Agriculture, Ecosystems and Environment 133 (2009) 183–195

European scale application of atmospheric reactive nitrogen measurements in alow-cost approach to infer dry deposition fluxes

Y.S. Tang a,*, I. Simmons a, N. van Dijk a, C. Di Marco a, E. Nemitz a, U. Dammgen b, K. Gilke b, V. Djuricic c,S. Vidic c, Z. Gliha c, D. Borovecki c, M. Mitosinkova d, J.E. Hanssen e, T.H. Uggerud e, M.J. Sanz f, P. Sanz f,J.V. Chorda f, C.R. Flechard g, Y. Fauvel g, M. Ferm h, C. Perrino i, M.A. Sutton a

a Centre for Ecology & Hydrology (CEH) Edinburgh Research Station, Bush Estate, Penicuik, Midlothian EH26 0QB, UKb Institute of Agricultural Climate Research, Johann Heinrich von Thunen Institut (vTI, formerly FAL), Bundesallee 50, 38116 Braunschweig, Germanyc Meteorological and Hydrological Service of Croatia, Research and Development Division, Gric 3, 10000 Zagreb, Croatiad Slovak Hydrometeorological Institute, Department of Air Quality, Jeseniova 17, 833 15 Bratislava, Slovak Republice Norwegian Institute for Air Research (NILU), P.O. Box 100, N-2027 Kjeller, Norwayf Fundacion CEAM, Parque Tecnologico, C/Charles H. Darwin 14, 46980 Paterna (Valencia), Spaing Institut National de la Recherche Agronomique (INRA), UMRSAS, 65 rue de St-Brieuc, 35042 Rennes Cedex, Franceh IVL Swedish Environmental Research Institute, P.O. Box 5302, SE-400 14 Gothenburg, Swedeni CNR National Research Council - Institute for Atmospheric Pollution, Via Salaria Km. 29.300, CP 10 – 00016, Monterotondo Stazione, Rome, Italy

A R T I C L E I N F O

Article history:

Received 2 September 2008

Received in revised form 14 April 2009

Accepted 27 April 2009

Available online 2 July 2009

Keywords:

Nitrogen

Denuder

Ammonia

Nitric acid

Aerosol

Dry deposition

Inferential modelling

A B S T R A C T

A European scale network was established in 2006 as part of the NitroEurope Integrated Project to infer

reactive nitrogen (Nr) dry deposition fluxes, based on low-cost sampling of gaseous and aerosol species

and inferential modelling. The network provides monthly measurements of NH3, NH4+, HNO3 and NO3

�,

as well as SO2, SO42�, HCl, Cl� and base cations at 58 sites. Measurements are made with an established

low-cost denuder methodology (DELTA) as a basis to: (1) examine temporal trends and spatial patterns

across Europe, (2) improve and calibrate inferential modelling techniques to estimate exchange of Nr

species, (3) provide best estimates of atmospheric dry N deposition, and (4) permit an analysis of net

GHG exchange in relation to atmospheric and agricultural N inputs at the European scale. Responsibility

for measurements is shared among seven European laboratories. An inter-comparison of the DELTA

implementation by 6 laboratories at 4 test sites (Montelibretti, Italy; Braunschweig, Germany; Paterna,

Spain and Auchencorth, UK) from July to October 2006 provided training for the laboratories and showed

that good agreement was achieved in different climatic conditions (87% of laboratory site-means within

20% of the inter-laboratory median). Results obtained from the first year of measurements show

substantial spatial variability in atmospheric Nr concentrations, illustrating the major local (NH3) and

regional (HNO3, NO3�, and NH4

+) differences in Nr concentrations. These results provide the basis to

develop future estimates of site-based Nr dry deposition fluxes across Europe, and highlight the role of

NH3, largely of agricultural origin, which was the largest single constituent and will dominate dry Nr

fluxes at most sites.

� 2009 Elsevier B.V. All rights reserved.

Contents lists available at ScienceDirect

Agriculture, Ecosystems and Environment

journal homepage: www.e lsev ier .com/ locate /agee

1. Introduction

The estimation of nitrogen dry deposition represents one of thekey uncertainties in quantifying net nitrogen inputs to terrestrialecosystems (e.g. Smith et al., 2000; Erisman et al., 2005; Suttonet al., 2007). Not only is this information important in its own right,for example in quantifying net nitrogen budgets, but it is alsoimportant in quantifying ecosystem responses to nitrogen. For

* Corresponding author. Tel.: +44 0 1314458562; fax: +44 0 1314453943.

E-mail address: yst@ceh.ac.uk (Y.S. Tang).

0167-8809/$ – see front matter � 2009 Elsevier B.V. All rights reserved.

doi:10.1016/j.agee.2009.04.027

example, uncertainty in background atmospheric nitrogen deposi-tion was estimated to be one of the key sources of uncertainty insetting empirical critical loads for nitrogen deposition (Suttonet al., 2003; Bleeker et al., 2004). Similarly, recent debate on thequantitative response of net ecosystem productivity has focusedon uncertainties in estimating nitrogen deposition, particularly atsites where local dry deposition measurements are not available(Magnani et al., 2007; De Vries et al., 2008; Sutton et al., 2008).

Estimating atmospheric nitrogen deposition is a complex task,particularly given the large number of reactive nitrogen (Nr)components and the different deposition processes associatedwith each of them. Nr compounds in the atmosphere include

Y.S. Tang et al. / Agriculture, Ecosystems and Environment 133 (2009) 183–195184

ammonia (NH3) emitted predominantly from agricultural activ-ities, especially intensive management of livestock, nitrogenoxides (NOx = NO + NO2) from fossil fuel combustion in industryand traffic, acids (HNO3 and HONO) and PAN (peroxy-acetyl-nitrate) formed as secondary reaction products, and N containingaerosols ((NH4)2SO4, NH4HSO4, and NH4NO3) from neutralizationof the acid gases by NH3. Given this complexity, it quickly becomesapparent that it is not financially feasible to measure allcomponents of nitrogen fluxes directly in multi-site continentalscale networks, as for example done for carbon dioxide.

Recognizing this constraint, the NitroEurope Integrated Project(NEU) (Sutton et al., 2007; Skiba et al., 2009) has developed a ‘3-level’ flux measurement strategy to provide a comprehensiveassessment of the fluxes, pools and processes controlling thenitrogen cycle for European terrestrial ecosystems. This approachrecognizes that there are different requirements for data on Nrfluxes at different sites. At the most intensive level, data arerequired from a small number of representative sites that can beused to quantify fluxes directly, understand processes and informmodel development. By contrast, at other sites the need is toprovide a realistic estimate of nitrogen deposition, informed bybasic measurements that can be used to interpret other nitrogenresponses (e.g. ecosystem biodiversity or net carbon exchange).

