the aerosol levels on the radiation properties, and there is no reaction of radicals 

with aerosol surface or within water droplets. E.g., the plume that arrived in 

Verzago in the early afternoon caused a 10% drop of the JNO2 values at the 

surface. 

3.4.9.3 Role of vertical mixing 

The representation of the vertical mixing in the models has an important 

influence on the VOC/NOx sensitivity. In the analysis of Spirig et al. (2002), 

model calculations predicted a NOx sensitive O3 production in the residual layer 
84 Field Campaigns 

earlier in the day. LIDAR measurements on the ARAT aircraft confirm that there 

was an increase in O3 concentration above the mixing layer. The analysis of the 

flight in the morning of June 2 (0930 LST to 1030 LST) indicates a mean net 

ozone production decreasing from 10 to 2 ppb/h, going from 700 m asl to 1200 m 

asl. However, these increases are not significant due to the large scatter of the 

data. We cannot determine whether the ozone production in the residual layer is 

due to remaining precursors or due to fresh emissions, because we have no direct 

information on the vertical profiles of the parameters driving the ozone 

formation, i.e., NO and the ODD-H levels. But it is evident that ozone produced 

in the residual layer earlier in the day would influence the sensitivity of the O3

concentration at the surface in the afternoon, most likely in an accentuation of 

NOx sensitivity. The sensitivity analysis by Bärtsch-Ritter et al. (2003a) showed 

a lower ozone peak in the urban plume and a smaller spatial extension of this 

plume as a result of higher mixing layers. Increasing the mixing layer increased 

the number of NOx sensitive grid cells. 

3.4.9.4 Scale considerations 

The PIPAPO field campaign showed that the relevant spatial scale for the ozone 

production in the Milan plume is 10 to 30 km. Peak values of ozone, secondary 

aerosols, and other photo-oxidants are reached within a few 10 km from the 

major emission sources. It is on this scale that reduction strategies have to be 

assessed. PIPAPO looked at two periods of only a few days. Extrapolation of the 

analysis to the seasonal scale relevant for reduction strategies and application 

was not in the scope of the PIPAPO activity. Nevertheless, we are convinced that 

the model approaches used in the PIPAPO studies can be extended to longer time 

scales to get the integrated NOx/VOC sensitivity for the whole summer. 

However, it is essential to use a sufficient spatial resolution in the models (see 

section 3.4.8.5) for this task. The analysis also shows that the measuring network 

in the Po Basin should be complemented by indicator species in order to get an 

independent approach of the spatial and temporal variability of the ozone 

production sensitivity based on field measurements. 

The situation in the Milan area calls for a second project focused on the 

interaction of secondary aerosol formation and photo-oxidant production. 

Because the highest aerosol levels are found during the stagnant winter 

conditions, the measurements should also include winter campaigns. 

Acknowledgements 

Financial support through the commission for technology and industry (KTI) 

(Eurotrac-2 project LOOP), and the Swiss Agency for the Environment, Forests 

and Landscape (SAEFL) (Project “Biogene Aerosole”) is greatly acknowledged. 

Various institutions of the Lombardy region helped to organize the campaign. 

We especially thank Dr. Matteo Tamponi and Dr. Guido Lanzani for their 

enthusiastic support before and during the PIPAPO field campaign. Thomas 

Staffelbach built up the PIPAPO database and Marx Stampfli 

(www.mathematics.ch) developed the data visualization tool. 
LOOP Final Report 85

3.5 Atmospheric pollution over the Paris area: the 

ESQUIF project 

Matthias Beekmann 

Institut Perre et Simon Laplace, Service d’Aeronomie, Paris, France 

Laurent Menut 

Laboratoire Interuniversitaires des Sciences Atmospheriques (LISA), France 

3.5.1 General introduction to the campaign 

ESQUIF (“Étude et Simulation de la QUalité de l'air en Ile de France”, a French 

acronym for “Air quality study and modelling over the Paris area”) is the first 

comprehensive project dedicated to the study of air pollution in the French Ile de 

France region, with Paris in its centre (Menut et al., 2000). The project has been 

initiated jointly by the Institut Pierre Simon Laplace (IPSL) and the Laboratoire 

Inter-universitaire des Systèmes Atmosphériques (LISA), and the partnership 

was extended to the Laboratoire d'Aérologie, the Forschung Zentrum of Jülich, 

AIRPARIF (the local air-quality monitoring network) and Météo-France. The 

project was carried out over three years (1998-2000). The project was 

coordinated by Robert Vautard (Laboratoire de Meteorologie Dynamique, IPSL). 

Besides the chemical and physical understanding of pollution episodes, ESQUIF 

also aims at the validation of existing models dedicated to pollution analysis, 

scenarios and forecast, by establishing a comprehensive and thorough database. 

The particular interest of the Paris area stems from its geographical situation: It is 

a large city located far (by about 200 km) from other densely populated areas. It 

is therefore in principle easier than for other European cities to distinguish the air 

masses charged with locally emitted pollutants from those charged with 

pollutants emitted in remote areas. Another geographical interest of the Paris area 

is its low topography, which in the absence of local forcing makes the 

accumulation / dispersion of pollutants more complex. 

More specifically, the ESQUIF project focuses on several research issues, the 

most important ones being listed here: 

The thermodynamics of the boundary layer in and around a big city: The 

main questions are (a) the role of the vertical structure of the boundary layer 

and the turbulent mixing processes in the occurrence of pollution episodes, 

and (b) whether models are able to simulate the air flow, its vertical structure 

and the surface fluxes encountered during low dispersion episodes, and, if 

not, how to improve the various parameterisations used within the models. 

The photochemistry of pollutants: the focus here is essentially on the 

relationship between local photochemical ozone build-up and anthropogenic 

and biogenic emissions; this question includes the investigation of the 

chemical regime in the Paris area (VOC or NOx limited) and is thus strongly 
86 Field Campaigns 

linked to the LOOP question. This question also includes the evaluation of 

existing emission inventories using measurements acquired during the 

campaign. 

The transport of pollutants at the interface of the urban/regional and the 

continental scale: both the inflow of pollutants into the Ile de France region 

and the fate of the plume outside of the region have been evaluated. 

The physical and chemical evolution of urban and suburban aerosols and 

their impact on photolysis frequencies. 

The measurement campaign started during summer 1998, and lasted until the 

winter 1999-2000: eleven episodes of 1-5 days duration, denoted hereafter the 

ESQUIF IOPs (Intensive Observation Periods) and representative for different 

weather situations implying enhanced photochemical activity have been 

documented by measurements and simulations. 

Following the ESQUIF objectives, the campaign consisted both in aircraft and 

ground-based measurements. The latter included routine measurements by the 

local air quality network AIRPARIF and dedicated measurements by a equipped 

van, by lidar systems or by a DOAS system. For airborne measurements, various 

flight plans were defined: the flights aiming at documenting the spatial ozone 

distribution in loops around the city at various distances from the centre, the “city 

plume”' flights aiming at following the urban plume, and the “chemical regimes'' 

flights consisting in iso-latitude regular legs over the Paris area. The large body 

of experimental data gathered during these flights includes measurements of 

gaseous pollutants (O3, NO, NO2, PAN, HONO, NOy, SO2, CO, VOC’s and 

HCHO), aerosol parameters (chemical composition, size distribution, optical 

parameter as extinction coefficient), radiative parameters like the NO2 photolysis 

frequency and meteorological parameters (winds, humidity, boundary layer 

height etc.). 