Based on this rationale, NitroEurope has established thefollowing flux network:

� Level 3: 13 ‘‘Super Sites’’—for detailed investigation of Nbudgets/fluxes and interactions with C-cycling, supported bydetailed plant/soil inventorying and process studies;� Level 2: 9 ‘‘Regional Sites’’ for application of low-cost N flux

methods, as a basis to establish a future long-term fluxmonitoring capability at CO2 flux sites;� Level 1: 58 ‘‘Inferential Sites’’ allowing interpretation of measured

CO2 fluxes in relation to inferential estimates of N supply and keysoil parameters.

At each level, targeted measurements address a range ofobjectives for integrated assessment of nitrogen, thus allowing thebest use of available resources. Level 3 activities focus on processmeasurements at a few key sites that use expensive high resolutionmanual air sampling methods or automatic continuous monitorsand state-of-the-art instrumentation for validation of highresolution atmospheric chemistry/transport models, source–receptor relationships and rapid temporal changes in concentra-tions and fluxes (Skiba et al., 2009). The Level 2 network provides abasis to extend the regional coverage of N flux measurements. TheLevel 1 network is referred to as ‘inferential’ since dry depositionflux measurements are not made. Rather, measurements are madeof atmospheric Nr concentrations, which are used together with arange of dry deposition models to infer dry deposition fluxes. Othermeasurements made at the Level 1 sites include estimation of wetdeposition fluxes, plus soil and plant bioassays.

The overall goal of the Level 1 network is to deliver a long-termdataset on Nr species in a cost-effective way, with the followingobjectives: (1) to examine temporal and spatial patterns andtrends across Europe, (2) to improve and calibrate inferentialmodelling techniques to estimate N exchange (by comparison withthe Level 3 measurements), (3) to provide best estimates ofatmospheric dry N deposition, and (4) to allow an analysis of netgreenhouse gas exchange in relation to atmospheric Nr depositionand agricultural N inputs across the NitroEurope IP and CarboEu-rope IP networks.

For the Level 1 measurements of Nr components, the coreapproach is the application of a low-cost, low temporal frequencydenuder method ‘DELTA’ (DEnuder for Long-Term Atmosphericsampling; Sutton et al., 2001b), to provide monthly speciated

measurements of Nr at>50 sites across Europe. Most other manualdenuder implementations are designed for sampling over hourly todaily timescales (e.g. Ferm, 1979), while the DELTA has beenoptimized for sampling over weekly to monthly periods, resultingin greatly reduced sample preparation and chemical analysis costs.This requires that high temporal resolution is sacrificed in returnfor a system that can be operated effectively in long-termmonitoring at many sites.

The DELTA method was originally developed for long-termsampling of NH3 and NH4

+, as applied in the UK National AmmoniaMonitoring Network since 1996 (Sutton et al., 2001a; Tang andSutton, 2003; Tang et al., 2009). Following further methoddevelopment, it was implemented in the UK Nitric Acid MonitoringNetwork from 1999 for long-term sampling of acid gases (HNO3,HONO, HCl, and SO2) and aerosols (NO3

�, NO2�, Cl�, SO4

2�, Na+,Ca2+, and Mg2+) (Sutton et al., in preparation; Tang et al., 2008). TheDELTA approach has also been recommended for Level 1monitoring in the EMEP monitoring strategy (Sutton et al.,2004; Aas, 2005); its application here through NEU represents acontribution toward that goal.

Although the DELTA method had been established in the UK forsome years (e.g. Sutton et al., 2001a,b), the first task in establishingthe European network was to share and establish the approachwith a team of European coordinating laboratories. For thispurpose, a 4-month inter-comparison was conducted at fourEuropean sites, designed to check laboratory performance, whileconsidering contrasting climatic conditions and atmosphericconcentrations of air pollutants across Europe. The inter-compar-ison also provided training to the teams, while the infrastructurewas being built up. Following the inter-comparison, measure-ments in the network commenced in November 2006, providingmonthly measurements of gaseous NH3 and HNO3, and aerosolNH4

+ and NO3� at 58 sites. Measurements are also made of SO2,

HCl, and aerosol SO42�, Cl�, Na+, Ca2+ and Mg2+, which will be

reported elsewhere. In this paper, results from the field inter-comparison and the first full year of measurements of Nr speciesfrom the Level 1 network are presented.

2. Methods

2.1. Description of the DELTA methodology

The DELTA system, described in detail by Sutton et al. (2001b)comprised of a denuder filter sampling train, an air pump toprovide low sampling flow rates of 0.2–0.4 L min�1 and a highsensitivity dry gas meter to record sampled volume. For this study,the air intake is set at 1.5 m above the ground/vegetation, or at 2–3 m above the forest canopy on towers. Sampling is conducteddirectly from the atmosphere, since loss of HNO3 may occur to inletlines (De Santis et al., 1988). Given the power constraints atmonitoring locations, and as a means to avoid the safety risks ofmains electricity, a 6 V air pump was used in the DELTA system atmost of the sites.

The use of short borosilicate glass denuders allows easyexchange of samples through the post. The first pair of (K2CO3/glycerol coated) 15 cm denuders removes acid gases HNO3, SO2

and HCl, followed by the second pair of (citric acid or phosphorousacid coated) 10 cm denuders in series to remove NH3 (Fig. 1). Citricacid was used except in warm/Mediterranean conditions, wherethis acid can partially desorb, in which case phosphorous acid wasused (Perrino and Gherardi, 1999). Two sets of coated cellulosefilter papers in a 2-stage filter pack at the end of the sampling traincollect aerosol components. The first filter is impregnated withK2CO3/glycerol to sample aerosol NO3

�, SO42�, Cl� plus the base

cations Na+, Ca2+ and Mg2+, followed by a citric acid/phosphorous-coated filter to collect evolved aerosol NH4

+ (Fig. 1). The base

Fig. 1. Left: DEnuder for Long-Term Atmospheric sampling (DELTA) as applied for the monthly measurements of trace gas and aerosols in the NEU ‘Inferential Network’ of

Level 1 sites. Right: sampling train consisting of 2 � 15 cm (L) K2CO3 + glycerol-coated denuders (determination of HNO3, SO2, and HCl), 2 � 10 cm (L) acid-coated denuders

(determination of NH3), carbonate-coated filter (determination of NO3�, SO4

2�, Cl�, Na+, Ca2+, and Mg2+) and acid-coated filter (determination of evolved NH4+). VTI adopted a

modified configuration of the denuders, consisting of 1 � 15 cm (L) + 1 � 10 cm (L) carbonate-coated denuders, and 1 � 15 cm (L) + 1 � 10 cm (L) acid-coated denuder.

Y.S. Tang et al. / Agriculture, Ecosystems and Environment 133 (2009) 183–195 185

coating of the denuder and first filter is made with KOH whichconverts readily to K2CO3 on reaction with CO2 in the atmosphere,while glycerol is added to increase adhesion and reducevolatilisation of the carbonate coating, and also to minimiseoxidation of nitrite to nitrate which can occur when ozone ispresent (Allegrini et al., 1987; Perrino et al., 1990).

2.2. Analysis and calculations in DELTA methodology

Exposed samples are stored at 4 8C until analysis. Acid-coateddenuders and filters are extracted into 3 ml and 4 ml deionisedwater, respectively, and analysed for NH4

+ using either colorimetry(indophenol blue or salicylate method; e.g. EMEP, 1996), ionchromatography (IC), or a conductivity based ammonia flowinjection analysis system (AMFIA, developed at ECN, Petten, NL;Wyers et al., 1993). Participation of the laboratories in analyticalinter-comparisons showed no systematic bias in measurementresults between the different methodological approaches for theanalysis of NH4

+. The detection limit for NH4+ was comparable for

all 3 methods which was determined as 0.01 mg L�1. With amonthly sampling period, the detection limit of the DELTA methodfor gaseous NH3 and aerosol NH4

+ was determined as0.01 mg NH3 m�3 and 0.02 mg NH4

+ m�3, respectively.Carbonate-coated denuders and filters are extracted into

5 ml of 0.05% H2O2 solution, followed by analysis of trace ions byIC. The detection limit for NO3

� was 0.01 mg L�1. With a monthlysampling period, the detection limit of the DELTA methodfor gaseous HNO3 and aerosol NO3

� was determined as0.03 mg HNO3 m�3 and 0.05 mg NO3

�m�3, respectively.The use of two denuders in series permits the determination of

capture efficiency, by comparing the amounts of trace gas in bothdenuders. An infinite series correction factor, based on the captureefficiency, is applied for trace gas not captured (see Sutton et al.,2001b; Tang et al., 2008).

Loss of NH3 due to volatilisation of NH4+ from the acid-coated

filter paper has been investigated, by adding a third citric acid-coated denuder after the filter pack, and was found to be negligible.The use of basic carbonate-coated filter paper aims to volatiliseNH4

+ aerosol which is then captured on the acid-coated filter.

Analysis of the carbonate-coated filters has shown that negligibleamounts of NH4

+ are retained. This procedure is thus able to reduceanalysis costs, as well as the need for (expensive) PTFE(polytetrafluoroethylene, or teflon) and/or nylon pre-filters, whichis consistent with the aims of this low-cost approach.

Laboratory and field/transport blanks were prepared togetherwith every batch of samples. Laboratory blanks were subtractedfrom samples, while analysis of field/transport blanks served tocheck for possible contamination of samples during transport andstorage. Field blanks were placed in the same DELTA enclosure asthe field sample, but attached to the inside of the door. Transportblanks were posted together with the field samples, but remainedin the same transport box and were posted back to the laboratorieswith the field sample. Results from the field and transport blankswere found to be similar to laboratory blanks from all laboratoriesand for all sites.

2.3. DELTA inter-comparison

The NEU network is based on implementation of the DELTAmethodology across all sites, with coordinating laboratoriespreparing samples and applying different analytical methods forthe chemical analysis. In order to improve the data comparabilityand to assess performance of the laboratories, inter-laboratorycomparisons are conducted in the form of (1) analytical inter-comparison of trace ion analysis, whereby reference samples aredistributed to laboratories for analysis and reporting once a yearand (2) DELTA measurement inter-comparisons.

The first major DELTA inter-comparison exercise was con-ducted at four European sites (Montelibretti, Italy; Braunschweig,Germany; Paterna, Spain and Auchencorth, UK) in contrastingclimatic conditions over a 4-month period between July andOctober 2006. Six DELTA systems were installed at each site fortime-integrated sampling over sampling periods of 14 days.Names and acronyms of the participating laboratories are given inFig. 2. Each of the six laboratories was responsible for preparingsampling trains and sending a set of sample to each of the inter-comparison sites and carrying out chemical analysis on thesamples.

Fig. 2. NEU ‘Inferential Network’ of Level 1 sites. The coordinating laboratories are: CEAM, Fundacion CEAM; vTI, von Thunen Institut; INRA, Institut National de la Recherche

Agronomique; MHSC, Meteorological and Hydrological Service of Croatia; NERC-CEH, Centre for Ecology and Hydrology; NILU, Norwegian Institute for Air Research; SHMU,

Slovak Hydrometeorological Institute.

Y.S. Tang et al. / Agriculture, Ecosystems and Environment 133 (2009) 183–195186

The 4 test sites were identified on the basis of the availability ofindependent measurements by reference methods. At Monteli-bretti (urban site near Rome), an Annular Denuder System (ADS,Possanzini et al., 1983; Allegrini et al., 1987) operated by CNR,served as the independent reference. The annular denuders consistof two concentric glass tubes, sampling at high flow rates of 10–15 L min�1, with a sampling period of 24 h. The sampling trainconsisted of 2NaCl-coated denuders (determination of HNO3);2Na2CO3 + glycerol-coated denuders (determination of SO2);H3PO3-coated denuders (determination of NH3); cyclone(2.5 mm particle size cut-off); nylon filter (determination ofNH4

+, NO3�, SO4

2�, and Cl�); H3PO3-impregnated filter (determi-nation of evolved NH4

+).

Auchencorth, a rural background (moorland) site in SouthernScotland provided contrasting conditions for the DELTA measure-ments. Here, a 2-channel MARGA (Monitor for Aerosols and Gases)system (manufactured by Applikon Analytical) provided contin-uous hourly measurements. Water-soluble gases are quantita-tively absorbed in water on a wet rotating denuder (WRD), andaerosols are removed in a Steam Jet Aerosol Collector (SJAC) at theend of the WRD. Collection of the gases and aerosols is followed byon-line analysis of trace ions by IC and AMFIA system. Cycloneswith cut-off diameters for PM10 (particulate matter �10 mm) andPM2.5 (particulate matter �2.5 mm) placed at inlets determinedthe different particle size cut-offs for each of the two MARGAchannels.

Y.S. Tang et al. / Agriculture, Ecosystems and Environment 133 (2009) 183–195 187

The Braunschweig test site is at a long-established experi-mental field station in an agricultural landscape managed by vTI,equipped with an extensive range of manual denuder systems (seeSection 4.4, Dammgen, 2007; Dammgen et al., in preparation).Paterna is an experimental station at CEAM (Mediterraneanclimate), Valencia, which is equipped with a honeycomb denudermethod. However, reference data were not available during theinter-comparison period due to saturation problems of thehoneycomb denuder method.