The ESQUIF campaign also allowed a detailed evaluation of chemistry-transport 

and meteorology-chemistry models which were in part developed in parallel to 

the project (AZUR (LISA), CHIMERE (IPSL), MESO-NH Chimie (Laboratoire 

d’Aerologie), MOCAGE (Meteo France). 

More detailed information about the outset and major results of the campaign can 

be found on the ESQUIF website (http://esquif.lmd.polytechnique.fr) and in peer 

reviewed articles (see publication list). 

3.5.2 Overview of results relevant for the LOOP project 

In the following, some results that are especially relevant for the LOOP project 

will be highlighted. 

The sensitivity of local ozone build-up to VOC and NOx emissions was evaluated 

in several model studies: For instance, simulations with the AZUR model 

(LISA), driven by ECMWF meteorological data, indicate a clearly VOC limited 

chemical regime in the pollution plume downwind of Paris for August 8 and 9 

during IOP 2. In this study (and in the following text), the chemical regime is 

always determined by the difference in ozone levels within the urban plume 
LOOP Final Report 87

simulated for 30% reduced VOC and NOx emissions. This result is confirmed by 

corresponding simulations with another chemistry-transport model, CHIMERE 

(IPSL), but using, among others, a different chemical mechanism (MELCHIOR 

instead of MOCA) (Derognat et al., 2002). For another IOP (July 16-17/ 7 1999), 

simulations with the base case version of CHIMERE also yield a VOC limited 

regime, but a NOx limited regime for July 18. For this period , additional 

numerical experiments were performed in order to evaluate the degree of 

confidence that can be put into chemical regime simulations (Sillman et al., 

2002). When simultaneously increasing VOC emissions by 40% and decreasing 

NOx emissions by 30%, a NOx limited chemical regime is simulated for July 17, 

instead of the VOC limited regime for the base case simulations (Sillman et al., 

2002). Moreover, O3/ NOy scatter plots show a better agreement between 

simulations and measurements for the modified case. This shows the potential of 

uncertainty in factors like emissions, and in particular in the VOC / NOx

emission ratio, to make simulations of the chemical regime uncertain for specific 

days. The question now is whether such large changes in the emission ratio (by a 

factor of two) as applied in this study, are compatible with uncertainty in 

emission data bases. A comparison between simulated and measured VOC and 

NOy species for the whole set of afternoon flights performed during ESQUIF 

allows to give uncertainty bounds on emissions (Vautard et al., 2002). For these 

simulations, the CHIMERE model was modified in order to take into account 

transport and chemical loss for each of the more than 30 VOC species measured 

on the DIMONA and AZTEC aircraft and specified in the emission profiles 

provided by IER (R. Friedrichs), University of Stuttgart. This study does not 

make evident any significant bias in the NOx and VOC emission data base used, 

but fixes their uncertainty bounds (90% confidence level) at respectively 35 and 

40% (Vautard et al., 2002). However, only a third to a half of individual VOC’s 

specified in the emission data base were measured. Thus, the uncertainty in the 

total VOC / NOx emission ratio may be somewhat larger than indicated in the 

present study, and an increase by a factor of two, as applied in the Sillman et al.

study, still could be realistic. A more formal uncertainty analysis was performed 

with the CHIMERE model using Bayesian Monte Carlo analysis and taking into 

account uncertainty in model input parameters as emissions, meteorological data 

and chemical rates coefficients (Beekmann and Derognat, 2002). This type of 

analysis is able to take into account the measurement constraint, i.e., only Monte 

Carlo simulations comparing sufficiently well with observations are retained as 

realistic. It allows to make probabilistic statements about chemical regimes. For 

July 17, the chemical regimes are found to be NOx limited with 60% probability, 

again showing as in the Sillman (2002) study that a NOx limited regime better 

fits with measurements than a VOC limited one for this day. Certainly, such 

probabilistic statements are to some extent uncertain themselves due to the fact 

that the initial uncertainties in input parameters cannot be determined precisely. 

Nevertheless, sensitivity tests, with alternative input parameter uncertainties, 

prove them to be qualitatively correct. 

The model sensitivity of ozone build-up for another CTM (similar to CHIMERE 

and AZUR) with respect to emissions, rate constants and meteorological 

parameters was determined using the adjoint technique (Menut, 2002). This 
88 Field Campaigns 

technique allows the evaluation of a whole set of temporally resolved 

sensitivities for infinitesimally small changes of different parameters in only one 

simulation. For example, the ozone level at the suburban site Rambouillet at 15 

UT (near the centre and time of the urban plume ozone maximum) is positively 

sensitive to NO emissions occurring between 10 and 15 UT, but negatively 

sensitive to those occurring before 10 UT (yielding a very small integrated 

sensitivity). The sensitivity to reactive VOC emissions like alkenes and aromatic 

compounds peaks at 6 UT and 10 UT, indicating a several hours time scale of 

ozone build-up and transport between the urban emissions regions and the 

suburban site. 

The impact of biogenic VOC (isoprene and terpene) emissions on ozone levels in 

the urban plume was assessed in another specific study (Derognat et al., 2002). 

Biogenic VOC emission data bases for the continental scale were elaborated 

using the methodology and emission factors outlined in Simpson et al. (1999). 

For the Ile de France region, additional information from the high resolution 

USGS data base (1 km) and form species distributions given by the Office 

National des Forets was taken into account, and could be evaluated with isoprene 

measurements taken with online gas-chromatography on board of the METAIR/ 

DIMONA aircraft. The maximal impact of biogenic VOC emissions on ozone 

peaks in the urban plume varied between 3 and 40 ppb, with a median of 9 ppb, 

for all simulated intensive days during the ESQUIF campaign. The most 

important determining factor was temperature (higher T increasing biogenic 

emissions) and local NOx levels (higher NOx increasing ozone build-up from 

BVOCs). A bit more than a half of the effect was due to BVOC emissions 

outside of the Ile de France region, enhancing ozone advected to the Ile de 

France area. For the IOP2 period (August 6-11, 1998), it also could be shown 

that biogenic emissions rendered the chemical regime less VOC limited, but 

without changing it to NOx limited. Indeed, the mean difference between 

afternoon ozone levels for 35% NOx emission and VOC emission reductions 

averaged over the plume decreased from 25 ppb to 15 ppb. 

More detailed results concerning chemical regime simulations for the whole 

summers 1998 and 1999 are presented in the next section. 

3.5.3 Climatology of the chemical regime in the Paris - Ile de 

France region – a model simulation 

In order to assess the climatological occurrence of VOC or NOx limited chemical 

regimes in the ozone plume of the Paris agglomeration, we performed a 

climatological simulation during two summers (respectively from May to 

September 1998 and 1999) using the CHIMERE regional model with reference 

simulations and with either anthropogenic NOx and VOC emissions reduced by 

35%. CHIMERE regional (Vautard et al., 2001) is a chemistry and transport 

model covering a domain of 150x150 km around Paris and driven by ECMWF 

meteorological data. It is imbedded in the CHIMERE continental model covering 

Western Europe (Schmidt et al., 2001, http://euler.polytechnique.fr/chimere). 

The study is part of Claude Derognat's thesis work (Derognat, 2002). 
LOOP Final Report 89

Results of simulations are displayed as relative changes in OX (O3+NO2) for two 

emission scenarios, NOx Ile de France emissions –35% and VOC Ile de France 

emissions –35%: 

Eff (Ox Ox )/(Ox -Ox ) E E 35% E 35% ref noemis

E

VOC NOx VOC

NOx

  

where OX

noemis designs a simulation without Ile de France emissions allowing to 

determine Ox produced from Ile de France emissions (local OX build-up). For 

each day at 15 UT, OX is averaged for different distances from the Paris centre 

(6-20 km, 20-40 km, 40-60 km) for points with large local OX build-up. Positive 

values of the term above correspond to a VOC limited chemical regime. 

Figure 37 shows that independently of the distance, the chemical regime is either 

VOC limited, or intermediate (i.e., when differences are below about 10%) 

(Derognat, 2002). Days with frankly NOx limited regimes apparently do not 

occur in the simulations. Interestingly, for days with local OX build-up below 20 

ppb (grey bars), the chemical regime becomes more VOC limited for larger 

distances from the agglomeration. This feature differs from the general view, that 

the chemical regime should become more and more NOx limited with larger 

distances from the sources. On the contrary, in particular for days when cloud 

cover reduces actinic fluxes and radical production by photolysis, and when 

photochemical ozone production is not very strong, positive feedbacks 

apparently strengthen the VOC limited regime over time. Nevertheless, it is 

expected that at still larger distances, but which are outside the model domain, 

the chemical regime finally switch to NOx limited. 

We next question, weather CHIMERE is able to correctly simulate the chemical 

regime. For this purpose, we compare for four different flights performed during 

the ESQUIF campaign simulated and measured O3/ NOz scatter plots (Figure 38). 

For two of the days the simulated O3/ NOz slope is underestimated by 

CHIMERE, while it is overestimated for another day. This does not allow to 

conclude on any bias in the simulated chemical regimes. Nevertheless, as also 

was shown in the previous section by means of Monte Carlo analysis, still a 

significant uncertainty in the chemical regime subsists, especially for 

intermediate regimes (Beekmann and Derognat, 2002). This has also been shown 

by an analysis for a particular day of the ESQUIF campaign, July 17, 1999 

(Sillman et al., 2002). 

We next seek for reasons for the day-to-day variability in the chemical regime. A 

linear correlation analysis shows that among many parameters tested, the ozone 

concentrations advected into the model domain and the inverse of wind speed are 

best correlated with the chemical regime. Figure 39 shows the chemical regime 

as defined above, but at a distance comprised between 40 and 60 km from town 

centre, as a function of these two parameters. 
90 Field Campaigns 

Figure 37. Predicted reduction in Ox (in %) resulting from a 35% reduction in the emissions rate for 

anthropogenic VOC minus reduction in Ox (in %) resulting from a 35% reduction in the emission rate for 

anthropogenic NOx, averaged for different distances from the Paris centre (6-20 km (a), 20-40 km (b), 40-

60 km (c)) for points with large local Ox build-up and plotted for each day of spring-summer (MayAugust) 1998 and 1999. 

a) 

b) 

c) 
LOOP Final Report 91

Figure 38. Ozone mixing ratios plotted over the NOz (NOy – NOx), for measurement collected by the 

DIMONA plane (crosses) during IOPs of the ESQUIF campaign (Menut et al., 2000) or predicted 

(triangles) by the CHIMERE model and interpolated over the flights. 

Figure 39. Predicted reduction in Ox (in %) resulting from a 35% reduction in the emission rate for 

anthropogenic VOC minus reduction in Ox (in %) resulting from a 35% reduction in the emission rate for 

anthropogenic NOx, as a function of ozone concentrations advected from the large scale and the inverse of 

wind speed (averaged values for a distance comprised between 40 and 60 km from the Paris centre and 

for points grid with large local Ox build-up) and plotted only for the clear sky days of spring-summer 

(May-August) 1998 and 1999.
92 Field Campaigns 

As expected, the chemical regime has a tendency to become more NOx limited 

for advected high ozone concentrations and for strong wind speeds. Indeed, on 

one hand, photolysis of imported ozone is an important radical source favouring 

the occurrence of NOx limited regimes. On the other hand, the inverse of wind 

speed is well correlated with NOy, which has been used as an indicator of the 

chemical regime (low NOY = strong wind = NOx limited). Both parameters alone 

explain already about 50-60% of the variability in the chemical regime. Other 

parameters (direction of the plume, temperature triggering or not biogenic 

emissions, humidity, etc. may account for the rest of the variability. 

Acknowledgements 

The ESQUIF project has been supported by the Ministère de l'Aménagement du 

Territoire et de l'Environnement, the Conseil Régional Ile de France and ElfAquitaine. 
LOOP Final Report 93

3.6 ESCOMPTE 

B. Cros 

Laboratoire d’Aerologie, Toulouse, France 

P. Durand 

METEO-FRANCE, Toulouse, France 

S. Pinceloup, G. Laverdet, G. Le Bras 

CNRS-LCSR, Orléans, France 

P. Perros, Isabelle Coll 

LISA, University of Paris 12, Creteil, France 

3.6.1 General framework of the ESCOMPTE programme 

In order to help in designing ozone abatement policy, development of combined 

photochemical and dynamical models is essential to better understand and 

forecast air pollution events over urbanized and rural areas. There is presently an 

important effort in developing and improving meso-scale chemistry-transport 

models, the more advanced ones involving an aerosol scheme. Preliminary work 

confirms the important contribution of the regional scale processes to the 

pollutant concentrations observed at the local scale. This is particularly true for 

ozone which concentration depends on reservoir species likely to be transported 

over long distances. Thus, comparisons of model output against field 

measurements require a detailed 4-D data base of primary pollutants emission 

together with the dynamics and chemical composition of the atmosphere. The 

ESCOMPTE field campaign (Cros, 2002) has been designed to provide us with 

this database for some pollution events. The main characteristics of the 

ESCOMPTE program can be found at the URL http://medias.obsmip.fr/escompte. 

3.6.2 The ESCOMPTE area and period 

An area around Marseille city and Berre pond, in the south-eastern part of 

France, has been selected to host the ESCOMPTE field campaign. This site of 

120kmX120km fulfils most of the conditions required for the project: strong 

pollutant sources (urban and industrial) within the experimental area and high 

occurrence of photochemical pollution events ; existence of a dense, operational 

pollution monitoring network; a channelling of pollutant plumes by sea-breeze 

circulations and terrain features. The experiment was conducted between June 

4th and July 16th, 2001. 