2.4. Establishment of Inferential Network

The NEU Level 1 network (Fig. 2) was established to provide 4years of speciated measurements of gaseous HNO3, NH3 andaerosol NO3

�, NH4+, as well as other related trace gas and aerosols.

Site selection included all the NEU Level 3 sites, plus the network ofmain CO2 flux measurement sites of CarboEurope, with theultimate aim to investigate relationships between net GHGexchange and nitrogen supply. DELTA measurements began inNovember 2006, with most of the sites fully operational by January2007. A network of local site operators representing the scienceteams of each site perform the monthly changeover of samples andpost the exposed samples back to their designated laboratories.Monitoring is on a monthly timescale that provides the most cost-effective way of providing concentration fields and long-termtrends in pollutant concentrations, while giving sufficient resolu-tion to examine the main seasonal differences.

Initially, six European coordinating laboratories shared themanagement and operation of the Level 1 Network. For the first 7months of the network, 9 of the sites were maintained by CEH.However, as a result of CEH institutional restructuring, respon-sibility for 7 of these sites were transferred to INRA (InstitutNational de la Recherche Agronomique, France) from August 2007.The remaining Level 1 sites in the UK are operated by CEH inparallel to a further 30 sites in the National Nitric Acid MonitoringNetwork (Sutton et al., in preparation; Tang et al., 2008).

2.5. Quality control and data analysis

Quality Assurance (QA) and Quality Control (QC) approachesused in the NEU network are based on the quality managementsystem applied in the UK air monitoring networks (Tang andSutton, 2003). QA of the network is maintained through carefuladherence to written sampling protocols of good laboratory andsite operator practice. The proficiency of the coordinatinglaboratories is also assured by participation in recognizedAnalytical Quality Control schemes for aqueous ion analysis intheir own country, as well as participation in the EMEP laboratoryinter-comparison (once annual—http://www.emep.int) andWMO-GAW (twice annual—http://www.qasac-americas.org/lab_ic.html) schemes. To demonstrate comparability of measure-ments between laboratories, each year further inter-comparisonexercises are also carried out as described in Section 2.3.

Monthly air concentration data are entered by the laboratoriesonto a standardised template for their respective sites andsubmitted to CEH for collation. The data are checked, screenedaccording to set QC criteria and put on the NitroEurope database.Data passing and failing the QC thresholds can then be compared toidentify any biases. Two levels of data filtration are provided:

2.5.1. Standard data filtration

Two denuders in series are used for every sample to checkcapture efficiency for trace gas: distinction is made betweensamples providing �75% of the total trace gas captured in the firstof the two denuders, compared with <75% of the total capturebeing in the first denuder. Values less than this indicate an

imperfectly coated film or some other sampling problems and itcannot then be guaranteed that all the gas of interest is captured inboth denuders, and the capture efficiency correction (>10%)becomes more uncertain. For the aerosol components, scatter plotsof the concentrations of acidic (NO3

� and SO42�) and basic (NH4

+)aerosol components are made to check the quality of themeasurements (close chemical coupling expected), and to identifyoutliers. Data are also set to fail the QC standard where themonthly air sampling rate is 0.2 L min�1. Any low flow rate for amonth is investigated promptly with the site operator.

2.5.2. Manual screening of outliers

In addition to the above tests, the full dataset is investigated foroutliers in relation to the functioning of the equipment. This isdesigned to identify the small number of runs where there wasclearly a sampling malfunction. This exclusion includes suchevents as vandalized samples, water ingress and invasion byinvertebrates.

3. Results

3.1. Inter-laboratory field comparison of the DELTA methodology

A total of eight 14-day sampling periods were obtained from theinter-comparison exercise. Data from all 4 test sites are comparedin Fig. 3, where the estimate for each site/sampling period for all sixlaboratories is compared with the median estimate. A median isused rather than a mean as the reference, since this is lessinfluenced by outlier results. The performances of the differentsampling operations for each species are also indicated, accordingto the R2 and slope of the dataset in relation to the medianestimates. Since the plots show a non-significant intercept in allinstances, the results for measured concentrations (x) were fittedsimply as xlab = axlab median. Statistically the slope (a) is equivalentto the mean ratio of each laboratory against the reference. Thisapproach, together with the associated R2 values (intercept set atzero), is sufficient to highlight the main features of the inter-comparison.

The best agreement was obtained in the inter-comparison foraerosol nitrate. Most laboratories had R2 > 0.9 and slopes within�10% of the median estimates, combining the data for all sites andsampling periods. The poorest agreement for aerosol nitrate wasR2 = 0.76, largely as a result of two outlier points.

A broadly similar performance was obtained for HNO3 and NH3

in the inter-comparison. Some laboratories showed very closeagreement to the median estimates, with more scatter observedfrom the others. For example, with HNO3, NILU, NERC and SHMUgave R2 > 0.95 and slopes within �10%. By contrast, both CEAM andvTI showed poorer agreement due to outliers. For NH3, four of thelaboratories reported agreement that was within�11% of the medianestimates overall, with all laboratories having R2 > 0.8 However,some systematically high readings (MHSC, slope 1.24) and lowreadings (CEAM, slope 0.82) were recorded against the medianestimates.

The lowest level of agreement was found for aerosol NH4+, with

MHSC reading highest and CEAM reading lowest, as with theanalysis of NH3. In this case, CEAM provided the clearest outlierestimates (Fig. 3), although the discrepancy was found to varyaccording to monitoring location. At Auchencorth, CEAM agreedwithin 7% of the median estimates, while at Paterna, the estimateswere around 70% lower than the median (Table 1). For CEAM, theunder-read was attributed to problems with the acid coating onthe aerosol filters (and to some extent the denuders for NH3, asindicated in Fig. 3), and has since been rectified. In the case ofMHSC, the over-read may have been due to a positive bias in NH4

+

analysis (on IC), since this laboratory overestimated aqueous NH4+

Fig. 3. Inter-comparison of the measured gaseous HNO3 and NH3 and aerosol NO3� and NH4

+ concentrations of all six laboratories with the median estimate of the

laboratories for the site/sampling period. Data points are 14-day measurements from reference sites in Scotland (Auchencorth, NitroEurope Level 3 site), Germany

(Braunschweig), Italy (Montelibretti) and Spain (Paterna). As the intercepts were not significant, the regressions were fitted simply as xlab = axlab median to allow easy

comparison. The values of R2 and a are shown below the graphs.