3.6.3 Experimental set-up 

The ground-based platforms, specifically deployed for the experiment, are 

represented on Figure 40. They involve 20 stations, equipped for gas (ozone, 
94 Field Campaigns 

nitrogen oxides, VOCs, ...) and/or particles measurements; among them, two 

were installed on ships, and two mobile stations (cars, not indicated on the Figure 

40) were placed according to the plume locations. The surface energy budget was 

measured on 9 sites to cover the landscape variety in the area ; among them, four 

were in the urbanized area of Marseille (Mestayer and Durand, 2002); at some 

sites, fluxes of trace gases (ozone, NOx) were also measured for 

emission/deposition velocities computation. 

Figure 40. Ground based measurement platforms of the ESCOMPTE campaign. 

The meteorological basic parameters (wind, temperature, moisture and radiation) 

were measured on the 9 abovementioned and on 5 complementary sites. Wind 

profile was continuously measured on 12 sites by 7 sodars, 4 UHF and 4 VHF 

radars. A scanning Doppler Lidar measured the 3-D wind field over the Marseille 

agglomeration. 3 upward pointing, and 2 scanning ozone lidars were set-up on a 

SW-NE axis (main breeze axis) through the domain. 4 radiosonde systems, 2 of 

them capable of ozone profiling, were activated during the Intense Observing 

Periods (IOPs). During these IOPs, the pollutants plumes were tracked by 33 

constant-volume balloons, launched in the boundary layer from the emission 

areas (Marseille city or Berre pond); they were equipped with radiosondes, some 

of them with an ozone probe. 7 aircraft were flown during pollution episodes; 4 

(DO 128 from IMK, FRG ; Fokker 27 from INSU, France ; Merlin 4 and Piper 

 Ozone Lidar profiler Radar (VHF or UHF) wind profiler Sodar (wind profiler) 

 Ozone scanning Lidar Surface chemistry (gaz or particles) 

 Radiosonde station 

Surface meteo. Station 

 Wind scanning Lidar Surface flux and meteo. station 

 ESCOMPTE : surface-based platforms
LOOP Final Report 95

Aztec 23 from Météo-France) were able to in situ document dynamics and 

chemistry ; a ULM from IFU (FRG) measured ozone, aerosol and UV radiation ; 

the Falcon 20 from DLR (FRG) embarked the Doppler lidar WIND ; and a Piper 

Aztec 28 embarked an IR camera for surface temperature characterization over 

the Marseille area. 

3.6.4 The campaign progress 

The first week was devoted to a QC/QA operation. This was completed by wingto-wing flights performed at the end of the campaign. 5 IOPs for a total of 15 

days were documented, two of them corresponding to breeze circulation with 

high pollution levels, and two characterized by a “plume regime”, with a 

channelling of the pollutants towards the eastern part of the domain. 

Side-projects: 

At the same place and during the same period two other scientific experiments 

were associated to ESCOMPTE. These side-programs UBL (Urban Boundary 

Layer) and GPS/H2O (Atmospheric water vapour tomography by GPS) benefited 

of the ESCOMPTE experimental environment but also usefully complemented 

some measurements of the main program. 

On-going studies: 

ESCOMPTE has to bring inputs on the following questions: 

what are the respective role of dynamics and chemistry on the pollution 

events? 

how to take into account urban emissions in regional or global models? 

can an operational model of pollution events be developed ? 

which strategy has to be set up in order to reduce photo-oxidant and particle 

concentrations? 

ESCOMPTE data base and data policy: 

From the ESCOMPTE program it is expected to put together a comprehensive 

and coherent database, allowing for testing and evaluating regional pollution 

models. The so-called ESCOMPTE database (EDB) is managed by MédiasFrance. It will involve the data collected during the 2001 campaign, the hourly 

emissions data for the ESCOMPTE IOPs and a background data set 

(meteorological data, data from monitoring networks on air quality, 

meteorological and chemical large-scale environment, satellite data, orography, 

surface coverage, etc.). 

The EDB access is restricted to the ESCOMPTE community until Apr. 2003. 

The data of the IOP3 (July 2nd – July 4th) will be hidden, even for the 

ESCOMPTE community, until Oct. 2003, in order to contribute to a model 

evaluation exercise. 
96 Field Campaigns 

3.6.5 Specific results: photochemical ozone production and 

chemical regime 

In this section, first “chemical” results from the ESCOMPTE campaign directly 

addressing LOOP objectives are presented. Photochemical ozone production 

rates are estimated from several techniques (radical measurements, PSS method, 

simulations). The local and integrated chemical regime is determined. Results 

from ESCOMPTE are at this stage more preliminary than those from other 

campaigns, but nevertheless they illustrate the potential of results that can be 

expected. 

3.6.5.1 Measurements of peroxy radicals and related species 

at a rural site during the ESCOMPTE Campaign 

Concentrations of peroxy radicals, RO2, NOx and ozone were continuously 

measured during the ESCOMPTE campaign at the rural site of Dupail. The site is 

located 35 km North-East of Marseille. Complementary measurements of 

aldehydes, peroxides, hydrocarbons were made by other groups. The aim of these 

measurements, especially those of peroxy radicals, was to contribute to better 

understand the photochemistry of ozone and to assess the contribution of local 

photochemical ozone production to the ozone budget. 

Peroxy radical concentrations were measured using the chemical amplifier 

technique. The influence of relative humidity on the chain length determined in 

the laboratory was taken into account. 

Daily profiles of RO2, NOx and ozone 

Daily profiles of the above species were recorded every day during the period 

14th June – 11th July 2001, including the 3 IOP (14 - 15th June, 21 – 26th June, 

2nd – 3rd July) periods. (Figure 41). 

The RO2 concentration peak occurs at around 14h (local time) with maxima 

of 80 pptv. The ozone peak occurs at 15h –16h. 

The NOx levels were most of the time lower than a few ppbv, ie 

characteristic of a rural site. 

Figure 41. Averaged profiles over the whole campaign, a) O3 and NOx, b) RO2. 
LOOP Final Report 97

Very different RO2 and ozone profiles were observed under different 

meteorological conditions: 

Case a : 18/06/01 Case b : 25/06/01 

Wind: North, North-East (mistral) Wind: South, South-East (breeze) 

Mean wind speed : 20 km/h Mean wind speed : 3,5 km/h

Maximum wind speed : 30 km/h Maximum wind speed : 11 km/h 

Tmean= 15,3°C Tmax = 20°C Tmean= 22,2°C Tmax = 31°C 

Figure 42. RO2 and ozone profiles under different meteorological conditions, a) in presence of mistral, b) 

in presence of breeze. 

Ozone concentration is almost The ozone profile is more usual 

constant throughout the day with daytime maximum 

(» 40 ppbv). There is no decrease High levels of ozone were observed 

of ozone during the night (loss by 

deposition is compensated by 

transportation over the site). 

The concentration of RO2 are low The concentrations of RO2 are high 

with a maximum of 40 pptv with a maximum of 180 pptv. 

Ozone production rate 

The ozone production rate, PO3, has been calculated using the radical budget 

method from the simultaneous measurements of NO and peroxy radicals: 

HO2 + NO  OH + NO2 (R 1) 

HO2 + NO  RO + NO2 (R 2) 

NO2 + h  NO + O (R 3) 

O + O2 + M  O3 + M (R 4) 

P(O3) = d[O3]/dt = k1 [HO2] [NO] + k2 [RO2] [NO] (with k1 k2 8.10-12 cm3

molecule-1 s-1). 