Y.S. Tang et al. / Agriculture, Ecosystems and Environment 133 (2009) 183–195188

concentrations by 25% in a 1 ppm NH4+ reference sample in the

2006 analytical inter-comparison. (In the 2007 aqueous inter-comparison, MHSC NH4

+ measurements agreed within 0.6% of thereference.) With the exception of CEAM and MHSC, all the otherlaboratories had slopes for NH4

+ aerosol within 10% of the medianestimates.

In considering the results of this inter-comparison, it should benoted that caution is needed in interpreting individual monthlyvalues, as illustrated by the occurrence of some outliers. However,the overall site averages (for the 8 sampling periods) were broadlycomparable, and show that each of the laboratories is able toclearly resolve the main differences in mean concentrations at thefour different field sites (Table 1).

The level of agreement reported in Table 1 can be summarizedin terms of the percentage of the laboratory mean estimates foreach of the 4 sites and for each of the 4 Nr species (i.e. 16 siterecords), that are within 10% and 20% of the overall medianestimates. Excluding the CEAM estimates of NHx where the (nowrectified) analytical problem was identified, 65% (laboratory range44–81%) of the laboratory site-means were within 10% of the

laboratory median estimate. Similarly, on average 87% (laboratoryrange 69–100%) of the laboratory site-means were within 20% ofthe laboratory median.

Further checks on the DELTA results were made at two of thefield sites, where independent high resolution data were availablefor comparison with the DELTA measurements.

Daily ADS results at Montelibretti (Fig. 4) and hourly MARGAresults at Auchencorth (Fig. 5) were averaged to the corresponding14-day mean values for the purpose of comparison with the DELTAdata. Although the ADS and MARGA measurements are also subjectto uncertainty, this further inter-comparison shows encouragingagreement. At Montelibretti, for NH3 and NH4

+, the DELTA waswithin 9% and 18% of the ADS. For NO3

�, the DELTA agreed within24% of the total aerosol NO3

�measured on the ADS (NO3� on PM2.5

filter + NO3� in cyclone with 2.5 mm cut-off = PMx). For HNO3, the

DELTA results were much higher than recorded by the NaCl-coateddenuder, but agreed within 9% of the sum of the NaCl and Na2CO3-coated denuders.

At Auchencorth, the MARGA did not work effectively for thefirst 4 inter-comparison periods, and only partially for periods 5–8.

Fig. 4. Inter-comparison of the median gaseous HNO3 and NH3 and aerosol NO3� and NH4

+ concentrations of all laboratories with measurements from a co-located Annular

Denuder System (ADS) at Montelibretti, Italy. 14-Day mean concentrations were derived from the average of daily ADS data for the corresponding DELTA sampling periods.

The bars indicate the minimum and maximum values of the concentrations reported by the laboratories. Mean data for the whole period are compared below the graphs.

Table 1Inter-comparison of results from the six laboratories at the four reference sites. The results shown are the mean concentrations of NH3, HNO3, NH4

+ and NO3� from each

laboratory for each site, and also the overall median estimates derived from all laboratories for each site.

Inter-comparison sites Coordinating laboratories Median, all data (sample size)

NILU NERC MHSC vTI SHMU CEAM

Ammonia (mg NH3 m�3)

Auchencorth 1.73 1.72 1.78 1.56 1.83 1.42 1.73 (n = 46)

Braunschweig 4.14 3.77 4.01 3.69 3.61 2.80 3.73 (n = 39)

Montelibretti 2.77 2.68 3.02 2.60 3.00 1.94 2.70 (n = 44)

Paterna 6.22 5.27 7.00 4.57 5.55 4.39 5.21 (n = 45)

Nitric acid (mg HNO3 m�3)

Auchencorth 0.63 0.62 0.86 0.47 0.64 0.71 0.65 (n = 46)

Braunschweig 2.31 2.63 2.52 1.86 2.31 1.76 2.22 (n = 39)

Montelibretti 2.60 2.86 2.92 2.27 2.75 2.45 2.66 (n = 42)

Paterna 2.61 2.73 3.24 2.05 2.63 2.82 2.71 (n = 44)

Ammonium (mg NH4+ m�3)

Auchencorth 0.72 0.78 1.19 0.86 1.22 0.84 0.91 (n = 45)

Braunschweig 1.34 1.68 2.16 1.26 1.70 1.38 1.67 (n = 40)

Montelibretti 1.25 1.43 1.69 1.39 1.41 1.03 1.36 (n = 44)

Paterna 1.81 1.56 2.08 2.12 2.04 0.50 1.79 (n = 44)

Nitrate (mg NO3�m�3)

Auchencorth 1.28 1.34 1.41 1.05 1.36 1.45 1.36 (n = 44)

Braunschweig 2.77 3.39 3.36 1.88 3.22 3.83 3.36 (n = 38)

Montelibretti nd 2.53 2.44 2.44 2.45 2.80 2.48 (n = 36)

Paterna 4.34 4.34 4.60 4.32 4.57 4.73 4.52 (n = 44)

nd = no data (not analysed).

Y.S. Tang et al. / Agriculture, Ecosystems and Environment 133 (2009) 183–195 189

Fig. 5. Inter-comparison of the median gaseous HNO3 and NH3 and aerosol NO3� and NH4

+ concentrations of all laboratories with measurements from a co-located MARGA at

Auchencorth Moss, UK for measurement periods 5–8. (Operational problems occurred with the MARGA during the first 4 periods.) Time-integrated mean concentrations from

the MARGA were derived from the hourly average MARGA data for the corresponding DELTA sampling periods. The bars indicate the minimum and maximum values of the

concentrations reported by the different laboratories. Mean data for the whole period are compared below the graphs; the numbers in parentheses indicate the % data capture

by the MARGA for measurement periods 5–8, respectively.

Y.S. Tang et al. / Agriculture, Ecosystems and Environment 133 (2009) 183–195190

Inter-comparison of DELTA measurements with MARGA over thelast 4 periods showed that the closest agreements were found forPeriod 8, where the MARGA was also operational for the largestfraction of the time (Fig. 5). The DELTA NH3 and NH4

+ were within10 and 24% of the MARGA NH3 and NH4

+ (PM2.5). (The higher valueof MARGA NH4

+ PM2.5 than PM10 for period 6 may be due touncertainties related to the low data capture for this period.) TheDELTA NO3

� aerosol agreed within 19% of the MARGA PM2.5, beinglower than the PM10. The DELTA HNO3 was much larger than theMARGA HNO3, and was even 63% larger than the sum of theMARGA HNO3 + HONO, possible reasons for which are consideredin the discussion.