0

30

60

90

120

150

180

00:00 06:00 12:00 18:00 00:00

[RO2] (pptv)

0

20

40

60

80

100

120

140

[O3] (ppbv)

0

30

60

90

120

150

180

00:00 06:00 12:00 18:00 00:00

[RO2] (pptv)

0

20

40

60

80

100

120

140

[O3] (ppbv)
98 Field Campaigns 

Figure 43 shows the calculated P(O3) for the IOP of 21-26 June, where two 

different sets of values have been obtained : 

IOP 2a (21-23 June): P(O3) : up to 40 ppbv h-1 corresponding to relatively 

clean air masses advected over the site from NW wind. 

IOP 2b (24-26 June): P(O3) : up to 100 ppbv h-1 corresponding to polluted 

air masses originating the Marseille and Etang de Berre areas. 

0

50

100

150

200

250

21/06 22/06 23/06 24/06 25/06 26/06 27/06

PO3 (ppbv h-1)

Figure 43. P(O3) from the radical budget method. 

However, the obtained P(O3) values appear to be high compared to those derived 

from the radical budget method at similar sites (e.g., Volz Thomas et al. (2003) 

and Spirig et al. (2002)). 

A possible overestimation of our P(O3) values can not be totally excluded. It may 

result from the overestimation of the measured NO concentrations, these 

concentrations being always close to the detection limit. 

Similar high values of P(O3) have been calculated by the photostationary state 

method over the same area and during the same period, from aircraft 

measurements (Perros and Pleuvy, pers. communication 2002). 

Sensitivity of ozone production to NOx and VOCs 

The sensitivities of P(O3) to NOx and VOCs has been calculated by applying the 

Steady State Approximation to HOx and RO2 radicals, and using a 0-D model 

(Spirig et al., 2002). The model used input data concentrations of species such as 

VOCs measured at the site by Blake et al. (pers. communication, 2002).- 

dln P(O3) / dln [X] , when X are NOx or VOCs are plotted in Figure 44 as a 

function of LN/Q where Q is the formation rate of HOx and RO2 radicals and LN, 

the loss rate of the radicals by reaction with NOx (Kleinman et al., 1997). 

The results of Figure 44 shows that during the IOP considered (21-26 June), the 

ozone production rate is sensitive to NOx in most of the cases. This behaviour is 

characteristic of a rural site as Dupail. 
LOOP Final Report 99

-1,0

-0,8

-0,6

-0,4

-0,2

0,0

0,2

0,4

0,6

0,8

1,0

0 0,2 0,4 0,6 0,8 1

Ln/Q

dlnPO3/dln[X]

dlnPO3/dlnNOx SSA POI2a dlnPO3/dlnCOV SSA POI2a

dlnPO3/dlnNOx SSA POI2b dlnPO3/dlnCOV SSA POI2b

Sensible aux NOx Sensible aux COV

Figure 44. Sensitivity of P(O3) to NOx and VOCs. 

Conclusion 

Concentrations of O3, NOx and RO2 have been simultaneously and 

continuously measured over a long period at a rural site. 

P(O3) calculated from the radical budget indicates a significant local 

photochemical production of ozone, although P(O3) appears to be too high. 

P(O3) have been found to be mostly sensitive to NOx at the rural site of 

Dupail. 

3.6.5.2 Estimate of local ozone production rates and its 

chemical regime from airborne measurements 

During the ESCOMPTE campaign, airborne measurements on several aircrafts 

have measured ozone and related trace gas species. In order to quantify the ozone 

production in the ESCOMPTE domain we calculated the ozone production and 

the ozone production efficiency from measurements performed on the 

INSU/ARAT aircraft. We also determined the chemical regime governing the 

ozone production. 

The ozone production P(O3) was determined for each flight during each IOP 

using the photostationary steady state relation (see section 2.1.5): 

P(O3)=J(NO2)·[NO2] - k3 · [NO] · [O3] (5) 

All the parameters of this relation were continuously measured aboard the 

aircraft. 
100 Field Campaigns 

The aircraft flew around noon in the boundary layer (altitude 750 meters above 

sea level). The trajectory of the aircraft is presented on the following maps by the 

signs. P(O3) was calculated for each point of the trajectory and then interpolated 

for the whole domain covered by the flight. in Figure 45 we present the spatial 

distribution of the ozone production velocity for the IOP2b (June 24 and 25th) at 

noon. 

June 24th June 25th 

Figure 45. Spatial distribution of P(O3) (ppb h-1) observed on June 24 and 25th at noon. 

The ozone production velocity was generally high (> 10 ppbv/h) and even 

exceeded 50 ppbv/h over some parts of the domain. It is known that the 

stationary state method has a tendency to overestimate ozone production rates. 

Nevertheless, similarly high values were also calculated during the same period 

using NO and radical measurements at Dupail (see section 3.6.5.1). 

Ozone production efficiency (OPE) gives the number of ozone molecules 

produced in the plume per molecule of NO emitted. This number is calculated 

from the slope of the regression between [O3] and [NOz] when d(O3)/dt >0 

(Trainer et al., 1993). We calculated OPE for each flight performed at noon 

during the IOP 2b (Table 6). 

Table 6. Ozone production efficiencies for different dates and locations from ARAT data during IOP2b.

Day June 24th June 25th June 26th 

Origin of 

the plume 

Marseille 

(urban) 

Berre 

(Industrial) 

Berre 

(Industrial) 

Fos 

(Industrial) 

Marseille 

(urban) 

Berre 

(Industrial) 

OPE 15 16 7 3 6 8 

R2 0.93 0.86 0.76 0.58 0.66 0.86 

The observed regressions observed were generally good, allowing thus a proper 

determination of the slopes. We can notice that OPE is strongly variable 

depending on the location and the day. At the beginning of the period the values 

were high as well for an urban plume (Marseille) as for an industrial plume 

(Berre). At the end of the IOP, OPE decreased and some difference can be 

noticed between urban and industrial plumes (June 26th) or between industrial 

plumes from different origin (June 25th). Research is currently performed in our 

4.4 4.6 4.8 5.0 5.2 5.4 5.6 5.8 6.0 43.0

43.2

43.4

43.6

43.8

44.0

4.4 4.6 4.8 5.0 5.2 5.4 5.6 5.8 6.0 43.0

43.2

43.4

43.6

43.8

44.0

10

20

40

50

10

20

40

50
LOOP Final Report 101

laboratory in order to understand these differences. These rather large values for 

OPE’s (with the exception of the Fos plume on June 25th) also indicate an 

intermediate or NOx limited chemical regime. 

The study of the variation of ozone production velocity as a function of NOx

concentration allowed us to determine also the local ozone production chemical 

regime. If P(O3) increase as a function of NOx then the chemical system is NOx

limited. If P(O3) decrease with an increase of NOx then the chemical system is 

VOC limited. 