3.2. Atmospheric concentrations measured across NEU Level 1 sites

The majority of sites in the Level 1 network providedmeasurements from January 2007 onwards. Therefore data fromthe period January 2007 to December 2007 were selected toprovide the first complete year’s data for analysis. A large degree ofvariation in annual mean concentrations between the sites acrossEurope can already be seen, with most of the measured Nconcentration dominated by reduced nitrogen (NH3, NH4

+) ratherthan oxidized nitrogen species targeted (HNO3 and NO3

�) (Fig. 6).

The cleanest sites were those in Northern Finland, such asSodankyla and Lompolojankka, where total measured Nr concen-tration was <0.2 mg m�3 N. Conversely, the largest concentrationswere recorded at Piana del Sele in southern Italy (total12 mg m�3 N), Pavia in the Po Valley of northern Italy(8 mg m�3 N), Cabauw in the Netherlands (total 10 mg m�3 N)and Gebesee, an arable area in Germany (8 mg m�3 N). At thesehigh concentration sites, gaseous NH3 generally accounted formore than 50% of the total measured Nr concentration, while NH3

was the largest single Nr constituent (>25% of total measured N) at55% of the Level 1 sites.

Maps of the spatial patterns of Nr illustrate the degree of spatialvariability in the component concentrations across Europe (Fig. 7).In the case of HNO3 and aerosol NO3 and NH4

+, clear regionalpatterns can be seen, with broad elevation in central Europe. Bycontrast, gaseous NH3 concentrations are much more spatiallyvariable, even on a local scale.

Scatter plots of the concentration of gas and aerosol phases ofthe different components highlight the significant spatial correla-tions between the concentrations of the different pollutants(Fig. 8). For this comparison, estimates of SO2 and SO4

2�

concentrations provided by the DELTA systems were also included.The comparison of the gas phase concentrations shows that there

Fig. 6. Monitored annual mean concentrations of gaseous HNO3 and NH3 and particulate NO3� and NH4

+ at the Level 1 sites (January 2007–December 2007). Replicated DELTA

sampling at two sites, Bush (UK-Bu, UK-BuP) and Slovakian EMEP SK04 station (SK-04, SK-04P) demonstrated excellent agreement of the measurements (an annual average

difference of <4% in HNO3, <6% in NO3�, <2% in NH3 and NH4

+). Kaamanen = no data.

Fig. 7. Spatial patterns of monitored gaseous NH3, HNO3 and aerosol NH4+, NO3

� concentrations in the NitroEurope Level 1 network. Each coloured point represents the

annual mean of 2007 data at the site.

Y.S. Tang et al. / Agriculture, Ecosystems and Environment 133 (2009) 183–195 191

is estimated to be more NH3 than either SO2 or HNO3 at these sites(on an equivalent basis), while estimated SO2 concentration iscomparable to HNO3. For the aerosol components, a close couplingbetween the anions NO3

�, SO42� and the NH4

+ aerosol isdemonstrated by the high correlations. As with the gases, reduced

nitrogen (NH4+) is in molar excess over either SO4

2� or NO3�, with

nearly twice as much NO3� as SO4

2�. The high correlationsbetween the aerosol species also indicate the quality of themeasurements, since uncertainty in the measurements on amonthly basis would propagate through to scatter in these plots.

Fig. 8. Scatter plots of the monitored mean concentration of gas and aerosol phases of the different components. Each point represents the individual NitroEurope site annual

mean for 2007.

Y.S. Tang et al. / Agriculture, Ecosystems and Environment 133 (2009) 183–195192

Overall, the plot of the sum of aerosol NO3� + SO4

2� versus aerosolNH4

+ shows a slope which is not significantly different to the 1:1line, indicating that the acidic aerosol is on average fullyneutralized by ammonium.

4. Discussion

4.1. DELTA inter-comparison

The first 4-month DELTA inter-comparison at 4 test sitesdemonstrated generally close agreement between the laboratories.Overall, 65% and 87% of the site-mean estimates (for each Nrcomponent by each laboratory) were within 10% and 20%,respectively of the inter-laboratory median (Table 1, Section3.1). The performance can also be summarized as the averageinter-laboratory mean differences compared with the medianestimates, which were 10%, 10%, 16% and 5% for NH3, HNO3, NH4

+

and NO3�, respectively (Table 1). If the CEAM data for NHx are

excluded (related to the analytical problem), the mean differencesare 7% for NH3 and 14% for NH4

+.The laboratory performance shown in Table 1 can be

summarized as the mean difference from the inter-laboratorymedians for all sites and compounds, with values of: 14%, 5%, 15%,15%, 6% and 18% for NILU, NERC-CEH, MHSC, VTI, SHMU and CEAM,respectively. It should be noted that with the exception of NERC-CEH, this inter-comparison represented the first tests in using theDELTA system by the different laboratories. As such, thecomparison is considered very encouraging, particularly for nitrateaerosol. The random scatter can be attributed to precision in thelaboratory operations (e.g. blank cleanliness, analytical proce-dures). In the case of CEAM, the lower level of agreement wasspecifically due to a bias for NHx (26% mean difference), which wasattributed to the need to refine the NHx sampling and analysis atthe start of the project. By contrast, the CEAM performance forHNO3 and NO3

� was better (10% mean difference).Given the overall close agreement for mean concentrations, and

the need to better understand the differences, no correction ismade at this stage for any possible biases between laboratories.

Further annual inter-comparisons are being conducted to assessthe long-term comparability between the laboratories, which willbe reported elsewhere, and these show improved inter-compar-ability of the measurements between laboratories.

4.2. Comparison of DELTA with ADS at Monteibretti

At the Montelibretti site, independent high resolution (daily)measurements are provided by the ADS. The agreement for NH3

and NH4+ between the ADS and DELTA measurements of 9 and

18%, respectively, is encouraging, and consistent with the inter-laboratory analytical variation of the multiple DELTA systems. ForNO3

�, the DELTA results were closer to the PMx value (sum of NO3�

on cyclone + on PM2.5 filter) than to the PM2.5 value (NO3� on

PM2.5 filter only). In the absence of other analytical differences,this would suggest that both fine and coarse mode NO3

� aresampled by the DELTA system. The particle cut-off size for theDELTA inlet (with a 90 mm diameter funnel at inlet to act as rainshield) was estimated to be 4–5 mm (E. Nemitz, unpublisheddata). This compares with an estimated particle cut-off for theADS of about 4–8 mm (pers. comm. C. Perrino), depending on thewind velocity. The difference in measured NO3

� may then beattributed to uncertainty in the particle cut-off size of the inlet forboth systems. In addition, the molar ion balance ratio of[NO3

� + 2SO42�]/NH4

+ was 1.4, which suggests that significantcoarse nitrate (e.g. calcium nitrate) was present at Montelibretti,part of which was sampled by the DELTA systems.

Conversely, the cut-off size should have no effect on NH4+

particles, which are mainly in the fine mode (<1 mm), as reflectedin the closer agreement between the 2 systems.

For HNO3, the comparison at Montelibretti appears to indicatethat the DELTA system may be overestimating HNO3 by up to 100%,which may be due to an artefact in HNO3 measurements on thecarbonate-coated denuders, caused by the additional retention ofone or more N-containing interfering species, such as HONO, NOx,PAN and NH4NO3 (Bai et al., 2003). In the ADS, a NaCl coating isused which is highly selective for HNO3 (Allegrini et al., 1987). NO2

and PAN that might cause a small interference are corrected for

Y.S. Tang et al. / Agriculture, Ecosystems and Environment 133 (2009) 183–195 193

from the distribution of nitrate between the first and seconddenuder (absolute differential technique), assuming that they arecollected with the same efficiencies on the 2NaCl denuders (e.g.Allegrini et al., 1987; Perrino et al., 1990) and that HNO3 iscollected with 100% efficiency in the first denuder.

It should be noted that the rationale of using a carbonatecoating in the NEU DELTA system is that it is an effective sorbentfor all acid gases (e.g. Ferm, 1986), whereas NaCl is effective onlyfor HNO3. Thus the carbonate coating allows simultaneoussampling of HNO3, SO2 and HCl in rural conditions, while avoidingthe use of excessively long sampling trains (and associated costincreases). Although nitrous acid (HONO) is also removed by thecarbonate coating, this should not normally cause a significantinterference, as it would be detected as nitrite in the sampleextracts. However, the presence of ozone (O3) can oxidize HONO toHNO3 (Sickles and Hodson, 1989; Bytnerowicz et al., 2005). Giventhe long sampling time of the DELTA, such an interference fromHONO may have caused the apparent overestimation of HNO3

concentrations at Montelibretti. This would be consistent with ourfinding that NO2

� in the DELTA denuders (i.e. the signal of collectedHONO), where analysed, was mostly around detection limit(LOD = 0.05 mg HONO m�3).

Air concentrations of HONO are estimated by long-termmonitoring at Montelibretti with the ADS to be of the same orderof magnitude as HNO3 of 1–3 mg m�3 (C. Perrino, unpublisheddata), while NOx and PAN at Montelibretti are large, typical ofpolluted urban air (Perrino et al., 2001). Hence, HONO could causepositive bias in HNO3 determination on the DELTA system atMontelibretti. By contrast, in conditions typical of rural sites, suchas the majority of the NEU Level 1 sites, HONO interference (as wellas possible NO2 and PAN interference) should be negligible, asestimated [NO2] � 5 ppb, [PAN] � 3 ppb; and [HONO] � 0.05–0.3 ppb (based on an average ratio of HONO/NO2 of 1–6%, e.g.Genfa et al., 2003; Acker et al., 2004). Although a much smallerHONO interference of the DELTA HNO3 signal is therefore expectedfor the rural sites of the NEU Level 1 network, further independenttests are warranted to quantify this effect.

4.3. Comparison of DELTA with MARGA at Auchencorth

At Auchencorth, broad agreement was found for NH3, NH4+ and

NO3� between the DELTA and MARGA measurements (Fig. 5,

Section 3.1), these being within 10%, 24% and 19%, respectively. Forthe latter of these the agreement was closest to PM2.5 rather thanPM10, suggesting a significant contribution of NO3

� in particles<4–5 mm. This is supported by a molar ion balance (ratio of NH4

+-to-NO3 + 2SO4

2�) of 1.0. For HNO3, the DELTA agreed closest withthe sum of HONO and HNO3 from MARGA. Superficially, this mightbe interpreted as further evidence suggesting a positive inter-ference of HONO to the DELTA HNO3 signal at this rural site.However, for the MARGA, HONO concentrations (range = 0.001–2.2 mg HONO m�3) measured were consistently higher than thecorresponding HNO3 concentrations (0.001–0.43 mg HNO3 m�3),which was around the limit of detection of the instrument most ofthe time. Such a ratio of HONO-N/HNO3-N of up to 7 is notexpected. A long polyethylene inlet (2 m, not heated) and cycloneare used in the MARGA system, and this may introduce samplingbiases attributed to: (a) HNO3 loss to inlet surfaces, which lead toan underestimation of HNO3 concentrations (De Santis et al., 1988;Ianniello et al., 2007), (b) additional HONO formed on walls of inlet,produced by heterogeneous reactions of NO2 on surfaces(Kleffmann et al., 2006), and (c) reaction between HNO3 and NaClwithin the inlet to form NaNO3 and HCl (Li-Jones et al., 2001),which will also lead to an underestimation of HNO3.

Part of the uncertainty in the comparison between the DELTAand the MARGA may be attributable to the rather low data capture

by the latter instrument for some parts of the study. However, theencouraging agreement for NH3 and NH4

+ tends to indicate thatsufficient MARGA data were obtained to allow broad comparison.Further tests of the MARGA system should quantify the effect of theinlet line.

As regards the possibility of significant NO2 and PAN inter-ference in HNO3 determination at the rural NEU sites, this is notsupported by the measurements. A possible NO2 and PAN signalwould be seen in both the first and the second carbonate-coateddenuders. This would be manifested as an apparently lowercapture efficiency of HNO3 in the first denuder. In fact, the averagedenuder capture efficiency for HNO3 (based on the inter-comparison at Auchencorth) was 88% in the first denuder, whichwas comparable to that for SO2, indicating little evidence ofsignificant NO2 or PAN capture. At present therefore, the evidencepoints to a possible interference whereby HONO captured as NO2

�

in the carbonate-coated denuder is oxidized to NO3� in the

denuder before chemical analysis. This appears to provide asignificant effect that must be considered for urban sites, likeMontelibretti, while further tests are required to quantify thecontribution to the rural HNO3 determinations, which at presentmust be considered as upper estimates.

4.4. Comparison of DELTA with ADS and cylindrical denuders at

Braunschweig

In addition to the inter-comparison data reported here, acomprehensive inter-comparison exercise with various denudersand passive samplers was performed at Braunschweig fromNovember 2006 until December 2008. The study included sixDELTA samplers operated in parallel, KAPS annular denuder filtersamplers (ADS, vTI), cylindrical denuders from FUB (Rapperswil,Switzerland) and LUBW (Karlsruhe, Germany), as well as Ferm andRadiello passive samplers. Apart from KAPS which was used fordaily sampling, all other devices were exposed for two weeks.

Preliminary results can be summarized as follows (Dammgenet al., in preparation): for atmospheric NH3 concentrations, theresults agree almost perfectly between all types of samplersinvolved. In this case, sampling is, in practice, unambiguous. ForHNO3, K2CO3-coated denuders are thought likely to collect afraction of NO2 present, while HONO may be oxidized to someextent, as described above. Sampling for particulate NH4

+ yieldedthe same mean concentrations between methods. For individualsampling periods, no linear correlations could yet be established.