At the beginning of the IOP (June 24th) P(O3) and [NOx] were strongly 

correlated. P(O3) increase and reach high values (50 ppb/h) The NOx

concentrations were moderate and remained lower than 3 ppb. For this day, the 

local chemical regime is NOx limited for the whole domain. For the second day 

we can see a similar variation except for the highest NOx levels above 7 ppb 

where PO3 saturates (Figure 46). The chemical regime is thus NOx limited below 

7 ppb, and intermediate or VOC limited above. The last day of the IOP (June 

26th) NOx concentrations reached again levels above 10 ppb, but this time no 

saturation occurred even for these large values and thus the chemical regime 

witch was NOx limited. As a conclusion, at least for NOx values below 3ppb, the 

chemical regime was locally NOx limited for all three days. 

y = 0,0224x + 9,0684

R2

 = 0,9464

y = 0,0022x + 151,2

R2

 = 0,4232

0

20

40

60

80

100

120

140

160

180

200

0 2000 4000 6000 8000 10000 12000

Figure 46. Variation of P(O3) (ppb/h) as a function of NOx (ppt) for June 25th at noon for all flight data. 

3.6.5.3 Simulation of local ozone production rates during 

ESCOMPTE 

3-D Eulerian modelling of the IOP2B episode has been conducted at LISA with 

the A3UR model (EDF-IFP-LISA) using the chemical scheme Moca, in order to 

better understand the chemical ways and primary pollutants responsible for such 

ozone production. 

Meteorological fields were calculated with RAMS at LaMP 

(S. Cautenet / M.Taghavi) using ECMWF initialisation and nudging every 6 

hours, soil and vegetation model, and two nested grids (grid 1: (28 x 28 cells) 

Dx=Dy=15km, grid 2: (61 x 61 cells) Dx=Dy=3km with 35 levels in the vertical 

dimension). Anthropogenic and biogenic emissions have been supplied within 
102 Field Campaigns 

the ESCOMPTE frame. It is, however, quite important to keep in mind that this 

inventory is only a preliminary one - it thus has consequences on all simulation 

interpretations. The domain of A3UR calculations is a 162 km large grid with a 

horizontal resolution of 3km and 15 vertical levels of increasing depth from 0 to 

3000m. As can be seen in Figure 47, A3UR (in red) correctly reproduces the 

diurnal ozone maxima and fits its temporal evolution well (in black). 

Figure 47. Ozone time series at three locations in the ESCOMPTE domain. AZUR is the CTM of the 

A3UR system. Results are shown for June 24th to 26th. 

Instantaneous O3 production rates P(O3) have been obtained by explicit 

calculation during Azur runs. Hourly values have been extracted, and the diurnal 

maxima are presented here for 12 UTC. 

Figure 48. Instantaneous O3 production rates calculated with AZUR between 0-50 m height for June 25, 

12 UTC in ppb/h. 

The most noticeable feature is the high values of ozone production calculated by 

the model. Indeed, the whole industrialized, heavy-traffic and urban zones are 

subject to fast ozone production of 60 to 70 ppbv/hour as a mean, during 3 hours 

at the end of the morning. At 12 UTC, we still observe very intense ozone 

production in this area, reaching 100-120ppbv/h in the heart of the industrial 

 BERRE AIX CENTRE CADARACHE 
LOOP Final Report 103

zone. The weak dispersion of the plume accounts for a large proportion of these 

values. Nevertheless, the intense local peaks could be due to a bad resolution in 

the temporary emission inventory, leading to locally unrealistic emissions, and 

has to be tested again with the final version of the inventory. Although no 

explicit comparison to estimated P(O3) values from observations has yet been 

made, the range of simulation and observation based values seems to fit rather 

well for noon. After 15 UTC, simulated P(O3) strongly decreases, due to a 

combination of lower emissions, maximum boundary layer depth and decreasing 

photolysis rates. 

3.6.5.4 Conclusion for specific ESCOMPTE results 

The most striking feature of these three contributions are the large photochemical 

production rates (up to 50-100 ppb/h), estimated independently by three different 

methods. Clearly, each of these methods has its own uncertainty, which has 

further to be elucidated in future. It also appears a tendency for a more NOx

limited chemical regime (both locally and when integrated) than generally 

expected for urban plumes. Reasons for this may be the large biogenic VOC 

emissions in the area, a possibly higher VOC / NOx emission ratio of industrial 

emissions or the specific meteorology of the region and have to be explored in 

future research. 

Acknowledgements 

The ESCOMPTE program is a French initiative. It is supported by a large 

number of European, U.S. and Canadian organisations, among them the 

contributions of the Agence pour l’Environnement et la Maîtrise de l’Energie, the 

French Ministry of Environment, Météo-France and the Centre National de la 

Recherche Scientifique are of considerable importance. 
4. Integration - scaling up 

Albrecht Neftel 

Swiss Federal Institute for Agroecology and Agriculture, Zürich, Switzerland 

Wilfried Winiwarter 

ARC Seibersdorf Research, Vienna, Austria 

4.1 LOOP interactions with environmental policy 

There are close links between the scientific community and the policy 

application, the links are often closer than scientists believe. In atmospheric 

sciences, this starts at the level of input data for air quality models. Emission 

inventories generally are policy driven instruments. They first have been 

established in order to allow environmental policy to start. Only at a later stage 

more scientific approaches (validation, uncertainty assessment) of inventories 

started. 

Consequently, emission inventories (even if compiled at high standards) 

basically are policy driven. They are constructed in part reflecting the main 

interests of the stakeholders involved. A general agreement between the different 

stakeholders on the validity of the results is more important than the agreement 

towards actually measurable values. Furthermore, discrepancies exist between 

emission inventories and real emissions, part of which may be attributed to the 

above mechanism, the other part to more fundamental difficulties in a correct 

assessment of emissions (see section 2.5 for details). 

An additional link is evident in the role of policy makers as users of the 

atmospheric scientists’ results. In order to be able to deliver what may be needed, 

the scientist must know the needs of the users. 

4.2 The need for environmental agencies 

Environmental agencies require solutions for the problems they are facing. 

Environmental problems exist at various scales; but the responsibility of agencies 

is directed towards different scales as well, according to the generally accepted 

principle of subsidiarity (local agencies vs. international agencies). 

Consequently, agencies need the ability to distinguish which kind of problems 

they may tackle, and which problems go beyond their scope. This clearly makes 

it necessary to assess the range of effects a certain pollution might have, and to 

identify sources of a certain pollution. 

In terms of ozone, problem areas have been identified due to the effects. There 

are short time health effects, coinciding with high peak concentrations, and longterm effects on both plants and humans that depend on the exposure level over a 
106 Integration – scaling up 

longer period. Consequently, threshold values have been identified for both peak 

ozone and long-term exposures. 

A one-hour mean value of 180 μg/m3 was set as an information threshold by the 

EU directive 92/72/EEC (now replaced by directive 2002/3/EC), and target 

values for an 8-hour mean of 120 μg/m3 (with certain tolerance conditions) 

according to WHO recommendations, also in directive 2002/3/EC. In current 

practice, long-term exposure is measured as the integral above a certain 

threshold, currently set at 80 μg/m3 (AOT40 = accumulation over threshold 40 

ppb = 80 μg/m3). Critical levels are defined as the cumulative exposure above 

threshold below which no damages occur. In the example of crops, an AOT40 

values below 3,000 ppb·h accumulated over three months during the vegetation 

period is considered cause no damage, whilst an AOT40 of 10,000 ppb·h 

accumulated over six months is the corresponding critical level for forest trees. 

Only hours with global radiation above 50 Wm-2 are considered. This approach is 

defined as “level I”. Still under scientific discussion are “level II”-approaches 

that would address the actual fluxes to plants and thresholds towards the longterm health effects of humans. From a scientific point of view such approaches 

would clearly be preferable. 

Peak ozone is strongly linked with patterns of hot and sunny weather coupled 

with low wind speeds, so-called ozone episodes, in air masses with a high density 

of precursor emissions (i.e., usually urban or industrial plumes upon a continental 

background of pre-existing ozone). In contrast, AOT values are dominated by 

ozone levels under moderate ozone production conditions, as a consequence of 

their cumulative nature. 

4.2.1 Peak ozone 

The experiments within LOOP were designed to investigate the changeover from 

VOC to NOx sensitive ozone productions that occur mainly in urban plumes. 

Spatial scales were chosen accordingly and ranged up to a few tens of kilometres. 

The existence of urban plumes is basically well known, and LOOP helped to 

shed light on the chemical processes and the status of the chemical regimes 

within the plume. Consequently, LOOP solutions support local and regional scale 

questions. Results may directly flow into abatement plans of local agencies. 

Modelling at different scales indicates that a critical size of modelling grids 

exists in order to capture VOC sensitive cores of plumes. E.g., in order to resolve 

properly the VOC/NOx sensitivity of the Milan plume, a grid resolution of 4 to 

10 km (depending on the model, see section 3.4.8.5) is required. Results change 

dramatically when grid sizes above the critical size are used. In general, VOC 

sensitive areas during ozone episodes decrease with increasing grid size. 

It is interesting to note that in most cases (the Milan area is an exception) no 

further difference seems to exist at grid sizes below 10x10 km2

. A possible 

reason for this is that the resolution of the emission inventory starts to match the 

resolution of all other elements of the model. In that case, further refinement of 

the inventory would not lead to any better results, unless the other elements 

(temporal resolution, meteorological information) also were refined. As soon as 
LOOP Final Report 107

the urban plume is completely covered in one grid cell of the model, and is not 

mixed over a much larger area any more, the chemical regime is resolved 

adequately. Further advancements could only be made if emissions and 

meteorology were all also known on a finer scale. 

4.2.2 Ozone levels and cumulated indices (AOT-values) 

Ozone formed in plumes, as described above, will be distributed over 

considerable distances and will contribute to the ozone burden further downwind. 

Generally spoken, the ozone burden in the European PBL is always a mixture of 

ozone transported from the free troposphere, ozone advected from other 

continents and ozone produced within the European PBL. The first two 

contributions yield ozone concentrations around 40 ppb over large areas. As a 

consequence of the step function included in the AOT40 calculation, AOT40 is 

extremely sensitive to small changes in ozone concentrations around 40 ppb. 

Investigations within LOOP focused on areas up to hundred km. AOT 40 values 

within this scale are at least as strongly determined by inflow conditions as by 

the production within the domain. 

As mentioned above, the level II approach requires the calculation of ozone 

deposition fluxes. This is a difficult task, as these fluxes will strongly depend on 

morning hour concentrations and mixing heights, which are very difficult to 

calculate. 

A transfer of results from event based samples to the regional and long term 

situation requires clustering of all important weather patterns, and transferring 

results for each cluster to a long term average according to its statistical 

probability or observed occurrence to a long-term situation. Results for each 

cluster (=weather pattern) need to be available. As ozone chemistry is considered 

to be clearly non-linear, it is not possible to extrapolate from episode-focused 

field experiments (=one cluster) to the conditions outside of episodes. Only if 

further research allows to assign chemical regimes to the specific weather 

patterns, such an extrapolation (along the respective chemical regimes) is 

possible. Currently that has not been achieved, though. 

Consequently, no definite conclusions from the LOOP campaign can be drawn in 

terms of ozone levels. 

4.3 Influence of LOOP on environmental policy 

LOOP has been devised bottom-up, in order to answer questions posed by 

scientists. Such project structures may influence and shape policy decisions, but 

are normally not directly used. Instead, results initiate further activities. The 

success in influencing environmental policy should thus be measured in terms of 

footprints. The distinctive LOOP - footprints are: 

Better understanding of ozone formation on the local scale for each LOOP 

site may be used by the respective local organizations. As, in some cases, the 

LOOP contractors are directly responsible for atmospheric quality, a transfer 
108 Integration – scaling up 

to these local agencies is assured. Similar arguments also apply for cases of 

transboundary pollutant transport at the same scales. 

LOOP provided a seed for the City Delta project, which runs under the EU 

CAFE (clean air for Europe) programme. City Delta concentrates in part on 

the same sites of Europe, and some of the scientists involved are the same. 

City Delta is a modelling study focussing on different cities, different 

photochemical models and runs on different spatial scales. An extension to 

modelling efforts within LOOP, it applies more different emission reduction 

scenarios and it has an emphasis on particulate matter. As it is closely linked 

(from the side of the contractor) with European environmental policy, its 

outcome will flow into European policy more directly. 

Joint meetings with the EMEP community have triggered intensified 

considerations of small-scale processes in continental-scale models. These 

should certainly be considered in the further development of the EMEP 

model, which is the basis of European ozone related policy, as it has been 

used in the full scenario analysis for deriving the Gothenborg protocol as 

well as EU's national emission ceilings. 
5. Synthesis: LOOP Messages in a Nutshell 

Christoph Spirig, Albrecht Neftel 

Swiss Federal Research Station for Agroecology and Agriculture, Zurich, Switzerland 

Josef Dommen 

Paul Scherrer Institute, Laboratory of Atmospheric Chemistry, Villigen, Switzerland 

5.1 Are the simulations of the efficiency of VOC versus 

NOx emission reduction on the ozone production 

on a sound base? 

The LOOP community attending the 2nd Gerzensee workshop judged that errors 

in the state of the art chemical schemes in CTMs are smaller compared to 

uncertainties in emission inventories and transport schemes (horizontal and 

vertical). Model results need careful evaluation. Such testing needs consideration 

of more parameters than ozone concentration alone (for example peroxides, NOy, 

formaldehyde etc.). Chemical schemes must be evaluated with measurements of 

as many species as possible, including radicals. If no radical measurements are 

available they should be assessed using observation based modelling. 

5.2 Do biogenic emissions influence the VOC – NOx

sensitivity of the ozone production? 

Biogenic emissions depend on environmental conditions, mainly temperature, 

radiation and water supply, and on the phenological state of the plants. 

Conditions that are favourable for ozone formation also have the potential of 

high biogenic VOC and NO emissions. Biogenic VOC emissions are considered 

to have more influence on ozone formation than biogenic NO emissions. VOC 

emissions show a strong seasonal pattern with highest values in July and August. 