4.5. Basis of the denuder calculation

One of the points of discussion in applying the DELTA approachhas been how to treat the results of the two denuders used inseries. When the DELTA method was established in the UKammonia network (Sutton et al., 2001b), it was concluded that anyNHx appearing in the second denuder was primarily due tocarryover of NH3 due to imperfect coating of the first denuder,providing an important QC check on the denuder coating for eachmonthly sample. This conclusion is supported by the Braunsch-weig inter-comparison (Dammgen et al., in preparation).

An alternative explanation of NHx appearing in the seconddenuder is the capture of NH4

+ containing particles. Since theseparticles are generally <1 mm diameter, this effect appears to besmall compared with the occasional incomplete capture of NH3.Such a conclusion might also be expected to hold for the correctionof SO2 and SO4

2�. By contrast, there remains a need for furthertests/analysis to clarify the most appropriate second denudercorrection for HNO3 and NO3

�, since coarse mode NO3� would be

more likely to be captured on denuder surfaces (as well as possibletrace capture of NO2). Nevertheless, if this was significant,

Y.S. Tang et al. / Agriculture, Ecosystems and Environment 133 (2009) 183–195194

differences in capture efficiency would be expected for thedifferent components. In the present inter-comparison, the resultsfor NERC-CEH at the 4 locations provided mean capture efficiencyin the first denuder (as % of the total in both denuders) of 90%, 92%,91% and 90% for HNO3, SO2, HCl and NH3, respectively. Thedifferences are not significant (P > 0.1, n = 30), highlighting asimilar performance for each of the components.

4.6. First year of network measurement results

From the first year of measurements in the Level 1 network,substantial variations in concentration of the different componentscan already be seen between sites (Figs. 5 and 6). The type andconcentrations of atmospheric N species vary, as influenced byemission source types and strengths, land use, seasonality effectsand meteorological conditions (Sutton et al., 2004). The largestatmospheric N concentrations were measured at sites close tointensively managed agricultural areas, dominated by ammonia(e.g. Gebesee, Piana del Sele and Cabauw, sites 3, 19, and 43), whilethe smallest concentrations were measured over remote forestsites (e.g. Sodankyla and Lompolojankka, Finland, sites 31 and 33).

These differences reflect the origin of these components, withHNO3, NO3

� and NH4+ resulting from secondary processing of

atmospheric Nr emissions, while NH3 concentrations reflectdispersion away from mainly ground level sources. It can thusbe considered that the NH3 concentrations represent localemission conditions, combined with regional differences. Thus,while it may be possible to estimate concentrations of HNO3, NO3

�

and NH4+ from regional models, this is not possible for NH3, for

which either site-based measurements or high resolution modelsare in general necessary.

Aerosol N accounted for 14–70% of the total atmospheric Nconcentrations measured, while gaseous N accounted for 30–86%.Of the total N concentrations, 63–96% were reduced N (NH4

+ andNH3), compared with only 4–37% as oxidized N (HNO3 and NO3

�).Recognizing the uncertainties identified in the inter-comparison,these latter figures may also include a contribution from HONO,providing an upper estimate of the sum of HNO3 and NO3

�. It isthus clear that NH3 and its reaction product NH4

+ dominate the Nrspecies measured in this study, with NH3 being the most importantindividual term for the calculation of total N dry deposition. Itshould be noted that NO2 concentrations are not estimated by theDELTA method, and this will also provide a relevant term for N drydeposition. However, based on rather small deposition velocitiesfor NO2 (Smith et al., 2000), the NO2 contribution will (especiallyfor rural semi-natural and forest ecosystems) be smaller than forNH3.

To estimate annual dry deposition fluxes of nitrogen atindividual sites, the N concentration data are being combinedwith local micrometeorological data and ecosystem informationusing three different canopy budget models. While this will bedescribed elsewhere, it is already clear from the presentmeasurements and typical deposition velocities that the largestcontribution to dry deposition will result from atmospheric NH3.This is encouraging from a measurement perpspective, since itmeans that the uncertainties associated with DELTA speciation ofHNO3 and HONO will have a modest effect on overall uncertaintiesin dry N deposition. In that context, the largest challenge will be togeneralize net annual bi-directional exchange of NH3 in relation tocompensation points, meteorological conditions and land manage-ment decisions.

5. Conclusions

A comprehensive European dataset on monthly gaseous HNO3,NH3, and aerosol NH4

+, NO3� concentrations is being delivered by

the NEU Level 1 ‘Inferential Network’, which will allow seasonaltemporal trends and spatial patterns, as well as nitrogen drydeposition fluxes from the different Nr species being monitored tobe separately quantified, important for quantifying ecosystemresponses to nitrogen. At the same time, measurements areprovided of SO2, HCl, and aerosol SO4

2�, Cl� and base cations whichwill be reported elsewhere.

The use of the harmonised DELTA methodology, coupled to adefined QA/QC programme ensures comparability of data made byseven coordinating laboratories who share responsibility for theseLevel 1 measurements across the network. Comparison of theDELTA methodology with independent ADS measurements atMontelibretti suggests the existence of interference of otheroxidized Nr components (most likely HONO) with HNO3 con-centrations. Although a much smaller interference is expected forthe rural sites of the NEU Level 1 network, further independenttests are warranted to quantify this effect.

Data from the first years of the Level 1 network showsubstantial spatial variability across European sites, illustratingthe major local (NH3) and regional (HNO3, NH4

+, and NO3�)

differences in Nr concentrations. These estimates are now beingused in three different inferential models to estimated N drydeposition fluxes. Based on the high NH3 concentrations reportedhere and typically large deposition velocities, NH3, which is mainlyof agricultural origin, is estimated to be the most important speciesin defining N dry deposition. Combined with estimates of wetdeposition to these sites, this analysis will in due course allowinvestigation of interactions between N supply and greenhouse gasexchange estimated for the same Level 1 sites.

Acknowledgements

This work was carried out with funding from the EuropeanUnion for the NitroEurope IP project, the UK Department forEnvironment, Food and Rural Affairs (DEFRA) and DevolvedAdministrations for the UK National Ammonia and Nitric acidMonitoring Networks, and supporting funds from NERC. Thesupport and assistance provided by the network of NitroEuropeand CarboEurope site operators and contributions from thecoordinating laboratories are gratefully acknowledged. FundacionCEAM is partly supported by Generalitat Valenciana, Bancaja, andthe Programm CONSOLIDER-INGENIO 2010 (GRACCIE). NiNE andCOST729 also provided travel grants for several coauthors.

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