The contribution of biogenic VOCs to the total OH reactivity typically increases 

from values below 20% in urban areas to over 60% a few hours downwind. As a 

consequence, the impact of biogenic emissions on ozone formation also increases 

during this transport to remote areas. The biogenic emissions shift the VOC/NOx

concentration ratio toward higher values and therefore influence the chemical 

regime toward NOx sensitivity. 

5.3 Can indicators be used to characterize chemical 

regimes of ozone production? 

Correlation plots of O3 vs NOy, H2O2 vs HNO3, etc. are valuable diagnostic tools 

to analyse the VOC/NOx sensitivity of the ozone chemistry. Such ratios have 

been proposed as indicators to distinguish VOC and NOx sensitivity of the 
110 Synthesis: LOOP Messages in a Nutshell 

integrated ozone production, as their values show characteristic different ranges 

for VOC and NOx sensitive regimes. Indicator values may help to elucidate 

reasons for model/measurement discrepancies. However, both measurement and 

interpretation of indicator species and their ratios is difficult, and models should 

not be tuned based on a model/measurement discrepancy of indicators alone. 

The absolute values of the indicator ratios are influenced by boundary conditions. 

Especially for smaller domains, the concentrations at the inflow will largely 

determine the level of species with a lifetime of days and more. However it is 

still very useful to compare the spatial patterns and temporal changes of the 

indicator ratios within the model with measurements. It was recently suggested to 

use the changes of indicator values during a given transport time rather than 

absolute values. This requires measurements of the indicator species to be made 

in a Lagrangian experiment, i.e., by aircraft. 

5.4 How does the grid resolution influence the model 

results? 

There are many urban plumes observed in Europe, which are not captured by the 

coarse grids of many continental scale models. Model calculations from fine to 

coarse grids in the Milan area suggest that the averaged ozone concentrations 

over a fine grid is not much different compared to the corresponding mean ozone 

concentration in a coarse grid, but peak values often increase with increasing 

resolution. It seems likely that a coarse grid model may lose some of or all of the 

VOC sensitive part of an urban plume. This may lead to wrong predictions 

regarding emission reductions. On the other hand, big point sources of NOx

create erroneously large areas of VOC limitation in coarse grid models. 

For the convention on Long Range Transboundary Air Pollution (LRTAP) of the 

United Nations Economic Commission for Europe (UN-ECE), source-receptor 

matrices between individual countries need to be calculated. For this purpose, the 

EMEP model activities were set up. There is no quantification of how much 

regional plumes contribute to ozone sensitivity of the EMEP model. 

Furthermore, there is not enough experimental data (covering the long-term 

EMEP scale) to evaluate the model thoroughly because of the lack of ozone 

stations in certain regions of Europe and the lack of long term monitoring of 

precursors, meteorological data and indicator species. 

5.5 What is the influence of aerosols? 

Although published results are not conclusive up to now, they indicate that the 

general picture of ozone production on regional scales should not be greatly 

affected by the amount of the aerosol load. On the other hand, the PIPAPO 

campaign showed that JNO2 values were reduced by more than 10% in the Milan 

plume by the presence of aerosols, leading to a substantial reduction in local 

ozone formation rates. Other effects of aerosols could be due to heterogeneous 

reactions. Night-time loss of NO2 via formation of N2O5 and its adsorption on 

aerosols is an important process in the NO2 budget and should be considered in 
LOOP Final Report 111

models. High NO2 concentrations with unexplained NO2/NO ratios were 

observed in Paris in winter, which might be due to heterogeneous processes and 

reactions on aerosols have been suggested as a possible loss process for radicals 

in order to explain the lower OH concentrations than those predicted by 

photochemical models constrained by observations. 

In general, the influence of heterogeneous processes on photochemistry is still 

uncertain and there is not yet a sound basis for including it in models. 

5.6 How do photochemical models relate to the AOT 

concept ? 

Whereas the AOT value (accumulated ozone dose over a threshold) has initially 

been a useful parameter to link ozone concentrations to its environmental effects, 

it is unfavourable for use in the interpretation of measurements and model 

simulations. The concept of the AOT value involves a step function from zero to 

unity at the threshold level. The inherent uncertainty of both measured and 

modelled concentration data therefore leads to a much larger uncertainty in AOT 

values. The flux approach (as proposed at the UN/ECE-LRTAP workshop in 

Switzerland, 1999) may prove more robust than AOT40, at least if no threshold 

is introduced or if this threshold is very low. This so-called “level-II” approach is 

under development under the LRTAP Convention’s Working Group on Effects. 

However the modelling of ozone deposition fluxes is a difficult task, as these 

fluxes will strongly depend on morning hour concentrations and mixing heights. 

Both stability and ozone concentrations near ground are difficult to calculate 

during night and morning hours. 

5.7 What kind of activities are still needed? 

Improving emission inventories is a must for significantly improving the 

diagnostic and prognostic capability of photochemical models. The present 

VOC measuring network has been very valuable to evaluate emission 

inventories. Further evaluation of emission inventories is necessary. 

For a reliable simulation of the aerosol levels, spatially high resolved NH3

inventories are necessary. 

Investigations on the role of biogenic emissions, both VOCs and NOx should 

continue. Approaches for obtaining regionally integrated fluxes of isoprene 

and its oxidation products, terpenes and carbonyl compounds have to be 

implemented. 

More local closures including radical measurements would be useful in order 

to investigate the discrepancies between measured and modelled radical 

concentrations. 

Models should be tested on real situations, where reductions of VOC’s 

and/or NOx occur, as for example weekday vs. weekend, holiday effects, 

emission reductions over longer time scales, different reduction 

achievements in different European regions. In the Milan area, the month of 
112 Synthesis: LOOP Messages in a Nutshell 

August offers an interesting possibility. Due to general holidays 

(“Ferragosto”) during that month, human activities and emissions of NOx

and VOC are considerably changed as first investigations have shown. 

In order to meet EMEP requirements, a change in focus from episodic to 

long-term campaigns is needed. Therefore, more monitoring stations with a 

comprehensive set of measured species (allowing a determination of ODD-H 

radicals and a characterisation of the ozone production) are required for 

urban and rural situations. Vertical information on species composition and 

also mixing heights are of great importance for model evaluation. 

At least 10 specialised monitoring stations (super-sites) across Europe 

should be installed. They should not only be geographically distributed, but 

also consider different VOC/NOx sensitive areas according to present EMEP 

model calculations. Besides O3, NOx, and SO2 (frequently measured species 

in the current monitoring network), measurements of additional species and 

meteorological data are needed to evaluate emission inventories, transport, 

and chemistry: 

 Urban station Rural station 

Basic equipment O3, NOx, SO2 O3 NOx, SO2

Emission evaluation Speciated VOCs, 

aldehydes, CO 

Speciated VOCs, 

aldehydes, CO 

Chemistry evaluation NOy, HCHO, JNO2 NOy, HCHO, H2O2, 

ROOH, JNO2

A complement to super-sites would be a concept with mainly airborne 

measurements. However, aircraft measurements should be performed for at 

least 2 months (or at regular intervals, e.g., biweekly) in order to be more 

valuable than year-round measurements at surface super sites. 
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